CNVR-MVS | | | 99.40 1 | 99.26 1 | 99.84 6 | 99.98 2 | 99.51 6 | 99.98 9 | 98.69 57 | 98.20 3 | 99.93 1 | 99.98 2 | 96.82 23 | 100.00 1 | 99.75 28 | 100.00 1 | 99.99 24 |
|
patch_mono-2 | | | 98.24 64 | 99.12 5 | 95.59 213 | 99.67 92 | 86.91 329 | 99.95 43 | 98.89 43 | 97.60 12 | 99.90 2 | 99.76 76 | 96.54 28 | 99.98 46 | 99.94 12 | 99.82 91 | 99.88 96 |
|
NCCC | | | 99.37 2 | 99.25 2 | 99.71 13 | 99.96 8 | 99.15 20 | 99.97 18 | 98.62 69 | 98.02 6 | 99.90 2 | 99.95 3 | 97.33 17 | 100.00 1 | 99.54 39 | 100.00 1 | 100.00 1 |
|
TSAR-MVS + MP. | | | 98.93 16 | 98.77 18 | 99.41 42 | 99.74 82 | 98.67 48 | 99.77 132 | 98.38 147 | 96.73 37 | 99.88 4 | 99.74 87 | 94.89 65 | 99.59 145 | 99.80 24 | 99.98 35 | 99.97 67 |
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition |
test0726 | | | | | | 99.93 27 | 99.29 14 | 99.96 25 | 98.42 132 | 97.28 19 | 99.86 5 | 99.94 4 | 97.22 19 | | | | |
|
xiu_mvs_v2_base | | | 98.23 65 | 97.97 67 | 99.02 80 | 98.69 148 | 98.66 50 | 99.52 186 | 98.08 193 | 97.05 27 | 99.86 5 | 99.86 31 | 90.65 168 | 99.71 134 | 99.39 47 | 98.63 136 | 98.69 211 |
|
PS-MVSNAJ | | | 98.44 48 | 98.20 52 | 99.16 62 | 98.80 144 | 98.92 27 | 99.54 184 | 98.17 182 | 97.34 17 | 99.85 7 | 99.85 35 | 91.20 157 | 99.89 84 | 99.41 46 | 99.67 101 | 98.69 211 |
|
旧先验2 | | | | | | | | 99.46 197 | | 94.21 123 | 99.85 7 | | | 99.95 65 | 96.96 145 | | |
|
IU-MVS | | | | | | 99.93 27 | 99.31 9 | | 98.41 136 | 97.71 8 | 99.84 9 | | | | 100.00 1 | 100.00 1 | 100.00 1 |
|
ETH3 D test6400 | | | 98.81 23 | 98.54 28 | 99.59 21 | 99.93 27 | 98.93 26 | 99.93 67 | 98.46 107 | 94.56 105 | 99.84 9 | 99.92 13 | 94.32 84 | 99.86 95 | 99.96 9 | 99.98 35 | 100.00 1 |
|
DVP-MVS |  | | 99.30 4 | 99.16 3 | 99.73 11 | 99.93 27 | 99.29 14 | 99.95 43 | 98.32 160 | 97.28 19 | 99.83 11 | 99.91 15 | 97.22 19 | 100.00 1 | 99.99 5 | 100.00 1 | 99.89 94 |
Zhenlong Yuan, Jinguo Luo, Fei Shen, Zhaoxin Li, Cong Liu, Tianlu Mao, Zhaoqi Wang: DVP-MVS: Synergize Depth-Edge and Visibility Prior for Multi-View Stereo. AAAI2025 |
test_0728_THIRD | | | | | | | | | | 96.48 43 | 99.83 11 | 99.91 15 | 97.87 6 | 100.00 1 | 99.92 13 | 100.00 1 | 100.00 1 |
|
xxxxxxxxxxxxxcwj | | | 98.98 15 | 98.79 17 | 99.54 26 | 99.82 70 | 98.79 37 | 99.96 25 | 97.52 244 | 97.66 10 | 99.81 13 | 99.89 21 | 94.70 68 | 99.86 95 | 99.84 19 | 99.93 67 | 99.96 74 |
|
SF-MVS | | | 98.67 31 | 98.40 37 | 99.50 32 | 99.77 78 | 98.67 48 | 99.90 80 | 98.21 177 | 93.53 153 | 99.81 13 | 99.89 21 | 94.70 68 | 99.86 95 | 99.84 19 | 99.93 67 | 99.96 74 |
|
ETH3D-3000-0.1 | | | 98.68 30 | 98.42 33 | 99.47 37 | 99.83 68 | 98.57 55 | 99.90 80 | 98.37 150 | 93.81 144 | 99.81 13 | 99.90 19 | 94.34 80 | 99.86 95 | 99.84 19 | 99.98 35 | 99.97 67 |
|
SD-MVS | | | 98.92 17 | 98.70 19 | 99.56 24 | 99.70 90 | 98.73 45 | 99.94 61 | 98.34 157 | 96.38 48 | 99.81 13 | 99.76 76 | 94.59 70 | 99.98 46 | 99.84 19 | 99.96 52 | 99.97 67 |
Zhenlong Yuan, Jiakai Cao, Zhaoxin Li, Hao Jiang and Zhaoqi Wang: SD-MVS: Segmentation-driven Deformation Multi-View Stereo with Spherical Refinement and EM optimization. AAAI2024 |
DVP-MVS++ | | | 99.26 6 | 99.09 9 | 99.77 8 | 99.91 44 | 99.31 9 | 99.95 43 | 98.43 120 | 96.48 43 | 99.80 17 | 99.93 11 | 97.44 14 | 100.00 1 | 99.92 13 | 99.98 35 | 100.00 1 |
|
PC_three_1452 | | | | | | | | | | 96.96 30 | 99.80 17 | 99.79 64 | 97.49 10 | 100.00 1 | 99.99 5 | 99.98 35 | 100.00 1 |
|
SED-MVS | | | 99.28 5 | 99.11 7 | 99.77 8 | 99.93 27 | 99.30 11 | 99.96 25 | 98.43 120 | 97.27 21 | 99.80 17 | 99.94 4 | 96.71 24 | 100.00 1 | 100.00 1 | 100.00 1 | 100.00 1 |
|
test_241102_TWO | | | | | | | | | 98.43 120 | 97.27 21 | 99.80 17 | 99.94 4 | 97.18 21 | 100.00 1 | 100.00 1 | 100.00 1 | 100.00 1 |
|
test_241102_ONE | | | | | | 99.93 27 | 99.30 11 | | 98.43 120 | 97.26 23 | 99.80 17 | 99.88 24 | 96.71 24 | 100.00 1 | | | |
|
MSLP-MVS++ | | | 99.13 8 | 99.01 11 | 99.49 34 | 99.94 14 | 98.46 63 | 99.98 9 | 98.86 47 | 97.10 26 | 99.80 17 | 99.94 4 | 95.92 37 | 100.00 1 | 99.51 40 | 100.00 1 | 100.00 1 |
|
SteuartSystems-ACMMP | | | 99.02 12 | 98.97 13 | 99.18 57 | 98.72 147 | 97.71 86 | 99.98 9 | 98.44 112 | 96.85 31 | 99.80 17 | 99.91 15 | 97.57 8 | 99.85 99 | 99.44 44 | 99.99 22 | 99.99 24 |
Skip Steuart: Steuart Systems R&D Blog. |
testdata | | | | | 98.42 123 | 99.47 107 | 95.33 176 | | 98.56 79 | 93.78 146 | 99.79 24 | 99.85 35 | 93.64 105 | 99.94 73 | 94.97 172 | 99.94 61 | 100.00 1 |
|
9.14 | | | | 98.38 40 | | 99.87 57 | | 99.91 75 | 98.33 158 | 93.22 162 | 99.78 25 | 99.89 21 | 94.57 71 | 99.85 99 | 99.84 19 | 99.97 48 | |
|
SMA-MVS |  | | 98.76 27 | 98.48 31 | 99.62 18 | 99.87 57 | 98.87 31 | 99.86 105 | 98.38 147 | 93.19 163 | 99.77 26 | 99.94 4 | 95.54 44 | 100.00 1 | 99.74 30 | 99.99 22 | 100.00 1 |
Yufeng Yin; Xiaoyan Liu; Zichao Zhang: SMA-MVS: Segmentation-Guided Multi-Scale Anchor Deformation Patch Multi-View Stereo. IEEE Transactions on Circuits and Systems for Video Technology |
CDPH-MVS | | | 98.65 32 | 98.36 44 | 99.49 34 | 99.94 14 | 98.73 45 | 99.87 93 | 98.33 158 | 93.97 136 | 99.76 27 | 99.87 28 | 94.99 61 | 99.75 126 | 98.55 91 | 100.00 1 | 99.98 55 |
|
test_one_0601 | | | | | | 99.94 14 | 99.30 11 | | 98.41 136 | 96.63 40 | 99.75 28 | 99.93 11 | 97.49 10 | | | | |
|
APD-MVS |  | | 98.62 33 | 98.35 45 | 99.41 42 | 99.90 47 | 98.51 60 | 99.87 93 | 98.36 152 | 94.08 128 | 99.74 29 | 99.73 89 | 94.08 92 | 99.74 130 | 99.42 45 | 99.99 22 | 99.99 24 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
ETH3D cwj APD-0.16 | | | 98.40 52 | 98.07 62 | 99.40 44 | 99.59 96 | 98.41 64 | 99.86 105 | 98.24 173 | 92.18 203 | 99.73 30 | 99.87 28 | 93.47 107 | 99.85 99 | 99.74 30 | 99.95 55 | 99.93 85 |
|
test_prior3 | | | 98.99 14 | 98.84 16 | 99.43 38 | 99.94 14 | 98.49 61 | 99.95 43 | 98.65 62 | 95.78 64 | 99.73 30 | 99.76 76 | 96.00 33 | 99.80 111 | 99.78 26 | 100.00 1 | 99.99 24 |
|
test_prior2 | | | | | | | | 99.95 43 | | 95.78 64 | 99.73 30 | 99.76 76 | 96.00 33 | | 99.78 26 | 100.00 1 | |
|
testtj | | | 98.89 19 | 98.69 20 | 99.52 29 | 99.94 14 | 98.56 57 | 99.90 80 | 98.55 85 | 95.14 84 | 99.72 33 | 99.84 48 | 95.46 47 | 100.00 1 | 99.65 38 | 99.99 22 | 99.99 24 |
|
TEST9 | | | | | | 99.92 36 | 98.92 27 | 99.96 25 | 98.43 120 | 93.90 141 | 99.71 34 | 99.86 31 | 95.88 38 | 99.85 99 | | | |
|
train_agg | | | 98.88 20 | 98.65 22 | 99.59 21 | 99.92 36 | 98.92 27 | 99.96 25 | 98.43 120 | 94.35 115 | 99.71 34 | 99.86 31 | 95.94 35 | 99.85 99 | 99.69 37 | 99.98 35 | 99.99 24 |
|
test_8 | | | | | | 99.92 36 | 98.88 30 | 99.96 25 | 98.43 120 | 94.35 115 | 99.69 36 | 99.85 35 | 95.94 35 | 99.85 99 | | | |
|
CS-MVS | | | 97.79 83 | 97.91 73 | 97.43 162 | 99.10 120 | 94.42 198 | 99.99 3 | 97.10 282 | 95.07 85 | 99.68 37 | 99.75 82 | 92.95 123 | 98.34 213 | 98.38 96 | 99.14 127 | 99.54 151 |
|
test12 | | | | | 99.43 38 | 99.74 82 | 98.56 57 | | 98.40 140 | | 99.65 38 | | 94.76 66 | 99.75 126 | | 99.98 35 | 99.99 24 |
|
DPE-MVS |  | | 99.26 6 | 99.10 8 | 99.74 10 | 99.89 50 | 99.24 18 | 99.87 93 | 98.44 112 | 97.48 16 | 99.64 39 | 99.94 4 | 96.68 26 | 99.99 40 | 99.99 5 | 100.00 1 | 99.99 24 |
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025 |
agg_prior1 | | | 98.88 20 | 98.66 21 | 99.54 26 | 99.93 27 | 98.77 40 | 99.96 25 | 98.43 120 | 94.63 103 | 99.63 40 | 99.85 35 | 95.79 41 | 99.85 99 | 99.72 34 | 99.99 22 | 99.99 24 |
|
agg_prior | | | | | | 99.93 27 | 98.77 40 | | 98.43 120 | | 99.63 40 | | | 99.85 99 | | | |
|
DROMVSNet | | | 97.38 100 | 97.24 93 | 97.80 144 | 97.41 215 | 95.64 169 | 99.99 3 | 97.06 287 | 94.59 104 | 99.63 40 | 99.32 130 | 89.20 188 | 98.14 227 | 98.76 79 | 99.23 124 | 99.62 133 |
|
xiu_mvs_v1_base_debu | | | 97.43 93 | 97.06 98 | 98.55 110 | 97.74 199 | 98.14 70 | 99.31 215 | 97.86 213 | 96.43 45 | 99.62 43 | 99.69 98 | 85.56 221 | 99.68 138 | 99.05 56 | 98.31 143 | 97.83 220 |
|
CS-MVS-test | | | 97.88 76 | 97.94 71 | 97.70 152 | 99.28 115 | 95.20 183 | 99.98 9 | 97.15 277 | 95.53 75 | 99.62 43 | 99.79 64 | 92.08 146 | 98.38 209 | 98.75 80 | 99.28 122 | 99.52 155 |
|
xiu_mvs_v1_base | | | 97.43 93 | 97.06 98 | 98.55 110 | 97.74 199 | 98.14 70 | 99.31 215 | 97.86 213 | 96.43 45 | 99.62 43 | 99.69 98 | 85.56 221 | 99.68 138 | 99.05 56 | 98.31 143 | 97.83 220 |
|
xiu_mvs_v1_base_debi | | | 97.43 93 | 97.06 98 | 98.55 110 | 97.74 199 | 98.14 70 | 99.31 215 | 97.86 213 | 96.43 45 | 99.62 43 | 99.69 98 | 85.56 221 | 99.68 138 | 99.05 56 | 98.31 143 | 97.83 220 |
|
原ACMM1 | | | | | 98.96 85 | 99.73 86 | 96.99 120 | | 98.51 99 | 94.06 131 | 99.62 43 | 99.85 35 | 94.97 62 | 99.96 58 | 95.11 168 | 99.95 55 | 99.92 91 |
|
PHI-MVS | | | 98.41 50 | 98.21 51 | 99.03 78 | 99.86 59 | 97.10 116 | 99.98 9 | 98.80 52 | 90.78 241 | 99.62 43 | 99.78 70 | 95.30 50 | 100.00 1 | 99.80 24 | 99.93 67 | 99.99 24 |
|
DPM-MVS | | | 98.83 22 | 98.46 32 | 99.97 1 | 99.33 113 | 99.92 1 | 99.96 25 | 98.44 112 | 97.96 7 | 99.55 49 | 99.94 4 | 97.18 21 | 100.00 1 | 93.81 203 | 99.94 61 | 99.98 55 |
|
新几何1 | | | | | 99.42 41 | 99.75 81 | 98.27 68 | | 98.63 68 | 92.69 181 | 99.55 49 | 99.82 55 | 94.40 74 | 100.00 1 | 91.21 237 | 99.94 61 | 99.99 24 |
|
ACMMP_NAP | | | 98.49 44 | 98.14 56 | 99.54 26 | 99.66 93 | 98.62 54 | 99.85 108 | 98.37 150 | 94.68 100 | 99.53 51 | 99.83 51 | 92.87 125 | 100.00 1 | 98.66 87 | 99.84 84 | 99.99 24 |
|
1121 | | | 98.03 71 | 97.57 83 | 99.40 44 | 99.74 82 | 98.21 69 | 98.31 301 | 98.62 69 | 92.78 176 | 99.53 51 | 99.83 51 | 95.08 54 | 100.00 1 | 94.36 190 | 99.92 71 | 99.99 24 |
|
PMMVS | | | 96.76 120 | 96.76 109 | 96.76 183 | 98.28 168 | 92.10 252 | 99.91 75 | 97.98 200 | 94.12 126 | 99.53 51 | 99.39 126 | 86.93 209 | 98.73 181 | 96.95 146 | 97.73 157 | 99.45 164 |
|
FOURS1 | | | | | | 99.92 36 | 97.66 90 | 99.95 43 | 98.36 152 | 95.58 73 | 99.52 54 | | | | | | |
|
MSP-MVS | | | 99.09 9 | 99.12 5 | 98.98 83 | 99.93 27 | 97.24 109 | 99.95 43 | 98.42 132 | 97.50 15 | 99.52 54 | 99.88 24 | 97.43 16 | 99.71 134 | 99.50 41 | 99.98 35 | 100.00 1 |
Zhenlong Yuan, Cong Liu, Fei Shen, Zhaoxin Li, Jingguo luo, Tianlu Mao and Zhaoqi Wang: MSP-MVS: Multi-granularity Segmentation Prior Guided Multi-View Stereo. AAAI2025 |
test_part2 | | | | | | 99.89 50 | 99.25 17 | | | | 99.49 56 | | | | | | |
|
APDe-MVS | | | 99.06 11 | 98.91 14 | 99.51 31 | 99.94 14 | 98.76 44 | 99.91 75 | 98.39 143 | 97.20 25 | 99.46 57 | 99.85 35 | 95.53 46 | 99.79 114 | 99.86 18 | 100.00 1 | 99.99 24 |
|
region2R | | | 98.54 40 | 98.37 42 | 99.05 76 | 99.96 8 | 97.18 112 | 99.96 25 | 98.55 85 | 94.87 94 | 99.45 58 | 99.85 35 | 94.07 93 | 100.00 1 | 98.67 84 | 100.00 1 | 99.98 55 |
|
HPM-MVS++ |  | | 99.07 10 | 98.88 15 | 99.63 15 | 99.90 47 | 99.02 23 | 99.95 43 | 98.56 79 | 97.56 14 | 99.44 59 | 99.85 35 | 95.38 49 | 100.00 1 | 99.31 49 | 99.99 22 | 99.87 98 |
|
MVSFormer | | | 96.94 112 | 96.60 113 | 97.95 140 | 97.28 225 | 97.70 88 | 99.55 182 | 97.27 267 | 91.17 230 | 99.43 60 | 99.54 114 | 90.92 164 | 96.89 295 | 94.67 185 | 99.62 104 | 99.25 185 |
|
lupinMVS | | | 97.85 78 | 97.60 81 | 98.62 103 | 97.28 225 | 97.70 88 | 99.99 3 | 97.55 238 | 95.50 77 | 99.43 60 | 99.67 102 | 90.92 164 | 98.71 183 | 98.40 95 | 99.62 104 | 99.45 164 |
|
Regformer-1 | | | 98.79 25 | 98.60 25 | 99.36 48 | 99.85 60 | 98.34 66 | 99.87 93 | 98.52 92 | 96.05 57 | 99.41 62 | 99.79 64 | 94.93 63 | 99.76 123 | 99.07 55 | 99.90 76 | 99.99 24 |
|
Regformer-2 | | | 98.78 26 | 98.59 26 | 99.36 48 | 99.85 60 | 98.32 67 | 99.87 93 | 98.52 92 | 96.04 58 | 99.41 62 | 99.79 64 | 94.92 64 | 99.76 123 | 99.05 56 | 99.90 76 | 99.98 55 |
|
XVS | | | 98.70 29 | 98.55 27 | 99.15 64 | 99.94 14 | 97.50 99 | 99.94 61 | 98.42 132 | 96.22 53 | 99.41 62 | 99.78 70 | 94.34 80 | 99.96 58 | 98.92 66 | 99.95 55 | 99.99 24 |
|
X-MVStestdata | | | 93.83 197 | 92.06 228 | 99.15 64 | 99.94 14 | 97.50 99 | 99.94 61 | 98.42 132 | 96.22 53 | 99.41 62 | 41.37 380 | 94.34 80 | 99.96 58 | 98.92 66 | 99.95 55 | 99.99 24 |
|
SR-MVS-dyc-post | | | 98.31 57 | 98.17 54 | 98.71 96 | 99.79 75 | 96.37 141 | 99.76 137 | 98.31 162 | 94.43 110 | 99.40 66 | 99.75 82 | 93.28 114 | 99.78 116 | 98.90 69 | 99.92 71 | 99.97 67 |
|
RE-MVS-def | | | | 98.13 57 | | 99.79 75 | 96.37 141 | 99.76 137 | 98.31 162 | 94.43 110 | 99.40 66 | 99.75 82 | 92.95 123 | | 98.90 69 | 99.92 71 | 99.97 67 |
|
APD-MVS_3200maxsize | | | 98.25 63 | 98.08 61 | 98.78 92 | 99.81 73 | 96.60 132 | 99.82 119 | 98.30 165 | 93.95 138 | 99.37 68 | 99.77 72 | 92.84 126 | 99.76 123 | 98.95 63 | 99.92 71 | 99.97 67 |
|
PGM-MVS | | | 98.34 55 | 98.13 57 | 98.99 82 | 99.92 36 | 97.00 119 | 99.75 140 | 99.50 17 | 93.90 141 | 99.37 68 | 99.76 76 | 93.24 117 | 100.00 1 | 97.75 126 | 99.96 52 | 99.98 55 |
|
SR-MVS | | | 98.46 46 | 98.30 48 | 98.93 87 | 99.88 54 | 97.04 117 | 99.84 112 | 98.35 155 | 94.92 91 | 99.32 70 | 99.80 60 | 93.35 109 | 99.78 116 | 99.30 50 | 99.95 55 | 99.96 74 |
|
ZD-MVS | | | | | | 99.92 36 | 98.57 55 | | 98.52 92 | 92.34 198 | 99.31 71 | 99.83 51 | 95.06 56 | 99.80 111 | 99.70 36 | 99.97 48 | |
|
HFP-MVS | | | 98.56 38 | 98.37 42 | 99.14 66 | 99.96 8 | 97.43 104 | 99.95 43 | 98.61 71 | 94.77 96 | 99.31 71 | 99.85 35 | 94.22 87 | 100.00 1 | 98.70 82 | 99.98 35 | 99.98 55 |
|
#test# | | | 98.59 36 | 98.41 35 | 99.14 66 | 99.96 8 | 97.43 104 | 99.95 43 | 98.61 71 | 95.00 87 | 99.31 71 | 99.85 35 | 94.22 87 | 100.00 1 | 98.78 77 | 99.98 35 | 99.98 55 |
|
ACMMPR | | | 98.50 43 | 98.32 46 | 99.05 76 | 99.96 8 | 97.18 112 | 99.95 43 | 98.60 73 | 94.77 96 | 99.31 71 | 99.84 48 | 93.73 102 | 100.00 1 | 98.70 82 | 99.98 35 | 99.98 55 |
|
ETV-MVS | | | 97.92 75 | 97.80 76 | 98.25 130 | 98.14 177 | 96.48 135 | 99.98 9 | 97.63 227 | 95.61 72 | 99.29 75 | 99.46 120 | 92.55 134 | 98.82 174 | 99.02 62 | 98.54 137 | 99.46 162 |
|
test222 | | | | | | 99.55 101 | 97.41 107 | 99.34 211 | 98.55 85 | 91.86 212 | 99.27 76 | 99.83 51 | 93.84 100 | | | 99.95 55 | 99.99 24 |
|
abl_6 | | | 97.67 88 | 97.34 90 | 98.66 100 | 99.68 91 | 96.11 155 | 99.68 156 | 98.14 188 | 93.80 145 | 99.27 76 | 99.70 95 | 88.65 195 | 99.98 46 | 97.46 130 | 99.72 98 | 99.89 94 |
|
test1172 | | | 98.38 54 | 98.25 49 | 98.77 93 | 99.88 54 | 96.56 134 | 99.80 125 | 98.36 152 | 94.68 100 | 99.20 78 | 99.80 60 | 93.28 114 | 99.78 116 | 99.34 48 | 99.92 71 | 99.98 55 |
|
CANet_DTU | | | 96.76 120 | 96.15 124 | 98.60 105 | 98.78 145 | 97.53 94 | 99.84 112 | 97.63 227 | 97.25 24 | 99.20 78 | 99.64 106 | 81.36 255 | 99.98 46 | 92.77 223 | 98.89 130 | 98.28 214 |
|
EPNet | | | 98.49 44 | 98.40 37 | 98.77 93 | 99.62 95 | 96.80 127 | 99.90 80 | 99.51 16 | 97.60 12 | 99.20 78 | 99.36 129 | 93.71 103 | 99.91 79 | 97.99 113 | 98.71 135 | 99.61 136 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
DeepPCF-MVS | | 95.94 2 | 97.71 87 | 98.98 12 | 93.92 277 | 99.63 94 | 81.76 355 | 99.96 25 | 98.56 79 | 99.47 1 | 99.19 81 | 99.99 1 | 94.16 91 | 100.00 1 | 99.92 13 | 99.93 67 | 100.00 1 |
|
VNet | | | 97.21 105 | 96.57 115 | 99.13 71 | 98.97 128 | 97.82 84 | 99.03 248 | 99.21 28 | 94.31 118 | 99.18 82 | 98.88 170 | 86.26 216 | 99.89 84 | 98.93 65 | 94.32 213 | 99.69 119 |
|
MCST-MVS | | | 99.32 3 | 99.14 4 | 99.86 5 | 99.97 3 | 99.59 5 | 99.97 18 | 98.64 65 | 98.47 2 | 99.13 83 | 99.92 13 | 96.38 30 | 100.00 1 | 99.74 30 | 100.00 1 | 100.00 1 |
|
DeepC-MVS_fast | | 96.59 1 | 98.81 23 | 98.54 28 | 99.62 18 | 99.90 47 | 98.85 33 | 99.24 224 | 98.47 105 | 98.14 4 | 99.08 84 | 99.91 15 | 93.09 120 | 100.00 1 | 99.04 60 | 99.99 22 | 100.00 1 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
114514_t | | | 97.41 98 | 96.83 106 | 99.14 66 | 99.51 105 | 97.83 83 | 99.89 88 | 98.27 170 | 88.48 278 | 99.06 85 | 99.66 104 | 90.30 172 | 99.64 144 | 96.32 154 | 99.97 48 | 99.96 74 |
|
PVSNet | | 91.05 13 | 97.13 106 | 96.69 111 | 98.45 120 | 99.52 103 | 95.81 160 | 99.95 43 | 99.65 11 | 94.73 98 | 99.04 86 | 99.21 141 | 84.48 230 | 99.95 65 | 94.92 174 | 98.74 134 | 99.58 145 |
|
CHOSEN 280x420 | | | 99.01 13 | 99.03 10 | 98.95 86 | 99.38 111 | 98.87 31 | 98.46 294 | 99.42 21 | 97.03 28 | 99.02 87 | 99.09 145 | 99.35 1 | 98.21 225 | 99.73 33 | 99.78 94 | 99.77 110 |
|
Regformer-3 | | | 98.58 37 | 98.41 35 | 99.10 72 | 99.84 65 | 97.57 92 | 99.66 160 | 98.52 92 | 95.79 63 | 99.01 88 | 99.77 72 | 94.40 74 | 99.75 126 | 98.82 73 | 99.83 85 | 99.98 55 |
|
Regformer-4 | | | 98.56 38 | 98.39 39 | 99.08 74 | 99.84 65 | 97.52 95 | 99.66 160 | 98.52 92 | 95.76 66 | 99.01 88 | 99.77 72 | 94.33 83 | 99.75 126 | 98.80 76 | 99.83 85 | 99.98 55 |
|
MG-MVS | | | 98.91 18 | 98.65 22 | 99.68 14 | 99.94 14 | 99.07 22 | 99.64 168 | 99.44 19 | 97.33 18 | 99.00 90 | 99.72 91 | 94.03 94 | 99.98 46 | 98.73 81 | 100.00 1 | 100.00 1 |
|
diffmvs | | | 97.00 110 | 96.64 112 | 98.09 136 | 97.64 206 | 96.17 151 | 99.81 121 | 97.19 271 | 94.67 102 | 98.95 91 | 99.28 131 | 86.43 213 | 98.76 179 | 98.37 97 | 97.42 165 | 99.33 178 |
|
HPM-MVS_fast | | | 97.80 82 | 97.50 84 | 98.68 98 | 99.79 75 | 96.42 137 | 99.88 90 | 98.16 185 | 91.75 217 | 98.94 92 | 99.54 114 | 91.82 152 | 99.65 143 | 97.62 128 | 99.99 22 | 99.99 24 |
|
dcpmvs_2 | | | 97.42 97 | 98.09 60 | 95.42 218 | 99.58 100 | 87.24 326 | 99.23 225 | 96.95 300 | 94.28 120 | 98.93 93 | 99.73 89 | 94.39 78 | 99.16 164 | 99.89 17 | 99.82 91 | 99.86 100 |
|
CP-MVS | | | 98.45 47 | 98.32 46 | 98.87 89 | 99.96 8 | 96.62 131 | 99.97 18 | 98.39 143 | 94.43 110 | 98.90 94 | 99.87 28 | 94.30 85 | 100.00 1 | 99.04 60 | 99.99 22 | 99.99 24 |
|
MVS_Test | | | 96.46 132 | 95.74 145 | 98.61 104 | 98.18 174 | 97.23 110 | 99.31 215 | 97.15 277 | 91.07 234 | 98.84 95 | 97.05 239 | 88.17 198 | 98.97 170 | 94.39 189 | 97.50 162 | 99.61 136 |
|
API-MVS | | | 97.86 77 | 97.66 78 | 98.47 118 | 99.52 103 | 95.41 174 | 99.47 195 | 98.87 46 | 91.68 218 | 98.84 95 | 99.85 35 | 92.34 140 | 99.99 40 | 98.44 94 | 99.96 52 | 100.00 1 |
|
GST-MVS | | | 98.27 60 | 97.97 67 | 99.17 60 | 99.92 36 | 97.57 92 | 99.93 67 | 98.39 143 | 94.04 134 | 98.80 97 | 99.74 87 | 92.98 122 | 100.00 1 | 98.16 103 | 99.76 95 | 99.93 85 |
|
MVS_111021_LR | | | 98.42 49 | 98.38 40 | 98.53 115 | 99.39 110 | 95.79 161 | 99.87 93 | 99.86 2 | 96.70 38 | 98.78 98 | 99.79 64 | 92.03 147 | 99.90 80 | 99.17 52 | 99.86 83 | 99.88 96 |
|
h-mvs33 | | | 94.92 171 | 94.36 174 | 96.59 189 | 98.85 141 | 91.29 273 | 98.93 259 | 98.94 37 | 95.90 60 | 98.77 99 | 98.42 199 | 90.89 166 | 99.77 120 | 97.80 119 | 70.76 352 | 98.72 210 |
|
hse-mvs2 | | | 94.38 187 | 94.08 180 | 95.31 222 | 98.27 169 | 90.02 297 | 99.29 220 | 98.56 79 | 95.90 60 | 98.77 99 | 98.00 208 | 90.89 166 | 98.26 223 | 97.80 119 | 69.20 358 | 97.64 225 |
|
TSAR-MVS + GP. | | | 98.60 34 | 98.51 30 | 98.86 90 | 99.73 86 | 96.63 130 | 99.97 18 | 97.92 207 | 98.07 5 | 98.76 101 | 99.55 112 | 95.00 60 | 99.94 73 | 99.91 16 | 97.68 159 | 99.99 24 |
|
sss | | | 97.57 90 | 97.03 102 | 99.18 57 | 98.37 163 | 98.04 75 | 99.73 148 | 99.38 22 | 93.46 155 | 98.76 101 | 99.06 147 | 91.21 156 | 99.89 84 | 96.33 153 | 97.01 174 | 99.62 133 |
|
CostFormer | | | 96.10 143 | 95.88 142 | 96.78 182 | 97.03 232 | 92.55 243 | 97.08 330 | 97.83 216 | 90.04 253 | 98.72 103 | 94.89 314 | 95.01 59 | 98.29 217 | 96.54 152 | 95.77 196 | 99.50 159 |
|
tpmrst | | | 96.27 142 | 95.98 130 | 97.13 173 | 97.96 184 | 93.15 227 | 96.34 339 | 98.17 182 | 92.07 206 | 98.71 104 | 95.12 305 | 93.91 97 | 98.73 181 | 94.91 176 | 96.62 179 | 99.50 159 |
|
MVS_111021_HR | | | 98.72 28 | 98.62 24 | 99.01 81 | 99.36 112 | 97.18 112 | 99.93 67 | 99.90 1 | 96.81 35 | 98.67 105 | 99.77 72 | 93.92 96 | 99.89 84 | 99.27 51 | 99.94 61 | 99.96 74 |
|
MAR-MVS | | | 97.43 93 | 97.19 95 | 98.15 135 | 99.47 107 | 94.79 193 | 99.05 246 | 98.76 53 | 92.65 184 | 98.66 106 | 99.82 55 | 88.52 196 | 99.98 46 | 98.12 105 | 99.63 103 | 99.67 122 |
Zhenyu Xu, Yiguang Liu, Xuelei Shi, Ying Wang, Yunan Zheng: MARMVS: Matching Ambiguity Reduced Multiple View Stereo for Efficient Large Scale Scene Reconstruction. CVPR 2020 |
Effi-MVS+ | | | 96.30 139 | 95.69 146 | 98.16 132 | 97.85 191 | 96.26 144 | 97.41 323 | 97.21 270 | 90.37 246 | 98.65 107 | 98.58 189 | 86.61 212 | 98.70 184 | 97.11 139 | 97.37 167 | 99.52 155 |
|
HPM-MVS |  | | 97.96 72 | 97.72 77 | 98.68 98 | 99.84 65 | 96.39 140 | 99.90 80 | 98.17 182 | 92.61 186 | 98.62 108 | 99.57 111 | 91.87 150 | 99.67 141 | 98.87 71 | 99.99 22 | 99.99 24 |
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023 |
mPP-MVS | | | 98.39 53 | 98.20 52 | 98.97 84 | 99.97 3 | 96.92 123 | 99.95 43 | 98.38 147 | 95.04 86 | 98.61 109 | 99.80 60 | 93.39 108 | 100.00 1 | 98.64 88 | 100.00 1 | 99.98 55 |
|
jason | | | 97.24 103 | 96.86 105 | 98.38 126 | 95.73 271 | 97.32 108 | 99.97 18 | 97.40 257 | 95.34 80 | 98.60 110 | 99.54 114 | 87.70 200 | 98.56 190 | 97.94 116 | 99.47 115 | 99.25 185 |
jason: jason. |
CANet | | | 98.27 60 | 97.82 75 | 99.63 15 | 99.72 88 | 99.10 21 | 99.98 9 | 98.51 99 | 97.00 29 | 98.52 111 | 99.71 93 | 87.80 199 | 99.95 65 | 99.75 28 | 99.38 119 | 99.83 102 |
|
EI-MVSNet-Vis-set | | | 98.27 60 | 98.11 59 | 98.75 95 | 99.83 68 | 96.59 133 | 99.40 201 | 98.51 99 | 95.29 81 | 98.51 112 | 99.76 76 | 93.60 106 | 99.71 134 | 98.53 92 | 99.52 112 | 99.95 82 |
|
ZNCC-MVS | | | 98.31 57 | 98.03 63 | 99.17 60 | 99.88 54 | 97.59 91 | 99.94 61 | 98.44 112 | 94.31 118 | 98.50 113 | 99.82 55 | 93.06 121 | 99.99 40 | 98.30 100 | 99.99 22 | 99.93 85 |
|
LFMVS | | | 94.75 176 | 93.56 194 | 98.30 128 | 99.03 123 | 95.70 167 | 98.74 278 | 97.98 200 | 87.81 287 | 98.47 114 | 99.39 126 | 67.43 341 | 99.53 146 | 98.01 111 | 95.20 207 | 99.67 122 |
|
tpm2 | | | 95.47 162 | 95.18 159 | 96.35 199 | 96.91 237 | 91.70 266 | 96.96 333 | 97.93 205 | 88.04 284 | 98.44 115 | 95.40 291 | 93.32 111 | 97.97 236 | 94.00 197 | 95.61 200 | 99.38 171 |
|
alignmvs | | | 97.81 81 | 97.33 91 | 99.25 52 | 98.77 146 | 98.66 50 | 99.99 3 | 98.44 112 | 94.40 114 | 98.41 116 | 99.47 118 | 93.65 104 | 99.42 156 | 98.57 90 | 94.26 214 | 99.67 122 |
|
UA-Net | | | 96.54 129 | 95.96 135 | 98.27 129 | 98.23 171 | 95.71 166 | 98.00 315 | 98.45 109 | 93.72 149 | 98.41 116 | 99.27 134 | 88.71 194 | 99.66 142 | 91.19 238 | 97.69 158 | 99.44 166 |
|
DP-MVS Recon | | | 98.41 50 | 98.02 64 | 99.56 24 | 99.97 3 | 98.70 47 | 99.92 71 | 98.44 112 | 92.06 208 | 98.40 118 | 99.84 48 | 95.68 42 | 100.00 1 | 98.19 101 | 99.71 99 | 99.97 67 |
|
CPTT-MVS | | | 97.64 89 | 97.32 92 | 98.58 108 | 99.97 3 | 95.77 162 | 99.96 25 | 98.35 155 | 89.90 254 | 98.36 119 | 99.79 64 | 91.18 160 | 99.99 40 | 98.37 97 | 99.99 22 | 99.99 24 |
|
PAPM | | | 98.60 34 | 98.42 33 | 99.14 66 | 96.05 259 | 98.96 24 | 99.90 80 | 99.35 24 | 96.68 39 | 98.35 120 | 99.66 104 | 96.45 29 | 98.51 193 | 99.45 43 | 99.89 78 | 99.96 74 |
|
HY-MVS | | 92.50 7 | 97.79 83 | 97.17 97 | 99.63 15 | 98.98 127 | 99.32 8 | 97.49 322 | 99.52 14 | 95.69 70 | 98.32 121 | 97.41 226 | 93.32 111 | 99.77 120 | 98.08 109 | 95.75 198 | 99.81 104 |
|
EI-MVSNet-UG-set | | | 98.14 67 | 97.99 66 | 98.60 105 | 99.80 74 | 96.27 143 | 99.36 210 | 98.50 103 | 95.21 83 | 98.30 122 | 99.75 82 | 93.29 113 | 99.73 133 | 98.37 97 | 99.30 121 | 99.81 104 |
|
PVSNet_BlendedMVS | | | 96.05 145 | 95.82 144 | 96.72 185 | 99.59 96 | 96.99 120 | 99.95 43 | 99.10 29 | 94.06 131 | 98.27 123 | 95.80 272 | 89.00 190 | 99.95 65 | 99.12 53 | 87.53 266 | 93.24 327 |
|
PVSNet_Blended | | | 97.94 73 | 97.64 79 | 98.83 91 | 99.59 96 | 96.99 120 | 100.00 1 | 99.10 29 | 95.38 78 | 98.27 123 | 99.08 146 | 89.00 190 | 99.95 65 | 99.12 53 | 99.25 123 | 99.57 146 |
|
MP-MVS |  | | 98.23 65 | 97.97 67 | 99.03 78 | 99.94 14 | 97.17 115 | 99.95 43 | 98.39 143 | 94.70 99 | 98.26 125 | 99.81 59 | 91.84 151 | 100.00 1 | 98.85 72 | 99.97 48 | 99.93 85 |
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo. |
WTY-MVS | | | 98.10 69 | 97.60 81 | 99.60 20 | 98.92 134 | 99.28 16 | 99.89 88 | 99.52 14 | 95.58 73 | 98.24 126 | 99.39 126 | 93.33 110 | 99.74 130 | 97.98 115 | 95.58 201 | 99.78 109 |
|
DELS-MVS | | | 98.54 40 | 98.22 50 | 99.50 32 | 99.15 119 | 98.65 52 | 100.00 1 | 98.58 75 | 97.70 9 | 98.21 127 | 99.24 139 | 92.58 133 | 99.94 73 | 98.63 89 | 99.94 61 | 99.92 91 |
Christian Sormann, Emanuele Santellani, Mattia Rossi, Andreas Kuhn, Friedrich Fraundorfer: DELS-MVS: Deep Epipolar Line Search for Multi-View Stereo. Winter Conference on Applications of Computer Vision (WACV), 2023 |
MDTV_nov1_ep13_2view | | | | | | | 96.26 144 | 96.11 343 | | 91.89 211 | 98.06 128 | | 94.40 74 | | 94.30 193 | | 99.67 122 |
|
PAPR | | | 98.52 42 | 98.16 55 | 99.58 23 | 99.97 3 | 98.77 40 | 99.95 43 | 98.43 120 | 95.35 79 | 98.03 129 | 99.75 82 | 94.03 94 | 99.98 46 | 98.11 106 | 99.83 85 | 99.99 24 |
|
MDTV_nov1_ep13 | | | | 95.69 146 | | 97.90 187 | 94.15 202 | 95.98 345 | 98.44 112 | 93.12 165 | 97.98 130 | 95.74 274 | 95.10 53 | 98.58 189 | 90.02 261 | 96.92 176 | |
|
test2506 | | | 97.53 91 | 97.19 95 | 98.58 108 | 98.66 150 | 96.90 124 | 98.81 273 | 99.77 5 | 94.93 89 | 97.95 131 | 98.96 160 | 92.51 135 | 99.20 160 | 94.93 173 | 98.15 147 | 99.64 128 |
|
GG-mvs-BLEND | | | | | 98.54 113 | 98.21 172 | 98.01 76 | 93.87 354 | 98.52 92 | | 97.92 132 | 97.92 214 | 99.02 2 | 97.94 241 | 98.17 102 | 99.58 109 | 99.67 122 |
|
EIA-MVS | | | 97.53 91 | 97.46 85 | 97.76 149 | 98.04 181 | 94.84 190 | 99.98 9 | 97.61 232 | 94.41 113 | 97.90 133 | 99.59 109 | 92.40 138 | 98.87 172 | 98.04 110 | 99.13 128 | 99.59 139 |
|
test_yl | | | 97.83 79 | 97.37 88 | 99.21 54 | 99.18 116 | 97.98 78 | 99.64 168 | 99.27 26 | 91.43 226 | 97.88 134 | 98.99 154 | 95.84 39 | 99.84 108 | 98.82 73 | 95.32 205 | 99.79 106 |
|
DCV-MVSNet | | | 97.83 79 | 97.37 88 | 99.21 54 | 99.18 116 | 97.98 78 | 99.64 168 | 99.27 26 | 91.43 226 | 97.88 134 | 98.99 154 | 95.84 39 | 99.84 108 | 98.82 73 | 95.32 205 | 99.79 106 |
|
canonicalmvs | | | 97.09 109 | 96.32 121 | 99.39 46 | 98.93 132 | 98.95 25 | 99.72 151 | 97.35 260 | 94.45 108 | 97.88 134 | 99.42 122 | 86.71 210 | 99.52 147 | 98.48 93 | 93.97 218 | 99.72 116 |
|
VDDNet | | | 93.12 216 | 91.91 232 | 96.76 183 | 96.67 252 | 92.65 241 | 98.69 283 | 98.21 177 | 82.81 338 | 97.75 137 | 99.28 131 | 61.57 357 | 99.48 154 | 98.09 108 | 94.09 216 | 98.15 216 |
|
EPMVS | | | 96.53 130 | 96.01 127 | 98.09 136 | 98.43 160 | 96.12 154 | 96.36 338 | 99.43 20 | 93.53 153 | 97.64 138 | 95.04 307 | 94.41 73 | 98.38 209 | 91.13 239 | 98.11 150 | 99.75 112 |
|
JIA-IIPM | | | 91.76 251 | 90.70 251 | 94.94 233 | 96.11 257 | 87.51 324 | 93.16 357 | 98.13 190 | 75.79 358 | 97.58 139 | 77.68 369 | 92.84 126 | 97.97 236 | 88.47 275 | 96.54 180 | 99.33 178 |
|
EPNet_dtu | | | 95.71 155 | 95.39 152 | 96.66 187 | 98.92 134 | 93.41 223 | 99.57 178 | 98.90 42 | 96.19 55 | 97.52 140 | 98.56 191 | 92.65 131 | 97.36 257 | 77.89 342 | 98.33 142 | 99.20 188 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
PAPM_NR | | | 98.12 68 | 97.93 72 | 98.70 97 | 99.94 14 | 96.13 152 | 99.82 119 | 98.43 120 | 94.56 105 | 97.52 140 | 99.70 95 | 94.40 74 | 99.98 46 | 97.00 143 | 99.98 35 | 99.99 24 |
|
thisisatest0515 | | | 97.41 98 | 97.02 103 | 98.59 107 | 97.71 205 | 97.52 95 | 99.97 18 | 98.54 89 | 91.83 213 | 97.45 142 | 99.04 148 | 97.50 9 | 99.10 166 | 94.75 182 | 96.37 185 | 99.16 190 |
|
OMC-MVS | | | 97.28 101 | 97.23 94 | 97.41 163 | 99.76 79 | 93.36 226 | 99.65 164 | 97.95 203 | 96.03 59 | 97.41 143 | 99.70 95 | 89.61 179 | 99.51 148 | 96.73 150 | 98.25 146 | 99.38 171 |
|
gg-mvs-nofinetune | | | 93.51 207 | 91.86 234 | 98.47 118 | 97.72 203 | 97.96 80 | 92.62 358 | 98.51 99 | 74.70 361 | 97.33 144 | 69.59 372 | 98.91 3 | 97.79 244 | 97.77 124 | 99.56 110 | 99.67 122 |
|
PatchT | | | 90.38 275 | 88.75 289 | 95.25 224 | 95.99 261 | 90.16 293 | 91.22 365 | 97.54 240 | 76.80 354 | 97.26 145 | 86.01 364 | 91.88 149 | 96.07 328 | 66.16 365 | 95.91 193 | 99.51 157 |
|
PLC |  | 95.54 3 | 97.93 74 | 97.89 74 | 98.05 138 | 99.82 70 | 94.77 194 | 99.92 71 | 98.46 107 | 93.93 139 | 97.20 146 | 99.27 134 | 95.44 48 | 99.97 56 | 97.41 131 | 99.51 114 | 99.41 169 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
zzz-MVS | | | 98.33 56 | 98.00 65 | 99.30 50 | 99.85 60 | 97.93 81 | 99.80 125 | 98.28 167 | 95.76 66 | 97.18 147 | 99.88 24 | 92.74 129 | 100.00 1 | 98.67 84 | 99.88 80 | 99.99 24 |
|
MTAPA | | | 98.29 59 | 97.96 70 | 99.30 50 | 99.85 60 | 97.93 81 | 99.39 205 | 98.28 167 | 95.76 66 | 97.18 147 | 99.88 24 | 92.74 129 | 100.00 1 | 98.67 84 | 99.88 80 | 99.99 24 |
|
PatchmatchNet |  | | 95.94 149 | 95.45 150 | 97.39 165 | 97.83 192 | 94.41 199 | 96.05 344 | 98.40 140 | 92.86 169 | 97.09 149 | 95.28 302 | 94.21 90 | 98.07 232 | 89.26 267 | 98.11 150 | 99.70 117 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
thisisatest0530 | | | 97.10 107 | 96.72 110 | 98.22 131 | 97.60 208 | 96.70 128 | 99.92 71 | 98.54 89 | 91.11 233 | 97.07 150 | 98.97 158 | 97.47 12 | 99.03 167 | 93.73 208 | 96.09 188 | 98.92 200 |
|
CR-MVSNet | | | 93.45 210 | 92.62 214 | 95.94 207 | 96.29 254 | 92.66 239 | 92.01 361 | 96.23 333 | 92.62 185 | 96.94 151 | 93.31 338 | 91.04 161 | 96.03 329 | 79.23 335 | 95.96 191 | 99.13 194 |
|
RPMNet | | | 89.76 289 | 87.28 304 | 97.19 172 | 96.29 254 | 92.66 239 | 92.01 361 | 98.31 162 | 70.19 366 | 96.94 151 | 85.87 365 | 87.25 205 | 99.78 116 | 62.69 368 | 95.96 191 | 99.13 194 |
|
baseline | | | 96.43 133 | 95.98 130 | 97.76 149 | 97.34 219 | 95.17 184 | 99.51 188 | 97.17 274 | 93.92 140 | 96.90 153 | 99.28 131 | 85.37 224 | 98.64 187 | 97.50 129 | 96.86 178 | 99.46 162 |
|
ECVR-MVS |  | | 95.66 157 | 95.05 162 | 97.51 158 | 98.66 150 | 93.71 214 | 98.85 270 | 98.45 109 | 94.93 89 | 96.86 154 | 98.96 160 | 75.22 308 | 99.20 160 | 95.34 165 | 98.15 147 | 99.64 128 |
|
Vis-MVSNet |  | | 95.72 153 | 95.15 160 | 97.45 160 | 97.62 207 | 94.28 201 | 99.28 221 | 98.24 173 | 94.27 122 | 96.84 155 | 98.94 166 | 79.39 274 | 98.76 179 | 93.25 214 | 98.49 138 | 99.30 181 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
VDD-MVS | | | 93.77 201 | 92.94 207 | 96.27 201 | 98.55 154 | 90.22 292 | 98.77 277 | 97.79 218 | 90.85 239 | 96.82 156 | 99.42 122 | 61.18 359 | 99.77 120 | 98.95 63 | 94.13 215 | 98.82 206 |
|
UGNet | | | 95.33 164 | 94.57 171 | 97.62 155 | 98.55 154 | 94.85 189 | 98.67 285 | 99.32 25 | 95.75 69 | 96.80 157 | 96.27 263 | 72.18 322 | 99.96 58 | 94.58 187 | 99.05 129 | 98.04 218 |
Wanjuan Su, Qingshan Xu, Wenbing Tao: Uncertainty-guided Multi-view Stereo Network for Depth Estimation. IEEE Transactions on Circuits and Systems for Video Technology, 2022 |
AdaColmap |  | | 97.23 104 | 96.80 108 | 98.51 116 | 99.99 1 | 95.60 170 | 99.09 235 | 98.84 49 | 93.32 159 | 96.74 158 | 99.72 91 | 86.04 217 | 100.00 1 | 98.01 111 | 99.43 118 | 99.94 84 |
|
tpm | | | 93.70 205 | 93.41 200 | 94.58 248 | 95.36 282 | 87.41 325 | 97.01 331 | 96.90 307 | 90.85 239 | 96.72 159 | 94.14 330 | 90.40 171 | 96.84 298 | 90.75 251 | 88.54 249 | 99.51 157 |
|
test1111 | | | 95.57 159 | 94.98 164 | 97.37 166 | 98.56 152 | 93.37 225 | 98.86 268 | 98.45 109 | 94.95 88 | 96.63 160 | 98.95 164 | 75.21 309 | 99.11 165 | 95.02 171 | 98.14 149 | 99.64 128 |
|
tttt0517 | | | 96.85 115 | 96.49 117 | 97.92 142 | 97.48 214 | 95.89 159 | 99.85 108 | 98.54 89 | 90.72 242 | 96.63 160 | 98.93 168 | 97.47 12 | 99.02 168 | 93.03 221 | 95.76 197 | 98.85 204 |
|
mvs-test1 | | | 95.53 160 | 95.97 133 | 94.20 264 | 97.77 196 | 85.44 337 | 99.95 43 | 97.06 287 | 94.92 91 | 96.58 162 | 98.72 180 | 85.81 218 | 98.98 169 | 94.80 179 | 98.11 150 | 98.18 215 |
|
casdiffmvs | | | 96.42 134 | 95.97 133 | 97.77 148 | 97.30 223 | 94.98 186 | 99.84 112 | 97.09 284 | 93.75 148 | 96.58 162 | 99.26 137 | 85.07 226 | 98.78 177 | 97.77 124 | 97.04 173 | 99.54 151 |
|
CNLPA | | | 97.76 85 | 97.38 87 | 98.92 88 | 99.53 102 | 96.84 125 | 99.87 93 | 98.14 188 | 93.78 146 | 96.55 164 | 99.69 98 | 92.28 141 | 99.98 46 | 97.13 138 | 99.44 117 | 99.93 85 |
|
PatchMatch-RL | | | 96.04 146 | 95.40 151 | 97.95 140 | 99.59 96 | 95.22 182 | 99.52 186 | 99.07 32 | 93.96 137 | 96.49 165 | 98.35 200 | 82.28 245 | 99.82 110 | 90.15 260 | 99.22 125 | 98.81 207 |
|
MP-MVS-pluss | | | 98.07 70 | 97.64 79 | 99.38 47 | 99.74 82 | 98.41 64 | 99.74 143 | 98.18 181 | 93.35 157 | 96.45 166 | 99.85 35 | 92.64 132 | 99.97 56 | 98.91 68 | 99.89 78 | 99.77 110 |
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
ADS-MVSNet2 | | | 93.80 200 | 93.88 185 | 93.55 290 | 97.87 189 | 85.94 333 | 94.24 350 | 96.84 312 | 90.07 251 | 96.43 167 | 94.48 325 | 90.29 173 | 95.37 337 | 87.44 285 | 97.23 168 | 99.36 174 |
|
ADS-MVSNet | | | 94.79 173 | 94.02 181 | 97.11 175 | 97.87 189 | 93.79 211 | 94.24 350 | 98.16 185 | 90.07 251 | 96.43 167 | 94.48 325 | 90.29 173 | 98.19 226 | 87.44 285 | 97.23 168 | 99.36 174 |
|
ACMMP |  | | 97.74 86 | 97.44 86 | 98.66 100 | 99.92 36 | 96.13 152 | 99.18 229 | 99.45 18 | 94.84 95 | 96.41 169 | 99.71 93 | 91.40 154 | 99.99 40 | 97.99 113 | 98.03 155 | 99.87 98 |
Qingshan Xu, Weihang Kong, Wenbing Tao, Marc Pollefeys: Multi-Scale Geometric Consistency Guided and Planar Prior Assisted Multi-View Stereo. IEEE Transactions on Pattern Analysis and Machine Intelligence |
PVSNet_Blended_VisFu | | | 97.27 102 | 96.81 107 | 98.66 100 | 98.81 143 | 96.67 129 | 99.92 71 | 98.64 65 | 94.51 107 | 96.38 170 | 98.49 193 | 89.05 189 | 99.88 90 | 97.10 140 | 98.34 141 | 99.43 167 |
|
AUN-MVS | | | 93.28 211 | 92.60 215 | 95.34 220 | 98.29 166 | 90.09 295 | 99.31 215 | 98.56 79 | 91.80 216 | 96.35 171 | 98.00 208 | 89.38 182 | 98.28 219 | 92.46 224 | 69.22 357 | 97.64 225 |
|
thres200 | | | 96.96 111 | 96.21 123 | 99.22 53 | 98.97 128 | 98.84 34 | 99.85 108 | 99.71 6 | 93.17 164 | 96.26 172 | 98.88 170 | 89.87 177 | 99.51 148 | 94.26 194 | 94.91 208 | 99.31 180 |
|
HyFIR lowres test | | | 96.66 127 | 96.43 119 | 97.36 168 | 99.05 122 | 93.91 210 | 99.70 153 | 99.80 3 | 90.54 243 | 96.26 172 | 98.08 205 | 92.15 144 | 98.23 224 | 96.84 149 | 95.46 202 | 99.93 85 |
|
SCA | | | 94.69 177 | 93.81 187 | 97.33 170 | 97.10 228 | 94.44 196 | 98.86 268 | 98.32 160 | 93.30 160 | 96.17 174 | 95.59 281 | 76.48 296 | 97.95 239 | 91.06 241 | 97.43 163 | 99.59 139 |
|
tfpn200view9 | | | 96.79 118 | 95.99 128 | 99.19 56 | 98.94 130 | 98.82 35 | 99.78 129 | 99.71 6 | 92.86 169 | 96.02 175 | 98.87 172 | 89.33 183 | 99.50 150 | 93.84 200 | 94.57 209 | 99.27 183 |
|
thres400 | | | 96.78 119 | 95.99 128 | 99.16 62 | 98.94 130 | 98.82 35 | 99.78 129 | 99.71 6 | 92.86 169 | 96.02 175 | 98.87 172 | 89.33 183 | 99.50 150 | 93.84 200 | 94.57 209 | 99.16 190 |
|
dp | | | 95.05 168 | 94.43 173 | 96.91 178 | 97.99 183 | 92.73 237 | 96.29 340 | 97.98 200 | 89.70 257 | 95.93 177 | 94.67 320 | 93.83 101 | 98.45 198 | 86.91 297 | 96.53 181 | 99.54 151 |
|
thres100view900 | | | 96.74 122 | 95.92 140 | 99.18 57 | 98.90 137 | 98.77 40 | 99.74 143 | 99.71 6 | 92.59 188 | 95.84 178 | 98.86 174 | 89.25 185 | 99.50 150 | 93.84 200 | 94.57 209 | 99.27 183 |
|
thres600view7 | | | 96.69 125 | 95.87 143 | 99.14 66 | 98.90 137 | 98.78 39 | 99.74 143 | 99.71 6 | 92.59 188 | 95.84 178 | 98.86 174 | 89.25 185 | 99.50 150 | 93.44 213 | 94.50 212 | 99.16 190 |
|
EPP-MVSNet | | | 96.69 125 | 96.60 113 | 96.96 177 | 97.74 199 | 93.05 230 | 99.37 208 | 98.56 79 | 88.75 272 | 95.83 180 | 99.01 151 | 96.01 32 | 98.56 190 | 96.92 147 | 97.20 170 | 99.25 185 |
|
TESTMET0.1,1 | | | 96.74 122 | 96.26 122 | 98.16 132 | 97.36 218 | 96.48 135 | 99.96 25 | 98.29 166 | 91.93 210 | 95.77 181 | 98.07 206 | 95.54 44 | 98.29 217 | 90.55 252 | 98.89 130 | 99.70 117 |
|
F-COLMAP | | | 96.93 113 | 96.95 104 | 96.87 180 | 99.71 89 | 91.74 262 | 99.85 108 | 97.95 203 | 93.11 166 | 95.72 182 | 99.16 143 | 92.35 139 | 99.94 73 | 95.32 166 | 99.35 120 | 98.92 200 |
|
test-LLR | | | 96.47 131 | 96.04 126 | 97.78 146 | 97.02 233 | 95.44 172 | 99.96 25 | 98.21 177 | 94.07 129 | 95.55 183 | 96.38 258 | 93.90 98 | 98.27 221 | 90.42 255 | 98.83 132 | 99.64 128 |
|
test-mter | | | 96.39 135 | 95.93 138 | 97.78 146 | 97.02 233 | 95.44 172 | 99.96 25 | 98.21 177 | 91.81 215 | 95.55 183 | 96.38 258 | 95.17 51 | 98.27 221 | 90.42 255 | 98.83 132 | 99.64 128 |
|
IS-MVSNet | | | 96.29 140 | 95.90 141 | 97.45 160 | 98.13 178 | 94.80 192 | 99.08 237 | 97.61 232 | 92.02 209 | 95.54 185 | 98.96 160 | 90.64 169 | 98.08 230 | 93.73 208 | 97.41 166 | 99.47 161 |
|
CHOSEN 1792x2688 | | | 96.81 117 | 96.53 116 | 97.64 153 | 98.91 136 | 93.07 228 | 99.65 164 | 99.80 3 | 95.64 71 | 95.39 186 | 98.86 174 | 84.35 233 | 99.90 80 | 96.98 144 | 99.16 126 | 99.95 82 |
|
CDS-MVSNet | | | 96.34 136 | 96.07 125 | 97.13 173 | 97.37 217 | 94.96 187 | 99.53 185 | 97.91 208 | 91.55 221 | 95.37 187 | 98.32 201 | 95.05 57 | 97.13 276 | 93.80 204 | 95.75 198 | 99.30 181 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
Effi-MVS+-dtu | | | 94.53 184 | 95.30 155 | 92.22 308 | 97.77 196 | 82.54 348 | 99.59 174 | 97.06 287 | 94.92 91 | 95.29 188 | 95.37 295 | 85.81 218 | 97.89 242 | 94.80 179 | 97.07 172 | 96.23 235 |
|
CSCG | | | 97.10 107 | 97.04 101 | 97.27 171 | 99.89 50 | 91.92 257 | 99.90 80 | 99.07 32 | 88.67 274 | 95.26 189 | 99.82 55 | 93.17 119 | 99.98 46 | 98.15 104 | 99.47 115 | 99.90 93 |
|
Vis-MVSNet (Re-imp) | | | 96.32 137 | 95.98 130 | 97.35 169 | 97.93 186 | 94.82 191 | 99.47 195 | 98.15 187 | 91.83 213 | 95.09 190 | 99.11 144 | 91.37 155 | 97.47 255 | 93.47 212 | 97.43 163 | 99.74 113 |
|
TAMVS | | | 95.85 150 | 95.58 148 | 96.65 188 | 97.07 229 | 93.50 219 | 99.17 230 | 97.82 217 | 91.39 229 | 95.02 191 | 98.01 207 | 92.20 142 | 97.30 264 | 93.75 207 | 95.83 195 | 99.14 193 |
|
XVG-OURS-SEG-HR | | | 94.79 173 | 94.70 170 | 95.08 228 | 98.05 180 | 89.19 306 | 99.08 237 | 97.54 240 | 93.66 150 | 94.87 192 | 99.58 110 | 78.78 279 | 99.79 114 | 97.31 133 | 93.40 222 | 96.25 233 |
|
XVG-OURS | | | 94.82 172 | 94.74 169 | 95.06 229 | 98.00 182 | 89.19 306 | 99.08 237 | 97.55 238 | 94.10 127 | 94.71 193 | 99.62 107 | 80.51 266 | 99.74 130 | 96.04 157 | 93.06 226 | 96.25 233 |
|
ab-mvs | | | 94.69 177 | 93.42 198 | 98.51 116 | 98.07 179 | 96.26 144 | 96.49 337 | 98.68 58 | 90.31 248 | 94.54 194 | 97.00 241 | 76.30 298 | 99.71 134 | 95.98 158 | 93.38 223 | 99.56 147 |
|
TAPA-MVS | | 92.12 8 | 94.42 186 | 93.60 191 | 96.90 179 | 99.33 113 | 91.78 261 | 99.78 129 | 98.00 197 | 89.89 255 | 94.52 195 | 99.47 118 | 91.97 148 | 99.18 162 | 69.90 358 | 99.52 112 | 99.73 114 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
TR-MVS | | | 94.54 182 | 93.56 194 | 97.49 159 | 97.96 184 | 94.34 200 | 98.71 281 | 97.51 246 | 90.30 249 | 94.51 196 | 98.69 181 | 75.56 303 | 98.77 178 | 92.82 222 | 95.99 190 | 99.35 176 |
|
Fast-Effi-MVS+ | | | 95.02 169 | 94.19 177 | 97.52 157 | 97.88 188 | 94.55 195 | 99.97 18 | 97.08 285 | 88.85 271 | 94.47 197 | 97.96 213 | 84.59 229 | 98.41 201 | 89.84 263 | 97.10 171 | 99.59 139 |
|
DeepC-MVS | | 94.51 4 | 96.92 114 | 96.40 120 | 98.45 120 | 99.16 118 | 95.90 158 | 99.66 160 | 98.06 194 | 96.37 51 | 94.37 198 | 99.49 117 | 83.29 240 | 99.90 80 | 97.63 127 | 99.61 107 | 99.55 148 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
RPSCF | | | 91.80 248 | 92.79 212 | 88.83 335 | 98.15 176 | 69.87 369 | 98.11 311 | 96.60 325 | 83.93 331 | 94.33 199 | 99.27 134 | 79.60 273 | 99.46 155 | 91.99 228 | 93.16 225 | 97.18 229 |
|
BH-RMVSNet | | | 95.18 165 | 94.31 176 | 97.80 144 | 98.17 175 | 95.23 181 | 99.76 137 | 97.53 242 | 92.52 193 | 94.27 200 | 99.25 138 | 76.84 292 | 98.80 175 | 90.89 248 | 99.54 111 | 99.35 176 |
|
CVMVSNet | | | 94.68 179 | 94.94 165 | 93.89 279 | 96.80 245 | 86.92 328 | 99.06 242 | 98.98 35 | 94.45 108 | 94.23 201 | 99.02 149 | 85.60 220 | 95.31 339 | 90.91 247 | 95.39 204 | 99.43 167 |
|
baseline1 | | | 95.78 152 | 94.86 166 | 98.54 113 | 98.47 159 | 98.07 73 | 99.06 242 | 97.99 198 | 92.68 182 | 94.13 202 | 98.62 186 | 93.28 114 | 98.69 185 | 93.79 205 | 85.76 275 | 98.84 205 |
|
Anonymous202405211 | | | 93.10 217 | 91.99 230 | 96.40 196 | 99.10 120 | 89.65 303 | 98.88 264 | 97.93 205 | 83.71 333 | 94.00 203 | 98.75 179 | 68.79 333 | 99.88 90 | 95.08 170 | 91.71 228 | 99.68 120 |
|
cascas | | | 94.64 180 | 93.61 189 | 97.74 151 | 97.82 193 | 96.26 144 | 99.96 25 | 97.78 219 | 85.76 313 | 94.00 203 | 97.54 222 | 76.95 291 | 99.21 159 | 97.23 136 | 95.43 203 | 97.76 224 |
|
Anonymous20240529 | | | 92.10 241 | 90.65 252 | 96.47 190 | 98.82 142 | 90.61 284 | 98.72 280 | 98.67 61 | 75.54 359 | 93.90 205 | 98.58 189 | 66.23 344 | 99.90 80 | 94.70 184 | 90.67 229 | 98.90 203 |
|
MVS_0304 | | | 89.28 296 | 88.31 295 | 92.21 309 | 97.05 231 | 86.53 330 | 97.76 320 | 99.57 13 | 85.58 318 | 93.86 206 | 92.71 342 | 51.04 370 | 96.30 319 | 84.49 310 | 92.72 227 | 93.79 310 |
|
LS3D | | | 95.84 151 | 95.11 161 | 98.02 139 | 99.85 60 | 95.10 185 | 98.74 278 | 98.50 103 | 87.22 294 | 93.66 207 | 99.86 31 | 87.45 203 | 99.95 65 | 90.94 246 | 99.81 93 | 99.02 198 |
|
GeoE | | | 94.36 190 | 93.48 196 | 96.99 176 | 97.29 224 | 93.54 218 | 99.96 25 | 96.72 321 | 88.35 281 | 93.43 208 | 98.94 166 | 82.05 246 | 98.05 233 | 88.12 280 | 96.48 183 | 99.37 173 |
|
HQP-NCC | | | | | | 95.78 265 | | 99.87 93 | | 96.82 32 | 93.37 209 | | | | | | |
|
ACMP_Plane | | | | | | 95.78 265 | | 99.87 93 | | 96.82 32 | 93.37 209 | | | | | | |
|
HQP4-MVS | | | | | | | | | | | 93.37 209 | | | 98.39 205 | | | 94.53 239 |
|
HQP-MVS | | | 94.61 181 | 94.50 172 | 94.92 234 | 95.78 265 | 91.85 258 | 99.87 93 | 97.89 209 | 96.82 32 | 93.37 209 | 98.65 183 | 80.65 264 | 98.39 205 | 97.92 117 | 89.60 230 | 94.53 239 |
|
HQP_MVS | | | 94.49 185 | 94.36 174 | 94.87 235 | 95.71 274 | 91.74 262 | 99.84 112 | 97.87 211 | 96.38 48 | 93.01 213 | 98.59 187 | 80.47 268 | 98.37 211 | 97.79 122 | 89.55 233 | 94.52 241 |
|
plane_prior3 | | | | | | | 91.64 268 | | | 96.63 40 | 93.01 213 | | | | | | |
|
GA-MVS | | | 93.83 197 | 92.84 210 | 96.80 181 | 95.73 271 | 93.57 216 | 99.88 90 | 97.24 269 | 92.57 190 | 92.92 215 | 96.66 251 | 78.73 280 | 97.67 248 | 87.75 283 | 94.06 217 | 99.17 189 |
|
tpm cat1 | | | 93.51 207 | 92.52 220 | 96.47 190 | 97.77 196 | 91.47 272 | 96.13 342 | 98.06 194 | 80.98 345 | 92.91 216 | 93.78 333 | 89.66 178 | 98.87 172 | 87.03 293 | 96.39 184 | 99.09 196 |
|
1112_ss | | | 96.01 147 | 95.20 158 | 98.42 123 | 97.80 194 | 96.41 138 | 99.65 164 | 96.66 323 | 92.71 179 | 92.88 217 | 99.40 124 | 92.16 143 | 99.30 157 | 91.92 230 | 93.66 219 | 99.55 148 |
|
Test_1112_low_res | | | 95.72 153 | 94.83 167 | 98.42 123 | 97.79 195 | 96.41 138 | 99.65 164 | 96.65 324 | 92.70 180 | 92.86 218 | 96.13 267 | 92.15 144 | 99.30 157 | 91.88 231 | 93.64 220 | 99.55 148 |
|
IB-MVS | | 92.85 6 | 94.99 170 | 93.94 183 | 98.16 132 | 97.72 203 | 95.69 168 | 99.99 3 | 98.81 50 | 94.28 120 | 92.70 219 | 96.90 243 | 95.08 54 | 99.17 163 | 96.07 156 | 73.88 350 | 99.60 138 |
Christian Sormann, Mattia Rossi, Andreas Kuhn and Friedrich Fraundorfer: IB-MVS: An Iterative Algorithm for Deep Multi-View Stereo based on Binary Decisions. BMVC 2021 |
iter_conf_final | | | 96.01 147 | 95.93 138 | 96.28 200 | 98.38 162 | 97.03 118 | 99.87 93 | 97.03 291 | 94.05 133 | 92.61 220 | 97.98 211 | 98.01 5 | 97.34 259 | 97.02 142 | 88.39 252 | 94.47 244 |
|
Fast-Effi-MVS+-dtu | | | 93.72 204 | 93.86 186 | 93.29 293 | 97.06 230 | 86.16 331 | 99.80 125 | 96.83 313 | 92.66 183 | 92.58 221 | 97.83 215 | 81.39 254 | 97.67 248 | 89.75 264 | 96.87 177 | 96.05 237 |
|
iter_conf05 | | | 96.07 144 | 95.95 137 | 96.44 194 | 98.43 160 | 97.52 95 | 99.91 75 | 96.85 311 | 94.16 124 | 92.49 222 | 97.98 211 | 98.20 4 | 97.34 259 | 97.26 135 | 88.29 253 | 94.45 250 |
|
tpmvs | | | 94.28 192 | 93.57 193 | 96.40 196 | 98.55 154 | 91.50 271 | 95.70 349 | 98.55 85 | 87.47 289 | 92.15 223 | 94.26 329 | 91.42 153 | 98.95 171 | 88.15 278 | 95.85 194 | 98.76 209 |
|
BH-w/o | | | 95.71 155 | 95.38 153 | 96.68 186 | 98.49 158 | 92.28 247 | 99.84 112 | 97.50 247 | 92.12 205 | 92.06 224 | 98.79 178 | 84.69 228 | 98.67 186 | 95.29 167 | 99.66 102 | 99.09 196 |
|
VPA-MVSNet | | | 92.70 227 | 91.55 239 | 96.16 203 | 95.09 284 | 96.20 149 | 98.88 264 | 99.00 34 | 91.02 236 | 91.82 225 | 95.29 301 | 76.05 302 | 97.96 238 | 95.62 164 | 81.19 307 | 94.30 264 |
|
baseline2 | | | 96.71 124 | 96.49 117 | 97.37 166 | 95.63 278 | 95.96 157 | 99.74 143 | 98.88 45 | 92.94 168 | 91.61 226 | 98.97 158 | 97.72 7 | 98.62 188 | 94.83 178 | 98.08 154 | 97.53 228 |
|
OPM-MVS | | | 93.21 212 | 92.80 211 | 94.44 257 | 93.12 321 | 90.85 279 | 99.77 132 | 97.61 232 | 96.19 55 | 91.56 227 | 98.65 183 | 75.16 310 | 98.47 194 | 93.78 206 | 89.39 236 | 93.99 295 |
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS). |
EI-MVSNet | | | 93.73 203 | 93.40 201 | 94.74 240 | 96.80 245 | 92.69 238 | 99.06 242 | 97.67 224 | 88.96 267 | 91.39 228 | 99.02 149 | 88.75 193 | 97.30 264 | 91.07 240 | 87.85 260 | 94.22 269 |
|
MVSTER | | | 95.53 160 | 95.22 157 | 96.45 192 | 98.56 152 | 97.72 85 | 99.91 75 | 97.67 224 | 92.38 197 | 91.39 228 | 97.14 233 | 97.24 18 | 97.30 264 | 94.80 179 | 87.85 260 | 94.34 262 |
|
test_low_dy_conf_001 | | | 93.16 213 | 92.88 209 | 94.01 272 | 93.16 318 | 90.65 283 | 99.58 175 | 97.66 226 | 92.21 202 | 91.34 230 | 97.80 216 | 82.45 244 | 97.05 282 | 93.64 210 | 88.05 257 | 94.32 263 |
|
mvsmamba | | | 94.10 193 | 93.72 188 | 95.25 224 | 93.57 308 | 94.13 203 | 99.67 159 | 96.45 330 | 93.63 152 | 91.34 230 | 97.77 217 | 86.29 215 | 97.22 270 | 96.65 151 | 88.10 256 | 94.40 252 |
|
BH-untuned | | | 95.18 165 | 94.83 167 | 96.22 202 | 98.36 164 | 91.22 274 | 99.80 125 | 97.32 264 | 90.91 237 | 91.08 232 | 98.67 182 | 83.51 237 | 98.54 192 | 94.23 195 | 99.61 107 | 98.92 200 |
|
CLD-MVS | | | 94.06 195 | 93.90 184 | 94.55 250 | 96.02 260 | 90.69 280 | 99.98 9 | 97.72 220 | 96.62 42 | 91.05 233 | 98.85 177 | 77.21 288 | 98.47 194 | 98.11 106 | 89.51 235 | 94.48 243 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
MVS | | | 96.60 128 | 95.56 149 | 99.72 12 | 96.85 242 | 99.22 19 | 98.31 301 | 98.94 37 | 91.57 220 | 90.90 234 | 99.61 108 | 86.66 211 | 99.96 58 | 97.36 132 | 99.88 80 | 99.99 24 |
|
MSDG | | | 94.37 188 | 93.36 202 | 97.40 164 | 98.88 139 | 93.95 209 | 99.37 208 | 97.38 258 | 85.75 315 | 90.80 235 | 99.17 142 | 84.11 235 | 99.88 90 | 86.35 298 | 98.43 140 | 98.36 213 |
|
VPNet | | | 91.81 245 | 90.46 254 | 95.85 210 | 94.74 290 | 95.54 171 | 98.98 253 | 98.59 74 | 92.14 204 | 90.77 236 | 97.44 225 | 68.73 335 | 97.54 252 | 94.89 177 | 77.89 333 | 94.46 245 |
|
MIMVSNet | | | 90.30 278 | 88.67 290 | 95.17 227 | 96.45 253 | 91.64 268 | 92.39 359 | 97.15 277 | 85.99 309 | 90.50 237 | 93.19 340 | 66.95 342 | 94.86 345 | 82.01 325 | 93.43 221 | 99.01 199 |
|
mvs_anonymous | | | 95.65 158 | 95.03 163 | 97.53 156 | 98.19 173 | 95.74 164 | 99.33 212 | 97.49 248 | 90.87 238 | 90.47 238 | 97.10 235 | 88.23 197 | 97.16 273 | 95.92 159 | 97.66 160 | 99.68 120 |
|
bld_raw_dy_0_64 | | | 92.74 225 | 92.03 229 | 94.87 235 | 93.09 323 | 93.46 220 | 99.12 232 | 95.41 350 | 92.84 172 | 90.44 239 | 97.54 222 | 78.08 285 | 97.04 285 | 93.94 198 | 87.77 262 | 94.11 284 |
|
Patchmatch-test | | | 92.65 230 | 91.50 240 | 96.10 205 | 96.85 242 | 90.49 287 | 91.50 363 | 97.19 271 | 82.76 339 | 90.23 240 | 95.59 281 | 95.02 58 | 98.00 235 | 77.41 344 | 96.98 175 | 99.82 103 |
|
LPG-MVS_test | | | 92.96 219 | 92.71 213 | 93.71 284 | 95.43 280 | 88.67 312 | 99.75 140 | 97.62 229 | 92.81 173 | 90.05 241 | 98.49 193 | 75.24 306 | 98.40 203 | 95.84 161 | 89.12 237 | 94.07 287 |
|
LGP-MVS_train | | | | | 93.71 284 | 95.43 280 | 88.67 312 | | 97.62 229 | 92.81 173 | 90.05 241 | 98.49 193 | 75.24 306 | 98.40 203 | 95.84 161 | 89.12 237 | 94.07 287 |
|
DP-MVS | | | 94.54 182 | 93.42 198 | 97.91 143 | 99.46 109 | 94.04 205 | 98.93 259 | 97.48 249 | 81.15 344 | 90.04 243 | 99.55 112 | 87.02 208 | 99.95 65 | 88.97 269 | 98.11 150 | 99.73 114 |
|
test_djsdf | | | 92.83 222 | 92.29 223 | 94.47 255 | 91.90 340 | 92.46 244 | 99.55 182 | 97.27 267 | 91.17 230 | 89.96 244 | 96.07 269 | 81.10 257 | 96.89 295 | 94.67 185 | 88.91 239 | 94.05 289 |
|
ACMM | | 91.95 10 | 92.88 221 | 92.52 220 | 93.98 276 | 95.75 270 | 89.08 309 | 99.77 132 | 97.52 244 | 93.00 167 | 89.95 245 | 97.99 210 | 76.17 300 | 98.46 197 | 93.63 211 | 88.87 241 | 94.39 254 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
1314 | | | 96.84 116 | 95.96 135 | 99.48 36 | 96.74 249 | 98.52 59 | 98.31 301 | 98.86 47 | 95.82 62 | 89.91 246 | 98.98 156 | 87.49 202 | 99.96 58 | 97.80 119 | 99.73 97 | 99.96 74 |
|
XVG-ACMP-BASELINE | | | 91.22 258 | 90.75 249 | 92.63 305 | 93.73 306 | 85.61 334 | 98.52 293 | 97.44 251 | 92.77 177 | 89.90 247 | 96.85 247 | 66.64 343 | 98.39 205 | 92.29 226 | 88.61 246 | 93.89 303 |
|
miper_enhance_ethall | | | 94.36 190 | 93.98 182 | 95.49 214 | 98.68 149 | 95.24 180 | 99.73 148 | 97.29 266 | 93.28 161 | 89.86 248 | 95.97 270 | 94.37 79 | 97.05 282 | 92.20 227 | 84.45 287 | 94.19 272 |
|
nrg030 | | | 93.51 207 | 92.53 219 | 96.45 192 | 94.36 295 | 97.20 111 | 99.81 121 | 97.16 276 | 91.60 219 | 89.86 248 | 97.46 224 | 86.37 214 | 97.68 247 | 95.88 160 | 80.31 319 | 94.46 245 |
|
V42 | | | 91.28 256 | 90.12 265 | 94.74 240 | 93.42 313 | 93.46 220 | 99.68 156 | 97.02 292 | 87.36 291 | 89.85 250 | 95.05 306 | 81.31 256 | 97.34 259 | 87.34 288 | 80.07 321 | 93.40 322 |
|
v144192 | | | 90.79 266 | 89.52 274 | 94.59 247 | 93.11 322 | 92.77 233 | 99.56 180 | 96.99 295 | 86.38 305 | 89.82 251 | 94.95 313 | 80.50 267 | 97.10 279 | 83.98 313 | 80.41 317 | 93.90 302 |
|
GBi-Net | | | 90.88 263 | 89.82 268 | 94.08 268 | 97.53 210 | 91.97 253 | 98.43 296 | 96.95 300 | 87.05 295 | 89.68 252 | 94.72 316 | 71.34 325 | 96.11 324 | 87.01 294 | 85.65 276 | 94.17 273 |
|
test1 | | | 90.88 263 | 89.82 268 | 94.08 268 | 97.53 210 | 91.97 253 | 98.43 296 | 96.95 300 | 87.05 295 | 89.68 252 | 94.72 316 | 71.34 325 | 96.11 324 | 87.01 294 | 85.65 276 | 94.17 273 |
|
FMVSNet3 | | | 92.69 228 | 91.58 237 | 95.99 206 | 98.29 166 | 97.42 106 | 99.26 223 | 97.62 229 | 89.80 256 | 89.68 252 | 95.32 297 | 81.62 253 | 96.27 320 | 87.01 294 | 85.65 276 | 94.29 265 |
|
IterMVS-LS | | | 92.69 228 | 92.11 226 | 94.43 259 | 96.80 245 | 92.74 235 | 99.45 198 | 96.89 308 | 88.98 265 | 89.65 255 | 95.38 294 | 88.77 192 | 96.34 317 | 90.98 245 | 82.04 301 | 94.22 269 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
v1144 | | | 91.09 259 | 89.83 267 | 94.87 235 | 93.25 317 | 93.69 215 | 99.62 171 | 96.98 297 | 86.83 301 | 89.64 256 | 94.99 311 | 80.94 259 | 97.05 282 | 85.08 307 | 81.16 308 | 93.87 305 |
|
v1921920 | | | 90.46 273 | 89.12 281 | 94.50 253 | 92.96 327 | 92.46 244 | 99.49 192 | 96.98 297 | 86.10 308 | 89.61 257 | 95.30 298 | 78.55 282 | 97.03 288 | 82.17 324 | 80.89 315 | 94.01 292 |
|
v1192 | | | 90.62 271 | 89.25 279 | 94.72 242 | 93.13 319 | 93.07 228 | 99.50 190 | 97.02 292 | 86.33 306 | 89.56 258 | 95.01 308 | 79.22 275 | 97.09 281 | 82.34 323 | 81.16 308 | 94.01 292 |
|
PCF-MVS | | 94.20 5 | 95.18 165 | 94.10 179 | 98.43 122 | 98.55 154 | 95.99 156 | 97.91 317 | 97.31 265 | 90.35 247 | 89.48 259 | 99.22 140 | 85.19 225 | 99.89 84 | 90.40 257 | 98.47 139 | 99.41 169 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
3Dnovator | | 91.47 12 | 96.28 141 | 95.34 154 | 99.08 74 | 96.82 244 | 97.47 102 | 99.45 198 | 98.81 50 | 95.52 76 | 89.39 260 | 99.00 153 | 81.97 247 | 99.95 65 | 97.27 134 | 99.83 85 | 99.84 101 |
|
v1240 | | | 90.20 281 | 88.79 288 | 94.44 257 | 93.05 325 | 92.27 248 | 99.38 206 | 96.92 306 | 85.89 310 | 89.36 261 | 94.87 315 | 77.89 287 | 97.03 288 | 80.66 331 | 81.08 311 | 94.01 292 |
|
FIs | | | 94.10 193 | 93.43 197 | 96.11 204 | 94.70 291 | 96.82 126 | 99.58 175 | 98.93 41 | 92.54 191 | 89.34 262 | 97.31 229 | 87.62 201 | 97.10 279 | 94.22 196 | 86.58 271 | 94.40 252 |
|
ITE_SJBPF | | | | | 92.38 306 | 95.69 276 | 85.14 338 | | 95.71 343 | 92.81 173 | 89.33 263 | 98.11 204 | 70.23 330 | 98.42 200 | 85.91 302 | 88.16 255 | 93.59 319 |
|
v2v482 | | | 91.30 254 | 90.07 266 | 95.01 230 | 93.13 319 | 93.79 211 | 99.77 132 | 97.02 292 | 88.05 283 | 89.25 264 | 95.37 295 | 80.73 262 | 97.15 274 | 87.28 289 | 80.04 322 | 94.09 286 |
|
UniMVSNet (Re) | | | 93.07 218 | 92.13 225 | 95.88 208 | 94.84 288 | 96.24 148 | 99.88 90 | 98.98 35 | 92.49 195 | 89.25 264 | 95.40 291 | 87.09 207 | 97.14 275 | 93.13 219 | 78.16 331 | 94.26 266 |
|
bld_raw_conf005 | | | 92.79 223 | 92.18 224 | 94.61 245 | 93.38 315 | 92.27 248 | 98.99 251 | 95.20 356 | 93.34 158 | 89.25 264 | 97.67 220 | 78.03 286 | 97.21 271 | 95.81 163 | 87.99 259 | 94.35 260 |
|
UniMVSNet_NR-MVSNet | | | 92.95 220 | 92.11 226 | 95.49 214 | 94.61 293 | 95.28 178 | 99.83 118 | 99.08 31 | 91.49 222 | 89.21 267 | 96.86 246 | 87.14 206 | 96.73 303 | 93.20 215 | 77.52 336 | 94.46 245 |
|
DU-MVS | | | 92.46 233 | 91.45 242 | 95.49 214 | 94.05 300 | 95.28 178 | 99.81 121 | 98.74 54 | 92.25 201 | 89.21 267 | 96.64 253 | 81.66 251 | 96.73 303 | 93.20 215 | 77.52 336 | 94.46 245 |
|
eth_miper_zixun_eth | | | 92.41 234 | 91.93 231 | 93.84 280 | 97.28 225 | 90.68 281 | 98.83 271 | 96.97 299 | 88.57 277 | 89.19 269 | 95.73 276 | 89.24 187 | 96.69 305 | 89.97 262 | 81.55 304 | 94.15 279 |
|
cl22 | | | 93.77 201 | 93.25 205 | 95.33 221 | 99.49 106 | 94.43 197 | 99.61 172 | 98.09 191 | 90.38 245 | 89.16 270 | 95.61 279 | 90.56 170 | 97.34 259 | 91.93 229 | 84.45 287 | 94.21 271 |
|
Baseline_NR-MVSNet | | | 90.33 277 | 89.51 275 | 92.81 303 | 92.84 328 | 89.95 299 | 99.77 132 | 93.94 367 | 84.69 328 | 89.04 271 | 95.66 278 | 81.66 251 | 96.52 310 | 90.99 244 | 76.98 342 | 91.97 345 |
|
FC-MVSNet-test | | | 93.81 199 | 93.15 206 | 95.80 211 | 94.30 297 | 96.20 149 | 99.42 200 | 98.89 43 | 92.33 199 | 89.03 272 | 97.27 231 | 87.39 204 | 96.83 299 | 93.20 215 | 86.48 272 | 94.36 257 |
|
QAPM | | | 95.40 163 | 94.17 178 | 99.10 72 | 96.92 236 | 97.71 86 | 99.40 201 | 98.68 58 | 89.31 259 | 88.94 273 | 98.89 169 | 82.48 243 | 99.96 58 | 93.12 220 | 99.83 85 | 99.62 133 |
|
RRT_MVS | | | 93.14 215 | 92.92 208 | 93.78 281 | 93.31 316 | 90.04 296 | 99.66 160 | 97.69 222 | 92.53 192 | 88.91 274 | 97.76 218 | 84.36 231 | 96.93 293 | 95.10 169 | 86.99 269 | 94.37 255 |
|
miper_ehance_all_eth | | | 93.16 213 | 92.60 215 | 94.82 239 | 97.57 209 | 93.56 217 | 99.50 190 | 97.07 286 | 88.75 272 | 88.85 275 | 95.52 285 | 90.97 163 | 96.74 302 | 90.77 250 | 84.45 287 | 94.17 273 |
|
AllTest | | | 92.48 232 | 91.64 235 | 95.00 231 | 99.01 124 | 88.43 316 | 98.94 258 | 96.82 315 | 86.50 303 | 88.71 276 | 98.47 197 | 74.73 312 | 99.88 90 | 85.39 304 | 96.18 186 | 96.71 231 |
|
TestCases | | | | | 95.00 231 | 99.01 124 | 88.43 316 | | 96.82 315 | 86.50 303 | 88.71 276 | 98.47 197 | 74.73 312 | 99.88 90 | 85.39 304 | 96.18 186 | 96.71 231 |
|
c3_l | | | 92.53 231 | 91.87 233 | 94.52 251 | 97.40 216 | 92.99 231 | 99.40 201 | 96.93 305 | 87.86 285 | 88.69 278 | 95.44 289 | 89.95 176 | 96.44 313 | 90.45 254 | 80.69 316 | 94.14 282 |
|
pmmvs4 | | | 92.10 241 | 91.07 247 | 95.18 226 | 92.82 330 | 94.96 187 | 99.48 194 | 96.83 313 | 87.45 290 | 88.66 279 | 96.56 256 | 83.78 236 | 96.83 299 | 89.29 266 | 84.77 285 | 93.75 312 |
|
PS-MVSNAJss | | | 93.64 206 | 93.31 203 | 94.61 245 | 92.11 337 | 92.19 250 | 99.12 232 | 97.38 258 | 92.51 194 | 88.45 280 | 96.99 242 | 91.20 157 | 97.29 267 | 94.36 190 | 87.71 263 | 94.36 257 |
|
UniMVSNet_ETH3D | | | 90.06 285 | 88.58 291 | 94.49 254 | 94.67 292 | 88.09 321 | 97.81 319 | 97.57 237 | 83.91 332 | 88.44 281 | 97.41 226 | 57.44 363 | 97.62 250 | 91.41 235 | 88.59 248 | 97.77 223 |
|
TranMVSNet+NR-MVSNet | | | 91.68 252 | 90.61 253 | 94.87 235 | 93.69 307 | 93.98 208 | 99.69 154 | 98.65 62 | 91.03 235 | 88.44 281 | 96.83 250 | 80.05 271 | 96.18 323 | 90.26 259 | 76.89 344 | 94.45 250 |
|
FMVSNet2 | | | 91.02 260 | 89.56 272 | 95.41 219 | 97.53 210 | 95.74 164 | 98.98 253 | 97.41 256 | 87.05 295 | 88.43 283 | 95.00 310 | 71.34 325 | 96.24 322 | 85.12 306 | 85.21 281 | 94.25 268 |
|
COLMAP_ROB |  | 90.47 14 | 92.18 239 | 91.49 241 | 94.25 263 | 99.00 126 | 88.04 322 | 98.42 299 | 96.70 322 | 82.30 341 | 88.43 283 | 99.01 151 | 76.97 290 | 99.85 99 | 86.11 301 | 96.50 182 | 94.86 238 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
3Dnovator+ | | 91.53 11 | 96.31 138 | 95.24 156 | 99.52 29 | 96.88 241 | 98.64 53 | 99.72 151 | 98.24 173 | 95.27 82 | 88.42 285 | 98.98 156 | 82.76 242 | 99.94 73 | 97.10 140 | 99.83 85 | 99.96 74 |
|
v148 | | | 90.70 267 | 89.63 270 | 93.92 277 | 92.97 326 | 90.97 276 | 99.75 140 | 96.89 308 | 87.51 288 | 88.27 286 | 95.01 308 | 81.67 250 | 97.04 285 | 87.40 287 | 77.17 341 | 93.75 312 |
|
DSMNet-mixed | | | 88.28 302 | 88.24 297 | 88.42 339 | 89.64 358 | 75.38 367 | 98.06 313 | 89.86 375 | 85.59 317 | 88.20 287 | 92.14 349 | 76.15 301 | 91.95 363 | 78.46 340 | 96.05 189 | 97.92 219 |
|
WR-MVS | | | 92.31 236 | 91.25 244 | 95.48 217 | 94.45 294 | 95.29 177 | 99.60 173 | 98.68 58 | 90.10 250 | 88.07 288 | 96.89 244 | 80.68 263 | 96.80 301 | 93.14 218 | 79.67 323 | 94.36 257 |
|
test0.0.03 1 | | | 93.86 196 | 93.61 189 | 94.64 244 | 95.02 287 | 92.18 251 | 99.93 67 | 98.58 75 | 94.07 129 | 87.96 289 | 98.50 192 | 93.90 98 | 94.96 343 | 81.33 328 | 93.17 224 | 96.78 230 |
|
XXY-MVS | | | 91.82 244 | 90.46 254 | 95.88 208 | 93.91 303 | 95.40 175 | 98.87 267 | 97.69 222 | 88.63 276 | 87.87 290 | 97.08 236 | 74.38 315 | 97.89 242 | 91.66 233 | 84.07 291 | 94.35 260 |
|
Patchmtry | | | 89.70 290 | 88.49 292 | 93.33 292 | 96.24 256 | 89.94 301 | 91.37 364 | 96.23 333 | 78.22 352 | 87.69 291 | 93.31 338 | 91.04 161 | 96.03 329 | 80.18 334 | 82.10 300 | 94.02 290 |
|
DIV-MVS_self_test | | | 92.32 235 | 91.60 236 | 94.47 255 | 97.31 222 | 92.74 235 | 99.58 175 | 96.75 319 | 86.99 298 | 87.64 292 | 95.54 283 | 89.55 180 | 96.50 311 | 88.58 272 | 82.44 298 | 94.17 273 |
|
D2MVS | | | 92.76 224 | 92.59 218 | 93.27 294 | 95.13 283 | 89.54 305 | 99.69 154 | 99.38 22 | 92.26 200 | 87.59 293 | 94.61 322 | 85.05 227 | 97.79 244 | 91.59 234 | 88.01 258 | 92.47 339 |
|
cl____ | | | 92.31 236 | 91.58 237 | 94.52 251 | 97.33 221 | 92.77 233 | 99.57 178 | 96.78 318 | 86.97 299 | 87.56 294 | 95.51 286 | 89.43 181 | 96.62 307 | 88.60 271 | 82.44 298 | 94.16 278 |
|
v8 | | | 90.54 272 | 89.17 280 | 94.66 243 | 93.43 312 | 93.40 224 | 99.20 227 | 96.94 304 | 85.76 313 | 87.56 294 | 94.51 323 | 81.96 248 | 97.19 272 | 84.94 308 | 78.25 330 | 93.38 324 |
|
miper_lstm_enhance | | | 91.81 245 | 91.39 243 | 93.06 300 | 97.34 219 | 89.18 308 | 99.38 206 | 96.79 317 | 86.70 302 | 87.47 296 | 95.22 303 | 90.00 175 | 95.86 333 | 88.26 276 | 81.37 306 | 94.15 279 |
|
anonymousdsp | | | 91.79 250 | 90.92 248 | 94.41 260 | 90.76 351 | 92.93 232 | 98.93 259 | 97.17 274 | 89.08 261 | 87.46 297 | 95.30 298 | 78.43 284 | 96.92 294 | 92.38 225 | 88.73 244 | 93.39 323 |
|
jajsoiax | | | 91.92 243 | 91.18 245 | 94.15 265 | 91.35 346 | 90.95 277 | 99.00 250 | 97.42 254 | 92.61 186 | 87.38 298 | 97.08 236 | 72.46 321 | 97.36 257 | 94.53 188 | 88.77 243 | 94.13 283 |
|
mvs_tets | | | 91.81 245 | 91.08 246 | 94.00 274 | 91.63 344 | 90.58 285 | 98.67 285 | 97.43 252 | 92.43 196 | 87.37 299 | 97.05 239 | 71.76 323 | 97.32 263 | 94.75 182 | 88.68 245 | 94.11 284 |
|
v10 | | | 90.25 280 | 88.82 287 | 94.57 249 | 93.53 310 | 93.43 222 | 99.08 237 | 96.87 310 | 85.00 323 | 87.34 300 | 94.51 323 | 80.93 260 | 97.02 290 | 82.85 320 | 79.23 324 | 93.26 326 |
|
pmmvs5 | | | 90.17 283 | 89.09 282 | 93.40 291 | 92.10 338 | 89.77 302 | 99.74 143 | 95.58 347 | 85.88 312 | 87.24 301 | 95.74 274 | 73.41 319 | 96.48 312 | 88.54 273 | 83.56 294 | 93.95 298 |
|
ACMP | | 92.05 9 | 92.74 225 | 92.42 222 | 93.73 282 | 95.91 264 | 88.72 311 | 99.81 121 | 97.53 242 | 94.13 125 | 87.00 302 | 98.23 202 | 74.07 316 | 98.47 194 | 96.22 155 | 88.86 242 | 93.99 295 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
MVS-HIRNet | | | 86.22 310 | 83.19 322 | 95.31 222 | 96.71 251 | 90.29 291 | 92.12 360 | 97.33 263 | 62.85 367 | 86.82 303 | 70.37 371 | 69.37 332 | 97.49 253 | 75.12 351 | 97.99 156 | 98.15 216 |
|
Anonymous20231211 | | | 89.86 287 | 88.44 293 | 94.13 267 | 98.93 132 | 90.68 281 | 98.54 291 | 98.26 171 | 76.28 355 | 86.73 304 | 95.54 283 | 70.60 329 | 97.56 251 | 90.82 249 | 80.27 320 | 94.15 279 |
|
v7n | | | 89.65 291 | 88.29 296 | 93.72 283 | 92.22 336 | 90.56 286 | 99.07 241 | 97.10 282 | 85.42 321 | 86.73 304 | 94.72 316 | 80.06 270 | 97.13 276 | 81.14 329 | 78.12 332 | 93.49 320 |
|
IterMVS-SCA-FT | | | 90.85 265 | 90.16 264 | 92.93 301 | 96.72 250 | 89.96 298 | 98.89 262 | 96.99 295 | 88.95 268 | 86.63 306 | 95.67 277 | 76.48 296 | 95.00 342 | 87.04 292 | 84.04 293 | 93.84 307 |
|
EU-MVSNet | | | 90.14 284 | 90.34 258 | 89.54 331 | 92.55 333 | 81.06 359 | 98.69 283 | 98.04 196 | 91.41 228 | 86.59 307 | 96.84 249 | 80.83 261 | 93.31 359 | 86.20 299 | 81.91 302 | 94.26 266 |
|
OpenMVS |  | 90.15 15 | 94.77 175 | 93.59 192 | 98.33 127 | 96.07 258 | 97.48 101 | 99.56 180 | 98.57 77 | 90.46 244 | 86.51 308 | 98.95 164 | 78.57 281 | 99.94 73 | 93.86 199 | 99.74 96 | 97.57 227 |
|
IterMVS | | | 90.91 262 | 90.17 263 | 93.12 297 | 96.78 248 | 90.42 290 | 98.89 262 | 97.05 290 | 89.03 263 | 86.49 309 | 95.42 290 | 76.59 295 | 95.02 341 | 87.22 290 | 84.09 290 | 93.93 300 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
WR-MVS_H | | | 91.30 254 | 90.35 257 | 94.15 265 | 94.17 299 | 92.62 242 | 99.17 230 | 98.94 37 | 88.87 270 | 86.48 310 | 94.46 327 | 84.36 231 | 96.61 308 | 88.19 277 | 78.51 329 | 93.21 328 |
|
MS-PatchMatch | | | 90.65 268 | 90.30 259 | 91.71 315 | 94.22 298 | 85.50 336 | 98.24 305 | 97.70 221 | 88.67 274 | 86.42 311 | 96.37 260 | 67.82 339 | 98.03 234 | 83.62 316 | 99.62 104 | 91.60 347 |
|
CP-MVSNet | | | 91.23 257 | 90.22 261 | 94.26 262 | 93.96 302 | 92.39 246 | 99.09 235 | 98.57 77 | 88.95 268 | 86.42 311 | 96.57 255 | 79.19 276 | 96.37 315 | 90.29 258 | 78.95 326 | 94.02 290 |
|
test_part1 | | | 92.15 240 | 90.72 250 | 96.44 194 | 98.87 140 | 97.46 103 | 98.99 251 | 98.26 171 | 85.89 310 | 86.34 313 | 96.34 261 | 81.71 249 | 97.48 254 | 91.06 241 | 78.99 325 | 94.37 255 |
|
LF4IMVS | | | 89.25 297 | 88.85 286 | 90.45 325 | 92.81 331 | 81.19 358 | 98.12 310 | 94.79 360 | 91.44 225 | 86.29 314 | 97.11 234 | 65.30 349 | 98.11 229 | 88.53 274 | 85.25 280 | 92.07 342 |
|
PVSNet_0 | | 88.03 19 | 91.80 248 | 90.27 260 | 96.38 198 | 98.27 169 | 90.46 288 | 99.94 61 | 99.61 12 | 93.99 135 | 86.26 315 | 97.39 228 | 71.13 328 | 99.89 84 | 98.77 78 | 67.05 362 | 98.79 208 |
|
PS-CasMVS | | | 90.63 270 | 89.51 275 | 93.99 275 | 93.83 304 | 91.70 266 | 98.98 253 | 98.52 92 | 88.48 278 | 86.15 316 | 96.53 257 | 75.46 304 | 96.31 318 | 88.83 270 | 78.86 328 | 93.95 298 |
|
FMVSNet1 | | | 88.50 300 | 86.64 306 | 94.08 268 | 95.62 279 | 91.97 253 | 98.43 296 | 96.95 300 | 83.00 336 | 86.08 317 | 94.72 316 | 59.09 361 | 96.11 324 | 81.82 327 | 84.07 291 | 94.17 273 |
|
PEN-MVS | | | 90.19 282 | 89.06 283 | 93.57 289 | 93.06 324 | 90.90 278 | 99.06 242 | 98.47 105 | 88.11 282 | 85.91 318 | 96.30 262 | 76.67 293 | 95.94 332 | 87.07 291 | 76.91 343 | 93.89 303 |
|
ppachtmachnet_test | | | 89.58 292 | 88.35 294 | 93.25 295 | 92.40 334 | 90.44 289 | 99.33 212 | 96.73 320 | 85.49 319 | 85.90 319 | 95.77 273 | 81.09 258 | 96.00 331 | 76.00 350 | 82.49 297 | 93.30 325 |
|
OurMVSNet-221017-0 | | | 89.81 288 | 89.48 277 | 90.83 321 | 91.64 343 | 81.21 357 | 98.17 309 | 95.38 352 | 91.48 223 | 85.65 320 | 97.31 229 | 72.66 320 | 97.29 267 | 88.15 278 | 84.83 284 | 93.97 297 |
|
our_test_3 | | | 90.39 274 | 89.48 277 | 93.12 297 | 92.40 334 | 89.57 304 | 99.33 212 | 96.35 332 | 87.84 286 | 85.30 321 | 94.99 311 | 84.14 234 | 96.09 327 | 80.38 332 | 84.56 286 | 93.71 317 |
|
testgi | | | 89.01 298 | 88.04 299 | 91.90 313 | 93.49 311 | 84.89 340 | 99.73 148 | 95.66 345 | 93.89 143 | 85.14 322 | 98.17 203 | 59.68 360 | 94.66 347 | 77.73 343 | 88.88 240 | 96.16 236 |
|
DTE-MVSNet | | | 89.40 293 | 88.24 297 | 92.88 302 | 92.66 332 | 89.95 299 | 99.10 234 | 98.22 176 | 87.29 292 | 85.12 323 | 96.22 264 | 76.27 299 | 95.30 340 | 83.56 317 | 75.74 347 | 93.41 321 |
|
FMVSNet5 | | | 88.32 301 | 87.47 303 | 90.88 319 | 96.90 240 | 88.39 318 | 97.28 325 | 95.68 344 | 82.60 340 | 84.67 324 | 92.40 347 | 79.83 272 | 91.16 365 | 76.39 349 | 81.51 305 | 93.09 329 |
|
tfpnnormal | | | 89.29 295 | 87.61 302 | 94.34 261 | 94.35 296 | 94.13 203 | 98.95 257 | 98.94 37 | 83.94 330 | 84.47 325 | 95.51 286 | 74.84 311 | 97.39 256 | 77.05 347 | 80.41 317 | 91.48 349 |
|
MVP-Stereo | | | 90.93 261 | 90.45 256 | 92.37 307 | 91.25 348 | 88.76 310 | 98.05 314 | 96.17 335 | 87.27 293 | 84.04 326 | 95.30 298 | 78.46 283 | 97.27 269 | 83.78 315 | 99.70 100 | 91.09 350 |
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
LTVRE_ROB | | 88.28 18 | 90.29 279 | 89.05 284 | 94.02 271 | 95.08 285 | 90.15 294 | 97.19 327 | 97.43 252 | 84.91 326 | 83.99 327 | 97.06 238 | 74.00 317 | 98.28 219 | 84.08 311 | 87.71 263 | 93.62 318 |
Andreas Kuhn, Heiko Hirschmüller, Daniel Scharstein, Helmut Mayer: A TV Prior for High-Quality Scalable Multi-View Stereo Reconstruction. International Journal of Computer Vision 2016 |
pm-mvs1 | | | 89.36 294 | 87.81 301 | 94.01 272 | 93.40 314 | 91.93 256 | 98.62 288 | 96.48 329 | 86.25 307 | 83.86 328 | 96.14 266 | 73.68 318 | 97.04 285 | 86.16 300 | 75.73 348 | 93.04 331 |
|
USDC | | | 90.00 286 | 88.96 285 | 93.10 299 | 94.81 289 | 88.16 320 | 98.71 281 | 95.54 348 | 93.66 150 | 83.75 329 | 97.20 232 | 65.58 346 | 98.31 216 | 83.96 314 | 87.49 267 | 92.85 334 |
|
CL-MVSNet_self_test | | | 84.50 321 | 83.15 323 | 88.53 338 | 86.00 366 | 81.79 354 | 98.82 272 | 97.35 260 | 85.12 322 | 83.62 330 | 90.91 354 | 76.66 294 | 91.40 364 | 69.53 359 | 60.36 367 | 92.40 340 |
|
ACMH+ | | 89.98 16 | 90.35 276 | 89.54 273 | 92.78 304 | 95.99 261 | 86.12 332 | 98.81 273 | 97.18 273 | 89.38 258 | 83.14 331 | 97.76 218 | 68.42 337 | 98.43 199 | 89.11 268 | 86.05 274 | 93.78 311 |
|
Anonymous20231206 | | | 86.32 309 | 85.42 311 | 89.02 334 | 89.11 360 | 80.53 363 | 99.05 246 | 95.28 353 | 85.43 320 | 82.82 332 | 93.92 331 | 74.40 314 | 93.44 358 | 66.99 363 | 81.83 303 | 93.08 330 |
|
KD-MVS_self_test | | | 83.59 326 | 82.06 326 | 88.20 340 | 86.93 364 | 80.70 361 | 97.21 326 | 96.38 331 | 82.87 337 | 82.49 333 | 88.97 357 | 67.63 340 | 92.32 361 | 73.75 353 | 62.30 366 | 91.58 348 |
|
SixPastTwentyTwo | | | 88.73 299 | 88.01 300 | 90.88 319 | 91.85 341 | 82.24 350 | 98.22 307 | 95.18 358 | 88.97 266 | 82.26 334 | 96.89 244 | 71.75 324 | 96.67 306 | 84.00 312 | 82.98 295 | 93.72 316 |
|
KD-MVS_2432*1600 | | | 88.00 304 | 86.10 308 | 93.70 286 | 96.91 237 | 94.04 205 | 97.17 328 | 97.12 280 | 84.93 324 | 81.96 335 | 92.41 345 | 92.48 136 | 94.51 348 | 79.23 335 | 52.68 370 | 92.56 336 |
|
miper_refine_blended | | | 88.00 304 | 86.10 308 | 93.70 286 | 96.91 237 | 94.04 205 | 97.17 328 | 97.12 280 | 84.93 324 | 81.96 335 | 92.41 345 | 92.48 136 | 94.51 348 | 79.23 335 | 52.68 370 | 92.56 336 |
|
TinyColmap | | | 87.87 306 | 86.51 307 | 91.94 312 | 95.05 286 | 85.57 335 | 97.65 321 | 94.08 365 | 84.40 329 | 81.82 337 | 96.85 247 | 62.14 356 | 98.33 214 | 80.25 333 | 86.37 273 | 91.91 346 |
|
ACMH | | 89.72 17 | 90.64 269 | 89.63 270 | 93.66 288 | 95.64 277 | 88.64 314 | 98.55 289 | 97.45 250 | 89.03 263 | 81.62 338 | 97.61 221 | 69.75 331 | 98.41 201 | 89.37 265 | 87.62 265 | 93.92 301 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
Anonymous20240521 | | | 85.15 317 | 83.81 318 | 89.16 333 | 88.32 361 | 82.69 346 | 98.80 275 | 95.74 342 | 79.72 348 | 81.53 339 | 90.99 352 | 65.38 348 | 94.16 350 | 72.69 354 | 81.11 310 | 90.63 355 |
|
pmmvs6 | | | 85.69 311 | 83.84 317 | 91.26 318 | 90.00 357 | 84.41 342 | 97.82 318 | 96.15 336 | 75.86 357 | 81.29 340 | 95.39 293 | 61.21 358 | 96.87 297 | 83.52 318 | 73.29 351 | 92.50 338 |
|
TransMVSNet (Re) | | | 87.25 307 | 85.28 312 | 93.16 296 | 93.56 309 | 91.03 275 | 98.54 291 | 94.05 366 | 83.69 334 | 81.09 341 | 96.16 265 | 75.32 305 | 96.40 314 | 76.69 348 | 68.41 359 | 92.06 343 |
|
test_method | | | 80.79 329 | 79.70 332 | 84.08 346 | 92.83 329 | 67.06 371 | 99.51 188 | 95.42 349 | 54.34 369 | 81.07 342 | 93.53 335 | 44.48 372 | 92.22 362 | 78.90 339 | 77.23 340 | 92.94 332 |
|
NR-MVSNet | | | 91.56 253 | 90.22 261 | 95.60 212 | 94.05 300 | 95.76 163 | 98.25 304 | 98.70 56 | 91.16 232 | 80.78 343 | 96.64 253 | 83.23 241 | 96.57 309 | 91.41 235 | 77.73 335 | 94.46 245 |
|
LCM-MVSNet-Re | | | 92.31 236 | 92.60 215 | 91.43 316 | 97.53 210 | 79.27 365 | 99.02 249 | 91.83 372 | 92.07 206 | 80.31 344 | 94.38 328 | 83.50 238 | 95.48 335 | 97.22 137 | 97.58 161 | 99.54 151 |
|
TDRefinement | | | 84.76 318 | 82.56 325 | 91.38 317 | 74.58 374 | 84.80 341 | 97.36 324 | 94.56 363 | 84.73 327 | 80.21 345 | 96.12 268 | 63.56 353 | 98.39 205 | 87.92 281 | 63.97 363 | 90.95 353 |
|
N_pmnet | | | 80.06 332 | 80.78 330 | 77.89 350 | 91.94 339 | 45.28 381 | 98.80 275 | 56.82 384 | 78.10 353 | 80.08 346 | 93.33 336 | 77.03 289 | 95.76 334 | 68.14 362 | 82.81 296 | 92.64 335 |
|
test_0402 | | | 85.58 312 | 83.94 316 | 90.50 323 | 93.81 305 | 85.04 339 | 98.55 289 | 95.20 356 | 76.01 356 | 79.72 347 | 95.13 304 | 64.15 352 | 96.26 321 | 66.04 366 | 86.88 270 | 90.21 358 |
|
test20.03 | | | 84.72 320 | 83.99 314 | 86.91 342 | 88.19 363 | 80.62 362 | 98.88 264 | 95.94 339 | 88.36 280 | 78.87 348 | 94.62 321 | 68.75 334 | 89.11 369 | 66.52 364 | 75.82 346 | 91.00 351 |
|
pmmvs3 | | | 80.27 331 | 77.77 335 | 87.76 341 | 80.32 372 | 82.43 349 | 98.23 306 | 91.97 371 | 72.74 364 | 78.75 349 | 87.97 359 | 57.30 364 | 90.99 366 | 70.31 357 | 62.37 365 | 89.87 359 |
|
MIMVSNet1 | | | 82.58 327 | 80.51 331 | 88.78 336 | 86.68 365 | 84.20 343 | 96.65 335 | 95.41 350 | 78.75 351 | 78.59 350 | 92.44 344 | 51.88 368 | 89.76 368 | 65.26 367 | 78.95 326 | 92.38 341 |
|
DeepMVS_CX |  | | | | 82.92 349 | 95.98 263 | 58.66 375 | | 96.01 338 | 92.72 178 | 78.34 351 | 95.51 286 | 58.29 362 | 98.08 230 | 82.57 321 | 85.29 279 | 92.03 344 |
|
Patchmatch-RL test | | | 86.90 308 | 85.98 310 | 89.67 330 | 84.45 368 | 75.59 366 | 89.71 366 | 92.43 370 | 86.89 300 | 77.83 352 | 90.94 353 | 94.22 87 | 93.63 356 | 87.75 283 | 69.61 354 | 99.79 106 |
|
lessismore_v0 | | | | | 90.53 322 | 90.58 352 | 80.90 360 | | 95.80 341 | | 77.01 353 | 95.84 271 | 66.15 345 | 96.95 291 | 83.03 319 | 75.05 349 | 93.74 315 |
|
K. test v3 | | | 88.05 303 | 87.24 305 | 90.47 324 | 91.82 342 | 82.23 351 | 98.96 256 | 97.42 254 | 89.05 262 | 76.93 354 | 95.60 280 | 68.49 336 | 95.42 336 | 85.87 303 | 81.01 313 | 93.75 312 |
|
ambc | | | | | 83.23 348 | 77.17 373 | 62.61 372 | 87.38 368 | 94.55 364 | | 76.72 355 | 86.65 363 | 30.16 374 | 96.36 316 | 84.85 309 | 69.86 353 | 90.73 354 |
|
PM-MVS | | | 80.47 330 | 78.88 334 | 85.26 345 | 83.79 370 | 72.22 368 | 95.89 347 | 91.08 373 | 85.71 316 | 76.56 356 | 88.30 358 | 36.64 373 | 93.90 353 | 82.39 322 | 69.57 355 | 89.66 361 |
|
OpenMVS_ROB |  | 79.82 20 | 83.77 325 | 81.68 328 | 90.03 328 | 88.30 362 | 82.82 345 | 98.46 294 | 95.22 355 | 73.92 363 | 76.00 357 | 91.29 351 | 55.00 365 | 96.94 292 | 68.40 361 | 88.51 250 | 90.34 356 |
|
UnsupCasMVSNet_eth | | | 85.52 313 | 83.99 314 | 90.10 327 | 89.36 359 | 83.51 344 | 96.65 335 | 97.99 198 | 89.14 260 | 75.89 358 | 93.83 332 | 63.25 354 | 93.92 352 | 81.92 326 | 67.90 361 | 92.88 333 |
|
new_pmnet | | | 84.49 322 | 82.92 324 | 89.21 332 | 90.03 356 | 82.60 347 | 96.89 334 | 95.62 346 | 80.59 346 | 75.77 359 | 89.17 356 | 65.04 350 | 94.79 346 | 72.12 355 | 81.02 312 | 90.23 357 |
|
EG-PatchMatch MVS | | | 85.35 316 | 83.81 318 | 89.99 329 | 90.39 353 | 81.89 353 | 98.21 308 | 96.09 337 | 81.78 343 | 74.73 360 | 93.72 334 | 51.56 369 | 97.12 278 | 79.16 338 | 88.61 246 | 90.96 352 |
|
pmmvs-eth3d | | | 84.03 324 | 81.97 327 | 90.20 326 | 84.15 369 | 87.09 327 | 98.10 312 | 94.73 362 | 83.05 335 | 74.10 361 | 87.77 360 | 65.56 347 | 94.01 351 | 81.08 330 | 69.24 356 | 89.49 362 |
|
new-patchmatchnet | | | 81.19 328 | 79.34 333 | 86.76 343 | 82.86 371 | 80.36 364 | 97.92 316 | 95.27 354 | 82.09 342 | 72.02 362 | 86.87 362 | 62.81 355 | 90.74 367 | 71.10 356 | 63.08 364 | 89.19 364 |
|
ET-MVSNet_ETH3D | | | 94.37 188 | 93.28 204 | 97.64 153 | 98.30 165 | 97.99 77 | 99.99 3 | 97.61 232 | 94.35 115 | 71.57 363 | 99.45 121 | 96.23 31 | 95.34 338 | 96.91 148 | 85.14 282 | 99.59 139 |
|
UnsupCasMVSNet_bld | | | 79.97 333 | 77.03 336 | 88.78 336 | 85.62 367 | 81.98 352 | 93.66 355 | 97.35 260 | 75.51 360 | 70.79 364 | 83.05 366 | 48.70 371 | 94.91 344 | 78.31 341 | 60.29 368 | 89.46 363 |
|
CMPMVS |  | 61.59 21 | 84.75 319 | 85.14 313 | 83.57 347 | 90.32 354 | 62.54 373 | 96.98 332 | 97.59 236 | 74.33 362 | 69.95 365 | 96.66 251 | 64.17 351 | 98.32 215 | 87.88 282 | 88.41 251 | 89.84 360 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
testmvs | | | 40.60 345 | 44.45 348 | 29.05 362 | 19.49 386 | 14.11 387 | 99.68 156 | 18.47 385 | 20.74 378 | 64.59 366 | 98.48 196 | 10.95 383 | 17.09 382 | 56.66 372 | 11.01 378 | 55.94 375 |
|
LCM-MVSNet | | | 67.77 336 | 64.73 339 | 76.87 351 | 62.95 380 | 56.25 377 | 89.37 367 | 93.74 369 | 44.53 372 | 61.99 367 | 80.74 367 | 20.42 380 | 86.53 371 | 69.37 360 | 59.50 369 | 87.84 365 |
|
PMMVS2 | | | 67.15 337 | 64.15 340 | 76.14 352 | 70.56 377 | 62.07 374 | 93.89 353 | 87.52 379 | 58.09 368 | 60.02 368 | 78.32 368 | 22.38 379 | 84.54 372 | 59.56 370 | 47.03 372 | 81.80 368 |
|
Gipuma |  | | 66.95 338 | 65.00 338 | 72.79 353 | 91.52 345 | 67.96 370 | 66.16 373 | 95.15 359 | 47.89 371 | 58.54 369 | 67.99 373 | 29.74 375 | 87.54 370 | 50.20 373 | 77.83 334 | 62.87 373 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
YYNet1 | | | 85.50 315 | 83.33 320 | 92.00 311 | 90.89 350 | 88.38 319 | 99.22 226 | 96.55 326 | 79.60 350 | 57.26 370 | 92.72 341 | 79.09 278 | 93.78 355 | 77.25 345 | 77.37 339 | 93.84 307 |
|
MDA-MVSNet_test_wron | | | 85.51 314 | 83.32 321 | 92.10 310 | 90.96 349 | 88.58 315 | 99.20 227 | 96.52 327 | 79.70 349 | 57.12 371 | 92.69 343 | 79.11 277 | 93.86 354 | 77.10 346 | 77.46 338 | 93.86 306 |
|
MDA-MVSNet-bldmvs | | | 84.09 323 | 81.52 329 | 91.81 314 | 91.32 347 | 88.00 323 | 98.67 285 | 95.92 340 | 80.22 347 | 55.60 372 | 93.32 337 | 68.29 338 | 93.60 357 | 73.76 352 | 76.61 345 | 93.82 309 |
|
FPMVS | | | 68.72 335 | 68.72 337 | 68.71 355 | 65.95 378 | 44.27 383 | 95.97 346 | 94.74 361 | 51.13 370 | 53.26 373 | 90.50 355 | 25.11 378 | 83.00 373 | 60.80 369 | 80.97 314 | 78.87 369 |
|
test123 | | | 37.68 346 | 39.14 349 | 33.31 361 | 19.94 385 | 24.83 386 | 98.36 300 | 9.75 386 | 15.53 379 | 51.31 374 | 87.14 361 | 19.62 381 | 17.74 381 | 47.10 374 | 3.47 380 | 57.36 374 |
|
tmp_tt | | | 65.23 339 | 62.94 342 | 72.13 354 | 44.90 383 | 50.03 379 | 81.05 370 | 89.42 378 | 38.45 373 | 48.51 375 | 99.90 19 | 54.09 366 | 78.70 375 | 91.84 232 | 18.26 377 | 87.64 366 |
|
E-PMN | | | 52.30 342 | 52.18 344 | 52.67 359 | 71.51 375 | 45.40 380 | 93.62 356 | 76.60 382 | 36.01 375 | 43.50 376 | 64.13 375 | 27.11 377 | 67.31 378 | 31.06 378 | 26.06 374 | 45.30 377 |
|
EMVS | | | 51.44 344 | 51.22 346 | 52.11 360 | 70.71 376 | 44.97 382 | 94.04 352 | 75.66 383 | 35.34 377 | 42.40 377 | 61.56 378 | 28.93 376 | 65.87 379 | 27.64 379 | 24.73 375 | 45.49 376 |
|
MVE |  | 53.74 22 | 51.54 343 | 47.86 347 | 62.60 357 | 59.56 381 | 50.93 378 | 79.41 371 | 77.69 381 | 35.69 376 | 36.27 378 | 61.76 377 | 5.79 386 | 69.63 376 | 37.97 377 | 36.61 373 | 67.24 371 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
ANet_high | | | 56.10 340 | 52.24 343 | 67.66 356 | 49.27 382 | 56.82 376 | 83.94 369 | 82.02 380 | 70.47 365 | 33.28 379 | 64.54 374 | 17.23 382 | 69.16 377 | 45.59 375 | 23.85 376 | 77.02 370 |
|
PMVS |  | 49.05 23 | 53.75 341 | 51.34 345 | 60.97 358 | 40.80 384 | 34.68 384 | 74.82 372 | 89.62 377 | 37.55 374 | 28.67 380 | 72.12 370 | 7.09 384 | 81.63 374 | 43.17 376 | 68.21 360 | 66.59 372 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
wuyk23d | | | 20.37 348 | 20.84 351 | 18.99 363 | 65.34 379 | 27.73 385 | 50.43 374 | 7.67 387 | 9.50 380 | 8.01 381 | 6.34 381 | 6.13 385 | 26.24 380 | 23.40 380 | 10.69 379 | 2.99 378 |
|
EGC-MVSNET | | | 69.38 334 | 63.76 341 | 86.26 344 | 90.32 354 | 81.66 356 | 96.24 341 | 93.85 368 | 0.99 381 | 3.22 382 | 92.33 348 | 52.44 367 | 92.92 360 | 59.53 371 | 84.90 283 | 84.21 367 |
|
test_blank | | | 0.00 351 | 0.00 354 | 0.00 364 | 0.00 387 | 0.00 388 | 0.00 375 | 0.00 388 | 0.00 382 | 0.00 383 | 0.02 382 | 0.00 387 | 0.00 383 | 0.00 381 | 0.00 381 | 0.00 379 |
|
uanet_test | | | 0.00 351 | 0.00 354 | 0.00 364 | 0.00 387 | 0.00 388 | 0.00 375 | 0.00 388 | 0.00 382 | 0.00 383 | 0.00 383 | 0.00 387 | 0.00 383 | 0.00 381 | 0.00 381 | 0.00 379 |
|
DCPMVS | | | 0.00 351 | 0.00 354 | 0.00 364 | 0.00 387 | 0.00 388 | 0.00 375 | 0.00 388 | 0.00 382 | 0.00 383 | 0.00 383 | 0.00 387 | 0.00 383 | 0.00 381 | 0.00 381 | 0.00 379 |
|
cdsmvs_eth3d_5k | | | 23.43 347 | 31.24 350 | 0.00 364 | 0.00 387 | 0.00 388 | 0.00 375 | 98.09 191 | 0.00 382 | 0.00 383 | 99.67 102 | 83.37 239 | 0.00 383 | 0.00 381 | 0.00 381 | 0.00 379 |
|
pcd_1.5k_mvsjas | | | 7.60 350 | 10.13 353 | 0.00 364 | 0.00 387 | 0.00 388 | 0.00 375 | 0.00 388 | 0.00 382 | 0.00 383 | 0.00 383 | 91.20 157 | 0.00 383 | 0.00 381 | 0.00 381 | 0.00 379 |
|
sosnet-low-res | | | 0.00 351 | 0.00 354 | 0.00 364 | 0.00 387 | 0.00 388 | 0.00 375 | 0.00 388 | 0.00 382 | 0.00 383 | 0.00 383 | 0.00 387 | 0.00 383 | 0.00 381 | 0.00 381 | 0.00 379 |
|
sosnet | | | 0.00 351 | 0.00 354 | 0.00 364 | 0.00 387 | 0.00 388 | 0.00 375 | 0.00 388 | 0.00 382 | 0.00 383 | 0.00 383 | 0.00 387 | 0.00 383 | 0.00 381 | 0.00 381 | 0.00 379 |
|
uncertanet | | | 0.00 351 | 0.00 354 | 0.00 364 | 0.00 387 | 0.00 388 | 0.00 375 | 0.00 388 | 0.00 382 | 0.00 383 | 0.00 383 | 0.00 387 | 0.00 383 | 0.00 381 | 0.00 381 | 0.00 379 |
|
Regformer | | | 0.00 351 | 0.00 354 | 0.00 364 | 0.00 387 | 0.00 388 | 0.00 375 | 0.00 388 | 0.00 382 | 0.00 383 | 0.00 383 | 0.00 387 | 0.00 383 | 0.00 381 | 0.00 381 | 0.00 379 |
|
ab-mvs-re | | | 8.28 349 | 11.04 352 | 0.00 364 | 0.00 387 | 0.00 388 | 0.00 375 | 0.00 388 | 0.00 382 | 0.00 383 | 99.40 124 | 0.00 387 | 0.00 383 | 0.00 381 | 0.00 381 | 0.00 379 |
|
uanet | | | 0.00 351 | 0.00 354 | 0.00 364 | 0.00 387 | 0.00 388 | 0.00 375 | 0.00 388 | 0.00 382 | 0.00 383 | 0.00 383 | 0.00 387 | 0.00 383 | 0.00 381 | 0.00 381 | 0.00 379 |
|
MSC_two_6792asdad | | | | | 99.93 2 | 99.91 44 | 99.80 2 | | 98.41 136 | | | | | 100.00 1 | 99.96 9 | 100.00 1 | 100.00 1 |
|
No_MVS | | | | | 99.93 2 | 99.91 44 | 99.80 2 | | 98.41 136 | | | | | 100.00 1 | 99.96 9 | 100.00 1 | 100.00 1 |
|
eth-test2 | | | | | | 0.00 387 | | | | | | | | | | | |
|
eth-test | | | | | | 0.00 387 | | | | | | | | | | | |
|
OPU-MVS | | | | | 99.93 2 | 99.89 50 | 99.80 2 | 99.96 25 | | | | 99.80 60 | 97.44 14 | 100.00 1 | 100.00 1 | 99.98 35 | 100.00 1 |
|
save fliter | | | | | | 99.82 70 | 98.79 37 | 99.96 25 | 98.40 140 | 97.66 10 | | | | | | | |
|
test_0728_SECOND | | | | | 99.82 7 | 99.94 14 | 99.47 7 | 99.95 43 | 98.43 120 | | | | | 100.00 1 | 99.99 5 | 100.00 1 | 100.00 1 |
|
GSMVS | | | | | | | | | | | | | | | | | 99.59 139 |
|
sam_mvs1 | | | | | | | | | | | | | 94.72 67 | | | | 99.59 139 |
|
sam_mvs | | | | | | | | | | | | | 94.25 86 | | | | |
|
MTGPA |  | | | | | | | | 98.28 167 | | | | | | | | |
|
test_post1 | | | | | | | | 95.78 348 | | | | 59.23 379 | 93.20 118 | 97.74 246 | 91.06 241 | | |
|
test_post | | | | | | | | | | | | 63.35 376 | 94.43 72 | 98.13 228 | | | |
|
patchmatchnet-post | | | | | | | | | | | | 91.70 350 | 95.12 52 | 97.95 239 | | | |
|
MTMP | | | | | | | | 99.87 93 | 96.49 328 | | | | | | | | |
|
gm-plane-assit | | | | | | 96.97 235 | 93.76 213 | | | 91.47 224 | | 98.96 160 | | 98.79 176 | 94.92 174 | | |
|
test9_res | | | | | | | | | | | | | | | 99.71 35 | 99.99 22 | 100.00 1 |
|
agg_prior2 | | | | | | | | | | | | | | | 99.48 42 | 100.00 1 | 100.00 1 |
|
test_prior4 | | | | | | | 98.05 74 | 99.94 61 | | | | | | | | | |
|
test_prior | | | | | 99.43 38 | 99.94 14 | 98.49 61 | | 98.65 62 | | | | | 99.80 111 | | | 99.99 24 |
|
新几何2 | | | | | | | | 99.40 201 | | | | | | | | | |
|
旧先验1 | | | | | | 99.76 79 | 97.52 95 | | 98.64 65 | | | 99.85 35 | 95.63 43 | | | 99.94 61 | 99.99 24 |
|
无先验 | | | | | | | | 99.49 192 | 98.71 55 | 93.46 155 | | | | 100.00 1 | 94.36 190 | | 99.99 24 |
|
原ACMM2 | | | | | | | | 99.90 80 | | | | | | | | | |
|
testdata2 | | | | | | | | | | | | | | 99.99 40 | 90.54 253 | | |
|
segment_acmp | | | | | | | | | | | | | 96.68 26 | | | | |
|
testdata1 | | | | | | | | 99.28 221 | | 96.35 52 | | | | | | | |
|
plane_prior7 | | | | | | 95.71 274 | 91.59 270 | | | | | | | | | | |
|
plane_prior6 | | | | | | 95.76 269 | 91.72 265 | | | | | | 80.47 268 | | | | |
|
plane_prior5 | | | | | | | | | 97.87 211 | | | | | 98.37 211 | 97.79 122 | 89.55 233 | 94.52 241 |
|
plane_prior4 | | | | | | | | | | | | 98.59 187 | | | | | |
|
plane_prior2 | | | | | | | | 99.84 112 | | 96.38 48 | | | | | | | |
|
plane_prior1 | | | | | | 95.73 271 | | | | | | | | | | | |
|
plane_prior | | | | | | | 91.74 262 | 99.86 105 | | 96.76 36 | | | | | | 89.59 232 | |
|
n2 | | | | | | | | | 0.00 388 | | | | | | | | |
|
nn | | | | | | | | | 0.00 388 | | | | | | | | |
|
door-mid | | | | | | | | | 89.69 376 | | | | | | | | |
|
test11 | | | | | | | | | 98.44 112 | | | | | | | | |
|
door | | | | | | | | | 90.31 374 | | | | | | | | |
|
HQP5-MVS | | | | | | | 91.85 258 | | | | | | | | | | |
|
BP-MVS | | | | | | | | | | | | | | | 97.92 117 | | |
|
HQP3-MVS | | | | | | | | | 97.89 209 | | | | | | | 89.60 230 | |
|
HQP2-MVS | | | | | | | | | | | | | 80.65 264 | | | | |
|
NP-MVS | | | | | | 95.77 268 | 91.79 260 | | | | | 98.65 183 | | | | | |
|
ACMMP++_ref | | | | | | | | | | | | | | | | 87.04 268 | |
|
ACMMP++ | | | | | | | | | | | | | | | | 88.23 254 | |
|
Test By Simon | | | | | | | | | | | | | 92.82 128 | | | | |
|