SED-MVS | | | 99.61 2 | 99.52 7 | 99.88 6 | 99.84 33 | 99.90 2 | 99.60 77 | 99.48 146 | 99.08 16 | 99.91 1 | 99.81 66 | 99.20 7 | 99.96 20 | 98.91 75 | 99.85 59 | 99.79 61 |
|
test_241102_ONE | | | | | | 99.84 33 | 99.90 2 | | 99.48 146 | 99.07 18 | 99.91 1 | 99.74 123 | 99.20 7 | 99.76 183 | | | |
|
EI-MVSNet-UG-set | | | 99.58 5 | 99.57 2 | 99.64 80 | 99.78 47 | 99.14 133 | 99.60 77 | 99.45 186 | 99.01 23 | 99.90 3 | 99.83 46 | 98.98 27 | 99.93 73 | 99.59 5 | 99.95 7 | 99.86 14 |
|
EI-MVSNet-Vis-set | | | 99.58 5 | 99.56 4 | 99.64 80 | 99.78 47 | 99.15 132 | 99.61 76 | 99.45 186 | 99.01 23 | 99.89 4 | 99.82 53 | 99.01 19 | 99.92 84 | 99.56 8 | 99.95 7 | 99.85 17 |
|
DVP-MVS++ | | | 99.59 3 | 99.50 9 | 99.88 6 | 99.51 160 | 99.88 8 | 99.87 6 | 99.51 105 | 98.99 30 | 99.88 5 | 99.81 66 | 99.27 5 | 99.96 20 | 98.85 89 | 99.80 88 | 99.81 45 |
|
test_241102_TWO | | | | | | | | | 99.48 146 | 99.08 16 | 99.88 5 | 99.81 66 | 98.94 35 | 99.96 20 | 98.91 75 | 99.84 66 | 99.88 8 |
|
DPE-MVS |  | | 99.46 26 | 99.32 35 | 99.91 2 | 99.78 47 | 99.88 8 | 99.36 202 | 99.51 105 | 98.73 60 | 99.88 5 | 99.84 42 | 98.72 65 | 99.96 20 | 98.16 176 | 99.87 41 | 99.88 8 |
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025 |
Regformer-4 | | | 99.59 3 | 99.54 5 | 99.73 61 | 99.76 56 | 99.41 101 | 99.58 92 | 99.49 133 | 99.02 20 | 99.88 5 | 99.80 82 | 99.00 25 | 99.94 58 | 99.45 21 | 99.92 12 | 99.84 21 |
|
SD-MVS | | | 99.41 46 | 99.52 7 | 99.05 170 | 99.74 75 | 99.68 54 | 99.46 158 | 99.52 92 | 99.11 11 | 99.88 5 | 99.91 8 | 99.43 1 | 97.70 358 | 98.72 110 | 99.93 11 | 99.77 71 |
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 |
APDe-MVS | | | 99.66 1 | 99.57 2 | 99.92 1 | 99.77 52 | 99.89 4 | 99.75 32 | 99.56 58 | 99.02 20 | 99.88 5 | 99.85 33 | 99.18 10 | 99.96 20 | 99.22 43 | 99.92 12 | 99.90 1 |
|
Regformer-3 | | | 99.57 8 | 99.53 6 | 99.68 68 | 99.76 56 | 99.29 114 | 99.58 92 | 99.44 195 | 99.01 23 | 99.87 11 | 99.80 82 | 98.97 28 | 99.91 95 | 99.44 23 | 99.92 12 | 99.83 32 |
|
test0726 | | | | | | 99.85 26 | 99.89 4 | 99.62 70 | 99.50 125 | 99.10 12 | 99.86 12 | 99.82 53 | 98.94 35 | | | | |
|
Vis-MVSNet |  | | 99.12 89 | 98.97 95 | 99.56 94 | 99.78 47 | 99.10 138 | 99.68 46 | 99.66 27 | 98.49 76 | 99.86 12 | 99.87 24 | 94.77 217 | 99.84 141 | 99.19 46 | 99.41 142 | 99.74 82 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
PC_three_1452 | | | | | | | | | | 98.18 111 | 99.84 14 | 99.70 139 | 99.31 3 | 98.52 343 | 98.30 166 | 99.80 88 | 99.81 45 |
|
IU-MVS | | | | | | 99.84 33 | 99.88 8 | | 99.32 259 | 98.30 97 | 99.84 14 | | | | 98.86 87 | 99.85 59 | 99.89 2 |
|
xiu_mvs_v1_base_debu | | | 99.29 61 | 99.27 55 | 99.34 133 | 99.63 128 | 98.97 153 | 99.12 262 | 99.51 105 | 98.86 47 | 99.84 14 | 99.47 241 | 98.18 102 | 99.99 1 | 99.50 12 | 99.31 151 | 99.08 207 |
|
xiu_mvs_v1_base | | | 99.29 61 | 99.27 55 | 99.34 133 | 99.63 128 | 98.97 153 | 99.12 262 | 99.51 105 | 98.86 47 | 99.84 14 | 99.47 241 | 98.18 102 | 99.99 1 | 99.50 12 | 99.31 151 | 99.08 207 |
|
xiu_mvs_v1_base_debi | | | 99.29 61 | 99.27 55 | 99.34 133 | 99.63 128 | 98.97 153 | 99.12 262 | 99.51 105 | 98.86 47 | 99.84 14 | 99.47 241 | 98.18 102 | 99.99 1 | 99.50 12 | 99.31 151 | 99.08 207 |
|
Regformer-1 | | | 99.53 12 | 99.47 12 | 99.72 64 | 99.71 94 | 99.44 98 | 99.49 144 | 99.46 174 | 98.95 39 | 99.83 19 | 99.76 112 | 99.01 19 | 99.93 73 | 99.17 49 | 99.87 41 | 99.80 55 |
|
Regformer-2 | | | 99.54 10 | 99.47 12 | 99.75 54 | 99.71 94 | 99.52 88 | 99.49 144 | 99.49 133 | 98.94 40 | 99.83 19 | 99.76 112 | 99.01 19 | 99.94 58 | 99.15 52 | 99.87 41 | 99.80 55 |
|
DeepPCF-MVS | | 98.18 3 | 98.81 135 | 99.37 24 | 97.12 325 | 99.60 142 | 91.75 362 | 98.61 336 | 99.44 195 | 99.35 1 | 99.83 19 | 99.85 33 | 98.70 67 | 99.81 163 | 99.02 63 | 99.91 17 | 99.81 45 |
|
TSAR-MVS + GP. | | | 99.36 53 | 99.36 26 | 99.36 132 | 99.67 109 | 98.61 194 | 99.07 272 | 99.33 249 | 99.00 27 | 99.82 22 | 99.81 66 | 99.06 16 | 99.84 141 | 99.09 57 | 99.42 141 | 99.65 121 |
|
abl_6 | | | 99.44 32 | 99.31 42 | 99.83 36 | 99.85 26 | 99.75 43 | 99.66 52 | 99.59 44 | 98.13 115 | 99.82 22 | 99.81 66 | 98.60 74 | 99.96 20 | 98.46 150 | 99.88 37 | 99.79 61 |
|
FOURS1 | | | | | | 99.91 1 | 99.93 1 | 99.87 6 | 99.56 58 | 99.10 12 | 99.81 24 | | | | | | |
|
DVP-MVS |  | | 99.57 8 | 99.47 12 | 99.88 6 | 99.85 26 | 99.89 4 | 99.57 98 | 99.37 232 | 99.10 12 | 99.81 24 | 99.80 82 | 98.94 35 | 99.96 20 | 98.93 72 | 99.86 52 | 99.81 45 |
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 | | | | | | | | | | 98.99 30 | 99.81 24 | 99.80 82 | 99.09 14 | 99.96 20 | 98.85 89 | 99.90 24 | 99.88 8 |
|
MVSFormer | | | 99.17 77 | 99.12 71 | 99.29 146 | 99.51 160 | 98.94 162 | 99.88 2 | 99.46 174 | 97.55 181 | 99.80 27 | 99.65 168 | 97.39 123 | 99.28 281 | 99.03 61 | 99.85 59 | 99.65 121 |
|
lupinMVS | | | 99.13 83 | 99.01 90 | 99.46 121 | 99.51 160 | 98.94 162 | 99.05 277 | 99.16 290 | 97.86 145 | 99.80 27 | 99.56 207 | 97.39 123 | 99.86 129 | 98.94 70 | 99.85 59 | 99.58 146 |
|
tttt0517 | | | 98.42 160 | 98.14 172 | 99.28 149 | 99.66 118 | 98.38 215 | 99.74 35 | 96.85 363 | 97.68 168 | 99.79 29 | 99.74 123 | 91.39 307 | 99.89 118 | 98.83 95 | 99.56 134 | 99.57 147 |
|
APD-MVS_3200maxsize | | | 99.48 21 | 99.35 29 | 99.85 28 | 99.76 56 | 99.83 17 | 99.63 64 | 99.54 75 | 98.36 90 | 99.79 29 | 99.82 53 | 98.86 44 | 99.95 47 | 98.62 124 | 99.81 84 | 99.78 69 |
|
jason | | | 99.13 83 | 99.03 83 | 99.45 122 | 99.46 181 | 98.87 169 | 99.12 262 | 99.26 275 | 98.03 135 | 99.79 29 | 99.65 168 | 97.02 137 | 99.85 135 | 99.02 63 | 99.90 24 | 99.65 121 |
jason: jason. |
SteuartSystems-ACMMP | | | 99.54 10 | 99.42 16 | 99.87 12 | 99.82 38 | 99.81 27 | 99.59 84 | 99.51 105 | 98.62 66 | 99.79 29 | 99.83 46 | 99.28 4 | 99.97 12 | 98.48 146 | 99.90 24 | 99.84 21 |
Skip Steuart: Steuart Systems R&D Blog. |
DeepC-MVS_fast | | 98.69 1 | 99.49 17 | 99.39 20 | 99.77 50 | 99.63 128 | 99.59 73 | 99.36 202 | 99.46 174 | 99.07 18 | 99.79 29 | 99.82 53 | 98.85 45 | 99.92 84 | 98.68 117 | 99.87 41 | 99.82 39 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
SMA-MVS |  | | 99.44 32 | 99.30 45 | 99.85 28 | 99.73 83 | 99.83 17 | 99.56 105 | 99.47 164 | 97.45 193 | 99.78 34 | 99.82 53 | 99.18 10 | 99.91 95 | 98.79 101 | 99.89 34 | 99.81 45 |
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 |
TSAR-MVS + MP. | | | 99.58 5 | 99.50 9 | 99.81 41 | 99.91 1 | 99.66 59 | 99.63 64 | 99.39 217 | 98.91 45 | 99.78 34 | 99.85 33 | 99.36 2 | 99.94 58 | 98.84 92 | 99.88 37 | 99.82 39 |
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition |
test2506 | | | 96.81 293 | 96.65 291 | 97.29 321 | 99.74 75 | 92.21 361 | 99.60 77 | 85.06 380 | 99.13 8 | 99.77 36 | 99.93 4 | 87.82 350 | 99.85 135 | 99.38 26 | 99.38 143 | 99.80 55 |
|
CS-MVS | | | 99.50 16 | 99.49 11 | 99.52 108 | 99.76 56 | 99.35 106 | 99.90 1 | 99.55 67 | 98.56 70 | 99.77 36 | 99.70 139 | 98.75 60 | 99.77 177 | 99.64 2 | 99.78 95 | 99.42 180 |
|
test_part2 | | | | | | 99.81 41 | 99.83 17 | | | | 99.77 36 | | | | | | |
|
MSP-MVS | | | 99.42 41 | 99.27 55 | 99.88 6 | 99.89 9 | 99.80 29 | 99.67 48 | 99.50 125 | 98.70 62 | 99.77 36 | 99.49 232 | 98.21 100 | 99.95 47 | 98.46 150 | 99.77 100 | 99.88 8 |
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 |
CS-MVS-test | | | 99.42 41 | 99.39 20 | 99.52 108 | 99.77 52 | 99.35 106 | 99.80 20 | 99.57 52 | 98.56 70 | 99.77 36 | 99.44 247 | 98.16 105 | 99.77 177 | 99.64 2 | 99.78 95 | 99.42 180 |
|
UA-Net | | | 99.42 41 | 99.29 49 | 99.80 43 | 99.62 134 | 99.55 80 | 99.50 134 | 99.70 15 | 98.79 56 | 99.77 36 | 99.96 1 | 97.45 122 | 99.96 20 | 98.92 74 | 99.90 24 | 99.89 2 |
|
APD-MVS |  | | 99.27 64 | 99.08 76 | 99.84 35 | 99.75 67 | 99.79 33 | 99.50 134 | 99.50 125 | 97.16 221 | 99.77 36 | 99.82 53 | 98.78 52 | 99.94 58 | 97.56 230 | 99.86 52 | 99.80 55 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
SR-MVS-dyc-post | | | 99.45 28 | 99.31 42 | 99.85 28 | 99.76 56 | 99.82 23 | 99.63 64 | 99.52 92 | 98.38 86 | 99.76 43 | 99.82 53 | 98.53 77 | 99.95 47 | 98.61 127 | 99.81 84 | 99.77 71 |
|
RE-MVS-def | | | | 99.34 31 | | 99.76 56 | 99.82 23 | 99.63 64 | 99.52 92 | 98.38 86 | 99.76 43 | 99.82 53 | 98.75 60 | | 98.61 127 | 99.81 84 | 99.77 71 |
|
ACMMP_NAP | | | 99.47 24 | 99.34 31 | 99.88 6 | 99.87 16 | 99.86 13 | 99.47 155 | 99.48 146 | 98.05 132 | 99.76 43 | 99.86 27 | 98.82 48 | 99.93 73 | 98.82 99 | 99.91 17 | 99.84 21 |
|
HPM-MVS_fast | | | 99.51 15 | 99.40 19 | 99.85 28 | 99.91 1 | 99.79 33 | 99.76 31 | 99.56 58 | 97.72 164 | 99.76 43 | 99.75 117 | 99.13 12 | 99.92 84 | 99.07 59 | 99.92 12 | 99.85 17 |
|
test1172 | | | 99.43 36 | 99.29 49 | 99.85 28 | 99.75 67 | 99.82 23 | 99.60 77 | 99.56 58 | 98.28 98 | 99.74 47 | 99.79 94 | 98.53 77 | 99.95 47 | 98.55 141 | 99.78 95 | 99.79 61 |
|
VNet | | | 99.11 94 | 98.90 104 | 99.73 61 | 99.52 158 | 99.56 78 | 99.41 178 | 99.39 217 | 99.01 23 | 99.74 47 | 99.78 101 | 95.56 186 | 99.92 84 | 99.52 10 | 98.18 219 | 99.72 95 |
|
patch_mono-2 | | | 99.26 66 | 99.62 1 | 98.16 278 | 99.81 41 | 94.59 340 | 99.52 123 | 99.64 33 | 99.33 2 | 99.73 49 | 99.90 10 | 99.00 25 | 99.99 1 | 99.69 1 | 99.98 2 | 99.89 2 |
|
SR-MVS | | | 99.43 36 | 99.29 49 | 99.86 21 | 99.75 67 | 99.83 17 | 99.59 84 | 99.62 34 | 98.21 107 | 99.73 49 | 99.79 94 | 98.68 68 | 99.96 20 | 98.44 152 | 99.77 100 | 99.79 61 |
|
thisisatest0530 | | | 98.35 167 | 98.03 186 | 99.31 139 | 99.63 128 | 98.56 196 | 99.54 117 | 96.75 365 | 97.53 186 | 99.73 49 | 99.65 168 | 91.25 310 | 99.89 118 | 98.62 124 | 99.56 134 | 99.48 168 |
|
DROMVSNet | | | 99.44 32 | 99.39 20 | 99.58 90 | 99.56 152 | 99.49 91 | 99.88 2 | 99.58 50 | 98.38 86 | 99.73 49 | 99.69 148 | 98.20 101 | 99.70 209 | 99.64 2 | 99.82 81 | 99.54 151 |
|
diffmvs | | | 99.14 81 | 99.02 86 | 99.51 112 | 99.61 138 | 98.96 157 | 99.28 224 | 99.49 133 | 98.46 79 | 99.72 53 | 99.71 135 | 96.50 154 | 99.88 123 | 99.31 35 | 99.11 165 | 99.67 114 |
|
xxxxxxxxxxxxxcwj | | | 99.43 36 | 99.32 35 | 99.75 54 | 99.76 56 | 99.59 73 | 99.14 260 | 99.53 86 | 99.00 27 | 99.71 54 | 99.80 82 | 98.95 32 | 99.93 73 | 98.19 171 | 99.84 66 | 99.74 82 |
|
SF-MVS | | | 99.38 51 | 99.24 60 | 99.79 46 | 99.79 45 | 99.68 54 | 99.57 98 | 99.54 75 | 97.82 155 | 99.71 54 | 99.80 82 | 98.95 32 | 99.93 73 | 98.19 171 | 99.84 66 | 99.74 82 |
|
xiu_mvs_v2_base | | | 99.26 66 | 99.25 59 | 99.29 146 | 99.53 156 | 98.91 166 | 99.02 286 | 99.45 186 | 98.80 55 | 99.71 54 | 99.26 296 | 98.94 35 | 99.98 7 | 99.34 32 | 99.23 156 | 98.98 221 |
|
PS-MVSNAJ | | | 99.32 57 | 99.32 35 | 99.30 143 | 99.57 148 | 98.94 162 | 98.97 300 | 99.46 174 | 98.92 44 | 99.71 54 | 99.24 298 | 99.01 19 | 99.98 7 | 99.35 28 | 99.66 125 | 98.97 222 |
|
PGM-MVS | | | 99.45 28 | 99.31 42 | 99.86 21 | 99.87 16 | 99.78 40 | 99.58 92 | 99.65 32 | 97.84 149 | 99.71 54 | 99.80 82 | 99.12 13 | 99.97 12 | 98.33 162 | 99.87 41 | 99.83 32 |
|
114514_t | | | 98.93 117 | 98.67 132 | 99.72 64 | 99.85 26 | 99.53 85 | 99.62 70 | 99.59 44 | 92.65 348 | 99.71 54 | 99.78 101 | 98.06 109 | 99.90 110 | 98.84 92 | 99.91 17 | 99.74 82 |
|
PVSNet_Blended_VisFu | | | 99.36 53 | 99.28 53 | 99.61 85 | 99.86 22 | 99.07 142 | 99.47 155 | 99.93 2 | 97.66 172 | 99.71 54 | 99.86 27 | 97.73 117 | 99.96 20 | 99.47 19 | 99.82 81 | 99.79 61 |
|
zzz-MVS | | | 99.49 17 | 99.36 26 | 99.89 4 | 99.90 4 | 99.86 13 | 99.36 202 | 99.47 164 | 98.79 56 | 99.68 61 | 99.81 66 | 98.43 86 | 99.97 12 | 98.88 78 | 99.90 24 | 99.83 32 |
|
MTAPA | | | 99.52 14 | 99.39 20 | 99.89 4 | 99.90 4 | 99.86 13 | 99.66 52 | 99.47 164 | 98.79 56 | 99.68 61 | 99.81 66 | 98.43 86 | 99.97 12 | 98.88 78 | 99.90 24 | 99.83 32 |
|
HFP-MVS | | | 99.49 17 | 99.37 24 | 99.86 21 | 99.87 16 | 99.80 29 | 99.66 52 | 99.67 22 | 98.15 113 | 99.68 61 | 99.69 148 | 99.06 16 | 99.96 20 | 98.69 115 | 99.87 41 | 99.84 21 |
|
#test# | | | 99.43 36 | 99.29 49 | 99.86 21 | 99.87 16 | 99.80 29 | 99.55 114 | 99.67 22 | 97.83 150 | 99.68 61 | 99.69 148 | 99.06 16 | 99.96 20 | 98.39 154 | 99.87 41 | 99.84 21 |
|
VDDNet | | | 97.55 269 | 97.02 286 | 99.16 161 | 99.49 172 | 98.12 227 | 99.38 195 | 99.30 266 | 95.35 318 | 99.68 61 | 99.90 10 | 82.62 363 | 99.93 73 | 99.31 35 | 98.13 224 | 99.42 180 |
|
HPM-MVS |  | | 99.42 41 | 99.28 53 | 99.83 36 | 99.90 4 | 99.72 47 | 99.81 16 | 99.54 75 | 97.59 176 | 99.68 61 | 99.63 181 | 98.91 40 | 99.94 58 | 98.58 133 | 99.91 17 | 99.84 21 |
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023 |
VDD-MVS | | | 97.73 250 | 97.35 266 | 98.88 201 | 99.47 180 | 97.12 264 | 99.34 211 | 98.85 324 | 98.19 108 | 99.67 67 | 99.85 33 | 82.98 361 | 99.92 84 | 99.49 16 | 98.32 212 | 99.60 138 |
|
ACMMPR | | | 99.49 17 | 99.36 26 | 99.86 21 | 99.87 16 | 99.79 33 | 99.66 52 | 99.67 22 | 98.15 113 | 99.67 67 | 99.69 148 | 98.95 32 | 99.96 20 | 98.69 115 | 99.87 41 | 99.84 21 |
|
PVSNet_BlendedMVS | | | 98.86 123 | 98.80 119 | 99.03 173 | 99.76 56 | 98.79 180 | 99.28 224 | 99.91 3 | 97.42 199 | 99.67 67 | 99.37 268 | 97.53 120 | 99.88 123 | 98.98 66 | 97.29 260 | 98.42 323 |
|
PVSNet_Blended | | | 99.08 100 | 98.97 95 | 99.42 127 | 99.76 56 | 98.79 180 | 98.78 322 | 99.91 3 | 96.74 254 | 99.67 67 | 99.49 232 | 97.53 120 | 99.88 123 | 98.98 66 | 99.85 59 | 99.60 138 |
|
sss | | | 99.17 77 | 99.05 78 | 99.53 102 | 99.62 134 | 98.97 153 | 99.36 202 | 99.62 34 | 97.83 150 | 99.67 67 | 99.65 168 | 97.37 127 | 99.95 47 | 99.19 46 | 99.19 159 | 99.68 111 |
|
ECVR-MVS |  | | 98.04 200 | 98.05 184 | 98.00 290 | 99.74 75 | 94.37 343 | 99.59 84 | 94.98 371 | 99.13 8 | 99.66 72 | 99.93 4 | 90.67 316 | 99.84 141 | 99.40 25 | 99.38 143 | 99.80 55 |
|
h-mvs33 | | | 97.70 257 | 97.28 275 | 98.97 181 | 99.70 101 | 97.27 258 | 99.36 202 | 99.45 186 | 98.94 40 | 99.66 72 | 99.64 175 | 94.93 205 | 99.99 1 | 99.48 17 | 84.36 359 | 99.65 121 |
|
hse-mvs2 | | | 97.50 275 | 97.14 282 | 98.59 232 | 99.49 172 | 97.05 271 | 99.28 224 | 99.22 281 | 98.94 40 | 99.66 72 | 99.42 253 | 94.93 205 | 99.65 222 | 99.48 17 | 83.80 361 | 99.08 207 |
|
region2R | | | 99.48 21 | 99.35 29 | 99.87 12 | 99.88 12 | 99.80 29 | 99.65 59 | 99.66 27 | 98.13 115 | 99.66 72 | 99.68 155 | 98.96 29 | 99.96 20 | 98.62 124 | 99.87 41 | 99.84 21 |
|
RPSCF | | | 98.22 175 | 98.62 142 | 96.99 326 | 99.82 38 | 91.58 363 | 99.72 36 | 99.44 195 | 96.61 265 | 99.66 72 | 99.89 14 | 95.92 173 | 99.82 159 | 97.46 240 | 99.10 168 | 99.57 147 |
|
OMC-MVS | | | 99.08 100 | 99.04 81 | 99.20 157 | 99.67 109 | 98.22 221 | 99.28 224 | 99.52 92 | 98.07 127 | 99.66 72 | 99.81 66 | 97.79 115 | 99.78 175 | 97.79 205 | 99.81 84 | 99.60 138 |
|
test1111 | | | 98.04 200 | 98.11 175 | 97.83 301 | 99.74 75 | 93.82 348 | 99.58 92 | 95.40 370 | 99.12 10 | 99.65 78 | 99.93 4 | 90.73 315 | 99.84 141 | 99.43 24 | 99.38 143 | 99.82 39 |
|
test_one_0601 | | | | | | 99.81 41 | 99.88 8 | | 99.49 133 | 98.97 36 | 99.65 78 | 99.81 66 | 99.09 14 | | | | |
|
LFMVS | | | 97.90 221 | 97.35 266 | 99.54 96 | 99.52 158 | 99.01 148 | 99.39 190 | 98.24 348 | 97.10 229 | 99.65 78 | 99.79 94 | 84.79 358 | 99.91 95 | 99.28 38 | 98.38 207 | 99.69 107 |
|
MVS_111021_LR | | | 99.41 46 | 99.33 33 | 99.65 75 | 99.77 52 | 99.51 90 | 98.94 307 | 99.85 6 | 98.82 51 | 99.65 78 | 99.74 123 | 98.51 80 | 99.80 168 | 98.83 95 | 99.89 34 | 99.64 128 |
|
9.14 | | | | 99.10 73 | | 99.72 88 | | 99.40 186 | 99.51 105 | 97.53 186 | 99.64 82 | 99.78 101 | 98.84 46 | 99.91 95 | 97.63 221 | 99.82 81 | |
|
GST-MVS | | | 99.40 49 | 99.24 60 | 99.85 28 | 99.86 22 | 99.79 33 | 99.60 77 | 99.67 22 | 97.97 138 | 99.63 83 | 99.68 155 | 98.52 79 | 99.95 47 | 98.38 156 | 99.86 52 | 99.81 45 |
|
CPTT-MVS | | | 99.11 94 | 98.90 104 | 99.74 59 | 99.80 44 | 99.46 96 | 99.59 84 | 99.49 133 | 97.03 236 | 99.63 83 | 99.69 148 | 97.27 130 | 99.96 20 | 97.82 203 | 99.84 66 | 99.81 45 |
|
ACMMP |  | | 99.45 28 | 99.32 35 | 99.82 38 | 99.89 9 | 99.67 57 | 99.62 70 | 99.69 18 | 98.12 117 | 99.63 83 | 99.84 42 | 98.73 64 | 99.96 20 | 98.55 141 | 99.83 75 | 99.81 45 |
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 |
DeepC-MVS | | 98.35 2 | 99.30 59 | 99.19 65 | 99.64 80 | 99.82 38 | 99.23 121 | 99.62 70 | 99.55 67 | 98.94 40 | 99.63 83 | 99.95 2 | 95.82 178 | 99.94 58 | 99.37 27 | 99.97 4 | 99.73 89 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
CHOSEN 280x420 | | | 99.12 89 | 99.13 70 | 99.08 166 | 99.66 118 | 97.89 238 | 98.43 346 | 99.71 13 | 98.88 46 | 99.62 87 | 99.76 112 | 96.63 150 | 99.70 209 | 99.46 20 | 99.99 1 | 99.66 117 |
|
PHI-MVS | | | 99.30 59 | 99.17 67 | 99.70 67 | 99.56 152 | 99.52 88 | 99.58 92 | 99.80 8 | 97.12 225 | 99.62 87 | 99.73 130 | 98.58 75 | 99.90 110 | 98.61 127 | 99.91 17 | 99.68 111 |
|
ETH3D-3000-0.1 | | | 99.21 71 | 99.02 86 | 99.77 50 | 99.73 83 | 99.69 52 | 99.38 195 | 99.51 105 | 97.45 193 | 99.61 89 | 99.75 117 | 98.51 80 | 99.91 95 | 97.45 242 | 99.83 75 | 99.71 102 |
|
test_yl | | | 98.86 123 | 98.63 137 | 99.54 96 | 99.49 172 | 99.18 125 | 99.50 134 | 99.07 301 | 98.22 105 | 99.61 89 | 99.51 226 | 95.37 192 | 99.84 141 | 98.60 130 | 98.33 208 | 99.59 142 |
|
DCV-MVSNet | | | 98.86 123 | 98.63 137 | 99.54 96 | 99.49 172 | 99.18 125 | 99.50 134 | 99.07 301 | 98.22 105 | 99.61 89 | 99.51 226 | 95.37 192 | 99.84 141 | 98.60 130 | 98.33 208 | 99.59 142 |
|
MG-MVS | | | 99.13 83 | 99.02 86 | 99.45 122 | 99.57 148 | 98.63 191 | 99.07 272 | 99.34 242 | 98.99 30 | 99.61 89 | 99.82 53 | 97.98 111 | 99.87 126 | 97.00 267 | 99.80 88 | 99.85 17 |
|
MP-MVS-pluss | | | 99.37 52 | 99.20 64 | 99.88 6 | 99.90 4 | 99.87 12 | 99.30 218 | 99.52 92 | 97.18 219 | 99.60 93 | 99.79 94 | 98.79 51 | 99.95 47 | 98.83 95 | 99.91 17 | 99.83 32 |
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
CDPH-MVS | | | 99.13 83 | 98.91 103 | 99.80 43 | 99.75 67 | 99.71 49 | 99.15 258 | 99.41 207 | 96.60 267 | 99.60 93 | 99.55 210 | 98.83 47 | 99.90 110 | 97.48 237 | 99.83 75 | 99.78 69 |
|
EPP-MVSNet | | | 99.13 83 | 98.99 91 | 99.53 102 | 99.65 123 | 99.06 143 | 99.81 16 | 99.33 249 | 97.43 197 | 99.60 93 | 99.88 19 | 97.14 132 | 99.84 141 | 99.13 53 | 98.94 180 | 99.69 107 |
|
testtj | | | 99.12 89 | 98.87 108 | 99.86 21 | 99.72 88 | 99.79 33 | 99.44 163 | 99.51 105 | 97.29 209 | 99.59 96 | 99.74 123 | 98.15 106 | 99.96 20 | 96.74 282 | 99.69 117 | 99.81 45 |
|
HyFIR lowres test | | | 99.11 94 | 98.92 101 | 99.65 75 | 99.90 4 | 99.37 104 | 99.02 286 | 99.91 3 | 97.67 171 | 99.59 96 | 99.75 117 | 95.90 175 | 99.73 193 | 99.53 9 | 99.02 176 | 99.86 14 |
|
MVS_Test | | | 99.10 97 | 98.97 95 | 99.48 116 | 99.49 172 | 99.14 133 | 99.67 48 | 99.34 242 | 97.31 207 | 99.58 98 | 99.76 112 | 97.65 119 | 99.82 159 | 98.87 82 | 99.07 171 | 99.46 175 |
|
MDTV_nov1_ep13_2view | | | | | | | 95.18 331 | 99.35 208 | | 96.84 249 | 99.58 98 | | 95.19 201 | | 97.82 203 | | 99.46 175 |
|
DELS-MVS | | | 99.48 21 | 99.42 16 | 99.65 75 | 99.72 88 | 99.40 103 | 99.05 277 | 99.66 27 | 99.14 7 | 99.57 100 | 99.80 82 | 98.46 84 | 99.94 58 | 99.57 7 | 99.84 66 | 99.60 138 |
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 |
ZD-MVS | | | | | | 99.71 94 | 99.79 33 | | 99.61 36 | 96.84 249 | 99.56 101 | 99.54 215 | 98.58 75 | 99.96 20 | 96.93 274 | 99.75 104 | |
|
CR-MVSNet | | | 98.17 182 | 97.93 199 | 98.87 205 | 99.18 249 | 98.49 207 | 99.22 248 | 99.33 249 | 96.96 240 | 99.56 101 | 99.38 265 | 94.33 235 | 99.00 323 | 94.83 323 | 98.58 198 | 99.14 199 |
|
RPMNet | | | 96.72 295 | 95.90 305 | 99.19 158 | 99.18 249 | 98.49 207 | 99.22 248 | 99.52 92 | 88.72 359 | 99.56 101 | 97.38 356 | 94.08 245 | 99.95 47 | 86.87 366 | 98.58 198 | 99.14 199 |
|
IS-MVSNet | | | 99.05 104 | 98.87 108 | 99.57 92 | 99.73 83 | 99.32 109 | 99.75 32 | 99.20 285 | 98.02 136 | 99.56 101 | 99.86 27 | 96.54 153 | 99.67 215 | 98.09 180 | 99.13 164 | 99.73 89 |
|
ZNCC-MVS | | | 99.47 24 | 99.33 33 | 99.87 12 | 99.87 16 | 99.81 27 | 99.64 62 | 99.67 22 | 98.08 126 | 99.55 105 | 99.64 175 | 98.91 40 | 99.96 20 | 98.72 110 | 99.90 24 | 99.82 39 |
|
thisisatest0515 | | | 98.14 186 | 97.79 210 | 99.19 158 | 99.50 170 | 98.50 206 | 98.61 336 | 96.82 364 | 96.95 242 | 99.54 106 | 99.43 250 | 91.66 303 | 99.86 129 | 98.08 184 | 99.51 138 | 99.22 196 |
|
MVS_111021_HR | | | 99.41 46 | 99.32 35 | 99.66 71 | 99.72 88 | 99.47 95 | 98.95 305 | 99.85 6 | 98.82 51 | 99.54 106 | 99.73 130 | 98.51 80 | 99.74 186 | 98.91 75 | 99.88 37 | 99.77 71 |
|
CP-MVS | | | 99.45 28 | 99.32 35 | 99.85 28 | 99.83 37 | 99.75 43 | 99.69 41 | 99.52 92 | 98.07 127 | 99.53 108 | 99.63 181 | 98.93 39 | 99.97 12 | 98.74 106 | 99.91 17 | 99.83 32 |
|
WTY-MVS | | | 99.06 102 | 98.88 107 | 99.61 85 | 99.62 134 | 99.16 128 | 99.37 198 | 99.56 58 | 98.04 133 | 99.53 108 | 99.62 187 | 96.84 142 | 99.94 58 | 98.85 89 | 98.49 205 | 99.72 95 |
|
MCST-MVS | | | 99.43 36 | 99.30 45 | 99.82 38 | 99.79 45 | 99.74 46 | 99.29 222 | 99.40 213 | 98.79 56 | 99.52 110 | 99.62 187 | 98.91 40 | 99.90 110 | 98.64 122 | 99.75 104 | 99.82 39 |
|
PatchT | | | 97.03 290 | 96.44 295 | 98.79 219 | 98.99 284 | 98.34 216 | 99.16 254 | 99.07 301 | 92.13 349 | 99.52 110 | 97.31 359 | 94.54 230 | 98.98 325 | 88.54 360 | 98.73 194 | 99.03 215 |
|
CANet | | | 99.25 69 | 99.14 69 | 99.59 87 | 99.41 191 | 99.16 128 | 99.35 208 | 99.57 52 | 98.82 51 | 99.51 112 | 99.61 191 | 96.46 155 | 99.95 47 | 99.59 5 | 99.98 2 | 99.65 121 |
|
mPP-MVS | | | 99.44 32 | 99.30 45 | 99.86 21 | 99.88 12 | 99.79 33 | 99.69 41 | 99.48 146 | 98.12 117 | 99.50 113 | 99.75 117 | 98.78 52 | 99.97 12 | 98.57 135 | 99.89 34 | 99.83 32 |
|
PatchMatch-RL | | | 98.84 134 | 98.62 142 | 99.52 108 | 99.71 94 | 99.28 115 | 99.06 275 | 99.77 9 | 97.74 163 | 99.50 113 | 99.53 219 | 95.41 190 | 99.84 141 | 97.17 260 | 99.64 128 | 99.44 178 |
|
PVSNet | | 96.02 17 | 98.85 131 | 98.84 114 | 98.89 198 | 99.73 83 | 97.28 257 | 98.32 352 | 99.60 41 | 97.86 145 | 99.50 113 | 99.57 204 | 96.75 147 | 99.86 129 | 98.56 138 | 99.70 116 | 99.54 151 |
|
LS3D | | | 99.27 64 | 99.12 71 | 99.74 59 | 99.18 249 | 99.75 43 | 99.56 105 | 99.57 52 | 98.45 80 | 99.49 116 | 99.85 33 | 97.77 116 | 99.94 58 | 98.33 162 | 99.84 66 | 99.52 157 |
|
MP-MVS |  | | 99.33 56 | 99.15 68 | 99.87 12 | 99.88 12 | 99.82 23 | 99.66 52 | 99.46 174 | 98.09 122 | 99.48 117 | 99.74 123 | 98.29 97 | 99.96 20 | 97.93 194 | 99.87 41 | 99.82 39 |
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo. |
旧先验2 | | | | | | | | 98.96 301 | | 96.70 257 | 99.47 118 | | | 99.94 58 | 98.19 171 | | |
|
MSDG | | | 98.98 113 | 98.80 119 | 99.53 102 | 99.76 56 | 99.19 123 | 98.75 325 | 99.55 67 | 97.25 213 | 99.47 118 | 99.77 108 | 97.82 114 | 99.87 126 | 96.93 274 | 99.90 24 | 99.54 151 |
|
CDS-MVSNet | | | 99.09 98 | 99.03 83 | 99.25 152 | 99.42 188 | 98.73 183 | 99.45 159 | 99.46 174 | 98.11 119 | 99.46 120 | 99.77 108 | 98.01 110 | 99.37 262 | 98.70 112 | 98.92 183 | 99.66 117 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
MSLP-MVS++ | | | 99.46 26 | 99.47 12 | 99.44 126 | 99.60 142 | 99.16 128 | 99.41 178 | 99.71 13 | 98.98 33 | 99.45 121 | 99.78 101 | 99.19 9 | 99.54 239 | 99.28 38 | 99.84 66 | 99.63 132 |
|
XVG-OURS | | | 98.73 143 | 98.68 131 | 98.88 201 | 99.70 101 | 97.73 246 | 98.92 308 | 99.55 67 | 98.52 74 | 99.45 121 | 99.84 42 | 95.27 196 | 99.91 95 | 98.08 184 | 98.84 188 | 99.00 218 |
|
tpmrst | | | 98.33 168 | 98.48 153 | 97.90 297 | 99.16 257 | 94.78 338 | 99.31 216 | 99.11 295 | 97.27 211 | 99.45 121 | 99.59 197 | 95.33 194 | 99.84 141 | 98.48 146 | 98.61 195 | 99.09 206 |
|
TAMVS | | | 99.12 89 | 99.08 76 | 99.24 154 | 99.46 181 | 98.55 197 | 99.51 128 | 99.46 174 | 98.09 122 | 99.45 121 | 99.82 53 | 98.34 94 | 99.51 240 | 98.70 112 | 98.93 181 | 99.67 114 |
|
ETV-MVS | | | 99.26 66 | 99.21 63 | 99.40 128 | 99.46 181 | 99.30 113 | 99.56 105 | 99.52 92 | 98.52 74 | 99.44 125 | 99.27 294 | 98.41 90 | 99.86 129 | 99.10 56 | 99.59 133 | 99.04 214 |
|
CANet_DTU | | | 98.97 115 | 98.87 108 | 99.25 152 | 99.33 210 | 98.42 214 | 99.08 271 | 99.30 266 | 99.16 6 | 99.43 126 | 99.75 117 | 95.27 196 | 99.97 12 | 98.56 138 | 99.95 7 | 99.36 187 |
|
SCA | | | 98.19 179 | 98.16 170 | 98.27 273 | 99.30 219 | 95.55 319 | 99.07 272 | 98.97 309 | 97.57 179 | 99.43 126 | 99.57 204 | 92.72 272 | 99.74 186 | 97.58 225 | 99.20 158 | 99.52 157 |
|
testdata | | | | | 99.54 96 | 99.75 67 | 98.95 159 | | 99.51 105 | 97.07 231 | 99.43 126 | 99.70 139 | 98.87 43 | 99.94 58 | 97.76 208 | 99.64 128 | 99.72 95 |
|
DPM-MVS | | | 98.95 116 | 98.71 128 | 99.66 71 | 99.63 128 | 99.55 80 | 98.64 335 | 99.10 296 | 97.93 141 | 99.42 129 | 99.55 210 | 98.67 71 | 99.80 168 | 95.80 304 | 99.68 122 | 99.61 136 |
|
XVG-OURS-SEG-HR | | | 98.69 146 | 98.62 142 | 98.89 198 | 99.71 94 | 97.74 245 | 99.12 262 | 99.54 75 | 98.44 83 | 99.42 129 | 99.71 135 | 94.20 239 | 99.92 84 | 98.54 143 | 98.90 185 | 99.00 218 |
|
baseline | | | 99.15 80 | 99.02 86 | 99.53 102 | 99.66 118 | 99.14 133 | 99.72 36 | 99.48 146 | 98.35 91 | 99.42 129 | 99.84 42 | 96.07 166 | 99.79 171 | 99.51 11 | 99.14 163 | 99.67 114 |
|
DP-MVS Recon | | | 99.12 89 | 98.95 99 | 99.65 75 | 99.74 75 | 99.70 51 | 99.27 229 | 99.57 52 | 96.40 284 | 99.42 129 | 99.68 155 | 98.75 60 | 99.80 168 | 97.98 190 | 99.72 111 | 99.44 178 |
|
Effi-MVS+-dtu | | | 98.78 139 | 98.89 106 | 98.47 250 | 99.33 210 | 96.91 284 | 99.57 98 | 99.30 266 | 98.47 77 | 99.41 133 | 98.99 324 | 96.78 144 | 99.74 186 | 98.73 108 | 99.38 143 | 98.74 247 |
|
casdiffmvs | | | 99.13 83 | 98.98 94 | 99.56 94 | 99.65 123 | 99.16 128 | 99.56 105 | 99.50 125 | 98.33 95 | 99.41 133 | 99.86 27 | 95.92 173 | 99.83 152 | 99.45 21 | 99.16 160 | 99.70 104 |
|
MIMVSNet | | | 97.73 250 | 97.45 249 | 98.57 236 | 99.45 186 | 97.50 252 | 99.02 286 | 98.98 308 | 96.11 306 | 99.41 133 | 99.14 309 | 90.28 318 | 98.74 340 | 95.74 305 | 98.93 181 | 99.47 173 |
|
CSCG | | | 99.32 57 | 99.32 35 | 99.32 138 | 99.85 26 | 98.29 217 | 99.71 38 | 99.66 27 | 98.11 119 | 99.41 133 | 99.80 82 | 98.37 93 | 99.96 20 | 98.99 65 | 99.96 6 | 99.72 95 |
|
F-COLMAP | | | 99.19 73 | 99.04 81 | 99.64 80 | 99.78 47 | 99.27 117 | 99.42 176 | 99.54 75 | 97.29 209 | 99.41 133 | 99.59 197 | 98.42 89 | 99.93 73 | 98.19 171 | 99.69 117 | 99.73 89 |
|
EIA-MVS | | | 99.18 75 | 99.09 75 | 99.45 122 | 99.49 172 | 99.18 125 | 99.67 48 | 99.53 86 | 97.66 172 | 99.40 138 | 99.44 247 | 98.10 107 | 99.81 163 | 98.94 70 | 99.62 131 | 99.35 188 |
|
MDTV_nov1_ep13 | | | | 98.32 163 | | 99.11 264 | 94.44 342 | 99.27 229 | 98.74 332 | 97.51 188 | 99.40 138 | 99.62 187 | 94.78 214 | 99.76 183 | 97.59 224 | 98.81 191 | |
|
ETH3D cwj APD-0.16 | | | 99.06 102 | 98.84 114 | 99.72 64 | 99.51 160 | 99.60 70 | 99.23 243 | 99.44 195 | 97.04 234 | 99.39 140 | 99.67 161 | 98.30 96 | 99.92 84 | 97.27 249 | 99.69 117 | 99.64 128 |
|
CVMVSNet | | | 98.57 154 | 98.67 132 | 98.30 268 | 99.35 205 | 95.59 318 | 99.50 134 | 99.55 67 | 98.60 68 | 99.39 140 | 99.83 46 | 94.48 231 | 99.45 245 | 98.75 105 | 98.56 201 | 99.85 17 |
|
CNVR-MVS | | | 99.42 41 | 99.30 45 | 99.78 48 | 99.62 134 | 99.71 49 | 99.26 238 | 99.52 92 | 98.82 51 | 99.39 140 | 99.71 135 | 98.96 29 | 99.85 135 | 98.59 132 | 99.80 88 | 99.77 71 |
|
Effi-MVS+ | | | 98.81 135 | 98.59 148 | 99.48 116 | 99.46 181 | 99.12 137 | 98.08 358 | 99.50 125 | 97.50 189 | 99.38 143 | 99.41 257 | 96.37 159 | 99.81 163 | 99.11 55 | 98.54 202 | 99.51 163 |
|
mvs_anonymous | | | 99.03 107 | 98.99 91 | 99.16 161 | 99.38 200 | 98.52 203 | 99.51 128 | 99.38 223 | 97.79 156 | 99.38 143 | 99.81 66 | 97.30 128 | 99.45 245 | 99.35 28 | 98.99 178 | 99.51 163 |
|
XVS | | | 99.53 12 | 99.42 16 | 99.87 12 | 99.85 26 | 99.83 17 | 99.69 41 | 99.68 19 | 98.98 33 | 99.37 145 | 99.74 123 | 98.81 49 | 99.94 58 | 98.79 101 | 99.86 52 | 99.84 21 |
|
X-MVStestdata | | | 96.55 297 | 95.45 312 | 99.87 12 | 99.85 26 | 99.83 17 | 99.69 41 | 99.68 19 | 98.98 33 | 99.37 145 | 64.01 376 | 98.81 49 | 99.94 58 | 98.79 101 | 99.86 52 | 99.84 21 |
|
PatchmatchNet |  | | 98.31 169 | 98.36 158 | 98.19 276 | 99.16 257 | 95.32 327 | 99.27 229 | 98.92 315 | 97.37 203 | 99.37 145 | 99.58 200 | 94.90 208 | 99.70 209 | 97.43 244 | 99.21 157 | 99.54 151 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
AllTest | | | 98.87 120 | 98.72 126 | 99.31 139 | 99.86 22 | 98.48 209 | 99.56 105 | 99.61 36 | 97.85 147 | 99.36 148 | 99.85 33 | 95.95 170 | 99.85 135 | 96.66 288 | 99.83 75 | 99.59 142 |
|
TestCases | | | | | 99.31 139 | 99.86 22 | 98.48 209 | | 99.61 36 | 97.85 147 | 99.36 148 | 99.85 33 | 95.95 170 | 99.85 135 | 96.66 288 | 99.83 75 | 99.59 142 |
|
Vis-MVSNet (Re-imp) | | | 98.87 120 | 98.72 126 | 99.31 139 | 99.71 94 | 98.88 168 | 99.80 20 | 99.44 195 | 97.91 143 | 99.36 148 | 99.78 101 | 95.49 189 | 99.43 254 | 97.91 195 | 99.11 165 | 99.62 134 |
|
alignmvs | | | 98.81 135 | 98.56 150 | 99.58 90 | 99.43 187 | 99.42 100 | 99.51 128 | 98.96 311 | 98.61 67 | 99.35 151 | 98.92 330 | 94.78 214 | 99.77 177 | 99.35 28 | 98.11 225 | 99.54 151 |
|
VPA-MVSNet | | | 98.29 172 | 97.95 196 | 99.30 143 | 99.16 257 | 99.54 82 | 99.50 134 | 99.58 50 | 98.27 100 | 99.35 151 | 99.37 268 | 92.53 281 | 99.65 222 | 99.35 28 | 94.46 320 | 98.72 249 |
|
AdaColmap |  | | 99.01 111 | 98.80 119 | 99.66 71 | 99.56 152 | 99.54 82 | 99.18 252 | 99.70 15 | 98.18 111 | 99.35 151 | 99.63 181 | 96.32 160 | 99.90 110 | 97.48 237 | 99.77 100 | 99.55 149 |
|
test222 | | | | | | 99.75 67 | 99.49 91 | 98.91 310 | 99.49 133 | 96.42 282 | 99.34 154 | 99.65 168 | 98.28 98 | | | 99.69 117 | 99.72 95 |
|
API-MVS | | | 99.04 105 | 99.03 83 | 99.06 168 | 99.40 196 | 99.31 112 | 99.55 114 | 99.56 58 | 98.54 72 | 99.33 155 | 99.39 264 | 98.76 57 | 99.78 175 | 96.98 269 | 99.78 95 | 98.07 340 |
|
v144192 | | | 97.92 219 | 97.60 233 | 98.87 205 | 98.83 306 | 98.65 189 | 99.55 114 | 99.34 242 | 96.20 296 | 99.32 156 | 99.40 260 | 94.36 234 | 99.26 285 | 96.37 295 | 95.03 312 | 98.70 255 |
|
GeoE | | | 98.85 131 | 98.62 142 | 99.53 102 | 99.61 138 | 99.08 140 | 99.80 20 | 99.51 105 | 97.10 229 | 99.31 157 | 99.78 101 | 95.23 200 | 99.77 177 | 98.21 169 | 99.03 174 | 99.75 77 |
|
canonicalmvs | | | 99.02 108 | 98.86 112 | 99.51 112 | 99.42 188 | 99.32 109 | 99.80 20 | 99.48 146 | 98.63 65 | 99.31 157 | 98.81 333 | 97.09 134 | 99.75 185 | 99.27 40 | 97.90 229 | 99.47 173 |
|
V42 | | | 98.06 194 | 97.79 210 | 98.86 208 | 98.98 287 | 98.84 173 | 99.69 41 | 99.34 242 | 96.53 271 | 99.30 159 | 99.37 268 | 94.67 223 | 99.32 276 | 97.57 229 | 94.66 317 | 98.42 323 |
|
ab-mvs | | | 98.86 123 | 98.63 137 | 99.54 96 | 99.64 125 | 99.19 123 | 99.44 163 | 99.54 75 | 97.77 158 | 99.30 159 | 99.81 66 | 94.20 239 | 99.93 73 | 99.17 49 | 98.82 189 | 99.49 167 |
|
TAPA-MVS | | 97.07 15 | 97.74 249 | 97.34 269 | 98.94 185 | 99.70 101 | 97.53 251 | 99.25 240 | 99.51 105 | 91.90 350 | 99.30 159 | 99.63 181 | 98.78 52 | 99.64 225 | 88.09 362 | 99.87 41 | 99.65 121 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
RRT_MVS | | | 98.60 153 | 98.44 154 | 99.05 170 | 98.88 296 | 99.14 133 | 99.49 144 | 99.38 223 | 97.76 159 | 99.29 162 | 99.86 27 | 95.38 191 | 99.36 266 | 98.81 100 | 97.16 265 | 98.64 283 |
|
新几何1 | | | | | 99.75 54 | 99.75 67 | 99.59 73 | | 99.54 75 | 96.76 253 | 99.29 162 | 99.64 175 | 98.43 86 | 99.94 58 | 96.92 276 | 99.66 125 | 99.72 95 |
|
VPNet | | | 97.84 230 | 97.44 254 | 99.01 175 | 99.21 242 | 98.94 162 | 99.48 150 | 99.57 52 | 98.38 86 | 99.28 164 | 99.73 130 | 88.89 335 | 99.39 257 | 99.19 46 | 93.27 337 | 98.71 251 |
|
HY-MVS | | 97.30 7 | 98.85 131 | 98.64 136 | 99.47 119 | 99.42 188 | 99.08 140 | 99.62 70 | 99.36 233 | 97.39 202 | 99.28 164 | 99.68 155 | 96.44 157 | 99.92 84 | 98.37 158 | 98.22 214 | 99.40 185 |
|
PAPM_NR | | | 99.04 105 | 98.84 114 | 99.66 71 | 99.74 75 | 99.44 98 | 99.39 190 | 99.38 223 | 97.70 166 | 99.28 164 | 99.28 291 | 98.34 94 | 99.85 135 | 96.96 271 | 99.45 139 | 99.69 107 |
|
ETH3 D test6400 | | | 98.70 144 | 98.35 160 | 99.73 61 | 99.69 104 | 99.60 70 | 99.16 254 | 99.45 186 | 95.42 317 | 99.27 167 | 99.60 194 | 97.39 123 | 99.91 95 | 95.36 315 | 99.83 75 | 99.70 104 |
|
HPM-MVS++ |  | | 99.39 50 | 99.23 62 | 99.87 12 | 99.75 67 | 99.84 16 | 99.43 169 | 99.51 105 | 98.68 64 | 99.27 167 | 99.53 219 | 98.64 73 | 99.96 20 | 98.44 152 | 99.80 88 | 99.79 61 |
|
v1240 | | | 97.69 258 | 97.32 272 | 98.79 219 | 98.85 304 | 98.43 212 | 99.48 150 | 99.36 233 | 96.11 306 | 99.27 167 | 99.36 271 | 93.76 254 | 99.24 287 | 94.46 326 | 95.23 307 | 98.70 255 |
|
thres600view7 | | | 97.86 226 | 97.51 242 | 98.92 189 | 99.72 88 | 97.95 236 | 99.59 84 | 98.74 332 | 97.94 140 | 99.27 167 | 98.62 340 | 91.75 297 | 99.86 129 | 93.73 334 | 98.19 218 | 98.96 224 |
|
PLC |  | 97.94 4 | 99.02 108 | 98.85 113 | 99.53 102 | 99.66 118 | 99.01 148 | 99.24 242 | 99.52 92 | 96.85 248 | 99.27 167 | 99.48 238 | 98.25 99 | 99.91 95 | 97.76 208 | 99.62 131 | 99.65 121 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
thres100view900 | | | 97.76 242 | 97.45 249 | 98.69 227 | 99.72 88 | 97.86 241 | 99.59 84 | 98.74 332 | 97.93 141 | 99.26 172 | 98.62 340 | 91.75 297 | 99.83 152 | 93.22 339 | 98.18 219 | 98.37 329 |
|
EPMVS | | | 97.82 235 | 97.65 228 | 98.35 263 | 98.88 296 | 95.98 311 | 99.49 144 | 94.71 373 | 97.57 179 | 99.26 172 | 99.48 238 | 92.46 286 | 99.71 203 | 97.87 198 | 99.08 170 | 99.35 188 |
|
1121 | | | 99.09 98 | 98.87 108 | 99.75 54 | 99.74 75 | 99.60 70 | 99.27 229 | 99.48 146 | 96.82 252 | 99.25 174 | 99.65 168 | 98.38 91 | 99.93 73 | 97.53 233 | 99.67 124 | 99.73 89 |
|
Fast-Effi-MVS+-dtu | | | 98.77 141 | 98.83 118 | 98.60 231 | 99.41 191 | 96.99 278 | 99.52 123 | 99.49 133 | 98.11 119 | 99.24 175 | 99.34 277 | 96.96 140 | 99.79 171 | 97.95 193 | 99.45 139 | 99.02 217 |
|
v1921920 | | | 97.80 239 | 97.45 249 | 98.84 212 | 98.80 307 | 98.53 199 | 99.52 123 | 99.34 242 | 96.15 303 | 99.24 175 | 99.47 241 | 93.98 247 | 99.29 280 | 95.40 313 | 95.13 310 | 98.69 259 |
|
LPG-MVS_test | | | 98.22 175 | 98.13 173 | 98.49 244 | 99.33 210 | 97.05 271 | 99.58 92 | 99.55 67 | 97.46 190 | 99.24 175 | 99.83 46 | 92.58 279 | 99.72 197 | 98.09 180 | 97.51 245 | 98.68 264 |
|
LGP-MVS_train | | | | | 98.49 244 | 99.33 210 | 97.05 271 | | 99.55 67 | 97.46 190 | 99.24 175 | 99.83 46 | 92.58 279 | 99.72 197 | 98.09 180 | 97.51 245 | 98.68 264 |
|
v1144 | | | 97.98 211 | 97.69 224 | 98.85 211 | 98.87 300 | 98.66 188 | 99.54 117 | 99.35 238 | 96.27 290 | 99.23 179 | 99.35 274 | 94.67 223 | 99.23 288 | 96.73 283 | 95.16 309 | 98.68 264 |
|
Anonymous20240529 | | | 98.09 191 | 97.68 225 | 99.34 133 | 99.66 118 | 98.44 211 | 99.40 186 | 99.43 203 | 93.67 339 | 99.22 180 | 99.89 14 | 90.23 322 | 99.93 73 | 99.26 41 | 98.33 208 | 99.66 117 |
|
OPM-MVS | | | 98.19 179 | 98.10 176 | 98.45 252 | 98.88 296 | 97.07 269 | 99.28 224 | 99.38 223 | 98.57 69 | 99.22 180 | 99.81 66 | 92.12 290 | 99.66 218 | 98.08 184 | 97.54 243 | 98.61 302 |
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS). |
test_djsdf | | | 98.67 148 | 98.57 149 | 98.98 179 | 98.70 322 | 98.91 166 | 99.88 2 | 99.46 174 | 97.55 181 | 99.22 180 | 99.88 19 | 95.73 181 | 99.28 281 | 99.03 61 | 97.62 236 | 98.75 243 |
|
test12 | | | | | 99.75 54 | 99.64 125 | 99.61 68 | | 99.29 271 | | 99.21 183 | | 98.38 91 | 99.89 118 | | 99.74 107 | 99.74 82 |
|
NCCC | | | 99.34 55 | 99.19 65 | 99.79 46 | 99.61 138 | 99.65 62 | 99.30 218 | 99.48 146 | 98.86 47 | 99.21 183 | 99.63 181 | 98.72 65 | 99.90 110 | 98.25 167 | 99.63 130 | 99.80 55 |
|
PMMVS | | | 98.80 138 | 98.62 142 | 99.34 133 | 99.27 228 | 98.70 185 | 98.76 324 | 99.31 262 | 97.34 204 | 99.21 183 | 99.07 315 | 97.20 131 | 99.82 159 | 98.56 138 | 98.87 186 | 99.52 157 |
|
v1192 | | | 97.81 237 | 97.44 254 | 98.91 193 | 98.88 296 | 98.68 186 | 99.51 128 | 99.34 242 | 96.18 298 | 99.20 186 | 99.34 277 | 94.03 246 | 99.36 266 | 95.32 316 | 95.18 308 | 98.69 259 |
|
EI-MVSNet | | | 98.67 148 | 98.67 132 | 98.68 228 | 99.35 205 | 97.97 232 | 99.50 134 | 99.38 223 | 96.93 245 | 99.20 186 | 99.83 46 | 97.87 112 | 99.36 266 | 98.38 156 | 97.56 241 | 98.71 251 |
|
MVSTER | | | 98.49 155 | 98.32 163 | 99.00 177 | 99.35 205 | 99.02 146 | 99.54 117 | 99.38 223 | 97.41 200 | 99.20 186 | 99.73 130 | 93.86 251 | 99.36 266 | 98.87 82 | 97.56 241 | 98.62 293 |
|
Anonymous202405211 | | | 98.30 171 | 97.98 191 | 99.26 151 | 99.57 148 | 98.16 223 | 99.41 178 | 98.55 344 | 96.03 311 | 99.19 189 | 99.74 123 | 91.87 294 | 99.92 84 | 99.16 51 | 98.29 213 | 99.70 104 |
|
v2v482 | | | 98.06 194 | 97.77 215 | 98.92 189 | 98.90 294 | 98.82 177 | 99.57 98 | 99.36 233 | 96.65 261 | 99.19 189 | 99.35 274 | 94.20 239 | 99.25 286 | 97.72 214 | 94.97 313 | 98.69 259 |
|
CNLPA | | | 99.14 81 | 98.99 91 | 99.59 87 | 99.58 146 | 99.41 101 | 99.16 254 | 99.44 195 | 98.45 80 | 99.19 189 | 99.49 232 | 98.08 108 | 99.89 118 | 97.73 212 | 99.75 104 | 99.48 168 |
|
UGNet | | | 98.87 120 | 98.69 130 | 99.40 128 | 99.22 240 | 98.72 184 | 99.44 163 | 99.68 19 | 99.24 4 | 99.18 192 | 99.42 253 | 92.74 271 | 99.96 20 | 99.34 32 | 99.94 10 | 99.53 156 |
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 |
tfpn200view9 | | | 97.72 252 | 97.38 262 | 98.72 225 | 99.69 104 | 97.96 234 | 99.50 134 | 98.73 337 | 97.83 150 | 99.17 193 | 98.45 345 | 91.67 301 | 99.83 152 | 93.22 339 | 98.18 219 | 98.37 329 |
|
thres400 | | | 97.77 241 | 97.38 262 | 98.92 189 | 99.69 104 | 97.96 234 | 99.50 134 | 98.73 337 | 97.83 150 | 99.17 193 | 98.45 345 | 91.67 301 | 99.83 152 | 93.22 339 | 98.18 219 | 98.96 224 |
|
Test_1112_low_res | | | 98.89 119 | 98.66 135 | 99.57 92 | 99.69 104 | 98.95 159 | 99.03 283 | 99.47 164 | 96.98 238 | 99.15 195 | 99.23 299 | 96.77 146 | 99.89 118 | 98.83 95 | 98.78 192 | 99.86 14 |
|
baseline1 | | | 98.31 169 | 97.95 196 | 99.38 131 | 99.50 170 | 98.74 182 | 99.59 84 | 98.93 313 | 98.41 84 | 99.14 196 | 99.60 194 | 94.59 226 | 99.79 171 | 98.48 146 | 93.29 336 | 99.61 136 |
|
1112_ss | | | 98.98 113 | 98.77 122 | 99.59 87 | 99.68 108 | 99.02 146 | 99.25 240 | 99.48 146 | 97.23 216 | 99.13 197 | 99.58 200 | 96.93 141 | 99.90 110 | 98.87 82 | 98.78 192 | 99.84 21 |
|
CLD-MVS | | | 98.16 183 | 98.10 176 | 98.33 264 | 99.29 223 | 96.82 287 | 98.75 325 | 99.44 195 | 97.83 150 | 99.13 197 | 99.55 210 | 92.92 265 | 99.67 215 | 98.32 164 | 97.69 233 | 98.48 314 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
原ACMM1 | | | | | 99.65 75 | 99.73 83 | 99.33 108 | | 99.47 164 | 97.46 190 | 99.12 199 | 99.66 167 | 98.67 71 | 99.91 95 | 97.70 217 | 99.69 117 | 99.71 102 |
|
tpm | | | 97.67 263 | 97.55 236 | 98.03 285 | 99.02 281 | 95.01 333 | 99.43 169 | 98.54 345 | 96.44 280 | 99.12 199 | 99.34 277 | 91.83 296 | 99.60 233 | 97.75 210 | 96.46 277 | 99.48 168 |
|
HQP_MVS | | | 98.27 174 | 98.22 169 | 98.44 255 | 99.29 223 | 96.97 280 | 99.39 190 | 99.47 164 | 98.97 36 | 99.11 201 | 99.61 191 | 92.71 274 | 99.69 213 | 97.78 206 | 97.63 234 | 98.67 271 |
|
plane_prior3 | | | | | | | 97.00 277 | | | 98.69 63 | 99.11 201 | | | | | | |
|
CHOSEN 1792x2688 | | | 99.19 73 | 99.10 73 | 99.45 122 | 99.89 9 | 98.52 203 | 99.39 190 | 99.94 1 | 98.73 60 | 99.11 201 | 99.89 14 | 95.50 188 | 99.94 58 | 99.50 12 | 99.97 4 | 99.89 2 |
|
mvs-test1 | | | 98.86 123 | 98.84 114 | 98.89 198 | 99.33 210 | 97.77 244 | 99.44 163 | 99.30 266 | 98.47 77 | 99.10 204 | 99.43 250 | 96.78 144 | 99.95 47 | 98.73 108 | 99.02 176 | 98.96 224 |
|
bset_n11_16_dypcd | | | 98.16 183 | 97.97 192 | 98.73 223 | 98.26 342 | 98.28 219 | 97.99 360 | 98.01 353 | 97.68 168 | 99.10 204 | 99.63 181 | 95.68 183 | 99.15 301 | 98.78 104 | 96.55 274 | 98.75 243 |
|
v8 | | | 97.95 215 | 97.63 231 | 98.93 187 | 98.95 291 | 98.81 179 | 99.80 20 | 99.41 207 | 96.03 311 | 99.10 204 | 99.42 253 | 94.92 207 | 99.30 279 | 96.94 273 | 94.08 328 | 98.66 279 |
|
ADS-MVSNet2 | | | 98.02 204 | 98.07 183 | 97.87 298 | 99.33 210 | 95.19 330 | 99.23 243 | 99.08 299 | 96.24 293 | 99.10 204 | 99.67 161 | 94.11 243 | 98.93 335 | 96.81 279 | 99.05 172 | 99.48 168 |
|
ADS-MVSNet | | | 98.20 178 | 98.08 180 | 98.56 238 | 99.33 210 | 96.48 298 | 99.23 243 | 99.15 291 | 96.24 293 | 99.10 204 | 99.67 161 | 94.11 243 | 99.71 203 | 96.81 279 | 99.05 172 | 99.48 168 |
|
thres200 | | | 97.61 267 | 97.28 275 | 98.62 230 | 99.64 125 | 98.03 228 | 99.26 238 | 98.74 332 | 97.68 168 | 99.09 209 | 98.32 349 | 91.66 303 | 99.81 163 | 92.88 343 | 98.22 214 | 98.03 343 |
|
dp | | | 97.75 246 | 97.80 209 | 97.59 312 | 99.10 267 | 93.71 351 | 99.32 214 | 98.88 322 | 96.48 277 | 99.08 210 | 99.55 210 | 92.67 277 | 99.82 159 | 96.52 290 | 98.58 198 | 99.24 195 |
|
GBi-Net | | | 97.68 260 | 97.48 244 | 98.29 269 | 99.51 160 | 97.26 260 | 99.43 169 | 99.48 146 | 96.49 273 | 99.07 211 | 99.32 284 | 90.26 319 | 98.98 325 | 97.10 262 | 96.65 270 | 98.62 293 |
|
test1 | | | 97.68 260 | 97.48 244 | 98.29 269 | 99.51 160 | 97.26 260 | 99.43 169 | 99.48 146 | 96.49 273 | 99.07 211 | 99.32 284 | 90.26 319 | 98.98 325 | 97.10 262 | 96.65 270 | 98.62 293 |
|
FMVSNet3 | | | 98.03 202 | 97.76 218 | 98.84 212 | 99.39 199 | 98.98 150 | 99.40 186 | 99.38 223 | 96.67 259 | 99.07 211 | 99.28 291 | 92.93 264 | 98.98 325 | 97.10 262 | 96.65 270 | 98.56 309 |
|
IterMVS-LS | | | 98.46 157 | 98.42 156 | 98.58 235 | 99.59 144 | 98.00 230 | 99.37 198 | 99.43 203 | 96.94 244 | 99.07 211 | 99.59 197 | 97.87 112 | 99.03 318 | 98.32 164 | 95.62 299 | 98.71 251 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
pmmvs4 | | | 98.13 187 | 97.90 201 | 98.81 216 | 98.61 331 | 98.87 169 | 98.99 293 | 99.21 284 | 96.44 280 | 99.06 215 | 99.58 200 | 95.90 175 | 99.11 310 | 97.18 259 | 96.11 285 | 98.46 320 |
|
XVG-ACMP-BASELINE | | | 97.83 232 | 97.71 223 | 98.20 275 | 99.11 264 | 96.33 303 | 99.41 178 | 99.52 92 | 98.06 131 | 99.05 216 | 99.50 229 | 89.64 329 | 99.73 193 | 97.73 212 | 97.38 258 | 98.53 310 |
|
CostFormer | | | 97.72 252 | 97.73 221 | 97.71 308 | 99.15 260 | 94.02 347 | 99.54 117 | 99.02 305 | 94.67 330 | 99.04 217 | 99.35 274 | 92.35 289 | 99.77 177 | 98.50 145 | 97.94 228 | 99.34 190 |
|
DP-MVS | | | 99.16 79 | 98.95 99 | 99.78 48 | 99.77 52 | 99.53 85 | 99.41 178 | 99.50 125 | 97.03 236 | 99.04 217 | 99.88 19 | 97.39 123 | 99.92 84 | 98.66 120 | 99.90 24 | 99.87 13 |
|
ACMM | | 97.58 5 | 98.37 166 | 98.34 161 | 98.48 246 | 99.41 191 | 97.10 265 | 99.56 105 | 99.45 186 | 98.53 73 | 99.04 217 | 99.85 33 | 93.00 263 | 99.71 203 | 98.74 106 | 97.45 252 | 98.64 283 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
Fast-Effi-MVS+ | | | 98.70 144 | 98.43 155 | 99.51 112 | 99.51 160 | 99.28 115 | 99.52 123 | 99.47 164 | 96.11 306 | 99.01 220 | 99.34 277 | 96.20 164 | 99.84 141 | 97.88 197 | 98.82 189 | 99.39 186 |
|
nrg030 | | | 98.64 151 | 98.42 156 | 99.28 149 | 99.05 277 | 99.69 52 | 99.81 16 | 99.46 174 | 98.04 133 | 99.01 220 | 99.82 53 | 96.69 149 | 99.38 259 | 99.34 32 | 94.59 319 | 98.78 235 |
|
test_prior3 | | | 99.21 71 | 99.05 78 | 99.68 68 | 99.67 109 | 99.48 93 | 98.96 301 | 99.56 58 | 98.34 92 | 99.01 220 | 99.52 222 | 98.68 68 | 99.83 152 | 97.96 191 | 99.74 107 | 99.74 82 |
|
test_prior2 | | | | | | | | 98.96 301 | | 98.34 92 | 99.01 220 | 99.52 222 | 98.68 68 | | 97.96 191 | 99.74 107 | |
|
MAR-MVS | | | 98.86 123 | 98.63 137 | 99.54 96 | 99.37 202 | 99.66 59 | 99.45 159 | 99.54 75 | 96.61 265 | 99.01 220 | 99.40 260 | 97.09 134 | 99.86 129 | 97.68 220 | 99.53 137 | 99.10 202 |
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 |
PS-MVSNAJss | | | 98.92 118 | 98.92 101 | 98.90 195 | 98.78 311 | 98.53 199 | 99.78 26 | 99.54 75 | 98.07 127 | 99.00 225 | 99.76 112 | 99.01 19 | 99.37 262 | 99.13 53 | 97.23 261 | 98.81 232 |
|
PAPR | | | 98.63 152 | 98.34 161 | 99.51 112 | 99.40 196 | 99.03 145 | 98.80 320 | 99.36 233 | 96.33 285 | 99.00 225 | 99.12 313 | 98.46 84 | 99.84 141 | 95.23 317 | 99.37 150 | 99.66 117 |
|
D2MVS | | | 98.41 162 | 98.50 152 | 98.15 280 | 99.26 230 | 96.62 294 | 99.40 186 | 99.61 36 | 97.71 165 | 98.98 227 | 99.36 271 | 96.04 167 | 99.67 215 | 98.70 112 | 97.41 256 | 98.15 338 |
|
v10 | | | 97.85 227 | 97.52 240 | 98.86 208 | 98.99 284 | 98.67 187 | 99.75 32 | 99.41 207 | 95.70 314 | 98.98 227 | 99.41 257 | 94.75 219 | 99.23 288 | 96.01 300 | 94.63 318 | 98.67 271 |
|
miper_enhance_ethall | | | 98.16 183 | 98.08 180 | 98.41 257 | 98.96 290 | 97.72 247 | 98.45 345 | 99.32 259 | 96.95 242 | 98.97 229 | 99.17 305 | 97.06 136 | 99.22 291 | 97.86 199 | 95.99 288 | 98.29 331 |
|
UniMVSNet (Re) | | | 98.29 172 | 98.00 189 | 99.13 164 | 99.00 283 | 99.36 105 | 99.49 144 | 99.51 105 | 97.95 139 | 98.97 229 | 99.13 310 | 96.30 161 | 99.38 259 | 98.36 160 | 93.34 335 | 98.66 279 |
|
TEST9 | | | | | | 99.67 109 | 99.65 62 | 99.05 277 | 99.41 207 | 96.22 295 | 98.95 231 | 99.49 232 | 98.77 55 | 99.91 95 | | | |
|
train_agg | | | 99.02 108 | 98.77 122 | 99.77 50 | 99.67 109 | 99.65 62 | 99.05 277 | 99.41 207 | 96.28 288 | 98.95 231 | 99.49 232 | 98.76 57 | 99.91 95 | 97.63 221 | 99.72 111 | 99.75 77 |
|
RRT_test8_iter05 | | | 97.72 252 | 97.60 233 | 98.08 282 | 99.23 236 | 96.08 310 | 99.63 64 | 99.49 133 | 97.54 184 | 98.94 233 | 99.81 66 | 87.99 346 | 99.35 270 | 99.21 45 | 96.51 276 | 98.81 232 |
|
BH-RMVSNet | | | 98.41 162 | 98.08 180 | 99.40 128 | 99.41 191 | 98.83 176 | 99.30 218 | 98.77 328 | 97.70 166 | 98.94 233 | 99.65 168 | 92.91 267 | 99.74 186 | 96.52 290 | 99.55 136 | 99.64 128 |
|
test_8 | | | | | | 99.67 109 | 99.61 68 | 99.03 283 | 99.41 207 | 96.28 288 | 98.93 235 | 99.48 238 | 98.76 57 | 99.91 95 | | | |
|
3Dnovator | | 97.25 9 | 99.24 70 | 99.05 78 | 99.81 41 | 99.12 262 | 99.66 59 | 99.84 10 | 99.74 10 | 99.09 15 | 98.92 236 | 99.90 10 | 95.94 172 | 99.98 7 | 98.95 69 | 99.92 12 | 99.79 61 |
|
v7n | | | 97.87 224 | 97.52 240 | 98.92 189 | 98.76 315 | 98.58 195 | 99.84 10 | 99.46 174 | 96.20 296 | 98.91 237 | 99.70 139 | 94.89 209 | 99.44 250 | 96.03 299 | 93.89 330 | 98.75 243 |
|
JIA-IIPM | | | 97.50 275 | 97.02 286 | 98.93 187 | 98.73 317 | 97.80 243 | 99.30 218 | 98.97 309 | 91.73 351 | 98.91 237 | 94.86 364 | 95.10 202 | 99.71 203 | 97.58 225 | 97.98 227 | 99.28 194 |
|
v148 | | | 97.79 240 | 97.55 236 | 98.50 243 | 98.74 316 | 97.72 247 | 99.54 117 | 99.33 249 | 96.26 291 | 98.90 239 | 99.51 226 | 94.68 222 | 99.14 302 | 97.83 202 | 93.15 339 | 98.63 291 |
|
GA-MVS | | | 97.85 227 | 97.47 246 | 99.00 177 | 99.38 200 | 97.99 231 | 98.57 339 | 99.15 291 | 97.04 234 | 98.90 239 | 99.30 287 | 89.83 325 | 99.38 259 | 96.70 285 | 98.33 208 | 99.62 134 |
|
tpm2 | | | 97.44 280 | 97.34 269 | 97.74 307 | 99.15 260 | 94.36 344 | 99.45 159 | 98.94 312 | 93.45 344 | 98.90 239 | 99.44 247 | 91.35 308 | 99.59 234 | 97.31 247 | 98.07 226 | 99.29 193 |
|
miper_ehance_all_eth | | | 98.18 181 | 98.10 176 | 98.41 257 | 99.23 236 | 97.72 247 | 98.72 328 | 99.31 262 | 96.60 267 | 98.88 242 | 99.29 289 | 97.29 129 | 99.13 305 | 97.60 223 | 95.99 288 | 98.38 328 |
|
eth_miper_zixun_eth | | | 98.05 199 | 97.96 194 | 98.33 264 | 99.26 230 | 97.38 255 | 98.56 341 | 99.31 262 | 96.65 261 | 98.88 242 | 99.52 222 | 96.58 151 | 99.12 309 | 97.39 246 | 95.53 302 | 98.47 316 |
|
cl22 | | | 97.85 227 | 97.64 230 | 98.48 246 | 99.09 269 | 97.87 239 | 98.60 338 | 99.33 249 | 97.11 228 | 98.87 244 | 99.22 300 | 92.38 288 | 99.17 300 | 98.21 169 | 95.99 288 | 98.42 323 |
|
agg_prior1 | | | 99.01 111 | 98.76 124 | 99.76 53 | 99.67 109 | 99.62 66 | 98.99 293 | 99.40 213 | 96.26 291 | 98.87 244 | 99.49 232 | 98.77 55 | 99.91 95 | 97.69 218 | 99.72 111 | 99.75 77 |
|
agg_prior | | | | | | 99.67 109 | 99.62 66 | | 99.40 213 | | 98.87 244 | | | 99.91 95 | | | |
|
anonymousdsp | | | 98.44 158 | 98.28 166 | 98.94 185 | 98.50 337 | 98.96 157 | 99.77 28 | 99.50 125 | 97.07 231 | 98.87 244 | 99.77 108 | 94.76 218 | 99.28 281 | 98.66 120 | 97.60 237 | 98.57 308 |
|
DSMNet-mixed | | | 97.25 285 | 97.35 266 | 96.95 329 | 97.84 348 | 93.61 354 | 99.57 98 | 96.63 366 | 96.13 305 | 98.87 244 | 98.61 342 | 94.59 226 | 97.70 358 | 95.08 319 | 98.86 187 | 99.55 149 |
|
FMVSNet2 | | | 97.72 252 | 97.36 264 | 98.80 218 | 99.51 160 | 98.84 173 | 99.45 159 | 99.42 205 | 96.49 273 | 98.86 249 | 99.29 289 | 90.26 319 | 98.98 325 | 96.44 292 | 96.56 273 | 98.58 307 |
|
c3_l | | | 98.12 189 | 98.04 185 | 98.38 261 | 99.30 219 | 97.69 250 | 98.81 319 | 99.33 249 | 96.67 259 | 98.83 250 | 99.34 277 | 97.11 133 | 98.99 324 | 97.58 225 | 95.34 305 | 98.48 314 |
|
ITE_SJBPF | | | | | 98.08 282 | 99.29 223 | 96.37 301 | | 98.92 315 | 98.34 92 | 98.83 250 | 99.75 117 | 91.09 311 | 99.62 231 | 95.82 302 | 97.40 257 | 98.25 334 |
|
Anonymous20231211 | | | 97.88 222 | 97.54 239 | 98.90 195 | 99.71 94 | 98.53 199 | 99.48 150 | 99.57 52 | 94.16 335 | 98.81 252 | 99.68 155 | 93.23 259 | 99.42 255 | 98.84 92 | 94.42 322 | 98.76 241 |
|
Patchmtry | | | 97.75 246 | 97.40 260 | 98.81 216 | 99.10 267 | 98.87 169 | 99.11 268 | 99.33 249 | 94.83 327 | 98.81 252 | 99.38 265 | 94.33 235 | 99.02 320 | 96.10 297 | 95.57 300 | 98.53 310 |
|
miper_lstm_enhance | | | 98.00 209 | 97.91 200 | 98.28 272 | 99.34 209 | 97.43 254 | 98.88 312 | 99.36 233 | 96.48 277 | 98.80 254 | 99.55 210 | 95.98 168 | 98.91 336 | 97.27 249 | 95.50 303 | 98.51 312 |
|
BH-untuned | | | 98.42 160 | 98.36 158 | 98.59 232 | 99.49 172 | 96.70 290 | 99.27 229 | 99.13 294 | 97.24 215 | 98.80 254 | 99.38 265 | 95.75 180 | 99.74 186 | 97.07 265 | 99.16 160 | 99.33 191 |
|
FIs | | | 98.78 139 | 98.63 137 | 99.23 156 | 99.18 249 | 99.54 82 | 99.83 13 | 99.59 44 | 98.28 98 | 98.79 256 | 99.81 66 | 96.75 147 | 99.37 262 | 99.08 58 | 96.38 279 | 98.78 235 |
|
OurMVSNet-221017-0 | | | 97.88 222 | 97.77 215 | 98.19 276 | 98.71 321 | 96.53 296 | 99.88 2 | 99.00 306 | 97.79 156 | 98.78 257 | 99.94 3 | 91.68 300 | 99.35 270 | 97.21 253 | 96.99 268 | 98.69 259 |
|
MVS-HIRNet | | | 95.75 311 | 95.16 315 | 97.51 315 | 99.30 219 | 93.69 352 | 98.88 312 | 95.78 368 | 85.09 362 | 98.78 257 | 92.65 366 | 91.29 309 | 99.37 262 | 94.85 322 | 99.85 59 | 99.46 175 |
|
tpmvs | | | 97.98 211 | 98.02 188 | 97.84 300 | 99.04 278 | 94.73 339 | 99.31 216 | 99.20 285 | 96.10 310 | 98.76 259 | 99.42 253 | 94.94 204 | 99.81 163 | 96.97 270 | 98.45 206 | 98.97 222 |
|
Patchmatch-test | | | 97.93 216 | 97.65 228 | 98.77 221 | 99.18 249 | 97.07 269 | 99.03 283 | 99.14 293 | 96.16 301 | 98.74 260 | 99.57 204 | 94.56 228 | 99.72 197 | 93.36 338 | 99.11 165 | 99.52 157 |
|
QAPM | | | 98.67 148 | 98.30 165 | 99.80 43 | 99.20 244 | 99.67 57 | 99.77 28 | 99.72 11 | 94.74 329 | 98.73 261 | 99.90 10 | 95.78 179 | 99.98 7 | 96.96 271 | 99.88 37 | 99.76 76 |
|
3Dnovator+ | | 97.12 13 | 99.18 75 | 98.97 95 | 99.82 38 | 99.17 255 | 99.68 54 | 99.81 16 | 99.51 105 | 99.20 5 | 98.72 262 | 99.89 14 | 95.68 183 | 99.97 12 | 98.86 87 | 99.86 52 | 99.81 45 |
|
IterMVS-SCA-FT | | | 97.82 235 | 97.75 219 | 98.06 284 | 99.57 148 | 96.36 302 | 99.02 286 | 99.49 133 | 97.18 219 | 98.71 263 | 99.72 134 | 92.72 272 | 99.14 302 | 97.44 243 | 95.86 293 | 98.67 271 |
|
UniMVSNet_NR-MVSNet | | | 98.22 175 | 97.97 192 | 98.96 182 | 98.92 293 | 98.98 150 | 99.48 150 | 99.53 86 | 97.76 159 | 98.71 263 | 99.46 245 | 96.43 158 | 99.22 291 | 98.57 135 | 92.87 342 | 98.69 259 |
|
DU-MVS | | | 98.08 193 | 97.79 210 | 98.96 182 | 98.87 300 | 98.98 150 | 99.41 178 | 99.45 186 | 97.87 144 | 98.71 263 | 99.50 229 | 94.82 211 | 99.22 291 | 98.57 135 | 92.87 342 | 98.68 264 |
|
tpm cat1 | | | 97.39 281 | 97.36 264 | 97.50 316 | 99.17 255 | 93.73 350 | 99.43 169 | 99.31 262 | 91.27 352 | 98.71 263 | 99.08 314 | 94.31 237 | 99.77 177 | 96.41 294 | 98.50 204 | 99.00 218 |
|
XXY-MVS | | | 98.38 165 | 98.09 179 | 99.24 154 | 99.26 230 | 99.32 109 | 99.56 105 | 99.55 67 | 97.45 193 | 98.71 263 | 99.83 46 | 93.23 259 | 99.63 230 | 98.88 78 | 96.32 281 | 98.76 241 |
|
IterMVS | | | 97.83 232 | 97.77 215 | 98.02 287 | 99.58 146 | 96.27 305 | 99.02 286 | 99.48 146 | 97.22 217 | 98.71 263 | 99.70 139 | 92.75 269 | 99.13 305 | 97.46 240 | 96.00 287 | 98.67 271 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
FC-MVSNet-test | | | 98.75 142 | 98.62 142 | 99.15 163 | 99.08 271 | 99.45 97 | 99.86 9 | 99.60 41 | 98.23 104 | 98.70 269 | 99.82 53 | 96.80 143 | 99.22 291 | 99.07 59 | 96.38 279 | 98.79 234 |
|
COLMAP_ROB |  | 97.56 6 | 98.86 123 | 98.75 125 | 99.17 160 | 99.88 12 | 98.53 199 | 99.34 211 | 99.59 44 | 97.55 181 | 98.70 269 | 99.89 14 | 95.83 177 | 99.90 110 | 98.10 179 | 99.90 24 | 99.08 207 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
TR-MVS | | | 97.76 242 | 97.41 259 | 98.82 214 | 99.06 274 | 97.87 239 | 98.87 314 | 98.56 343 | 96.63 264 | 98.68 271 | 99.22 300 | 92.49 282 | 99.65 222 | 95.40 313 | 97.79 231 | 98.95 227 |
|
WR-MVS | | | 98.06 194 | 97.73 221 | 99.06 168 | 98.86 303 | 99.25 119 | 99.19 251 | 99.35 238 | 97.30 208 | 98.66 272 | 99.43 250 | 93.94 248 | 99.21 296 | 98.58 133 | 94.28 324 | 98.71 251 |
|
HQP-NCC | | | | | | 99.19 246 | | 98.98 297 | | 98.24 101 | 98.66 272 | | | | | | |
|
ACMP_Plane | | | | | | 99.19 246 | | 98.98 297 | | 98.24 101 | 98.66 272 | | | | | | |
|
HQP4-MVS | | | | | | | | | | | 98.66 272 | | | 99.64 225 | | | 98.64 283 |
|
HQP-MVS | | | 98.02 204 | 97.90 201 | 98.37 262 | 99.19 246 | 96.83 285 | 98.98 297 | 99.39 217 | 98.24 101 | 98.66 272 | 99.40 260 | 92.47 283 | 99.64 225 | 97.19 257 | 97.58 239 | 98.64 283 |
|
LF4IMVS | | | 97.52 272 | 97.46 248 | 97.70 309 | 98.98 287 | 95.55 319 | 99.29 222 | 98.82 327 | 98.07 127 | 98.66 272 | 99.64 175 | 89.97 324 | 99.61 232 | 97.01 266 | 96.68 269 | 97.94 350 |
|
mvs_tets | | | 98.40 164 | 98.23 168 | 98.91 193 | 98.67 325 | 98.51 205 | 99.66 52 | 99.53 86 | 98.19 108 | 98.65 278 | 99.81 66 | 92.75 269 | 99.44 250 | 99.31 35 | 97.48 251 | 98.77 239 |
|
TESTMET0.1,1 | | | 97.55 269 | 97.27 278 | 98.40 259 | 98.93 292 | 96.53 296 | 98.67 331 | 97.61 359 | 96.96 240 | 98.64 279 | 99.28 291 | 88.63 339 | 99.45 245 | 97.30 248 | 99.38 143 | 99.21 197 |
|
jajsoiax | | | 98.43 159 | 98.28 166 | 98.88 201 | 98.60 332 | 98.43 212 | 99.82 14 | 99.53 86 | 98.19 108 | 98.63 280 | 99.80 82 | 93.22 261 | 99.44 250 | 99.22 43 | 97.50 247 | 98.77 239 |
|
Baseline_NR-MVSNet | | | 97.76 242 | 97.45 249 | 98.68 228 | 99.09 269 | 98.29 217 | 99.41 178 | 98.85 324 | 95.65 315 | 98.63 280 | 99.67 161 | 94.82 211 | 99.10 312 | 98.07 187 | 92.89 341 | 98.64 283 |
|
EPNet | | | 98.86 123 | 98.71 128 | 99.30 143 | 97.20 358 | 98.18 222 | 99.62 70 | 98.91 318 | 99.28 3 | 98.63 280 | 99.81 66 | 95.96 169 | 99.99 1 | 99.24 42 | 99.72 111 | 99.73 89 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
test-LLR | | | 98.06 194 | 97.90 201 | 98.55 240 | 98.79 308 | 97.10 265 | 98.67 331 | 97.75 356 | 97.34 204 | 98.61 283 | 98.85 331 | 94.45 232 | 99.45 245 | 97.25 251 | 99.38 143 | 99.10 202 |
|
test-mter | | | 97.49 278 | 97.13 283 | 98.55 240 | 98.79 308 | 97.10 265 | 98.67 331 | 97.75 356 | 96.65 261 | 98.61 283 | 98.85 331 | 88.23 343 | 99.45 245 | 97.25 251 | 99.38 143 | 99.10 202 |
|
DIV-MVS_self_test | | | 98.01 207 | 97.85 207 | 98.48 246 | 99.24 235 | 97.95 236 | 98.71 329 | 99.35 238 | 96.50 272 | 98.60 285 | 99.54 215 | 95.72 182 | 99.03 318 | 97.21 253 | 95.77 294 | 98.46 320 |
|
cl____ | | | 98.01 207 | 97.84 208 | 98.55 240 | 99.25 234 | 97.97 232 | 98.71 329 | 99.34 242 | 96.47 279 | 98.59 286 | 99.54 215 | 95.65 185 | 99.21 296 | 97.21 253 | 95.77 294 | 98.46 320 |
|
FMVSNet1 | | | 96.84 292 | 96.36 296 | 98.29 269 | 99.32 217 | 97.26 260 | 99.43 169 | 99.48 146 | 95.11 321 | 98.55 287 | 99.32 284 | 83.95 360 | 98.98 325 | 95.81 303 | 96.26 282 | 98.62 293 |
|
UniMVSNet_ETH3D | | | 97.32 283 | 96.81 289 | 98.87 205 | 99.40 196 | 97.46 253 | 99.51 128 | 99.53 86 | 95.86 313 | 98.54 288 | 99.77 108 | 82.44 364 | 99.66 218 | 98.68 117 | 97.52 244 | 99.50 166 |
|
AUN-MVS | | | 96.88 291 | 96.31 297 | 98.59 232 | 99.48 179 | 97.04 274 | 99.27 229 | 99.22 281 | 97.44 196 | 98.51 289 | 99.41 257 | 91.97 292 | 99.66 218 | 97.71 215 | 83.83 360 | 99.07 212 |
|
PCF-MVS | | 97.08 14 | 97.66 264 | 97.06 285 | 99.47 119 | 99.61 138 | 99.09 139 | 98.04 359 | 99.25 277 | 91.24 353 | 98.51 289 | 99.70 139 | 94.55 229 | 99.91 95 | 92.76 346 | 99.85 59 | 99.42 180 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
TranMVSNet+NR-MVSNet | | | 97.93 216 | 97.66 227 | 98.76 222 | 98.78 311 | 98.62 192 | 99.65 59 | 99.49 133 | 97.76 159 | 98.49 291 | 99.60 194 | 94.23 238 | 98.97 332 | 98.00 189 | 92.90 340 | 98.70 255 |
|
CP-MVSNet | | | 98.09 191 | 97.78 213 | 99.01 175 | 98.97 289 | 99.24 120 | 99.67 48 | 99.46 174 | 97.25 213 | 98.48 292 | 99.64 175 | 93.79 252 | 99.06 314 | 98.63 123 | 94.10 327 | 98.74 247 |
|
ACMP | | 97.20 11 | 98.06 194 | 97.94 198 | 98.45 252 | 99.37 202 | 97.01 276 | 99.44 163 | 99.49 133 | 97.54 184 | 98.45 293 | 99.79 94 | 91.95 293 | 99.72 197 | 97.91 195 | 97.49 250 | 98.62 293 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
test_part1 | | | 97.75 246 | 97.24 279 | 99.29 146 | 99.59 144 | 99.63 65 | 99.65 59 | 99.49 133 | 96.17 299 | 98.44 294 | 99.69 148 | 89.80 326 | 99.47 242 | 98.68 117 | 93.66 332 | 98.78 235 |
|
MVS_0304 | | | 96.79 294 | 96.52 294 | 97.59 312 | 99.22 240 | 94.92 336 | 99.04 282 | 99.59 44 | 96.49 273 | 98.43 295 | 98.99 324 | 80.48 367 | 99.39 257 | 97.15 261 | 99.27 154 | 98.47 316 |
|
cascas | | | 97.69 258 | 97.43 257 | 98.48 246 | 98.60 332 | 97.30 256 | 98.18 357 | 99.39 217 | 92.96 347 | 98.41 296 | 98.78 336 | 93.77 253 | 99.27 284 | 98.16 176 | 98.61 195 | 98.86 229 |
|
WR-MVS_H | | | 98.13 187 | 97.87 206 | 98.90 195 | 99.02 281 | 98.84 173 | 99.70 39 | 99.59 44 | 97.27 211 | 98.40 297 | 99.19 304 | 95.53 187 | 99.23 288 | 98.34 161 | 93.78 331 | 98.61 302 |
|
BH-w/o | | | 98.00 209 | 97.89 205 | 98.32 266 | 99.35 205 | 96.20 307 | 99.01 291 | 98.90 320 | 96.42 282 | 98.38 298 | 99.00 323 | 95.26 198 | 99.72 197 | 96.06 298 | 98.61 195 | 99.03 215 |
|
pmmvs5 | | | 97.52 272 | 97.30 274 | 98.16 278 | 98.57 334 | 96.73 289 | 99.27 229 | 98.90 320 | 96.14 304 | 98.37 299 | 99.53 219 | 91.54 306 | 99.14 302 | 97.51 235 | 95.87 292 | 98.63 291 |
|
DWT-MVSNet_test | | | 97.53 271 | 97.40 260 | 97.93 294 | 99.03 280 | 94.86 337 | 99.57 98 | 98.63 341 | 96.59 269 | 98.36 300 | 98.79 334 | 89.32 331 | 99.74 186 | 98.14 178 | 98.16 223 | 99.20 198 |
|
EU-MVSNet | | | 97.98 211 | 98.03 186 | 97.81 304 | 98.72 319 | 96.65 293 | 99.66 52 | 99.66 27 | 98.09 122 | 98.35 301 | 99.82 53 | 95.25 199 | 98.01 351 | 97.41 245 | 95.30 306 | 98.78 235 |
|
FMVSNet5 | | | 96.43 301 | 96.19 299 | 97.15 322 | 99.11 264 | 95.89 313 | 99.32 214 | 99.52 92 | 94.47 334 | 98.34 302 | 99.07 315 | 87.54 351 | 97.07 362 | 92.61 347 | 95.72 297 | 98.47 316 |
|
PS-CasMVS | | | 97.93 216 | 97.59 235 | 98.95 184 | 98.99 284 | 99.06 143 | 99.68 46 | 99.52 92 | 97.13 223 | 98.31 303 | 99.68 155 | 92.44 287 | 99.05 315 | 98.51 144 | 94.08 328 | 98.75 243 |
|
USDC | | | 97.34 282 | 97.20 280 | 97.75 306 | 99.07 272 | 95.20 329 | 98.51 343 | 99.04 304 | 97.99 137 | 98.31 303 | 99.86 27 | 89.02 333 | 99.55 238 | 95.67 308 | 97.36 259 | 98.49 313 |
|
PEN-MVS | | | 97.76 242 | 97.44 254 | 98.72 225 | 98.77 314 | 98.54 198 | 99.78 26 | 99.51 105 | 97.06 233 | 98.29 305 | 99.64 175 | 92.63 278 | 98.89 338 | 98.09 180 | 93.16 338 | 98.72 249 |
|
tfpnnormal | | | 97.84 230 | 97.47 246 | 98.98 179 | 99.20 244 | 99.22 122 | 99.64 62 | 99.61 36 | 96.32 286 | 98.27 306 | 99.70 139 | 93.35 258 | 99.44 250 | 95.69 306 | 95.40 304 | 98.27 332 |
|
ppachtmachnet_test | | | 97.49 278 | 97.45 249 | 97.61 311 | 98.62 329 | 95.24 328 | 98.80 320 | 99.46 174 | 96.11 306 | 98.22 307 | 99.62 187 | 96.45 156 | 98.97 332 | 93.77 333 | 95.97 291 | 98.61 302 |
|
our_test_3 | | | 97.65 265 | 97.68 225 | 97.55 314 | 98.62 329 | 94.97 334 | 98.84 316 | 99.30 266 | 96.83 251 | 98.19 308 | 99.34 277 | 97.01 138 | 99.02 320 | 95.00 321 | 96.01 286 | 98.64 283 |
|
LTVRE_ROB | | 97.16 12 | 98.02 204 | 97.90 201 | 98.40 259 | 99.23 236 | 96.80 288 | 99.70 39 | 99.60 41 | 97.12 225 | 98.18 309 | 99.70 139 | 91.73 299 | 99.72 197 | 98.39 154 | 97.45 252 | 98.68 264 |
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 |
ACMH | | 97.28 8 | 98.10 190 | 97.99 190 | 98.44 255 | 99.41 191 | 96.96 282 | 99.60 77 | 99.56 58 | 98.09 122 | 98.15 310 | 99.91 8 | 90.87 314 | 99.70 209 | 98.88 78 | 97.45 252 | 98.67 271 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
MS-PatchMatch | | | 97.24 286 | 97.32 272 | 96.99 326 | 98.45 339 | 93.51 355 | 98.82 318 | 99.32 259 | 97.41 200 | 98.13 311 | 99.30 287 | 88.99 334 | 99.56 236 | 95.68 307 | 99.80 88 | 97.90 353 |
|
MVS | | | 97.28 284 | 96.55 293 | 99.48 116 | 98.78 311 | 98.95 159 | 99.27 229 | 99.39 217 | 83.53 363 | 98.08 312 | 99.54 215 | 96.97 139 | 99.87 126 | 94.23 329 | 99.16 160 | 99.63 132 |
|
PAPM | | | 97.59 268 | 97.09 284 | 99.07 167 | 99.06 274 | 98.26 220 | 98.30 353 | 99.10 296 | 94.88 326 | 98.08 312 | 99.34 277 | 96.27 162 | 99.64 225 | 89.87 355 | 98.92 183 | 99.31 192 |
|
OpenMVS |  | 96.50 16 | 98.47 156 | 98.12 174 | 99.52 108 | 99.04 278 | 99.53 85 | 99.82 14 | 99.72 11 | 94.56 332 | 98.08 312 | 99.88 19 | 94.73 220 | 99.98 7 | 97.47 239 | 99.76 103 | 99.06 213 |
|
gg-mvs-nofinetune | | | 96.17 306 | 95.32 314 | 98.73 223 | 98.79 308 | 98.14 225 | 99.38 195 | 94.09 374 | 91.07 355 | 98.07 315 | 91.04 369 | 89.62 330 | 99.35 270 | 96.75 281 | 99.09 169 | 98.68 264 |
|
test0.0.03 1 | | | 97.71 256 | 97.42 258 | 98.56 238 | 98.41 340 | 97.82 242 | 98.78 322 | 98.63 341 | 97.34 204 | 98.05 316 | 98.98 327 | 94.45 232 | 98.98 325 | 95.04 320 | 97.15 266 | 98.89 228 |
|
1314 | | | 98.68 147 | 98.54 151 | 99.11 165 | 98.89 295 | 98.65 189 | 99.27 229 | 99.49 133 | 96.89 246 | 97.99 317 | 99.56 207 | 97.72 118 | 99.83 152 | 97.74 211 | 99.27 154 | 98.84 231 |
|
DTE-MVSNet | | | 97.51 274 | 97.19 281 | 98.46 251 | 98.63 328 | 98.13 226 | 99.84 10 | 99.48 146 | 96.68 258 | 97.97 318 | 99.67 161 | 92.92 265 | 98.56 342 | 96.88 278 | 92.60 345 | 98.70 255 |
|
SixPastTwentyTwo | | | 97.50 275 | 97.33 271 | 98.03 285 | 98.65 326 | 96.23 306 | 99.77 28 | 98.68 340 | 97.14 222 | 97.90 319 | 99.93 4 | 90.45 317 | 99.18 299 | 97.00 267 | 96.43 278 | 98.67 271 |
|
pm-mvs1 | | | 97.68 260 | 97.28 275 | 98.88 201 | 99.06 274 | 98.62 192 | 99.50 134 | 99.45 186 | 96.32 286 | 97.87 320 | 99.79 94 | 92.47 283 | 99.35 270 | 97.54 232 | 93.54 334 | 98.67 271 |
|
testgi | | | 97.65 265 | 97.50 243 | 98.13 281 | 99.36 204 | 96.45 299 | 99.42 176 | 99.48 146 | 97.76 159 | 97.87 320 | 99.45 246 | 91.09 311 | 98.81 339 | 94.53 325 | 98.52 203 | 99.13 201 |
|
EPNet_dtu | | | 98.03 202 | 97.96 194 | 98.23 274 | 98.27 341 | 95.54 321 | 99.23 243 | 98.75 329 | 99.02 20 | 97.82 322 | 99.71 135 | 96.11 165 | 99.48 241 | 93.04 342 | 99.65 127 | 99.69 107 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
TinyColmap | | | 97.12 288 | 96.89 288 | 97.83 301 | 99.07 272 | 95.52 322 | 98.57 339 | 98.74 332 | 97.58 178 | 97.81 323 | 99.79 94 | 88.16 344 | 99.56 236 | 95.10 318 | 97.21 262 | 98.39 327 |
|
ACMH+ | | 97.24 10 | 97.92 219 | 97.78 213 | 98.32 266 | 99.46 181 | 96.68 292 | 99.56 105 | 99.54 75 | 98.41 84 | 97.79 324 | 99.87 24 | 90.18 323 | 99.66 218 | 98.05 188 | 97.18 264 | 98.62 293 |
|
N_pmnet | | | 94.95 319 | 95.83 307 | 92.31 345 | 98.47 338 | 79.33 372 | 99.12 262 | 92.81 378 | 93.87 337 | 97.68 325 | 99.13 310 | 93.87 250 | 99.01 322 | 91.38 350 | 96.19 283 | 98.59 306 |
|
KD-MVS_2432*1600 | | | 94.62 320 | 93.72 326 | 97.31 319 | 97.19 359 | 95.82 314 | 98.34 349 | 99.20 285 | 95.00 324 | 97.57 326 | 98.35 347 | 87.95 347 | 98.10 348 | 92.87 344 | 77.00 367 | 98.01 344 |
|
miper_refine_blended | | | 94.62 320 | 93.72 326 | 97.31 319 | 97.19 359 | 95.82 314 | 98.34 349 | 99.20 285 | 95.00 324 | 97.57 326 | 98.35 347 | 87.95 347 | 98.10 348 | 92.87 344 | 77.00 367 | 98.01 344 |
|
PVSNet_0 | | 94.43 19 | 96.09 308 | 95.47 311 | 97.94 293 | 99.31 218 | 94.34 345 | 97.81 361 | 99.70 15 | 97.12 225 | 97.46 328 | 98.75 337 | 89.71 327 | 99.79 171 | 97.69 218 | 81.69 363 | 99.68 111 |
|
pmmvs6 | | | 96.53 298 | 96.09 301 | 97.82 303 | 98.69 323 | 95.47 323 | 99.37 198 | 99.47 164 | 93.46 343 | 97.41 329 | 99.78 101 | 87.06 352 | 99.33 274 | 96.92 276 | 92.70 344 | 98.65 281 |
|
new_pmnet | | | 96.38 302 | 96.03 302 | 97.41 317 | 98.13 345 | 95.16 332 | 99.05 277 | 99.20 285 | 93.94 336 | 97.39 330 | 98.79 334 | 91.61 305 | 99.04 316 | 90.43 353 | 95.77 294 | 98.05 342 |
|
CL-MVSNet_self_test | | | 94.49 322 | 93.97 325 | 96.08 338 | 96.16 362 | 93.67 353 | 98.33 351 | 99.38 223 | 95.13 319 | 97.33 331 | 98.15 351 | 92.69 276 | 96.57 365 | 88.67 359 | 79.87 365 | 97.99 347 |
|
IB-MVS | | 95.67 18 | 96.22 303 | 95.44 313 | 98.57 236 | 99.21 242 | 96.70 290 | 98.65 334 | 97.74 358 | 96.71 256 | 97.27 332 | 98.54 343 | 86.03 354 | 99.92 84 | 98.47 149 | 86.30 357 | 99.10 202 |
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 |
GG-mvs-BLEND | | | | | 98.45 252 | 98.55 335 | 98.16 223 | 99.43 169 | 93.68 375 | | 97.23 333 | 98.46 344 | 89.30 332 | 99.22 291 | 95.43 312 | 98.22 214 | 97.98 348 |
|
MVP-Stereo | | | 97.81 237 | 97.75 219 | 97.99 291 | 97.53 351 | 96.60 295 | 98.96 301 | 98.85 324 | 97.22 217 | 97.23 333 | 99.36 271 | 95.28 195 | 99.46 244 | 95.51 310 | 99.78 95 | 97.92 352 |
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
Anonymous20240521 | | | 96.20 305 | 95.89 306 | 97.13 324 | 97.72 350 | 94.96 335 | 99.79 25 | 99.29 271 | 93.01 346 | 97.20 335 | 99.03 320 | 89.69 328 | 98.36 345 | 91.16 351 | 96.13 284 | 98.07 340 |
|
TransMVSNet (Re) | | | 97.15 287 | 96.58 292 | 98.86 208 | 99.12 262 | 98.85 172 | 99.49 144 | 98.91 318 | 95.48 316 | 97.16 336 | 99.80 82 | 93.38 257 | 99.11 310 | 94.16 331 | 91.73 347 | 98.62 293 |
|
KD-MVS_self_test | | | 95.00 317 | 94.34 322 | 96.96 328 | 97.07 361 | 95.39 326 | 99.56 105 | 99.44 195 | 95.11 321 | 97.13 337 | 97.32 358 | 91.86 295 | 97.27 361 | 90.35 354 | 81.23 364 | 98.23 336 |
|
NR-MVSNet | | | 97.97 214 | 97.61 232 | 99.02 174 | 98.87 300 | 99.26 118 | 99.47 155 | 99.42 205 | 97.63 174 | 97.08 338 | 99.50 229 | 95.07 203 | 99.13 305 | 97.86 199 | 93.59 333 | 98.68 264 |
|
Anonymous20231206 | | | 96.22 303 | 96.03 302 | 96.79 333 | 97.31 356 | 94.14 346 | 99.63 64 | 99.08 299 | 96.17 299 | 97.04 339 | 99.06 317 | 93.94 248 | 97.76 357 | 86.96 365 | 95.06 311 | 98.47 316 |
|
test_0402 | | | 96.64 296 | 96.24 298 | 97.85 299 | 98.85 304 | 96.43 300 | 99.44 163 | 99.26 275 | 93.52 341 | 96.98 340 | 99.52 222 | 88.52 340 | 99.20 298 | 92.58 348 | 97.50 247 | 97.93 351 |
|
MIMVSNet1 | | | 95.51 312 | 95.04 316 | 96.92 330 | 97.38 353 | 95.60 317 | 99.52 123 | 99.50 125 | 93.65 340 | 96.97 341 | 99.17 305 | 85.28 357 | 96.56 366 | 88.36 361 | 95.55 301 | 98.60 305 |
|
TDRefinement | | | 95.42 314 | 94.57 320 | 97.97 292 | 89.83 373 | 96.11 309 | 99.48 150 | 98.75 329 | 96.74 254 | 96.68 342 | 99.88 19 | 88.65 338 | 99.71 203 | 98.37 158 | 82.74 362 | 98.09 339 |
|
baseline2 | | | 97.87 224 | 97.55 236 | 98.82 214 | 99.18 249 | 98.02 229 | 99.41 178 | 96.58 367 | 96.97 239 | 96.51 343 | 99.17 305 | 93.43 256 | 99.57 235 | 97.71 215 | 99.03 174 | 98.86 229 |
|
pmmvs3 | | | 94.09 326 | 93.25 329 | 96.60 335 | 94.76 368 | 94.49 341 | 98.92 308 | 98.18 351 | 89.66 356 | 96.48 344 | 98.06 352 | 86.28 353 | 97.33 360 | 89.68 356 | 87.20 356 | 97.97 349 |
|
DeepMVS_CX |  | | | | 93.34 343 | 99.29 223 | 82.27 369 | | 99.22 281 | 85.15 361 | 96.33 345 | 99.05 318 | 90.97 313 | 99.73 193 | 93.57 336 | 97.77 232 | 98.01 344 |
|
LCM-MVSNet-Re | | | 97.83 232 | 98.15 171 | 96.87 331 | 99.30 219 | 92.25 360 | 99.59 84 | 98.26 347 | 97.43 197 | 96.20 346 | 99.13 310 | 96.27 162 | 98.73 341 | 98.17 175 | 98.99 178 | 99.64 128 |
|
test20.03 | | | 96.12 307 | 95.96 304 | 96.63 334 | 97.44 352 | 95.45 324 | 99.51 128 | 99.38 223 | 96.55 270 | 96.16 347 | 99.25 297 | 93.76 254 | 96.17 367 | 87.35 364 | 94.22 325 | 98.27 332 |
|
K. test v3 | | | 97.10 289 | 96.79 290 | 98.01 288 | 98.72 319 | 96.33 303 | 99.87 6 | 97.05 362 | 97.59 176 | 96.16 347 | 99.80 82 | 88.71 336 | 99.04 316 | 96.69 286 | 96.55 274 | 98.65 281 |
|
UnsupCasMVSNet_eth | | | 96.44 300 | 96.12 300 | 97.40 318 | 98.65 326 | 95.65 316 | 99.36 202 | 99.51 105 | 97.13 223 | 96.04 349 | 98.99 324 | 88.40 341 | 98.17 347 | 96.71 284 | 90.27 350 | 98.40 326 |
|
test_method | | | 91.10 329 | 91.36 332 | 90.31 349 | 95.85 363 | 73.72 377 | 94.89 366 | 99.25 277 | 68.39 369 | 95.82 350 | 99.02 322 | 80.50 366 | 98.95 334 | 93.64 335 | 94.89 316 | 98.25 334 |
|
lessismore_v0 | | | | | 97.79 305 | 98.69 323 | 95.44 325 | | 94.75 372 | | 95.71 351 | 99.87 24 | 88.69 337 | 99.32 276 | 95.89 301 | 94.93 315 | 98.62 293 |
|
Patchmatch-RL test | | | 95.84 310 | 95.81 308 | 95.95 339 | 95.61 364 | 90.57 364 | 98.24 354 | 98.39 346 | 95.10 323 | 95.20 352 | 98.67 339 | 94.78 214 | 97.77 356 | 96.28 296 | 90.02 351 | 99.51 163 |
|
ambc | | | | | 93.06 344 | 92.68 369 | 82.36 368 | 98.47 344 | 98.73 337 | | 95.09 353 | 97.41 355 | 55.55 373 | 99.10 312 | 96.42 293 | 91.32 348 | 97.71 354 |
|
PM-MVS | | | 92.96 328 | 92.23 331 | 95.14 341 | 95.61 364 | 89.98 366 | 99.37 198 | 98.21 349 | 94.80 328 | 95.04 354 | 97.69 353 | 65.06 370 | 97.90 354 | 94.30 327 | 89.98 352 | 97.54 358 |
|
OpenMVS_ROB |  | 92.34 20 | 94.38 324 | 93.70 328 | 96.41 337 | 97.38 353 | 93.17 356 | 99.06 275 | 98.75 329 | 86.58 360 | 94.84 355 | 98.26 350 | 81.53 365 | 99.32 276 | 89.01 358 | 97.87 230 | 96.76 360 |
|
EG-PatchMatch MVS | | | 95.97 309 | 95.69 309 | 96.81 332 | 97.78 349 | 92.79 358 | 99.16 254 | 98.93 313 | 96.16 301 | 94.08 356 | 99.22 300 | 82.72 362 | 99.47 242 | 95.67 308 | 97.50 247 | 98.17 337 |
|
pmmvs-eth3d | | | 95.34 316 | 94.73 318 | 97.15 322 | 95.53 366 | 95.94 312 | 99.35 208 | 99.10 296 | 95.13 319 | 93.55 357 | 97.54 354 | 88.15 345 | 97.91 353 | 94.58 324 | 89.69 353 | 97.61 355 |
|
new-patchmatchnet | | | 94.48 323 | 94.08 323 | 95.67 340 | 95.08 367 | 92.41 359 | 99.18 252 | 99.28 273 | 94.55 333 | 93.49 358 | 97.37 357 | 87.86 349 | 97.01 363 | 91.57 349 | 88.36 354 | 97.61 355 |
|
UnsupCasMVSNet_bld | | | 93.53 327 | 92.51 330 | 96.58 336 | 97.38 353 | 93.82 348 | 98.24 354 | 99.48 146 | 91.10 354 | 93.10 359 | 96.66 360 | 74.89 368 | 98.37 344 | 94.03 332 | 87.71 355 | 97.56 357 |
|
Gipuma |  | | 90.99 330 | 90.15 333 | 93.51 342 | 98.73 317 | 90.12 365 | 93.98 367 | 99.45 186 | 79.32 365 | 92.28 360 | 94.91 363 | 69.61 369 | 97.98 352 | 87.42 363 | 95.67 298 | 92.45 366 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
CMPMVS |  | 69.68 23 | 94.13 325 | 94.90 317 | 91.84 346 | 97.24 357 | 80.01 371 | 98.52 342 | 99.48 146 | 89.01 357 | 91.99 361 | 99.67 161 | 85.67 356 | 99.13 305 | 95.44 311 | 97.03 267 | 96.39 362 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
PMMVS2 | | | 86.87 331 | 85.37 335 | 91.35 348 | 90.21 372 | 83.80 367 | 98.89 311 | 97.45 361 | 83.13 364 | 91.67 362 | 95.03 362 | 48.49 375 | 94.70 369 | 85.86 367 | 77.62 366 | 95.54 363 |
|
LCM-MVSNet | | | 86.80 332 | 85.22 336 | 91.53 347 | 87.81 374 | 80.96 370 | 98.23 356 | 98.99 307 | 71.05 367 | 90.13 363 | 96.51 361 | 48.45 376 | 96.88 364 | 90.51 352 | 85.30 358 | 96.76 360 |
|
ET-MVSNet_ETH3D | | | 96.49 299 | 95.64 310 | 99.05 170 | 99.53 156 | 98.82 177 | 98.84 316 | 97.51 360 | 97.63 174 | 84.77 364 | 99.21 303 | 92.09 291 | 98.91 336 | 98.98 66 | 92.21 346 | 99.41 184 |
|
E-PMN | | | 80.61 336 | 79.88 338 | 82.81 353 | 90.75 371 | 76.38 375 | 97.69 362 | 95.76 369 | 66.44 371 | 83.52 365 | 92.25 367 | 62.54 372 | 87.16 373 | 68.53 372 | 61.40 370 | 84.89 371 |
|
FPMVS | | | 84.93 333 | 85.65 334 | 82.75 354 | 86.77 375 | 63.39 379 | 98.35 348 | 98.92 315 | 74.11 366 | 83.39 366 | 98.98 327 | 50.85 374 | 92.40 371 | 84.54 368 | 94.97 313 | 92.46 365 |
|
EMVS | | | 80.02 337 | 79.22 339 | 82.43 355 | 91.19 370 | 76.40 374 | 97.55 364 | 92.49 379 | 66.36 372 | 83.01 367 | 91.27 368 | 64.63 371 | 85.79 374 | 65.82 373 | 60.65 371 | 85.08 370 |
|
YYNet1 | | | 95.36 315 | 94.51 321 | 97.92 295 | 97.89 347 | 97.10 265 | 99.10 270 | 99.23 280 | 93.26 345 | 80.77 368 | 99.04 319 | 92.81 268 | 98.02 350 | 94.30 327 | 94.18 326 | 98.64 283 |
|
MDA-MVSNet_test_wron | | | 95.45 313 | 94.60 319 | 98.01 288 | 98.16 344 | 97.21 263 | 99.11 268 | 99.24 279 | 93.49 342 | 80.73 369 | 98.98 327 | 93.02 262 | 98.18 346 | 94.22 330 | 94.45 321 | 98.64 283 |
|
MDA-MVSNet-bldmvs | | | 94.96 318 | 93.98 324 | 97.92 295 | 98.24 343 | 97.27 258 | 99.15 258 | 99.33 249 | 93.80 338 | 80.09 370 | 99.03 320 | 88.31 342 | 97.86 355 | 93.49 337 | 94.36 323 | 98.62 293 |
|
tmp_tt | | | 82.80 334 | 81.52 337 | 86.66 350 | 66.61 380 | 68.44 378 | 92.79 369 | 97.92 354 | 68.96 368 | 80.04 371 | 99.85 33 | 85.77 355 | 96.15 368 | 97.86 199 | 43.89 373 | 95.39 364 |
|
MVE |  | 76.82 21 | 76.91 339 | 74.31 343 | 84.70 351 | 85.38 377 | 76.05 376 | 96.88 365 | 93.17 376 | 67.39 370 | 71.28 372 | 89.01 371 | 21.66 382 | 87.69 372 | 71.74 371 | 72.29 369 | 90.35 368 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
ANet_high | | | 77.30 338 | 74.86 342 | 84.62 352 | 75.88 378 | 77.61 373 | 97.63 363 | 93.15 377 | 88.81 358 | 64.27 373 | 89.29 370 | 36.51 377 | 83.93 375 | 75.89 370 | 52.31 372 | 92.33 367 |
|
PMVS |  | 70.75 22 | 75.98 340 | 74.97 341 | 79.01 356 | 70.98 379 | 55.18 380 | 93.37 368 | 98.21 349 | 65.08 373 | 61.78 374 | 93.83 365 | 21.74 381 | 92.53 370 | 78.59 369 | 91.12 349 | 89.34 369 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
test123 | | | 39.01 343 | 42.50 345 | 28.53 358 | 39.17 381 | 20.91 382 | 98.75 325 | 19.17 383 | 19.83 376 | 38.57 375 | 66.67 373 | 33.16 378 | 15.42 377 | 37.50 376 | 29.66 375 | 49.26 372 |
|
testmvs | | | 39.17 342 | 43.78 344 | 25.37 359 | 36.04 382 | 16.84 383 | 98.36 347 | 26.56 381 | 20.06 375 | 38.51 376 | 67.32 372 | 29.64 379 | 15.30 378 | 37.59 375 | 39.90 374 | 43.98 373 |
|
wuyk23d | | | 40.18 341 | 41.29 346 | 36.84 357 | 86.18 376 | 49.12 381 | 79.73 370 | 22.81 382 | 27.64 374 | 25.46 377 | 28.45 377 | 21.98 380 | 48.89 376 | 55.80 374 | 23.56 376 | 12.51 374 |
|
EGC-MVSNET | | | 82.80 334 | 77.86 340 | 97.62 310 | 97.91 346 | 96.12 308 | 99.33 213 | 99.28 273 | 8.40 377 | 25.05 378 | 99.27 294 | 84.11 359 | 99.33 274 | 89.20 357 | 98.22 214 | 97.42 359 |
|
test_blank | | | 0.13 347 | 0.17 350 | 0.00 360 | 0.00 383 | 0.00 384 | 0.00 371 | 0.00 384 | 0.00 378 | 0.00 379 | 1.57 378 | 0.00 383 | 0.00 379 | 0.00 377 | 0.00 377 | 0.00 375 |
|
uanet_test | | | 0.02 348 | 0.03 351 | 0.00 360 | 0.00 383 | 0.00 384 | 0.00 371 | 0.00 384 | 0.00 378 | 0.00 379 | 0.27 379 | 0.00 383 | 0.00 379 | 0.00 377 | 0.00 377 | 0.00 375 |
|
cdsmvs_eth3d_5k | | | 24.64 344 | 32.85 347 | 0.00 360 | 0.00 383 | 0.00 384 | 0.00 371 | 99.51 105 | 0.00 378 | 0.00 379 | 99.56 207 | 96.58 151 | 0.00 379 | 0.00 377 | 0.00 377 | 0.00 375 |
|
pcd_1.5k_mvsjas | | | 8.27 346 | 11.03 349 | 0.00 360 | 0.00 383 | 0.00 384 | 0.00 371 | 0.00 384 | 0.00 378 | 0.00 379 | 0.27 379 | 99.01 19 | 0.00 379 | 0.00 377 | 0.00 377 | 0.00 375 |
|
sosnet-low-res | | | 0.02 348 | 0.03 351 | 0.00 360 | 0.00 383 | 0.00 384 | 0.00 371 | 0.00 384 | 0.00 378 | 0.00 379 | 0.27 379 | 0.00 383 | 0.00 379 | 0.00 377 | 0.00 377 | 0.00 375 |
|
sosnet | | | 0.02 348 | 0.03 351 | 0.00 360 | 0.00 383 | 0.00 384 | 0.00 371 | 0.00 384 | 0.00 378 | 0.00 379 | 0.27 379 | 0.00 383 | 0.00 379 | 0.00 377 | 0.00 377 | 0.00 375 |
|
uncertanet | | | 0.02 348 | 0.03 351 | 0.00 360 | 0.00 383 | 0.00 384 | 0.00 371 | 0.00 384 | 0.00 378 | 0.00 379 | 0.27 379 | 0.00 383 | 0.00 379 | 0.00 377 | 0.00 377 | 0.00 375 |
|
Regformer | | | 0.02 348 | 0.03 351 | 0.00 360 | 0.00 383 | 0.00 384 | 0.00 371 | 0.00 384 | 0.00 378 | 0.00 379 | 0.27 379 | 0.00 383 | 0.00 379 | 0.00 377 | 0.00 377 | 0.00 375 |
|
ab-mvs-re | | | 8.30 345 | 11.06 348 | 0.00 360 | 0.00 383 | 0.00 384 | 0.00 371 | 0.00 384 | 0.00 378 | 0.00 379 | 99.58 200 | 0.00 383 | 0.00 379 | 0.00 377 | 0.00 377 | 0.00 375 |
|
uanet | | | 0.02 348 | 0.03 351 | 0.00 360 | 0.00 383 | 0.00 384 | 0.00 371 | 0.00 384 | 0.00 378 | 0.00 379 | 0.27 379 | 0.00 383 | 0.00 379 | 0.00 377 | 0.00 377 | 0.00 375 |
|
MSC_two_6792asdad | | | | | 99.87 12 | 99.51 160 | 99.76 41 | | 99.33 249 | | | | | 99.96 20 | 98.87 82 | 99.84 66 | 99.89 2 |
|
No_MVS | | | | | 99.87 12 | 99.51 160 | 99.76 41 | | 99.33 249 | | | | | 99.96 20 | 98.87 82 | 99.84 66 | 99.89 2 |
|
eth-test2 | | | | | | 0.00 383 | | | | | | | | | | | |
|
eth-test | | | | | | 0.00 383 | | | | | | | | | | | |
|
OPU-MVS | | | | | 99.64 80 | 99.56 152 | 99.72 47 | 99.60 77 | | | | 99.70 139 | 99.27 5 | 99.42 255 | 98.24 168 | 99.80 88 | 99.79 61 |
|
save fliter | | | | | | 99.76 56 | 99.59 73 | 99.14 260 | 99.40 213 | 99.00 27 | | | | | | | |
|
test_0728_SECOND | | | | | 99.91 2 | 99.84 33 | 99.89 4 | 99.57 98 | 99.51 105 | | | | | 99.96 20 | 98.93 72 | 99.86 52 | 99.88 8 |
|
GSMVS | | | | | | | | | | | | | | | | | 99.52 157 |
|
sam_mvs1 | | | | | | | | | | | | | 94.86 210 | | | | 99.52 157 |
|
sam_mvs | | | | | | | | | | | | | 94.72 221 | | | | |
|
MTGPA |  | | | | | | | | 99.47 164 | | | | | | | | |
|
test_post1 | | | | | | | | 99.23 243 | | | | 65.14 375 | 94.18 242 | 99.71 203 | 97.58 225 | | |
|
test_post | | | | | | | | | | | | 65.99 374 | 94.65 225 | 99.73 193 | | | |
|
patchmatchnet-post | | | | | | | | | | | | 98.70 338 | 94.79 213 | 99.74 186 | | | |
|
MTMP | | | | | | | | 99.54 117 | 98.88 322 | | | | | | | | |
|
gm-plane-assit | | | | | | 98.54 336 | 92.96 357 | | | 94.65 331 | | 99.15 308 | | 99.64 225 | 97.56 230 | | |
|
test9_res | | | | | | | | | | | | | | | 97.49 236 | 99.72 111 | 99.75 77 |
|
agg_prior2 | | | | | | | | | | | | | | | 97.21 253 | 99.73 110 | 99.75 77 |
|
test_prior4 | | | | | | | 99.56 78 | 98.99 293 | | | | | | | | | |
|
test_prior | | | | | 99.68 68 | 99.67 109 | 99.48 93 | | 99.56 58 | | | | | 99.83 152 | | | 99.74 82 |
|
新几何2 | | | | | | | | 99.01 291 | | | | | | | | | |
|
旧先验1 | | | | | | 99.74 75 | 99.59 73 | | 99.54 75 | | | 99.69 148 | 98.47 83 | | | 99.68 122 | 99.73 89 |
|
无先验 | | | | | | | | 98.99 293 | 99.51 105 | 96.89 246 | | | | 99.93 73 | 97.53 233 | | 99.72 95 |
|
原ACMM2 | | | | | | | | 98.95 305 | | | | | | | | | |
|
testdata2 | | | | | | | | | | | | | | 99.95 47 | 96.67 287 | | |
|
segment_acmp | | | | | | | | | | | | | 98.96 29 | | | | |
|
testdata1 | | | | | | | | 98.85 315 | | 98.32 96 | | | | | | | |
|
plane_prior7 | | | | | | 99.29 223 | 97.03 275 | | | | | | | | | | |
|
plane_prior6 | | | | | | 99.27 228 | 96.98 279 | | | | | | 92.71 274 | | | | |
|
plane_prior5 | | | | | | | | | 99.47 164 | | | | | 99.69 213 | 97.78 206 | 97.63 234 | 98.67 271 |
|
plane_prior4 | | | | | | | | | | | | 99.61 191 | | | | | |
|
plane_prior2 | | | | | | | | 99.39 190 | | 98.97 36 | | | | | | | |
|
plane_prior1 | | | | | | 99.26 230 | | | | | | | | | | | |
|
plane_prior | | | | | | | 96.97 280 | 99.21 250 | | 98.45 80 | | | | | | 97.60 237 | |
|
n2 | | | | | | | | | 0.00 384 | | | | | | | | |
|
nn | | | | | | | | | 0.00 384 | | | | | | | | |
|
door-mid | | | | | | | | | 98.05 352 | | | | | | | | |
|
test11 | | | | | | | | | 99.35 238 | | | | | | | | |
|
door | | | | | | | | | 97.92 354 | | | | | | | | |
|
HQP5-MVS | | | | | | | 96.83 285 | | | | | | | | | | |
|
BP-MVS | | | | | | | | | | | | | | | 97.19 257 | | |
|
HQP3-MVS | | | | | | | | | 99.39 217 | | | | | | | 97.58 239 | |
|
HQP2-MVS | | | | | | | | | | | | | 92.47 283 | | | | |
|
NP-MVS | | | | | | 99.23 236 | 96.92 283 | | | | | 99.40 260 | | | | | |
|
ACMMP++_ref | | | | | | | | | | | | | | | | 97.19 263 | |
|
ACMMP++ | | | | | | | | | | | | | | | | 97.43 255 | |
|
Test By Simon | | | | | | | | | | | | | 98.75 60 | | | | |
|