ACMMP_Plus | | | 96.59 30 | 96.18 35 | 97.81 23 | 98.82 68 | 93.55 52 | 98.88 95 | 97.59 95 | 90.66 80 | 97.98 25 | 99.14 28 | 86.59 89 | 100.00 1 | 96.47 44 | 99.46 44 | 99.89 14 |
|
MCST-MVS | | | 98.18 2 | 97.95 4 | 98.86 1 | 99.85 3 | 96.60 5 | 99.70 10 | 97.98 51 | 97.18 2 | 95.96 61 | 99.33 8 | 92.62 12 | 100.00 1 | 98.99 6 | 99.93 1 | 99.98 2 |
|
CNVR-MVS | | | 98.46 1 | 98.38 1 | 98.72 3 | 99.80 4 | 96.19 9 | 99.80 7 | 97.99 50 | 97.05 3 | 99.41 1 | 99.59 2 | 92.89 11 | 100.00 1 | 98.99 6 | 99.90 4 | 99.96 4 |
|
MPTG | | | 96.21 44 | 95.96 41 | 96.96 58 | 99.29 44 | 91.19 100 | 98.69 111 | 97.45 117 | 92.58 46 | 94.39 85 | 99.24 13 | 86.43 94 | 99.99 4 | 96.22 48 | 99.40 50 | 99.71 42 |
|
MTAPA | | | 96.09 46 | 95.80 47 | 96.96 58 | 99.29 44 | 91.19 100 | 97.23 213 | 97.45 117 | 92.58 46 | 94.39 85 | 99.24 13 | 86.43 94 | 99.99 4 | 96.22 48 | 99.40 50 | 99.71 42 |
|
HPM-MVS++ | | | 97.72 6 | 97.59 7 | 98.14 14 | 99.53 33 | 94.76 29 | 99.19 53 | 97.75 72 | 95.66 11 | 98.21 15 | 99.29 9 | 91.10 19 | 99.99 4 | 97.68 28 | 99.87 5 | 99.68 47 |
|
DeepC-MVS_fast | | 93.52 2 | 97.16 14 | 96.84 19 | 98.13 15 | 99.61 17 | 94.45 39 | 98.85 96 | 97.64 87 | 96.51 6 | 95.88 62 | 99.39 7 | 87.35 78 | 99.99 4 | 96.61 41 | 99.69 27 | 99.96 4 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
MP-MVS | | | 96.00 47 | 95.82 45 | 96.54 86 | 99.47 36 | 90.13 128 | 99.36 44 | 97.41 124 | 90.64 83 | 95.49 70 | 98.95 52 | 85.51 104 | 99.98 8 | 96.00 55 | 99.59 39 | 99.52 62 |
|
mPP-MVS | | | 95.90 50 | 95.75 48 | 96.38 93 | 99.58 19 | 89.41 146 | 99.26 51 | 97.41 124 | 90.66 80 | 94.82 80 | 98.95 52 | 86.15 98 | 99.98 8 | 95.24 67 | 99.64 30 | 99.74 38 |
|
NCCC | | | 98.12 3 | 98.11 3 | 98.13 15 | 99.76 6 | 94.46 38 | 99.81 5 | 97.88 56 | 96.54 4 | 98.84 6 | 99.46 5 | 92.55 13 | 99.98 8 | 98.25 22 | 99.93 1 | 99.94 6 |
|
DP-MVS Recon | | | 95.85 51 | 95.15 57 | 97.95 19 | 99.87 2 | 94.38 42 | 99.60 17 | 97.48 114 | 86.58 182 | 94.42 84 | 99.13 30 | 87.36 77 | 99.98 8 | 93.64 89 | 98.33 84 | 99.48 67 |
|
AdaColmap | | | 93.82 89 | 93.06 92 | 96.10 103 | 99.88 1 | 89.07 148 | 98.33 156 | 97.55 103 | 86.81 180 | 90.39 138 | 98.65 74 | 75.09 189 | 99.98 8 | 93.32 95 | 97.53 95 | 99.26 81 |
|
test_part3 | | | | | | | | 99.43 33 | | 92.81 44 | | 99.48 3 | | 99.97 13 | 99.52 1 | | |
|
ESAPD | | | 97.97 4 | 97.82 6 | 98.43 10 | 99.54 27 | 95.42 14 | 99.43 33 | 97.69 78 | 92.81 44 | 98.13 16 | 99.48 3 | 93.96 6 | 99.97 13 | 99.52 1 | 99.83 12 | 99.90 9 |
|
region2R | | | 96.30 41 | 96.17 37 | 96.70 75 | 99.70 7 | 90.31 123 | 99.46 30 | 97.66 82 | 90.55 84 | 97.07 40 | 99.07 35 | 86.85 86 | 99.97 13 | 95.43 62 | 99.74 20 | 99.81 22 |
|
API-MVS | | | 94.78 69 | 94.18 70 | 96.59 84 | 99.21 49 | 90.06 132 | 98.80 101 | 97.78 70 | 83.59 232 | 93.85 95 | 99.21 16 | 83.79 121 | 99.97 13 | 92.37 105 | 99.00 63 | 99.74 38 |
|
HFP-MVS | | | 96.42 37 | 96.26 34 | 96.90 61 | 99.69 8 | 90.96 110 | 99.47 27 | 97.81 65 | 90.54 85 | 96.88 43 | 99.05 38 | 87.57 68 | 99.96 17 | 95.65 57 | 99.72 22 | 99.78 29 |
|
#test# | | | 96.48 34 | 96.34 32 | 96.90 61 | 99.69 8 | 90.96 110 | 99.53 24 | 97.81 65 | 90.94 78 | 96.88 43 | 99.05 38 | 87.57 68 | 99.96 17 | 95.87 56 | 99.72 22 | 99.78 29 |
|
PHI-MVS | | | 96.65 29 | 96.46 28 | 97.21 44 | 99.34 40 | 91.77 80 | 99.70 10 | 98.05 46 | 86.48 184 | 98.05 21 | 99.20 17 | 89.33 45 | 99.96 17 | 98.38 18 | 99.62 34 | 99.90 9 |
|
ACMMPR | | | 96.28 42 | 96.14 40 | 96.73 72 | 99.68 10 | 90.47 121 | 99.47 27 | 97.80 67 | 90.54 85 | 96.83 50 | 99.03 40 | 86.51 92 | 99.95 20 | 95.65 57 | 99.72 22 | 99.75 35 |
|
ACMMP | | | 94.67 74 | 94.30 67 | 95.79 112 | 99.25 47 | 88.13 164 | 98.41 150 | 98.67 22 | 90.38 88 | 91.43 120 | 98.72 70 | 82.22 149 | 99.95 20 | 93.83 86 | 95.76 122 | 99.29 77 |
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 | | | 95.80 53 | 95.30 53 | 97.29 42 | 98.95 62 | 92.66 70 | 98.59 128 | 97.14 143 | 88.95 122 | 93.12 101 | 99.25 11 | 85.62 101 | 99.94 22 | 96.56 43 | 99.48 43 | 99.28 79 |
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
DeepPCF-MVS | | 93.56 1 | 96.55 32 | 97.84 5 | 92.68 191 | 98.71 71 | 78.11 300 | 99.70 10 | 97.71 77 | 98.18 1 | 97.36 36 | 99.76 1 | 90.37 38 | 99.94 22 | 99.27 3 | 99.54 41 | 99.99 1 |
|
CANet | | | 97.00 19 | 96.49 27 | 98.55 6 | 98.86 67 | 96.10 10 | 99.83 4 | 97.52 107 | 95.90 8 | 97.21 37 | 98.90 57 | 82.66 141 | 99.93 24 | 98.71 9 | 98.80 73 | 99.63 54 |
|
MVS_0304 | | | 96.12 45 | 95.26 55 | 98.69 4 | 98.44 77 | 96.54 7 | 99.70 10 | 96.89 163 | 95.76 10 | 97.53 32 | 99.12 31 | 72.42 229 | 99.93 24 | 98.75 8 | 98.69 76 | 99.61 57 |
|
PGM-MVS | | | 95.85 51 | 95.65 50 | 96.45 89 | 99.50 35 | 89.77 138 | 98.22 171 | 98.90 16 | 89.19 113 | 96.74 52 | 98.95 52 | 85.91 100 | 99.92 26 | 93.94 82 | 99.46 44 | 99.66 50 |
|
CP-MVS | | | 96.22 43 | 96.15 39 | 96.42 91 | 99.67 11 | 89.62 141 | 99.70 10 | 97.61 93 | 90.07 99 | 96.00 58 | 99.16 24 | 87.43 72 | 99.92 26 | 96.03 54 | 99.72 22 | 99.70 44 |
|
PAPR | | | 96.35 38 | 95.82 45 | 97.94 20 | 99.63 14 | 94.19 45 | 99.42 37 | 97.55 103 | 92.43 50 | 93.82 97 | 99.12 31 | 87.30 79 | 99.91 28 | 94.02 81 | 99.06 60 | 99.74 38 |
|
MAR-MVS | | | 94.43 79 | 94.09 72 | 95.45 125 | 99.10 54 | 87.47 177 | 98.39 154 | 97.79 69 | 88.37 140 | 94.02 92 | 99.17 22 | 78.64 173 | 99.91 28 | 92.48 104 | 98.85 69 | 98.96 98 |
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 |
æ— å…ˆéªŒ | | | | | | | | 98.52 134 | 97.82 62 | 87.20 172 | | | | 99.90 30 | 87.64 150 | | 99.85 21 |
|
1121 | | | 95.19 63 | 94.45 65 | 97.42 36 | 98.88 65 | 92.58 74 | 96.22 249 | 97.75 72 | 85.50 195 | 96.86 46 | 99.01 45 | 88.59 55 | 99.90 30 | 87.64 150 | 99.60 37 | 99.79 25 |
|
PAPM_NR | | | 95.43 58 | 95.05 59 | 96.57 85 | 99.42 39 | 90.14 126 | 98.58 129 | 97.51 109 | 90.65 82 | 92.44 108 | 98.90 57 | 87.77 67 | 99.90 30 | 90.88 117 | 99.32 53 | 99.68 47 |
|
æ–°å‡ ä½•1 | | | | | 97.40 38 | 98.92 63 | 92.51 76 | | 97.77 71 | 85.52 193 | 96.69 54 | 99.06 37 | 88.08 64 | 99.89 33 | 84.88 173 | 99.62 34 | 99.79 25 |
|
testdata2 | | | | | | | | | | | | | | 99.88 34 | 84.16 180 | | |
|
SD-MVS | | | 97.51 8 | 97.40 11 | 97.81 23 | 99.01 58 | 93.79 49 | 99.33 49 | 97.38 127 | 93.73 29 | 98.83 7 | 99.02 41 | 90.87 30 | 99.88 34 | 98.69 10 | 99.74 20 | 99.77 34 |
|
DP-MVS | | | 88.75 193 | 86.56 201 | 95.34 127 | 98.92 63 | 87.45 178 | 97.64 201 | 93.52 291 | 70.55 317 | 81.49 235 | 97.25 123 | 74.43 203 | 99.88 34 | 71.14 299 | 94.09 135 | 98.67 122 |
|
XVS | | | 96.47 35 | 96.37 30 | 96.77 68 | 99.62 15 | 90.66 119 | 99.43 33 | 97.58 97 | 92.41 54 | 96.86 46 | 98.96 50 | 87.37 74 | 99.87 37 | 95.65 57 | 99.43 47 | 99.78 29 |
|
X-MVStestdata | | | 90.69 162 | 88.66 175 | 96.77 68 | 99.62 15 | 90.66 119 | 99.43 33 | 97.58 97 | 92.41 54 | 96.86 46 | 29.59 354 | 87.37 74 | 99.87 37 | 95.65 57 | 99.43 47 | 99.78 29 |
|
PVSNet_BlendedMVS | | | 93.36 103 | 93.20 90 | 93.84 170 | 98.77 69 | 91.61 86 | 99.47 27 | 98.04 47 | 91.44 69 | 94.21 89 | 92.63 219 | 83.50 123 | 99.87 37 | 97.41 29 | 83.37 225 | 90.05 283 |
|
PVSNet_Blended | | | 95.94 49 | 95.66 49 | 96.75 70 | 98.77 69 | 91.61 86 | 99.88 1 | 98.04 47 | 93.64 31 | 94.21 89 | 97.76 103 | 83.50 123 | 99.87 37 | 97.41 29 | 97.75 92 | 98.79 113 |
|
QAPM | | | 91.41 148 | 89.49 160 | 97.17 46 | 95.66 160 | 93.42 56 | 98.60 126 | 97.51 109 | 80.92 272 | 81.39 237 | 97.41 115 | 72.89 226 | 99.87 37 | 82.33 198 | 98.68 77 | 98.21 147 |
|
CSCG | | | 94.87 67 | 94.71 62 | 95.36 126 | 99.54 27 | 86.49 204 | 99.34 48 | 98.15 42 | 82.71 251 | 90.15 141 | 99.25 11 | 89.48 44 | 99.86 42 | 94.97 71 | 98.82 72 | 99.72 41 |
|
PLC | | 91.07 3 | 94.23 83 | 94.01 74 | 94.87 141 | 99.17 50 | 87.49 176 | 99.25 52 | 96.55 176 | 88.43 138 | 91.26 123 | 98.21 95 | 85.92 99 | 99.86 42 | 89.77 128 | 97.57 93 | 97.24 171 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
DeepC-MVS | | 91.02 4 | 94.56 78 | 93.92 81 | 96.46 88 | 97.16 112 | 90.76 115 | 98.39 154 | 97.11 146 | 93.92 22 | 88.66 159 | 98.33 90 | 78.14 175 | 99.85 44 | 95.02 69 | 98.57 80 | 98.78 116 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
CANet_DTU | | | 94.31 82 | 93.35 87 | 97.20 45 | 97.03 117 | 94.71 31 | 98.62 122 | 95.54 241 | 95.61 12 | 97.21 37 | 98.47 87 | 71.88 235 | 99.84 45 | 88.38 143 | 97.46 97 | 97.04 177 |
|
CNLPA | | | 93.64 96 | 92.74 98 | 96.36 94 | 98.96 61 | 90.01 134 | 99.19 53 | 95.89 220 | 86.22 187 | 89.40 154 | 98.85 60 | 80.66 160 | 99.84 45 | 88.57 142 | 96.92 102 | 99.24 82 |
|
MVS | | | 93.92 86 | 92.28 107 | 98.83 2 | 95.69 158 | 96.82 3 | 96.22 249 | 98.17 40 | 84.89 207 | 84.34 194 | 98.61 77 | 79.32 165 | 99.83 47 | 93.88 84 | 99.43 47 | 99.86 20 |
|
DELS-MVS | | | 97.12 15 | 96.60 26 | 98.68 5 | 98.03 85 | 96.57 6 | 99.84 3 | 97.84 60 | 96.36 7 | 95.20 75 | 98.24 92 | 88.17 61 | 99.83 47 | 96.11 52 | 99.60 37 | 99.64 52 |
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 |
LS3D | | | 90.19 167 | 88.72 173 | 94.59 148 | 98.97 59 | 86.33 211 | 96.90 223 | 96.60 170 | 74.96 306 | 84.06 197 | 98.74 67 | 75.78 186 | 99.83 47 | 74.93 269 | 97.57 93 | 97.62 164 |
|
3Dnovator | | 87.35 11 | 93.17 111 | 91.77 121 | 97.37 41 | 95.41 165 | 93.07 62 | 98.82 99 | 97.85 59 | 91.53 67 | 82.56 218 | 97.58 109 | 71.97 234 | 99.82 50 | 91.01 115 | 99.23 58 | 99.22 84 |
|
OpenMVS | | 85.28 14 | 90.75 160 | 88.84 171 | 96.48 87 | 93.58 213 | 93.51 54 | 98.80 101 | 97.41 124 | 82.59 252 | 78.62 260 | 97.49 112 | 68.00 262 | 99.82 50 | 84.52 177 | 98.55 81 | 96.11 195 |
|
MSLP-MVS++ | | | 97.50 9 | 97.45 10 | 97.63 27 | 99.65 13 | 93.21 57 | 99.70 10 | 98.13 44 | 94.61 16 | 97.78 30 | 99.46 5 | 89.85 40 | 99.81 52 | 97.97 24 | 99.91 3 | 99.88 15 |
|
CHOSEN 1792x2688 | | | 94.35 81 | 93.82 83 | 95.95 108 | 97.40 104 | 88.74 155 | 98.41 150 | 98.27 27 | 92.18 59 | 91.43 120 | 96.40 158 | 78.88 167 | 99.81 52 | 93.59 90 | 97.81 88 | 99.30 76 |
|
1314 | | | 93.44 99 | 91.98 117 | 97.84 21 | 95.24 167 | 94.38 42 | 96.22 249 | 97.92 54 | 90.18 93 | 82.28 223 | 97.71 105 | 77.63 178 | 99.80 54 | 91.94 110 | 98.67 78 | 99.34 73 |
|
3Dnovator+ | | 87.72 8 | 93.43 100 | 91.84 119 | 98.17 13 | 95.73 157 | 95.08 20 | 98.92 86 | 97.04 154 | 91.42 72 | 81.48 236 | 97.60 108 | 74.60 196 | 99.79 55 | 90.84 118 | 98.97 64 | 99.64 52 |
|
PCF-MVS | | 89.78 5 | 91.26 149 | 89.63 159 | 96.16 101 | 95.44 164 | 91.58 88 | 95.29 275 | 96.10 202 | 85.07 203 | 82.75 214 | 97.45 113 | 78.28 174 | 99.78 56 | 80.60 220 | 95.65 125 | 97.12 172 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
TSAR-MVS + GP. | | | 96.95 21 | 96.91 17 | 97.07 47 | 98.88 65 | 91.62 85 | 99.58 18 | 96.54 177 | 95.09 15 | 96.84 49 | 98.63 76 | 91.16 17 | 99.77 57 | 99.04 5 | 96.42 108 | 99.81 22 |
|
MVS_111021_LR | | | 95.78 54 | 95.94 42 | 95.28 129 | 98.19 82 | 87.69 171 | 98.80 101 | 99.26 12 | 93.39 34 | 95.04 78 | 98.69 73 | 84.09 119 | 99.76 58 | 96.96 38 | 99.06 60 | 98.38 138 |
|
MVS_111021_HR | | | 96.69 27 | 96.69 24 | 96.72 74 | 98.58 75 | 91.00 109 | 99.14 65 | 99.45 1 | 93.86 26 | 95.15 76 | 98.73 68 | 88.48 56 | 99.76 58 | 97.23 31 | 99.56 40 | 99.40 69 |
|
MG-MVS | | | 97.24 12 | 96.83 20 | 98.47 9 | 99.79 5 | 95.71 12 | 99.07 71 | 99.06 14 | 94.45 18 | 96.42 56 | 98.70 72 | 88.81 51 | 99.74 60 | 95.35 64 | 99.86 8 | 99.97 3 |
|
原ACMM1 | | | | | 96.18 98 | 99.03 57 | 90.08 129 | | 97.63 91 | 88.98 120 | 97.00 41 | 98.97 47 | 88.14 63 | 99.71 61 | 88.23 144 | 99.62 34 | 98.76 118 |
|
agg_prior3 | | | 97.09 17 | 96.97 16 | 97.45 34 | 99.56 25 | 92.79 69 | 99.36 44 | 97.67 81 | 89.59 103 | 98.36 13 | 99.16 24 | 90.57 34 | 99.68 62 | 98.58 14 | 99.85 9 | 99.88 15 |
|
PVSNet_Blended_VisFu | | | 94.67 74 | 94.11 71 | 96.34 95 | 97.14 113 | 91.10 105 | 99.32 50 | 97.43 122 | 92.10 60 | 91.53 118 | 96.38 161 | 83.29 129 | 99.68 62 | 93.42 94 | 96.37 109 | 98.25 145 |
|
UGNet | | | 91.91 141 | 90.85 143 | 95.10 133 | 97.06 116 | 88.69 156 | 98.01 188 | 98.24 29 | 92.41 54 | 92.39 109 | 93.61 200 | 60.52 299 | 99.68 62 | 88.14 145 | 97.25 99 | 96.92 182 |
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 |
TEST9 | | | | | | 99.57 23 | 93.17 58 | 99.38 40 | 97.66 82 | 89.57 105 | 98.39 11 | 99.18 20 | 90.88 29 | 99.66 65 | | | |
|
train_agg | | | 97.20 13 | 97.08 14 | 97.57 31 | 99.57 23 | 93.17 58 | 99.38 40 | 97.66 82 | 90.18 93 | 98.39 11 | 99.18 20 | 90.94 27 | 99.66 65 | 98.58 14 | 99.85 9 | 99.88 15 |
|
EPNet | | | 96.82 25 | 96.68 25 | 97.25 43 | 98.65 72 | 93.10 61 | 99.48 26 | 98.76 17 | 96.54 4 | 97.84 29 | 98.22 93 | 87.49 71 | 99.66 65 | 95.35 64 | 97.78 91 | 99.00 93 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
SteuartSystems-ACMMP | | | 97.25 11 | 97.34 12 | 97.01 50 | 97.38 105 | 91.46 89 | 99.75 8 | 97.66 82 | 94.14 21 | 98.13 16 | 99.26 10 | 92.16 14 | 99.66 65 | 97.91 26 | 99.64 30 | 99.90 9 |
Skip Steuart: Steuart Systems R&D Blog. |
sss | | | 94.85 68 | 93.94 80 | 97.58 29 | 96.43 138 | 94.09 46 | 98.93 84 | 99.16 13 | 89.50 107 | 95.27 73 | 97.85 99 | 81.50 154 | 99.65 69 | 92.79 103 | 94.02 136 | 98.99 95 |
|
F-COLMAP | | | 92.07 136 | 91.75 122 | 93.02 183 | 98.16 83 | 82.89 262 | 98.79 104 | 95.97 207 | 86.54 183 | 87.92 168 | 97.80 101 | 78.69 172 | 99.65 69 | 85.97 163 | 95.93 120 | 96.53 193 |
|
test_8 | | | | | | 99.55 26 | 93.07 62 | 99.37 43 | 97.64 87 | 90.18 93 | 98.36 13 | 99.19 18 | 90.94 27 | 99.64 71 | | | |
|
abl_6 | | | 94.63 76 | 94.48 64 | 95.09 134 | 98.61 74 | 86.96 191 | 98.06 186 | 96.97 160 | 89.31 109 | 95.86 64 | 98.56 79 | 79.82 161 | 99.64 71 | 94.53 79 | 98.65 79 | 98.66 123 |
|
PVSNet | | 87.13 12 | 93.69 92 | 92.83 97 | 96.28 96 | 97.99 86 | 90.22 125 | 99.38 40 | 98.93 15 | 91.42 72 | 93.66 98 | 97.68 106 | 71.29 241 | 99.64 71 | 87.94 147 | 97.20 100 | 98.98 96 |
|
agg_prior1 | | | 97.12 15 | 97.03 15 | 97.38 40 | 99.54 27 | 92.66 70 | 99.35 46 | 97.64 87 | 90.38 88 | 97.98 25 | 99.17 22 | 90.84 31 | 99.61 74 | 98.57 16 | 99.78 19 | 99.87 19 |
|
agg_prior | | | | | | 99.54 27 | 92.66 70 | | 97.64 87 | | 97.98 25 | | | 99.61 74 | | | |
|
PS-MVSNAJ | | | 96.87 24 | 96.40 29 | 98.29 11 | 97.35 106 | 97.29 1 | 99.03 75 | 97.11 146 | 95.83 9 | 98.97 3 | 99.14 28 | 82.48 144 | 99.60 76 | 98.60 11 | 99.08 59 | 98.00 153 |
|
MSDG | | | 88.29 199 | 86.37 203 | 94.04 164 | 96.90 120 | 86.15 218 | 96.52 236 | 94.36 279 | 77.89 299 | 79.22 256 | 96.95 141 | 69.72 248 | 99.59 77 | 73.20 288 | 92.58 147 | 96.37 194 |
|
APDe-MVS | | | 97.53 7 | 97.47 8 | 97.70 25 | 99.58 19 | 93.63 50 | 99.56 21 | 97.52 107 | 93.59 32 | 98.01 24 | 99.12 31 | 90.80 32 | 99.55 78 | 99.26 4 | 99.79 17 | 99.93 7 |
|
CPTT-MVS | | | 94.60 77 | 94.43 66 | 95.09 134 | 99.66 12 | 86.85 194 | 99.44 31 | 97.47 115 | 83.22 242 | 94.34 87 | 98.96 50 | 82.50 142 | 99.55 78 | 94.81 73 | 99.50 42 | 98.88 106 |
|
Regformer-1 | | | 96.97 20 | 96.80 21 | 97.47 33 | 99.46 37 | 93.11 60 | 98.89 93 | 97.94 52 | 92.89 41 | 96.90 42 | 99.02 41 | 89.78 41 | 99.53 80 | 97.06 32 | 99.26 56 | 99.75 35 |
|
Regformer-2 | | | 96.94 23 | 96.78 22 | 97.42 36 | 99.46 37 | 92.97 65 | 98.89 93 | 97.93 53 | 92.86 43 | 96.88 43 | 99.02 41 | 89.74 42 | 99.53 80 | 97.03 33 | 99.26 56 | 99.75 35 |
|
VNet | | | 95.08 64 | 94.26 68 | 97.55 32 | 98.07 84 | 93.88 48 | 98.68 114 | 98.73 20 | 90.33 90 | 97.16 39 | 97.43 114 | 79.19 166 | 99.53 80 | 96.91 39 | 91.85 158 | 99.24 82 |
|
Regformer-3 | | | 96.50 33 | 96.36 31 | 96.91 60 | 99.34 40 | 91.72 83 | 98.71 107 | 97.90 55 | 92.48 49 | 96.00 58 | 98.95 52 | 88.60 53 | 99.52 83 | 96.44 45 | 98.83 70 | 99.49 65 |
|
Regformer-4 | | | 96.45 36 | 96.33 33 | 96.81 67 | 99.34 40 | 91.44 90 | 98.71 107 | 97.88 56 | 92.43 50 | 95.97 60 | 98.95 52 | 88.42 57 | 99.51 84 | 96.40 46 | 98.83 70 | 99.49 65 |
|
test12 | | | | | 97.83 22 | 99.33 43 | 94.45 39 | | 97.55 103 | | 97.56 31 | | 88.60 53 | 99.50 85 | | 99.71 26 | 99.55 60 |
|
HSP-MVS | | | 97.73 5 | 98.15 2 | 96.44 90 | 99.54 27 | 90.14 126 | 99.41 38 | 97.47 115 | 95.46 14 | 98.60 8 | 99.19 18 | 95.71 4 | 99.49 86 | 98.15 23 | 99.85 9 | 99.69 46 |
|
test_prior3 | | | 97.07 18 | 97.09 13 | 97.01 50 | 99.58 19 | 91.77 80 | 99.57 19 | 97.57 100 | 91.43 70 | 98.12 19 | 98.97 47 | 90.43 36 | 99.49 86 | 98.33 19 | 99.81 15 | 99.79 25 |
|
test_prior | | | | | 97.01 50 | 99.58 19 | 91.77 80 | | 97.57 100 | | | | | 99.49 86 | | | 99.79 25 |
|
CDPH-MVS | | | 96.56 31 | 96.18 35 | 97.70 25 | 99.59 18 | 93.92 47 | 99.13 68 | 97.44 120 | 89.02 119 | 97.90 28 | 99.22 15 | 88.90 50 | 99.49 86 | 94.63 77 | 99.79 17 | 99.68 47 |
|
HY-MVS | | 88.56 7 | 95.29 62 | 94.23 69 | 98.48 8 | 97.72 90 | 96.41 8 | 94.03 287 | 98.74 18 | 92.42 53 | 95.65 68 | 94.76 180 | 86.52 91 | 99.49 86 | 95.29 66 | 92.97 142 | 99.53 61 |
|
EI-MVSNet-UG-set | | | 95.43 58 | 95.29 54 | 95.86 111 | 99.07 56 | 89.87 135 | 98.43 147 | 97.80 67 | 91.78 64 | 94.11 91 | 98.77 64 | 86.25 97 | 99.48 91 | 94.95 72 | 96.45 107 | 98.22 146 |
|
EI-MVSNet-Vis-set | | | 95.76 56 | 95.63 52 | 96.17 100 | 99.14 51 | 90.33 122 | 98.49 140 | 97.82 62 | 91.92 61 | 94.75 81 | 98.88 59 | 87.06 82 | 99.48 91 | 95.40 63 | 97.17 101 | 98.70 121 |
|
WTY-MVS | | | 95.97 48 | 95.11 58 | 98.54 7 | 97.62 93 | 96.65 4 | 99.44 31 | 98.74 18 | 92.25 57 | 95.21 74 | 98.46 89 | 86.56 90 | 99.46 93 | 95.00 70 | 92.69 146 | 99.50 64 |
|
APD-MVS | | | 96.95 21 | 96.72 23 | 97.63 27 | 99.51 34 | 93.58 51 | 99.16 58 | 97.44 120 | 90.08 98 | 98.59 9 | 99.07 35 | 89.06 47 | 99.42 94 | 97.92 25 | 99.66 28 | 99.88 15 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
ab-mvs | | | 91.05 154 | 89.17 165 | 96.69 76 | 95.96 151 | 91.72 83 | 92.62 299 | 97.23 136 | 85.61 192 | 89.74 147 | 93.89 193 | 68.55 257 | 99.42 94 | 91.09 113 | 87.84 197 | 98.92 104 |
|
PatchMatch-RL | | | 91.47 146 | 90.54 152 | 94.26 157 | 98.20 80 | 86.36 210 | 96.94 221 | 97.14 143 | 87.75 157 | 88.98 156 | 95.75 167 | 71.80 237 | 99.40 96 | 80.92 213 | 97.39 98 | 97.02 178 |
|
XVG-OURS-SEG-HR | | | 90.95 156 | 90.66 151 | 91.83 202 | 95.18 173 | 81.14 279 | 95.92 260 | 95.92 214 | 88.40 139 | 90.33 139 | 97.85 99 | 70.66 244 | 99.38 97 | 92.83 102 | 88.83 194 | 94.98 198 |
|
HPM-MVS | | | 95.41 60 | 95.22 56 | 95.99 105 | 99.29 44 | 89.14 147 | 99.17 57 | 97.09 150 | 87.28 171 | 95.40 71 | 98.48 86 | 84.93 111 | 99.38 97 | 95.64 61 | 99.65 29 | 99.47 68 |
|
xiu_mvs_v2_base | | | 96.66 28 | 96.17 37 | 98.11 17 | 97.11 114 | 96.96 2 | 99.01 78 | 97.04 154 | 95.51 13 | 98.86 5 | 99.11 34 | 82.19 150 | 99.36 99 | 98.59 13 | 98.14 85 | 98.00 153 |
|
APD-MVS_3200maxsize | | | 95.64 57 | 95.65 50 | 95.62 116 | 99.24 48 | 87.80 170 | 98.42 148 | 97.22 137 | 88.93 124 | 96.64 55 | 98.98 46 | 85.49 105 | 99.36 99 | 96.68 40 | 99.27 55 | 99.70 44 |
|
XVG-OURS | | | 90.83 158 | 90.49 153 | 91.86 201 | 95.23 168 | 81.25 277 | 95.79 268 | 95.92 214 | 88.96 121 | 90.02 143 | 98.03 98 | 71.60 238 | 99.35 101 | 91.06 114 | 87.78 198 | 94.98 198 |
|
PVSNet_0 | | 83.28 16 | 87.31 207 | 85.16 225 | 93.74 173 | 94.78 187 | 84.59 245 | 98.91 87 | 98.69 21 | 89.81 101 | 78.59 262 | 93.23 209 | 61.95 294 | 99.34 102 | 94.75 74 | 55.72 335 | 97.30 170 |
|
HPM-MVS_fast | | | 94.89 66 | 94.62 63 | 95.70 115 | 99.11 53 | 88.44 161 | 99.14 65 | 97.11 146 | 85.82 190 | 95.69 67 | 98.47 87 | 83.46 125 | 99.32 103 | 93.16 97 | 99.63 33 | 99.35 71 |
|
114514_t | | | 94.06 85 | 93.05 93 | 97.06 48 | 99.08 55 | 92.26 78 | 98.97 82 | 97.01 158 | 82.58 253 | 92.57 106 | 98.22 93 | 80.68 159 | 99.30 104 | 89.34 134 | 99.02 62 | 99.63 54 |
|
VDD-MVS | | | 91.24 152 | 90.18 155 | 94.45 152 | 97.08 115 | 85.84 230 | 98.40 153 | 96.10 202 | 86.99 173 | 93.36 99 | 98.16 96 | 54.27 316 | 99.20 105 | 96.59 42 | 90.63 175 | 98.31 144 |
|
AllTest | | | 84.97 245 | 83.12 247 | 90.52 231 | 96.82 128 | 78.84 293 | 95.89 261 | 92.17 313 | 77.96 296 | 75.94 276 | 95.50 170 | 55.48 311 | 99.18 106 | 71.15 297 | 87.14 199 | 93.55 204 |
|
TestCases | | | | | 90.52 231 | 96.82 128 | 78.84 293 | | 92.17 313 | 77.96 296 | 75.94 276 | 95.50 170 | 55.48 311 | 99.18 106 | 71.15 297 | 87.14 199 | 93.55 204 |
|
xiu_mvs_v1_base_debu | | | 94.73 70 | 93.98 75 | 96.99 53 | 95.19 170 | 95.24 17 | 98.62 122 | 96.50 178 | 92.99 37 | 97.52 33 | 98.83 61 | 72.37 230 | 99.15 108 | 97.03 33 | 96.74 103 | 96.58 190 |
|
xiu_mvs_v1_base | | | 94.73 70 | 93.98 75 | 96.99 53 | 95.19 170 | 95.24 17 | 98.62 122 | 96.50 178 | 92.99 37 | 97.52 33 | 98.83 61 | 72.37 230 | 99.15 108 | 97.03 33 | 96.74 103 | 96.58 190 |
|
xiu_mvs_v1_base_debi | | | 94.73 70 | 93.98 75 | 96.99 53 | 95.19 170 | 95.24 17 | 98.62 122 | 96.50 178 | 92.99 37 | 97.52 33 | 98.83 61 | 72.37 230 | 99.15 108 | 97.03 33 | 96.74 103 | 96.58 190 |
|
OMC-MVS | | | 93.90 87 | 93.62 85 | 94.73 145 | 98.63 73 | 87.00 190 | 98.04 187 | 96.56 175 | 92.19 58 | 92.46 107 | 98.73 68 | 79.49 164 | 99.14 111 | 92.16 108 | 94.34 134 | 98.03 152 |
|
COLMAP_ROB | | 82.69 18 | 84.54 251 | 82.82 251 | 89.70 248 | 96.72 132 | 78.85 292 | 95.89 261 | 92.83 306 | 71.55 314 | 77.54 271 | 95.89 166 | 59.40 302 | 99.14 111 | 67.26 306 | 88.26 195 | 91.11 250 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
UA-Net | | | 93.30 106 | 92.62 101 | 95.34 127 | 96.27 142 | 88.53 160 | 95.88 263 | 96.97 160 | 90.90 79 | 95.37 72 | 97.07 135 | 82.38 147 | 99.10 113 | 83.91 186 | 94.86 131 | 98.38 138 |
|
TSAR-MVS + MP. | | | 97.44 10 | 97.46 9 | 97.39 39 | 99.12 52 | 93.49 55 | 98.52 134 | 97.50 112 | 94.46 17 | 98.99 2 | 98.64 75 | 91.58 16 | 99.08 114 | 98.49 17 | 99.83 12 | 99.60 58 |
|
canonicalmvs | | | 95.02 65 | 93.96 78 | 98.20 12 | 97.53 99 | 95.92 11 | 98.71 107 | 96.19 198 | 91.78 64 | 95.86 64 | 98.49 85 | 79.53 163 | 99.03 115 | 96.12 51 | 91.42 166 | 99.66 50 |
|
alignmvs | | | 95.77 55 | 95.00 60 | 98.06 18 | 97.35 106 | 95.68 13 | 99.71 9 | 97.50 112 | 91.50 68 | 96.16 57 | 98.61 77 | 86.28 96 | 99.00 116 | 96.19 50 | 91.74 160 | 99.51 63 |
|
旧先验2 | | | | | | | | 98.67 116 | | 85.75 191 | 98.96 4 | | | 98.97 117 | 93.84 85 | | |
|
LFMVS | | | 92.23 130 | 90.84 144 | 96.42 91 | 98.24 79 | 91.08 107 | 98.24 169 | 96.22 196 | 83.39 240 | 94.74 82 | 98.31 91 | 61.12 298 | 98.85 118 | 94.45 80 | 92.82 143 | 99.32 74 |
|
TAPA-MVS | | 87.50 9 | 90.35 163 | 89.05 167 | 94.25 158 | 98.48 76 | 85.17 240 | 98.42 148 | 96.58 174 | 82.44 257 | 87.24 175 | 98.53 80 | 82.77 140 | 98.84 119 | 59.09 325 | 97.88 87 | 98.72 119 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
IB-MVS | | 89.43 6 | 92.12 135 | 90.83 146 | 95.98 106 | 95.40 166 | 90.78 114 | 99.81 5 | 98.06 45 | 91.23 76 | 85.63 185 | 93.66 199 | 90.63 33 | 98.78 120 | 91.22 112 | 71.85 296 | 98.36 141 |
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 |
VDDNet | | | 90.08 171 | 88.54 181 | 94.69 146 | 94.41 192 | 87.68 172 | 98.21 174 | 96.40 183 | 76.21 302 | 93.33 100 | 97.75 104 | 54.93 314 | 98.77 121 | 94.71 76 | 90.96 169 | 97.61 165 |
|
thres200 | | | 93.69 92 | 92.59 102 | 96.97 57 | 97.76 88 | 94.74 30 | 99.35 46 | 99.36 2 | 89.23 112 | 91.21 125 | 96.97 140 | 83.42 126 | 98.77 121 | 85.08 171 | 90.96 169 | 97.39 168 |
|
conf200view11 | | | 93.32 105 | 92.15 112 | 96.84 66 | 97.62 93 | 94.84 24 | 99.06 73 | 99.36 2 | 87.96 150 | 90.47 135 | 96.78 144 | 83.29 129 | 98.75 123 | 84.11 182 | 90.69 171 | 96.94 179 |
|
thres100view900 | | | 93.34 104 | 92.15 112 | 96.90 61 | 97.62 93 | 94.84 24 | 99.06 73 | 99.36 2 | 87.96 150 | 90.47 135 | 96.78 144 | 83.29 129 | 98.75 123 | 84.11 182 | 90.69 171 | 97.12 172 |
|
tfpn200view9 | | | 93.43 100 | 92.27 108 | 96.90 61 | 97.68 91 | 94.84 24 | 99.18 55 | 99.36 2 | 88.45 135 | 90.79 128 | 96.90 142 | 83.31 127 | 98.75 123 | 84.11 182 | 90.69 171 | 97.12 172 |
|
thres400 | | | 93.39 102 | 92.27 108 | 96.73 72 | 97.68 91 | 94.84 24 | 99.18 55 | 99.36 2 | 88.45 135 | 90.79 128 | 96.90 142 | 83.31 127 | 98.75 123 | 84.11 182 | 90.69 171 | 96.61 184 |
|
testdata | | | | | 95.26 130 | 98.20 80 | 87.28 186 | | 97.60 94 | 85.21 199 | 98.48 10 | 99.15 26 | 88.15 62 | 98.72 127 | 90.29 122 | 99.45 46 | 99.78 29 |
|
thres600view7 | | | 93.18 110 | 92.00 116 | 96.75 70 | 97.62 93 | 94.92 21 | 99.07 71 | 99.36 2 | 87.96 150 | 90.47 135 | 96.78 144 | 83.29 129 | 98.71 128 | 82.93 194 | 90.47 178 | 96.61 184 |
|
1112_ss | | | 92.71 120 | 91.55 126 | 96.20 97 | 95.56 161 | 91.12 103 | 98.48 141 | 94.69 271 | 88.29 143 | 86.89 179 | 98.50 83 | 87.02 83 | 98.66 129 | 84.75 174 | 89.77 186 | 98.81 111 |
|
Test_1112_low_res | | | 92.27 129 | 90.97 140 | 96.18 98 | 95.53 162 | 91.10 105 | 98.47 143 | 94.66 272 | 88.28 144 | 86.83 180 | 93.50 204 | 87.00 84 | 98.65 130 | 84.69 175 | 89.74 187 | 98.80 112 |
|
view600 | | | 92.78 115 | 91.50 127 | 96.63 79 | 97.51 100 | 94.66 33 | 98.91 87 | 99.36 2 | 87.31 167 | 89.64 150 | 96.59 150 | 83.26 133 | 98.63 131 | 80.76 216 | 90.15 180 | 96.61 184 |
|
view800 | | | 92.78 115 | 91.50 127 | 96.63 79 | 97.51 100 | 94.66 33 | 98.91 87 | 99.36 2 | 87.31 167 | 89.64 150 | 96.59 150 | 83.26 133 | 98.63 131 | 80.76 216 | 90.15 180 | 96.61 184 |
|
conf0.05thres1000 | | | 92.78 115 | 91.50 127 | 96.63 79 | 97.51 100 | 94.66 33 | 98.91 87 | 99.36 2 | 87.31 167 | 89.64 150 | 96.59 150 | 83.26 133 | 98.63 131 | 80.76 216 | 90.15 180 | 96.61 184 |
|
tfpn | | | 92.78 115 | 91.50 127 | 96.63 79 | 97.51 100 | 94.66 33 | 98.91 87 | 99.36 2 | 87.31 167 | 89.64 150 | 96.59 150 | 83.26 133 | 98.63 131 | 80.76 216 | 90.15 180 | 96.61 184 |
|
cascas | | | 90.93 157 | 89.33 164 | 95.76 114 | 95.69 158 | 93.03 64 | 98.99 81 | 96.59 171 | 80.49 274 | 86.79 181 | 94.45 183 | 65.23 281 | 98.60 135 | 93.52 91 | 92.18 154 | 95.66 197 |
|
DI_MVS_plusplus_test | | | 89.41 180 | 87.24 195 | 95.92 110 | 89.06 288 | 90.75 117 | 98.18 176 | 96.63 168 | 89.29 111 | 70.54 298 | 90.31 265 | 63.50 288 | 98.40 136 | 92.25 107 | 95.44 126 | 98.60 124 |
|
test_normal | | | 89.37 181 | 87.18 197 | 95.93 109 | 88.94 290 | 90.83 113 | 98.24 169 | 96.62 169 | 89.31 109 | 70.38 300 | 90.20 272 | 63.50 288 | 98.37 137 | 92.06 109 | 95.41 127 | 98.59 127 |
|
RPSCF | | | 85.33 243 | 85.55 220 | 84.67 304 | 94.63 190 | 62.28 330 | 93.73 290 | 93.76 286 | 74.38 309 | 85.23 188 | 97.06 136 | 64.09 284 | 98.31 138 | 80.98 211 | 86.08 207 | 93.41 206 |
|
gm-plane-assit | | | | | | 94.69 189 | 88.14 163 | | | 88.22 145 | | 97.20 127 | | 98.29 139 | 90.79 119 | | |
|
MVS_Test | | | 93.67 95 | 92.67 100 | 96.69 76 | 96.72 132 | 92.66 70 | 97.22 214 | 96.03 204 | 87.69 161 | 95.12 77 | 94.03 187 | 81.55 153 | 98.28 140 | 89.17 138 | 96.46 106 | 99.14 87 |
|
diffmvs | | | 92.07 136 | 90.77 148 | 95.97 107 | 96.41 139 | 91.32 98 | 96.46 238 | 95.98 205 | 81.73 264 | 94.33 88 | 93.36 205 | 78.72 171 | 98.20 141 | 84.28 178 | 95.66 124 | 98.41 134 |
|
tpmvs | | | 89.16 182 | 87.76 186 | 93.35 176 | 97.19 111 | 84.75 244 | 90.58 317 | 97.36 129 | 81.99 260 | 84.56 191 | 89.31 283 | 83.98 120 | 98.17 142 | 74.85 271 | 90.00 185 | 97.12 172 |
|
BH-RMVSNet | | | 91.25 151 | 89.99 157 | 95.03 139 | 96.75 131 | 88.55 158 | 98.65 118 | 94.95 265 | 87.74 158 | 87.74 169 | 97.80 101 | 68.27 259 | 98.14 143 | 80.53 221 | 97.49 96 | 98.41 134 |
|
PMMVS | | | 93.62 97 | 93.90 82 | 92.79 187 | 96.79 130 | 81.40 273 | 98.85 96 | 96.81 164 | 91.25 75 | 96.82 51 | 98.15 97 | 77.02 181 | 98.13 144 | 93.15 98 | 96.30 112 | 98.83 110 |
|
DWT-MVSNet_test | | | 94.36 80 | 93.95 79 | 95.62 116 | 96.99 118 | 89.47 144 | 96.62 234 | 97.38 127 | 90.96 77 | 93.07 103 | 97.27 122 | 93.73 8 | 98.09 145 | 85.86 167 | 93.65 138 | 99.29 77 |
|
lupinMVS | | | 96.32 40 | 95.94 42 | 97.44 35 | 95.05 180 | 94.87 22 | 99.86 2 | 96.50 178 | 93.82 27 | 98.04 22 | 98.77 64 | 85.52 102 | 98.09 145 | 96.98 37 | 98.97 64 | 99.37 70 |
|
TR-MVS | | | 90.77 159 | 89.44 161 | 94.76 143 | 96.31 141 | 88.02 167 | 97.92 190 | 95.96 209 | 85.52 193 | 88.22 161 | 97.23 125 | 66.80 271 | 98.09 145 | 84.58 176 | 92.38 148 | 98.17 149 |
|
mvs-test1 | | | 91.57 144 | 92.20 110 | 89.70 248 | 95.15 174 | 74.34 309 | 99.51 25 | 95.40 252 | 91.92 61 | 91.02 126 | 97.25 123 | 74.27 206 | 98.08 148 | 89.45 130 | 95.83 121 | 96.67 183 |
|
tpm cat1 | | | 88.89 186 | 87.27 194 | 93.76 172 | 95.79 154 | 85.32 236 | 90.76 315 | 97.09 150 | 76.14 303 | 85.72 184 | 88.59 288 | 82.92 138 | 98.04 149 | 76.96 246 | 91.43 165 | 97.90 159 |
|
PatchFormer-LS_test | | | 94.08 84 | 93.60 86 | 95.53 123 | 96.92 119 | 89.57 142 | 96.51 237 | 97.34 131 | 91.29 74 | 92.22 111 | 97.18 128 | 91.66 15 | 98.02 150 | 87.05 154 | 92.21 153 | 99.00 93 |
|
Effi-MVS+ | | | 93.87 88 | 93.15 91 | 96.02 104 | 95.79 154 | 90.76 115 | 96.70 231 | 95.78 223 | 86.98 175 | 95.71 66 | 97.17 130 | 79.58 162 | 98.01 151 | 94.57 78 | 96.09 116 | 99.31 75 |
|
Vis-MVSNet | | | 92.64 123 | 91.85 118 | 95.03 139 | 95.12 176 | 88.23 162 | 98.48 141 | 96.81 164 | 91.61 66 | 92.16 112 | 97.22 126 | 71.58 239 | 98.00 152 | 85.85 168 | 97.81 88 | 98.88 106 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
jason | | | 95.40 61 | 94.86 61 | 97.03 49 | 92.91 225 | 94.23 44 | 99.70 10 | 96.30 189 | 93.56 33 | 96.73 53 | 98.52 81 | 81.46 155 | 97.91 153 | 96.08 53 | 98.47 82 | 98.96 98 |
jason: jason. |
BH-w/o | | | 92.32 127 | 91.79 120 | 93.91 168 | 96.85 121 | 86.18 216 | 99.11 69 | 95.74 225 | 88.13 147 | 84.81 189 | 97.00 138 | 77.26 180 | 97.91 153 | 89.16 139 | 98.03 86 | 97.64 161 |
|
ACMM | | 86.95 13 | 88.77 192 | 88.22 185 | 90.43 233 | 93.61 212 | 81.34 275 | 98.50 138 | 95.92 214 | 87.88 154 | 83.85 198 | 95.20 175 | 67.20 268 | 97.89 155 | 86.90 158 | 84.90 214 | 92.06 227 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
PAPM | | | 96.35 38 | 95.94 42 | 97.58 29 | 94.10 196 | 95.25 16 | 98.93 84 | 98.17 40 | 94.26 19 | 93.94 93 | 98.72 70 | 89.68 43 | 97.88 156 | 96.36 47 | 99.29 54 | 99.62 56 |
|
OPM-MVS | | | 89.76 175 | 89.15 166 | 91.57 212 | 90.53 254 | 85.58 234 | 98.11 181 | 95.93 213 | 92.88 42 | 86.05 182 | 96.47 157 | 67.06 270 | 97.87 157 | 89.29 137 | 86.08 207 | 91.26 247 |
|
CMPMVS | | 58.40 21 | 80.48 285 | 80.11 273 | 81.59 314 | 85.10 316 | 59.56 333 | 94.14 286 | 95.95 210 | 68.54 325 | 60.71 327 | 93.31 206 | 55.35 313 | 97.87 157 | 83.06 193 | 84.85 215 | 87.33 307 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
ACMP | | 87.39 10 | 88.71 194 | 88.24 184 | 90.12 239 | 93.91 205 | 81.06 280 | 98.50 138 | 95.67 231 | 89.43 108 | 80.37 242 | 95.55 169 | 65.67 278 | 97.83 159 | 90.55 121 | 84.51 216 | 91.47 240 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
tpmp4_e23 | | | 91.05 154 | 90.07 156 | 93.97 167 | 95.77 156 | 85.30 237 | 92.64 298 | 97.09 150 | 84.42 214 | 91.53 118 | 90.31 265 | 87.38 73 | 97.82 160 | 80.86 215 | 90.62 176 | 98.79 113 |
|
CLD-MVS | | | 91.06 153 | 90.71 149 | 92.10 198 | 94.05 199 | 86.10 219 | 99.55 22 | 96.29 192 | 94.16 20 | 84.70 190 | 97.17 130 | 69.62 249 | 97.82 160 | 94.74 75 | 86.08 207 | 92.39 212 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
EPP-MVSNet | | | 93.75 91 | 93.67 84 | 94.01 165 | 95.86 153 | 85.70 232 | 98.67 116 | 97.66 82 | 84.46 212 | 91.36 122 | 97.18 128 | 91.16 17 | 97.79 162 | 92.93 100 | 93.75 137 | 98.53 129 |
|
ACMH | | 83.09 17 | 84.60 249 | 82.61 256 | 90.57 229 | 93.18 223 | 82.94 259 | 96.27 244 | 94.92 266 | 81.01 270 | 72.61 295 | 93.61 200 | 56.54 307 | 97.79 162 | 74.31 274 | 81.07 238 | 90.99 258 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
LPG-MVS_test | | | 88.86 187 | 88.47 182 | 90.06 240 | 93.35 220 | 80.95 281 | 98.22 171 | 95.94 211 | 87.73 159 | 83.17 204 | 96.11 163 | 66.28 275 | 97.77 164 | 90.19 123 | 85.19 211 | 91.46 241 |
|
LGP-MVS_train | | | | | 90.06 240 | 93.35 220 | 80.95 281 | | 95.94 211 | 87.73 159 | 83.17 204 | 96.11 163 | 66.28 275 | 97.77 164 | 90.19 123 | 85.19 211 | 91.46 241 |
|
HQP4-MVS | | | | | | | | | | | 87.57 170 | | | 97.77 164 | | | 92.72 207 |
|
BH-untuned | | | 91.46 147 | 90.84 144 | 93.33 177 | 96.51 137 | 84.83 243 | 98.84 98 | 95.50 244 | 86.44 186 | 83.50 199 | 96.70 147 | 75.49 188 | 97.77 164 | 86.78 160 | 97.81 88 | 97.40 167 |
|
HQP-MVS | | | 91.50 145 | 91.23 131 | 92.29 195 | 93.95 200 | 86.39 208 | 99.16 58 | 96.37 184 | 93.92 22 | 87.57 170 | 96.67 148 | 73.34 219 | 97.77 164 | 93.82 87 | 86.29 202 | 92.72 207 |
|
HQP_MVS | | | 91.26 149 | 90.95 141 | 92.16 197 | 93.84 207 | 86.07 221 | 99.02 76 | 96.30 189 | 93.38 35 | 86.99 176 | 96.52 154 | 72.92 224 | 97.75 169 | 93.46 92 | 86.17 205 | 92.67 209 |
|
plane_prior5 | | | | | | | | | 96.30 189 | | | | | 97.75 169 | 93.46 92 | 86.17 205 | 92.67 209 |
|
tpmrst | | | 92.78 115 | 92.16 111 | 94.65 147 | 96.27 142 | 87.45 178 | 91.83 306 | 97.10 149 | 89.10 118 | 94.68 83 | 90.69 248 | 88.22 60 | 97.73 171 | 89.78 127 | 91.80 159 | 98.77 117 |
|
ACMH+ | | 83.78 15 | 84.21 254 | 82.56 258 | 89.15 259 | 93.73 211 | 79.16 288 | 96.43 239 | 94.28 280 | 81.09 269 | 74.00 286 | 94.03 187 | 54.58 315 | 97.67 172 | 76.10 255 | 78.81 247 | 90.63 272 |
|
XVG-ACMP-BASELINE | | | 85.86 235 | 84.95 229 | 88.57 268 | 89.90 266 | 77.12 303 | 94.30 283 | 95.60 240 | 87.40 166 | 82.12 226 | 92.99 215 | 53.42 319 | 97.66 173 | 85.02 172 | 83.83 221 | 90.92 260 |
|
USDC | | | 84.74 246 | 82.93 248 | 90.16 238 | 91.73 241 | 83.54 254 | 95.00 277 | 93.30 293 | 88.77 128 | 73.19 288 | 93.30 207 | 53.62 318 | 97.65 174 | 75.88 257 | 81.54 237 | 89.30 292 |
|
TESTMET0.1,1 | | | 93.82 89 | 93.26 89 | 95.49 124 | 95.21 169 | 90.25 124 | 99.15 62 | 97.54 106 | 89.18 115 | 91.79 113 | 94.87 178 | 89.13 46 | 97.63 175 | 86.21 161 | 96.29 113 | 98.60 124 |
|
LTVRE_ROB | | 81.71 19 | 84.59 250 | 82.72 255 | 90.18 237 | 92.89 226 | 83.18 257 | 93.15 295 | 94.74 268 | 78.99 283 | 75.14 281 | 92.69 217 | 65.64 279 | 97.63 175 | 69.46 301 | 81.82 236 | 89.74 288 |
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 |
MDTV_nov1_ep13 | | | | 90.47 154 | | 96.14 148 | 88.55 158 | 91.34 310 | 97.51 109 | 89.58 104 | 92.24 110 | 90.50 262 | 86.99 85 | 97.61 177 | 77.64 241 | 92.34 149 | |
|
tfpn_ndepth | | | 93.28 107 | 92.32 105 | 96.16 101 | 97.74 89 | 92.86 68 | 99.01 78 | 98.19 38 | 85.50 195 | 89.84 146 | 97.12 132 | 93.57 9 | 97.58 178 | 79.39 227 | 90.50 177 | 98.04 151 |
|
test-LLR | | | 93.11 112 | 92.68 99 | 94.40 153 | 94.94 184 | 87.27 187 | 99.15 62 | 97.25 133 | 90.21 91 | 91.57 115 | 94.04 185 | 84.89 112 | 97.58 178 | 85.94 164 | 96.13 114 | 98.36 141 |
|
test-mter | | | 93.27 108 | 92.89 96 | 94.40 153 | 94.94 184 | 87.27 187 | 99.15 62 | 97.25 133 | 88.95 122 | 91.57 115 | 94.04 185 | 88.03 65 | 97.58 178 | 85.94 164 | 96.13 114 | 98.36 141 |
|
TinyColmap | | | 80.42 286 | 77.94 286 | 87.85 283 | 92.09 234 | 78.58 295 | 93.74 289 | 89.94 333 | 74.99 305 | 69.77 301 | 91.78 228 | 46.09 329 | 97.58 178 | 65.17 313 | 77.89 251 | 87.38 306 |
|
Fast-Effi-MVS+ | | | 91.72 143 | 90.79 147 | 94.49 150 | 95.89 152 | 87.40 181 | 99.54 23 | 95.70 229 | 85.01 205 | 89.28 155 | 95.68 168 | 77.75 177 | 97.57 182 | 83.22 190 | 95.06 128 | 98.51 130 |
|
CostFormer | | | 92.89 114 | 92.48 104 | 94.12 161 | 94.99 182 | 85.89 226 | 92.89 297 | 97.00 159 | 86.98 175 | 95.00 79 | 90.78 243 | 90.05 39 | 97.51 183 | 92.92 101 | 91.73 161 | 98.96 98 |
|
HyFIR lowres test | | | 93.68 94 | 93.29 88 | 94.87 141 | 97.57 98 | 88.04 166 | 98.18 176 | 98.47 23 | 87.57 163 | 91.24 124 | 95.05 176 | 85.49 105 | 97.46 184 | 93.22 96 | 92.82 143 | 99.10 89 |
|
EPMVS | | | 92.59 125 | 91.59 125 | 95.59 118 | 97.22 110 | 90.03 133 | 91.78 307 | 98.04 47 | 90.42 87 | 91.66 114 | 90.65 254 | 86.49 93 | 97.46 184 | 81.78 207 | 96.31 111 | 99.28 79 |
|
dp | | | 90.16 168 | 88.83 172 | 94.14 160 | 96.38 140 | 86.42 206 | 91.57 308 | 97.06 153 | 84.76 209 | 88.81 157 | 90.19 273 | 84.29 118 | 97.43 186 | 75.05 268 | 91.35 168 | 98.56 128 |
|
conf0.01 | | | 92.06 138 | 90.99 134 | 95.24 131 | 96.84 122 | 91.39 91 | 98.31 159 | 98.20 31 | 83.57 233 | 88.08 162 | 97.34 116 | 91.05 20 | 97.40 187 | 75.80 258 | 89.74 187 | 96.94 179 |
|
conf0.002 | | | 92.06 138 | 90.99 134 | 95.24 131 | 96.84 122 | 91.39 91 | 98.31 159 | 98.20 31 | 83.57 233 | 88.08 162 | 97.34 116 | 91.05 20 | 97.40 187 | 75.80 258 | 89.74 187 | 96.94 179 |
|
thresconf0.02 | | | 92.14 131 | 90.99 134 | 95.58 119 | 96.84 122 | 91.39 91 | 98.31 159 | 98.20 31 | 83.57 233 | 88.08 162 | 97.34 116 | 91.05 20 | 97.40 187 | 75.80 258 | 89.74 187 | 97.94 155 |
|
tfpn_n400 | | | 92.14 131 | 90.99 134 | 95.58 119 | 96.84 122 | 91.39 91 | 98.31 159 | 98.20 31 | 83.57 233 | 88.08 162 | 97.34 116 | 91.05 20 | 97.40 187 | 75.80 258 | 89.74 187 | 97.94 155 |
|
tfpnconf | | | 92.14 131 | 90.99 134 | 95.58 119 | 96.84 122 | 91.39 91 | 98.31 159 | 98.20 31 | 83.57 233 | 88.08 162 | 97.34 116 | 91.05 20 | 97.40 187 | 75.80 258 | 89.74 187 | 97.94 155 |
|
tfpnview11 | | | 92.14 131 | 90.99 134 | 95.58 119 | 96.84 122 | 91.39 91 | 98.31 159 | 98.20 31 | 83.57 233 | 88.08 162 | 97.34 116 | 91.05 20 | 97.40 187 | 75.80 258 | 89.74 187 | 97.94 155 |
|
CHOSEN 280x420 | | | 96.80 26 | 96.85 18 | 96.66 78 | 97.85 87 | 94.42 41 | 94.76 279 | 98.36 25 | 92.50 48 | 95.62 69 | 97.52 110 | 97.92 1 | 97.38 193 | 98.31 21 | 98.80 73 | 98.20 148 |
|
ITE_SJBPF | | | | | 87.93 282 | 92.26 231 | 76.44 304 | | 93.47 292 | 87.67 162 | 79.95 247 | 95.49 172 | 56.50 308 | 97.38 193 | 75.24 267 | 82.33 234 | 89.98 285 |
|
MS-PatchMatch | | | 86.75 220 | 85.92 209 | 89.22 257 | 91.97 235 | 82.47 266 | 96.91 222 | 96.14 201 | 83.74 228 | 77.73 268 | 93.53 203 | 58.19 303 | 97.37 195 | 76.75 250 | 98.35 83 | 87.84 301 |
|
IS-MVSNet | | | 93.00 113 | 92.51 103 | 94.49 150 | 96.14 148 | 87.36 184 | 98.31 159 | 95.70 229 | 88.58 131 | 90.17 140 | 97.50 111 | 83.02 137 | 97.22 196 | 87.06 153 | 96.07 118 | 98.90 105 |
|
tfpn1000 | | | 92.67 122 | 91.64 124 | 95.78 113 | 97.61 97 | 92.34 77 | 98.69 111 | 98.18 39 | 84.15 217 | 88.80 158 | 96.99 139 | 93.56 10 | 97.21 197 | 76.56 252 | 90.19 179 | 97.77 160 |
|
tpm2 | | | 91.77 142 | 91.09 132 | 93.82 171 | 94.83 186 | 85.56 235 | 92.51 300 | 97.16 142 | 84.00 219 | 93.83 96 | 90.66 253 | 87.54 70 | 97.17 198 | 87.73 149 | 91.55 164 | 98.72 119 |
|
TDRefinement | | | 78.01 296 | 75.31 297 | 86.10 296 | 70.06 340 | 73.84 311 | 93.59 293 | 91.58 322 | 74.51 308 | 73.08 290 | 91.04 236 | 49.63 326 | 97.12 199 | 74.88 270 | 59.47 329 | 87.33 307 |
|
test_post | | | | | | | | | | | | 46.00 349 | 87.37 74 | 97.11 200 | | | |
|
PatchmatchNet | | | 92.05 140 | 91.04 133 | 95.06 137 | 96.17 146 | 89.04 149 | 91.26 311 | 97.26 132 | 89.56 106 | 90.64 132 | 90.56 260 | 88.35 59 | 97.11 200 | 79.53 224 | 96.07 118 | 99.03 92 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
VPA-MVSNet | | | 89.10 183 | 87.66 189 | 93.45 175 | 92.56 227 | 91.02 108 | 97.97 189 | 98.32 26 | 86.92 177 | 86.03 183 | 92.01 224 | 68.84 256 | 97.10 202 | 90.92 116 | 75.34 260 | 92.23 219 |
|
XXY-MVS | | | 87.75 201 | 86.02 207 | 92.95 185 | 90.46 255 | 89.70 139 | 97.71 199 | 95.90 218 | 84.02 218 | 80.95 238 | 94.05 184 | 67.51 266 | 97.10 202 | 85.16 170 | 78.41 248 | 92.04 228 |
|
ADS-MVSNet | | | 88.99 184 | 87.30 193 | 94.07 162 | 96.21 144 | 87.56 175 | 87.15 322 | 96.78 166 | 83.01 246 | 89.91 144 | 87.27 298 | 78.87 168 | 97.01 204 | 74.20 276 | 92.27 151 | 97.64 161 |
|
GA-MVS | | | 90.10 169 | 88.69 174 | 94.33 155 | 92.44 229 | 87.97 168 | 99.08 70 | 96.26 194 | 89.65 102 | 86.92 178 | 93.11 212 | 68.09 260 | 96.96 205 | 82.54 197 | 90.15 180 | 98.05 150 |
|
JIA-IIPM | | | 85.97 233 | 84.85 231 | 89.33 256 | 93.23 222 | 73.68 312 | 85.05 328 | 97.13 145 | 69.62 322 | 91.56 117 | 68.03 338 | 88.03 65 | 96.96 205 | 77.89 240 | 93.12 140 | 97.34 169 |
|
GG-mvs-BLEND | | | | | 96.98 56 | 96.53 135 | 94.81 28 | 87.20 321 | 97.74 74 | | 93.91 94 | 96.40 158 | 96.56 2 | 96.94 207 | 95.08 68 | 98.95 67 | 99.20 85 |
|
nrg030 | | | 90.23 165 | 88.87 170 | 94.32 156 | 91.53 243 | 93.54 53 | 98.79 104 | 95.89 220 | 88.12 148 | 84.55 192 | 94.61 182 | 78.80 170 | 96.88 208 | 92.35 106 | 75.21 261 | 92.53 211 |
|
Effi-MVS+-dtu | | | 89.97 173 | 90.68 150 | 87.81 284 | 95.15 174 | 71.98 318 | 97.87 194 | 95.40 252 | 91.92 61 | 87.57 170 | 91.44 232 | 74.27 206 | 96.84 209 | 89.45 130 | 93.10 141 | 94.60 200 |
|
gg-mvs-nofinetune | | | 90.00 172 | 87.71 188 | 96.89 65 | 96.15 147 | 94.69 32 | 85.15 327 | 97.74 74 | 68.32 326 | 92.97 105 | 60.16 340 | 96.10 3 | 96.84 209 | 93.89 83 | 98.87 68 | 99.14 87 |
|
patchmatchnet-post | | | | | | | | | | | | 84.86 307 | 88.73 52 | 96.81 211 | | | |
|
Test4 | | | 85.71 241 | 82.59 257 | 95.07 136 | 84.45 318 | 89.84 137 | 97.20 215 | 95.73 226 | 89.19 113 | 64.59 323 | 87.58 294 | 40.59 337 | 96.77 212 | 88.95 141 | 95.01 129 | 98.60 124 |
|
VPNet | | | 88.30 198 | 86.57 200 | 93.49 174 | 91.95 236 | 91.35 97 | 98.18 176 | 97.20 139 | 88.61 130 | 84.52 193 | 94.89 177 | 62.21 293 | 96.76 213 | 89.34 134 | 72.26 292 | 92.36 213 |
|
LF4IMVS | | | 81.94 269 | 81.17 268 | 84.25 305 | 87.23 311 | 68.87 326 | 93.35 294 | 91.93 318 | 83.35 241 | 75.40 280 | 93.00 214 | 49.25 327 | 96.65 214 | 78.88 232 | 78.11 250 | 87.22 310 |
|
v6 | | | 87.27 210 | 85.86 212 | 91.50 213 | 89.97 263 | 86.84 196 | 98.45 144 | 95.67 231 | 83.85 224 | 83.11 206 | 90.97 239 | 74.46 201 | 96.58 215 | 81.97 203 | 74.34 269 | 91.09 251 |
|
MVS-HIRNet | | | 79.01 291 | 75.13 298 | 90.66 228 | 93.82 209 | 81.69 271 | 85.16 326 | 93.75 287 | 54.54 338 | 74.17 285 | 59.15 342 | 57.46 305 | 96.58 215 | 63.74 314 | 94.38 132 | 93.72 203 |
|
v1neww | | | 87.29 208 | 85.88 210 | 91.50 213 | 90.07 256 | 86.87 192 | 98.45 144 | 95.66 234 | 83.84 225 | 83.07 207 | 90.99 237 | 74.58 198 | 96.56 217 | 81.96 204 | 74.33 270 | 91.07 254 |
|
v7new | | | 87.29 208 | 85.88 210 | 91.50 213 | 90.07 256 | 86.87 192 | 98.45 144 | 95.66 234 | 83.84 225 | 83.07 207 | 90.99 237 | 74.58 198 | 96.56 217 | 81.96 204 | 74.33 270 | 91.07 254 |
|
EI-MVSNet | | | 89.87 174 | 89.38 163 | 91.36 217 | 94.32 193 | 85.87 227 | 97.61 202 | 96.59 171 | 85.10 201 | 85.51 186 | 97.10 133 | 81.30 157 | 96.56 217 | 83.85 188 | 83.03 228 | 91.64 234 |
|
MVSTER | | | 92.71 120 | 92.32 105 | 93.86 169 | 97.29 108 | 92.95 66 | 99.01 78 | 96.59 171 | 90.09 97 | 85.51 186 | 94.00 189 | 94.61 5 | 96.56 217 | 90.77 120 | 83.03 228 | 92.08 226 |
|
v1 | | | 87.23 212 | 85.76 214 | 91.66 210 | 89.88 268 | 87.37 183 | 98.54 132 | 95.64 236 | 83.91 221 | 82.88 211 | 90.70 246 | 74.64 192 | 96.53 221 | 81.54 209 | 74.08 276 | 91.08 252 |
|
V42 | | | 87.00 216 | 85.68 219 | 90.98 223 | 89.91 264 | 86.08 220 | 98.32 158 | 95.61 239 | 83.67 231 | 82.72 215 | 90.67 251 | 74.00 212 | 96.53 221 | 81.94 206 | 74.28 273 | 90.32 277 |
|
Fast-Effi-MVS+-dtu | | | 88.84 188 | 88.59 179 | 89.58 251 | 93.44 218 | 78.18 298 | 98.65 118 | 94.62 273 | 88.46 134 | 84.12 196 | 95.37 174 | 68.91 254 | 96.52 223 | 82.06 201 | 91.70 162 | 94.06 201 |
|
PS-MVSNAJss | | | 89.54 178 | 89.05 167 | 91.00 222 | 88.77 291 | 84.36 247 | 97.39 205 | 95.97 207 | 88.47 132 | 81.88 232 | 93.80 195 | 82.48 144 | 96.50 224 | 89.34 134 | 83.34 226 | 92.15 223 |
|
v1141 | | | 87.23 212 | 85.75 216 | 91.67 209 | 89.88 268 | 87.43 180 | 98.52 134 | 95.62 237 | 83.91 221 | 82.83 213 | 90.69 248 | 74.70 191 | 96.49 225 | 81.53 210 | 74.08 276 | 91.07 254 |
|
divwei89l23v2f112 | | | 87.23 212 | 85.75 216 | 91.66 210 | 89.88 268 | 87.40 181 | 98.53 133 | 95.62 237 | 83.91 221 | 82.84 212 | 90.67 251 | 74.75 190 | 96.49 225 | 81.55 208 | 74.05 278 | 91.08 252 |
|
TAMVS | | | 92.62 124 | 92.09 115 | 94.20 159 | 94.10 196 | 87.68 172 | 98.41 150 | 96.97 160 | 87.53 164 | 89.74 147 | 96.04 165 | 84.77 115 | 96.49 225 | 88.97 140 | 92.31 150 | 98.42 133 |
|
tfpnnormal | | | 83.65 262 | 81.35 266 | 90.56 230 | 91.37 246 | 88.06 165 | 97.29 209 | 97.87 58 | 78.51 288 | 76.20 274 | 90.91 241 | 64.78 282 | 96.47 228 | 61.71 318 | 73.50 280 | 87.13 311 |
|
v2v482 | | | 87.27 210 | 85.76 214 | 91.78 208 | 89.59 279 | 87.58 174 | 98.56 130 | 95.54 241 | 84.53 211 | 82.51 219 | 91.78 228 | 73.11 223 | 96.47 228 | 82.07 200 | 74.14 275 | 91.30 246 |
|
MVP-Stereo | | | 86.61 224 | 85.83 213 | 88.93 263 | 88.70 293 | 83.85 252 | 96.07 256 | 94.41 278 | 82.15 259 | 75.64 279 | 91.96 226 | 67.65 265 | 96.45 230 | 77.20 245 | 98.72 75 | 86.51 314 |
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
Patchmatch-test | | | 86.25 230 | 84.06 242 | 92.82 186 | 94.42 191 | 82.88 263 | 82.88 337 | 94.23 281 | 71.58 313 | 79.39 254 | 90.62 256 | 89.00 49 | 96.42 231 | 63.03 315 | 91.37 167 | 99.16 86 |
|
v7 | | | 86.91 217 | 85.45 222 | 91.29 218 | 90.06 258 | 86.73 198 | 98.26 167 | 95.49 245 | 83.08 245 | 82.95 210 | 90.96 240 | 73.37 217 | 96.42 231 | 79.90 223 | 74.97 262 | 90.71 269 |
|
testing_2 | | | 80.92 282 | 77.24 290 | 91.98 200 | 78.88 332 | 87.83 169 | 93.96 288 | 95.72 227 | 84.27 216 | 56.20 333 | 80.42 324 | 38.64 339 | 96.40 233 | 87.20 152 | 79.85 243 | 91.72 232 |
|
v8 | | | 86.11 231 | 84.45 237 | 91.10 220 | 89.99 262 | 86.85 194 | 97.24 212 | 95.36 254 | 81.99 260 | 79.89 248 | 89.86 276 | 74.53 200 | 96.39 234 | 78.83 233 | 72.32 290 | 90.05 283 |
|
Vis-MVSNet (Re-imp) | | | 93.26 109 | 93.00 95 | 94.06 163 | 96.14 148 | 86.71 200 | 98.68 114 | 96.70 167 | 88.30 142 | 89.71 149 | 97.64 107 | 85.43 108 | 96.39 234 | 88.06 146 | 96.32 110 | 99.08 90 |
|
test_post1 | | | | | | | | 90.74 316 | | | | 41.37 352 | 85.38 109 | 96.36 236 | 83.16 191 | | |
|
v144192 | | | 86.40 227 | 84.89 230 | 90.91 224 | 89.48 284 | 85.59 233 | 98.21 174 | 95.43 251 | 82.45 256 | 82.62 217 | 90.58 259 | 72.79 227 | 96.36 236 | 78.45 235 | 74.04 279 | 90.79 264 |
|
v1144 | | | 86.83 219 | 85.31 224 | 91.40 216 | 89.75 273 | 87.21 189 | 98.31 159 | 95.45 249 | 83.22 242 | 82.70 216 | 90.78 243 | 73.36 218 | 96.36 236 | 79.49 225 | 74.69 266 | 90.63 272 |
|
jajsoiax | | | 87.35 206 | 86.51 202 | 89.87 243 | 87.75 305 | 81.74 270 | 97.03 220 | 95.98 205 | 88.47 132 | 80.15 245 | 93.80 195 | 61.47 295 | 96.36 236 | 89.44 132 | 84.47 218 | 91.50 239 |
|
CDS-MVSNet | | | 93.47 98 | 93.04 94 | 94.76 143 | 94.75 188 | 89.45 145 | 98.82 99 | 97.03 156 | 87.91 153 | 90.97 127 | 96.48 156 | 89.06 47 | 96.36 236 | 89.50 129 | 92.81 145 | 98.49 131 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
v7n | | | 84.42 253 | 82.75 254 | 89.43 255 | 88.15 298 | 81.86 269 | 96.75 229 | 95.67 231 | 80.53 273 | 78.38 266 | 89.43 281 | 69.89 246 | 96.35 241 | 73.83 282 | 72.13 294 | 90.07 282 |
|
UniMVSNet (Re) | | | 89.50 179 | 88.32 183 | 93.03 182 | 92.21 232 | 90.96 110 | 98.90 92 | 98.39 24 | 89.13 116 | 83.22 201 | 92.03 222 | 81.69 152 | 96.34 242 | 86.79 159 | 72.53 287 | 91.81 231 |
|
v1192 | | | 86.32 229 | 84.71 234 | 91.17 219 | 89.53 282 | 86.40 207 | 98.13 180 | 95.44 250 | 82.52 255 | 82.42 221 | 90.62 256 | 71.58 239 | 96.33 243 | 77.23 243 | 74.88 263 | 90.79 264 |
|
v52 | | | 84.19 256 | 82.92 249 | 88.01 280 | 87.64 307 | 79.92 285 | 96.23 247 | 95.32 257 | 79.87 278 | 78.51 263 | 89.05 284 | 69.50 252 | 96.32 244 | 77.95 239 | 72.24 293 | 87.79 304 |
|
V4 | | | 84.20 255 | 82.92 249 | 88.02 279 | 87.59 308 | 79.91 286 | 96.21 252 | 95.36 254 | 79.88 277 | 78.51 263 | 89.00 285 | 69.52 251 | 96.32 244 | 77.96 238 | 72.29 291 | 87.83 303 |
|
v148 | | | 86.38 228 | 85.06 226 | 90.37 235 | 89.47 285 | 84.10 249 | 98.52 134 | 95.48 246 | 83.80 227 | 80.93 239 | 90.22 270 | 74.60 196 | 96.31 246 | 80.92 213 | 71.55 298 | 90.69 270 |
|
mvs_tets | | | 87.09 215 | 86.22 205 | 89.71 247 | 87.87 301 | 81.39 274 | 96.73 230 | 95.90 218 | 88.19 146 | 79.99 246 | 93.61 200 | 59.96 301 | 96.31 246 | 89.40 133 | 84.34 219 | 91.43 243 |
|
v1240 | | | 85.77 239 | 84.11 241 | 90.73 227 | 89.26 287 | 85.15 241 | 97.88 193 | 95.23 263 | 81.89 263 | 82.16 225 | 90.55 261 | 69.60 250 | 96.31 246 | 75.59 266 | 74.87 264 | 90.72 268 |
|
v1921920 | | | 86.02 232 | 84.44 238 | 90.77 226 | 89.32 286 | 85.20 238 | 98.10 182 | 95.35 256 | 82.19 258 | 82.25 224 | 90.71 245 | 70.73 242 | 96.30 249 | 76.85 249 | 74.49 267 | 90.80 263 |
|
v10 | | | 85.73 240 | 84.01 243 | 90.87 225 | 90.03 259 | 86.73 198 | 97.20 215 | 95.22 264 | 81.25 268 | 79.85 249 | 89.75 277 | 73.30 222 | 96.28 250 | 76.87 247 | 72.64 286 | 89.61 290 |
|
v748 | | | 83.84 261 | 82.31 259 | 88.41 273 | 87.65 306 | 79.10 290 | 96.66 232 | 95.51 243 | 80.09 276 | 77.65 269 | 88.53 289 | 69.81 247 | 96.23 251 | 75.67 265 | 69.25 303 | 89.91 286 |
|
EG-PatchMatch MVS | | | 79.92 287 | 77.59 287 | 86.90 291 | 87.06 312 | 77.90 302 | 96.20 253 | 94.06 284 | 74.61 307 | 66.53 321 | 88.76 287 | 40.40 338 | 96.20 252 | 67.02 307 | 83.66 224 | 86.61 312 |
|
FIs | | | 90.70 161 | 89.87 158 | 93.18 179 | 92.29 230 | 91.12 103 | 98.17 179 | 98.25 28 | 89.11 117 | 83.44 200 | 94.82 179 | 82.26 148 | 96.17 253 | 87.76 148 | 82.76 230 | 92.25 217 |
|
mvs_anonymous | | | 92.50 126 | 91.65 123 | 95.06 137 | 96.60 134 | 89.64 140 | 97.06 219 | 96.44 182 | 86.64 181 | 84.14 195 | 93.93 191 | 82.49 143 | 96.17 253 | 91.47 111 | 96.08 117 | 99.35 71 |
|
OurMVSNet-221017-0 | | | 84.13 259 | 83.59 245 | 85.77 298 | 87.81 302 | 70.24 322 | 94.89 278 | 93.65 290 | 86.08 188 | 76.53 273 | 93.28 208 | 61.41 296 | 96.14 255 | 80.95 212 | 77.69 253 | 90.93 259 |
|
pm-mvs1 | | | 84.68 247 | 82.78 253 | 90.40 234 | 89.58 280 | 85.18 239 | 97.31 208 | 94.73 269 | 81.93 262 | 76.05 275 | 92.01 224 | 65.48 280 | 96.11 256 | 78.75 234 | 69.14 304 | 89.91 286 |
|
OpenMVS_ROB | | 73.86 20 | 77.99 297 | 75.06 299 | 86.77 292 | 83.81 322 | 77.94 301 | 96.38 241 | 91.53 323 | 67.54 328 | 68.38 305 | 87.13 301 | 43.94 331 | 96.08 257 | 55.03 329 | 81.83 235 | 86.29 318 |
|
pmmvs4 | | | 87.58 205 | 86.17 206 | 91.80 204 | 89.58 280 | 88.92 150 | 97.25 211 | 95.28 258 | 82.54 254 | 80.49 241 | 93.17 211 | 75.62 187 | 96.05 258 | 82.75 195 | 78.90 246 | 90.42 275 |
|
MVSFormer | | | 94.71 73 | 94.08 73 | 96.61 83 | 95.05 180 | 94.87 22 | 97.77 197 | 96.17 199 | 86.84 178 | 98.04 22 | 98.52 81 | 85.52 102 | 95.99 259 | 89.83 125 | 98.97 64 | 98.96 98 |
|
test_djsdf | | | 88.26 200 | 87.73 187 | 89.84 245 | 88.05 300 | 82.21 267 | 97.77 197 | 96.17 199 | 86.84 178 | 82.41 222 | 91.95 227 | 72.07 233 | 95.99 259 | 89.83 125 | 84.50 217 | 91.32 245 |
|
FC-MVSNet-test | | | 90.22 166 | 89.40 162 | 92.67 192 | 91.78 240 | 89.86 136 | 97.89 191 | 98.22 30 | 88.81 127 | 82.96 209 | 94.66 181 | 81.90 151 | 95.96 261 | 85.89 166 | 82.52 233 | 92.20 222 |
|
anonymousdsp | | | 86.69 221 | 85.75 216 | 89.53 252 | 86.46 314 | 82.94 259 | 96.39 240 | 95.71 228 | 83.97 220 | 79.63 251 | 90.70 246 | 68.85 255 | 95.94 262 | 86.01 162 | 84.02 220 | 89.72 289 |
|
UniMVSNet_NR-MVSNet | | | 89.60 177 | 88.55 180 | 92.75 189 | 92.17 233 | 90.07 130 | 98.74 106 | 98.15 42 | 88.37 140 | 83.21 202 | 93.98 190 | 82.86 139 | 95.93 263 | 86.95 156 | 72.47 288 | 92.25 217 |
|
DU-MVS | | | 88.83 189 | 87.51 190 | 92.79 187 | 91.46 244 | 90.07 130 | 98.71 107 | 97.62 92 | 88.87 126 | 83.21 202 | 93.68 197 | 74.63 194 | 95.93 263 | 86.95 156 | 72.47 288 | 92.36 213 |
|
WR-MVS | | | 88.54 196 | 87.22 196 | 92.52 193 | 91.93 238 | 89.50 143 | 98.56 130 | 97.84 60 | 86.99 173 | 81.87 233 | 93.81 194 | 74.25 208 | 95.92 265 | 85.29 169 | 74.43 268 | 92.12 224 |
|
Patchmatch-test1 | | | 90.10 169 | 88.61 176 | 94.57 149 | 94.95 183 | 88.83 151 | 96.26 245 | 97.21 138 | 90.06 100 | 90.03 142 | 90.68 250 | 66.61 273 | 95.83 266 | 77.31 242 | 94.36 133 | 99.05 91 |
|
NR-MVSNet | | | 87.74 203 | 86.00 208 | 92.96 184 | 91.46 244 | 90.68 118 | 96.65 233 | 97.42 123 | 88.02 149 | 73.42 287 | 93.68 197 | 77.31 179 | 95.83 266 | 84.26 179 | 71.82 297 | 92.36 213 |
|
pmmvs6 | | | 79.90 288 | 77.31 289 | 87.67 285 | 84.17 320 | 78.13 299 | 95.86 265 | 93.68 289 | 67.94 327 | 72.67 294 | 89.62 279 | 50.98 324 | 95.75 268 | 74.80 272 | 66.04 311 | 89.14 295 |
|
EPNet_dtu | | | 92.28 128 | 92.15 112 | 92.70 190 | 97.29 108 | 84.84 242 | 98.64 120 | 97.82 62 | 92.91 40 | 93.02 104 | 97.02 137 | 85.48 107 | 95.70 269 | 72.25 295 | 94.89 130 | 97.55 166 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
tpm | | | 89.67 176 | 88.95 169 | 91.82 203 | 92.54 228 | 81.43 272 | 92.95 296 | 95.92 214 | 87.81 155 | 90.50 134 | 89.44 280 | 84.99 110 | 95.65 270 | 83.67 189 | 82.71 231 | 98.38 138 |
|
IterMVS-LS | | | 88.34 197 | 87.44 191 | 91.04 221 | 94.10 196 | 85.85 229 | 98.10 182 | 95.48 246 | 85.12 200 | 82.03 230 | 91.21 234 | 81.35 156 | 95.63 271 | 83.86 187 | 75.73 258 | 91.63 235 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
SixPastTwentyTwo | | | 82.63 264 | 81.58 264 | 85.79 297 | 88.12 299 | 71.01 321 | 95.17 276 | 92.54 309 | 84.33 215 | 72.93 292 | 92.08 221 | 60.41 300 | 95.61 272 | 74.47 273 | 74.15 274 | 90.75 267 |
|
pmmvs5 | | | 85.87 234 | 84.40 240 | 90.30 236 | 88.53 295 | 84.23 248 | 98.60 126 | 93.71 288 | 81.53 266 | 80.29 243 | 92.02 223 | 64.51 283 | 95.52 273 | 82.04 202 | 78.34 249 | 91.15 249 |
|
lessismore_v0 | | | | | 85.08 300 | 85.59 315 | 69.28 325 | | 90.56 328 | | 67.68 314 | 90.21 271 | 54.21 317 | 95.46 274 | 73.88 280 | 62.64 317 | 90.50 274 |
|
TranMVSNet+NR-MVSNet | | | 87.75 201 | 86.31 204 | 92.07 199 | 90.81 251 | 88.56 157 | 98.33 156 | 97.18 140 | 87.76 156 | 81.87 233 | 93.90 192 | 72.45 228 | 95.43 275 | 83.13 192 | 71.30 300 | 92.23 219 |
|
Baseline_NR-MVSNet | | | 85.83 236 | 84.82 232 | 88.87 264 | 88.73 292 | 83.34 255 | 98.63 121 | 91.66 320 | 80.41 275 | 82.44 220 | 91.35 233 | 74.63 194 | 95.42 276 | 84.13 181 | 71.39 299 | 87.84 301 |
|
FMVSNet3 | | | 88.81 191 | 87.08 198 | 93.99 166 | 96.52 136 | 94.59 37 | 98.08 184 | 96.20 197 | 85.85 189 | 82.12 226 | 91.60 231 | 74.05 211 | 95.40 277 | 79.04 229 | 80.24 239 | 91.99 229 |
|
WR-MVS_H | | | 86.53 226 | 85.49 221 | 89.66 250 | 91.04 249 | 83.31 256 | 97.53 204 | 98.20 31 | 84.95 206 | 79.64 250 | 90.90 242 | 78.01 176 | 95.33 278 | 76.29 254 | 72.81 284 | 90.35 276 |
|
FMVSNet2 | | | 86.90 218 | 84.79 233 | 93.24 178 | 95.11 177 | 92.54 75 | 97.67 200 | 95.86 222 | 82.94 248 | 80.55 240 | 91.17 235 | 62.89 290 | 95.29 279 | 77.23 243 | 79.71 245 | 91.90 230 |
|
CP-MVSNet | | | 86.54 225 | 85.45 222 | 89.79 246 | 91.02 250 | 82.78 265 | 97.38 207 | 97.56 102 | 85.37 197 | 79.53 253 | 93.03 213 | 71.86 236 | 95.25 280 | 79.92 222 | 73.43 282 | 91.34 244 |
|
TransMVSNet (Re) | | | 81.97 268 | 79.61 277 | 89.08 260 | 89.70 275 | 84.01 250 | 97.26 210 | 91.85 319 | 78.84 284 | 73.07 291 | 91.62 230 | 67.17 269 | 95.21 281 | 67.50 305 | 59.46 330 | 88.02 300 |
|
PS-CasMVS | | | 85.81 237 | 84.58 236 | 89.49 254 | 90.77 252 | 82.11 268 | 97.20 215 | 97.36 129 | 84.83 208 | 79.12 257 | 92.84 216 | 67.42 267 | 95.16 282 | 78.39 236 | 73.25 283 | 91.21 248 |
|
test_0402 | | | 78.81 293 | 76.33 295 | 86.26 294 | 91.18 247 | 78.44 297 | 95.88 263 | 91.34 324 | 68.55 324 | 70.51 299 | 89.91 275 | 52.65 320 | 94.99 283 | 47.14 335 | 79.78 244 | 85.34 328 |
|
GBi-Net | | | 86.67 222 | 84.96 227 | 91.80 204 | 95.11 177 | 88.81 152 | 96.77 226 | 95.25 259 | 82.94 248 | 82.12 226 | 90.25 267 | 62.89 290 | 94.97 284 | 79.04 229 | 80.24 239 | 91.62 236 |
|
test1 | | | 86.67 222 | 84.96 227 | 91.80 204 | 95.11 177 | 88.81 152 | 96.77 226 | 95.25 259 | 82.94 248 | 82.12 226 | 90.25 267 | 62.89 290 | 94.97 284 | 79.04 229 | 80.24 239 | 91.62 236 |
|
FMVSNet1 | | | 83.94 260 | 81.32 267 | 91.80 204 | 91.94 237 | 88.81 152 | 96.77 226 | 95.25 259 | 77.98 294 | 78.25 267 | 90.25 267 | 50.37 325 | 94.97 284 | 73.27 287 | 77.81 252 | 91.62 236 |
|
PEN-MVS | | | 85.21 244 | 83.93 244 | 89.07 261 | 89.89 267 | 81.31 276 | 97.09 218 | 97.24 135 | 84.45 213 | 78.66 259 | 92.68 218 | 68.44 258 | 94.87 287 | 75.98 256 | 70.92 301 | 91.04 257 |
|
PatchT | | | 85.44 242 | 83.19 246 | 92.22 196 | 93.13 224 | 83.00 258 | 83.80 335 | 96.37 184 | 70.62 316 | 90.55 133 | 79.63 329 | 84.81 114 | 94.87 287 | 58.18 327 | 91.59 163 | 98.79 113 |
|
CR-MVSNet | | | 88.83 189 | 87.38 192 | 93.16 180 | 93.47 215 | 86.24 213 | 84.97 329 | 94.20 282 | 88.92 125 | 90.76 130 | 86.88 302 | 84.43 116 | 94.82 289 | 70.64 300 | 92.17 155 | 98.41 134 |
|
RPMNet | | | 84.62 248 | 81.78 261 | 93.16 180 | 93.47 215 | 86.24 213 | 84.97 329 | 96.28 193 | 64.85 332 | 90.76 130 | 78.80 331 | 80.95 158 | 94.82 289 | 53.76 330 | 92.17 155 | 98.41 134 |
|
Patchmtry | | | 83.61 263 | 81.64 263 | 89.50 253 | 93.36 219 | 82.84 264 | 84.10 332 | 94.20 282 | 69.47 323 | 79.57 252 | 86.88 302 | 84.43 116 | 94.78 291 | 68.48 304 | 74.30 272 | 90.88 261 |
|
ambc | | | | | 79.60 316 | 72.76 338 | 56.61 339 | 76.20 341 | 92.01 317 | | 68.25 308 | 80.23 327 | 23.34 345 | 94.73 292 | 73.78 283 | 60.81 321 | 87.48 305 |
|
LCM-MVSNet-Re | | | 88.59 195 | 88.61 176 | 88.51 270 | 95.53 162 | 72.68 316 | 96.85 224 | 88.43 339 | 88.45 135 | 73.14 289 | 90.63 255 | 75.82 185 | 94.38 293 | 92.95 99 | 95.71 123 | 98.48 132 |
|
DTE-MVSNet | | | 84.14 258 | 82.80 252 | 88.14 278 | 88.95 289 | 79.87 287 | 96.81 225 | 96.24 195 | 83.50 239 | 77.60 270 | 92.52 220 | 67.89 264 | 94.24 294 | 72.64 294 | 69.05 305 | 90.32 277 |
|
N_pmnet | | | 70.19 309 | 69.87 308 | 71.12 324 | 88.24 297 | 30.63 355 | 95.85 266 | 28.70 356 | 70.18 320 | 68.73 303 | 86.55 304 | 64.04 285 | 93.81 295 | 53.12 331 | 73.46 281 | 88.94 296 |
|
UnsupCasMVSNet_bld | | | 73.85 305 | 70.14 307 | 84.99 301 | 79.44 330 | 75.73 305 | 88.53 320 | 95.24 262 | 70.12 321 | 61.94 326 | 74.81 334 | 41.41 335 | 93.62 296 | 68.65 303 | 51.13 341 | 85.62 325 |
|
K. test v3 | | | 81.04 280 | 79.77 274 | 84.83 302 | 87.41 309 | 70.23 323 | 95.60 272 | 93.93 285 | 83.70 230 | 67.51 317 | 89.35 282 | 55.76 309 | 93.58 297 | 76.67 251 | 68.03 308 | 90.67 271 |
|
semantic-postprocess | | | | | 89.00 262 | 93.46 217 | 82.90 261 | | 94.70 270 | 85.02 204 | 78.62 260 | 90.35 263 | 66.63 272 | 93.33 298 | 79.38 228 | 77.36 255 | 90.76 266 |
|
IterMVS | | | 85.81 237 | 84.67 235 | 89.22 257 | 93.51 214 | 83.67 253 | 96.32 243 | 94.80 267 | 85.09 202 | 78.69 258 | 90.17 274 | 66.57 274 | 93.17 299 | 79.48 226 | 77.42 254 | 90.81 262 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
v18 | | | 82.00 267 | 79.76 275 | 88.72 265 | 90.03 259 | 86.81 197 | 96.17 254 | 93.12 294 | 78.70 285 | 68.39 304 | 82.10 311 | 74.64 192 | 93.00 300 | 74.21 275 | 60.45 323 | 86.35 315 |
|
v16 | | | 81.90 270 | 79.65 276 | 88.65 266 | 90.02 261 | 86.66 201 | 96.01 258 | 93.07 296 | 78.53 287 | 68.27 306 | 82.05 312 | 74.39 204 | 92.96 301 | 74.02 279 | 60.48 322 | 86.33 317 |
|
v17 | | | 81.87 272 | 79.61 277 | 88.64 267 | 89.91 264 | 86.64 202 | 96.01 258 | 93.08 295 | 78.54 286 | 68.27 306 | 81.96 313 | 74.44 202 | 92.95 302 | 74.03 278 | 60.22 325 | 86.34 316 |
|
CVMVSNet | | | 90.30 164 | 90.91 142 | 88.46 271 | 94.32 193 | 73.58 313 | 97.61 202 | 97.59 95 | 90.16 96 | 88.43 160 | 97.10 133 | 76.83 182 | 92.86 303 | 82.64 196 | 93.54 139 | 98.93 103 |
|
PM-MVS | | | 74.88 303 | 72.85 304 | 80.98 315 | 78.98 331 | 64.75 328 | 90.81 314 | 85.77 343 | 80.95 271 | 68.23 309 | 82.81 308 | 29.08 343 | 92.84 304 | 76.54 253 | 62.46 318 | 85.36 327 |
|
v15 | | | 81.62 273 | 79.32 280 | 88.52 269 | 89.80 271 | 86.56 203 | 95.83 267 | 92.96 299 | 78.50 289 | 67.88 310 | 81.68 315 | 74.22 209 | 92.82 305 | 73.46 285 | 59.55 326 | 86.18 320 |
|
MIMVSNet | | | 84.48 252 | 81.83 260 | 92.42 194 | 91.73 241 | 87.36 184 | 85.52 325 | 94.42 277 | 81.40 267 | 81.91 231 | 87.58 294 | 51.92 321 | 92.81 306 | 73.84 281 | 88.15 196 | 97.08 176 |
|
V9 | | | 81.46 276 | 79.15 282 | 88.39 275 | 89.75 273 | 86.17 217 | 95.62 271 | 92.92 301 | 78.22 291 | 67.65 315 | 81.64 316 | 73.95 213 | 92.80 307 | 73.15 289 | 59.43 331 | 86.21 319 |
|
ADS-MVSNet2 | | | 87.62 204 | 86.88 199 | 89.86 244 | 96.21 144 | 79.14 289 | 87.15 322 | 92.99 297 | 83.01 246 | 89.91 144 | 87.27 298 | 78.87 168 | 92.80 307 | 74.20 276 | 92.27 151 | 97.64 161 |
|
V14 | | | 81.55 275 | 79.26 281 | 88.42 272 | 89.80 271 | 86.33 211 | 95.72 270 | 92.96 299 | 78.35 290 | 67.82 311 | 81.70 314 | 74.13 210 | 92.78 309 | 73.32 286 | 59.50 328 | 86.16 322 |
|
v13 | | | 81.30 279 | 78.99 285 | 88.25 277 | 89.61 278 | 85.87 227 | 95.39 274 | 92.90 303 | 77.93 298 | 67.45 319 | 81.52 318 | 73.66 215 | 92.75 310 | 72.91 292 | 59.53 327 | 86.14 323 |
|
v12 | | | 81.37 278 | 79.05 283 | 88.33 276 | 89.68 276 | 86.05 223 | 95.48 273 | 92.92 301 | 78.08 292 | 67.55 316 | 81.58 317 | 73.75 214 | 92.75 310 | 73.05 290 | 59.37 332 | 86.18 320 |
|
LP | | | 77.80 299 | 74.39 301 | 88.01 280 | 91.93 238 | 79.02 291 | 80.88 339 | 92.90 303 | 65.43 330 | 72.00 296 | 81.29 321 | 65.78 277 | 92.73 312 | 43.76 340 | 75.58 259 | 92.27 216 |
|
v11 | | | 81.38 277 | 79.03 284 | 88.41 273 | 89.68 276 | 86.43 205 | 95.74 269 | 92.82 308 | 78.03 293 | 67.74 312 | 81.45 319 | 73.33 221 | 92.69 313 | 72.23 296 | 60.27 324 | 86.11 324 |
|
DeepMVS_CX | | | | | 76.08 320 | 90.74 253 | 51.65 343 | | 90.84 326 | 86.47 185 | 57.89 331 | 87.98 290 | 35.88 341 | 92.60 314 | 65.77 312 | 65.06 313 | 83.97 331 |
|
Patchmatch-RL test | | | 81.90 270 | 80.13 271 | 87.23 289 | 80.71 327 | 70.12 324 | 84.07 333 | 88.19 340 | 83.16 244 | 70.57 297 | 82.18 310 | 87.18 80 | 92.59 315 | 82.28 199 | 62.78 316 | 98.98 96 |
|
pmmvs-eth3d | | | 78.71 294 | 76.16 296 | 86.38 293 | 80.25 328 | 81.19 278 | 94.17 285 | 92.13 315 | 77.97 295 | 66.90 320 | 82.31 309 | 55.76 309 | 92.56 316 | 73.63 284 | 62.31 319 | 85.38 326 |
|
MDA-MVSNet-bldmvs | | | 77.82 298 | 74.75 300 | 87.03 290 | 88.33 296 | 78.52 296 | 96.34 242 | 92.85 305 | 75.57 304 | 48.87 338 | 87.89 291 | 57.32 306 | 92.49 317 | 60.79 320 | 64.80 314 | 90.08 281 |
|
new_pmnet | | | 76.02 301 | 73.71 302 | 82.95 308 | 83.88 321 | 72.85 315 | 91.26 311 | 92.26 312 | 70.44 318 | 62.60 325 | 81.37 320 | 47.64 328 | 92.32 318 | 61.85 317 | 72.10 295 | 83.68 332 |
|
UnsupCasMVSNet_eth | | | 78.90 292 | 76.67 294 | 85.58 299 | 82.81 324 | 74.94 307 | 91.98 305 | 96.31 188 | 84.64 210 | 65.84 322 | 87.71 293 | 51.33 322 | 92.23 319 | 72.89 293 | 56.50 334 | 89.56 291 |
|
Anonymous20231206 | | | 80.76 283 | 79.42 279 | 84.79 303 | 84.78 317 | 72.98 314 | 96.53 235 | 92.97 298 | 79.56 280 | 74.33 283 | 88.83 286 | 61.27 297 | 92.15 320 | 60.59 321 | 75.92 257 | 89.24 294 |
|
MDA-MVSNet_test_wron | | | 79.65 289 | 77.05 291 | 87.45 287 | 87.79 304 | 80.13 283 | 96.25 246 | 94.44 275 | 73.87 310 | 51.80 336 | 87.47 297 | 68.04 261 | 92.12 321 | 66.02 310 | 67.79 309 | 90.09 280 |
|
YYNet1 | | | 79.64 290 | 77.04 292 | 87.43 288 | 87.80 303 | 79.98 284 | 96.23 247 | 94.44 275 | 73.83 311 | 51.83 335 | 87.53 296 | 67.96 263 | 92.07 322 | 66.00 311 | 67.75 310 | 90.23 279 |
|
test0.0.03 1 | | | 88.96 185 | 88.61 176 | 90.03 242 | 91.09 248 | 84.43 246 | 98.97 82 | 97.02 157 | 90.21 91 | 80.29 243 | 96.31 162 | 84.89 112 | 91.93 323 | 72.98 291 | 85.70 210 | 93.73 202 |
|
testpf | | | 80.59 284 | 80.13 271 | 81.97 312 | 94.25 195 | 71.65 319 | 60.37 347 | 95.46 248 | 70.99 315 | 76.97 272 | 87.74 292 | 73.58 216 | 91.67 324 | 76.86 248 | 84.97 213 | 82.60 335 |
|
testgi | | | 82.29 265 | 81.00 269 | 86.17 295 | 87.24 310 | 74.84 308 | 97.39 205 | 91.62 321 | 88.63 129 | 75.85 278 | 95.42 173 | 46.07 330 | 91.55 325 | 66.87 309 | 79.94 242 | 92.12 224 |
|
EU-MVSNet | | | 84.19 256 | 84.42 239 | 83.52 307 | 88.64 294 | 67.37 327 | 96.04 257 | 95.76 224 | 85.29 198 | 78.44 265 | 93.18 210 | 70.67 243 | 91.48 326 | 75.79 264 | 75.98 256 | 91.70 233 |
|
Anonymous20231211 | | | 67.10 310 | 63.29 313 | 78.54 317 | 75.68 334 | 60.00 332 | 92.05 304 | 88.86 337 | 49.84 339 | 59.35 330 | 78.48 332 | 26.15 344 | 90.76 327 | 45.96 337 | 53.24 338 | 84.88 330 |
|
DSMNet-mixed | | | 81.60 274 | 81.43 265 | 82.10 310 | 84.36 319 | 60.79 331 | 93.63 292 | 86.74 341 | 79.00 282 | 79.32 255 | 87.15 300 | 63.87 286 | 89.78 328 | 66.89 308 | 91.92 157 | 95.73 196 |
|
FMVSNet5 | | | 82.29 265 | 80.54 270 | 87.52 286 | 93.79 210 | 84.01 250 | 93.73 290 | 92.47 310 | 76.92 301 | 74.27 284 | 86.15 306 | 63.69 287 | 89.24 329 | 69.07 302 | 74.79 265 | 89.29 293 |
|
new-patchmatchnet | | | 74.80 304 | 72.40 305 | 81.99 311 | 78.36 333 | 72.20 317 | 94.44 280 | 92.36 311 | 77.06 300 | 63.47 324 | 79.98 328 | 51.04 323 | 88.85 330 | 60.53 322 | 54.35 336 | 84.92 329 |
|
pmmvs3 | | | 72.86 306 | 69.76 309 | 82.17 309 | 73.86 335 | 74.19 310 | 94.20 284 | 89.01 336 | 64.23 333 | 67.72 313 | 80.91 323 | 41.48 334 | 88.65 331 | 62.40 316 | 54.02 337 | 83.68 332 |
|
MIMVSNet1 | | | 75.92 302 | 73.30 303 | 83.81 306 | 81.29 325 | 75.57 306 | 92.26 303 | 92.05 316 | 73.09 312 | 67.48 318 | 86.18 305 | 40.87 336 | 87.64 332 | 55.78 328 | 70.68 302 | 88.21 297 |
|
test20.03 | | | 78.51 295 | 77.48 288 | 81.62 313 | 83.07 323 | 71.03 320 | 96.11 255 | 92.83 306 | 81.66 265 | 69.31 302 | 89.68 278 | 57.53 304 | 87.29 333 | 58.65 326 | 68.47 306 | 86.53 313 |
|
1111 | | | 72.28 307 | 71.36 306 | 75.02 322 | 73.04 336 | 57.38 337 | 92.30 301 | 90.22 331 | 62.27 334 | 59.46 328 | 80.36 325 | 76.23 183 | 87.07 334 | 44.29 338 | 64.08 315 | 80.59 336 |
|
.test1245 | | | 61.50 313 | 64.44 312 | 52.65 337 | 73.04 336 | 57.38 337 | 92.30 301 | 90.22 331 | 62.27 334 | 59.46 328 | 80.36 325 | 76.23 183 | 87.07 334 | 44.29 338 | 1.80 352 | 13.50 352 |
|
testus | | | 77.11 300 | 76.95 293 | 77.58 319 | 80.02 329 | 58.93 335 | 97.78 195 | 90.48 329 | 79.68 279 | 72.84 293 | 90.61 258 | 37.72 340 | 86.57 336 | 60.28 323 | 83.18 227 | 87.23 309 |
|
test2356 | | | 80.96 281 | 81.77 262 | 78.52 318 | 81.02 326 | 62.33 329 | 98.22 171 | 94.49 274 | 79.38 281 | 74.56 282 | 90.34 264 | 70.65 245 | 85.10 337 | 60.83 319 | 86.42 201 | 88.14 298 |
|
no-one | | | 56.69 317 | 51.89 320 | 71.08 325 | 59.35 348 | 58.65 336 | 83.78 336 | 84.81 346 | 61.73 336 | 36.46 344 | 56.52 344 | 18.15 350 | 84.78 338 | 47.03 336 | 19.19 346 | 69.81 342 |
|
test1235678 | | | 71.07 308 | 69.53 310 | 75.71 321 | 71.87 339 | 55.27 341 | 94.32 281 | 90.76 327 | 70.23 319 | 57.61 332 | 79.06 330 | 43.13 332 | 83.72 339 | 50.48 332 | 68.30 307 | 88.14 298 |
|
test12356 | | | 66.36 311 | 65.12 311 | 70.08 327 | 66.92 341 | 50.46 344 | 89.96 318 | 88.58 338 | 66.00 329 | 53.38 334 | 78.13 333 | 32.89 342 | 82.87 340 | 48.36 334 | 61.87 320 | 76.92 337 |
|
LCM-MVSNet | | | 60.07 315 | 56.37 316 | 71.18 323 | 54.81 350 | 48.67 345 | 82.17 338 | 89.48 335 | 37.95 342 | 49.13 337 | 69.12 335 | 13.75 354 | 81.76 341 | 59.28 324 | 51.63 340 | 83.10 334 |
|
Gipuma | | | 54.77 318 | 52.22 319 | 62.40 331 | 86.50 313 | 59.37 334 | 50.20 348 | 90.35 330 | 36.52 344 | 41.20 342 | 49.49 346 | 18.33 349 | 81.29 342 | 32.10 346 | 65.34 312 | 46.54 348 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
PMMVS2 | | | 58.97 316 | 55.07 317 | 70.69 326 | 62.72 342 | 55.37 340 | 85.97 324 | 80.52 347 | 49.48 340 | 45.94 339 | 68.31 337 | 15.73 352 | 80.78 343 | 49.79 333 | 37.12 342 | 75.91 339 |
|
FPMVS | | | 61.57 312 | 60.32 314 | 65.34 329 | 60.14 346 | 42.44 349 | 91.02 313 | 89.72 334 | 44.15 341 | 42.63 341 | 80.93 322 | 19.02 347 | 80.59 344 | 42.50 341 | 72.76 285 | 73.00 340 |
|
testmv | | | 60.41 314 | 57.98 315 | 67.69 328 | 58.16 349 | 47.14 346 | 89.09 319 | 86.74 341 | 61.52 337 | 44.30 340 | 68.44 336 | 20.98 346 | 79.92 345 | 40.94 342 | 51.67 339 | 76.01 338 |
|
PMVS | | 41.42 23 | 45.67 322 | 42.50 323 | 55.17 335 | 34.28 354 | 32.37 353 | 66.24 345 | 78.71 349 | 30.72 346 | 22.04 350 | 59.59 341 | 4.59 356 | 77.85 346 | 27.49 347 | 58.84 333 | 55.29 346 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
wuykxyi23d | | | 43.53 323 | 37.95 326 | 60.27 332 | 45.36 352 | 44.79 347 | 68.27 344 | 74.26 351 | 33.48 345 | 18.21 352 | 40.16 353 | 3.64 357 | 71.01 347 | 38.85 343 | 19.31 345 | 65.02 343 |
|
PNet_i23d | | | 48.05 321 | 44.98 322 | 57.28 333 | 60.15 344 | 42.39 350 | 80.85 340 | 73.14 352 | 36.78 343 | 27.46 346 | 56.66 343 | 6.38 355 | 68.34 348 | 36.65 344 | 26.72 344 | 61.10 344 |
|
ANet_high | | | 50.71 320 | 46.17 321 | 64.33 330 | 44.27 353 | 52.30 342 | 76.13 342 | 78.73 348 | 64.95 331 | 27.37 347 | 55.23 345 | 14.61 353 | 67.74 349 | 36.01 345 | 18.23 348 | 72.95 341 |
|
tmp_tt | | | 53.66 319 | 52.86 318 | 56.05 334 | 32.75 355 | 41.97 351 | 73.42 343 | 76.12 350 | 21.91 350 | 39.68 343 | 96.39 160 | 42.59 333 | 65.10 350 | 78.00 237 | 14.92 350 | 61.08 345 |
|
MVE | | 44.00 22 | 41.70 324 | 37.64 327 | 53.90 336 | 49.46 351 | 43.37 348 | 65.09 346 | 66.66 353 | 26.19 349 | 25.77 349 | 48.53 347 | 3.58 359 | 63.35 351 | 26.15 348 | 27.28 343 | 54.97 347 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
E-PMN | | | 41.02 325 | 40.93 324 | 41.29 338 | 61.97 343 | 33.83 352 | 84.00 334 | 65.17 354 | 27.17 347 | 27.56 345 | 46.72 348 | 17.63 351 | 60.41 352 | 19.32 349 | 18.82 347 | 29.61 349 |
|
EMVS | | | 39.96 326 | 39.88 325 | 40.18 339 | 59.57 347 | 32.12 354 | 84.79 331 | 64.57 355 | 26.27 348 | 26.14 348 | 44.18 351 | 18.73 348 | 59.29 353 | 17.03 350 | 17.67 349 | 29.12 350 |
|
wuyk23d | | | 16.71 330 | 16.73 332 | 16.65 341 | 60.15 344 | 25.22 356 | 41.24 349 | 5.17 357 | 6.56 351 | 5.48 354 | 3.61 355 | 3.64 357 | 22.72 354 | 15.20 351 | 9.52 351 | 1.99 354 |
|
test123 | | | 16.58 331 | 19.47 331 | 7.91 342 | 3.59 357 | 5.37 357 | 94.32 281 | 1.39 359 | 2.49 353 | 13.98 353 | 44.60 350 | 2.91 360 | 2.65 355 | 11.35 353 | 0.57 354 | 15.70 351 |
|
testmvs | | | 18.81 329 | 23.05 330 | 6.10 343 | 4.48 356 | 2.29 358 | 97.78 195 | 3.00 358 | 3.27 352 | 18.60 351 | 62.71 339 | 1.53 361 | 2.49 356 | 14.26 352 | 1.80 352 | 13.50 352 |
|
cdsmvs_eth3d_5k | | | 22.52 328 | 30.03 329 | 0.00 344 | 0.00 358 | 0.00 359 | 0.00 350 | 97.17 141 | 0.00 354 | 0.00 355 | 98.77 64 | 74.35 205 | 0.00 357 | 0.00 354 | 0.00 355 | 0.00 355 |
|
pcd_1.5k_mvsjas | | | 6.87 333 | 9.16 334 | 0.00 344 | 0.00 358 | 0.00 359 | 0.00 350 | 0.00 360 | 0.00 354 | 0.00 355 | 0.00 356 | 82.48 144 | 0.00 357 | 0.00 354 | 0.00 355 | 0.00 355 |
|
pcd1.5k->3k | | | 35.91 327 | 37.64 327 | 30.74 340 | 89.49 283 | 0.00 359 | 0.00 350 | 96.36 187 | 0.00 354 | 0.00 355 | 0.00 356 | 69.17 253 | 0.00 357 | 0.00 354 | 83.71 223 | 92.21 221 |
|
sosnet-low-res | | | 0.00 334 | 0.00 335 | 0.00 344 | 0.00 358 | 0.00 359 | 0.00 350 | 0.00 360 | 0.00 354 | 0.00 355 | 0.00 356 | 0.00 362 | 0.00 357 | 0.00 354 | 0.00 355 | 0.00 355 |
|
sosnet | | | 0.00 334 | 0.00 335 | 0.00 344 | 0.00 358 | 0.00 359 | 0.00 350 | 0.00 360 | 0.00 354 | 0.00 355 | 0.00 356 | 0.00 362 | 0.00 357 | 0.00 354 | 0.00 355 | 0.00 355 |
|
uncertanet | | | 0.00 334 | 0.00 335 | 0.00 344 | 0.00 358 | 0.00 359 | 0.00 350 | 0.00 360 | 0.00 354 | 0.00 355 | 0.00 356 | 0.00 362 | 0.00 357 | 0.00 354 | 0.00 355 | 0.00 355 |
|
Regformer | | | 0.00 334 | 0.00 335 | 0.00 344 | 0.00 358 | 0.00 359 | 0.00 350 | 0.00 360 | 0.00 354 | 0.00 355 | 0.00 356 | 0.00 362 | 0.00 357 | 0.00 354 | 0.00 355 | 0.00 355 |
|
ab-mvs-re | | | 8.21 332 | 10.94 333 | 0.00 344 | 0.00 358 | 0.00 359 | 0.00 350 | 0.00 360 | 0.00 354 | 0.00 355 | 98.50 83 | 0.00 362 | 0.00 357 | 0.00 354 | 0.00 355 | 0.00 355 |
|
uanet | | | 0.00 334 | 0.00 335 | 0.00 344 | 0.00 358 | 0.00 359 | 0.00 350 | 0.00 360 | 0.00 354 | 0.00 355 | 0.00 356 | 0.00 362 | 0.00 357 | 0.00 354 | 0.00 355 | 0.00 355 |
|
GSMVS | | | | | | | | | | | | | | | | | 98.84 108 |
|
test_part2 | | | | | | 99.54 27 | 95.42 14 | | | | 98.13 16 | | | | | | |
|
test_part1 | | | | | | | | | 97.69 78 | | | | 93.96 6 | | | 99.83 12 | 99.90 9 |
|
sam_mvs1 | | | | | | | | | | | | | 88.39 58 | | | | 98.84 108 |
|
sam_mvs | | | | | | | | | | | | | 87.08 81 | | | | |
|
MTGPA | | | | | | | | | 97.45 117 | | | | | | | | |
|
MTMP | | | | | | | | | 91.09 325 | | | | | | | | |
|
test9_res | | | | | | | | | | | | | | | 98.60 11 | 99.87 5 | 99.90 9 |
|
agg_prior2 | | | | | | | | | | | | | | | 97.84 27 | 99.87 5 | 99.91 8 |
|
test_prior4 | | | | | | | 92.00 79 | 99.41 38 | | | | | | | | | |
|
test_prior2 | | | | | | | | 99.57 19 | | 91.43 70 | 98.12 19 | 98.97 47 | 90.43 36 | | 98.33 19 | 99.81 15 | |
|
æ–°å‡ ä½•2 | | | | | | | | 98.26 167 | | | | | | | | | |
|
旧先验1 | | | | | | 98.97 59 | 92.90 67 | | 97.74 74 | | | 99.15 26 | 91.05 20 | | | 99.33 52 | 99.60 58 |
|
原ACMM2 | | | | | | | | 98.69 111 | | | | | | | | | |
|
test222 | | | | | | 98.32 78 | 91.21 99 | 98.08 184 | 97.58 97 | 83.74 228 | 95.87 63 | 99.02 41 | 86.74 87 | | | 99.64 30 | 99.81 22 |
|
segment_acmp | | | | | | | | | | | | | 90.56 35 | | | | |
|
testdata1 | | | | | | | | 97.89 191 | | 92.43 50 | | | | | | | |
|
plane_prior7 | | | | | | 93.84 207 | 85.73 231 | | | | | | | | | | |
|
plane_prior6 | | | | | | 93.92 204 | 86.02 224 | | | | | | 72.92 224 | | | | |
|
plane_prior4 | | | | | | | | | | | | 96.52 154 | | | | | |
|
plane_prior3 | | | | | | | 85.91 225 | | | 93.65 30 | 86.99 176 | | | | | | |
|
plane_prior2 | | | | | | | | 99.02 76 | | 93.38 35 | | | | | | | |
|
plane_prior1 | | | | | | 93.90 206 | | | | | | | | | | | |
|
plane_prior | | | | | | | 86.07 221 | 99.14 65 | | 93.81 28 | | | | | | 86.26 204 | |
|
n2 | | | | | | | | | 0.00 360 | | | | | | | | |
|
nn | | | | | | | | | 0.00 360 | | | | | | | | |
|
door-mid | | | | | | | | | 84.90 345 | | | | | | | | |
|
test11 | | | | | | | | | 97.68 80 | | | | | | | | |
|
door | | | | | | | | | 85.30 344 | | | | | | | | |
|
HQP5-MVS | | | | | | | 86.39 208 | | | | | | | | | | |
|
HQP-NCC | | | | | | 93.95 200 | | 99.16 58 | | 93.92 22 | 87.57 170 | | | | | | |
|
ACMP_Plane | | | | | | 93.95 200 | | 99.16 58 | | 93.92 22 | 87.57 170 | | | | | | |
|
BP-MVS | | | | | | | | | | | | | | | 93.82 87 | | |
|
HQP3-MVS | | | | | | | | | 96.37 184 | | | | | | | 86.29 202 | |
|
HQP2-MVS | | | | | | | | | | | | | 73.34 219 | | | | |
|
NP-MVS | | | | | | 93.94 203 | 86.22 215 | | | | | 96.67 148 | | | | | |
|
MDTV_nov1_ep13_2view | | | | | | | 91.17 102 | 91.38 309 | | 87.45 165 | 93.08 102 | | 86.67 88 | | 87.02 155 | | 98.95 102 |
|
ACMMP++_ref | | | | | | | | | | | | | | | | 82.64 232 | |
|
ACMMP++ | | | | | | | | | | | | | | | | 83.83 221 | |
|
Test By Simon | | | | | | | | | | | | | 83.62 122 | | | | |
|