zzz-MVS | | | 98.55 24 | 98.25 30 | 99.46 8 | 99.76 1 | 98.64 11 | 98.55 159 | 98.74 82 | 97.27 25 | 98.02 67 | 99.39 8 | 94.81 57 | 99.96 1 | 97.91 30 | 99.79 11 | 99.77 14 |
|
MTAPA | | | 98.58 19 | 98.29 27 | 99.46 8 | 99.76 1 | 98.64 11 | 98.90 77 | 98.74 82 | 97.27 25 | 98.02 67 | 99.39 8 | 94.81 57 | 99.96 1 | 97.91 30 | 99.79 11 | 99.77 14 |
|
HSP-MVS | | | 98.70 5 | 98.52 8 | 99.24 27 | 99.75 3 | 98.23 31 | 99.26 18 | 98.58 123 | 97.52 7 | 99.41 3 | 98.78 90 | 96.00 26 | 99.79 74 | 97.79 39 | 99.59 55 | 99.69 38 |
|
MP-MVS | | | 98.33 40 | 98.01 41 | 99.28 22 | 99.75 3 | 98.18 36 | 99.22 29 | 98.79 72 | 96.13 64 | 97.92 77 | 99.23 32 | 94.54 62 | 99.94 3 | 96.74 84 | 99.78 15 | 99.73 30 |
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo. |
mPP-MVS | | | 98.51 28 | 98.26 29 | 99.25 26 | 99.75 3 | 98.04 42 | 99.28 17 | 98.81 63 | 96.24 60 | 98.35 55 | 99.23 32 | 95.46 41 | 99.94 3 | 97.42 57 | 99.81 8 | 99.77 14 |
|
HPM-MVS_fast | | | 98.38 34 | 98.13 37 | 99.12 42 | 99.75 3 | 97.86 49 | 99.44 4 | 98.82 60 | 94.46 140 | 98.94 24 | 99.20 38 | 95.16 51 | 99.74 90 | 97.58 49 | 99.85 2 | 99.77 14 |
|
region2R | | | 98.61 14 | 98.38 17 | 99.29 20 | 99.74 7 | 98.16 37 | 99.23 23 | 98.93 36 | 96.15 62 | 98.94 24 | 99.17 42 | 95.91 31 | 99.94 3 | 97.55 52 | 99.79 11 | 99.78 7 |
|
ACMMPR | | | 98.59 17 | 98.36 19 | 99.29 20 | 99.74 7 | 98.15 38 | 99.23 23 | 98.95 33 | 96.10 67 | 98.93 28 | 99.19 41 | 95.70 36 | 99.94 3 | 97.62 47 | 99.79 11 | 99.78 7 |
|
HPM-MVS | | | 98.36 36 | 98.10 38 | 99.13 40 | 99.74 7 | 97.82 52 | 99.53 1 | 98.80 70 | 94.63 133 | 98.61 43 | 98.97 68 | 95.13 52 | 99.77 84 | 97.65 46 | 99.83 7 | 99.79 4 |
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023 |
ACMMP | | | 98.23 43 | 97.95 43 | 99.09 44 | 99.74 7 | 97.62 58 | 99.03 62 | 99.41 6 | 95.98 69 | 97.60 95 | 99.36 17 | 94.45 67 | 99.93 9 | 97.14 63 | 98.85 100 | 99.70 37 |
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 |
MP-MVS-pluss | | | 98.31 41 | 97.92 44 | 99.49 6 | 99.72 11 | 98.88 7 | 98.43 177 | 98.78 74 | 94.10 146 | 97.69 89 | 99.42 6 | 95.25 48 | 99.92 15 | 98.09 24 | 99.80 10 | 99.67 49 |
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
HFP-MVS | | | 98.63 13 | 98.40 14 | 99.32 18 | 99.72 11 | 98.29 28 | 99.23 23 | 98.96 31 | 96.10 67 | 98.94 24 | 99.17 42 | 96.06 23 | 99.92 15 | 97.62 47 | 99.78 15 | 99.75 22 |
|
#test# | | | 98.54 26 | 98.27 28 | 99.32 18 | 99.72 11 | 98.29 28 | 98.98 69 | 98.96 31 | 95.65 80 | 98.94 24 | 99.17 42 | 96.06 23 | 99.92 15 | 97.21 62 | 99.78 15 | 99.75 22 |
|
PGM-MVS | | | 98.49 29 | 98.23 34 | 99.27 25 | 99.72 11 | 98.08 41 | 98.99 66 | 99.49 5 | 95.43 88 | 99.03 18 | 99.32 21 | 95.56 38 | 99.94 3 | 96.80 82 | 99.77 20 | 99.78 7 |
|
XVS | | | 98.70 5 | 98.49 12 | 99.34 15 | 99.70 15 | 98.35 25 | 99.29 15 | 98.88 47 | 97.40 14 | 98.46 48 | 99.20 38 | 95.90 32 | 99.89 29 | 97.85 35 | 99.74 35 | 99.78 7 |
|
X-MVStestdata | | | 94.06 250 | 92.30 270 | 99.34 15 | 99.70 15 | 98.35 25 | 99.29 15 | 98.88 47 | 97.40 14 | 98.46 48 | 43.50 359 | 95.90 32 | 99.89 29 | 97.85 35 | 99.74 35 | 99.78 7 |
|
TSAR-MVS + MP. | | | 98.78 3 | 98.62 4 | 99.24 27 | 99.69 17 | 98.28 30 | 99.14 45 | 98.66 110 | 96.84 43 | 99.56 2 | 99.31 22 | 96.34 13 | 99.70 96 | 98.32 20 | 99.73 37 | 99.73 30 |
|
CSCG | | | 97.85 54 | 97.74 48 | 98.20 96 | 99.67 18 | 95.16 164 | 99.22 29 | 99.32 7 | 93.04 202 | 97.02 113 | 98.92 79 | 95.36 44 | 99.91 24 | 97.43 56 | 99.64 48 | 99.52 69 |
|
CP-MVS | | | 98.57 21 | 98.36 19 | 99.19 30 | 99.66 19 | 97.86 49 | 99.34 11 | 98.87 50 | 95.96 70 | 98.60 44 | 99.13 47 | 96.05 25 | 99.94 3 | 97.77 40 | 99.86 1 | 99.77 14 |
|
CPTT-MVS | | | 97.72 58 | 97.32 65 | 98.92 55 | 99.64 20 | 97.10 76 | 99.12 50 | 98.81 63 | 92.34 233 | 98.09 61 | 99.08 57 | 93.01 83 | 99.92 15 | 96.06 106 | 99.77 20 | 99.75 22 |
|
test_part2 | | | | | | 99.63 21 | 99.18 1 | | | | 99.27 7 | | | | | | |
|
ESAPD | | | 98.70 5 | 98.39 15 | 99.62 1 | 99.63 21 | 99.18 1 | 98.55 159 | 98.84 55 | 96.40 57 | 99.27 7 | 99.31 22 | 97.38 2 | 99.93 9 | 96.37 98 | 99.78 15 | 99.76 20 |
|
ACMMP_Plus | | | 98.61 14 | 98.30 26 | 99.55 3 | 99.62 23 | 98.95 6 | 98.82 99 | 98.81 63 | 95.80 74 | 99.16 15 | 99.47 5 | 95.37 43 | 99.92 15 | 97.89 33 | 99.75 32 | 99.79 4 |
|
MCST-MVS | | | 98.65 10 | 98.37 18 | 99.48 7 | 99.60 24 | 98.87 8 | 98.41 179 | 98.68 100 | 97.04 38 | 98.52 47 | 98.80 88 | 96.78 6 | 99.83 47 | 97.93 29 | 99.61 51 | 99.74 28 |
|
APDe-MVS | | | 99.02 1 | 98.84 1 | 99.55 3 | 99.57 25 | 98.96 5 | 99.39 5 | 98.93 36 | 97.38 17 | 99.41 3 | 99.54 1 | 96.66 7 | 99.84 46 | 98.86 2 | 99.85 2 | 99.87 1 |
|
abl_6 | | | 98.30 42 | 98.03 40 | 99.13 40 | 99.56 26 | 97.76 54 | 99.13 48 | 98.82 60 | 96.14 63 | 99.26 9 | 99.37 13 | 93.33 79 | 99.93 9 | 96.96 69 | 99.67 42 | 99.69 38 |
|
DP-MVS Recon | | | 97.86 53 | 97.46 60 | 99.06 47 | 99.53 27 | 98.35 25 | 98.33 186 | 98.89 44 | 92.62 216 | 98.05 63 | 98.94 76 | 95.34 45 | 99.65 104 | 96.04 107 | 99.42 78 | 99.19 111 |
|
APD-MVS | | | 98.35 37 | 98.00 42 | 99.42 11 | 99.51 28 | 98.72 10 | 98.80 108 | 98.82 60 | 94.52 136 | 99.23 11 | 99.25 31 | 95.54 40 | 99.80 62 | 96.52 92 | 99.77 20 | 99.74 28 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
HPM-MVS++ | | | 98.58 19 | 98.25 30 | 99.55 3 | 99.50 29 | 99.08 3 | 98.72 129 | 98.66 110 | 97.51 8 | 98.15 58 | 98.83 85 | 95.70 36 | 99.92 15 | 97.53 54 | 99.67 42 | 99.66 51 |
|
APD-MVS_3200maxsize | | | 98.53 27 | 98.33 25 | 99.15 39 | 99.50 29 | 97.92 48 | 99.15 44 | 98.81 63 | 96.24 60 | 99.20 13 | 99.37 13 | 95.30 46 | 99.80 62 | 97.73 42 | 99.67 42 | 99.72 33 |
|
114514_t | | | 96.93 98 | 96.27 109 | 98.92 55 | 99.50 29 | 97.63 57 | 98.85 93 | 98.90 42 | 84.80 332 | 97.77 82 | 99.11 49 | 92.84 84 | 99.66 103 | 94.85 143 | 99.77 20 | 99.47 80 |
|
PAPM_NR | | | 97.46 69 | 97.11 74 | 98.50 78 | 99.50 29 | 96.41 105 | 98.63 146 | 98.60 117 | 95.18 107 | 97.06 110 | 98.06 154 | 94.26 71 | 99.57 120 | 93.80 171 | 98.87 99 | 99.52 69 |
|
SMA-MVS | | | 98.57 21 | 98.24 32 | 99.56 2 | 99.48 33 | 99.04 4 | 98.95 72 | 98.80 70 | 93.67 176 | 99.37 5 | 99.50 3 | 96.52 11 | 99.89 29 | 98.06 25 | 99.81 8 | 99.75 22 |
|
CDPH-MVS | | | 97.94 49 | 97.49 58 | 99.28 22 | 99.47 34 | 98.44 17 | 97.91 235 | 98.67 107 | 92.57 219 | 98.77 35 | 98.85 83 | 95.93 30 | 99.72 91 | 95.56 126 | 99.69 41 | 99.68 44 |
|
EI-MVSNet-Vis-set | | | 98.47 30 | 98.39 15 | 98.69 64 | 99.46 35 | 96.49 101 | 98.30 193 | 98.69 97 | 97.21 28 | 98.84 30 | 99.36 17 | 95.41 42 | 99.78 79 | 98.62 6 | 99.65 46 | 99.80 3 |
|
EI-MVSNet-UG-set | | | 98.41 32 | 98.34 22 | 98.61 69 | 99.45 36 | 96.32 109 | 98.28 195 | 98.68 100 | 97.17 31 | 98.74 37 | 99.37 13 | 95.25 48 | 99.79 74 | 98.57 8 | 99.54 67 | 99.73 30 |
|
F-COLMAP | | | 97.09 93 | 96.80 85 | 97.97 110 | 99.45 36 | 94.95 176 | 98.55 159 | 98.62 116 | 93.02 203 | 96.17 162 | 98.58 110 | 94.01 74 | 99.81 55 | 93.95 167 | 98.90 96 | 99.14 120 |
|
Regformer-3 | | | 98.59 17 | 98.50 11 | 98.86 59 | 99.43 38 | 97.05 77 | 98.40 180 | 98.68 100 | 97.43 13 | 99.06 17 | 99.31 22 | 95.80 35 | 99.77 84 | 98.62 6 | 99.76 26 | 99.78 7 |
|
Regformer-4 | | | 98.64 11 | 98.53 7 | 98.99 49 | 99.43 38 | 97.37 66 | 98.40 180 | 98.79 72 | 97.46 12 | 99.09 16 | 99.31 22 | 95.86 34 | 99.80 62 | 98.64 4 | 99.76 26 | 99.79 4 |
|
Regformer-1 | | | 98.66 9 | 98.51 10 | 99.12 42 | 99.35 40 | 97.81 53 | 98.37 182 | 98.76 78 | 97.49 10 | 99.20 13 | 99.21 35 | 96.08 22 | 99.79 74 | 98.42 16 | 99.73 37 | 99.75 22 |
|
Regformer-2 | | | 98.69 8 | 98.52 8 | 99.19 30 | 99.35 40 | 98.01 44 | 98.37 182 | 98.81 63 | 97.48 11 | 99.21 12 | 99.21 35 | 96.13 19 | 99.80 62 | 98.40 18 | 99.73 37 | 99.75 22 |
|
新几何1 | | | | | 99.16 37 | 99.34 42 | 98.01 44 | | 98.69 97 | 90.06 285 | 98.13 59 | 98.95 75 | 94.60 61 | 99.89 29 | 91.97 222 | 99.47 72 | 99.59 64 |
|
1121 | | | 97.37 80 | 96.77 91 | 99.16 37 | 99.34 42 | 97.99 47 | 98.19 205 | 98.68 100 | 90.14 284 | 98.01 70 | 98.97 68 | 94.80 59 | 99.87 38 | 93.36 180 | 99.46 75 | 99.61 59 |
|
DP-MVS | | | 96.59 110 | 95.93 119 | 98.57 71 | 99.34 42 | 96.19 113 | 98.70 133 | 98.39 158 | 89.45 302 | 94.52 189 | 99.35 19 | 91.85 105 | 99.85 43 | 92.89 199 | 98.88 97 | 99.68 44 |
|
SD-MVS | | | 98.64 11 | 98.68 3 | 98.53 76 | 99.33 45 | 98.36 24 | 98.90 77 | 98.85 54 | 97.28 21 | 99.72 1 | 99.39 8 | 96.63 9 | 97.60 305 | 98.17 23 | 99.85 2 | 99.64 56 |
|
HyFIR lowres test | | | 96.90 100 | 96.49 103 | 98.14 99 | 99.33 45 | 95.56 149 | 97.38 274 | 99.65 2 | 92.34 233 | 97.61 94 | 98.20 145 | 89.29 145 | 99.10 173 | 96.97 67 | 97.60 148 | 99.77 14 |
|
OMC-MVS | | | 97.55 68 | 97.34 64 | 98.20 96 | 99.33 45 | 95.92 134 | 98.28 195 | 98.59 118 | 95.52 85 | 97.97 73 | 99.10 51 | 93.28 81 | 99.49 132 | 95.09 140 | 98.88 97 | 99.19 111 |
|
原ACMM1 | | | | | 98.65 67 | 99.32 48 | 96.62 92 | | 98.67 107 | 93.27 197 | 97.81 81 | 98.97 68 | 95.18 50 | 99.83 47 | 93.84 169 | 99.46 75 | 99.50 74 |
|
CNVR-MVS | | | 98.78 3 | 98.56 6 | 99.45 10 | 99.32 48 | 98.87 8 | 98.47 172 | 98.81 63 | 97.72 4 | 98.76 36 | 99.16 45 | 97.05 4 | 99.78 79 | 98.06 25 | 99.66 45 | 99.69 38 |
|
TEST9 | | | | | | 99.31 50 | 98.50 15 | 97.92 232 | 98.73 87 | 92.63 215 | 97.74 85 | 98.68 99 | 96.20 15 | 99.80 62 | | | |
|
train_agg | | | 97.97 46 | 97.52 56 | 99.33 17 | 99.31 50 | 98.50 15 | 97.92 232 | 98.73 87 | 92.98 205 | 97.74 85 | 98.68 99 | 96.20 15 | 99.80 62 | 96.59 88 | 99.57 58 | 99.68 44 |
|
test_prior3 | | | 98.22 44 | 97.90 45 | 99.19 30 | 99.31 50 | 98.22 33 | 97.80 248 | 98.84 55 | 96.12 65 | 97.89 79 | 98.69 97 | 95.96 28 | 99.70 96 | 96.89 73 | 99.60 52 | 99.65 53 |
|
test_prior | | | | | 99.19 30 | 99.31 50 | 98.22 33 | | 98.84 55 | | | | | 99.70 96 | | | 99.65 53 |
|
PatchMatch-RL | | | 96.59 110 | 96.03 117 | 98.27 92 | 99.31 50 | 96.51 100 | 97.91 235 | 99.06 21 | 93.72 168 | 96.92 119 | 98.06 154 | 88.50 182 | 99.65 104 | 91.77 228 | 99.00 93 | 98.66 154 |
|
agg_prior1 | | | 97.95 48 | 97.51 57 | 99.28 22 | 99.30 55 | 98.38 20 | 97.81 247 | 98.72 89 | 93.16 199 | 97.57 97 | 98.66 102 | 96.14 18 | 99.81 55 | 96.63 87 | 99.56 64 | 99.66 51 |
|
agg_prior | | | | | | 99.30 55 | 98.38 20 | | 98.72 89 | | 97.57 97 | | | 99.81 55 | | | |
|
CHOSEN 1792x2688 | | | 97.12 91 | 96.80 85 | 98.08 105 | 99.30 55 | 94.56 216 | 98.05 221 | 99.71 1 | 93.57 180 | 97.09 106 | 98.91 80 | 88.17 187 | 99.89 29 | 96.87 79 | 99.56 64 | 99.81 2 |
|
test_8 | | | | | | 99.29 58 | 98.44 17 | 97.89 240 | 98.72 89 | 92.98 205 | 97.70 88 | 98.66 102 | 96.20 15 | 99.80 62 | | | |
|
agg_prior3 | | | 97.87 52 | 97.42 62 | 99.23 29 | 99.29 58 | 98.23 31 | 97.92 232 | 98.72 89 | 92.38 232 | 97.59 96 | 98.64 104 | 96.09 21 | 99.79 74 | 96.59 88 | 99.57 58 | 99.68 44 |
|
旧先验1 | | | | | | 99.29 58 | 97.48 62 | | 98.70 96 | | | 99.09 55 | 95.56 38 | | | 99.47 72 | 99.61 59 |
|
PLC | | 95.07 4 | 97.20 87 | 96.78 88 | 98.44 83 | 99.29 58 | 96.31 111 | 98.14 211 | 98.76 78 | 92.41 230 | 96.39 158 | 98.31 136 | 94.92 56 | 99.78 79 | 94.06 165 | 98.77 104 | 99.23 107 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
COLMAP_ROB | | 93.27 12 | 95.33 174 | 94.87 165 | 96.71 191 | 99.29 58 | 93.24 254 | 98.58 152 | 98.11 209 | 89.92 290 | 93.57 237 | 99.10 51 | 86.37 227 | 99.79 74 | 90.78 245 | 98.10 131 | 97.09 213 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
NCCC | | | 98.61 14 | 98.35 21 | 99.38 12 | 99.28 63 | 98.61 13 | 98.45 173 | 98.76 78 | 97.82 3 | 98.45 51 | 98.93 77 | 96.65 8 | 99.83 47 | 97.38 59 | 99.41 79 | 99.71 35 |
|
PVSNet_Blended_VisFu | | | 97.70 59 | 97.46 60 | 98.44 83 | 99.27 64 | 95.91 136 | 98.63 146 | 99.16 17 | 94.48 139 | 97.67 90 | 98.88 81 | 92.80 85 | 99.91 24 | 97.11 64 | 99.12 90 | 99.50 74 |
|
MVS_111021_LR | | | 98.34 38 | 98.23 34 | 98.67 66 | 99.27 64 | 96.90 83 | 97.95 230 | 99.58 3 | 97.14 33 | 98.44 52 | 99.01 65 | 95.03 54 | 99.62 111 | 97.91 30 | 99.75 32 | 99.50 74 |
|
MSLP-MVS++ | | | 98.56 23 | 98.57 5 | 98.55 73 | 99.26 66 | 96.80 86 | 98.71 130 | 99.05 23 | 97.28 21 | 98.84 30 | 99.28 28 | 96.47 12 | 99.40 138 | 98.52 14 | 99.70 40 | 99.47 80 |
|
AllTest | | | 95.24 179 | 94.65 179 | 96.99 176 | 99.25 67 | 93.21 255 | 98.59 150 | 98.18 190 | 91.36 259 | 93.52 239 | 98.77 92 | 84.67 260 | 99.72 91 | 89.70 272 | 97.87 138 | 98.02 181 |
|
TestCases | | | | | 96.99 176 | 99.25 67 | 93.21 255 | | 98.18 190 | 91.36 259 | 93.52 239 | 98.77 92 | 84.67 260 | 99.72 91 | 89.70 272 | 97.87 138 | 98.02 181 |
|
PVSNet_BlendedMVS | | | 96.73 105 | 96.60 98 | 97.12 169 | 99.25 67 | 95.35 158 | 98.26 197 | 99.26 8 | 94.28 142 | 97.94 75 | 97.46 201 | 92.74 86 | 99.81 55 | 96.88 76 | 93.32 237 | 96.20 298 |
|
PVSNet_Blended | | | 97.38 79 | 97.12 72 | 98.14 99 | 99.25 67 | 95.35 158 | 97.28 284 | 99.26 8 | 93.13 200 | 97.94 75 | 98.21 144 | 92.74 86 | 99.81 55 | 96.88 76 | 99.40 81 | 99.27 103 |
|
DeepC-MVS | | 95.98 3 | 97.88 51 | 97.58 52 | 98.77 61 | 99.25 67 | 96.93 81 | 98.83 97 | 98.75 81 | 96.96 41 | 96.89 121 | 99.50 3 | 90.46 130 | 99.87 38 | 97.84 37 | 99.76 26 | 99.52 69 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
DeepC-MVS_fast | | 96.70 1 | 98.55 24 | 98.34 22 | 99.18 34 | 99.25 67 | 98.04 42 | 98.50 169 | 98.78 74 | 97.72 4 | 98.92 29 | 99.28 28 | 95.27 47 | 99.82 53 | 97.55 52 | 99.77 20 | 99.69 38 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
test222 | | | | | | 99.23 73 | 97.17 75 | 97.40 272 | 98.66 110 | 88.68 309 | 98.05 63 | 98.96 73 | 94.14 72 | | | 99.53 68 | 99.61 59 |
|
TSAR-MVS + GP. | | | 98.38 34 | 98.24 32 | 98.81 60 | 99.22 74 | 97.25 72 | 98.11 216 | 98.29 172 | 97.19 30 | 98.99 23 | 99.02 61 | 96.22 14 | 99.67 102 | 98.52 14 | 98.56 113 | 99.51 72 |
|
SteuartSystems-ACMMP | | | 98.90 2 | 98.75 2 | 99.36 14 | 99.22 74 | 98.43 19 | 99.10 52 | 98.87 50 | 97.38 17 | 99.35 6 | 99.40 7 | 97.78 1 | 99.87 38 | 97.77 40 | 99.85 2 | 99.78 7 |
Skip Steuart: Steuart Systems R&D Blog. |
MVS_111021_HR | | | 98.47 30 | 98.34 22 | 98.88 58 | 99.22 74 | 97.32 67 | 97.91 235 | 99.58 3 | 97.20 29 | 98.33 56 | 99.00 66 | 95.99 27 | 99.64 106 | 98.05 27 | 99.76 26 | 99.69 38 |
|
testdata | | | | | 98.26 93 | 99.20 77 | 95.36 156 | | 98.68 100 | 91.89 244 | 98.60 44 | 99.10 51 | 94.44 68 | 99.82 53 | 94.27 160 | 99.44 77 | 99.58 66 |
|
PVSNet | | 91.96 18 | 96.35 118 | 96.15 113 | 96.96 179 | 99.17 78 | 92.05 268 | 96.08 321 | 98.68 100 | 93.69 172 | 97.75 84 | 97.80 179 | 88.86 160 | 99.69 100 | 94.26 161 | 99.01 92 | 99.15 118 |
|
test12 | | | | | 99.18 34 | 99.16 79 | 98.19 35 | | 98.53 131 | | 98.07 62 | | 95.13 52 | 99.72 91 | | 99.56 64 | 99.63 58 |
|
AdaColmap | | | 97.15 90 | 96.70 93 | 98.48 80 | 99.16 79 | 96.69 91 | 98.01 225 | 98.89 44 | 94.44 141 | 96.83 123 | 98.68 99 | 90.69 128 | 99.76 86 | 94.36 156 | 99.29 86 | 98.98 135 |
|
PHI-MVS | | | 98.34 38 | 98.06 39 | 99.18 34 | 99.15 81 | 98.12 40 | 99.04 61 | 99.09 19 | 93.32 194 | 98.83 32 | 99.10 51 | 96.54 10 | 99.83 47 | 97.70 44 | 99.76 26 | 99.59 64 |
|
TAPA-MVS | | 93.98 7 | 95.35 172 | 94.56 183 | 97.74 123 | 99.13 82 | 94.83 194 | 98.33 186 | 98.64 115 | 86.62 318 | 96.29 160 | 98.61 105 | 94.00 75 | 99.29 147 | 80.00 332 | 99.41 79 | 99.09 125 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
MG-MVS | | | 97.81 55 | 97.60 51 | 98.44 83 | 99.12 83 | 95.97 120 | 97.75 252 | 98.78 74 | 96.89 42 | 98.46 48 | 99.22 34 | 93.90 76 | 99.68 101 | 94.81 146 | 99.52 69 | 99.67 49 |
|
Anonymous20231211 | | | 94.10 246 | 93.26 255 | 96.61 208 | 99.11 84 | 94.28 226 | 99.01 64 | 98.88 47 | 86.43 320 | 92.81 259 | 97.57 196 | 81.66 294 | 98.68 217 | 94.83 144 | 89.02 284 | 96.88 233 |
|
view600 | | | 95.60 147 | 94.93 159 | 97.62 136 | 99.05 85 | 94.85 183 | 99.09 53 | 97.01 293 | 95.36 95 | 96.52 143 | 97.37 206 | 84.55 263 | 99.59 113 | 89.07 283 | 96.39 171 | 98.40 166 |
|
view800 | | | 95.60 147 | 94.93 159 | 97.62 136 | 99.05 85 | 94.85 183 | 99.09 53 | 97.01 293 | 95.36 95 | 96.52 143 | 97.37 206 | 84.55 263 | 99.59 113 | 89.07 283 | 96.39 171 | 98.40 166 |
|
conf0.05thres1000 | | | 95.60 147 | 94.93 159 | 97.62 136 | 99.05 85 | 94.85 183 | 99.09 53 | 97.01 293 | 95.36 95 | 96.52 143 | 97.37 206 | 84.55 263 | 99.59 113 | 89.07 283 | 96.39 171 | 98.40 166 |
|
tfpn | | | 95.60 147 | 94.93 159 | 97.62 136 | 99.05 85 | 94.85 183 | 99.09 53 | 97.01 293 | 95.36 95 | 96.52 143 | 97.37 206 | 84.55 263 | 99.59 113 | 89.07 283 | 96.39 171 | 98.40 166 |
|
CNLPA | | | 97.45 72 | 97.03 78 | 98.73 62 | 99.05 85 | 97.44 65 | 98.07 220 | 98.53 131 | 95.32 101 | 96.80 127 | 98.53 112 | 93.32 80 | 99.72 91 | 94.31 159 | 99.31 85 | 99.02 131 |
|
Anonymous20240529 | | | 95.10 185 | 94.22 197 | 97.75 122 | 99.01 90 | 94.26 228 | 98.87 85 | 98.83 59 | 85.79 327 | 96.64 131 | 98.97 68 | 78.73 312 | 99.85 43 | 96.27 100 | 94.89 208 | 99.12 122 |
|
Anonymous202405211 | | | 95.28 177 | 94.49 185 | 97.67 132 | 99.00 91 | 93.75 242 | 98.70 133 | 97.04 289 | 90.66 274 | 96.49 154 | 98.80 88 | 78.13 315 | 99.83 47 | 96.21 103 | 95.36 205 | 99.44 87 |
|
tfpn1000 | | | 95.72 138 | 95.11 149 | 97.58 142 | 99.00 91 | 95.73 144 | 99.24 21 | 95.49 335 | 94.08 147 | 96.87 122 | 97.45 203 | 85.81 243 | 99.30 144 | 91.78 227 | 96.22 188 | 97.71 194 |
|
DELS-MVS | | | 98.40 33 | 98.20 36 | 98.99 49 | 99.00 91 | 97.66 55 | 97.75 252 | 98.89 44 | 97.71 6 | 98.33 56 | 98.97 68 | 94.97 55 | 99.88 37 | 98.42 16 | 99.76 26 | 99.42 89 |
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 |
DeepPCF-MVS | | 96.37 2 | 97.93 50 | 98.48 13 | 96.30 238 | 99.00 91 | 89.54 302 | 97.43 271 | 98.87 50 | 98.16 2 | 99.26 9 | 99.38 12 | 96.12 20 | 99.64 106 | 98.30 21 | 99.77 20 | 99.72 33 |
|
tfpn111 | | | 95.43 162 | 94.74 175 | 97.51 146 | 98.98 95 | 94.92 177 | 98.87 85 | 96.90 301 | 95.38 91 | 96.61 133 | 96.88 263 | 84.29 270 | 99.59 113 | 88.43 293 | 96.32 177 | 98.02 181 |
|
conf200view11 | | | 95.40 167 | 94.70 177 | 97.50 151 | 98.98 95 | 94.92 177 | 98.87 85 | 96.90 301 | 95.38 91 | 96.61 133 | 96.88 263 | 84.29 270 | 99.56 122 | 88.11 299 | 96.29 179 | 98.02 181 |
|
thres100view900 | | | 95.38 168 | 94.70 177 | 97.41 155 | 98.98 95 | 94.92 177 | 98.87 85 | 96.90 301 | 95.38 91 | 96.61 133 | 96.88 263 | 84.29 270 | 99.56 122 | 88.11 299 | 96.29 179 | 97.76 189 |
|
thres600view7 | | | 95.49 158 | 94.77 173 | 97.67 132 | 98.98 95 | 95.02 169 | 98.85 93 | 96.90 301 | 95.38 91 | 96.63 132 | 96.90 260 | 84.29 270 | 99.59 113 | 88.65 292 | 96.33 176 | 98.40 166 |
|
tfpn_ndepth | | | 95.53 153 | 94.90 164 | 97.39 160 | 98.96 99 | 95.88 139 | 99.05 58 | 95.27 336 | 93.80 163 | 96.95 114 | 96.93 258 | 85.53 247 | 99.40 138 | 91.54 233 | 96.10 191 | 96.89 231 |
|
tfpn200view9 | | | 95.32 175 | 94.62 180 | 97.43 154 | 98.94 100 | 94.98 173 | 98.68 139 | 96.93 299 | 95.33 99 | 96.55 139 | 96.53 279 | 84.23 275 | 99.56 122 | 88.11 299 | 96.29 179 | 97.76 189 |
|
thres400 | | | 95.38 168 | 94.62 180 | 97.65 135 | 98.94 100 | 94.98 173 | 98.68 139 | 96.93 299 | 95.33 99 | 96.55 139 | 96.53 279 | 84.23 275 | 99.56 122 | 88.11 299 | 96.29 179 | 98.40 166 |
|
conf0.01 | | | 95.56 151 | 94.84 167 | 97.72 124 | 98.90 102 | 95.93 127 | 99.17 36 | 95.70 327 | 93.42 185 | 96.50 148 | 97.16 221 | 86.12 231 | 99.22 153 | 90.51 251 | 96.06 192 | 98.02 181 |
|
conf0.002 | | | 95.56 151 | 94.84 167 | 97.72 124 | 98.90 102 | 95.93 127 | 99.17 36 | 95.70 327 | 93.42 185 | 96.50 148 | 97.16 221 | 86.12 231 | 99.22 153 | 90.51 251 | 96.06 192 | 98.02 181 |
|
thresconf0.02 | | | 95.50 154 | 94.84 167 | 97.51 146 | 98.90 102 | 95.93 127 | 99.17 36 | 95.70 327 | 93.42 185 | 96.50 148 | 97.16 221 | 86.12 231 | 99.22 153 | 90.51 251 | 96.06 192 | 97.37 204 |
|
tfpn_n400 | | | 95.50 154 | 94.84 167 | 97.51 146 | 98.90 102 | 95.93 127 | 99.17 36 | 95.70 327 | 93.42 185 | 96.50 148 | 97.16 221 | 86.12 231 | 99.22 153 | 90.51 251 | 96.06 192 | 97.37 204 |
|
tfpnconf | | | 95.50 154 | 94.84 167 | 97.51 146 | 98.90 102 | 95.93 127 | 99.17 36 | 95.70 327 | 93.42 185 | 96.50 148 | 97.16 221 | 86.12 231 | 99.22 153 | 90.51 251 | 96.06 192 | 97.37 204 |
|
tfpnview11 | | | 95.50 154 | 94.84 167 | 97.51 146 | 98.90 102 | 95.93 127 | 99.17 36 | 95.70 327 | 93.42 185 | 96.50 148 | 97.16 221 | 86.12 231 | 99.22 153 | 90.51 251 | 96.06 192 | 97.37 204 |
|
MVS_0304 | | | 97.70 59 | 97.25 67 | 99.07 45 | 98.90 102 | 97.83 51 | 98.20 201 | 98.74 82 | 97.51 8 | 98.03 66 | 99.06 59 | 86.12 231 | 99.93 9 | 99.02 1 | 99.64 48 | 99.44 87 |
|
MSDG | | | 95.93 130 | 95.30 143 | 97.83 117 | 98.90 102 | 95.36 156 | 96.83 308 | 98.37 161 | 91.32 263 | 94.43 199 | 98.73 96 | 90.27 134 | 99.60 112 | 90.05 264 | 98.82 102 | 98.52 160 |
|
RPSCF | | | 94.87 197 | 95.40 133 | 93.26 315 | 98.89 110 | 82.06 340 | 98.33 186 | 98.06 221 | 90.30 281 | 96.56 137 | 99.26 30 | 87.09 215 | 99.49 132 | 93.82 170 | 96.32 177 | 98.24 176 |
|
VNet | | | 97.79 56 | 97.40 63 | 98.96 53 | 98.88 111 | 97.55 60 | 98.63 146 | 98.93 36 | 96.74 46 | 99.02 19 | 98.84 84 | 90.33 133 | 99.83 47 | 98.53 10 | 96.66 161 | 99.50 74 |
|
LFMVS | | | 95.86 133 | 94.98 155 | 98.47 81 | 98.87 112 | 96.32 109 | 98.84 96 | 96.02 321 | 93.40 191 | 98.62 42 | 99.20 38 | 74.99 330 | 99.63 109 | 97.72 43 | 97.20 152 | 99.46 84 |
|
UA-Net | | | 97.96 47 | 97.62 50 | 98.98 51 | 98.86 113 | 97.47 63 | 98.89 81 | 99.08 20 | 96.67 49 | 98.72 38 | 99.54 1 | 93.15 82 | 99.81 55 | 94.87 142 | 98.83 101 | 99.65 53 |
|
WTY-MVS | | | 97.37 80 | 96.92 82 | 98.72 63 | 98.86 113 | 96.89 85 | 98.31 191 | 98.71 94 | 95.26 103 | 97.67 90 | 98.56 111 | 92.21 96 | 99.78 79 | 95.89 112 | 96.85 157 | 99.48 79 |
|
IS-MVSNet | | | 97.22 85 | 96.88 83 | 98.25 94 | 98.85 115 | 96.36 107 | 99.19 35 | 97.97 226 | 95.39 90 | 97.23 103 | 98.99 67 | 91.11 120 | 98.93 194 | 94.60 150 | 98.59 111 | 99.47 80 |
|
VDD-MVS | | | 95.82 135 | 95.23 145 | 97.61 141 | 98.84 116 | 93.98 234 | 98.68 139 | 97.40 269 | 95.02 116 | 97.95 74 | 99.34 20 | 74.37 335 | 99.78 79 | 98.64 4 | 96.80 158 | 99.08 128 |
|
CHOSEN 280x420 | | | 97.18 88 | 97.18 71 | 97.20 163 | 98.81 117 | 93.27 252 | 95.78 329 | 99.15 18 | 95.25 104 | 96.79 128 | 98.11 150 | 92.29 92 | 99.07 176 | 98.56 9 | 99.85 2 | 99.25 105 |
|
thres200 | | | 95.25 178 | 94.57 182 | 97.28 161 | 98.81 117 | 94.92 177 | 98.20 201 | 97.11 285 | 95.24 106 | 96.54 141 | 96.22 292 | 84.58 262 | 99.53 129 | 87.93 304 | 96.50 168 | 97.39 202 |
|
XVG-OURS-SEG-HR | | | 96.51 113 | 96.34 106 | 97.02 175 | 98.77 119 | 93.76 240 | 97.79 250 | 98.50 140 | 95.45 87 | 96.94 116 | 99.09 55 | 87.87 199 | 99.55 128 | 96.76 83 | 95.83 201 | 97.74 191 |
|
XVG-OURS | | | 96.55 112 | 96.41 104 | 96.99 176 | 98.75 120 | 93.76 240 | 97.50 268 | 98.52 133 | 95.67 78 | 96.83 123 | 99.30 27 | 88.95 157 | 99.53 129 | 95.88 113 | 96.26 184 | 97.69 195 |
|
0601test | | | 97.22 85 | 96.78 88 | 98.54 75 | 98.73 121 | 96.60 95 | 98.45 173 | 98.31 166 | 94.70 126 | 98.02 67 | 98.42 122 | 90.80 126 | 99.70 96 | 96.81 81 | 96.79 159 | 99.34 92 |
|
CANet | | | 98.05 45 | 97.76 47 | 98.90 57 | 98.73 121 | 97.27 69 | 98.35 184 | 98.78 74 | 97.37 19 | 97.72 87 | 98.96 73 | 91.53 115 | 99.92 15 | 98.79 3 | 99.65 46 | 99.51 72 |
|
Vis-MVSNet (Re-imp) | | | 96.87 101 | 96.55 100 | 97.83 117 | 98.73 121 | 95.46 153 | 99.20 33 | 98.30 170 | 94.96 120 | 96.60 136 | 98.87 82 | 90.05 136 | 98.59 224 | 93.67 174 | 98.60 110 | 99.46 84 |
|
PAPR | | | 96.84 102 | 96.24 111 | 98.65 67 | 98.72 124 | 96.92 82 | 97.36 278 | 98.57 124 | 93.33 193 | 96.67 130 | 97.57 196 | 94.30 70 | 99.56 122 | 91.05 243 | 98.59 111 | 99.47 80 |
|
canonicalmvs | | | 97.67 61 | 97.23 69 | 98.98 51 | 98.70 125 | 98.38 20 | 99.34 11 | 98.39 158 | 96.76 45 | 97.67 90 | 97.40 205 | 92.26 93 | 99.49 132 | 98.28 22 | 96.28 183 | 99.08 128 |
|
API-MVS | | | 97.41 77 | 97.25 67 | 97.91 112 | 98.70 125 | 96.80 86 | 98.82 99 | 98.69 97 | 94.53 135 | 98.11 60 | 98.28 137 | 94.50 66 | 99.57 120 | 94.12 164 | 99.49 70 | 97.37 204 |
|
MAR-MVS | | | 96.91 99 | 96.40 105 | 98.45 82 | 98.69 127 | 96.90 83 | 98.66 144 | 98.68 100 | 92.40 231 | 97.07 109 | 97.96 161 | 91.54 114 | 99.75 88 | 93.68 173 | 98.92 95 | 98.69 151 |
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-MVSNAJ | | | 97.73 57 | 97.77 46 | 97.62 136 | 98.68 128 | 95.58 147 | 97.34 280 | 98.51 135 | 97.29 20 | 98.66 40 | 97.88 169 | 94.51 63 | 99.90 27 | 97.87 34 | 99.17 89 | 97.39 202 |
|
alignmvs | | | 97.56 67 | 97.07 77 | 99.01 48 | 98.66 129 | 98.37 23 | 98.83 97 | 98.06 221 | 96.74 46 | 98.00 72 | 97.65 189 | 90.80 126 | 99.48 136 | 98.37 19 | 96.56 165 | 99.19 111 |
|
Vis-MVSNet | | | 97.42 75 | 97.11 74 | 98.34 89 | 98.66 129 | 96.23 112 | 99.22 29 | 99.00 26 | 96.63 51 | 98.04 65 | 99.21 35 | 88.05 193 | 99.35 143 | 96.01 109 | 99.21 87 | 99.45 86 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
EPP-MVSNet | | | 97.46 69 | 97.28 66 | 97.99 109 | 98.64 131 | 95.38 155 | 99.33 13 | 98.31 166 | 93.61 179 | 97.19 104 | 99.07 58 | 94.05 73 | 99.23 151 | 96.89 73 | 98.43 120 | 99.37 91 |
|
ab-mvs | | | 96.42 116 | 95.71 127 | 98.55 73 | 98.63 132 | 96.75 89 | 97.88 241 | 98.74 82 | 93.84 160 | 96.54 141 | 98.18 146 | 85.34 252 | 99.75 88 | 95.93 111 | 96.35 175 | 99.15 118 |
|
PCF-MVS | | 93.45 11 | 94.68 214 | 93.43 250 | 98.42 86 | 98.62 133 | 96.77 88 | 95.48 331 | 98.20 185 | 84.63 333 | 93.34 244 | 98.32 135 | 88.55 179 | 99.81 55 | 84.80 323 | 98.96 94 | 98.68 152 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
xiu_mvs_v2_base | | | 97.66 62 | 97.70 49 | 97.56 144 | 98.61 134 | 95.46 153 | 97.44 269 | 98.46 145 | 97.15 32 | 98.65 41 | 98.15 147 | 94.33 69 | 99.80 62 | 97.84 37 | 98.66 109 | 97.41 200 |
|
sss | | | 97.39 78 | 96.98 80 | 98.61 69 | 98.60 135 | 96.61 94 | 98.22 199 | 98.93 36 | 93.97 154 | 98.01 70 | 98.48 117 | 91.98 103 | 99.85 43 | 96.45 94 | 98.15 129 | 99.39 90 |
|
Test_1112_low_res | | | 96.34 119 | 95.66 131 | 98.36 88 | 98.56 136 | 95.94 124 | 97.71 254 | 98.07 219 | 92.10 239 | 94.79 184 | 97.29 214 | 91.75 107 | 99.56 122 | 94.17 162 | 96.50 168 | 99.58 66 |
|
1112_ss | | | 96.63 107 | 96.00 118 | 98.50 78 | 98.56 136 | 96.37 106 | 98.18 209 | 98.10 214 | 92.92 207 | 94.84 180 | 98.43 120 | 92.14 98 | 99.58 119 | 94.35 157 | 96.51 167 | 99.56 68 |
|
BH-untuned | | | 95.95 129 | 95.72 124 | 96.65 202 | 98.55 138 | 92.26 265 | 98.23 198 | 97.79 233 | 93.73 167 | 94.62 186 | 98.01 158 | 88.97 156 | 99.00 185 | 93.04 190 | 98.51 114 | 98.68 152 |
|
LS3D | | | 97.16 89 | 96.66 97 | 98.68 65 | 98.53 139 | 97.19 74 | 98.93 75 | 98.90 42 | 92.83 213 | 95.99 167 | 99.37 13 | 92.12 99 | 99.87 38 | 93.67 174 | 99.57 58 | 98.97 136 |
|
HY-MVS | | 93.96 8 | 96.82 103 | 96.23 112 | 98.57 71 | 98.46 140 | 97.00 78 | 98.14 211 | 98.21 182 | 93.95 155 | 96.72 129 | 97.99 160 | 91.58 110 | 99.76 86 | 94.51 154 | 96.54 166 | 98.95 140 |
|
xiu_mvs_v1_base_debu | | | 97.60 63 | 97.56 53 | 97.72 124 | 98.35 141 | 95.98 116 | 97.86 243 | 98.51 135 | 97.13 34 | 99.01 20 | 98.40 123 | 91.56 111 | 99.80 62 | 98.53 10 | 98.68 105 | 97.37 204 |
|
xiu_mvs_v1_base | | | 97.60 63 | 97.56 53 | 97.72 124 | 98.35 141 | 95.98 116 | 97.86 243 | 98.51 135 | 97.13 34 | 99.01 20 | 98.40 123 | 91.56 111 | 99.80 62 | 98.53 10 | 98.68 105 | 97.37 204 |
|
xiu_mvs_v1_base_debi | | | 97.60 63 | 97.56 53 | 97.72 124 | 98.35 141 | 95.98 116 | 97.86 243 | 98.51 135 | 97.13 34 | 99.01 20 | 98.40 123 | 91.56 111 | 99.80 62 | 98.53 10 | 98.68 105 | 97.37 204 |
|
casdiffmvs | | | 97.42 75 | 97.12 72 | 98.31 91 | 98.35 141 | 96.55 99 | 99.05 58 | 98.20 185 | 94.97 119 | 97.55 99 | 98.11 150 | 92.33 91 | 99.18 161 | 97.70 44 | 97.85 140 | 99.18 115 |
|
BH-w/o | | | 95.38 168 | 95.08 151 | 96.26 240 | 98.34 145 | 91.79 272 | 97.70 255 | 97.43 266 | 92.87 210 | 94.24 213 | 97.22 219 | 88.66 175 | 98.84 205 | 91.55 232 | 97.70 146 | 98.16 178 |
|
MVS_Test | | | 97.28 83 | 97.00 79 | 98.13 101 | 98.33 146 | 95.97 120 | 98.74 124 | 98.07 219 | 94.27 143 | 98.44 52 | 98.07 153 | 92.48 88 | 99.26 148 | 96.43 95 | 98.19 128 | 99.16 117 |
|
BH-RMVSNet | | | 95.92 131 | 95.32 141 | 97.69 130 | 98.32 147 | 94.64 208 | 98.19 205 | 97.45 264 | 94.56 134 | 96.03 165 | 98.61 105 | 85.02 255 | 99.12 166 | 90.68 247 | 99.06 91 | 99.30 99 |
|
Fast-Effi-MVS+ | | | 96.28 122 | 95.70 128 | 98.03 108 | 98.29 148 | 95.97 120 | 98.58 152 | 98.25 178 | 91.74 248 | 95.29 174 | 97.23 218 | 91.03 123 | 99.15 163 | 92.90 197 | 97.96 134 | 98.97 136 |
|
UGNet | | | 96.78 104 | 96.30 108 | 98.19 98 | 98.24 149 | 95.89 138 | 98.88 84 | 98.93 36 | 97.39 16 | 96.81 126 | 97.84 173 | 82.60 289 | 99.90 27 | 96.53 91 | 99.49 70 | 98.79 146 |
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 |
MVSTER | | | 96.06 126 | 95.72 124 | 97.08 173 | 98.23 150 | 95.93 127 | 98.73 127 | 98.27 173 | 94.86 124 | 95.07 175 | 98.09 152 | 88.21 186 | 98.54 229 | 96.59 88 | 93.46 232 | 96.79 242 |
|
GBi-Net | | | 94.49 224 | 93.80 227 | 96.56 216 | 98.21 151 | 95.00 170 | 98.82 99 | 98.18 190 | 92.46 220 | 94.09 221 | 97.07 234 | 81.16 295 | 97.95 291 | 92.08 215 | 92.14 248 | 96.72 250 |
|
test1 | | | 94.49 224 | 93.80 227 | 96.56 216 | 98.21 151 | 95.00 170 | 98.82 99 | 98.18 190 | 92.46 220 | 94.09 221 | 97.07 234 | 81.16 295 | 97.95 291 | 92.08 215 | 92.14 248 | 96.72 250 |
|
FMVSNet2 | | | 94.47 226 | 93.61 240 | 97.04 174 | 98.21 151 | 96.43 104 | 98.79 113 | 98.27 173 | 92.46 220 | 93.50 241 | 97.09 232 | 81.16 295 | 98.00 289 | 91.09 239 | 91.93 252 | 96.70 254 |
|
Effi-MVS+ | | | 97.12 91 | 96.69 94 | 98.39 87 | 98.19 154 | 96.72 90 | 97.37 276 | 98.43 153 | 93.71 169 | 97.65 93 | 98.02 156 | 92.20 97 | 99.25 149 | 96.87 79 | 97.79 142 | 99.19 111 |
|
mvs_anonymous | | | 96.70 106 | 96.53 102 | 97.18 165 | 98.19 154 | 93.78 239 | 98.31 191 | 98.19 187 | 94.01 150 | 94.47 191 | 98.27 140 | 92.08 101 | 98.46 245 | 97.39 58 | 97.91 136 | 99.31 96 |
|
LCM-MVSNet-Re | | | 95.22 180 | 95.32 141 | 94.91 287 | 98.18 156 | 87.85 325 | 98.75 120 | 95.66 333 | 95.11 111 | 88.96 306 | 96.85 267 | 90.26 135 | 97.65 303 | 95.65 124 | 98.44 118 | 99.22 108 |
|
FMVSNet3 | | | 94.97 192 | 94.26 196 | 97.11 170 | 98.18 156 | 96.62 92 | 98.56 157 | 98.26 177 | 93.67 176 | 94.09 221 | 97.10 230 | 84.25 274 | 98.01 288 | 92.08 215 | 92.14 248 | 96.70 254 |
|
CANet_DTU | | | 96.96 97 | 96.55 100 | 98.21 95 | 98.17 158 | 96.07 115 | 97.98 228 | 98.21 182 | 97.24 27 | 97.13 105 | 98.93 77 | 86.88 220 | 99.91 24 | 95.00 141 | 99.37 83 | 98.66 154 |
|
diffmvs | | | 97.03 94 | 96.75 92 | 97.88 114 | 98.14 159 | 95.25 162 | 98.54 163 | 98.13 201 | 95.17 108 | 97.03 112 | 97.94 163 | 91.83 106 | 99.30 144 | 96.01 109 | 97.94 135 | 99.11 123 |
|
IterMVS-LS | | | 95.46 160 | 95.21 146 | 96.22 241 | 98.12 160 | 93.72 244 | 98.32 190 | 98.13 201 | 93.71 169 | 94.26 211 | 97.31 213 | 92.24 94 | 98.10 282 | 94.63 148 | 90.12 267 | 96.84 238 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
VDDNet | | | 95.36 171 | 94.53 184 | 97.86 115 | 98.10 161 | 95.13 166 | 98.85 93 | 97.75 235 | 90.46 277 | 98.36 54 | 99.39 8 | 73.27 337 | 99.64 106 | 97.98 28 | 96.58 164 | 98.81 145 |
|
MVSFormer | | | 97.57 66 | 97.49 58 | 97.84 116 | 98.07 162 | 95.76 142 | 99.47 2 | 98.40 156 | 94.98 117 | 98.79 33 | 98.83 85 | 92.34 89 | 98.41 260 | 96.91 71 | 99.59 55 | 99.34 92 |
|
lupinMVS | | | 97.44 73 | 97.22 70 | 98.12 102 | 98.07 162 | 95.76 142 | 97.68 257 | 97.76 234 | 94.50 137 | 98.79 33 | 98.61 105 | 92.34 89 | 99.30 144 | 97.58 49 | 99.59 55 | 99.31 96 |
|
TAMVS | | | 97.02 95 | 96.79 87 | 97.70 129 | 98.06 164 | 95.31 160 | 98.52 164 | 98.31 166 | 93.95 155 | 97.05 111 | 98.61 105 | 93.49 78 | 98.52 236 | 95.33 132 | 97.81 141 | 99.29 101 |
|
CDS-MVSNet | | | 96.99 96 | 96.69 94 | 97.90 113 | 98.05 165 | 95.98 116 | 98.20 201 | 98.33 165 | 93.67 176 | 96.95 114 | 98.49 116 | 93.54 77 | 98.42 253 | 95.24 138 | 97.74 145 | 99.31 96 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
ADS-MVSNet2 | | | 94.58 221 | 94.40 192 | 95.11 283 | 98.00 166 | 88.74 313 | 96.04 322 | 97.30 277 | 90.15 282 | 96.47 155 | 96.64 276 | 87.89 197 | 97.56 307 | 90.08 262 | 97.06 153 | 99.02 131 |
|
ADS-MVSNet | | | 95.00 188 | 94.45 190 | 96.63 205 | 98.00 166 | 91.91 270 | 96.04 322 | 97.74 236 | 90.15 282 | 96.47 155 | 96.64 276 | 87.89 197 | 98.96 189 | 90.08 262 | 97.06 153 | 99.02 131 |
|
IterMVS | | | 94.09 247 | 93.85 225 | 94.80 293 | 97.99 168 | 90.35 294 | 97.18 289 | 98.12 204 | 93.68 174 | 92.46 270 | 97.34 210 | 84.05 279 | 97.41 310 | 92.51 209 | 91.33 259 | 96.62 269 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
PVSNet_0 | | 88.72 19 | 91.28 294 | 90.03 297 | 95.00 285 | 97.99 168 | 87.29 328 | 94.84 338 | 98.50 140 | 92.06 240 | 89.86 298 | 95.19 309 | 79.81 307 | 99.39 140 | 92.27 212 | 69.79 350 | 98.33 174 |
|
semantic-postprocess | | | | | 94.85 290 | 97.98 170 | 90.56 292 | | 98.11 209 | 93.75 164 | 92.58 264 | 97.48 200 | 83.91 281 | 97.41 310 | 92.48 210 | 91.30 260 | 96.58 274 |
|
EI-MVSNet | | | 95.96 128 | 95.83 122 | 96.36 233 | 97.93 171 | 93.70 245 | 98.12 214 | 98.27 173 | 93.70 171 | 95.07 175 | 99.02 61 | 92.23 95 | 98.54 229 | 94.68 147 | 93.46 232 | 96.84 238 |
|
CVMVSNet | | | 95.43 162 | 96.04 116 | 93.57 311 | 97.93 171 | 83.62 334 | 98.12 214 | 98.59 118 | 95.68 77 | 96.56 137 | 99.02 61 | 87.51 209 | 97.51 308 | 93.56 177 | 97.44 149 | 99.60 62 |
|
PMMVS | | | 96.60 108 | 96.33 107 | 97.41 155 | 97.90 173 | 93.93 235 | 97.35 279 | 98.41 154 | 92.84 212 | 97.76 83 | 97.45 203 | 91.10 121 | 99.20 159 | 96.26 101 | 97.91 136 | 99.11 123 |
|
Effi-MVS+-dtu | | | 96.29 120 | 96.56 99 | 95.51 263 | 97.89 174 | 90.22 295 | 98.80 108 | 98.10 214 | 96.57 52 | 96.45 157 | 96.66 274 | 90.81 124 | 98.91 196 | 95.72 119 | 97.99 133 | 97.40 201 |
|
mvs-test1 | | | 96.60 108 | 96.68 96 | 96.37 232 | 97.89 174 | 91.81 271 | 98.56 157 | 98.10 214 | 96.57 52 | 96.52 143 | 97.94 163 | 90.81 124 | 99.45 137 | 95.72 119 | 98.01 132 | 97.86 188 |
|
QAPM | | | 96.29 120 | 95.40 133 | 98.96 53 | 97.85 176 | 97.60 59 | 99.23 23 | 98.93 36 | 89.76 294 | 93.11 252 | 99.02 61 | 89.11 150 | 99.93 9 | 91.99 221 | 99.62 50 | 99.34 92 |
|
3Dnovator+ | | 94.38 6 | 97.43 74 | 96.78 88 | 99.38 12 | 97.83 177 | 98.52 14 | 99.37 7 | 98.71 94 | 97.09 37 | 92.99 255 | 99.13 47 | 89.36 143 | 99.89 29 | 96.97 67 | 99.57 58 | 99.71 35 |
|
ACMH+ | | 92.99 14 | 94.30 233 | 93.77 230 | 95.88 253 | 97.81 178 | 92.04 269 | 98.71 130 | 98.37 161 | 93.99 152 | 90.60 294 | 98.47 118 | 80.86 300 | 99.05 177 | 92.75 201 | 92.40 247 | 96.55 279 |
|
3Dnovator | | 94.51 5 | 97.46 69 | 96.93 81 | 99.07 45 | 97.78 179 | 97.64 56 | 99.35 10 | 99.06 21 | 97.02 39 | 93.75 234 | 99.16 45 | 89.25 146 | 99.92 15 | 97.22 61 | 99.75 32 | 99.64 56 |
|
TR-MVS | | | 94.94 195 | 94.20 201 | 97.17 166 | 97.75 180 | 94.14 231 | 97.59 263 | 97.02 291 | 92.28 237 | 95.75 169 | 97.64 191 | 83.88 282 | 98.96 189 | 89.77 268 | 96.15 189 | 98.40 166 |
|
Fast-Effi-MVS+-dtu | | | 95.87 132 | 95.85 121 | 95.91 251 | 97.74 181 | 91.74 275 | 98.69 135 | 98.15 198 | 95.56 83 | 94.92 178 | 97.68 188 | 88.98 155 | 98.79 211 | 93.19 185 | 97.78 143 | 97.20 212 |
|
MIMVSNet | | | 93.26 266 | 92.21 271 | 96.41 230 | 97.73 182 | 93.13 257 | 95.65 330 | 97.03 290 | 91.27 267 | 94.04 224 | 96.06 296 | 75.33 328 | 97.19 313 | 86.56 311 | 96.23 186 | 98.92 141 |
|
Patchmatch-test1 | | | 95.32 175 | 94.97 157 | 96.35 234 | 97.67 183 | 91.29 280 | 97.33 281 | 97.60 241 | 94.68 128 | 96.92 119 | 96.95 252 | 83.97 280 | 98.50 239 | 91.33 238 | 98.32 124 | 99.25 105 |
|
ACMP | | 93.49 10 | 95.34 173 | 94.98 155 | 96.43 229 | 97.67 183 | 93.48 248 | 98.73 127 | 98.44 149 | 94.94 123 | 92.53 266 | 98.53 112 | 84.50 268 | 99.14 164 | 95.48 129 | 94.00 222 | 96.66 263 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
ACMH | | 92.88 16 | 94.55 222 | 93.95 219 | 96.34 236 | 97.63 185 | 93.26 253 | 98.81 105 | 98.49 144 | 93.43 184 | 89.74 299 | 98.53 112 | 81.91 292 | 99.08 175 | 93.69 172 | 93.30 238 | 96.70 254 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
tpmp4_e23 | | | 93.91 254 | 93.42 252 | 95.38 275 | 97.62 186 | 88.59 317 | 97.52 267 | 97.34 273 | 87.94 313 | 94.17 218 | 96.79 270 | 82.91 287 | 99.05 177 | 90.62 249 | 95.91 199 | 98.50 161 |
|
ACMM | | 93.85 9 | 95.69 142 | 95.38 137 | 96.61 208 | 97.61 187 | 93.84 238 | 98.91 76 | 98.44 149 | 95.25 104 | 94.28 210 | 98.47 118 | 86.04 241 | 99.12 166 | 95.50 128 | 93.95 224 | 96.87 235 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
Patchmatch-test | | | 94.42 228 | 93.68 237 | 96.63 205 | 97.60 188 | 91.76 273 | 94.83 339 | 97.49 261 | 89.45 302 | 94.14 219 | 97.10 230 | 88.99 152 | 98.83 207 | 85.37 321 | 98.13 130 | 99.29 101 |
|
PatchFormer-LS_test | | | 95.47 159 | 95.27 144 | 96.08 247 | 97.59 189 | 90.66 289 | 98.10 218 | 97.34 273 | 93.98 153 | 96.08 163 | 96.15 294 | 87.65 207 | 99.12 166 | 95.27 136 | 95.24 206 | 98.44 165 |
|
tpm cat1 | | | 93.36 261 | 92.80 261 | 95.07 284 | 97.58 190 | 87.97 323 | 96.76 309 | 97.86 231 | 82.17 340 | 93.53 238 | 96.04 297 | 86.13 230 | 99.13 165 | 89.24 280 | 95.87 200 | 98.10 179 |
|
MVS-HIRNet | | | 89.46 308 | 88.40 310 | 92.64 317 | 97.58 190 | 82.15 339 | 94.16 345 | 93.05 353 | 75.73 348 | 90.90 290 | 82.52 349 | 79.42 309 | 98.33 268 | 83.53 325 | 98.68 105 | 97.43 199 |
|
PatchmatchNet | | | 95.71 140 | 95.52 132 | 96.29 239 | 97.58 190 | 90.72 288 | 96.84 307 | 97.52 249 | 94.06 148 | 97.08 107 | 96.96 251 | 89.24 147 | 98.90 199 | 92.03 219 | 98.37 121 | 99.26 104 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
tpmrst | | | 95.63 144 | 95.69 129 | 95.44 269 | 97.54 193 | 88.54 318 | 96.97 294 | 97.56 243 | 93.50 182 | 97.52 100 | 96.93 258 | 89.49 140 | 99.16 162 | 95.25 137 | 96.42 170 | 98.64 156 |
|
FMVSNet1 | | | 93.19 269 | 92.07 272 | 96.56 216 | 97.54 193 | 95.00 170 | 98.82 99 | 98.18 190 | 90.38 280 | 92.27 273 | 97.07 234 | 73.68 336 | 97.95 291 | 89.36 279 | 91.30 260 | 96.72 250 |
|
CLD-MVS | | | 95.62 145 | 95.34 138 | 96.46 228 | 97.52 195 | 93.75 242 | 97.27 285 | 98.46 145 | 95.53 84 | 94.42 200 | 98.00 159 | 86.21 229 | 98.97 186 | 96.25 102 | 94.37 209 | 96.66 263 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
MDTV_nov1_ep13 | | | | 95.40 133 | | 97.48 196 | 88.34 320 | 96.85 306 | 97.29 278 | 93.74 166 | 97.48 101 | 97.26 215 | 89.18 148 | 99.05 177 | 91.92 224 | 97.43 150 | |
|
IB-MVS | | 91.98 17 | 93.27 265 | 91.97 273 | 97.19 164 | 97.47 197 | 93.41 251 | 97.09 292 | 95.99 322 | 93.32 194 | 92.47 269 | 95.73 303 | 78.06 316 | 99.53 129 | 94.59 151 | 82.98 327 | 98.62 157 |
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 |
tpmvs | | | 94.60 218 | 94.36 193 | 95.33 278 | 97.46 198 | 88.60 316 | 96.88 304 | 97.68 237 | 91.29 265 | 93.80 233 | 96.42 285 | 88.58 176 | 99.24 150 | 91.06 241 | 96.04 198 | 98.17 177 |
|
LPG-MVS_test | | | 95.62 145 | 95.34 138 | 96.47 225 | 97.46 198 | 93.54 246 | 98.99 66 | 98.54 128 | 94.67 129 | 94.36 202 | 98.77 92 | 85.39 249 | 99.11 170 | 95.71 121 | 94.15 217 | 96.76 245 |
|
LGP-MVS_train | | | | | 96.47 225 | 97.46 198 | 93.54 246 | | 98.54 128 | 94.67 129 | 94.36 202 | 98.77 92 | 85.39 249 | 99.11 170 | 95.71 121 | 94.15 217 | 96.76 245 |
|
jason | | | 97.32 82 | 97.08 76 | 98.06 107 | 97.45 201 | 95.59 146 | 97.87 242 | 97.91 229 | 94.79 125 | 98.55 46 | 98.83 85 | 91.12 119 | 99.23 151 | 97.58 49 | 99.60 52 | 99.34 92 |
jason: jason. |
HQP_MVS | | | 96.14 125 | 95.90 120 | 96.85 185 | 97.42 202 | 94.60 214 | 98.80 108 | 98.56 125 | 97.28 21 | 95.34 171 | 98.28 137 | 87.09 215 | 99.03 182 | 96.07 104 | 94.27 211 | 96.92 223 |
|
plane_prior7 | | | | | | 97.42 202 | 94.63 209 | | | | | | | | | | |
|
ITE_SJBPF | | | | | 95.44 269 | 97.42 202 | 91.32 279 | | 97.50 255 | 95.09 114 | 93.59 235 | 98.35 129 | 81.70 293 | 98.88 201 | 89.71 271 | 93.39 236 | 96.12 300 |
|
LTVRE_ROB | | 92.95 15 | 94.60 218 | 93.90 222 | 96.68 197 | 97.41 205 | 94.42 219 | 98.52 164 | 98.59 118 | 91.69 249 | 91.21 285 | 98.35 129 | 84.87 258 | 99.04 181 | 91.06 241 | 93.44 235 | 96.60 272 |
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 |
plane_prior1 | | | | | | 97.37 206 | | | | | | | | | | | |
|
plane_prior6 | | | | | | 97.35 207 | 94.61 212 | | | | | | 87.09 215 | | | | |
|
DWT-MVSNet_test | | | 94.82 201 | 94.36 193 | 96.20 242 | 97.35 207 | 90.79 286 | 98.34 185 | 96.57 316 | 92.91 208 | 95.33 173 | 96.44 284 | 82.00 291 | 99.12 166 | 94.52 153 | 95.78 202 | 98.70 150 |
|
dp | | | 94.15 244 | 93.90 222 | 94.90 288 | 97.31 209 | 86.82 330 | 96.97 294 | 97.19 284 | 91.22 269 | 96.02 166 | 96.61 278 | 85.51 248 | 99.02 184 | 90.00 266 | 94.30 210 | 98.85 142 |
|
NP-MVS | | | | | | 97.28 210 | 94.51 217 | | | | | 97.73 182 | | | | | |
|
CostFormer | | | 94.95 193 | 94.73 176 | 95.60 262 | 97.28 210 | 89.06 309 | 97.53 266 | 96.89 305 | 89.66 298 | 96.82 125 | 96.72 272 | 86.05 239 | 98.95 193 | 95.53 127 | 96.13 190 | 98.79 146 |
|
VPA-MVSNet | | | 95.75 137 | 95.11 149 | 97.69 130 | 97.24 212 | 97.27 69 | 98.94 74 | 99.23 12 | 95.13 110 | 95.51 170 | 97.32 212 | 85.73 244 | 98.91 196 | 97.33 60 | 89.55 275 | 96.89 231 |
|
tpm2 | | | 94.19 239 | 93.76 232 | 95.46 267 | 97.23 213 | 89.04 310 | 97.31 283 | 96.85 308 | 87.08 317 | 96.21 161 | 96.79 270 | 83.75 285 | 98.74 213 | 92.43 211 | 96.23 186 | 98.59 158 |
|
EPMVS | | | 94.99 189 | 94.48 186 | 96.52 221 | 97.22 214 | 91.75 274 | 97.23 286 | 91.66 354 | 94.11 145 | 97.28 102 | 96.81 269 | 85.70 245 | 98.84 205 | 93.04 190 | 97.28 151 | 98.97 136 |
|
FMVSNet5 | | | 91.81 289 | 90.92 283 | 94.49 300 | 97.21 215 | 92.09 267 | 98.00 227 | 97.55 247 | 89.31 305 | 90.86 291 | 95.61 308 | 74.48 333 | 95.32 338 | 85.57 318 | 89.70 271 | 96.07 302 |
|
HQP-NCC | | | | | | 97.20 216 | | 98.05 221 | | 96.43 54 | 94.45 192 | | | | | | |
|
ACMP_Plane | | | | | | 97.20 216 | | 98.05 221 | | 96.43 54 | 94.45 192 | | | | | | |
|
HQP-MVS | | | 95.72 138 | 95.40 133 | 96.69 194 | 97.20 216 | 94.25 229 | 98.05 221 | 98.46 145 | 96.43 54 | 94.45 192 | 97.73 182 | 86.75 221 | 98.96 189 | 95.30 133 | 94.18 215 | 96.86 237 |
|
OpenMVS | | 93.04 13 | 95.83 134 | 95.00 153 | 98.32 90 | 97.18 219 | 97.32 67 | 99.21 32 | 98.97 29 | 89.96 287 | 91.14 287 | 99.05 60 | 86.64 223 | 99.92 15 | 93.38 179 | 99.47 72 | 97.73 192 |
|
VPNet | | | 94.99 189 | 94.19 202 | 97.40 157 | 97.16 220 | 96.57 96 | 98.71 130 | 98.97 29 | 95.67 78 | 94.84 180 | 98.24 143 | 80.36 305 | 98.67 218 | 96.46 93 | 87.32 308 | 96.96 220 |
|
GA-MVS | | | 94.81 202 | 94.03 212 | 97.14 167 | 97.15 221 | 93.86 237 | 96.76 309 | 97.58 242 | 94.00 151 | 94.76 185 | 97.04 242 | 80.91 298 | 98.48 240 | 91.79 226 | 96.25 185 | 99.09 125 |
|
FIs | | | 96.51 113 | 96.12 114 | 97.67 132 | 97.13 222 | 97.54 61 | 99.36 8 | 99.22 14 | 95.89 71 | 94.03 225 | 98.35 129 | 91.98 103 | 98.44 250 | 96.40 96 | 92.76 244 | 97.01 217 |
|
1314 | | | 96.25 124 | 95.73 123 | 97.79 120 | 97.13 222 | 95.55 151 | 98.19 205 | 98.59 118 | 93.47 183 | 92.03 279 | 97.82 177 | 91.33 117 | 99.49 132 | 94.62 149 | 98.44 118 | 98.32 175 |
|
DeepMVS_CX | | | | | 86.78 331 | 97.09 224 | 72.30 351 | | 95.17 340 | 75.92 347 | 84.34 334 | 95.19 309 | 70.58 341 | 95.35 337 | 79.98 333 | 89.04 283 | 92.68 343 |
|
PAPM | | | 94.95 193 | 94.00 215 | 97.78 121 | 97.04 225 | 95.65 145 | 96.03 324 | 98.25 178 | 91.23 268 | 94.19 216 | 97.80 179 | 91.27 118 | 98.86 204 | 82.61 327 | 97.61 147 | 98.84 144 |
|
CR-MVSNet | | | 94.76 205 | 94.15 204 | 96.59 211 | 97.00 226 | 93.43 249 | 94.96 335 | 97.56 243 | 92.46 220 | 96.93 117 | 96.24 288 | 88.15 188 | 97.88 299 | 87.38 306 | 96.65 162 | 98.46 163 |
|
RPMNet | | | 92.52 275 | 91.17 278 | 96.59 211 | 97.00 226 | 93.43 249 | 94.96 335 | 97.26 281 | 82.27 339 | 96.93 117 | 92.12 342 | 86.98 218 | 97.88 299 | 76.32 341 | 96.65 162 | 98.46 163 |
|
UniMVSNet (Re) | | | 95.78 136 | 95.19 147 | 97.58 142 | 96.99 228 | 97.47 63 | 98.79 113 | 99.18 16 | 95.60 81 | 93.92 228 | 97.04 242 | 91.68 108 | 98.48 240 | 95.80 117 | 87.66 305 | 96.79 242 |
|
FC-MVSNet-test | | | 96.42 116 | 96.05 115 | 97.53 145 | 96.95 229 | 97.27 69 | 99.36 8 | 99.23 12 | 95.83 73 | 93.93 227 | 98.37 127 | 92.00 102 | 98.32 269 | 96.02 108 | 92.72 245 | 97.00 218 |
|
tfpnnormal | | | 93.66 257 | 92.70 264 | 96.55 219 | 96.94 230 | 95.94 124 | 98.97 70 | 99.19 15 | 91.04 271 | 91.38 284 | 97.34 210 | 84.94 257 | 98.61 221 | 85.45 320 | 89.02 284 | 95.11 318 |
|
TESTMET0.1,1 | | | 94.18 241 | 93.69 236 | 95.63 261 | 96.92 231 | 89.12 308 | 96.91 298 | 94.78 342 | 93.17 198 | 94.88 179 | 96.45 283 | 78.52 313 | 98.92 195 | 93.09 187 | 98.50 115 | 98.85 142 |
|
TinyColmap | | | 92.31 277 | 91.53 276 | 94.65 297 | 96.92 231 | 89.75 298 | 96.92 296 | 96.68 312 | 90.45 278 | 89.62 300 | 97.85 172 | 76.06 326 | 98.81 209 | 86.74 310 | 92.51 246 | 95.41 315 |
|
cascas | | | 94.63 217 | 93.86 224 | 96.93 182 | 96.91 233 | 94.27 227 | 96.00 325 | 98.51 135 | 85.55 328 | 94.54 188 | 96.23 290 | 84.20 277 | 98.87 202 | 95.80 117 | 96.98 156 | 97.66 196 |
|
nrg030 | | | 96.28 122 | 95.72 124 | 97.96 111 | 96.90 234 | 98.15 38 | 99.39 5 | 98.31 166 | 95.47 86 | 94.42 200 | 98.35 129 | 92.09 100 | 98.69 214 | 97.50 55 | 89.05 282 | 97.04 216 |
|
MVS | | | 94.67 215 | 93.54 244 | 98.08 105 | 96.88 235 | 96.56 97 | 98.19 205 | 98.50 140 | 78.05 346 | 92.69 261 | 98.02 156 | 91.07 122 | 99.63 109 | 90.09 261 | 98.36 122 | 98.04 180 |
|
WR-MVS_H | | | 95.05 187 | 94.46 188 | 96.81 187 | 96.86 236 | 95.82 141 | 99.24 21 | 99.24 10 | 93.87 159 | 92.53 266 | 96.84 268 | 90.37 131 | 98.24 277 | 93.24 183 | 87.93 300 | 96.38 291 |
|
UniMVSNet_NR-MVSNet | | | 95.71 140 | 95.15 148 | 97.40 157 | 96.84 237 | 96.97 79 | 98.74 124 | 99.24 10 | 95.16 109 | 93.88 229 | 97.72 184 | 91.68 108 | 98.31 271 | 95.81 115 | 87.25 310 | 96.92 223 |
|
USDC | | | 93.33 264 | 92.71 263 | 95.21 279 | 96.83 238 | 90.83 285 | 96.91 298 | 97.50 255 | 93.84 160 | 90.72 292 | 98.14 148 | 77.69 318 | 98.82 208 | 89.51 276 | 93.21 241 | 95.97 304 |
|
test-LLR | | | 95.10 185 | 94.87 165 | 95.80 256 | 96.77 239 | 89.70 299 | 96.91 298 | 95.21 337 | 95.11 111 | 94.83 182 | 95.72 305 | 87.71 203 | 98.97 186 | 93.06 188 | 98.50 115 | 98.72 148 |
|
test-mter | | | 94.08 248 | 93.51 247 | 95.80 256 | 96.77 239 | 89.70 299 | 96.91 298 | 95.21 337 | 92.89 209 | 94.83 182 | 95.72 305 | 77.69 318 | 98.97 186 | 93.06 188 | 98.50 115 | 98.72 148 |
|
Patchmtry | | | 93.22 267 | 92.35 269 | 95.84 254 | 96.77 239 | 93.09 258 | 94.66 341 | 97.56 243 | 87.37 316 | 92.90 256 | 96.24 288 | 88.15 188 | 97.90 295 | 87.37 307 | 90.10 268 | 96.53 281 |
|
gg-mvs-nofinetune | | | 92.21 278 | 90.58 292 | 97.13 168 | 96.75 242 | 95.09 167 | 95.85 327 | 89.40 357 | 85.43 329 | 94.50 190 | 81.98 350 | 80.80 301 | 98.40 266 | 92.16 213 | 98.33 123 | 97.88 187 |
|
XXY-MVS | | | 95.20 182 | 94.45 190 | 97.46 152 | 96.75 242 | 96.56 97 | 98.86 92 | 98.65 114 | 93.30 196 | 93.27 245 | 98.27 140 | 84.85 259 | 98.87 202 | 94.82 145 | 91.26 262 | 96.96 220 |
|
CP-MVSNet | | | 94.94 195 | 94.30 195 | 96.83 186 | 96.72 244 | 95.56 149 | 99.11 51 | 98.95 33 | 93.89 157 | 92.42 271 | 97.90 167 | 87.19 214 | 98.12 281 | 94.32 158 | 88.21 297 | 96.82 241 |
|
PatchT | | | 93.06 271 | 91.97 273 | 96.35 234 | 96.69 245 | 92.67 261 | 94.48 342 | 97.08 286 | 86.62 318 | 97.08 107 | 92.23 341 | 87.94 195 | 97.90 295 | 78.89 336 | 96.69 160 | 98.49 162 |
|
PS-CasMVS | | | 94.67 215 | 93.99 217 | 96.71 191 | 96.68 246 | 95.26 161 | 99.13 48 | 99.03 24 | 93.68 174 | 92.33 272 | 97.95 162 | 85.35 251 | 98.10 282 | 93.59 176 | 88.16 299 | 96.79 242 |
|
WR-MVS | | | 95.15 183 | 94.46 188 | 97.22 162 | 96.67 247 | 96.45 103 | 98.21 200 | 98.81 63 | 94.15 144 | 93.16 248 | 97.69 185 | 87.51 209 | 98.30 273 | 95.29 135 | 88.62 294 | 96.90 230 |
|
test_0402 | | | 91.32 293 | 90.27 295 | 94.48 301 | 96.60 248 | 91.12 282 | 98.50 169 | 97.22 283 | 86.10 323 | 88.30 309 | 96.98 249 | 77.65 320 | 97.99 290 | 78.13 338 | 92.94 243 | 94.34 333 |
|
TransMVSNet (Re) | | | 92.67 273 | 91.51 277 | 96.15 243 | 96.58 249 | 94.65 207 | 98.90 77 | 96.73 309 | 90.86 273 | 89.46 302 | 97.86 170 | 85.62 246 | 98.09 284 | 86.45 312 | 81.12 332 | 95.71 310 |
|
Anonymous20240521 | | | 94.80 203 | 94.03 212 | 97.11 170 | 96.56 250 | 96.46 102 | 99.30 14 | 98.44 149 | 92.86 211 | 91.21 285 | 97.01 246 | 89.59 139 | 98.58 226 | 92.03 219 | 89.23 280 | 96.30 295 |
|
XVG-ACMP-BASELINE | | | 94.54 223 | 94.14 205 | 95.75 259 | 96.55 251 | 91.65 276 | 98.11 216 | 98.44 149 | 94.96 120 | 94.22 214 | 97.90 167 | 79.18 311 | 99.11 170 | 94.05 166 | 93.85 225 | 96.48 287 |
|
DU-MVS | | | 95.42 164 | 94.76 174 | 97.40 157 | 96.53 252 | 96.97 79 | 98.66 144 | 98.99 28 | 95.43 88 | 93.88 229 | 97.69 185 | 88.57 177 | 98.31 271 | 95.81 115 | 87.25 310 | 96.92 223 |
|
NR-MVSNet | | | 94.98 191 | 94.16 203 | 97.44 153 | 96.53 252 | 97.22 73 | 98.74 124 | 98.95 33 | 94.96 120 | 89.25 304 | 97.69 185 | 89.32 144 | 98.18 279 | 94.59 151 | 87.40 307 | 96.92 223 |
|
tpm | | | 94.13 245 | 93.80 227 | 95.12 282 | 96.50 254 | 87.91 324 | 97.44 269 | 95.89 326 | 92.62 216 | 96.37 159 | 96.30 287 | 84.13 278 | 98.30 273 | 93.24 183 | 91.66 257 | 99.14 120 |
|
pm-mvs1 | | | 93.94 253 | 93.06 257 | 96.59 211 | 96.49 255 | 95.16 164 | 98.95 72 | 98.03 225 | 92.32 235 | 91.08 288 | 97.84 173 | 84.54 267 | 98.41 260 | 92.16 213 | 86.13 321 | 96.19 299 |
|
JIA-IIPM | | | 93.35 262 | 92.49 267 | 95.92 250 | 96.48 256 | 90.65 290 | 95.01 334 | 96.96 297 | 85.93 325 | 96.08 163 | 87.33 346 | 87.70 205 | 98.78 212 | 91.35 237 | 95.58 203 | 98.34 173 |
|
TranMVSNet+NR-MVSNet | | | 95.14 184 | 94.48 186 | 97.11 170 | 96.45 257 | 96.36 107 | 99.03 62 | 99.03 24 | 95.04 115 | 93.58 236 | 97.93 165 | 88.27 185 | 98.03 287 | 94.13 163 | 86.90 315 | 96.95 222 |
|
testgi | | | 93.06 271 | 92.45 268 | 94.88 289 | 96.43 258 | 89.90 296 | 98.75 120 | 97.54 248 | 95.60 81 | 91.63 283 | 97.91 166 | 74.46 334 | 97.02 315 | 86.10 314 | 93.67 227 | 97.72 193 |
|
v7 | | | 94.69 211 | 94.04 211 | 96.62 207 | 96.41 259 | 94.79 202 | 98.78 115 | 98.13 201 | 91.89 244 | 94.30 208 | 97.16 221 | 88.13 190 | 98.45 247 | 91.96 223 | 89.65 272 | 96.61 270 |
|
v1neww | | | 94.83 198 | 94.22 197 | 96.68 197 | 96.39 260 | 94.85 183 | 98.87 85 | 98.11 209 | 92.45 225 | 94.45 192 | 97.06 237 | 88.82 165 | 98.54 229 | 92.93 194 | 88.91 287 | 96.65 265 |
|
v7new | | | 94.83 198 | 94.22 197 | 96.68 197 | 96.39 260 | 94.85 183 | 98.87 85 | 98.11 209 | 92.45 225 | 94.45 192 | 97.06 237 | 88.82 165 | 98.54 229 | 92.93 194 | 88.91 287 | 96.65 265 |
|
v10 | | | 94.29 234 | 93.55 243 | 96.51 222 | 96.39 260 | 94.80 199 | 98.99 66 | 98.19 187 | 91.35 261 | 93.02 254 | 96.99 248 | 88.09 191 | 98.41 260 | 90.50 257 | 88.41 296 | 96.33 294 |
|
v16 | | | 92.08 281 | 90.94 281 | 95.49 265 | 96.38 263 | 94.84 192 | 98.81 105 | 97.51 252 | 89.94 289 | 85.25 326 | 93.28 323 | 88.86 160 | 96.91 318 | 88.70 290 | 79.78 335 | 94.72 325 |
|
v8 | | | 94.47 226 | 93.77 230 | 96.57 215 | 96.36 264 | 94.83 194 | 99.05 58 | 98.19 187 | 91.92 243 | 93.16 248 | 96.97 250 | 88.82 165 | 98.48 240 | 91.69 230 | 87.79 303 | 96.39 290 |
|
v6 | | | 94.83 198 | 94.21 200 | 96.69 194 | 96.36 264 | 94.85 183 | 98.87 85 | 98.11 209 | 92.46 220 | 94.44 198 | 97.05 241 | 88.76 171 | 98.57 227 | 92.95 193 | 88.92 286 | 96.65 265 |
|
LP | | | 91.12 296 | 89.99 298 | 94.53 299 | 96.35 266 | 88.70 314 | 93.86 346 | 97.35 272 | 84.88 331 | 90.98 289 | 94.77 314 | 84.40 269 | 97.43 309 | 75.41 343 | 91.89 254 | 97.47 198 |
|
GG-mvs-BLEND | | | | | 96.59 211 | 96.34 267 | 94.98 173 | 96.51 319 | 88.58 358 | | 93.10 253 | 94.34 319 | 80.34 306 | 98.05 286 | 89.53 275 | 96.99 155 | 96.74 247 |
|
v18 | | | 92.10 280 | 90.97 280 | 95.50 264 | 96.34 267 | 94.85 183 | 98.82 99 | 97.52 249 | 89.99 286 | 85.31 325 | 93.26 324 | 88.90 159 | 96.92 317 | 88.82 288 | 79.77 336 | 94.73 324 |
|
v17 | | | 92.08 281 | 90.94 281 | 95.48 266 | 96.34 267 | 94.83 194 | 98.81 105 | 97.52 249 | 89.95 288 | 85.32 323 | 93.24 325 | 88.91 158 | 96.91 318 | 88.76 289 | 79.63 337 | 94.71 326 |
|
v11 | | | 91.85 288 | 90.68 290 | 95.36 276 | 96.34 267 | 94.74 206 | 98.80 108 | 97.43 266 | 89.60 300 | 85.09 328 | 93.03 330 | 88.53 180 | 96.75 325 | 87.37 307 | 79.96 334 | 94.58 332 |
|
v13 | | | 91.88 287 | 90.69 289 | 95.43 271 | 96.33 271 | 94.78 204 | 98.75 120 | 97.50 255 | 89.68 297 | 84.93 332 | 92.98 332 | 88.84 163 | 96.83 322 | 88.14 298 | 79.09 340 | 94.69 327 |
|
V14 | | | 91.93 284 | 90.76 286 | 95.42 274 | 96.33 271 | 94.81 198 | 98.77 116 | 97.51 252 | 89.86 292 | 85.09 328 | 93.13 326 | 88.80 169 | 96.83 322 | 88.32 295 | 79.06 341 | 94.60 331 |
|
V42 | | | 94.78 204 | 94.14 205 | 96.70 193 | 96.33 271 | 95.22 163 | 98.97 70 | 98.09 217 | 92.32 235 | 94.31 206 | 97.06 237 | 88.39 183 | 98.55 228 | 92.90 197 | 88.87 289 | 96.34 293 |
|
V9 | | | 91.91 285 | 90.73 287 | 95.45 268 | 96.32 274 | 94.80 199 | 98.77 116 | 97.50 255 | 89.81 293 | 85.03 330 | 93.08 328 | 88.76 171 | 96.86 320 | 88.24 296 | 79.03 342 | 94.69 327 |
|
v15 | | | 91.94 283 | 90.77 285 | 95.43 271 | 96.31 275 | 94.83 194 | 98.77 116 | 97.50 255 | 89.92 290 | 85.13 327 | 93.08 328 | 88.76 171 | 96.86 320 | 88.40 294 | 79.10 339 | 94.61 330 |
|
v12 | | | 91.89 286 | 90.70 288 | 95.43 271 | 96.31 275 | 94.80 199 | 98.76 119 | 97.50 255 | 89.76 294 | 84.95 331 | 93.00 331 | 88.82 165 | 96.82 324 | 88.23 297 | 79.00 343 | 94.68 329 |
|
divwei89l23v2f112 | | | 94.76 205 | 94.12 208 | 96.67 200 | 96.28 277 | 94.85 183 | 98.69 135 | 98.12 204 | 92.44 227 | 94.29 209 | 96.94 254 | 88.85 162 | 98.48 240 | 92.67 202 | 88.79 293 | 96.67 260 |
|
PEN-MVS | | | 94.42 228 | 93.73 234 | 96.49 223 | 96.28 277 | 94.84 192 | 99.17 36 | 99.00 26 | 93.51 181 | 92.23 274 | 97.83 176 | 86.10 238 | 97.90 295 | 92.55 207 | 86.92 314 | 96.74 247 |
|
v1141 | | | 94.75 207 | 94.11 209 | 96.67 200 | 96.27 279 | 94.86 182 | 98.69 135 | 98.12 204 | 92.43 228 | 94.31 206 | 96.94 254 | 88.78 170 | 98.48 240 | 92.63 204 | 88.85 291 | 96.67 260 |
|
v1 | | | 94.75 207 | 94.11 209 | 96.69 194 | 96.27 279 | 94.87 181 | 98.69 135 | 98.12 204 | 92.43 228 | 94.32 205 | 96.94 254 | 88.71 174 | 98.54 229 | 92.66 203 | 88.84 292 | 96.67 260 |
|
v1144 | | | 94.59 220 | 93.92 220 | 96.60 210 | 96.21 281 | 94.78 204 | 98.59 150 | 98.14 200 | 91.86 247 | 94.21 215 | 97.02 244 | 87.97 194 | 98.41 260 | 91.72 229 | 89.57 273 | 96.61 270 |
|
Baseline_NR-MVSNet | | | 94.35 231 | 93.81 226 | 95.96 249 | 96.20 282 | 94.05 233 | 98.61 149 | 96.67 313 | 91.44 255 | 93.85 231 | 97.60 193 | 88.57 177 | 98.14 280 | 94.39 155 | 86.93 313 | 95.68 311 |
|
MS-PatchMatch | | | 93.84 255 | 93.63 238 | 94.46 303 | 96.18 283 | 89.45 303 | 97.76 251 | 98.27 173 | 92.23 238 | 92.13 277 | 97.49 199 | 79.50 308 | 98.69 214 | 89.75 270 | 99.38 82 | 95.25 316 |
|
pcd1.5k->3k | | | 39.42 336 | 41.78 337 | 32.35 349 | 96.17 284 | 0.00 368 | 0.00 360 | 98.54 128 | 0.00 363 | 0.00 364 | 0.00 365 | 87.78 202 | 0.00 366 | 0.00 363 | 93.56 231 | 97.06 214 |
|
v2v482 | | | 94.69 211 | 94.03 212 | 96.65 202 | 96.17 284 | 94.79 202 | 98.67 142 | 98.08 218 | 92.72 214 | 94.00 226 | 97.16 221 | 87.69 206 | 98.45 247 | 92.91 196 | 88.87 289 | 96.72 250 |
|
EPNet_dtu | | | 95.21 181 | 94.95 158 | 95.99 248 | 96.17 284 | 90.45 293 | 98.16 210 | 97.27 280 | 96.77 44 | 93.14 251 | 98.33 134 | 90.34 132 | 98.42 253 | 85.57 318 | 98.81 103 | 99.09 125 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
OPM-MVS | | | 95.69 142 | 95.33 140 | 96.76 189 | 96.16 287 | 94.63 209 | 98.43 177 | 98.39 158 | 96.64 50 | 95.02 177 | 98.78 90 | 85.15 254 | 99.05 177 | 95.21 139 | 94.20 214 | 96.60 272 |
|
v1192 | | | 94.32 232 | 93.58 242 | 96.53 220 | 96.10 288 | 94.45 218 | 98.50 169 | 98.17 195 | 91.54 252 | 94.19 216 | 97.06 237 | 86.95 219 | 98.43 252 | 90.14 260 | 89.57 273 | 96.70 254 |
|
v148 | | | 94.29 234 | 93.76 232 | 95.91 251 | 96.10 288 | 92.93 259 | 98.58 152 | 97.97 226 | 92.59 218 | 93.47 242 | 96.95 252 | 88.53 180 | 98.32 269 | 92.56 206 | 87.06 312 | 96.49 286 |
|
v144192 | | | 94.39 230 | 93.70 235 | 96.48 224 | 96.06 290 | 94.35 223 | 98.58 152 | 98.16 197 | 91.45 254 | 94.33 204 | 97.02 244 | 87.50 211 | 98.45 247 | 91.08 240 | 89.11 281 | 96.63 268 |
|
DTE-MVSNet | | | 93.98 252 | 93.26 255 | 96.14 244 | 96.06 290 | 94.39 221 | 99.20 33 | 98.86 53 | 93.06 201 | 91.78 280 | 97.81 178 | 85.87 242 | 97.58 306 | 90.53 250 | 86.17 319 | 96.46 289 |
|
v1240 | | | 94.06 250 | 93.29 254 | 96.34 236 | 96.03 292 | 93.90 236 | 98.44 175 | 98.17 195 | 91.18 270 | 94.13 220 | 97.01 246 | 86.05 239 | 98.42 253 | 89.13 282 | 89.50 276 | 96.70 254 |
|
v1921920 | | | 94.20 238 | 93.47 249 | 96.40 231 | 95.98 293 | 94.08 232 | 98.52 164 | 98.15 198 | 91.33 262 | 94.25 212 | 97.20 220 | 86.41 226 | 98.42 253 | 90.04 265 | 89.39 278 | 96.69 259 |
|
EU-MVSNet | | | 93.66 257 | 94.14 205 | 92.25 320 | 95.96 294 | 83.38 335 | 98.52 164 | 98.12 204 | 94.69 127 | 92.61 263 | 98.13 149 | 87.36 213 | 96.39 334 | 91.82 225 | 90.00 269 | 96.98 219 |
|
v52 | | | 94.18 241 | 93.52 245 | 96.13 245 | 95.95 295 | 94.29 225 | 99.23 23 | 98.21 182 | 91.42 256 | 92.84 257 | 96.89 261 | 87.85 200 | 98.53 235 | 91.51 234 | 87.81 301 | 95.57 314 |
|
v7n | | | 94.19 239 | 93.43 250 | 96.47 225 | 95.90 296 | 94.38 222 | 99.26 18 | 98.34 164 | 91.99 241 | 92.76 260 | 97.13 229 | 88.31 184 | 98.52 236 | 89.48 277 | 87.70 304 | 96.52 282 |
|
V4 | | | 94.18 241 | 93.52 245 | 96.13 245 | 95.89 297 | 94.31 224 | 99.23 23 | 98.22 181 | 91.42 256 | 92.82 258 | 96.89 261 | 87.93 196 | 98.52 236 | 91.51 234 | 87.81 301 | 95.58 313 |
|
gm-plane-assit | | | | | | 95.88 298 | 87.47 326 | | | 89.74 296 | | 96.94 254 | | 99.19 160 | 93.32 182 | | |
|
LF4IMVS | | | 93.14 270 | 92.79 262 | 94.20 306 | 95.88 298 | 88.67 315 | 97.66 259 | 97.07 287 | 93.81 162 | 91.71 281 | 97.65 189 | 77.96 317 | 98.81 209 | 91.47 236 | 91.92 253 | 95.12 317 |
|
PS-MVSNAJss | | | 96.43 115 | 96.26 110 | 96.92 184 | 95.84 300 | 95.08 168 | 99.16 43 | 98.50 140 | 95.87 72 | 93.84 232 | 98.34 133 | 94.51 63 | 98.61 221 | 96.88 76 | 93.45 234 | 97.06 214 |
|
testpf | | | 88.74 311 | 89.09 304 | 87.69 328 | 95.78 301 | 83.16 337 | 84.05 357 | 94.13 350 | 85.22 330 | 90.30 295 | 94.39 318 | 74.92 331 | 95.80 335 | 89.77 268 | 93.28 240 | 84.10 352 |
|
pmmvs4 | | | 94.69 211 | 93.99 217 | 96.81 187 | 95.74 302 | 95.94 124 | 97.40 272 | 97.67 238 | 90.42 279 | 93.37 243 | 97.59 194 | 89.08 151 | 98.20 278 | 92.97 192 | 91.67 256 | 96.30 295 |
|
v748 | | | 93.75 256 | 93.06 257 | 95.82 255 | 95.73 303 | 92.64 262 | 99.25 20 | 98.24 180 | 91.60 251 | 92.22 275 | 96.52 281 | 87.60 208 | 98.46 245 | 90.64 248 | 85.72 322 | 96.36 292 |
|
test_djsdf | | | 96.00 127 | 95.69 129 | 96.93 182 | 95.72 304 | 95.49 152 | 99.47 2 | 98.40 156 | 94.98 117 | 94.58 187 | 97.86 170 | 89.16 149 | 98.41 260 | 96.91 71 | 94.12 219 | 96.88 233 |
|
SixPastTwentyTwo | | | 93.34 263 | 92.86 260 | 94.75 294 | 95.67 305 | 89.41 305 | 98.75 120 | 96.67 313 | 93.89 157 | 90.15 297 | 98.25 142 | 80.87 299 | 98.27 276 | 90.90 244 | 90.64 264 | 96.57 276 |
|
K. test v3 | | | 92.55 274 | 91.91 275 | 94.48 301 | 95.64 306 | 89.24 306 | 99.07 57 | 94.88 341 | 94.04 149 | 86.78 314 | 97.59 194 | 77.64 321 | 97.64 304 | 92.08 215 | 89.43 277 | 96.57 276 |
|
OurMVSNet-221017-0 | | | 94.21 237 | 94.00 215 | 94.85 290 | 95.60 307 | 89.22 307 | 98.89 81 | 97.43 266 | 95.29 102 | 92.18 276 | 98.52 115 | 82.86 288 | 98.59 224 | 93.46 178 | 91.76 255 | 96.74 247 |
|
mvs_tets | | | 95.41 166 | 95.00 153 | 96.65 202 | 95.58 308 | 94.42 219 | 99.00 65 | 98.55 127 | 95.73 76 | 93.21 247 | 98.38 126 | 83.45 286 | 98.63 220 | 97.09 65 | 94.00 222 | 96.91 228 |
|
Gipuma | | | 78.40 323 | 76.75 324 | 83.38 337 | 95.54 309 | 80.43 341 | 79.42 358 | 97.40 269 | 64.67 351 | 73.46 346 | 80.82 352 | 45.65 356 | 93.14 347 | 66.32 351 | 87.43 306 | 76.56 357 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
test0.0.03 1 | | | 94.08 248 | 93.51 247 | 95.80 256 | 95.53 310 | 92.89 260 | 97.38 274 | 95.97 323 | 95.11 111 | 92.51 268 | 96.66 274 | 87.71 203 | 96.94 316 | 87.03 309 | 93.67 227 | 97.57 197 |
|
pmmvs5 | | | 93.65 259 | 92.97 259 | 95.68 260 | 95.49 311 | 92.37 264 | 98.20 201 | 97.28 279 | 89.66 298 | 92.58 264 | 97.26 215 | 82.14 290 | 98.09 284 | 93.18 186 | 90.95 263 | 96.58 274 |
|
N_pmnet | | | 87.12 316 | 87.77 313 | 85.17 335 | 95.46 312 | 61.92 358 | 97.37 276 | 70.66 365 | 85.83 326 | 88.73 308 | 96.04 297 | 85.33 253 | 97.76 302 | 80.02 331 | 90.48 265 | 95.84 306 |
|
our_test_3 | | | 93.65 259 | 93.30 253 | 94.69 295 | 95.45 313 | 89.68 301 | 96.91 298 | 97.65 239 | 91.97 242 | 91.66 282 | 96.88 263 | 89.67 138 | 97.93 294 | 88.02 303 | 91.49 258 | 96.48 287 |
|
ppachtmachnet_test | | | 93.22 267 | 92.63 265 | 94.97 286 | 95.45 313 | 90.84 284 | 96.88 304 | 97.88 230 | 90.60 275 | 92.08 278 | 97.26 215 | 88.08 192 | 97.86 301 | 85.12 322 | 90.33 266 | 96.22 297 |
|
jajsoiax | | | 95.45 161 | 95.03 152 | 96.73 190 | 95.42 315 | 94.63 209 | 99.14 45 | 98.52 133 | 95.74 75 | 93.22 246 | 98.36 128 | 83.87 283 | 98.65 219 | 96.95 70 | 94.04 220 | 96.91 228 |
|
DI_MVS_plusplus_test | | | 94.74 209 | 93.62 239 | 98.09 104 | 95.34 316 | 95.92 134 | 98.09 219 | 97.34 273 | 94.66 131 | 85.89 318 | 95.91 299 | 80.49 304 | 99.38 141 | 96.66 86 | 98.22 126 | 98.97 136 |
|
test_normal | | | 94.72 210 | 93.59 241 | 98.11 103 | 95.30 317 | 95.95 123 | 97.91 235 | 97.39 271 | 94.64 132 | 85.70 321 | 95.88 300 | 80.52 303 | 99.36 142 | 96.69 85 | 98.30 125 | 99.01 134 |
|
MDA-MVSNet-bldmvs | | | 89.97 305 | 88.35 311 | 94.83 292 | 95.21 318 | 91.34 278 | 97.64 260 | 97.51 252 | 88.36 311 | 71.17 349 | 96.13 295 | 79.22 310 | 96.63 331 | 83.65 324 | 86.27 318 | 96.52 282 |
|
anonymousdsp | | | 95.42 164 | 94.91 163 | 96.94 181 | 95.10 319 | 95.90 137 | 99.14 45 | 98.41 154 | 93.75 164 | 93.16 248 | 97.46 201 | 87.50 211 | 98.41 260 | 95.63 125 | 94.03 221 | 96.50 285 |
|
EPNet | | | 97.28 83 | 96.87 84 | 98.51 77 | 94.98 320 | 96.14 114 | 98.90 77 | 97.02 291 | 98.28 1 | 95.99 167 | 99.11 49 | 91.36 116 | 99.89 29 | 96.98 66 | 99.19 88 | 99.50 74 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
MVP-Stereo | | | 94.28 236 | 93.92 220 | 95.35 277 | 94.95 321 | 92.60 263 | 97.97 229 | 97.65 239 | 91.61 250 | 90.68 293 | 97.09 232 | 86.32 228 | 98.42 253 | 89.70 272 | 99.34 84 | 95.02 321 |
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
lessismore_v0 | | | | | 94.45 304 | 94.93 322 | 88.44 319 | | 91.03 355 | | 86.77 315 | 97.64 191 | 76.23 325 | 98.42 253 | 90.31 259 | 85.64 323 | 96.51 284 |
|
MDA-MVSNet_test_wron | | | 90.71 300 | 89.38 303 | 94.68 296 | 94.83 323 | 90.78 287 | 97.19 288 | 97.46 262 | 87.60 314 | 72.41 348 | 95.72 305 | 86.51 224 | 96.71 329 | 85.92 316 | 86.80 316 | 96.56 278 |
|
YYNet1 | | | 90.70 301 | 89.39 302 | 94.62 298 | 94.79 324 | 90.65 290 | 97.20 287 | 97.46 262 | 87.54 315 | 72.54 347 | 95.74 302 | 86.51 224 | 96.66 330 | 86.00 315 | 86.76 317 | 96.54 280 |
|
EG-PatchMatch MVS | | | 91.13 295 | 90.12 296 | 94.17 308 | 94.73 325 | 89.00 311 | 98.13 213 | 97.81 232 | 89.22 306 | 85.32 323 | 96.46 282 | 67.71 345 | 98.42 253 | 87.89 305 | 93.82 226 | 95.08 319 |
|
pmmvs6 | | | 91.77 290 | 90.63 291 | 95.17 281 | 94.69 326 | 91.24 281 | 98.67 142 | 97.92 228 | 86.14 322 | 89.62 300 | 97.56 198 | 75.79 327 | 98.34 267 | 90.75 246 | 84.56 326 | 95.94 305 |
|
new_pmnet | | | 90.06 304 | 89.00 307 | 93.22 316 | 94.18 327 | 88.32 321 | 96.42 320 | 96.89 305 | 86.19 321 | 85.67 322 | 93.62 321 | 77.18 323 | 97.10 314 | 81.61 329 | 89.29 279 | 94.23 334 |
|
DSMNet-mixed | | | 92.52 275 | 92.58 266 | 92.33 319 | 94.15 328 | 82.65 338 | 98.30 193 | 94.26 347 | 89.08 307 | 92.65 262 | 95.73 303 | 85.01 256 | 95.76 336 | 86.24 313 | 97.76 144 | 98.59 158 |
|
UnsupCasMVSNet_eth | | | 90.99 298 | 89.92 299 | 94.19 307 | 94.08 329 | 89.83 297 | 97.13 291 | 98.67 107 | 93.69 172 | 85.83 320 | 96.19 293 | 75.15 329 | 96.74 326 | 89.14 281 | 79.41 338 | 96.00 303 |
|
Anonymous20231206 | | | 91.66 291 | 91.10 279 | 93.33 313 | 94.02 330 | 87.35 327 | 98.58 152 | 97.26 281 | 90.48 276 | 90.16 296 | 96.31 286 | 83.83 284 | 96.53 332 | 79.36 334 | 89.90 270 | 96.12 300 |
|
test20.03 | | | 90.89 299 | 90.38 293 | 92.43 318 | 93.48 331 | 88.14 322 | 98.33 186 | 97.56 243 | 93.40 191 | 87.96 310 | 96.71 273 | 80.69 302 | 94.13 342 | 79.15 335 | 86.17 319 | 95.01 322 |
|
CMPMVS | | 66.06 21 | 89.70 306 | 89.67 301 | 89.78 324 | 93.19 332 | 76.56 344 | 97.00 293 | 98.35 163 | 80.97 342 | 81.57 338 | 97.75 181 | 74.75 332 | 98.61 221 | 89.85 267 | 93.63 229 | 94.17 335 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
OpenMVS_ROB | | 86.42 20 | 89.00 309 | 87.43 315 | 93.69 310 | 93.08 333 | 89.42 304 | 97.91 235 | 96.89 305 | 78.58 345 | 85.86 319 | 94.69 315 | 69.48 342 | 98.29 275 | 77.13 339 | 93.29 239 | 93.36 342 |
|
Test4 | | | 92.21 278 | 90.34 294 | 97.82 119 | 92.83 334 | 95.87 140 | 97.94 231 | 98.05 224 | 94.50 137 | 82.12 337 | 94.48 316 | 59.54 352 | 98.54 229 | 95.39 131 | 98.22 126 | 99.06 130 |
|
MIMVSNet1 | | | 89.67 307 | 88.28 312 | 93.82 309 | 92.81 335 | 91.08 283 | 98.01 225 | 97.45 264 | 87.95 312 | 87.90 311 | 95.87 301 | 67.63 346 | 94.56 341 | 78.73 337 | 88.18 298 | 95.83 307 |
|
UnsupCasMVSNet_bld | | | 87.17 315 | 85.12 318 | 93.31 314 | 91.94 336 | 88.77 312 | 94.92 337 | 98.30 170 | 84.30 334 | 82.30 336 | 90.04 343 | 63.96 350 | 97.25 312 | 85.85 317 | 74.47 349 | 93.93 340 |
|
testus | | | 88.91 310 | 89.08 305 | 88.40 327 | 91.39 337 | 76.05 345 | 96.56 315 | 96.48 317 | 89.38 304 | 89.39 303 | 95.17 311 | 70.94 340 | 93.56 345 | 77.04 340 | 95.41 204 | 95.61 312 |
|
Patchmatch-RL test | | | 91.49 292 | 90.85 284 | 93.41 312 | 91.37 338 | 84.40 332 | 92.81 347 | 95.93 325 | 91.87 246 | 87.25 312 | 94.87 313 | 88.99 152 | 96.53 332 | 92.54 208 | 82.00 329 | 99.30 99 |
|
pmmvs-eth3d | | | 90.36 303 | 89.05 306 | 94.32 305 | 91.10 339 | 92.12 266 | 97.63 262 | 96.95 298 | 88.86 308 | 84.91 333 | 93.13 326 | 78.32 314 | 96.74 326 | 88.70 290 | 81.81 331 | 94.09 337 |
|
PM-MVS | | | 87.77 314 | 86.55 316 | 91.40 323 | 91.03 340 | 83.36 336 | 96.92 296 | 95.18 339 | 91.28 266 | 86.48 317 | 93.42 322 | 53.27 353 | 96.74 326 | 89.43 278 | 81.97 330 | 94.11 336 |
|
new-patchmatchnet | | | 88.50 313 | 87.45 314 | 91.67 322 | 90.31 341 | 85.89 331 | 97.16 290 | 97.33 276 | 89.47 301 | 83.63 335 | 92.77 336 | 76.38 324 | 95.06 340 | 82.70 326 | 77.29 345 | 94.06 338 |
|
testing_2 | | | 90.61 302 | 88.50 309 | 96.95 180 | 90.08 342 | 95.57 148 | 97.69 256 | 98.06 221 | 93.02 203 | 76.55 343 | 92.48 339 | 61.18 351 | 98.44 250 | 95.45 130 | 91.98 251 | 96.84 238 |
|
test2356 | | | 88.68 312 | 88.61 308 | 88.87 326 | 89.90 343 | 78.23 342 | 95.11 333 | 96.66 315 | 88.66 310 | 89.06 305 | 94.33 320 | 73.14 338 | 92.56 349 | 75.56 342 | 95.11 207 | 95.81 308 |
|
pmmvs3 | | | 86.67 317 | 84.86 319 | 92.11 321 | 88.16 344 | 87.19 329 | 96.63 312 | 94.75 343 | 79.88 344 | 87.22 313 | 92.75 337 | 66.56 347 | 95.20 339 | 81.24 330 | 76.56 347 | 93.96 339 |
|
1111 | | | 84.94 319 | 84.30 320 | 86.86 330 | 87.59 345 | 75.10 347 | 96.63 312 | 96.43 318 | 82.53 337 | 80.75 340 | 92.91 334 | 68.94 343 | 93.79 343 | 68.24 349 | 84.66 325 | 91.70 344 |
|
.test1245 | | | 73.05 327 | 76.31 325 | 63.27 348 | 87.59 345 | 75.10 347 | 96.63 312 | 96.43 318 | 82.53 337 | 80.75 340 | 92.91 334 | 68.94 343 | 93.79 343 | 68.24 349 | 12.72 361 | 20.91 361 |
|
test1235678 | | | 86.26 318 | 85.81 317 | 87.62 329 | 86.97 347 | 75.00 349 | 96.55 317 | 96.32 320 | 86.08 324 | 81.32 339 | 92.98 332 | 73.10 339 | 92.05 350 | 71.64 346 | 87.32 308 | 95.81 308 |
|
ambc | | | | | 89.49 325 | 86.66 348 | 75.78 346 | 92.66 348 | 96.72 310 | | 86.55 316 | 92.50 338 | 46.01 355 | 97.90 295 | 90.32 258 | 82.09 328 | 94.80 323 |
|
TDRefinement | | | 91.06 297 | 89.68 300 | 95.21 279 | 85.35 349 | 91.49 277 | 98.51 168 | 97.07 287 | 91.47 253 | 88.83 307 | 97.84 173 | 77.31 322 | 99.09 174 | 92.79 200 | 77.98 344 | 95.04 320 |
|
test12356 | | | 83.47 320 | 83.37 321 | 83.78 336 | 84.43 350 | 70.09 354 | 95.12 332 | 95.60 334 | 82.98 335 | 78.89 342 | 92.43 340 | 64.99 348 | 91.41 352 | 70.36 347 | 85.55 324 | 89.82 346 |
|
PMMVS2 | | | 77.95 324 | 75.44 327 | 85.46 333 | 82.54 351 | 74.95 350 | 94.23 344 | 93.08 352 | 72.80 349 | 74.68 345 | 87.38 345 | 36.36 360 | 91.56 351 | 73.95 344 | 63.94 351 | 89.87 345 |
|
E-PMN | | | 64.94 332 | 64.25 332 | 67.02 346 | 82.28 352 | 59.36 362 | 91.83 350 | 85.63 361 | 52.69 356 | 60.22 354 | 77.28 355 | 41.06 358 | 80.12 360 | 46.15 358 | 41.14 355 | 61.57 359 |
|
EMVS | | | 64.07 333 | 63.26 334 | 66.53 347 | 81.73 353 | 58.81 363 | 91.85 349 | 84.75 362 | 51.93 358 | 59.09 355 | 75.13 356 | 43.32 357 | 79.09 361 | 42.03 359 | 39.47 356 | 61.69 358 |
|
no-one | | | 74.41 326 | 70.76 328 | 85.35 334 | 79.88 354 | 76.83 343 | 94.68 340 | 94.22 348 | 80.33 343 | 63.81 352 | 79.73 353 | 35.45 361 | 93.36 346 | 71.78 345 | 36.99 358 | 85.86 351 |
|
FPMVS | | | 77.62 325 | 77.14 323 | 79.05 340 | 79.25 355 | 60.97 359 | 95.79 328 | 95.94 324 | 65.96 350 | 67.93 351 | 94.40 317 | 37.73 359 | 88.88 355 | 68.83 348 | 88.46 295 | 87.29 348 |
|
PNet_i23d | | | 67.70 330 | 65.07 331 | 75.60 342 | 78.61 356 | 59.61 361 | 89.14 352 | 88.24 359 | 61.83 352 | 52.37 356 | 80.89 351 | 18.91 364 | 84.91 357 | 62.70 354 | 52.93 353 | 82.28 353 |
|
wuyk23d | | | 30.17 337 | 30.18 339 | 30.16 350 | 78.61 356 | 43.29 365 | 66.79 359 | 14.21 366 | 17.31 360 | 14.82 363 | 11.93 364 | 11.55 367 | 41.43 363 | 37.08 360 | 19.30 360 | 5.76 363 |
|
testmv | | | 78.74 321 | 77.35 322 | 82.89 338 | 78.16 358 | 69.30 355 | 95.87 326 | 94.65 344 | 81.11 341 | 70.98 350 | 87.11 347 | 46.31 354 | 90.42 353 | 65.28 352 | 76.72 346 | 88.95 347 |
|
LCM-MVSNet | | | 78.70 322 | 76.24 326 | 86.08 332 | 77.26 359 | 71.99 352 | 94.34 343 | 96.72 310 | 61.62 353 | 76.53 344 | 89.33 344 | 33.91 362 | 92.78 348 | 81.85 328 | 74.60 348 | 93.46 341 |
|
MVE | | 62.14 22 | 63.28 335 | 59.38 335 | 74.99 343 | 74.33 360 | 65.47 357 | 85.55 355 | 80.50 364 | 52.02 357 | 51.10 357 | 75.00 357 | 10.91 369 | 80.50 359 | 51.60 357 | 53.40 352 | 78.99 355 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
wuykxyi23d | | | 63.73 334 | 58.86 336 | 78.35 341 | 67.62 361 | 67.90 356 | 86.56 354 | 87.81 360 | 58.26 354 | 42.49 360 | 70.28 358 | 11.55 367 | 85.05 356 | 63.66 353 | 41.50 354 | 82.11 354 |
|
ANet_high | | | 69.08 328 | 65.37 330 | 80.22 339 | 65.99 362 | 71.96 353 | 90.91 351 | 90.09 356 | 82.62 336 | 49.93 358 | 78.39 354 | 29.36 363 | 81.75 358 | 62.49 355 | 38.52 357 | 86.95 350 |
|
PMVS | | 61.03 23 | 65.95 331 | 63.57 333 | 73.09 345 | 57.90 363 | 51.22 364 | 85.05 356 | 93.93 351 | 54.45 355 | 44.32 359 | 83.57 348 | 13.22 365 | 89.15 354 | 58.68 356 | 81.00 333 | 78.91 356 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
tmp_tt | | | 68.90 329 | 66.97 329 | 74.68 344 | 50.78 364 | 59.95 360 | 87.13 353 | 83.47 363 | 38.80 359 | 62.21 353 | 96.23 290 | 64.70 349 | 76.91 362 | 88.91 287 | 30.49 359 | 87.19 349 |
|
testmvs | | | 21.48 339 | 24.95 340 | 11.09 352 | 14.89 365 | 6.47 367 | 96.56 315 | 9.87 367 | 7.55 361 | 17.93 361 | 39.02 360 | 9.43 370 | 5.90 365 | 16.56 362 | 12.72 361 | 20.91 361 |
|
test123 | | | 20.95 340 | 23.72 341 | 12.64 351 | 13.54 366 | 8.19 366 | 96.55 317 | 6.13 368 | 7.48 362 | 16.74 362 | 37.98 361 | 12.97 366 | 6.05 364 | 16.69 361 | 5.43 363 | 23.68 360 |
|
cdsmvs_eth3d_5k | | | 23.98 338 | 31.98 338 | 0.00 353 | 0.00 367 | 0.00 368 | 0.00 360 | 98.59 118 | 0.00 363 | 0.00 364 | 98.61 105 | 90.60 129 | 0.00 366 | 0.00 363 | 0.00 364 | 0.00 364 |
|
pcd_1.5k_mvsjas | | | 7.88 342 | 10.50 343 | 0.00 353 | 0.00 367 | 0.00 368 | 0.00 360 | 0.00 369 | 0.00 363 | 0.00 364 | 0.00 365 | 94.51 63 | 0.00 366 | 0.00 363 | 0.00 364 | 0.00 364 |
|
sosnet-low-res | | | 0.00 343 | 0.00 344 | 0.00 353 | 0.00 367 | 0.00 368 | 0.00 360 | 0.00 369 | 0.00 363 | 0.00 364 | 0.00 365 | 0.00 371 | 0.00 366 | 0.00 363 | 0.00 364 | 0.00 364 |
|
sosnet | | | 0.00 343 | 0.00 344 | 0.00 353 | 0.00 367 | 0.00 368 | 0.00 360 | 0.00 369 | 0.00 363 | 0.00 364 | 0.00 365 | 0.00 371 | 0.00 366 | 0.00 363 | 0.00 364 | 0.00 364 |
|
uncertanet | | | 0.00 343 | 0.00 344 | 0.00 353 | 0.00 367 | 0.00 368 | 0.00 360 | 0.00 369 | 0.00 363 | 0.00 364 | 0.00 365 | 0.00 371 | 0.00 366 | 0.00 363 | 0.00 364 | 0.00 364 |
|
Regformer | | | 0.00 343 | 0.00 344 | 0.00 353 | 0.00 367 | 0.00 368 | 0.00 360 | 0.00 369 | 0.00 363 | 0.00 364 | 0.00 365 | 0.00 371 | 0.00 366 | 0.00 363 | 0.00 364 | 0.00 364 |
|
ab-mvs-re | | | 8.20 341 | 10.94 342 | 0.00 353 | 0.00 367 | 0.00 368 | 0.00 360 | 0.00 369 | 0.00 363 | 0.00 364 | 98.43 120 | 0.00 371 | 0.00 366 | 0.00 363 | 0.00 364 | 0.00 364 |
|
uanet | | | 0.00 343 | 0.00 344 | 0.00 353 | 0.00 367 | 0.00 368 | 0.00 360 | 0.00 369 | 0.00 363 | 0.00 364 | 0.00 365 | 0.00 371 | 0.00 366 | 0.00 363 | 0.00 364 | 0.00 364 |
|
GSMVS | | | | | | | | | | | | | | | | | 99.20 109 |
|
test_part3 | | | | | | | | 98.55 159 | | 96.40 57 | | 99.31 22 | | 99.93 9 | 96.37 98 | | |
|
test_part1 | | | | | | | | | 98.84 55 | | | | 97.38 2 | | | 99.78 15 | 99.76 20 |
|
sam_mvs1 | | | | | | | | | | | | | 89.45 141 | | | | 99.20 109 |
|
sam_mvs | | | | | | | | | | | | | 88.99 152 | | | | |
|
MTGPA | | | | | | | | | 98.74 82 | | | | | | | | |
|
test_post1 | | | | | | | | 96.68 311 | | | | 30.43 363 | 87.85 200 | 98.69 214 | 92.59 205 | | |
|
test_post | | | | | | | | | | | | 31.83 362 | 88.83 164 | 98.91 196 | | | |
|
patchmatchnet-post | | | | | | | | | | | | 95.10 312 | 89.42 142 | 98.89 200 | | | |
|
MTMP | | | | | | | | 98.89 81 | 94.14 349 | | | | | | | | |
|
test9_res | | | | | | | | | | | | | | | 96.39 97 | 99.57 58 | 99.69 38 |
|
agg_prior2 | | | | | | | | | | | | | | | 95.87 114 | 99.57 58 | 99.68 44 |
|
test_prior4 | | | | | | | 98.01 44 | 97.86 243 | | | | | | | | | |
|
test_prior2 | | | | | | | | 97.80 248 | | 96.12 65 | 97.89 79 | 98.69 97 | 95.96 28 | | 96.89 73 | 99.60 52 | |
|
旧先验2 | | | | | | | | 97.57 265 | | 91.30 264 | 98.67 39 | | | 99.80 62 | 95.70 123 | | |
|
新几何2 | | | | | | | | 97.64 260 | | | | | | | | | |
|
无先验 | | | | | | | | 97.58 264 | 98.72 89 | 91.38 258 | | | | 99.87 38 | 93.36 180 | | 99.60 62 |
|
原ACMM2 | | | | | | | | 97.67 258 | | | | | | | | | |
|
testdata2 | | | | | | | | | | | | | | 99.89 29 | 91.65 231 | | |
|
segment_acmp | | | | | | | | | | | | | 96.85 5 | | | | |
|
testdata1 | | | | | | | | 97.32 282 | | 96.34 59 | | | | | | | |
|
plane_prior5 | | | | | | | | | 98.56 125 | | | | | 99.03 182 | 96.07 104 | 94.27 211 | 96.92 223 |
|
plane_prior4 | | | | | | | | | | | | 98.28 137 | | | | | |
|
plane_prior3 | | | | | | | 94.61 212 | | | 97.02 39 | 95.34 171 | | | | | | |
|
plane_prior2 | | | | | | | | 98.80 108 | | 97.28 21 | | | | | | | |
|
plane_prior | | | | | | | 94.60 214 | 98.44 175 | | 96.74 46 | | | | | | 94.22 213 | |
|
n2 | | | | | | | | | 0.00 369 | | | | | | | | |
|
nn | | | | | | | | | 0.00 369 | | | | | | | | |
|
door-mid | | | | | | | | | 94.37 346 | | | | | | | | |
|
test11 | | | | | | | | | 98.66 110 | | | | | | | | |
|
door | | | | | | | | | 94.64 345 | | | | | | | | |
|
HQP5-MVS | | | | | | | 94.25 229 | | | | | | | | | | |
|
BP-MVS | | | | | | | | | | | | | | | 95.30 133 | | |
|
HQP4-MVS | | | | | | | | | | | 94.45 192 | | | 98.96 189 | | | 96.87 235 |
|
HQP3-MVS | | | | | | | | | 98.46 145 | | | | | | | 94.18 215 | |
|
HQP2-MVS | | | | | | | | | | | | | 86.75 221 | | | | |
|
MDTV_nov1_ep13_2view | | | | | | | 84.26 333 | 96.89 303 | | 90.97 272 | 97.90 78 | | 89.89 137 | | 93.91 168 | | 99.18 115 |
|
ACMMP++_ref | | | | | | | | | | | | | | | | 92.97 242 | |
|
ACMMP++ | | | | | | | | | | | | | | | | 93.61 230 | |
|
Test By Simon | | | | | | | | | | | | | 94.64 60 | | | | |
|