test_part2 | | | | | | 95.06 1 | 72.65 26 | | | | 91.80 1 | | | | | | |
|
ESAPD | | | 89.40 1 | 89.87 1 | 87.98 11 | 95.06 1 | 72.65 26 | 92.22 18 | 94.09 1 | 75.63 74 | 91.80 1 | 95.29 2 | 81.79 1 | 97.56 1 | 86.60 12 | 96.38 2 | 93.74 36 |
|
HPM-MVS++ | | | 89.02 4 | 89.15 4 | 88.63 1 | 95.01 3 | 76.03 1 | 92.38 14 | 92.85 34 | 80.26 14 | 87.78 13 | 94.27 18 | 75.89 9 | 96.81 10 | 87.45 9 | 96.44 1 | 93.05 64 |
|
CNVR-MVS | | | 88.93 5 | 89.13 5 | 88.33 3 | 94.77 4 | 73.82 6 | 90.51 41 | 93.00 26 | 80.90 10 | 88.06 11 | 94.06 26 | 76.43 6 | 96.84 9 | 88.48 4 | 95.99 6 | 94.34 15 |
|
ACMMPR | | | 87.44 16 | 87.23 18 | 88.08 7 | 94.64 5 | 73.59 8 | 93.04 5 | 93.20 19 | 76.78 52 | 84.66 37 | 94.52 9 | 68.81 57 | 96.65 16 | 84.53 25 | 94.90 27 | 94.00 28 |
|
region2R | | | 87.42 18 | 87.20 19 | 88.09 6 | 94.63 6 | 73.55 9 | 93.03 7 | 93.12 22 | 76.73 55 | 84.45 40 | 94.52 9 | 69.09 55 | 96.70 14 | 84.37 28 | 94.83 30 | 94.03 25 |
|
HFP-MVS | | | 87.58 14 | 87.47 15 | 87.94 12 | 94.58 7 | 73.54 11 | 93.04 5 | 93.24 17 | 76.78 52 | 84.91 31 | 94.44 14 | 70.78 40 | 96.61 18 | 84.53 25 | 94.89 28 | 93.66 38 |
|
#test# | | | 87.33 20 | 87.13 20 | 87.94 12 | 94.58 7 | 73.54 11 | 92.34 15 | 93.24 17 | 75.23 82 | 84.91 31 | 94.44 14 | 70.78 40 | 96.61 18 | 83.75 33 | 94.89 28 | 93.66 38 |
|
MCST-MVS | | | 87.37 19 | 87.25 17 | 87.73 21 | 94.53 9 | 72.46 33 | 89.82 55 | 93.82 6 | 73.07 126 | 84.86 36 | 92.89 47 | 76.22 7 | 96.33 25 | 84.89 21 | 95.13 24 | 94.40 12 |
|
APDe-MVS | | | 89.15 3 | 89.63 3 | 87.73 21 | 94.49 10 | 71.69 43 | 93.83 2 | 93.96 4 | 75.70 72 | 91.06 4 | 96.03 1 | 76.84 5 | 97.03 7 | 89.09 2 | 95.65 15 | 94.47 11 |
|
DP-MVS Recon | | | 83.11 68 | 82.09 73 | 86.15 51 | 94.44 11 | 70.92 53 | 88.79 83 | 92.20 54 | 70.53 166 | 79.17 93 | 91.03 81 | 64.12 91 | 96.03 33 | 68.39 161 | 90.14 75 | 91.50 104 |
|
XVS | | | 87.18 22 | 86.91 24 | 88.00 9 | 94.42 12 | 73.33 16 | 92.78 9 | 92.99 28 | 79.14 21 | 83.67 52 | 94.17 21 | 67.45 66 | 96.60 20 | 83.06 38 | 94.50 35 | 94.07 23 |
|
X-MVStestdata | | | 80.37 118 | 77.83 152 | 88.00 9 | 94.42 12 | 73.33 16 | 92.78 9 | 92.99 28 | 79.14 21 | 83.67 52 | 12.47 349 | 67.45 66 | 96.60 20 | 83.06 38 | 94.50 35 | 94.07 23 |
|
mPP-MVS | | | 86.67 29 | 86.32 30 | 87.72 23 | 94.41 14 | 73.55 9 | 92.74 11 | 92.22 53 | 76.87 50 | 82.81 62 | 94.25 19 | 66.44 73 | 96.24 28 | 82.88 42 | 94.28 41 | 93.38 51 |
|
NCCC | | | 88.06 8 | 88.01 11 | 88.24 5 | 94.41 14 | 73.62 7 | 91.22 32 | 92.83 35 | 81.50 7 | 85.79 23 | 93.47 35 | 73.02 26 | 97.00 8 | 84.90 19 | 94.94 26 | 94.10 21 |
|
MP-MVS | | | 87.71 12 | 87.64 13 | 87.93 15 | 94.36 16 | 73.88 4 | 92.71 13 | 92.65 42 | 77.57 35 | 83.84 49 | 94.40 17 | 72.24 32 | 96.28 27 | 85.65 15 | 95.30 23 | 93.62 45 |
|
HSP-MVS | | | 89.28 2 | 89.76 2 | 87.85 19 | 94.28 17 | 73.46 14 | 92.90 8 | 92.73 39 | 80.27 13 | 91.35 3 | 94.16 22 | 78.35 4 | 96.77 11 | 89.59 1 | 94.22 44 | 93.33 54 |
|
APD-MVS | | | 87.44 16 | 87.52 14 | 87.19 32 | 94.24 18 | 72.39 34 | 91.86 24 | 92.83 35 | 73.01 127 | 88.58 8 | 94.52 9 | 73.36 23 | 96.49 23 | 84.26 29 | 95.01 25 | 92.70 71 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
PGM-MVS | | | 86.68 28 | 86.27 31 | 87.90 16 | 94.22 19 | 73.38 15 | 90.22 50 | 93.04 23 | 75.53 76 | 83.86 48 | 94.42 16 | 67.87 63 | 96.64 17 | 82.70 43 | 94.57 34 | 93.66 38 |
|
CP-MVS | | | 87.11 23 | 86.92 23 | 87.68 26 | 94.20 20 | 73.86 5 | 93.98 1 | 92.82 37 | 76.62 57 | 83.68 51 | 94.46 13 | 67.93 61 | 95.95 37 | 84.20 31 | 94.39 38 | 93.23 56 |
|
MPTG | | | 87.53 15 | 87.41 16 | 87.90 16 | 94.18 21 | 74.25 2 | 90.23 49 | 92.02 60 | 79.45 19 | 85.88 20 | 94.80 6 | 68.07 59 | 96.21 29 | 86.69 10 | 95.34 19 | 93.23 56 |
|
MTAPA | | | 87.23 21 | 87.00 21 | 87.90 16 | 94.18 21 | 74.25 2 | 86.58 162 | 92.02 60 | 79.45 19 | 85.88 20 | 94.80 6 | 68.07 59 | 96.21 29 | 86.69 10 | 95.34 19 | 93.23 56 |
|
114514_t | | | 80.68 107 | 79.51 112 | 84.20 90 | 94.09 23 | 67.27 120 | 89.64 63 | 91.11 96 | 58.75 291 | 74.08 192 | 90.72 86 | 58.10 172 | 95.04 65 | 69.70 151 | 89.42 83 | 90.30 146 |
|
HPM-MVS | | | 87.11 23 | 86.98 22 | 87.50 29 | 93.88 24 | 72.16 38 | 92.19 20 | 93.33 16 | 76.07 69 | 83.81 50 | 93.95 28 | 69.77 50 | 96.01 34 | 85.15 16 | 94.66 32 | 94.32 17 |
|
ACMMP_Plus | | | 88.05 10 | 88.08 10 | 87.94 12 | 93.70 25 | 73.05 18 | 90.86 35 | 93.59 9 | 76.27 66 | 88.14 9 | 95.09 5 | 71.06 38 | 96.67 15 | 87.67 6 | 96.37 4 | 94.09 22 |
|
HPM-MVS_fast | | | 85.35 49 | 84.95 50 | 86.57 45 | 93.69 26 | 70.58 58 | 92.15 21 | 91.62 80 | 73.89 102 | 82.67 64 | 94.09 25 | 62.60 122 | 95.54 44 | 80.93 51 | 92.93 50 | 93.57 46 |
|
TSAR-MVS + MP. | | | 88.02 11 | 88.11 9 | 87.72 23 | 93.68 27 | 72.13 39 | 91.41 28 | 92.35 50 | 74.62 91 | 88.90 7 | 93.85 29 | 75.75 10 | 96.00 35 | 87.80 5 | 94.63 33 | 95.04 2 |
|
MP-MVS-pluss | | | 87.67 13 | 87.72 12 | 87.54 27 | 93.64 28 | 72.04 40 | 89.80 57 | 93.50 11 | 75.17 85 | 86.34 18 | 95.29 2 | 70.86 39 | 96.00 35 | 88.78 3 | 96.04 5 | 94.58 7 |
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
ACMMP | | | 85.89 41 | 85.39 43 | 87.38 30 | 93.59 29 | 72.63 28 | 92.74 11 | 93.18 21 | 76.78 52 | 80.73 84 | 93.82 30 | 64.33 89 | 96.29 26 | 82.67 44 | 90.69 69 | 93.23 56 |
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_fast | | 79.65 3 | 86.91 26 | 86.62 27 | 87.76 20 | 93.52 30 | 72.37 36 | 91.26 29 | 93.04 23 | 76.62 57 | 84.22 45 | 93.36 37 | 71.44 36 | 96.76 12 | 80.82 53 | 95.33 21 | 94.16 19 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
CDPH-MVS | | | 85.76 42 | 85.29 47 | 87.17 33 | 93.49 31 | 71.08 47 | 88.58 92 | 92.42 48 | 68.32 208 | 84.61 38 | 93.48 33 | 72.32 31 | 96.15 32 | 79.00 62 | 95.43 17 | 94.28 18 |
|
agg_prior3 | | | 86.16 38 | 85.85 39 | 87.10 35 | 93.31 32 | 72.86 23 | 88.77 84 | 91.68 79 | 68.29 209 | 84.26 44 | 92.83 49 | 72.83 27 | 95.42 49 | 84.97 17 | 95.71 12 | 93.02 65 |
|
DP-MVS | | | 76.78 195 | 74.57 210 | 83.42 113 | 93.29 33 | 69.46 78 | 88.55 93 | 83.70 237 | 63.98 250 | 70.20 238 | 88.89 120 | 54.01 205 | 94.80 75 | 46.66 298 | 81.88 171 | 86.01 274 |
|
CPTT-MVS | | | 83.73 57 | 83.33 58 | 84.92 73 | 93.28 34 | 70.86 54 | 92.09 22 | 90.38 113 | 68.75 197 | 79.57 89 | 92.83 49 | 60.60 158 | 93.04 152 | 80.92 52 | 91.56 61 | 90.86 119 |
|
TEST9 | | | | | | 93.26 35 | 72.96 19 | 88.75 86 | 91.89 69 | 68.44 202 | 85.00 29 | 93.10 41 | 74.36 18 | 95.41 50 | | | |
|
train_agg | | | 86.43 32 | 86.20 32 | 87.13 34 | 93.26 35 | 72.96 19 | 88.75 86 | 91.89 69 | 68.69 198 | 85.00 29 | 93.10 41 | 74.43 15 | 95.41 50 | 84.97 17 | 95.71 12 | 93.02 65 |
|
test_8 | | | | | | 93.13 37 | 72.57 30 | 88.68 89 | 91.84 72 | 68.69 198 | 84.87 35 | 93.10 41 | 74.43 15 | 95.16 58 | | | |
|
新几何1 | | | | | 83.42 113 | 93.13 37 | 70.71 56 | | 85.48 222 | 57.43 300 | 81.80 72 | 91.98 58 | 63.28 98 | 92.27 173 | 64.60 190 | 92.99 49 | 87.27 244 |
|
1121 | | | 80.84 98 | 79.77 103 | 84.05 95 | 93.11 39 | 70.78 55 | 84.66 210 | 85.42 223 | 57.37 301 | 81.76 73 | 92.02 57 | 63.41 96 | 94.12 95 | 67.28 167 | 92.93 50 | 87.26 245 |
|
AdaColmap | | | 80.58 111 | 79.42 114 | 84.06 94 | 93.09 40 | 68.91 86 | 89.36 66 | 88.97 167 | 69.27 185 | 75.70 168 | 89.69 102 | 57.20 181 | 95.77 39 | 63.06 197 | 88.41 98 | 87.50 239 |
|
原ACMM1 | | | | | 84.35 86 | 93.01 41 | 68.79 87 | | 92.44 45 | 63.96 251 | 81.09 80 | 91.57 68 | 66.06 77 | 95.45 47 | 67.19 169 | 94.82 31 | 88.81 202 |
|
CSCG | | | 86.41 34 | 86.19 33 | 87.07 36 | 92.91 42 | 72.48 32 | 90.81 36 | 93.56 10 | 73.95 99 | 83.16 57 | 91.07 78 | 75.94 8 | 95.19 57 | 79.94 60 | 94.38 39 | 93.55 47 |
|
agg_prior1 | | | 86.22 37 | 86.09 36 | 86.62 43 | 92.85 43 | 71.94 41 | 88.59 91 | 91.78 75 | 68.96 195 | 84.41 41 | 93.18 40 | 74.94 11 | 94.93 67 | 84.75 24 | 95.33 21 | 93.01 67 |
|
agg_prior | | | | | | 92.85 43 | 71.94 41 | | 91.78 75 | | 84.41 41 | | | 94.93 67 | | | |
|
MG-MVS | | | 83.41 63 | 83.45 56 | 83.28 118 | 92.74 45 | 62.28 218 | 88.17 107 | 89.50 145 | 75.22 83 | 81.49 74 | 92.74 53 | 66.75 70 | 95.11 60 | 72.85 123 | 91.58 60 | 92.45 78 |
|
APD-MVS_3200maxsize | | | 85.97 39 | 85.88 37 | 86.22 50 | 92.69 46 | 69.53 75 | 91.93 23 | 92.99 28 | 73.54 113 | 85.94 19 | 94.51 12 | 65.80 80 | 95.61 41 | 83.04 40 | 92.51 55 | 93.53 49 |
|
test12 | | | | | 86.80 39 | 92.63 47 | 70.70 57 | | 91.79 74 | | 82.71 63 | | 71.67 34 | 96.16 31 | | 94.50 35 | 93.54 48 |
|
test_prior3 | | | 86.73 27 | 86.86 26 | 86.33 47 | 92.61 48 | 69.59 73 | 88.85 81 | 92.97 31 | 75.41 78 | 84.91 31 | 93.54 31 | 74.28 19 | 95.48 45 | 83.31 34 | 95.86 8 | 93.91 30 |
|
test_prior | | | | | 86.33 47 | 92.61 48 | 69.59 73 | | 92.97 31 | | | | | 95.48 45 | | | 93.91 30 |
|
SD-MVS | | | 88.06 8 | 88.50 8 | 86.71 41 | 92.60 50 | 72.71 24 | 91.81 25 | 93.19 20 | 77.87 32 | 90.32 5 | 94.00 27 | 74.83 12 | 93.78 114 | 87.63 7 | 94.27 42 | 93.65 43 |
|
PAPM_NR | | | 83.02 69 | 82.41 68 | 84.82 75 | 92.47 51 | 66.37 132 | 87.93 114 | 91.80 73 | 73.82 107 | 77.32 133 | 90.66 87 | 67.90 62 | 94.90 71 | 70.37 146 | 89.48 82 | 93.19 60 |
|
DeepPCF-MVS | | 80.84 1 | 88.10 7 | 88.56 7 | 86.73 40 | 92.24 52 | 69.03 81 | 89.57 64 | 93.39 15 | 77.53 39 | 89.79 6 | 94.12 24 | 78.98 3 | 96.58 22 | 85.66 14 | 95.72 11 | 94.58 7 |
|
abl_6 | | | 85.23 50 | 84.95 50 | 86.07 53 | 92.23 53 | 70.48 59 | 90.80 37 | 92.08 58 | 73.51 114 | 85.26 26 | 94.16 22 | 62.75 115 | 95.92 38 | 82.46 46 | 91.30 64 | 91.81 98 |
|
SteuartSystems-ACMMP | | | 88.72 6 | 88.86 6 | 88.32 4 | 92.14 54 | 72.96 19 | 93.73 3 | 93.67 8 | 80.19 15 | 88.10 10 | 94.80 6 | 73.76 22 | 97.11 5 | 87.51 8 | 95.82 10 | 94.90 4 |
Skip Steuart: Steuart Systems R&D Blog. |
UA-Net | | | 85.08 53 | 84.96 49 | 85.45 58 | 92.07 55 | 68.07 107 | 89.78 58 | 90.86 101 | 82.48 2 | 84.60 39 | 93.20 39 | 69.35 53 | 95.22 56 | 71.39 142 | 90.88 68 | 93.07 63 |
|
旧先验1 | | | | | | 91.96 56 | 65.79 142 | | 86.37 214 | | | 93.08 45 | 69.31 54 | | | 92.74 52 | 88.74 205 |
|
MSLP-MVS++ | | | 85.43 47 | 85.76 41 | 84.45 82 | 91.93 57 | 70.24 60 | 90.71 38 | 92.86 33 | 77.46 41 | 84.22 45 | 92.81 52 | 67.16 69 | 92.94 154 | 80.36 56 | 94.35 40 | 90.16 149 |
|
LFMVS | | | 81.82 84 | 81.23 83 | 83.57 110 | 91.89 58 | 63.43 199 | 89.84 54 | 81.85 266 | 77.04 47 | 83.21 55 | 93.10 41 | 52.26 217 | 93.43 134 | 71.98 136 | 89.95 78 | 93.85 33 |
|
PLC | | 70.83 11 | 78.05 165 | 76.37 176 | 83.08 127 | 91.88 59 | 67.80 111 | 88.19 106 | 89.46 147 | 64.33 246 | 69.87 248 | 88.38 134 | 53.66 207 | 93.58 125 | 58.86 233 | 82.73 162 | 87.86 231 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
MVS_111021_HR | | | 85.14 52 | 84.75 52 | 86.32 49 | 91.65 60 | 72.70 25 | 85.98 177 | 90.33 118 | 76.11 68 | 82.08 68 | 91.61 67 | 71.36 37 | 94.17 94 | 81.02 50 | 92.58 54 | 92.08 91 |
|
test222 | | | | | | 91.50 61 | 68.26 103 | 84.16 227 | 83.20 248 | 54.63 312 | 79.74 87 | 91.63 66 | 58.97 167 | | | 91.42 62 | 86.77 256 |
|
TSAR-MVS + GP. | | | 85.71 43 | 85.33 44 | 86.84 38 | 91.34 62 | 72.50 31 | 89.07 76 | 87.28 204 | 76.41 59 | 85.80 22 | 90.22 94 | 74.15 21 | 95.37 54 | 81.82 47 | 91.88 57 | 92.65 74 |
|
MAR-MVS | | | 81.84 83 | 80.70 89 | 85.27 62 | 91.32 63 | 71.53 45 | 89.82 55 | 90.92 99 | 69.77 176 | 78.50 102 | 86.21 204 | 62.36 129 | 94.52 81 | 65.36 183 | 92.05 56 | 89.77 176 |
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 |
DeepC-MVS | | 79.81 2 | 87.08 25 | 86.88 25 | 87.69 25 | 91.16 64 | 72.32 37 | 90.31 47 | 93.94 5 | 77.12 44 | 82.82 61 | 94.23 20 | 72.13 33 | 97.09 6 | 84.83 22 | 95.37 18 | 93.65 43 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
3Dnovator+ | | 77.84 4 | 85.48 45 | 84.47 53 | 88.51 2 | 91.08 65 | 73.49 13 | 93.18 4 | 93.78 7 | 80.79 11 | 76.66 144 | 93.37 36 | 60.40 162 | 96.75 13 | 77.20 80 | 93.73 47 | 95.29 1 |
|
VDD-MVS | | | 83.01 70 | 82.36 70 | 84.96 70 | 91.02 66 | 66.40 131 | 88.91 78 | 88.11 187 | 77.57 35 | 84.39 43 | 93.29 38 | 52.19 218 | 93.91 105 | 77.05 83 | 88.70 90 | 94.57 9 |
|
API-MVS | | | 81.99 81 | 81.23 83 | 84.26 89 | 90.94 67 | 70.18 66 | 91.10 33 | 89.32 150 | 71.51 154 | 78.66 100 | 88.28 137 | 65.26 82 | 95.10 63 | 64.74 189 | 91.23 65 | 87.51 238 |
|
testdata | | | | | 79.97 207 | 90.90 68 | 64.21 183 | | 84.71 228 | 59.27 287 | 85.40 24 | 92.91 46 | 62.02 135 | 89.08 251 | 68.95 156 | 91.37 63 | 86.63 260 |
|
PHI-MVS | | | 86.43 32 | 86.17 34 | 87.24 31 | 90.88 69 | 70.96 49 | 92.27 17 | 94.07 3 | 72.45 138 | 85.22 27 | 91.90 60 | 69.47 52 | 96.42 24 | 83.28 36 | 95.94 7 | 94.35 14 |
|
VNet | | | 82.21 77 | 82.41 68 | 81.62 178 | 90.82 70 | 60.93 225 | 84.47 216 | 89.78 138 | 76.36 64 | 84.07 47 | 91.88 61 | 64.71 87 | 90.26 226 | 70.68 143 | 88.89 86 | 93.66 38 |
|
PVSNet_Blended_VisFu | | | 82.62 73 | 81.83 78 | 84.96 70 | 90.80 71 | 69.76 70 | 88.74 88 | 91.70 78 | 69.39 181 | 78.96 95 | 88.46 132 | 65.47 81 | 94.87 73 | 74.42 107 | 88.57 93 | 90.24 147 |
|
LS3D | | | 76.95 193 | 74.82 208 | 83.37 116 | 90.45 72 | 67.36 119 | 89.15 74 | 86.94 207 | 61.87 269 | 69.52 251 | 90.61 88 | 51.71 233 | 94.53 80 | 46.38 301 | 86.71 116 | 88.21 224 |
|
VDDNet | | | 81.52 89 | 80.67 90 | 84.05 95 | 90.44 73 | 64.13 185 | 89.73 60 | 85.91 220 | 71.11 157 | 83.18 56 | 93.48 33 | 50.54 251 | 93.49 129 | 73.40 119 | 88.25 99 | 94.54 10 |
|
CNLPA | | | 78.08 164 | 76.79 170 | 81.97 165 | 90.40 74 | 71.07 48 | 87.59 120 | 84.55 230 | 66.03 231 | 72.38 214 | 89.64 104 | 57.56 176 | 86.04 280 | 59.61 226 | 83.35 154 | 88.79 203 |
|
PAPR | | | 81.66 87 | 80.89 88 | 83.99 100 | 90.27 75 | 64.00 189 | 86.76 158 | 91.77 77 | 68.84 196 | 77.13 140 | 89.50 106 | 67.63 64 | 94.88 72 | 67.55 164 | 88.52 96 | 93.09 62 |
|
Vis-MVSNet | | | 83.46 62 | 82.80 66 | 85.43 59 | 90.25 76 | 68.74 91 | 90.30 48 | 90.13 127 | 76.33 65 | 80.87 83 | 92.89 47 | 61.00 151 | 94.20 91 | 72.45 130 | 90.97 66 | 93.35 53 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
MVS_0304 | | | 86.37 36 | 85.81 40 | 88.02 8 | 90.13 77 | 72.39 34 | 89.66 62 | 92.75 38 | 81.64 6 | 82.66 65 | 92.04 56 | 64.44 88 | 97.35 3 | 84.76 23 | 94.25 43 | 94.33 16 |
|
EPP-MVSNet | | | 83.40 64 | 83.02 62 | 84.57 78 | 90.13 77 | 64.47 179 | 92.32 16 | 90.73 102 | 74.45 93 | 79.35 92 | 91.10 76 | 69.05 56 | 95.12 59 | 72.78 124 | 87.22 110 | 94.13 20 |
|
CANet | | | 86.45 31 | 86.10 35 | 87.51 28 | 90.09 79 | 70.94 51 | 89.70 61 | 92.59 43 | 81.78 4 | 81.32 75 | 91.43 73 | 70.34 43 | 97.23 4 | 84.26 29 | 93.36 48 | 94.37 13 |
|
HQP_MVS | | | 83.64 59 | 83.14 59 | 85.14 65 | 90.08 80 | 68.71 93 | 91.25 30 | 92.44 45 | 79.12 23 | 78.92 96 | 91.00 82 | 60.42 160 | 95.38 52 | 78.71 65 | 86.32 121 | 91.33 107 |
|
plane_prior7 | | | | | | 90.08 80 | 68.51 99 | | | | | | | | | | |
|
CHOSEN 1792x2688 | | | 77.63 179 | 75.69 191 | 83.44 112 | 89.98 82 | 68.58 98 | 78.70 281 | 87.50 201 | 56.38 306 | 75.80 163 | 86.84 174 | 58.67 168 | 91.40 204 | 61.58 212 | 85.75 128 | 90.34 145 |
|
IS-MVSNet | | | 83.15 66 | 82.81 65 | 84.18 91 | 89.94 83 | 63.30 201 | 91.59 26 | 88.46 184 | 79.04 25 | 79.49 90 | 92.16 54 | 65.10 84 | 94.28 86 | 67.71 162 | 91.86 58 | 94.95 3 |
|
plane_prior1 | | | | | | 89.90 84 | | | | | | | | | | | |
|
canonicalmvs | | | 85.91 40 | 85.87 38 | 86.04 54 | 89.84 85 | 69.44 79 | 90.45 45 | 93.00 26 | 76.70 56 | 88.01 12 | 91.23 75 | 73.28 24 | 93.91 105 | 81.50 49 | 88.80 88 | 94.77 5 |
|
plane_prior6 | | | | | | 89.84 85 | 68.70 95 | | | | | | 60.42 160 | | | | |
|
view600 | | | 76.20 206 | 75.21 202 | 79.16 224 | 89.64 87 | 55.82 282 | 85.74 186 | 82.06 261 | 73.88 103 | 75.74 164 | 87.85 145 | 51.84 228 | 91.66 196 | 46.75 294 | 83.42 150 | 90.00 160 |
|
view800 | | | 76.20 206 | 75.21 202 | 79.16 224 | 89.64 87 | 55.82 282 | 85.74 186 | 82.06 261 | 73.88 103 | 75.74 164 | 87.85 145 | 51.84 228 | 91.66 196 | 46.75 294 | 83.42 150 | 90.00 160 |
|
conf0.05thres1000 | | | 76.20 206 | 75.21 202 | 79.16 224 | 89.64 87 | 55.82 282 | 85.74 186 | 82.06 261 | 73.88 103 | 75.74 164 | 87.85 145 | 51.84 228 | 91.66 196 | 46.75 294 | 83.42 150 | 90.00 160 |
|
tfpn | | | 76.20 206 | 75.21 202 | 79.16 224 | 89.64 87 | 55.82 282 | 85.74 186 | 82.06 261 | 73.88 103 | 75.74 164 | 87.85 145 | 51.84 228 | 91.66 196 | 46.75 294 | 83.42 150 | 90.00 160 |
|
NP-MVS | | | | | | 89.62 91 | 68.32 101 | | | | | 90.24 92 | | | | | |
|
HyFIR lowres test | | | 77.53 180 | 75.40 198 | 83.94 103 | 89.59 92 | 66.62 128 | 80.36 265 | 88.64 181 | 56.29 307 | 76.45 147 | 85.17 230 | 57.64 175 | 93.28 137 | 61.34 215 | 83.10 158 | 91.91 94 |
|
TAPA-MVS | | 73.13 9 | 79.15 145 | 77.94 150 | 82.79 149 | 89.59 92 | 62.99 211 | 88.16 108 | 91.51 85 | 65.77 232 | 77.14 139 | 91.09 77 | 60.91 152 | 93.21 139 | 50.26 277 | 87.05 112 | 92.17 89 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
conf200view11 | | | 76.55 197 | 75.55 194 | 79.57 217 | 89.52 94 | 56.99 264 | 85.83 182 | 83.23 245 | 73.94 100 | 76.32 152 | 87.12 169 | 51.89 225 | 91.95 179 | 48.33 284 | 83.75 143 | 89.78 174 |
|
thres100view900 | | | 76.50 199 | 75.55 194 | 79.33 219 | 89.52 94 | 56.99 264 | 85.83 182 | 83.23 245 | 73.94 100 | 76.32 152 | 87.12 169 | 51.89 225 | 91.95 179 | 48.33 284 | 83.75 143 | 89.07 185 |
|
alignmvs | | | 85.48 45 | 85.32 45 | 85.96 55 | 89.51 96 | 69.47 77 | 89.74 59 | 92.47 44 | 76.17 67 | 87.73 14 | 91.46 72 | 70.32 44 | 93.78 114 | 81.51 48 | 88.95 85 | 94.63 6 |
|
PS-MVSNAJ | | | 81.69 85 | 81.02 87 | 83.70 106 | 89.51 96 | 68.21 105 | 84.28 225 | 90.09 128 | 70.79 161 | 81.26 79 | 85.62 222 | 63.15 103 | 94.29 85 | 75.62 98 | 88.87 87 | 88.59 214 |
|
ACMP | | 74.13 6 | 81.51 91 | 80.57 91 | 84.36 85 | 89.42 98 | 68.69 96 | 89.97 53 | 91.50 87 | 74.46 92 | 75.04 185 | 90.41 90 | 53.82 206 | 94.54 79 | 77.56 76 | 82.91 159 | 89.86 170 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
thres600view7 | | | 76.50 199 | 75.44 196 | 79.68 212 | 89.40 99 | 57.16 261 | 85.53 196 | 83.23 245 | 73.79 108 | 76.26 154 | 87.09 171 | 51.89 225 | 91.89 183 | 48.05 290 | 83.72 147 | 90.00 160 |
|
BH-RMVSNet | | | 79.61 134 | 78.44 140 | 83.14 124 | 89.38 100 | 65.93 138 | 84.95 206 | 87.15 205 | 73.56 112 | 78.19 117 | 89.79 101 | 56.67 184 | 93.36 135 | 59.53 228 | 86.74 115 | 90.13 151 |
|
Regformer-1 | | | 86.41 34 | 86.33 29 | 86.64 42 | 89.33 101 | 70.93 52 | 88.43 94 | 91.39 89 | 82.14 3 | 86.65 17 | 90.09 96 | 74.39 17 | 95.01 66 | 83.97 32 | 90.63 70 | 93.97 29 |
|
Regformer-2 | | | 86.63 30 | 86.53 28 | 86.95 37 | 89.33 101 | 71.24 46 | 88.43 94 | 92.05 59 | 82.50 1 | 86.88 16 | 90.09 96 | 74.45 14 | 95.61 41 | 84.38 27 | 90.63 70 | 94.01 27 |
|
HQP-NCC | | | | | | 89.33 101 | | 89.17 70 | | 76.41 59 | 77.23 136 | | | | | | |
|
ACMP_Plane | | | | | | 89.33 101 | | 89.17 70 | | 76.41 59 | 77.23 136 | | | | | | |
|
HQP-MVS | | | 82.61 74 | 82.02 75 | 84.37 84 | 89.33 101 | 66.98 124 | 89.17 70 | 92.19 55 | 76.41 59 | 77.23 136 | 90.23 93 | 60.17 163 | 95.11 60 | 77.47 77 | 85.99 125 | 91.03 113 |
|
ACMM | | 73.20 8 | 80.78 106 | 79.84 102 | 83.58 109 | 89.31 106 | 68.37 100 | 89.99 52 | 91.60 81 | 70.28 170 | 77.25 134 | 89.66 103 | 53.37 209 | 93.53 128 | 74.24 110 | 82.85 160 | 88.85 200 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
Test_1112_low_res | | | 76.40 203 | 75.44 196 | 79.27 220 | 89.28 107 | 58.09 246 | 81.69 255 | 87.07 206 | 59.53 285 | 72.48 207 | 86.67 184 | 61.30 144 | 89.33 241 | 60.81 219 | 80.15 192 | 90.41 143 |
|
F-COLMAP | | | 76.38 204 | 74.33 215 | 82.50 156 | 89.28 107 | 66.95 127 | 88.41 97 | 89.03 159 | 64.05 248 | 66.83 279 | 88.61 127 | 46.78 273 | 92.89 155 | 57.48 245 | 78.55 207 | 87.67 234 |
|
LPG-MVS_test | | | 82.08 78 | 81.27 82 | 84.50 80 | 89.23 109 | 68.76 89 | 90.22 50 | 91.94 67 | 75.37 80 | 76.64 145 | 91.51 69 | 54.29 201 | 94.91 69 | 78.44 67 | 83.78 141 | 89.83 171 |
|
LGP-MVS_train | | | | | 84.50 80 | 89.23 109 | 68.76 89 | | 91.94 67 | 75.37 80 | 76.64 145 | 91.51 69 | 54.29 201 | 94.91 69 | 78.44 67 | 83.78 141 | 89.83 171 |
|
BH-untuned | | | 79.47 139 | 78.60 133 | 82.05 163 | 89.19 111 | 65.91 139 | 86.07 176 | 88.52 183 | 72.18 144 | 75.42 172 | 87.69 151 | 61.15 148 | 93.54 127 | 60.38 220 | 86.83 114 | 86.70 258 |
|
xiu_mvs_v2_base | | | 81.69 85 | 81.05 86 | 83.60 108 | 89.15 112 | 68.03 108 | 84.46 218 | 90.02 132 | 70.67 164 | 81.30 78 | 86.53 194 | 63.17 102 | 94.19 92 | 75.60 99 | 88.54 95 | 88.57 216 |
|
tfpn200view9 | | | 76.42 202 | 75.37 199 | 79.55 218 | 89.13 113 | 57.65 256 | 85.17 201 | 83.60 238 | 73.41 116 | 76.45 147 | 86.39 197 | 52.12 219 | 91.95 179 | 48.33 284 | 83.75 143 | 89.07 185 |
|
thres400 | | | 76.50 199 | 75.37 199 | 79.86 208 | 89.13 113 | 57.65 256 | 85.17 201 | 83.60 238 | 73.41 116 | 76.45 147 | 86.39 197 | 52.12 219 | 91.95 179 | 48.33 284 | 83.75 143 | 90.00 160 |
|
1112_ss | | | 77.40 189 | 76.43 174 | 80.32 201 | 89.11 115 | 60.41 231 | 83.65 234 | 87.72 197 | 62.13 267 | 73.05 200 | 86.72 178 | 62.58 124 | 89.97 230 | 62.11 207 | 80.80 182 | 90.59 133 |
|
Regformer-3 | | | 85.23 50 | 85.07 48 | 85.70 57 | 88.95 116 | 69.01 83 | 88.29 103 | 89.91 136 | 80.95 9 | 85.01 28 | 90.01 98 | 72.45 30 | 94.19 92 | 82.50 45 | 87.57 103 | 93.90 32 |
|
Regformer-4 | | | 85.68 44 | 85.45 42 | 86.35 46 | 88.95 116 | 69.67 72 | 88.29 103 | 91.29 91 | 81.73 5 | 85.36 25 | 90.01 98 | 72.62 29 | 95.35 55 | 83.28 36 | 87.57 103 | 94.03 25 |
|
Fast-Effi-MVS+ | | | 80.81 101 | 79.92 100 | 83.47 111 | 88.85 118 | 64.51 173 | 85.53 196 | 89.39 148 | 70.79 161 | 78.49 103 | 85.06 233 | 67.54 65 | 93.58 125 | 67.03 172 | 86.58 117 | 92.32 82 |
|
PVSNet_BlendedMVS | | | 80.60 109 | 80.02 98 | 82.36 159 | 88.85 118 | 65.40 148 | 86.16 173 | 92.00 63 | 69.34 184 | 78.11 119 | 86.09 207 | 66.02 78 | 94.27 87 | 71.52 140 | 82.06 168 | 87.39 240 |
|
PVSNet_Blended | | | 80.98 95 | 80.34 94 | 82.90 139 | 88.85 118 | 65.40 148 | 84.43 220 | 92.00 63 | 67.62 214 | 78.11 119 | 85.05 234 | 66.02 78 | 94.27 87 | 71.52 140 | 89.50 81 | 89.01 194 |
|
MVS_111021_LR | | | 82.61 74 | 82.11 72 | 84.11 92 | 88.82 121 | 71.58 44 | 85.15 203 | 86.16 217 | 74.69 90 | 80.47 85 | 91.04 79 | 62.29 130 | 90.55 224 | 80.33 57 | 90.08 76 | 90.20 148 |
|
BH-w/o | | | 78.21 160 | 77.33 162 | 80.84 193 | 88.81 122 | 65.13 158 | 84.87 207 | 87.85 195 | 69.75 177 | 74.52 190 | 84.74 240 | 61.34 143 | 93.11 147 | 58.24 240 | 85.84 127 | 84.27 290 |
|
FIs | | | 82.07 79 | 82.42 67 | 81.04 191 | 88.80 123 | 58.34 244 | 88.26 105 | 93.49 12 | 76.93 49 | 78.47 104 | 91.04 79 | 69.92 48 | 92.34 172 | 69.87 150 | 84.97 130 | 92.44 79 |
|
OPM-MVS | | | 83.50 61 | 82.95 63 | 85.14 65 | 88.79 124 | 70.95 50 | 89.13 75 | 91.52 84 | 77.55 38 | 80.96 82 | 91.75 62 | 60.71 154 | 94.50 82 | 79.67 61 | 86.51 119 | 89.97 167 |
|
WR-MVS | | | 79.49 138 | 79.22 125 | 80.27 203 | 88.79 124 | 58.35 243 | 85.06 204 | 88.61 182 | 78.56 29 | 77.65 127 | 88.34 135 | 63.81 95 | 90.66 223 | 64.98 187 | 77.22 221 | 91.80 99 |
|
OMC-MVS | | | 82.69 72 | 81.97 77 | 84.85 74 | 88.75 126 | 67.42 116 | 87.98 110 | 90.87 100 | 74.92 88 | 79.72 88 | 91.65 64 | 62.19 133 | 93.96 100 | 75.26 103 | 86.42 120 | 93.16 61 |
|
ACMH | | 67.68 16 | 75.89 213 | 73.93 218 | 81.77 169 | 88.71 127 | 66.61 129 | 88.62 90 | 89.01 162 | 69.81 175 | 66.78 280 | 86.70 183 | 41.95 301 | 91.51 203 | 55.64 255 | 78.14 213 | 87.17 247 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
Vis-MVSNet (Re-imp) | | | 78.36 158 | 78.45 138 | 78.07 243 | 88.64 128 | 51.78 309 | 86.70 159 | 79.63 287 | 74.14 97 | 75.11 183 | 90.83 85 | 61.29 145 | 89.75 233 | 58.10 241 | 91.60 59 | 92.69 73 |
|
PatchMatch-RL | | | 72.38 252 | 70.90 251 | 76.80 259 | 88.60 129 | 67.38 118 | 79.53 272 | 76.17 308 | 62.75 261 | 69.36 254 | 82.00 269 | 45.51 282 | 84.89 288 | 53.62 264 | 80.58 185 | 78.12 321 |
|
ACMH+ | | 68.96 14 | 76.01 212 | 74.01 217 | 82.03 164 | 88.60 129 | 65.31 153 | 88.86 80 | 87.55 199 | 70.25 171 | 67.75 270 | 87.47 158 | 41.27 302 | 93.19 142 | 58.37 238 | 75.94 243 | 87.60 236 |
|
LTVRE_ROB | | 69.57 13 | 76.25 205 | 74.54 212 | 81.41 183 | 88.60 129 | 64.38 182 | 79.24 275 | 89.12 158 | 70.76 163 | 69.79 250 | 87.86 144 | 49.09 263 | 93.20 141 | 56.21 254 | 80.16 191 | 86.65 259 |
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 |
DELS-MVS | | | 85.41 48 | 85.30 46 | 85.77 56 | 88.49 132 | 67.93 109 | 85.52 198 | 93.44 13 | 78.70 28 | 83.63 54 | 89.03 119 | 74.57 13 | 95.71 40 | 80.26 58 | 94.04 45 | 93.66 38 |
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 |
CLD-MVS | | | 82.31 76 | 81.65 79 | 84.29 88 | 88.47 133 | 67.73 113 | 85.81 185 | 92.35 50 | 75.78 70 | 78.33 110 | 86.58 191 | 64.01 92 | 94.35 84 | 76.05 90 | 87.48 108 | 90.79 120 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
UniMVSNet_NR-MVSNet | | | 81.88 82 | 81.54 80 | 82.92 138 | 88.46 134 | 63.46 197 | 87.13 142 | 92.37 49 | 80.19 15 | 78.38 108 | 89.14 116 | 71.66 35 | 93.05 150 | 70.05 147 | 76.46 238 | 92.25 85 |
|
ab-mvs | | | 79.51 136 | 78.97 129 | 81.14 189 | 88.46 134 | 60.91 226 | 83.84 232 | 89.24 155 | 70.36 168 | 79.03 94 | 88.87 121 | 63.23 101 | 90.21 228 | 65.12 184 | 82.57 165 | 92.28 84 |
|
FC-MVSNet-test | | | 81.52 89 | 82.02 75 | 80.03 206 | 88.42 136 | 55.97 281 | 87.95 112 | 93.42 14 | 77.10 45 | 77.38 131 | 90.98 84 | 69.96 47 | 91.79 185 | 68.46 160 | 84.50 135 | 92.33 81 |
|
Effi-MVS+ | | | 83.62 60 | 83.08 60 | 85.24 63 | 88.38 137 | 67.45 115 | 88.89 79 | 89.15 157 | 75.50 77 | 82.27 66 | 88.28 137 | 69.61 51 | 94.45 83 | 77.81 74 | 87.84 101 | 93.84 34 |
|
UniMVSNet (Re) | | | 81.60 88 | 81.11 85 | 83.09 126 | 88.38 137 | 64.41 181 | 87.60 119 | 93.02 25 | 78.42 31 | 78.56 101 | 88.16 139 | 69.78 49 | 93.26 138 | 69.58 152 | 76.49 237 | 91.60 100 |
|
VPNet | | | 78.69 153 | 78.66 132 | 78.76 232 | 88.31 139 | 55.72 287 | 84.45 219 | 86.63 210 | 76.79 51 | 78.26 115 | 90.55 89 | 59.30 165 | 89.70 235 | 66.63 173 | 77.05 223 | 90.88 118 |
|
TR-MVS | | | 77.44 187 | 76.18 182 | 81.20 187 | 88.24 140 | 63.24 203 | 84.61 214 | 86.40 213 | 67.55 216 | 77.81 124 | 86.48 196 | 54.10 203 | 93.15 144 | 57.75 244 | 82.72 163 | 87.20 246 |
|
EI-MVSNet-Vis-set | | | 84.19 54 | 83.81 54 | 85.31 60 | 88.18 141 | 67.85 110 | 87.66 118 | 89.73 140 | 80.05 17 | 82.95 58 | 89.59 105 | 70.74 42 | 94.82 74 | 80.66 55 | 84.72 134 | 93.28 55 |
|
test_0402 | | | 72.79 250 | 70.44 253 | 79.84 209 | 88.13 142 | 65.99 137 | 85.93 179 | 84.29 232 | 65.57 235 | 67.40 275 | 85.49 225 | 46.92 272 | 92.61 163 | 35.88 328 | 74.38 263 | 80.94 313 |
|
VPA-MVSNet | | | 80.60 109 | 80.55 92 | 80.76 195 | 88.07 143 | 60.80 228 | 86.86 152 | 91.58 82 | 75.67 73 | 80.24 86 | 89.45 112 | 63.34 97 | 90.25 227 | 70.51 145 | 79.22 206 | 91.23 110 |
|
UGNet | | | 80.83 100 | 79.59 108 | 84.54 79 | 88.04 144 | 68.09 106 | 89.42 65 | 88.16 186 | 76.95 48 | 76.22 155 | 89.46 110 | 49.30 261 | 93.94 102 | 68.48 159 | 90.31 72 | 91.60 100 |
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 |
WR-MVS_H | | | 78.51 155 | 78.49 137 | 78.56 235 | 88.02 145 | 56.38 276 | 88.43 94 | 92.67 40 | 77.14 43 | 73.89 193 | 87.55 155 | 66.25 74 | 89.24 243 | 58.92 232 | 73.55 271 | 90.06 158 |
|
QAPM | | | 80.88 96 | 79.50 113 | 85.03 68 | 88.01 146 | 68.97 85 | 91.59 26 | 92.00 63 | 66.63 224 | 75.15 182 | 92.16 54 | 57.70 174 | 95.45 47 | 63.52 193 | 88.76 89 | 90.66 128 |
|
3Dnovator | | 76.31 5 | 83.38 65 | 82.31 71 | 86.59 44 | 87.94 147 | 72.94 22 | 90.64 39 | 92.14 57 | 77.21 42 | 75.47 169 | 92.83 49 | 58.56 169 | 94.72 77 | 73.24 121 | 92.71 53 | 92.13 90 |
|
EI-MVSNet-UG-set | | | 83.81 56 | 83.38 57 | 85.09 67 | 87.87 148 | 67.53 114 | 87.44 129 | 89.66 141 | 79.74 18 | 82.23 67 | 89.41 114 | 70.24 45 | 94.74 76 | 79.95 59 | 83.92 140 | 92.99 68 |
|
conf0.002 | | | 73.67 232 | 72.42 232 | 77.42 252 | 87.85 149 | 53.28 301 | 83.38 238 | 79.08 290 | 68.40 203 | 72.45 208 | 86.08 208 | 50.60 246 | 89.19 244 | 44.25 309 | 79.66 195 | 89.78 174 |
|
thresconf0.02 | | | 73.39 237 | 72.42 232 | 76.31 262 | 87.85 149 | 53.28 301 | 83.38 238 | 79.08 290 | 68.40 203 | 72.45 208 | 86.08 208 | 50.60 246 | 89.19 244 | 44.25 309 | 79.66 195 | 86.48 261 |
|
tfpn_n400 | | | 73.39 237 | 72.42 232 | 76.31 262 | 87.85 149 | 53.28 301 | 83.38 238 | 79.08 290 | 68.40 203 | 72.45 208 | 86.08 208 | 50.60 246 | 89.19 244 | 44.25 309 | 79.66 195 | 86.48 261 |
|
tfpnconf | | | 73.39 237 | 72.42 232 | 76.31 262 | 87.85 149 | 53.28 301 | 83.38 238 | 79.08 290 | 68.40 203 | 72.45 208 | 86.08 208 | 50.60 246 | 89.19 244 | 44.25 309 | 79.66 195 | 86.48 261 |
|
tfpnview11 | | | 73.39 237 | 72.42 232 | 76.31 262 | 87.85 149 | 53.28 301 | 83.38 238 | 79.08 290 | 68.40 203 | 72.45 208 | 86.08 208 | 50.60 246 | 89.19 244 | 44.25 309 | 79.66 195 | 86.48 261 |
|
TranMVSNet+NR-MVSNet | | | 80.84 98 | 80.31 95 | 82.42 157 | 87.85 149 | 62.33 216 | 87.74 117 | 91.33 90 | 80.55 12 | 77.99 122 | 89.86 100 | 65.23 83 | 92.62 162 | 67.05 171 | 75.24 256 | 92.30 83 |
|
CP-MVSNet | | | 78.22 159 | 78.34 143 | 77.84 245 | 87.83 155 | 54.54 292 | 87.94 113 | 91.17 95 | 77.65 33 | 73.48 195 | 88.49 131 | 62.24 132 | 88.43 262 | 62.19 204 | 74.07 264 | 90.55 137 |
|
tfpn1000 | | | 73.44 236 | 72.49 230 | 76.29 266 | 87.81 156 | 53.69 298 | 84.05 231 | 78.81 296 | 67.99 211 | 72.09 220 | 86.27 203 | 49.95 256 | 89.04 252 | 44.09 314 | 81.38 175 | 86.15 269 |
|
DU-MVS | | | 81.12 94 | 80.52 93 | 82.90 139 | 87.80 157 | 63.46 197 | 87.02 147 | 91.87 71 | 79.01 26 | 78.38 108 | 89.07 117 | 65.02 85 | 93.05 150 | 70.05 147 | 76.46 238 | 92.20 87 |
|
NR-MVSNet | | | 80.23 121 | 79.38 116 | 82.78 150 | 87.80 157 | 63.34 200 | 86.31 170 | 91.09 97 | 79.01 26 | 72.17 216 | 89.07 117 | 67.20 68 | 92.81 160 | 66.08 178 | 75.65 247 | 92.20 87 |
|
TAMVS | | | 78.89 151 | 77.51 159 | 83.03 130 | 87.80 157 | 67.79 112 | 84.72 209 | 85.05 227 | 67.63 213 | 76.75 142 | 87.70 150 | 62.25 131 | 90.82 220 | 58.53 237 | 87.13 111 | 90.49 139 |
|
tfpn_ndepth | | | 73.70 230 | 72.75 227 | 76.52 260 | 87.78 160 | 54.92 290 | 84.32 224 | 80.28 282 | 67.57 215 | 72.50 205 | 84.82 237 | 50.12 254 | 89.44 240 | 45.73 304 | 81.66 173 | 85.20 280 |
|
thres200 | | | 75.55 217 | 74.47 213 | 78.82 231 | 87.78 160 | 57.85 253 | 83.07 245 | 83.51 241 | 72.44 140 | 75.84 162 | 84.42 242 | 52.08 221 | 91.75 188 | 47.41 292 | 83.64 148 | 86.86 254 |
|
PS-CasMVS | | | 78.01 167 | 78.09 147 | 77.77 247 | 87.71 162 | 54.39 294 | 88.02 109 | 91.22 92 | 77.50 40 | 73.26 197 | 88.64 126 | 60.73 153 | 88.41 263 | 61.88 208 | 73.88 268 | 90.53 138 |
|
PCF-MVS | | 73.52 7 | 80.38 117 | 78.84 130 | 85.01 69 | 87.71 162 | 68.99 84 | 83.65 234 | 91.46 88 | 63.00 256 | 77.77 126 | 90.28 91 | 66.10 75 | 95.09 64 | 61.40 213 | 88.22 100 | 90.94 117 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
GBi-Net | | | 78.40 156 | 77.40 160 | 81.40 184 | 87.60 164 | 63.01 208 | 88.39 98 | 89.28 151 | 71.63 150 | 75.34 175 | 87.28 161 | 54.80 194 | 91.11 211 | 62.72 198 | 79.57 200 | 90.09 154 |
|
test1 | | | 78.40 156 | 77.40 160 | 81.40 184 | 87.60 164 | 63.01 208 | 88.39 98 | 89.28 151 | 71.63 150 | 75.34 175 | 87.28 161 | 54.80 194 | 91.11 211 | 62.72 198 | 79.57 200 | 90.09 154 |
|
FMVSNet2 | | | 78.20 161 | 77.21 163 | 81.20 187 | 87.60 164 | 62.89 212 | 87.47 128 | 89.02 160 | 71.63 150 | 75.29 179 | 87.28 161 | 54.80 194 | 91.10 214 | 62.38 202 | 79.38 203 | 89.61 179 |
|
CDS-MVSNet | | | 79.07 147 | 77.70 156 | 83.17 122 | 87.60 164 | 68.23 104 | 84.40 222 | 86.20 216 | 67.49 217 | 76.36 151 | 86.54 193 | 61.54 139 | 90.79 221 | 61.86 209 | 87.33 109 | 90.49 139 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
HY-MVS | | 69.67 12 | 77.95 169 | 77.15 164 | 80.36 199 | 87.57 168 | 60.21 232 | 83.37 244 | 87.78 196 | 66.11 228 | 75.37 174 | 87.06 173 | 63.27 99 | 90.48 225 | 61.38 214 | 82.43 166 | 90.40 144 |
|
xiu_mvs_v1_base_debu | | | 80.80 103 | 79.72 105 | 84.03 97 | 87.35 169 | 70.19 63 | 85.56 191 | 88.77 176 | 69.06 190 | 81.83 69 | 88.16 139 | 50.91 240 | 92.85 156 | 78.29 71 | 87.56 105 | 89.06 187 |
|
xiu_mvs_v1_base | | | 80.80 103 | 79.72 105 | 84.03 97 | 87.35 169 | 70.19 63 | 85.56 191 | 88.77 176 | 69.06 190 | 81.83 69 | 88.16 139 | 50.91 240 | 92.85 156 | 78.29 71 | 87.56 105 | 89.06 187 |
|
xiu_mvs_v1_base_debi | | | 80.80 103 | 79.72 105 | 84.03 97 | 87.35 169 | 70.19 63 | 85.56 191 | 88.77 176 | 69.06 190 | 81.83 69 | 88.16 139 | 50.91 240 | 92.85 156 | 78.29 71 | 87.56 105 | 89.06 187 |
|
MVSFormer | | | 82.85 71 | 82.05 74 | 85.24 63 | 87.35 169 | 70.21 61 | 90.50 42 | 90.38 113 | 68.55 200 | 81.32 75 | 89.47 108 | 61.68 136 | 93.46 130 | 78.98 63 | 90.26 73 | 92.05 92 |
|
lupinMVS | | | 81.39 92 | 80.27 97 | 84.76 76 | 87.35 169 | 70.21 61 | 85.55 194 | 86.41 212 | 62.85 259 | 81.32 75 | 88.61 127 | 61.68 136 | 92.24 175 | 78.41 69 | 90.26 73 | 91.83 96 |
|
PAPM | | | 77.68 176 | 76.40 175 | 81.51 181 | 87.29 174 | 61.85 222 | 83.78 233 | 89.59 142 | 64.74 241 | 71.23 228 | 88.70 123 | 62.59 123 | 93.66 124 | 52.66 268 | 87.03 113 | 89.01 194 |
|
LCM-MVSNet-Re | | | 77.05 191 | 76.94 167 | 77.36 253 | 87.20 175 | 51.60 310 | 80.06 267 | 80.46 278 | 75.20 84 | 67.69 271 | 86.72 178 | 62.48 127 | 88.98 254 | 63.44 194 | 89.25 84 | 91.51 103 |
|
COLMAP_ROB | | 66.92 17 | 73.01 247 | 70.41 254 | 80.81 194 | 87.13 176 | 65.63 143 | 88.30 102 | 84.19 234 | 62.96 257 | 63.80 299 | 87.69 151 | 38.04 314 | 92.56 165 | 46.66 298 | 74.91 258 | 84.24 291 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
PEN-MVS | | | 77.73 174 | 77.69 157 | 77.84 245 | 87.07 177 | 53.91 296 | 87.91 115 | 91.18 94 | 77.56 37 | 73.14 199 | 88.82 122 | 61.23 146 | 89.17 249 | 59.95 223 | 72.37 277 | 90.43 142 |
|
pcd1.5k->3k | | | 34.07 322 | 35.26 322 | 30.50 337 | 86.92 178 | 0.00 358 | 0.00 349 | 91.58 82 | 0.00 353 | 0.00 354 | 0.00 355 | 56.23 186 | 0.00 356 | 0.00 353 | 82.60 164 | 91.49 105 |
|
MVS_Test | | | 83.15 66 | 83.06 61 | 83.41 115 | 86.86 179 | 63.21 204 | 86.11 175 | 92.00 63 | 74.31 94 | 82.87 60 | 89.44 113 | 70.03 46 | 93.21 139 | 77.39 79 | 88.50 97 | 93.81 35 |
|
FMVSNet3 | | | 77.88 172 | 76.85 168 | 80.97 192 | 86.84 180 | 62.36 215 | 86.52 164 | 88.77 176 | 71.13 156 | 75.34 175 | 86.66 185 | 54.07 204 | 91.10 214 | 62.72 198 | 79.57 200 | 89.45 181 |
|
FMVSNet1 | | | 77.44 187 | 76.12 183 | 81.40 184 | 86.81 181 | 63.01 208 | 88.39 98 | 89.28 151 | 70.49 167 | 74.39 191 | 87.28 161 | 49.06 264 | 91.11 211 | 60.91 217 | 78.52 208 | 90.09 154 |
|
nrg030 | | | 83.88 55 | 83.53 55 | 84.96 70 | 86.77 182 | 69.28 80 | 90.46 44 | 92.67 40 | 74.79 89 | 82.95 58 | 91.33 74 | 72.70 28 | 93.09 148 | 80.79 54 | 79.28 205 | 92.50 77 |
|
jason | | | 81.39 92 | 80.29 96 | 84.70 77 | 86.63 183 | 69.90 68 | 85.95 178 | 86.77 208 | 63.24 253 | 81.07 81 | 89.47 108 | 61.08 150 | 92.15 176 | 78.33 70 | 90.07 77 | 92.05 92 |
jason: jason. |
PS-MVSNAJss | | | 82.07 79 | 81.31 81 | 84.34 87 | 86.51 184 | 67.27 120 | 89.27 68 | 91.51 85 | 71.75 148 | 79.37 91 | 90.22 94 | 63.15 103 | 94.27 87 | 77.69 75 | 82.36 167 | 91.49 105 |
|
WTY-MVS | | | 75.65 216 | 75.68 192 | 75.57 273 | 86.40 185 | 56.82 267 | 77.92 287 | 82.40 255 | 65.10 238 | 76.18 157 | 87.72 149 | 63.13 106 | 80.90 302 | 60.31 221 | 81.96 169 | 89.00 196 |
|
DTE-MVSNet | | | 76.99 192 | 76.80 169 | 77.54 251 | 86.24 186 | 53.06 306 | 87.52 126 | 90.66 105 | 77.08 46 | 72.50 205 | 88.67 125 | 60.48 159 | 89.52 237 | 57.33 248 | 70.74 288 | 90.05 159 |
|
PVSNet | | 64.34 18 | 72.08 254 | 70.87 252 | 75.69 271 | 86.21 187 | 56.44 274 | 74.37 305 | 80.73 275 | 62.06 268 | 70.17 240 | 82.23 263 | 42.86 294 | 83.31 295 | 54.77 259 | 84.45 137 | 87.32 243 |
|
tfpnnormal | | | 74.39 224 | 73.16 224 | 78.08 242 | 86.10 188 | 58.05 247 | 84.65 213 | 87.53 200 | 70.32 169 | 71.22 229 | 85.63 221 | 54.97 193 | 89.86 231 | 43.03 317 | 75.02 257 | 86.32 266 |
|
IterMVS-LS | | | 80.06 126 | 79.38 116 | 82.11 162 | 85.89 189 | 63.20 205 | 86.79 155 | 89.34 149 | 74.19 95 | 75.45 171 | 86.72 178 | 66.62 71 | 92.39 169 | 72.58 128 | 76.86 229 | 90.75 122 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
Baseline_NR-MVSNet | | | 78.15 163 | 78.33 144 | 77.61 249 | 85.79 190 | 56.21 279 | 86.78 156 | 85.76 221 | 73.60 111 | 77.93 123 | 87.57 154 | 65.02 85 | 88.99 253 | 67.14 170 | 75.33 253 | 87.63 235 |
|
cascas | | | 76.72 196 | 74.64 209 | 82.99 132 | 85.78 191 | 65.88 140 | 82.33 249 | 89.21 156 | 60.85 275 | 72.74 202 | 81.02 282 | 47.28 270 | 93.75 118 | 67.48 165 | 85.02 129 | 89.34 182 |
|
MVS | | | 78.19 162 | 76.99 166 | 81.78 168 | 85.66 192 | 66.99 123 | 84.66 210 | 90.47 111 | 55.08 311 | 72.02 221 | 85.27 229 | 63.83 94 | 94.11 97 | 66.10 177 | 89.80 79 | 84.24 291 |
|
XVG-OURS | | | 80.41 113 | 79.23 124 | 83.97 101 | 85.64 193 | 69.02 82 | 83.03 246 | 90.39 112 | 71.09 158 | 77.63 128 | 91.49 71 | 54.62 200 | 91.35 205 | 75.71 96 | 83.47 149 | 91.54 102 |
|
CANet_DTU | | | 80.61 108 | 79.87 101 | 82.83 145 | 85.60 194 | 63.17 207 | 87.36 130 | 88.65 180 | 76.37 63 | 75.88 161 | 88.44 133 | 53.51 208 | 93.07 149 | 73.30 120 | 89.74 80 | 92.25 85 |
|
XVG-OURS-SEG-HR | | | 80.81 101 | 79.76 104 | 83.96 102 | 85.60 194 | 68.78 88 | 83.54 237 | 90.50 110 | 70.66 165 | 76.71 143 | 91.66 63 | 60.69 155 | 91.26 207 | 76.94 84 | 81.58 174 | 91.83 96 |
|
TransMVSNet (Re) | | | 75.39 220 | 74.56 211 | 77.86 244 | 85.50 196 | 57.10 263 | 86.78 156 | 86.09 219 | 72.17 145 | 71.53 226 | 87.34 160 | 63.01 107 | 89.31 242 | 56.84 251 | 61.83 318 | 87.17 247 |
|
MVP-Stereo | | | 76.12 210 | 74.46 214 | 81.13 190 | 85.37 197 | 69.79 69 | 84.42 221 | 87.95 193 | 65.03 239 | 67.46 273 | 85.33 228 | 53.28 210 | 91.73 189 | 58.01 242 | 83.27 155 | 81.85 310 |
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
OpenMVS | | 72.83 10 | 79.77 132 | 78.33 144 | 84.09 93 | 85.17 198 | 69.91 67 | 90.57 40 | 90.97 98 | 66.70 220 | 72.17 216 | 91.91 59 | 54.70 198 | 93.96 100 | 61.81 210 | 90.95 67 | 88.41 222 |
|
AllTest | | | 70.96 260 | 68.09 270 | 79.58 215 | 85.15 199 | 63.62 192 | 84.58 215 | 79.83 285 | 62.31 265 | 60.32 308 | 86.73 176 | 32.02 325 | 88.96 256 | 50.28 275 | 71.57 284 | 86.15 269 |
|
TestCases | | | | | 79.58 215 | 85.15 199 | 63.62 192 | | 79.83 285 | 62.31 265 | 60.32 308 | 86.73 176 | 32.02 325 | 88.96 256 | 50.28 275 | 71.57 284 | 86.15 269 |
|
Effi-MVS+-dtu | | | 80.03 127 | 78.57 136 | 84.42 83 | 85.13 201 | 68.74 91 | 88.77 84 | 88.10 189 | 74.99 86 | 74.97 186 | 83.49 252 | 57.27 178 | 93.36 135 | 73.53 117 | 80.88 180 | 91.18 111 |
|
mvs-test1 | | | 80.88 96 | 79.40 115 | 85.29 61 | 85.13 201 | 69.75 71 | 89.28 67 | 88.10 189 | 74.99 86 | 76.44 150 | 86.72 178 | 57.27 178 | 94.26 90 | 73.53 117 | 83.18 157 | 91.87 95 |
|
SixPastTwentyTwo | | | 73.37 241 | 71.26 248 | 79.70 211 | 85.08 203 | 57.89 252 | 85.57 190 | 83.56 240 | 71.03 159 | 65.66 287 | 85.88 214 | 42.10 299 | 92.57 164 | 59.11 231 | 63.34 315 | 88.65 207 |
|
EG-PatchMatch MVS | | | 74.04 227 | 71.82 242 | 80.71 196 | 84.92 204 | 67.42 116 | 85.86 181 | 88.08 191 | 66.04 230 | 64.22 296 | 83.85 246 | 35.10 323 | 92.56 165 | 57.44 246 | 80.83 181 | 82.16 309 |
|
IB-MVS | | 68.01 15 | 75.85 214 | 73.36 222 | 83.31 117 | 84.76 205 | 66.03 135 | 83.38 238 | 85.06 226 | 70.21 172 | 69.40 252 | 81.05 281 | 45.76 280 | 94.66 78 | 65.10 185 | 75.49 250 | 89.25 184 |
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 |
mvs_tets | | | 79.13 146 | 77.77 155 | 83.22 121 | 84.70 206 | 66.37 132 | 89.17 70 | 90.19 125 | 69.38 183 | 75.40 173 | 89.46 110 | 44.17 287 | 93.15 144 | 76.78 87 | 80.70 184 | 90.14 150 |
|
jajsoiax | | | 79.29 143 | 77.96 149 | 83.27 119 | 84.68 207 | 66.57 130 | 89.25 69 | 90.16 126 | 69.20 187 | 75.46 170 | 89.49 107 | 45.75 281 | 93.13 146 | 76.84 86 | 80.80 182 | 90.11 152 |
|
MIMVSNet | | | 70.69 262 | 69.30 258 | 74.88 278 | 84.52 208 | 56.35 277 | 75.87 297 | 79.42 288 | 64.59 242 | 67.76 269 | 82.41 260 | 41.10 303 | 81.54 301 | 46.64 300 | 81.34 176 | 86.75 257 |
|
MSDG | | | 73.36 243 | 70.99 250 | 80.49 197 | 84.51 209 | 65.80 141 | 80.71 262 | 86.13 218 | 65.70 233 | 65.46 288 | 83.74 249 | 44.60 284 | 90.91 219 | 51.13 272 | 76.89 228 | 84.74 287 |
|
mvs_anonymous | | | 79.42 141 | 79.11 126 | 80.34 200 | 84.45 210 | 57.97 250 | 82.59 247 | 87.62 198 | 67.40 219 | 76.17 159 | 88.56 130 | 68.47 58 | 89.59 236 | 70.65 144 | 86.05 124 | 93.47 50 |
|
EI-MVSNet | | | 80.52 112 | 79.98 99 | 82.12 161 | 84.28 211 | 63.19 206 | 86.41 167 | 88.95 169 | 74.18 96 | 78.69 98 | 87.54 156 | 66.62 71 | 92.43 167 | 72.57 129 | 80.57 186 | 90.74 123 |
|
CVMVSNet | | | 72.99 248 | 72.58 229 | 74.25 284 | 84.28 211 | 50.85 316 | 86.41 167 | 83.45 243 | 44.56 332 | 73.23 198 | 87.54 156 | 49.38 259 | 85.70 282 | 65.90 179 | 78.44 210 | 86.19 268 |
|
v13 | | | 77.50 185 | 76.07 188 | 81.77 169 | 84.23 213 | 65.07 159 | 87.34 131 | 88.91 174 | 72.92 128 | 68.35 267 | 81.97 270 | 62.53 126 | 91.69 195 | 72.20 135 | 66.22 309 | 88.56 217 |
|
pm-mvs1 | | | 77.25 190 | 76.68 171 | 78.93 229 | 84.22 214 | 58.62 241 | 86.41 167 | 88.36 185 | 71.37 155 | 73.31 196 | 88.01 143 | 61.22 147 | 89.15 250 | 64.24 191 | 73.01 273 | 89.03 193 |
|
v12 | | | 77.51 183 | 76.09 187 | 81.76 171 | 84.22 214 | 64.99 160 | 87.30 134 | 88.93 173 | 72.92 128 | 68.48 266 | 81.97 270 | 62.54 125 | 91.70 194 | 72.24 134 | 66.21 310 | 88.58 215 |
|
v11 | | | 77.45 186 | 76.06 189 | 81.59 180 | 84.22 214 | 64.52 171 | 87.11 144 | 89.02 160 | 72.76 133 | 68.76 260 | 81.90 275 | 62.09 134 | 91.71 193 | 71.98 136 | 66.73 302 | 88.56 217 |
|
EPNet | | | 83.72 58 | 82.92 64 | 86.14 52 | 84.22 214 | 69.48 76 | 91.05 34 | 85.27 224 | 81.30 8 | 76.83 141 | 91.65 64 | 66.09 76 | 95.56 43 | 76.00 91 | 93.85 46 | 93.38 51 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
V9 | | | 77.52 181 | 76.11 186 | 81.73 172 | 84.19 218 | 64.89 163 | 87.26 136 | 88.94 172 | 72.87 131 | 68.65 262 | 81.96 272 | 62.65 121 | 91.72 191 | 72.27 133 | 66.24 308 | 88.60 212 |
|
v17 | | | 77.68 176 | 76.35 180 | 81.69 174 | 84.15 219 | 64.65 168 | 87.33 132 | 88.99 164 | 72.70 135 | 69.25 257 | 82.07 266 | 62.82 113 | 91.79 185 | 72.69 127 | 67.15 301 | 88.63 208 |
|
v16 | | | 77.69 175 | 76.36 179 | 81.68 175 | 84.15 219 | 64.63 170 | 87.33 132 | 88.99 164 | 72.69 136 | 69.31 256 | 82.08 265 | 62.80 114 | 91.79 185 | 72.70 126 | 67.23 299 | 88.63 208 |
|
V14 | | | 77.52 181 | 76.12 183 | 81.70 173 | 84.15 219 | 64.77 166 | 87.21 138 | 88.95 169 | 72.80 132 | 68.79 259 | 81.94 273 | 62.69 118 | 91.72 191 | 72.31 132 | 66.27 307 | 88.60 212 |
|
v1neww | | | 80.40 114 | 79.54 109 | 82.98 133 | 84.10 222 | 64.51 173 | 87.57 121 | 90.22 122 | 73.25 119 | 78.47 104 | 86.65 186 | 62.83 111 | 93.86 108 | 75.72 94 | 77.02 224 | 90.58 134 |
|
v7new | | | 80.40 114 | 79.54 109 | 82.98 133 | 84.10 222 | 64.51 173 | 87.57 121 | 90.22 122 | 73.25 119 | 78.47 104 | 86.65 186 | 62.83 111 | 93.86 108 | 75.72 94 | 77.02 224 | 90.58 134 |
|
v18 | | | 77.67 178 | 76.35 180 | 81.64 177 | 84.09 224 | 64.47 179 | 87.27 135 | 89.01 162 | 72.59 137 | 69.39 253 | 82.04 267 | 62.85 109 | 91.80 184 | 72.72 125 | 67.20 300 | 88.63 208 |
|
v15 | | | 77.51 183 | 76.12 183 | 81.66 176 | 84.09 224 | 64.65 168 | 87.14 139 | 88.96 168 | 72.76 133 | 68.90 258 | 81.91 274 | 62.74 116 | 91.73 189 | 72.32 131 | 66.29 306 | 88.61 211 |
|
v8 | | | 79.97 129 | 79.02 128 | 82.80 147 | 84.09 224 | 64.50 177 | 87.96 111 | 90.29 121 | 74.13 98 | 75.24 180 | 86.81 175 | 62.88 108 | 93.89 107 | 74.39 108 | 75.40 252 | 90.00 160 |
|
v6 | | | 80.40 114 | 79.54 109 | 82.98 133 | 84.09 224 | 64.50 177 | 87.57 121 | 90.22 122 | 73.25 119 | 78.47 104 | 86.63 188 | 62.84 110 | 93.86 108 | 75.73 93 | 77.02 224 | 90.58 134 |
|
v7 | | | 80.24 120 | 79.26 123 | 83.15 123 | 84.07 228 | 64.94 162 | 87.56 124 | 90.67 103 | 72.26 143 | 78.28 111 | 86.51 195 | 61.45 141 | 94.03 99 | 75.14 104 | 77.41 218 | 90.49 139 |
|
v10 | | | 79.74 133 | 78.67 131 | 82.97 137 | 84.06 229 | 64.95 161 | 87.88 116 | 90.62 106 | 73.11 125 | 75.11 183 | 86.56 192 | 61.46 140 | 94.05 98 | 73.68 113 | 75.55 249 | 89.90 168 |
|
Patchmatch-test1 | | | 73.49 234 | 71.85 241 | 78.41 239 | 84.05 230 | 62.17 219 | 79.96 269 | 79.29 289 | 66.30 227 | 72.38 214 | 79.58 294 | 51.95 224 | 85.08 287 | 55.46 256 | 77.67 216 | 87.99 227 |
|
test_djsdf | | | 80.30 119 | 79.32 118 | 83.27 119 | 83.98 231 | 65.37 151 | 90.50 42 | 90.38 113 | 68.55 200 | 76.19 156 | 88.70 123 | 56.44 185 | 93.46 130 | 78.98 63 | 80.14 193 | 90.97 116 |
|
1314 | | | 76.53 198 | 75.30 201 | 80.21 204 | 83.93 232 | 62.32 217 | 84.66 210 | 88.81 175 | 60.23 279 | 70.16 241 | 84.07 245 | 55.30 192 | 90.73 222 | 67.37 166 | 83.21 156 | 87.59 237 |
|
MS-PatchMatch | | | 73.83 229 | 72.67 228 | 77.30 255 | 83.87 233 | 66.02 136 | 81.82 252 | 84.66 229 | 61.37 273 | 68.61 264 | 82.82 257 | 47.29 269 | 88.21 264 | 59.27 229 | 84.32 138 | 77.68 323 |
|
v1141 | | | 80.19 123 | 79.31 119 | 82.85 142 | 83.84 234 | 64.12 186 | 87.14 139 | 90.08 129 | 73.13 122 | 78.27 112 | 86.39 197 | 62.67 120 | 93.75 118 | 75.40 101 | 76.83 232 | 90.68 125 |
|
divwei89l23v2f112 | | | 80.19 123 | 79.31 119 | 82.85 142 | 83.84 234 | 64.11 188 | 87.13 142 | 90.08 129 | 73.13 122 | 78.27 112 | 86.39 197 | 62.69 118 | 93.75 118 | 75.40 101 | 76.82 233 | 90.68 125 |
|
v1 | | | 80.19 123 | 79.31 119 | 82.85 142 | 83.83 236 | 64.12 186 | 87.14 139 | 90.07 131 | 73.13 122 | 78.27 112 | 86.38 201 | 62.72 117 | 93.75 118 | 75.41 100 | 76.82 233 | 90.68 125 |
|
v1144 | | | 80.03 127 | 79.03 127 | 83.01 131 | 83.78 237 | 64.51 173 | 87.11 144 | 90.57 108 | 71.96 147 | 78.08 121 | 86.20 205 | 61.41 142 | 93.94 102 | 74.93 105 | 77.23 220 | 90.60 131 |
|
OurMVSNet-221017-0 | | | 74.26 226 | 72.42 232 | 79.80 210 | 83.76 238 | 59.59 234 | 85.92 180 | 86.64 209 | 66.39 226 | 66.96 278 | 87.58 153 | 39.46 308 | 91.60 201 | 65.76 181 | 69.27 292 | 88.22 223 |
|
v2v482 | | | 80.23 121 | 79.29 122 | 83.05 129 | 83.62 239 | 64.14 184 | 87.04 146 | 89.97 133 | 73.61 110 | 78.18 118 | 87.22 165 | 61.10 149 | 93.82 111 | 76.11 89 | 76.78 235 | 91.18 111 |
|
XXY-MVS | | | 75.41 219 | 75.56 193 | 74.96 277 | 83.59 240 | 57.82 254 | 80.59 264 | 83.87 236 | 66.54 225 | 74.93 187 | 88.31 136 | 63.24 100 | 80.09 306 | 62.16 205 | 76.85 230 | 86.97 252 |
|
v1192 | | | 79.59 135 | 78.43 141 | 83.07 128 | 83.55 241 | 64.52 171 | 86.93 150 | 90.58 107 | 70.83 160 | 77.78 125 | 85.90 213 | 59.15 166 | 93.94 102 | 73.96 112 | 77.19 222 | 90.76 121 |
|
tpmp4_e23 | | | 73.45 235 | 71.17 249 | 80.31 202 | 83.55 241 | 59.56 236 | 81.88 251 | 82.33 256 | 57.94 296 | 70.51 235 | 81.62 276 | 51.19 238 | 91.63 200 | 53.96 262 | 77.51 217 | 89.75 177 |
|
v7n | | | 78.97 150 | 77.58 158 | 83.14 124 | 83.45 243 | 65.51 146 | 88.32 101 | 91.21 93 | 73.69 109 | 72.41 213 | 86.32 202 | 57.93 173 | 93.81 112 | 69.18 155 | 75.65 247 | 90.11 152 |
|
v144192 | | | 79.47 139 | 78.37 142 | 82.78 150 | 83.35 244 | 63.96 190 | 86.96 148 | 90.36 116 | 69.99 173 | 77.50 129 | 85.67 219 | 60.66 156 | 93.77 116 | 74.27 109 | 76.58 236 | 90.62 129 |
|
tpm2 | | | 73.26 244 | 71.46 244 | 78.63 233 | 83.34 245 | 56.71 270 | 80.65 263 | 80.40 279 | 56.63 305 | 73.55 194 | 82.02 268 | 51.80 232 | 91.24 208 | 56.35 253 | 78.42 211 | 87.95 228 |
|
diffmvs | | | 79.51 136 | 78.59 134 | 82.25 160 | 83.31 246 | 62.66 213 | 84.17 226 | 88.11 187 | 67.64 212 | 76.09 160 | 87.47 158 | 64.01 92 | 91.15 210 | 71.71 139 | 84.82 133 | 92.94 69 |
|
v1921920 | | | 79.22 144 | 78.03 148 | 82.80 147 | 83.30 247 | 63.94 191 | 86.80 154 | 90.33 118 | 69.91 174 | 77.48 130 | 85.53 224 | 58.44 170 | 93.75 118 | 73.60 116 | 76.85 230 | 90.71 124 |
|
v1240 | | | 78.99 149 | 77.78 154 | 82.64 154 | 83.21 248 | 63.54 194 | 86.62 161 | 90.30 120 | 69.74 179 | 77.33 132 | 85.68 218 | 57.04 183 | 93.76 117 | 73.13 122 | 76.92 227 | 90.62 129 |
|
XVG-ACMP-BASELINE | | | 76.11 211 | 74.27 216 | 81.62 178 | 83.20 249 | 64.67 167 | 83.60 236 | 89.75 139 | 69.75 177 | 71.85 222 | 87.09 171 | 32.78 324 | 92.11 177 | 69.99 149 | 80.43 189 | 88.09 226 |
|
MDTV_nov1_ep13 | | | | 69.97 257 | | 83.18 250 | 53.48 299 | 77.10 291 | 80.18 284 | 60.45 276 | 69.33 255 | 80.44 286 | 48.89 265 | 86.90 273 | 51.60 270 | 78.51 209 | |
|
PatchmatchNet | | | 73.12 246 | 71.33 246 | 78.49 238 | 83.18 250 | 60.85 227 | 79.63 271 | 78.57 297 | 64.13 247 | 71.73 223 | 79.81 293 | 51.20 237 | 85.97 281 | 57.40 247 | 76.36 240 | 88.66 206 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
Fast-Effi-MVS+-dtu | | | 78.02 166 | 76.49 173 | 82.62 155 | 83.16 252 | 66.96 126 | 86.94 149 | 87.45 203 | 72.45 138 | 71.49 227 | 84.17 243 | 54.79 197 | 91.58 202 | 67.61 163 | 80.31 190 | 89.30 183 |
|
gg-mvs-nofinetune | | | 69.95 269 | 67.96 271 | 75.94 269 | 83.07 253 | 54.51 293 | 77.23 290 | 70.29 330 | 63.11 254 | 70.32 237 | 62.33 333 | 43.62 289 | 88.69 260 | 53.88 263 | 87.76 102 | 84.62 289 |
|
MVSTER | | | 79.01 148 | 77.88 151 | 82.38 158 | 83.07 253 | 64.80 165 | 84.08 230 | 88.95 169 | 69.01 194 | 78.69 98 | 87.17 168 | 54.70 198 | 92.43 167 | 74.69 106 | 80.57 186 | 89.89 169 |
|
K. test v3 | | | 71.19 258 | 68.51 264 | 79.21 222 | 83.04 255 | 57.78 255 | 84.35 223 | 76.91 306 | 72.90 130 | 62.99 302 | 82.86 256 | 39.27 309 | 91.09 216 | 61.65 211 | 52.66 333 | 88.75 204 |
|
FMVSNet5 | | | 69.50 271 | 67.96 271 | 74.15 285 | 82.97 256 | 55.35 288 | 80.01 268 | 82.12 260 | 62.56 263 | 63.02 300 | 81.53 277 | 36.92 318 | 81.92 299 | 48.42 283 | 74.06 265 | 85.17 283 |
|
PatchFormer-LS_test | | | 74.50 223 | 73.05 225 | 78.86 230 | 82.95 257 | 59.55 237 | 81.65 256 | 82.30 257 | 67.44 218 | 71.62 225 | 78.15 301 | 52.34 215 | 88.92 258 | 65.05 186 | 75.90 244 | 88.12 225 |
|
DWT-MVSNet_test | | | 73.70 230 | 71.86 240 | 79.21 222 | 82.91 258 | 58.94 239 | 82.34 248 | 82.17 258 | 65.21 236 | 71.05 231 | 78.31 299 | 44.21 286 | 90.17 229 | 63.29 196 | 77.28 219 | 88.53 219 |
|
DI_MVS_plusplus_test | | | 79.89 130 | 78.58 135 | 83.85 105 | 82.89 259 | 65.32 152 | 86.12 174 | 89.55 143 | 69.64 180 | 70.55 233 | 85.82 217 | 57.24 180 | 93.81 112 | 76.85 85 | 88.55 94 | 92.41 80 |
|
sss | | | 73.60 233 | 73.64 220 | 73.51 288 | 82.80 260 | 55.01 289 | 76.12 293 | 81.69 267 | 62.47 264 | 74.68 189 | 85.85 216 | 57.32 177 | 78.11 314 | 60.86 218 | 80.93 179 | 87.39 240 |
|
GA-MVS | | | 76.87 194 | 75.17 206 | 81.97 165 | 82.75 261 | 62.58 214 | 81.44 259 | 86.35 215 | 72.16 146 | 74.74 188 | 82.89 255 | 46.20 276 | 92.02 178 | 68.85 157 | 81.09 178 | 91.30 109 |
|
v148 | | | 78.72 152 | 77.80 153 | 81.47 182 | 82.73 262 | 61.96 221 | 86.30 171 | 88.08 191 | 73.26 118 | 76.18 157 | 85.47 226 | 62.46 128 | 92.36 171 | 71.92 138 | 73.82 269 | 90.09 154 |
|
test_normal | | | 79.81 131 | 78.45 138 | 83.89 104 | 82.70 263 | 65.40 148 | 85.82 184 | 89.48 146 | 69.39 181 | 70.12 242 | 85.66 220 | 57.15 182 | 93.71 123 | 77.08 82 | 88.62 92 | 92.56 76 |
|
semantic-postprocess | | | | | 80.11 205 | 82.69 264 | 64.85 164 | | 83.47 242 | 69.16 188 | 70.49 236 | 84.15 244 | 50.83 244 | 88.15 265 | 69.23 154 | 72.14 280 | 87.34 242 |
|
CostFormer | | | 75.24 221 | 73.90 219 | 79.27 220 | 82.65 265 | 58.27 245 | 80.80 260 | 82.73 253 | 61.57 270 | 75.33 178 | 83.13 254 | 55.52 190 | 91.07 217 | 64.98 187 | 78.34 212 | 88.45 220 |
|
EPNet_dtu | | | 75.46 218 | 74.86 207 | 77.23 256 | 82.57 266 | 54.60 291 | 86.89 151 | 83.09 249 | 71.64 149 | 66.25 285 | 85.86 215 | 55.99 187 | 88.04 267 | 54.92 258 | 86.55 118 | 89.05 191 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
RPSCF | | | 73.23 245 | 71.46 244 | 78.54 236 | 82.50 267 | 59.85 233 | 82.18 250 | 82.84 252 | 58.96 288 | 71.15 230 | 89.41 114 | 45.48 283 | 84.77 289 | 58.82 234 | 71.83 282 | 91.02 115 |
|
tpm cat1 | | | 70.57 263 | 68.31 266 | 77.35 254 | 82.41 268 | 57.95 251 | 78.08 286 | 80.22 283 | 52.04 323 | 68.54 265 | 77.66 306 | 52.00 223 | 87.84 269 | 51.77 269 | 72.07 281 | 86.25 267 |
|
v748 | | | 77.97 168 | 76.65 172 | 81.92 167 | 82.29 269 | 63.28 202 | 87.53 125 | 90.35 117 | 73.50 115 | 70.76 232 | 85.55 223 | 58.28 171 | 92.81 160 | 68.81 158 | 72.76 276 | 89.67 178 |
|
tpm | | | 72.37 253 | 71.71 243 | 74.35 283 | 82.19 270 | 52.00 307 | 79.22 276 | 77.29 304 | 64.56 243 | 72.95 201 | 83.68 251 | 51.35 235 | 83.26 296 | 58.33 239 | 75.80 245 | 87.81 232 |
|
tpmvs | | | 71.09 259 | 69.29 259 | 76.49 261 | 82.04 271 | 56.04 280 | 78.92 279 | 81.37 271 | 64.05 248 | 67.18 277 | 78.28 300 | 49.74 258 | 89.77 232 | 49.67 280 | 72.37 277 | 83.67 295 |
|
pmmvs4 | | | 74.03 228 | 71.91 239 | 80.39 198 | 81.96 272 | 68.32 101 | 81.45 258 | 82.14 259 | 59.32 286 | 69.87 248 | 85.13 231 | 52.40 214 | 88.13 266 | 60.21 222 | 74.74 260 | 84.73 288 |
|
TinyColmap | | | 67.30 282 | 64.81 284 | 74.76 280 | 81.92 273 | 56.68 271 | 80.29 266 | 81.49 270 | 60.33 277 | 56.27 323 | 83.22 253 | 24.77 334 | 87.66 271 | 45.52 305 | 69.47 291 | 79.95 317 |
|
ITE_SJBPF | | | | | 78.22 241 | 81.77 274 | 60.57 229 | | 83.30 244 | 69.25 186 | 67.54 272 | 87.20 166 | 36.33 320 | 87.28 272 | 54.34 260 | 74.62 261 | 86.80 255 |
|
MVS-HIRNet | | | 59.14 301 | 57.67 303 | 63.57 317 | 81.65 275 | 43.50 331 | 71.73 309 | 65.06 342 | 39.59 337 | 51.43 331 | 57.73 337 | 38.34 313 | 82.58 298 | 39.53 323 | 73.95 266 | 64.62 338 |
|
GG-mvs-BLEND | | | | | 75.38 275 | 81.59 276 | 55.80 286 | 79.32 274 | 69.63 332 | | 67.19 276 | 73.67 320 | 43.24 290 | 88.90 259 | 50.41 274 | 84.50 135 | 81.45 312 |
|
IterMVS | | | 74.29 225 | 72.94 226 | 78.35 240 | 81.53 277 | 63.49 196 | 81.58 257 | 82.49 254 | 68.06 210 | 69.99 245 | 83.69 250 | 51.66 234 | 85.54 283 | 65.85 180 | 71.64 283 | 86.01 274 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
CHOSEN 280x420 | | | 66.51 286 | 64.71 285 | 71.90 293 | 81.45 278 | 63.52 195 | 57.98 339 | 68.95 337 | 53.57 318 | 62.59 303 | 76.70 309 | 46.22 275 | 75.29 326 | 55.25 257 | 79.68 194 | 76.88 329 |
|
gm-plane-assit | | | | | | 81.40 279 | 53.83 297 | | | 62.72 262 | | 80.94 284 | | 92.39 169 | 63.40 195 | | |
|
pmmvs6 | | | 74.69 222 | 73.39 221 | 78.61 234 | 81.38 280 | 57.48 259 | 86.64 160 | 87.95 193 | 64.99 240 | 70.18 239 | 86.61 189 | 50.43 252 | 89.52 237 | 62.12 206 | 70.18 290 | 88.83 201 |
|
test-LLR | | | 72.94 249 | 72.43 231 | 74.48 281 | 81.35 281 | 58.04 248 | 78.38 282 | 77.46 302 | 66.66 221 | 69.95 246 | 79.00 297 | 48.06 267 | 79.24 308 | 66.13 175 | 84.83 131 | 86.15 269 |
|
test-mter | | | 71.41 257 | 70.39 255 | 74.48 281 | 81.35 281 | 58.04 248 | 78.38 282 | 77.46 302 | 60.32 278 | 69.95 246 | 79.00 297 | 36.08 321 | 79.24 308 | 66.13 175 | 84.83 131 | 86.15 269 |
|
CR-MVSNet | | | 73.37 241 | 71.27 247 | 79.67 213 | 81.32 283 | 65.19 156 | 75.92 295 | 80.30 280 | 59.92 282 | 72.73 203 | 81.19 278 | 52.50 212 | 86.69 274 | 59.84 224 | 77.71 214 | 87.11 250 |
|
RPMNet | | | 71.62 255 | 68.94 262 | 79.67 213 | 81.32 283 | 65.19 156 | 75.92 295 | 78.30 299 | 57.60 299 | 72.73 203 | 76.45 311 | 52.30 216 | 86.69 274 | 48.14 289 | 77.71 214 | 87.11 250 |
|
V42 | | | 79.38 142 | 78.24 146 | 82.83 145 | 81.10 285 | 65.50 147 | 85.55 194 | 89.82 137 | 71.57 153 | 78.21 116 | 86.12 206 | 60.66 156 | 93.18 143 | 75.64 97 | 75.46 251 | 89.81 173 |
|
lessismore_v0 | | | | | 78.97 228 | 81.01 286 | 57.15 262 | | 65.99 340 | | 61.16 305 | 82.82 257 | 39.12 310 | 91.34 206 | 59.67 225 | 46.92 337 | 88.43 221 |
|
Patchmtry | | | 70.74 261 | 69.16 260 | 75.49 274 | 80.72 287 | 54.07 295 | 74.94 304 | 80.30 280 | 58.34 292 | 70.01 243 | 81.19 278 | 52.50 212 | 86.54 276 | 53.37 265 | 71.09 286 | 85.87 276 |
|
PatchT | | | 68.46 277 | 67.85 273 | 70.29 302 | 80.70 288 | 43.93 330 | 72.47 308 | 74.88 314 | 60.15 280 | 70.55 233 | 76.57 310 | 49.94 257 | 81.59 300 | 50.58 273 | 74.83 259 | 85.34 279 |
|
USDC | | | 70.33 266 | 68.37 265 | 76.21 268 | 80.60 289 | 56.23 278 | 79.19 277 | 86.49 211 | 60.89 274 | 61.29 304 | 85.47 226 | 31.78 327 | 89.47 239 | 53.37 265 | 76.21 241 | 82.94 306 |
|
tpmrst | | | 72.39 251 | 72.13 238 | 73.18 290 | 80.54 290 | 49.91 320 | 79.91 270 | 79.08 290 | 63.11 254 | 71.69 224 | 79.95 290 | 55.32 191 | 82.77 297 | 65.66 182 | 73.89 267 | 86.87 253 |
|
anonymousdsp | | | 78.60 154 | 77.15 164 | 82.98 133 | 80.51 291 | 67.08 122 | 87.24 137 | 89.53 144 | 65.66 234 | 75.16 181 | 87.19 167 | 52.52 211 | 92.25 174 | 77.17 81 | 79.34 204 | 89.61 179 |
|
OpenMVS_ROB | | 64.09 19 | 70.56 264 | 68.19 267 | 77.65 248 | 80.26 292 | 59.41 238 | 85.01 205 | 82.96 251 | 58.76 290 | 65.43 289 | 82.33 261 | 37.63 317 | 91.23 209 | 45.34 307 | 76.03 242 | 82.32 307 |
|
Test4 | | | 77.83 173 | 75.90 190 | 83.62 107 | 80.24 293 | 65.25 154 | 85.27 200 | 90.67 103 | 69.03 193 | 66.48 283 | 83.75 248 | 43.07 292 | 93.00 153 | 75.93 92 | 88.66 91 | 92.62 75 |
|
Anonymous20231206 | | | 68.60 274 | 67.80 275 | 71.02 300 | 80.23 294 | 50.75 317 | 78.30 285 | 80.47 277 | 56.79 304 | 66.11 286 | 82.63 259 | 46.35 274 | 78.95 310 | 43.62 316 | 75.70 246 | 83.36 298 |
|
MIMVSNet1 | | | 68.58 275 | 66.78 280 | 73.98 286 | 80.07 295 | 51.82 308 | 80.77 261 | 84.37 231 | 64.40 245 | 59.75 311 | 82.16 264 | 36.47 319 | 83.63 293 | 42.73 318 | 70.33 289 | 86.48 261 |
|
ADS-MVSNet2 | | | 66.20 289 | 63.33 289 | 74.82 279 | 79.92 296 | 58.75 240 | 67.55 327 | 75.19 312 | 53.37 319 | 65.25 290 | 75.86 312 | 42.32 297 | 80.53 304 | 41.57 320 | 68.91 294 | 85.18 281 |
|
ADS-MVSNet | | | 64.36 294 | 62.88 293 | 68.78 309 | 79.92 296 | 47.17 325 | 67.55 327 | 71.18 328 | 53.37 319 | 65.25 290 | 75.86 312 | 42.32 297 | 73.99 331 | 41.57 320 | 68.91 294 | 85.18 281 |
|
dp | | | 66.80 283 | 65.43 283 | 70.90 301 | 79.74 298 | 48.82 323 | 75.12 302 | 74.77 316 | 59.61 284 | 64.08 297 | 77.23 307 | 42.89 293 | 80.72 303 | 48.86 282 | 66.58 304 | 83.16 300 |
|
EPMVS | | | 69.02 273 | 68.16 268 | 71.59 294 | 79.61 299 | 49.80 322 | 77.40 289 | 66.93 339 | 62.82 260 | 70.01 243 | 79.05 295 | 45.79 279 | 77.86 316 | 56.58 252 | 75.26 255 | 87.13 249 |
|
PVSNet_0 | | 57.27 20 | 61.67 298 | 59.27 299 | 68.85 308 | 79.61 299 | 57.44 260 | 68.01 325 | 73.44 324 | 55.93 308 | 58.54 313 | 70.41 326 | 44.58 285 | 77.55 317 | 47.01 293 | 35.91 339 | 71.55 333 |
|
Patchmatch-test | | | 64.82 292 | 63.24 290 | 69.57 304 | 79.42 301 | 49.82 321 | 63.49 334 | 69.05 336 | 51.98 324 | 59.95 310 | 80.13 289 | 50.91 240 | 70.98 337 | 40.66 322 | 73.57 270 | 87.90 230 |
|
V4 | | | 77.95 169 | 76.37 176 | 82.67 152 | 79.40 302 | 65.52 144 | 86.43 165 | 89.94 134 | 72.28 141 | 72.14 219 | 84.95 235 | 55.72 188 | 93.44 132 | 73.64 114 | 72.86 274 | 89.05 191 |
|
v52 | | | 77.94 171 | 76.37 176 | 82.67 152 | 79.39 303 | 65.52 144 | 86.43 165 | 89.94 134 | 72.28 141 | 72.15 218 | 84.94 236 | 55.70 189 | 93.44 132 | 73.64 114 | 72.84 275 | 89.06 187 |
|
MDA-MVSNet-bldmvs | | | 66.68 284 | 63.66 288 | 75.75 270 | 79.28 304 | 60.56 230 | 73.92 306 | 78.35 298 | 64.43 244 | 50.13 333 | 79.87 292 | 44.02 288 | 83.67 292 | 46.10 302 | 56.86 327 | 83.03 303 |
|
TESTMET0.1,1 | | | 69.89 270 | 69.00 261 | 72.55 291 | 79.27 305 | 56.85 266 | 78.38 282 | 74.71 318 | 57.64 298 | 68.09 268 | 77.19 308 | 37.75 315 | 76.70 319 | 63.92 192 | 84.09 139 | 84.10 294 |
|
N_pmnet | | | 52.79 311 | 53.26 309 | 51.40 330 | 78.99 306 | 7.68 355 | 69.52 317 | 3.89 355 | 51.63 326 | 57.01 320 | 74.98 315 | 40.83 304 | 65.96 344 | 37.78 326 | 64.67 313 | 80.56 316 |
|
EU-MVSNet | | | 68.53 276 | 67.61 278 | 71.31 299 | 78.51 307 | 47.01 326 | 84.47 216 | 84.27 233 | 42.27 333 | 66.44 284 | 84.79 239 | 40.44 306 | 83.76 291 | 58.76 235 | 68.54 298 | 83.17 299 |
|
pmmvs5 | | | 71.55 256 | 70.20 256 | 75.61 272 | 77.83 308 | 56.39 275 | 81.74 254 | 80.89 272 | 57.76 297 | 67.46 273 | 84.49 241 | 49.26 262 | 85.32 286 | 57.08 250 | 75.29 254 | 85.11 284 |
|
test0.0.03 1 | | | 68.00 278 | 67.69 277 | 68.90 307 | 77.55 309 | 47.43 324 | 75.70 298 | 72.95 325 | 66.66 221 | 66.56 281 | 82.29 262 | 48.06 267 | 75.87 323 | 44.97 308 | 74.51 262 | 83.41 297 |
|
Patchmatch-RL test | | | 70.24 267 | 67.78 276 | 77.61 249 | 77.43 310 | 59.57 235 | 71.16 310 | 70.33 329 | 62.94 258 | 68.65 262 | 72.77 321 | 50.62 245 | 85.49 284 | 69.58 152 | 66.58 304 | 87.77 233 |
|
pmmvs-eth3d | | | 70.50 265 | 67.83 274 | 78.52 237 | 77.37 311 | 66.18 134 | 81.82 252 | 81.51 269 | 58.90 289 | 63.90 298 | 80.42 287 | 42.69 295 | 86.28 279 | 58.56 236 | 65.30 312 | 83.11 301 |
|
testing_2 | | | 75.73 215 | 73.34 223 | 82.89 141 | 77.37 311 | 65.22 155 | 84.10 229 | 90.54 109 | 69.09 189 | 60.46 307 | 81.15 280 | 40.48 305 | 92.84 159 | 76.36 88 | 80.54 188 | 90.60 131 |
|
Anonymous20231211 | | | 64.82 292 | 61.79 296 | 73.91 287 | 77.11 313 | 50.92 315 | 85.29 199 | 81.53 268 | 54.19 313 | 57.98 315 | 78.03 302 | 26.90 330 | 87.83 270 | 37.92 325 | 57.12 326 | 82.99 304 |
|
JIA-IIPM | | | 66.32 288 | 62.82 294 | 76.82 258 | 77.09 314 | 61.72 223 | 65.34 331 | 75.38 310 | 58.04 295 | 64.51 294 | 62.32 334 | 42.05 300 | 86.51 277 | 51.45 271 | 69.22 293 | 82.21 308 |
|
Gipuma | | | 45.18 317 | 41.86 318 | 55.16 326 | 77.03 315 | 51.52 311 | 32.50 347 | 80.52 276 | 32.46 341 | 27.12 342 | 35.02 344 | 9.52 351 | 75.50 324 | 22.31 344 | 60.21 324 | 38.45 345 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
MDA-MVSNet_test_wron | | | 65.03 290 | 62.92 291 | 71.37 296 | 75.93 316 | 56.73 268 | 69.09 322 | 74.73 317 | 57.28 302 | 54.03 326 | 77.89 303 | 45.88 277 | 74.39 329 | 49.89 279 | 61.55 319 | 82.99 304 |
|
YYNet1 | | | 65.03 290 | 62.91 292 | 71.38 295 | 75.85 317 | 56.60 272 | 69.12 321 | 74.66 320 | 57.28 302 | 54.12 325 | 77.87 304 | 45.85 278 | 74.48 328 | 49.95 278 | 61.52 320 | 83.05 302 |
|
PMMVS | | | 69.34 272 | 68.67 263 | 71.35 298 | 75.67 318 | 62.03 220 | 75.17 299 | 73.46 323 | 50.00 328 | 68.68 261 | 79.05 295 | 52.07 222 | 78.13 313 | 61.16 216 | 82.77 161 | 73.90 331 |
|
testgi | | | 66.67 285 | 66.53 281 | 67.08 312 | 75.62 319 | 41.69 335 | 75.93 294 | 76.50 307 | 66.11 228 | 65.20 292 | 86.59 190 | 35.72 322 | 74.71 327 | 43.71 315 | 73.38 272 | 84.84 286 |
|
LP | | | 61.36 299 | 57.78 302 | 72.09 292 | 75.54 320 | 58.53 242 | 67.16 329 | 75.22 311 | 51.90 325 | 54.13 324 | 69.97 327 | 37.73 316 | 80.45 305 | 32.74 332 | 55.63 329 | 77.29 325 |
|
test20.03 | | | 67.45 280 | 66.95 279 | 68.94 306 | 75.48 321 | 44.84 328 | 77.50 288 | 77.67 301 | 66.66 221 | 63.01 301 | 83.80 247 | 47.02 271 | 78.40 312 | 42.53 319 | 68.86 296 | 83.58 296 |
|
PM-MVS | | | 66.41 287 | 64.14 287 | 73.20 289 | 73.92 322 | 56.45 273 | 78.97 278 | 64.96 343 | 63.88 252 | 64.72 293 | 80.24 288 | 19.84 340 | 83.44 294 | 66.24 174 | 64.52 314 | 79.71 318 |
|
UnsupCasMVSNet_bld | | | 63.70 296 | 61.53 298 | 70.21 303 | 73.69 323 | 51.39 313 | 72.82 307 | 81.89 265 | 55.63 309 | 57.81 316 | 71.80 323 | 38.67 311 | 78.61 311 | 49.26 281 | 52.21 334 | 80.63 314 |
|
UnsupCasMVSNet_eth | | | 67.33 281 | 65.99 282 | 71.37 296 | 73.48 324 | 51.47 312 | 75.16 300 | 85.19 225 | 65.20 237 | 60.78 306 | 80.93 285 | 42.35 296 | 77.20 318 | 57.12 249 | 53.69 332 | 85.44 278 |
|
TDRefinement | | | 67.49 279 | 64.34 286 | 76.92 257 | 73.47 325 | 61.07 224 | 84.86 208 | 82.98 250 | 59.77 283 | 58.30 314 | 85.13 231 | 26.06 332 | 87.89 268 | 47.92 291 | 60.59 323 | 81.81 311 |
|
ambc | | | | | 75.24 276 | 73.16 326 | 50.51 318 | 63.05 335 | 87.47 202 | | 64.28 295 | 77.81 305 | 17.80 343 | 89.73 234 | 57.88 243 | 60.64 322 | 85.49 277 |
|
CMPMVS | | 51.72 21 | 70.19 268 | 68.16 268 | 76.28 267 | 73.15 327 | 57.55 258 | 79.47 273 | 83.92 235 | 48.02 330 | 56.48 322 | 84.81 238 | 43.13 291 | 86.42 278 | 62.67 201 | 81.81 172 | 84.89 285 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
new-patchmatchnet | | | 61.73 297 | 61.73 297 | 61.70 320 | 72.74 328 | 24.50 351 | 69.16 320 | 78.03 300 | 61.40 271 | 56.72 321 | 75.53 314 | 38.42 312 | 76.48 321 | 45.95 303 | 57.67 325 | 84.13 293 |
|
testus | | | 59.00 302 | 57.91 301 | 62.25 319 | 72.25 329 | 39.09 338 | 69.74 315 | 75.02 313 | 53.04 321 | 57.21 319 | 73.72 319 | 18.76 342 | 70.33 338 | 32.86 331 | 68.57 297 | 77.35 324 |
|
testpf | | | 56.51 307 | 57.58 304 | 53.30 327 | 71.99 330 | 41.19 336 | 46.89 344 | 69.32 335 | 58.06 294 | 52.87 330 | 69.45 329 | 27.99 329 | 72.73 333 | 59.59 227 | 62.07 317 | 45.98 343 |
|
test2356 | | | 59.50 300 | 58.08 300 | 63.74 316 | 71.23 331 | 41.88 333 | 67.59 326 | 72.42 327 | 53.72 317 | 57.65 317 | 70.74 325 | 26.31 331 | 72.40 334 | 32.03 335 | 71.06 287 | 76.93 327 |
|
LF4IMVS | | | 64.02 295 | 62.19 295 | 69.50 305 | 70.90 332 | 53.29 300 | 76.13 292 | 77.18 305 | 52.65 322 | 58.59 312 | 80.98 283 | 23.55 335 | 76.52 320 | 53.06 267 | 66.66 303 | 78.68 320 |
|
test1235678 | | | 58.74 303 | 56.89 306 | 64.30 314 | 69.70 333 | 41.87 334 | 71.05 311 | 74.87 315 | 54.06 314 | 50.63 332 | 71.53 324 | 25.30 333 | 74.10 330 | 31.80 336 | 63.10 316 | 76.93 327 |
|
1111 | | | 57.11 306 | 56.82 307 | 57.97 324 | 69.10 334 | 28.28 346 | 68.90 323 | 74.54 321 | 54.01 315 | 53.71 327 | 74.51 316 | 23.09 336 | 67.90 342 | 32.28 333 | 61.26 321 | 77.73 322 |
|
.test1245 | | | 45.55 316 | 50.02 313 | 32.14 336 | 69.10 334 | 28.28 346 | 68.90 323 | 74.54 321 | 54.01 315 | 53.71 327 | 74.51 316 | 23.09 336 | 67.90 342 | 32.28 333 | 0.02 351 | 0.25 352 |
|
new_pmnet | | | 50.91 313 | 50.29 312 | 52.78 328 | 68.58 336 | 34.94 344 | 63.71 333 | 56.63 345 | 39.73 336 | 44.95 334 | 65.47 332 | 21.93 338 | 58.48 346 | 34.98 329 | 56.62 328 | 64.92 337 |
|
DSMNet-mixed | | | 57.77 305 | 56.90 305 | 60.38 321 | 67.70 337 | 35.61 341 | 69.18 319 | 53.97 346 | 32.30 343 | 57.49 318 | 79.88 291 | 40.39 307 | 68.57 341 | 38.78 324 | 72.37 277 | 76.97 326 |
|
FPMVS | | | 53.68 310 | 51.64 310 | 59.81 322 | 65.08 338 | 51.03 314 | 69.48 318 | 69.58 333 | 41.46 334 | 40.67 336 | 72.32 322 | 16.46 345 | 70.00 339 | 24.24 343 | 65.42 311 | 58.40 340 |
|
pmmvs3 | | | 57.79 304 | 54.26 308 | 68.37 310 | 64.02 339 | 56.72 269 | 75.12 302 | 65.17 341 | 40.20 335 | 52.93 329 | 69.86 328 | 20.36 339 | 75.48 325 | 45.45 306 | 55.25 331 | 72.90 332 |
|
test12356 | | | 49.28 315 | 48.51 315 | 51.59 329 | 62.06 340 | 19.11 352 | 60.40 336 | 72.45 326 | 47.60 331 | 40.64 337 | 65.68 331 | 13.84 347 | 68.72 340 | 27.29 340 | 46.67 338 | 66.94 336 |
|
testmv | | | 53.85 309 | 51.03 311 | 62.31 318 | 61.46 341 | 38.88 339 | 70.95 314 | 74.69 319 | 51.11 327 | 41.26 335 | 66.85 330 | 14.28 346 | 72.13 335 | 29.19 338 | 49.51 336 | 75.93 330 |
|
PNet_i23d | | | 38.26 321 | 35.42 321 | 46.79 331 | 58.74 342 | 35.48 342 | 59.65 337 | 51.25 347 | 32.45 342 | 23.44 346 | 47.53 342 | 2.04 356 | 58.96 345 | 25.60 342 | 18.09 346 | 45.92 344 |
|
wuyk23d | | | 16.82 328 | 15.94 329 | 19.46 339 | 58.74 342 | 31.45 345 | 39.22 345 | 3.74 356 | 6.84 349 | 6.04 351 | 2.70 352 | 1.27 357 | 24.29 352 | 10.54 350 | 14.40 350 | 2.63 350 |
|
no-one | | | 51.08 312 | 45.79 317 | 66.95 313 | 57.92 344 | 50.49 319 | 59.63 338 | 76.04 309 | 48.04 329 | 31.85 339 | 56.10 340 | 19.12 341 | 80.08 307 | 36.89 327 | 26.52 341 | 70.29 334 |
|
PMMVS2 | | | 40.82 319 | 38.86 320 | 46.69 332 | 53.84 345 | 16.45 353 | 48.61 343 | 49.92 348 | 37.49 338 | 31.67 340 | 60.97 336 | 8.14 353 | 56.42 347 | 28.42 339 | 30.72 340 | 67.19 335 |
|
LCM-MVSNet | | | 54.25 308 | 49.68 314 | 67.97 311 | 53.73 346 | 45.28 327 | 66.85 330 | 80.78 274 | 35.96 339 | 39.45 338 | 62.23 335 | 8.70 352 | 78.06 315 | 48.24 288 | 51.20 335 | 80.57 315 |
|
E-PMN | | | 31.77 323 | 30.64 324 | 35.15 334 | 52.87 347 | 27.67 348 | 57.09 341 | 47.86 349 | 24.64 344 | 16.40 348 | 33.05 346 | 11.23 349 | 54.90 348 | 14.46 348 | 18.15 345 | 22.87 347 |
|
EMVS | | | 30.81 324 | 29.65 325 | 34.27 335 | 50.96 348 | 25.95 350 | 56.58 342 | 46.80 350 | 24.01 346 | 15.53 349 | 30.68 347 | 12.47 348 | 54.43 349 | 12.81 349 | 17.05 347 | 22.43 348 |
|
ANet_high | | | 50.57 314 | 46.10 316 | 63.99 315 | 48.67 349 | 39.13 337 | 70.99 313 | 80.85 273 | 61.39 272 | 31.18 341 | 57.70 338 | 17.02 344 | 73.65 332 | 31.22 337 | 15.89 348 | 79.18 319 |
|
wuykxyi23d | | | 39.76 320 | 33.18 323 | 59.51 323 | 46.98 350 | 44.01 329 | 57.70 340 | 67.74 338 | 24.13 345 | 13.98 350 | 34.33 345 | 1.27 357 | 71.33 336 | 34.23 330 | 18.23 344 | 63.18 339 |
|
MVE | | 26.22 23 | 30.37 325 | 25.89 327 | 43.81 333 | 44.55 351 | 35.46 343 | 28.87 348 | 39.07 351 | 18.20 347 | 18.58 347 | 40.18 343 | 2.68 355 | 47.37 350 | 17.07 347 | 23.78 343 | 48.60 342 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
PMVS | | 37.38 22 | 44.16 318 | 40.28 319 | 55.82 325 | 40.82 352 | 42.54 332 | 65.12 332 | 63.99 344 | 34.43 340 | 24.48 343 | 57.12 339 | 3.92 354 | 76.17 322 | 17.10 346 | 55.52 330 | 48.75 341 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
DeepMVS_CX | | | | | 27.40 338 | 40.17 353 | 26.90 349 | | 24.59 354 | 17.44 348 | 23.95 344 | 48.61 341 | 9.77 350 | 26.48 351 | 18.06 345 | 24.47 342 | 28.83 346 |
|
tmp_tt | | | 18.61 327 | 21.40 328 | 10.23 340 | 4.82 354 | 10.11 354 | 34.70 346 | 30.74 353 | 1.48 350 | 23.91 345 | 26.07 348 | 28.42 328 | 13.41 353 | 27.12 341 | 15.35 349 | 7.17 349 |
|
testmvs | | | 6.04 331 | 8.02 332 | 0.10 342 | 0.08 355 | 0.03 357 | 69.74 315 | 0.04 357 | 0.05 351 | 0.31 352 | 1.68 353 | 0.02 360 | 0.04 354 | 0.24 351 | 0.02 351 | 0.25 352 |
|
test123 | | | 6.12 330 | 8.11 331 | 0.14 341 | 0.06 356 | 0.09 356 | 71.05 311 | 0.03 358 | 0.04 352 | 0.25 353 | 1.30 354 | 0.05 359 | 0.03 355 | 0.21 352 | 0.01 353 | 0.29 351 |
|
cdsmvs_eth3d_5k | | | 19.96 326 | 26.61 326 | 0.00 343 | 0.00 357 | 0.00 358 | 0.00 349 | 89.26 154 | 0.00 353 | 0.00 354 | 88.61 127 | 61.62 138 | 0.00 356 | 0.00 353 | 0.00 354 | 0.00 354 |
|
pcd_1.5k_mvsjas | | | 5.26 332 | 7.02 333 | 0.00 343 | 0.00 357 | 0.00 358 | 0.00 349 | 0.00 359 | 0.00 353 | 0.00 354 | 0.00 355 | 63.15 103 | 0.00 356 | 0.00 353 | 0.00 354 | 0.00 354 |
|
sosnet-low-res | | | 0.00 333 | 0.00 334 | 0.00 343 | 0.00 357 | 0.00 358 | 0.00 349 | 0.00 359 | 0.00 353 | 0.00 354 | 0.00 355 | 0.00 361 | 0.00 356 | 0.00 353 | 0.00 354 | 0.00 354 |
|
sosnet | | | 0.00 333 | 0.00 334 | 0.00 343 | 0.00 357 | 0.00 358 | 0.00 349 | 0.00 359 | 0.00 353 | 0.00 354 | 0.00 355 | 0.00 361 | 0.00 356 | 0.00 353 | 0.00 354 | 0.00 354 |
|
uncertanet | | | 0.00 333 | 0.00 334 | 0.00 343 | 0.00 357 | 0.00 358 | 0.00 349 | 0.00 359 | 0.00 353 | 0.00 354 | 0.00 355 | 0.00 361 | 0.00 356 | 0.00 353 | 0.00 354 | 0.00 354 |
|
Regformer | | | 0.00 333 | 0.00 334 | 0.00 343 | 0.00 357 | 0.00 358 | 0.00 349 | 0.00 359 | 0.00 353 | 0.00 354 | 0.00 355 | 0.00 361 | 0.00 356 | 0.00 353 | 0.00 354 | 0.00 354 |
|
ab-mvs-re | | | 7.23 329 | 9.64 330 | 0.00 343 | 0.00 357 | 0.00 358 | 0.00 349 | 0.00 359 | 0.00 353 | 0.00 354 | 86.72 178 | 0.00 361 | 0.00 356 | 0.00 353 | 0.00 354 | 0.00 354 |
|
uanet | | | 0.00 333 | 0.00 334 | 0.00 343 | 0.00 357 | 0.00 358 | 0.00 349 | 0.00 359 | 0.00 353 | 0.00 354 | 0.00 355 | 0.00 361 | 0.00 356 | 0.00 353 | 0.00 354 | 0.00 354 |
|
GSMVS | | | | | | | | | | | | | | | | | 88.96 198 |
|
test_part3 | | | | | | | | 92.22 18 | | 75.63 74 | | 95.29 2 | | 97.56 1 | 86.60 12 | | |
|
test_part1 | | | | | | | | | 94.09 1 | | | | 81.79 1 | | | 96.38 2 | 93.74 36 |
|
sam_mvs1 | | | | | | | | | | | | | 51.32 236 | | | | 88.96 198 |
|
sam_mvs | | | | | | | | | | | | | 50.01 255 | | | | |
|
MTGPA | | | | | | | | | 92.02 60 | | | | | | | | |
|
test_post1 | | | | | | | | 78.90 280 | | | | 5.43 351 | 48.81 266 | 85.44 285 | 59.25 230 | | |
|
test_post | | | | | | | | | | | | 5.46 350 | 50.36 253 | 84.24 290 | | | |
|
patchmatchnet-post | | | | | | | | | | | | 74.00 318 | 51.12 239 | 88.60 261 | | | |
|
MTMP | | | | | | | | | 32.83 352 | | | | | | | | |
|
test9_res | | | | | | | | | | | | | | | 84.90 19 | 95.70 14 | 92.87 70 |
|
agg_prior2 | | | | | | | | | | | | | | | 82.91 41 | 95.45 16 | 92.70 71 |
|
test_prior4 | | | | | | | 72.60 29 | 89.01 77 | | | | | | | | | |
|
test_prior2 | | | | | | | | 88.85 81 | | 75.41 78 | 84.91 31 | 93.54 31 | 74.28 19 | | 83.31 34 | 95.86 8 | |
|
旧先验2 | | | | | | | | 86.56 163 | | 58.10 293 | 87.04 15 | | | 88.98 254 | 74.07 111 | | |
|
新几何2 | | | | | | | | 86.29 172 | | | | | | | | | |
|
无先验 | | | | | | | | 87.48 127 | 88.98 166 | 60.00 281 | | | | 94.12 95 | 67.28 167 | | 88.97 197 |
|
原ACMM2 | | | | | | | | 86.86 152 | | | | | | | | | |
|
testdata2 | | | | | | | | | | | | | | 91.01 218 | 62.37 203 | | |
|
segment_acmp | | | | | | | | | | | | | 73.08 25 | | | | |
|
testdata1 | | | | | | | | 84.14 228 | | 75.71 71 | | | | | | | |
|
plane_prior5 | | | | | | | | | 92.44 45 | | | | | 95.38 52 | 78.71 65 | 86.32 121 | 91.33 107 |
|
plane_prior4 | | | | | | | | | | | | 91.00 82 | | | | | |
|
plane_prior3 | | | | | | | 68.60 97 | | | 78.44 30 | 78.92 96 | | | | | | |
|
plane_prior2 | | | | | | | | 91.25 30 | | 79.12 23 | | | | | | | |
|
plane_prior | | | | | | | 68.71 93 | 90.38 46 | | 77.62 34 | | | | | | 86.16 123 | |
|
n2 | | | | | | | | | 0.00 359 | | | | | | | | |
|
nn | | | | | | | | | 0.00 359 | | | | | | | | |
|
door-mid | | | | | | | | | 69.98 331 | | | | | | | | |
|
test11 | | | | | | | | | 92.23 52 | | | | | | | | |
|
door | | | | | | | | | 69.44 334 | | | | | | | | |
|
HQP5-MVS | | | | | | | 66.98 124 | | | | | | | | | | |
|
BP-MVS | | | | | | | | | | | | | | | 77.47 77 | | |
|
HQP4-MVS | | | | | | | | | | | 77.24 135 | | | 95.11 60 | | | 91.03 113 |
|
HQP3-MVS | | | | | | | | | 92.19 55 | | | | | | | 85.99 125 | |
|
HQP2-MVS | | | | | | | | | | | | | 60.17 163 | | | | |
|
MDTV_nov1_ep13_2view | | | | | | | 37.79 340 | 75.16 300 | | 55.10 310 | 66.53 282 | | 49.34 260 | | 53.98 261 | | 87.94 229 |
|
ACMMP++_ref | | | | | | | | | | | | | | | | 81.95 170 | |
|
ACMMP++ | | | | | | | | | | | | | | | | 81.25 177 | |
|
Test By Simon | | | | | | | | | | | | | 64.33 89 | | | | |
|