test_part3 | | | | | | | | 99.88 66 | | 96.14 43 | | 99.91 6 | | 100.00 1 | 99.99 1 | | |
|
ESAPD | | | 99.18 4 | 98.99 7 | 99.75 3 | 99.89 36 | 99.25 6 | 99.88 66 | 98.41 122 | 96.14 43 | 99.49 32 | 99.91 6 | 97.20 11 | 100.00 1 | 99.99 1 | 99.99 13 | 99.99 11 |
|
ACMMP_Plus | | | 98.49 35 | 98.14 42 | 99.54 17 | 99.66 66 | 98.62 40 | 99.85 87 | 98.37 131 | 94.68 77 | 99.53 28 | 99.83 36 | 92.87 98 | 100.00 1 | 98.66 59 | 99.84 60 | 99.99 11 |
|
MPTG | | | 98.33 44 | 98.00 47 | 99.30 37 | 99.85 40 | 97.93 66 | 99.80 100 | 98.28 140 | 95.76 52 | 97.18 112 | 99.88 11 | 92.74 102 | 100.00 1 | 98.67 56 | 99.88 56 | 99.99 11 |
|
MTAPA | | | 98.29 45 | 97.96 51 | 99.30 37 | 99.85 40 | 97.93 66 | 99.39 179 | 98.28 140 | 95.76 52 | 97.18 112 | 99.88 11 | 92.74 102 | 100.00 1 | 98.67 56 | 99.88 56 | 99.99 11 |
|
HFP-MVS | | | 98.56 29 | 98.37 31 | 99.14 51 | 99.96 8 | 97.43 83 | 99.95 31 | 98.61 76 | 94.77 73 | 99.31 45 | 99.85 20 | 94.22 68 | 100.00 1 | 98.70 54 | 99.98 25 | 99.98 43 |
|
region2R | | | 98.54 31 | 98.37 31 | 99.05 65 | 99.96 8 | 97.18 97 | 99.96 19 | 98.55 88 | 94.87 71 | 99.45 35 | 99.85 20 | 94.07 74 | 100.00 1 | 98.67 56 | 100.00 1 | 99.98 43 |
|
#test# | | | 98.59 27 | 98.41 26 | 99.14 51 | 99.96 8 | 97.43 83 | 99.95 31 | 98.61 76 | 95.00 68 | 99.31 45 | 99.85 20 | 94.22 68 | 100.00 1 | 98.78 51 | 99.98 25 | 99.98 43 |
|
HPM-MVS++ | | | 99.07 6 | 98.88 11 | 99.63 8 | 99.90 33 | 99.02 12 | 99.95 31 | 98.56 84 | 97.56 9 | 99.44 36 | 99.85 20 | 95.38 38 | 100.00 1 | 99.31 29 | 99.99 13 | 99.87 74 |
|
新几何1 | | | | | 99.42 29 | 99.75 55 | 98.27 56 | | 98.63 73 | 92.69 139 | 99.55 27 | 99.82 39 | 94.40 59 | 100.00 1 | 91.21 189 | 99.94 43 | 99.99 11 |
|
无先验 | | | | | | | | 99.49 167 | 98.71 61 | 93.46 117 | | | | 100.00 1 | 94.36 142 | | 99.99 11 |
|
1121 | | | 98.03 55 | 97.57 61 | 99.40 32 | 99.74 56 | 98.21 57 | 98.31 270 | 98.62 74 | 92.78 134 | 99.53 28 | 99.83 36 | 95.08 43 | 100.00 1 | 94.36 142 | 99.92 50 | 99.99 11 |
|
MSLP-MVS++ | | | 99.13 5 | 99.01 6 | 99.49 22 | 99.94 14 | 98.46 51 | 99.98 6 | 98.86 53 | 97.10 15 | 99.80 8 | 99.94 4 | 95.92 29 | 100.00 1 | 99.51 21 | 100.00 1 | 100.00 1 |
|
ACMMPR | | | 98.50 34 | 98.32 35 | 99.05 65 | 99.96 8 | 97.18 97 | 99.95 31 | 98.60 78 | 94.77 73 | 99.31 45 | 99.84 34 | 93.73 84 | 100.00 1 | 98.70 54 | 99.98 25 | 99.98 43 |
|
MP-MVS | | | 98.23 49 | 97.97 49 | 99.03 67 | 99.94 14 | 97.17 100 | 99.95 31 | 98.39 126 | 94.70 76 | 98.26 91 | 99.81 42 | 91.84 118 | 100.00 1 | 98.85 48 | 99.97 34 | 99.93 65 |
|
PGM-MVS | | | 98.34 43 | 98.13 43 | 98.99 71 | 99.92 27 | 97.00 102 | 99.75 116 | 99.50 21 | 93.90 105 | 99.37 43 | 99.76 55 | 93.24 94 | 100.00 1 | 97.75 90 | 99.96 36 | 99.98 43 |
|
MCST-MVS | | | 99.32 3 | 99.14 3 | 99.86 1 | 99.97 3 | 99.59 1 | 99.97 12 | 98.64 70 | 98.47 2 | 99.13 54 | 99.92 5 | 96.38 22 | 100.00 1 | 99.74 13 | 100.00 1 | 100.00 1 |
|
mPP-MVS | | | 98.39 42 | 98.20 39 | 98.97 72 | 99.97 3 | 96.92 106 | 99.95 31 | 98.38 129 | 95.04 67 | 98.61 76 | 99.80 43 | 93.39 89 | 100.00 1 | 98.64 60 | 100.00 1 | 99.98 43 |
|
CNVR-MVS | | | 99.40 1 | 99.26 1 | 99.84 2 | 99.98 2 | 99.51 2 | 99.98 6 | 98.69 63 | 98.20 3 | 99.93 1 | 99.98 2 | 96.82 13 | 100.00 1 | 99.75 11 | 100.00 1 | 99.99 11 |
|
NCCC | | | 99.37 2 | 99.25 2 | 99.71 5 | 99.96 8 | 99.15 9 | 99.97 12 | 98.62 74 | 98.02 6 | 99.90 2 | 99.95 3 | 97.33 9 | 100.00 1 | 99.54 20 | 100.00 1 | 100.00 1 |
|
CP-MVS | | | 98.45 37 | 98.32 35 | 98.87 78 | 99.96 8 | 96.62 112 | 99.97 12 | 98.39 126 | 94.43 83 | 98.90 63 | 99.87 14 | 94.30 66 | 100.00 1 | 99.04 39 | 99.99 13 | 99.99 11 |
|
DP-MVS Recon | | | 98.41 40 | 98.02 46 | 99.56 15 | 99.97 3 | 98.70 34 | 99.92 52 | 98.44 107 | 92.06 169 | 98.40 84 | 99.84 34 | 95.68 32 | 100.00 1 | 98.19 70 | 99.71 72 | 99.97 53 |
|
PHI-MVS | | | 98.41 40 | 98.21 38 | 99.03 67 | 99.86 39 | 97.10 101 | 99.98 6 | 98.80 58 | 90.78 203 | 99.62 22 | 99.78 49 | 95.30 39 | 100.00 1 | 99.80 7 | 99.93 48 | 99.99 11 |
|
DeepPCF-MVS | | 95.94 2 | 97.71 66 | 98.98 8 | 93.92 246 | 99.63 67 | 81.76 319 | 99.96 19 | 98.56 84 | 99.47 1 | 99.19 52 | 99.99 1 | 94.16 72 | 100.00 1 | 99.92 3 | 99.93 48 | 100.00 1 |
|
DeepC-MVS_fast | | 96.59 1 | 98.81 18 | 98.54 23 | 99.62 11 | 99.90 33 | 98.85 20 | 99.24 194 | 98.47 103 | 98.14 4 | 99.08 55 | 99.91 6 | 93.09 97 | 100.00 1 | 99.04 39 | 99.99 13 | 100.00 1 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
AdaColmap | | | 97.23 80 | 96.80 81 | 98.51 101 | 99.99 1 | 95.60 147 | 99.09 204 | 98.84 55 | 93.32 120 | 96.74 120 | 99.72 64 | 86.04 178 | 100.00 1 | 98.01 78 | 99.43 91 | 99.94 64 |
|
testdata2 | | | | | | | | | | | | | | 99.99 27 | 90.54 202 | | |
|
CPTT-MVS | | | 97.64 68 | 97.32 67 | 98.58 95 | 99.97 3 | 95.77 139 | 99.96 19 | 98.35 133 | 89.90 214 | 98.36 85 | 99.79 44 | 91.18 127 | 99.99 27 | 98.37 68 | 99.99 13 | 99.99 11 |
|
API-MVS | | | 97.86 59 | 97.66 56 | 98.47 107 | 99.52 75 | 95.41 151 | 99.47 170 | 98.87 52 | 91.68 177 | 98.84 64 | 99.85 20 | 92.34 108 | 99.99 27 | 98.44 66 | 99.96 36 | 100.00 1 |
|
ACMMP | | | 97.74 65 | 97.44 63 | 98.66 88 | 99.92 27 | 96.13 130 | 99.18 198 | 99.45 22 | 94.84 72 | 96.41 129 | 99.71 66 | 91.40 121 | 99.99 27 | 97.99 80 | 98.03 120 | 99.87 74 |
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 |
CANet_DTU | | | 96.76 96 | 96.15 97 | 98.60 93 | 98.78 114 | 97.53 76 | 99.84 90 | 97.63 197 | 97.25 13 | 99.20 50 | 99.64 79 | 81.36 225 | 99.98 31 | 92.77 174 | 98.89 100 | 98.28 189 |
|
SD-MVS | | | 98.92 13 | 98.70 14 | 99.56 15 | 99.70 64 | 98.73 32 | 99.94 45 | 98.34 134 | 96.38 34 | 99.81 7 | 99.76 55 | 94.59 56 | 99.98 31 | 99.84 6 | 99.96 36 | 99.97 53 |
|
abl_6 | | | 97.67 67 | 97.34 65 | 98.66 88 | 99.68 65 | 96.11 134 | 99.68 138 | 98.14 158 | 93.80 108 | 99.27 48 | 99.70 68 | 88.65 157 | 99.98 31 | 97.46 93 | 99.72 71 | 99.89 71 |
|
PAPM_NR | | | 98.12 52 | 97.93 52 | 98.70 85 | 99.94 14 | 96.13 130 | 99.82 95 | 98.43 112 | 94.56 79 | 97.52 105 | 99.70 68 | 94.40 59 | 99.98 31 | 97.00 104 | 99.98 25 | 99.99 11 |
|
PAPR | | | 98.52 33 | 98.16 41 | 99.58 14 | 99.97 3 | 98.77 25 | 99.95 31 | 98.43 112 | 95.35 62 | 98.03 96 | 99.75 60 | 94.03 75 | 99.98 31 | 98.11 74 | 99.83 61 | 99.99 11 |
|
CSCG | | | 97.10 84 | 97.04 75 | 97.27 153 | 99.89 36 | 91.92 234 | 99.90 59 | 99.07 33 | 88.67 233 | 95.26 151 | 99.82 39 | 93.17 96 | 99.98 31 | 98.15 72 | 99.47 88 | 99.90 70 |
|
CNLPA | | | 97.76 64 | 97.38 64 | 98.92 76 | 99.53 74 | 96.84 107 | 99.87 71 | 98.14 158 | 93.78 109 | 96.55 123 | 99.69 71 | 92.28 109 | 99.98 31 | 97.13 100 | 99.44 90 | 99.93 65 |
|
MG-MVS | | | 98.91 14 | 98.65 16 | 99.68 7 | 99.94 14 | 99.07 11 | 99.64 150 | 99.44 23 | 97.33 12 | 99.00 61 | 99.72 64 | 94.03 75 | 99.98 31 | 98.73 53 | 100.00 1 | 100.00 1 |
|
MAR-MVS | | | 97.43 71 | 97.19 69 | 98.15 125 | 99.47 78 | 94.79 166 | 99.05 215 | 98.76 59 | 92.65 143 | 98.66 73 | 99.82 39 | 88.52 158 | 99.98 31 | 98.12 73 | 99.63 76 | 99.67 96 |
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 |
MP-MVS-pluss | | | 98.07 54 | 97.64 57 | 99.38 34 | 99.74 56 | 98.41 52 | 99.74 119 | 98.18 151 | 93.35 119 | 96.45 126 | 99.85 20 | 92.64 105 | 99.97 40 | 98.91 46 | 99.89 54 | 99.77 84 |
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
PLC | | 95.54 3 | 97.93 58 | 97.89 53 | 98.05 129 | 99.82 49 | 94.77 167 | 99.92 52 | 98.46 105 | 93.93 104 | 97.20 110 | 99.27 101 | 95.44 37 | 99.97 40 | 97.41 94 | 99.51 87 | 99.41 133 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
MVS_0304 | | | 97.52 70 | 96.79 82 | 99.69 6 | 99.59 69 | 99.30 4 | 99.97 12 | 98.01 167 | 96.99 19 | 98.84 64 | 99.79 44 | 78.90 255 | 99.96 42 | 99.74 13 | 99.32 94 | 99.81 79 |
|
XVS | | | 98.70 22 | 98.55 22 | 99.15 49 | 99.94 14 | 97.50 79 | 99.94 45 | 98.42 120 | 96.22 39 | 99.41 39 | 99.78 49 | 94.34 63 | 99.96 42 | 98.92 44 | 99.95 39 | 99.99 11 |
|
X-MVStestdata | | | 93.83 173 | 92.06 195 | 99.15 49 | 99.94 14 | 97.50 79 | 99.94 45 | 98.42 120 | 96.22 39 | 99.41 39 | 41.37 355 | 94.34 63 | 99.96 42 | 98.92 44 | 99.95 39 | 99.99 11 |
|
原ACMM1 | | | | | 98.96 73 | 99.73 60 | 96.99 103 | | 98.51 97 | 94.06 98 | 99.62 22 | 99.85 20 | 94.97 50 | 99.96 42 | 95.11 127 | 99.95 39 | 99.92 68 |
|
1314 | | | 96.84 92 | 95.96 106 | 99.48 24 | 96.74 200 | 98.52 47 | 98.31 270 | 98.86 53 | 95.82 48 | 89.91 210 | 98.98 119 | 87.49 164 | 99.96 42 | 97.80 86 | 99.73 70 | 99.96 57 |
|
MVS | | | 96.60 105 | 95.56 130 | 99.72 4 | 96.85 193 | 99.22 8 | 98.31 270 | 98.94 38 | 91.57 179 | 90.90 196 | 99.61 81 | 86.66 173 | 99.96 42 | 97.36 95 | 99.88 56 | 99.99 11 |
|
UGNet | | | 95.33 144 | 94.57 150 | 97.62 141 | 98.55 125 | 94.85 162 | 98.67 246 | 99.32 28 | 95.75 55 | 96.80 119 | 96.27 221 | 72.18 295 | 99.96 42 | 94.58 139 | 99.05 99 | 98.04 193 |
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 |
QAPM | | | 95.40 143 | 94.17 157 | 99.10 57 | 96.92 189 | 97.71 71 | 99.40 176 | 98.68 64 | 89.31 219 | 88.94 238 | 98.89 125 | 82.48 202 | 99.96 42 | 93.12 172 | 99.83 61 | 99.62 104 |
|
CANet | | | 98.27 46 | 97.82 54 | 99.63 8 | 99.72 62 | 99.10 10 | 99.98 6 | 98.51 97 | 97.00 18 | 98.52 78 | 99.71 66 | 87.80 161 | 99.95 50 | 99.75 11 | 99.38 92 | 99.83 77 |
|
旧先验2 | | | | | | | | 99.46 172 | | 94.21 90 | 99.85 5 | | | 99.95 50 | 96.96 106 | | |
|
PVSNet_BlendedMVS | | | 96.05 129 | 95.82 121 | 96.72 166 | 99.59 69 | 96.99 103 | 99.95 31 | 99.10 30 | 94.06 98 | 98.27 89 | 95.80 229 | 89.00 152 | 99.95 50 | 99.12 32 | 87.53 237 | 93.24 289 |
|
PVSNet_Blended | | | 97.94 57 | 97.64 57 | 98.83 80 | 99.59 69 | 96.99 103 | 100.00 1 | 99.10 30 | 95.38 61 | 98.27 89 | 99.08 112 | 89.00 152 | 99.95 50 | 99.12 32 | 99.25 96 | 99.57 114 |
|
DP-MVS | | | 94.54 162 | 93.42 173 | 97.91 133 | 99.46 80 | 94.04 177 | 98.93 226 | 97.48 216 | 81.15 311 | 90.04 207 | 99.55 84 | 87.02 170 | 99.95 50 | 88.97 224 | 98.11 116 | 99.73 89 |
|
PVSNet | | 91.05 13 | 97.13 83 | 96.69 85 | 98.45 109 | 99.52 75 | 95.81 137 | 99.95 31 | 99.65 16 | 94.73 75 | 99.04 57 | 99.21 107 | 84.48 191 | 99.95 50 | 94.92 129 | 98.74 104 | 99.58 113 |
|
3Dnovator | | 91.47 12 | 96.28 126 | 95.34 135 | 99.08 59 | 96.82 195 | 97.47 82 | 99.45 173 | 98.81 56 | 95.52 59 | 89.39 228 | 99.00 118 | 81.97 211 | 99.95 50 | 97.27 97 | 99.83 61 | 99.84 76 |
|
LS3D | | | 95.84 134 | 95.11 142 | 98.02 130 | 99.85 40 | 95.10 159 | 98.74 239 | 98.50 101 | 87.22 257 | 93.66 175 | 99.86 16 | 87.45 165 | 99.95 50 | 90.94 196 | 99.81 67 | 99.02 178 |
|
testdata | | | | | 98.42 112 | 99.47 78 | 95.33 153 | | 98.56 84 | 93.78 109 | 99.79 10 | 99.85 20 | 93.64 87 | 99.94 58 | 94.97 128 | 99.94 43 | 100.00 1 |
|
TSAR-MVS + GP. | | | 98.60 25 | 98.51 24 | 98.86 79 | 99.73 60 | 96.63 111 | 99.97 12 | 97.92 176 | 98.07 5 | 98.76 68 | 99.55 84 | 95.00 48 | 99.94 58 | 99.91 4 | 97.68 124 | 99.99 11 |
|
DELS-MVS | | | 98.54 31 | 98.22 37 | 99.50 21 | 99.15 86 | 98.65 38 | 100.00 1 | 98.58 80 | 97.70 7 | 98.21 93 | 99.24 105 | 92.58 106 | 99.94 58 | 98.63 61 | 99.94 43 | 99.92 68 |
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 |
F-COLMAP | | | 96.93 89 | 96.95 77 | 96.87 161 | 99.71 63 | 91.74 240 | 99.85 87 | 97.95 173 | 93.11 124 | 95.72 144 | 99.16 109 | 92.35 107 | 99.94 58 | 95.32 125 | 99.35 93 | 98.92 180 |
|
3Dnovator+ | | 91.53 11 | 96.31 123 | 95.24 137 | 99.52 19 | 96.88 192 | 98.64 39 | 99.72 130 | 98.24 144 | 95.27 65 | 88.42 246 | 98.98 119 | 82.76 201 | 99.94 58 | 97.10 102 | 99.83 61 | 99.96 57 |
|
OpenMVS | | 90.15 15 | 94.77 156 | 93.59 167 | 98.33 118 | 96.07 209 | 97.48 81 | 99.56 158 | 98.57 82 | 90.46 205 | 86.51 266 | 98.95 123 | 78.57 258 | 99.94 58 | 93.86 152 | 99.74 69 | 97.57 199 |
|
EPNet | | | 98.49 35 | 98.40 28 | 98.77 82 | 99.62 68 | 96.80 109 | 99.90 59 | 99.51 20 | 97.60 8 | 99.20 50 | 99.36 99 | 93.71 85 | 99.91 64 | 97.99 80 | 98.71 105 | 99.61 106 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
CHOSEN 1792x2688 | | | 96.81 93 | 96.53 90 | 97.64 140 | 98.91 102 | 93.07 206 | 99.65 146 | 99.80 3 | 95.64 57 | 95.39 148 | 98.86 131 | 84.35 193 | 99.90 65 | 96.98 105 | 99.16 98 | 99.95 62 |
|
MVS_111021_LR | | | 98.42 39 | 98.38 30 | 98.53 100 | 99.39 81 | 95.79 138 | 99.87 71 | 99.86 2 | 96.70 27 | 98.78 67 | 99.79 44 | 92.03 114 | 99.90 65 | 99.17 31 | 99.86 59 | 99.88 73 |
|
DeepC-MVS | | 94.51 4 | 96.92 90 | 96.40 92 | 98.45 109 | 99.16 85 | 95.90 136 | 99.66 143 | 98.06 164 | 96.37 37 | 94.37 170 | 99.49 89 | 83.29 199 | 99.90 65 | 97.63 91 | 99.61 80 | 99.55 116 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
PS-MVSNAJ | | | 98.44 38 | 98.20 39 | 99.16 45 | 98.80 113 | 98.92 15 | 99.54 162 | 98.17 152 | 97.34 11 | 99.85 5 | 99.85 20 | 91.20 124 | 99.89 68 | 99.41 27 | 99.67 74 | 98.69 186 |
|
VNet | | | 97.21 81 | 96.57 89 | 99.13 56 | 98.97 95 | 97.82 69 | 99.03 217 | 99.21 29 | 94.31 87 | 99.18 53 | 98.88 127 | 86.26 177 | 99.89 68 | 98.93 43 | 94.32 183 | 99.69 94 |
|
sss | | | 97.57 69 | 97.03 76 | 99.18 42 | 98.37 131 | 98.04 63 | 99.73 125 | 99.38 26 | 93.46 117 | 98.76 68 | 99.06 113 | 91.21 123 | 99.89 68 | 96.33 112 | 97.01 142 | 99.62 104 |
|
MVS_111021_HR | | | 98.72 21 | 98.62 18 | 99.01 70 | 99.36 83 | 97.18 97 | 99.93 50 | 99.90 1 | 96.81 24 | 98.67 72 | 99.77 51 | 93.92 77 | 99.89 68 | 99.27 30 | 99.94 43 | 99.96 57 |
|
PVSNet_0 | | 88.03 19 | 91.80 210 | 90.27 222 | 96.38 175 | 98.27 135 | 90.46 261 | 99.94 45 | 99.61 17 | 93.99 100 | 86.26 272 | 97.39 186 | 71.13 301 | 99.89 68 | 98.77 52 | 67.05 326 | 98.79 184 |
|
PCF-MVS | | 94.20 5 | 95.18 146 | 94.10 158 | 98.43 111 | 98.55 125 | 95.99 135 | 97.91 287 | 97.31 232 | 90.35 207 | 89.48 227 | 99.22 106 | 85.19 188 | 99.89 68 | 90.40 205 | 98.47 108 | 99.41 133 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
AllTest | | | 92.48 198 | 91.64 198 | 95.00 203 | 99.01 90 | 88.43 283 | 98.94 225 | 96.82 281 | 86.50 265 | 88.71 239 | 98.47 166 | 74.73 285 | 99.88 74 | 85.39 264 | 96.18 151 | 96.71 202 |
|
TestCases | | | | | 95.00 203 | 99.01 90 | 88.43 283 | | 96.82 281 | 86.50 265 | 88.71 239 | 98.47 166 | 74.73 285 | 99.88 74 | 85.39 264 | 96.18 151 | 96.71 202 |
|
PVSNet_Blended_VisFu | | | 97.27 78 | 96.81 80 | 98.66 88 | 98.81 112 | 96.67 110 | 99.92 52 | 98.64 70 | 94.51 80 | 96.38 130 | 98.49 162 | 89.05 151 | 99.88 74 | 97.10 102 | 98.34 110 | 99.43 131 |
|
MSDG | | | 94.37 168 | 93.36 177 | 97.40 149 | 98.88 107 | 93.95 179 | 99.37 181 | 97.38 226 | 85.75 278 | 90.80 197 | 99.17 108 | 84.11 194 | 99.88 74 | 86.35 256 | 98.43 109 | 98.36 188 |
|
TEST9 | | | | | | 99.92 27 | 98.92 15 | 99.96 19 | 98.43 112 | 93.90 105 | 99.71 15 | 99.86 16 | 95.88 30 | 99.85 78 | | | |
|
train_agg | | | 98.88 15 | 98.65 16 | 99.59 13 | 99.92 27 | 98.92 15 | 99.96 19 | 98.43 112 | 94.35 85 | 99.71 15 | 99.86 16 | 95.94 27 | 99.85 78 | 99.69 18 | 99.98 25 | 99.99 11 |
|
test_8 | | | | | | 99.92 27 | 98.88 18 | 99.96 19 | 98.43 112 | 94.35 85 | 99.69 17 | 99.85 20 | 95.94 27 | 99.85 78 | | | |
|
agg_prior3 | | | 98.84 17 | 98.62 18 | 99.47 25 | 99.92 27 | 98.56 45 | 99.96 19 | 98.43 112 | 94.07 95 | 99.67 18 | 99.85 20 | 96.05 23 | 99.85 78 | 99.69 18 | 99.98 25 | 99.99 11 |
|
agg_prior1 | | | 98.88 15 | 98.66 15 | 99.54 17 | 99.93 24 | 98.77 25 | 99.96 19 | 98.43 112 | 94.63 78 | 99.63 20 | 99.85 20 | 95.79 31 | 99.85 78 | 99.72 16 | 99.99 13 | 99.99 11 |
|
agg_prior | | | | | | 99.93 24 | 98.77 25 | | 98.43 112 | | 99.63 20 | | | 99.85 78 | | | |
|
SteuartSystems-ACMMP | | | 99.02 9 | 98.97 9 | 99.18 42 | 98.72 116 | 97.71 71 | 99.98 6 | 98.44 107 | 96.85 20 | 99.80 8 | 99.91 6 | 97.57 4 | 99.85 78 | 99.44 25 | 99.99 13 | 99.99 11 |
Skip Steuart: Steuart Systems R&D Blog. |
COLMAP_ROB | | 90.47 14 | 92.18 204 | 91.49 202 | 94.25 234 | 99.00 92 | 88.04 288 | 98.42 265 | 96.70 283 | 82.30 301 | 88.43 244 | 99.01 116 | 76.97 266 | 99.85 78 | 86.11 259 | 96.50 149 | 94.86 210 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
PatchMatch-RL | | | 96.04 130 | 95.40 132 | 97.95 131 | 99.59 69 | 95.22 158 | 99.52 164 | 99.07 33 | 93.96 102 | 96.49 124 | 98.35 168 | 82.28 203 | 99.82 86 | 90.15 209 | 99.22 97 | 98.81 183 |
|
test_prior3 | | | 98.99 11 | 98.84 12 | 99.43 26 | 99.94 14 | 98.49 49 | 99.95 31 | 98.65 67 | 95.78 50 | 99.73 13 | 99.76 55 | 96.00 25 | 99.80 87 | 99.78 9 | 100.00 1 | 99.99 11 |
|
test_prior | | | | | 99.43 26 | 99.94 14 | 98.49 49 | | 98.65 67 | | | | | 99.80 87 | | | 99.99 11 |
|
APDe-MVS | | | 99.06 8 | 98.91 10 | 99.51 20 | 99.94 14 | 98.76 31 | 99.91 56 | 98.39 126 | 97.20 14 | 99.46 34 | 99.85 20 | 95.53 36 | 99.79 89 | 99.86 5 | 100.00 1 | 99.99 11 |
|
XVG-OURS-SEG-HR | | | 94.79 154 | 94.70 148 | 95.08 199 | 98.05 147 | 89.19 274 | 99.08 206 | 97.54 207 | 93.66 113 | 94.87 164 | 99.58 82 | 78.78 256 | 99.79 89 | 97.31 96 | 93.40 200 | 96.25 205 |
|
VDD-MVS | | | 93.77 177 | 92.94 180 | 96.27 177 | 98.55 125 | 90.22 264 | 98.77 238 | 97.79 188 | 90.85 201 | 96.82 118 | 99.42 92 | 61.18 329 | 99.77 91 | 98.95 41 | 94.13 187 | 98.82 182 |
|
HY-MVS | | 92.50 7 | 97.79 63 | 97.17 71 | 99.63 8 | 98.98 94 | 99.32 3 | 97.49 291 | 99.52 18 | 95.69 56 | 98.32 87 | 97.41 185 | 93.32 91 | 99.77 91 | 98.08 77 | 95.75 162 | 99.81 79 |
|
Regformer-1 | | | 98.79 19 | 98.60 20 | 99.36 35 | 99.85 40 | 98.34 53 | 99.87 71 | 98.52 91 | 96.05 45 | 99.41 39 | 99.79 44 | 94.93 51 | 99.76 93 | 99.07 34 | 99.90 52 | 99.99 11 |
|
Regformer-2 | | | 98.78 20 | 98.59 21 | 99.36 35 | 99.85 40 | 98.32 54 | 99.87 71 | 98.52 91 | 96.04 46 | 99.41 39 | 99.79 44 | 94.92 52 | 99.76 93 | 99.05 35 | 99.90 52 | 99.98 43 |
|
APD-MVS_3200maxsize | | | 98.25 48 | 98.08 45 | 98.78 81 | 99.81 50 | 96.60 113 | 99.82 95 | 98.30 138 | 93.95 103 | 99.37 43 | 99.77 51 | 92.84 99 | 99.76 93 | 98.95 41 | 99.92 50 | 99.97 53 |
|
Regformer-3 | | | 98.58 28 | 98.41 26 | 99.10 57 | 99.84 45 | 97.57 75 | 99.66 143 | 98.52 91 | 95.79 49 | 99.01 59 | 99.77 51 | 94.40 59 | 99.75 96 | 98.82 49 | 99.83 61 | 99.98 43 |
|
Regformer-4 | | | 98.56 29 | 98.39 29 | 99.08 59 | 99.84 45 | 97.52 77 | 99.66 143 | 98.52 91 | 95.76 52 | 99.01 59 | 99.77 51 | 94.33 65 | 99.75 96 | 98.80 50 | 99.83 61 | 99.98 43 |
|
CDPH-MVS | | | 98.65 23 | 98.36 33 | 99.49 22 | 99.94 14 | 98.73 32 | 99.87 71 | 98.33 135 | 93.97 101 | 99.76 11 | 99.87 14 | 94.99 49 | 99.75 96 | 98.55 63 | 100.00 1 | 99.98 43 |
|
test12 | | | | | 99.43 26 | 99.74 56 | 98.56 45 | | 98.40 124 | | 99.65 19 | | 94.76 54 | 99.75 96 | | 99.98 25 | 99.99 11 |
|
XVG-OURS | | | 94.82 153 | 94.74 147 | 95.06 200 | 98.00 148 | 89.19 274 | 99.08 206 | 97.55 205 | 94.10 93 | 94.71 165 | 99.62 80 | 80.51 238 | 99.74 100 | 96.04 116 | 93.06 205 | 96.25 205 |
|
APD-MVS | | | 98.62 24 | 98.35 34 | 99.41 30 | 99.90 33 | 98.51 48 | 99.87 71 | 98.36 132 | 94.08 94 | 99.74 12 | 99.73 63 | 94.08 73 | 99.74 100 | 99.42 26 | 99.99 13 | 99.99 11 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
WTY-MVS | | | 98.10 53 | 97.60 59 | 99.60 12 | 98.92 100 | 99.28 5 | 99.89 64 | 99.52 18 | 95.58 58 | 98.24 92 | 99.39 96 | 93.33 90 | 99.74 100 | 97.98 82 | 95.58 165 | 99.78 83 |
|
EI-MVSNet-UG-set | | | 98.14 51 | 97.99 48 | 98.60 93 | 99.80 51 | 96.27 121 | 99.36 183 | 98.50 101 | 95.21 66 | 98.30 88 | 99.75 60 | 93.29 93 | 99.73 103 | 98.37 68 | 99.30 95 | 99.81 79 |
|
HSP-MVS | | | 99.07 6 | 99.11 4 | 98.95 74 | 99.93 24 | 97.24 94 | 99.95 31 | 98.32 136 | 97.50 10 | 99.52 31 | 99.88 11 | 97.43 6 | 99.71 104 | 99.50 22 | 99.98 25 | 99.89 71 |
|
xiu_mvs_v2_base | | | 98.23 49 | 97.97 49 | 99.02 69 | 98.69 117 | 98.66 36 | 99.52 164 | 98.08 163 | 97.05 16 | 99.86 4 | 99.86 16 | 90.65 132 | 99.71 104 | 99.39 28 | 98.63 106 | 98.69 186 |
|
EI-MVSNet-Vis-set | | | 98.27 46 | 98.11 44 | 98.75 83 | 99.83 48 | 96.59 114 | 99.40 176 | 98.51 97 | 95.29 64 | 98.51 79 | 99.76 55 | 93.60 88 | 99.71 104 | 98.53 64 | 99.52 85 | 99.95 62 |
|
ab-mvs | | | 94.69 158 | 93.42 173 | 98.51 101 | 98.07 146 | 96.26 122 | 96.49 306 | 98.68 64 | 90.31 208 | 94.54 166 | 97.00 199 | 76.30 273 | 99.71 104 | 95.98 117 | 93.38 201 | 99.56 115 |
|
xiu_mvs_v1_base_debu | | | 97.43 71 | 97.06 72 | 98.55 96 | 97.74 166 | 98.14 58 | 99.31 186 | 97.86 183 | 96.43 31 | 99.62 22 | 99.69 71 | 85.56 183 | 99.68 108 | 99.05 35 | 98.31 112 | 97.83 195 |
|
xiu_mvs_v1_base | | | 97.43 71 | 97.06 72 | 98.55 96 | 97.74 166 | 98.14 58 | 99.31 186 | 97.86 183 | 96.43 31 | 99.62 22 | 99.69 71 | 85.56 183 | 99.68 108 | 99.05 35 | 98.31 112 | 97.83 195 |
|
xiu_mvs_v1_base_debi | | | 97.43 71 | 97.06 72 | 98.55 96 | 97.74 166 | 98.14 58 | 99.31 186 | 97.86 183 | 96.43 31 | 99.62 22 | 99.69 71 | 85.56 183 | 99.68 108 | 99.05 35 | 98.31 112 | 97.83 195 |
|
HPM-MVS | | | 97.96 56 | 97.72 55 | 98.68 86 | 99.84 45 | 96.39 120 | 99.90 59 | 98.17 152 | 92.61 145 | 98.62 75 | 99.57 83 | 91.87 117 | 99.67 111 | 98.87 47 | 99.99 13 | 99.99 11 |
|
UA-Net | | | 96.54 106 | 95.96 106 | 98.27 120 | 98.23 138 | 95.71 144 | 98.00 285 | 98.45 106 | 93.72 111 | 98.41 82 | 99.27 101 | 88.71 156 | 99.66 112 | 91.19 190 | 97.69 123 | 99.44 130 |
|
HPM-MVS_fast | | | 97.80 62 | 97.50 62 | 98.68 86 | 99.79 52 | 96.42 117 | 99.88 66 | 98.16 155 | 91.75 176 | 98.94 62 | 99.54 86 | 91.82 119 | 99.65 113 | 97.62 92 | 99.99 13 | 99.99 11 |
|
114514_t | | | 97.41 75 | 96.83 79 | 99.14 51 | 99.51 77 | 97.83 68 | 99.89 64 | 98.27 143 | 88.48 236 | 99.06 56 | 99.66 77 | 90.30 135 | 99.64 114 | 96.32 113 | 99.97 34 | 99.96 57 |
|
TSAR-MVS + MP. | | | 98.93 12 | 98.77 13 | 99.41 30 | 99.74 56 | 98.67 35 | 99.77 109 | 98.38 129 | 96.73 26 | 99.88 3 | 99.74 62 | 94.89 53 | 99.59 115 | 99.80 7 | 99.98 25 | 99.97 53 |
|
LFMVS | | | 94.75 157 | 93.56 169 | 98.30 119 | 99.03 89 | 95.70 145 | 98.74 239 | 97.98 170 | 87.81 244 | 98.47 80 | 99.39 96 | 67.43 313 | 99.53 116 | 98.01 78 | 95.20 169 | 99.67 96 |
|
canonicalmvs | | | 97.09 85 | 96.32 93 | 99.39 33 | 98.93 99 | 98.95 14 | 99.72 130 | 97.35 228 | 94.45 81 | 97.88 99 | 99.42 92 | 86.71 172 | 99.52 117 | 98.48 65 | 93.97 196 | 99.72 91 |
|
thres200 | | | 96.96 87 | 96.21 96 | 99.22 40 | 98.97 95 | 98.84 21 | 99.85 87 | 99.71 5 | 93.17 122 | 96.26 131 | 98.88 127 | 89.87 138 | 99.51 118 | 94.26 146 | 94.91 171 | 99.31 148 |
|
OMC-MVS | | | 97.28 77 | 97.23 68 | 97.41 148 | 99.76 53 | 93.36 200 | 99.65 146 | 97.95 173 | 96.03 47 | 97.41 107 | 99.70 68 | 89.61 140 | 99.51 118 | 96.73 110 | 98.25 115 | 99.38 140 |
|
tfpn111 | | | 96.69 101 | 95.87 119 | 99.16 45 | 98.90 103 | 98.77 25 | 99.74 119 | 99.71 5 | 92.59 147 | 95.84 138 | 98.86 131 | 89.25 143 | 99.50 120 | 93.44 163 | 94.50 176 | 99.20 159 |
|
conf200view11 | | | 96.73 100 | 95.92 109 | 99.16 45 | 98.90 103 | 98.77 25 | 99.74 119 | 99.71 5 | 92.59 147 | 95.84 138 | 98.86 131 | 89.25 143 | 99.50 120 | 93.84 153 | 94.57 172 | 99.20 159 |
|
thres100view900 | | | 96.74 98 | 95.92 109 | 99.18 42 | 98.90 103 | 98.77 25 | 99.74 119 | 99.71 5 | 92.59 147 | 95.84 138 | 98.86 131 | 89.25 143 | 99.50 120 | 93.84 153 | 94.57 172 | 99.27 153 |
|
tfpn200view9 | | | 96.79 94 | 95.99 101 | 99.19 41 | 98.94 97 | 98.82 22 | 99.78 104 | 99.71 5 | 92.86 127 | 96.02 134 | 98.87 129 | 89.33 141 | 99.50 120 | 93.84 153 | 94.57 172 | 99.27 153 |
|
thres600view7 | | | 96.69 101 | 95.87 119 | 99.14 51 | 98.90 103 | 98.78 24 | 99.74 119 | 99.71 5 | 92.59 147 | 95.84 138 | 98.86 131 | 89.25 143 | 99.50 120 | 93.44 163 | 94.50 176 | 99.16 165 |
|
thres400 | | | 96.78 95 | 95.99 101 | 99.16 45 | 98.94 97 | 98.82 22 | 99.78 104 | 99.71 5 | 92.86 127 | 96.02 134 | 98.87 129 | 89.33 141 | 99.50 120 | 93.84 153 | 94.57 172 | 99.16 165 |
|
VDDNet | | | 93.12 187 | 91.91 196 | 96.76 164 | 96.67 203 | 92.65 219 | 98.69 243 | 98.21 147 | 82.81 296 | 97.75 101 | 99.28 100 | 61.57 327 | 99.48 126 | 98.09 76 | 94.09 188 | 98.15 191 |
|
RPSCF | | | 91.80 210 | 92.79 183 | 88.83 308 | 98.15 143 | 69.87 331 | 98.11 281 | 96.60 287 | 83.93 292 | 94.33 171 | 99.27 101 | 79.60 246 | 99.46 127 | 91.99 182 | 93.16 204 | 97.18 200 |
|
view600 | | | 96.46 115 | 95.59 125 | 99.06 61 | 98.87 108 | 98.60 41 | 99.69 133 | 99.71 5 | 92.20 160 | 95.23 152 | 98.80 143 | 89.17 147 | 99.43 128 | 92.29 176 | 94.37 179 | 99.16 165 |
|
view800 | | | 96.46 115 | 95.59 125 | 99.06 61 | 98.87 108 | 98.60 41 | 99.69 133 | 99.71 5 | 92.20 160 | 95.23 152 | 98.80 143 | 89.17 147 | 99.43 128 | 92.29 176 | 94.37 179 | 99.16 165 |
|
conf0.05thres1000 | | | 96.46 115 | 95.59 125 | 99.06 61 | 98.87 108 | 98.60 41 | 99.69 133 | 99.71 5 | 92.20 160 | 95.23 152 | 98.80 143 | 89.17 147 | 99.43 128 | 92.29 176 | 94.37 179 | 99.16 165 |
|
tfpn | | | 96.46 115 | 95.59 125 | 99.06 61 | 98.87 108 | 98.60 41 | 99.69 133 | 99.71 5 | 92.20 160 | 95.23 152 | 98.80 143 | 89.17 147 | 99.43 128 | 92.29 176 | 94.37 179 | 99.16 165 |
|
alignmvs | | | 97.81 61 | 97.33 66 | 99.25 39 | 98.77 115 | 98.66 36 | 99.99 3 | 98.44 107 | 94.40 84 | 98.41 82 | 99.47 90 | 93.65 86 | 99.42 132 | 98.57 62 | 94.26 185 | 99.67 96 |
|
Test_1112_low_res | | | 95.72 135 | 94.83 145 | 98.42 112 | 97.79 162 | 96.41 118 | 99.65 146 | 96.65 285 | 92.70 138 | 92.86 185 | 96.13 225 | 92.15 112 | 99.30 133 | 91.88 184 | 93.64 198 | 99.55 116 |
|
1112_ss | | | 96.01 131 | 95.20 139 | 98.42 112 | 97.80 161 | 96.41 118 | 99.65 146 | 96.66 284 | 92.71 137 | 92.88 184 | 99.40 94 | 92.16 111 | 99.30 133 | 91.92 183 | 93.66 197 | 99.55 116 |
|
cascas | | | 94.64 160 | 93.61 164 | 97.74 137 | 97.82 160 | 96.26 122 | 99.96 19 | 97.78 189 | 85.76 275 | 94.00 174 | 97.54 182 | 76.95 267 | 99.21 135 | 97.23 98 | 95.43 167 | 97.76 198 |
|
TAPA-MVS | | 92.12 8 | 94.42 166 | 93.60 166 | 96.90 160 | 99.33 84 | 91.78 238 | 99.78 104 | 98.00 168 | 89.89 215 | 94.52 167 | 99.47 90 | 91.97 115 | 99.18 136 | 69.90 322 | 99.52 85 | 99.73 89 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
IB-MVS | | 92.85 6 | 94.99 152 | 93.94 160 | 98.16 122 | 97.72 170 | 95.69 146 | 99.99 3 | 98.81 56 | 94.28 88 | 92.70 186 | 96.90 201 | 95.08 43 | 99.17 137 | 96.07 115 | 73.88 316 | 99.60 108 |
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 |
tfpn_ndepth | | | 97.21 81 | 96.63 86 | 98.92 76 | 99.06 87 | 98.28 55 | 99.95 31 | 98.91 42 | 92.96 126 | 96.49 124 | 98.67 151 | 97.40 7 | 99.07 138 | 91.87 185 | 94.38 178 | 99.41 133 |
|
DI_MVS_plusplus_test | | | 92.48 198 | 90.60 212 | 98.11 127 | 91.88 302 | 96.13 130 | 99.64 150 | 97.73 190 | 92.69 139 | 76.02 310 | 93.79 292 | 70.49 302 | 99.07 138 | 95.88 119 | 97.26 135 | 99.14 171 |
|
test_normal | | | 92.44 201 | 90.54 213 | 98.12 126 | 91.85 303 | 96.18 129 | 99.68 138 | 97.73 190 | 92.66 141 | 75.76 314 | 93.74 294 | 70.49 302 | 99.04 140 | 95.71 123 | 97.27 134 | 99.13 173 |
|
mvs-test1 | | | 95.53 140 | 95.97 105 | 94.20 235 | 97.77 163 | 85.44 302 | 99.95 31 | 97.06 246 | 94.92 69 | 96.58 122 | 98.72 149 | 85.81 180 | 98.98 141 | 94.80 133 | 98.11 116 | 98.18 190 |
|
MVS_Test | | | 96.46 115 | 95.74 122 | 98.61 92 | 98.18 141 | 97.23 95 | 99.31 186 | 97.15 242 | 91.07 196 | 98.84 64 | 97.05 197 | 88.17 160 | 98.97 142 | 94.39 141 | 97.50 127 | 99.61 106 |
|
tpmvs | | | 94.28 169 | 93.57 168 | 96.40 174 | 98.55 125 | 91.50 249 | 95.70 319 | 98.55 88 | 87.47 252 | 92.15 188 | 94.26 285 | 91.42 120 | 98.95 143 | 88.15 230 | 95.85 159 | 98.76 185 |
|
diffmvs | | | 95.25 145 | 94.26 155 | 98.23 121 | 98.13 144 | 96.59 114 | 99.12 201 | 97.18 238 | 85.78 274 | 97.64 102 | 96.70 209 | 85.92 179 | 98.87 144 | 90.40 205 | 97.45 128 | 99.24 158 |
|
tpm cat1 | | | 93.51 182 | 92.52 188 | 96.47 171 | 97.77 163 | 91.47 250 | 96.13 312 | 98.06 164 | 80.98 312 | 92.91 183 | 93.78 293 | 89.66 139 | 98.87 144 | 87.03 248 | 96.39 150 | 99.09 176 |
|
tfpn1000 | | | 96.90 91 | 96.29 94 | 98.74 84 | 99.00 92 | 98.09 61 | 99.92 52 | 98.91 42 | 92.08 166 | 95.85 137 | 98.65 153 | 97.39 8 | 98.83 146 | 90.56 200 | 94.23 186 | 99.31 148 |
|
BH-RMVSNet | | | 95.18 146 | 94.31 154 | 97.80 134 | 98.17 142 | 95.23 157 | 99.76 115 | 97.53 209 | 92.52 153 | 94.27 172 | 99.25 104 | 76.84 268 | 98.80 147 | 90.89 198 | 99.54 84 | 99.35 145 |
|
gm-plane-assit | | | | | | 96.97 188 | 93.76 186 | | | 91.47 183 | | 98.96 121 | | 98.79 148 | 94.92 129 | | |
|
DWT-MVSNet_test | | | 97.31 76 | 97.19 69 | 97.66 139 | 98.24 137 | 94.67 168 | 98.86 234 | 98.20 150 | 93.60 115 | 98.09 94 | 98.89 125 | 97.51 5 | 98.78 149 | 94.04 150 | 97.28 133 | 99.55 116 |
|
TR-MVS | | | 94.54 162 | 93.56 169 | 97.49 144 | 97.96 150 | 94.34 172 | 98.71 241 | 97.51 213 | 90.30 209 | 94.51 168 | 98.69 150 | 75.56 278 | 98.77 150 | 92.82 173 | 95.99 155 | 99.35 145 |
|
Vis-MVSNet | | | 95.72 135 | 95.15 141 | 97.45 146 | 97.62 172 | 94.28 173 | 99.28 191 | 98.24 144 | 94.27 89 | 96.84 117 | 98.94 124 | 79.39 247 | 98.76 151 | 93.25 166 | 98.49 107 | 99.30 150 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
tpmrst | | | 96.27 127 | 95.98 103 | 97.13 155 | 97.96 150 | 93.15 205 | 96.34 309 | 98.17 152 | 92.07 167 | 98.71 71 | 95.12 254 | 93.91 79 | 98.73 152 | 94.91 131 | 96.62 146 | 99.50 125 |
|
PMMVS | | | 96.76 96 | 96.76 84 | 96.76 164 | 98.28 134 | 92.10 229 | 99.91 56 | 97.98 170 | 94.12 92 | 99.53 28 | 99.39 96 | 86.93 171 | 98.73 152 | 96.95 107 | 97.73 122 | 99.45 128 |
|
lupinMVS | | | 97.85 60 | 97.60 59 | 98.62 91 | 97.28 180 | 97.70 73 | 99.99 3 | 97.55 205 | 95.50 60 | 99.43 37 | 99.67 75 | 90.92 130 | 98.71 154 | 98.40 67 | 99.62 77 | 99.45 128 |
|
Effi-MVS+ | | | 96.30 124 | 95.69 123 | 98.16 122 | 97.85 157 | 96.26 122 | 97.41 292 | 97.21 236 | 90.37 206 | 98.65 74 | 98.58 159 | 86.61 174 | 98.70 155 | 97.11 101 | 97.37 132 | 99.52 122 |
|
PatchFormer-LS_test | | | 97.01 86 | 96.79 82 | 97.69 138 | 98.26 136 | 94.80 164 | 98.66 249 | 98.13 160 | 93.70 112 | 97.86 100 | 98.80 143 | 95.54 34 | 98.67 156 | 94.12 149 | 96.00 154 | 99.60 108 |
|
BH-w/o | | | 95.71 137 | 95.38 134 | 96.68 167 | 98.49 129 | 92.28 225 | 99.84 90 | 97.50 214 | 92.12 165 | 92.06 189 | 98.79 148 | 84.69 189 | 98.67 156 | 95.29 126 | 99.66 75 | 99.09 176 |
|
conf0.01 | | | 96.52 112 | 95.88 112 | 98.41 115 | 98.59 118 | 97.38 87 | 99.87 71 | 98.91 42 | 91.32 187 | 95.22 156 | 98.83 137 | 96.57 15 | 98.66 158 | 89.55 214 | 94.09 188 | 99.20 159 |
|
conf0.002 | | | 96.52 112 | 95.88 112 | 98.41 115 | 98.59 118 | 97.38 87 | 99.87 71 | 98.91 42 | 91.32 187 | 95.22 156 | 98.83 137 | 96.57 15 | 98.66 158 | 89.55 214 | 94.09 188 | 99.20 159 |
|
thresconf0.02 | | | 96.53 107 | 95.88 112 | 98.48 103 | 98.59 118 | 97.38 87 | 99.87 71 | 98.91 42 | 91.32 187 | 95.22 156 | 98.83 137 | 96.57 15 | 98.66 158 | 89.55 214 | 94.09 188 | 99.40 136 |
|
tfpn_n400 | | | 96.53 107 | 95.88 112 | 98.48 103 | 98.59 118 | 97.38 87 | 99.87 71 | 98.91 42 | 91.32 187 | 95.22 156 | 98.83 137 | 96.57 15 | 98.66 158 | 89.55 214 | 94.09 188 | 99.40 136 |
|
tfpnconf | | | 96.53 107 | 95.88 112 | 98.48 103 | 98.59 118 | 97.38 87 | 99.87 71 | 98.91 42 | 91.32 187 | 95.22 156 | 98.83 137 | 96.57 15 | 98.66 158 | 89.55 214 | 94.09 188 | 99.40 136 |
|
tfpnview11 | | | 96.53 107 | 95.88 112 | 98.48 103 | 98.59 118 | 97.38 87 | 99.87 71 | 98.91 42 | 91.32 187 | 95.22 156 | 98.83 137 | 96.57 15 | 98.66 158 | 89.55 214 | 94.09 188 | 99.40 136 |
|
MDTV_nov1_ep13 | | | | 95.69 123 | | 97.90 153 | 94.15 175 | 95.98 315 | 98.44 107 | 93.12 123 | 97.98 97 | 95.74 230 | 95.10 42 | 98.58 164 | 90.02 210 | 96.92 144 | |
|
jason | | | 97.24 79 | 96.86 78 | 98.38 117 | 95.73 222 | 97.32 93 | 99.97 12 | 97.40 224 | 95.34 63 | 98.60 77 | 99.54 86 | 87.70 162 | 98.56 165 | 97.94 83 | 99.47 88 | 99.25 155 |
jason: jason. |
EPP-MVSNet | | | 96.69 101 | 96.60 87 | 96.96 158 | 97.74 166 | 93.05 208 | 99.37 181 | 98.56 84 | 88.75 232 | 95.83 142 | 99.01 116 | 96.01 24 | 98.56 165 | 96.92 108 | 97.20 138 | 99.25 155 |
|
BH-untuned | | | 95.18 146 | 94.83 145 | 96.22 178 | 98.36 132 | 91.22 251 | 99.80 100 | 97.32 231 | 90.91 199 | 91.08 194 | 98.67 151 | 83.51 196 | 98.54 167 | 94.23 147 | 99.61 80 | 98.92 180 |
|
tpmp4_e23 | | | 95.15 149 | 94.69 149 | 96.55 170 | 97.84 158 | 91.77 239 | 97.10 298 | 97.91 177 | 88.33 239 | 97.19 111 | 95.06 258 | 93.92 77 | 98.51 168 | 89.64 213 | 95.19 170 | 99.37 142 |
|
PAPM | | | 98.60 25 | 98.42 25 | 99.14 51 | 96.05 210 | 98.96 13 | 99.90 59 | 99.35 27 | 96.68 28 | 98.35 86 | 99.66 77 | 96.45 21 | 98.51 168 | 99.45 24 | 99.89 54 | 99.96 57 |
|
OPM-MVS | | | 93.21 186 | 92.80 182 | 94.44 228 | 93.12 282 | 90.85 256 | 99.77 109 | 97.61 202 | 96.19 41 | 91.56 191 | 98.65 153 | 75.16 283 | 98.47 170 | 93.78 158 | 89.39 213 | 93.99 255 |
|
ACMP | | 92.05 9 | 92.74 193 | 92.42 190 | 93.73 249 | 95.91 215 | 88.72 278 | 99.81 97 | 97.53 209 | 94.13 91 | 87.00 259 | 98.23 170 | 74.07 289 | 98.47 170 | 96.22 114 | 88.86 219 | 93.99 255 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
CLD-MVS | | | 94.06 171 | 93.90 161 | 94.55 225 | 96.02 211 | 90.69 257 | 99.98 6 | 97.72 192 | 96.62 30 | 91.05 195 | 98.85 136 | 77.21 264 | 98.47 170 | 98.11 74 | 89.51 212 | 94.48 215 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
ACMM | | 91.95 10 | 92.88 191 | 92.52 188 | 93.98 245 | 95.75 221 | 89.08 276 | 99.77 109 | 97.52 211 | 93.00 125 | 89.95 209 | 97.99 176 | 76.17 275 | 98.46 173 | 93.63 161 | 88.87 218 | 94.39 223 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
dp | | | 95.05 150 | 94.43 152 | 96.91 159 | 97.99 149 | 92.73 215 | 96.29 310 | 97.98 170 | 89.70 217 | 95.93 136 | 94.67 277 | 93.83 83 | 98.45 174 | 86.91 252 | 96.53 148 | 99.54 120 |
|
ACMH+ | | 89.98 16 | 90.35 243 | 89.54 239 | 92.78 267 | 95.99 212 | 86.12 296 | 98.81 236 | 97.18 238 | 89.38 218 | 83.14 288 | 97.76 180 | 68.42 310 | 98.43 175 | 89.11 223 | 86.05 244 | 93.78 274 |
|
ITE_SJBPF | | | | | 92.38 278 | 95.69 227 | 85.14 303 | | 95.71 301 | 92.81 131 | 89.33 231 | 98.11 172 | 70.23 304 | 98.42 176 | 85.91 260 | 88.16 230 | 93.59 281 |
|
Fast-Effi-MVS+ | | | 95.02 151 | 94.19 156 | 97.52 143 | 97.88 154 | 94.55 169 | 99.97 12 | 97.08 245 | 88.85 231 | 94.47 169 | 97.96 177 | 84.59 190 | 98.41 177 | 89.84 211 | 97.10 140 | 99.59 110 |
|
ACMH | | 89.72 17 | 90.64 237 | 89.63 236 | 93.66 253 | 95.64 228 | 88.64 281 | 98.55 253 | 97.45 217 | 89.03 223 | 81.62 293 | 97.61 181 | 69.75 305 | 98.41 177 | 89.37 220 | 87.62 236 | 93.92 264 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
LPG-MVS_test | | | 92.96 189 | 92.71 184 | 93.71 251 | 95.43 230 | 88.67 279 | 99.75 116 | 97.62 199 | 92.81 131 | 90.05 204 | 98.49 162 | 75.24 281 | 98.40 179 | 95.84 121 | 89.12 214 | 94.07 244 |
|
LGP-MVS_train | | | | | 93.71 251 | 95.43 230 | 88.67 279 | | 97.62 199 | 92.81 131 | 90.05 204 | 98.49 162 | 75.24 281 | 98.40 179 | 95.84 121 | 89.12 214 | 94.07 244 |
|
XVG-ACMP-BASELINE | | | 91.22 226 | 90.75 209 | 92.63 269 | 93.73 255 | 85.61 299 | 98.52 257 | 97.44 218 | 92.77 135 | 89.90 211 | 96.85 205 | 66.64 315 | 98.39 181 | 92.29 176 | 88.61 223 | 93.89 267 |
|
HQP4-MVS | | | | | | | | | | | 93.37 176 | | | 98.39 181 | | | 94.53 211 |
|
HQP-MVS | | | 94.61 161 | 94.50 151 | 94.92 209 | 95.78 216 | 91.85 235 | 99.87 71 | 97.89 179 | 96.82 21 | 93.37 176 | 98.65 153 | 80.65 236 | 98.39 181 | 97.92 84 | 89.60 207 | 94.53 211 |
|
TDRefinement | | | 84.76 295 | 82.56 299 | 91.38 290 | 74.58 341 | 84.80 306 | 97.36 293 | 94.56 327 | 84.73 286 | 80.21 298 | 96.12 226 | 63.56 323 | 98.39 181 | 87.92 233 | 63.97 336 | 90.95 315 |
|
EPMVS | | | 96.53 107 | 96.01 100 | 98.09 128 | 98.43 130 | 96.12 133 | 96.36 308 | 99.43 24 | 93.53 116 | 97.64 102 | 95.04 260 | 94.41 58 | 98.38 185 | 91.13 191 | 98.11 116 | 99.75 86 |
|
HQP_MVS | | | 94.49 165 | 94.36 153 | 94.87 212 | 95.71 225 | 91.74 240 | 99.84 90 | 97.87 181 | 96.38 34 | 93.01 180 | 98.59 157 | 80.47 240 | 98.37 186 | 97.79 87 | 89.55 210 | 94.52 213 |
|
plane_prior5 | | | | | | | | | 97.87 181 | | | | | 98.37 186 | 97.79 87 | 89.55 210 | 94.52 213 |
|
TinyColmap | | | 87.87 272 | 86.51 273 | 91.94 285 | 95.05 236 | 85.57 300 | 97.65 289 | 94.08 330 | 84.40 290 | 81.82 292 | 96.85 205 | 62.14 326 | 98.33 188 | 80.25 294 | 86.37 243 | 91.91 306 |
|
CMPMVS | | 61.59 21 | 84.75 296 | 85.14 278 | 83.57 316 | 90.32 317 | 62.54 340 | 96.98 301 | 97.59 204 | 74.33 329 | 69.95 329 | 96.66 210 | 64.17 321 | 98.32 189 | 87.88 234 | 88.41 227 | 89.84 330 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
USDC | | | 90.00 252 | 88.96 250 | 93.10 261 | 94.81 239 | 88.16 287 | 98.71 241 | 95.54 307 | 93.66 113 | 83.75 286 | 97.20 190 | 65.58 317 | 98.31 190 | 83.96 275 | 87.49 238 | 92.85 297 |
|
TESTMET0.1,1 | | | 96.74 98 | 96.26 95 | 98.16 122 | 97.36 179 | 96.48 116 | 99.96 19 | 98.29 139 | 91.93 171 | 95.77 143 | 98.07 174 | 95.54 34 | 98.29 191 | 90.55 201 | 98.89 100 | 99.70 92 |
|
CostFormer | | | 96.10 128 | 95.88 112 | 96.78 163 | 97.03 185 | 92.55 221 | 97.08 299 | 97.83 186 | 90.04 213 | 98.72 70 | 94.89 269 | 95.01 47 | 98.29 191 | 96.54 111 | 95.77 161 | 99.50 125 |
|
LTVRE_ROB | | 88.28 18 | 90.29 246 | 89.05 249 | 94.02 241 | 95.08 234 | 90.15 266 | 97.19 297 | 97.43 219 | 84.91 284 | 83.99 284 | 97.06 196 | 74.00 290 | 98.28 193 | 84.08 272 | 87.71 234 | 93.62 280 |
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 |
test-LLR | | | 96.47 114 | 96.04 99 | 97.78 135 | 97.02 186 | 95.44 149 | 99.96 19 | 98.21 147 | 94.07 95 | 95.55 145 | 96.38 217 | 93.90 80 | 98.27 194 | 90.42 203 | 98.83 102 | 99.64 102 |
|
test-mter | | | 96.39 120 | 95.93 108 | 97.78 135 | 97.02 186 | 95.44 149 | 99.96 19 | 98.21 147 | 91.81 175 | 95.55 145 | 96.38 217 | 95.17 40 | 98.27 194 | 90.42 203 | 98.83 102 | 99.64 102 |
|
HyFIR lowres test | | | 96.66 104 | 96.43 91 | 97.36 151 | 99.05 88 | 93.91 180 | 99.70 132 | 99.80 3 | 90.54 204 | 96.26 131 | 98.08 173 | 92.15 112 | 98.23 196 | 96.84 109 | 95.46 166 | 99.93 65 |
|
CHOSEN 280x420 | | | 99.01 10 | 99.03 5 | 98.95 74 | 99.38 82 | 98.87 19 | 98.46 260 | 99.42 25 | 97.03 17 | 99.02 58 | 99.09 111 | 99.35 1 | 98.21 197 | 99.73 15 | 99.78 68 | 99.77 84 |
|
ADS-MVSNet | | | 94.79 154 | 94.02 159 | 97.11 157 | 97.87 155 | 93.79 182 | 94.24 321 | 98.16 155 | 90.07 211 | 96.43 127 | 94.48 281 | 90.29 136 | 98.19 198 | 87.44 238 | 97.23 136 | 99.36 143 |
|
test_post | | | | | | | | | | | | 63.35 350 | 94.43 57 | 98.13 199 | | | |
|
LF4IMVS | | | 89.25 262 | 88.85 251 | 90.45 298 | 92.81 290 | 81.19 321 | 98.12 280 | 94.79 324 | 91.44 184 | 86.29 271 | 97.11 192 | 65.30 319 | 98.11 200 | 88.53 227 | 85.25 249 | 92.07 302 |
|
IS-MVSNet | | | 96.29 125 | 95.90 111 | 97.45 146 | 98.13 144 | 94.80 164 | 99.08 206 | 97.61 202 | 92.02 170 | 95.54 147 | 98.96 121 | 90.64 133 | 98.08 201 | 93.73 160 | 97.41 131 | 99.47 127 |
|
DeepMVS_CX | | | | | 82.92 320 | 95.98 214 | 58.66 344 | | 96.01 297 | 92.72 136 | 78.34 304 | 95.51 236 | 58.29 333 | 98.08 201 | 82.57 283 | 85.29 248 | 92.03 304 |
|
PatchmatchNet | | | 95.94 132 | 95.45 131 | 97.39 150 | 97.83 159 | 94.41 171 | 96.05 314 | 98.40 124 | 92.86 127 | 97.09 114 | 95.28 251 | 94.21 71 | 98.07 203 | 89.26 222 | 98.11 116 | 99.70 92 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
MS-PatchMatch | | | 90.65 236 | 90.30 219 | 91.71 288 | 94.22 247 | 85.50 301 | 98.24 275 | 97.70 193 | 88.67 233 | 86.42 269 | 96.37 219 | 67.82 312 | 98.03 204 | 83.62 277 | 99.62 77 | 91.60 309 |
|
Patchmatch-test | | | 92.65 197 | 91.50 201 | 96.10 181 | 96.85 193 | 90.49 260 | 91.50 335 | 97.19 237 | 82.76 297 | 90.23 201 | 95.59 235 | 95.02 46 | 98.00 205 | 77.41 311 | 96.98 143 | 99.82 78 |
|
tpm2 | | | 95.47 142 | 95.18 140 | 96.35 176 | 96.91 190 | 91.70 244 | 96.96 302 | 97.93 175 | 88.04 243 | 98.44 81 | 95.40 239 | 93.32 91 | 97.97 206 | 94.00 151 | 95.61 164 | 99.38 140 |
|
JIA-IIPM | | | 91.76 213 | 90.70 210 | 94.94 207 | 96.11 208 | 87.51 290 | 93.16 328 | 98.13 160 | 75.79 325 | 97.58 104 | 77.68 340 | 92.84 99 | 97.97 206 | 88.47 228 | 96.54 147 | 99.33 147 |
|
VPA-MVSNet | | | 92.70 194 | 91.55 200 | 96.16 179 | 95.09 233 | 96.20 127 | 98.88 229 | 99.00 35 | 91.02 198 | 91.82 190 | 95.29 250 | 76.05 277 | 97.96 208 | 95.62 124 | 81.19 267 | 94.30 231 |
|
patchmatchnet-post | | | | | | | | | | | | 91.70 307 | 95.12 41 | 97.95 209 | | | |
|
GG-mvs-BLEND | | | | | 98.54 99 | 98.21 139 | 98.01 64 | 93.87 325 | 98.52 91 | | 97.92 98 | 97.92 178 | 99.02 2 | 97.94 210 | 98.17 71 | 99.58 82 | 99.67 96 |
|
Effi-MVS+-dtu | | | 94.53 164 | 95.30 136 | 92.22 282 | 97.77 163 | 82.54 313 | 99.59 154 | 97.06 246 | 94.92 69 | 95.29 150 | 95.37 244 | 85.81 180 | 97.89 211 | 94.80 133 | 97.07 141 | 96.23 207 |
|
XXY-MVS | | | 91.82 207 | 90.46 214 | 95.88 185 | 93.91 252 | 95.40 152 | 98.87 232 | 97.69 194 | 88.63 235 | 87.87 251 | 97.08 194 | 74.38 288 | 97.89 211 | 91.66 187 | 84.07 255 | 94.35 228 |
|
gg-mvs-nofinetune | | | 93.51 182 | 91.86 197 | 98.47 107 | 97.72 170 | 97.96 65 | 92.62 330 | 98.51 97 | 74.70 328 | 97.33 108 | 69.59 344 | 98.91 3 | 97.79 213 | 97.77 89 | 99.56 83 | 99.67 96 |
|
test_post1 | | | | | | | | 95.78 318 | | | | 59.23 353 | 93.20 95 | 97.74 214 | 91.06 193 | | |
|
nrg030 | | | 93.51 182 | 92.53 187 | 96.45 172 | 94.36 244 | 97.20 96 | 99.81 97 | 97.16 241 | 91.60 178 | 89.86 213 | 97.46 183 | 86.37 176 | 97.68 215 | 95.88 119 | 80.31 277 | 94.46 216 |
|
Fast-Effi-MVS+-dtu | | | 93.72 179 | 93.86 163 | 93.29 258 | 97.06 184 | 86.16 295 | 99.80 100 | 96.83 279 | 92.66 141 | 92.58 187 | 97.83 179 | 81.39 224 | 97.67 216 | 89.75 212 | 96.87 145 | 96.05 209 |
|
GA-MVS | | | 93.83 173 | 92.84 181 | 96.80 162 | 95.73 222 | 93.57 188 | 99.88 66 | 97.24 235 | 92.57 151 | 92.92 182 | 96.66 210 | 78.73 257 | 97.67 216 | 87.75 235 | 94.06 195 | 99.17 164 |
|
VPNet | | | 91.81 208 | 90.46 214 | 95.85 187 | 94.74 240 | 95.54 148 | 98.98 220 | 98.59 79 | 92.14 164 | 90.77 198 | 97.44 184 | 68.73 308 | 97.54 218 | 94.89 132 | 77.89 297 | 94.46 216 |
|
MVS-HIRNet | | | 86.22 282 | 83.19 297 | 95.31 194 | 96.71 202 | 90.29 263 | 92.12 332 | 97.33 230 | 62.85 339 | 86.82 262 | 70.37 343 | 69.37 306 | 97.49 219 | 75.12 317 | 97.99 121 | 98.15 191 |
|
Vis-MVSNet (Re-imp) | | | 96.32 122 | 95.98 103 | 97.35 152 | 97.93 152 | 94.82 163 | 99.47 170 | 98.15 157 | 91.83 174 | 95.09 162 | 99.11 110 | 91.37 122 | 97.47 220 | 93.47 162 | 97.43 129 | 99.74 87 |
|
Test4 | | | 88.80 266 | 85.91 275 | 97.48 145 | 87.33 325 | 95.72 143 | 99.29 190 | 97.04 255 | 92.82 130 | 70.35 328 | 91.46 308 | 44.37 343 | 97.43 221 | 93.37 165 | 97.17 139 | 99.29 152 |
|
tfpnnormal | | | 89.29 261 | 87.61 267 | 94.34 232 | 94.35 245 | 94.13 176 | 98.95 224 | 98.94 38 | 83.94 291 | 84.47 282 | 95.51 236 | 74.84 284 | 97.39 222 | 77.05 314 | 80.41 275 | 91.48 311 |
|
v6 | | | 91.44 216 | 90.27 222 | 94.93 208 | 93.44 264 | 93.44 191 | 99.73 125 | 97.05 250 | 87.57 245 | 90.05 204 | 95.10 257 | 81.87 214 | 97.39 222 | 87.45 237 | 80.17 278 | 93.98 259 |
|
jajsoiax | | | 91.92 206 | 91.18 205 | 94.15 236 | 91.35 309 | 90.95 254 | 99.00 219 | 97.42 221 | 92.61 145 | 87.38 255 | 97.08 194 | 72.46 294 | 97.36 224 | 94.53 140 | 88.77 220 | 94.13 241 |
|
EPNet_dtu | | | 95.71 137 | 95.39 133 | 96.66 168 | 98.92 100 | 93.41 196 | 99.57 156 | 98.90 50 | 96.19 41 | 97.52 105 | 98.56 160 | 92.65 104 | 97.36 224 | 77.89 308 | 98.33 111 | 99.20 159 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
Patchmatch-test1 | | | 94.39 167 | 93.46 171 | 97.17 154 | 97.10 182 | 94.44 170 | 98.86 234 | 98.32 136 | 93.30 121 | 96.17 133 | 95.38 242 | 76.48 272 | 97.34 226 | 88.12 232 | 97.43 129 | 99.74 87 |
|
V42 | | | 91.28 224 | 90.12 230 | 94.74 216 | 93.42 266 | 93.46 190 | 99.68 138 | 97.02 256 | 87.36 254 | 89.85 214 | 95.05 259 | 81.31 226 | 97.34 226 | 87.34 243 | 80.07 281 | 93.40 284 |
|
v1 | | | 91.36 220 | 90.14 228 | 95.04 201 | 93.35 270 | 93.80 181 | 99.77 109 | 97.05 250 | 87.53 249 | 89.77 216 | 94.91 267 | 81.99 208 | 97.33 228 | 86.90 254 | 79.98 284 | 94.00 252 |
|
v1neww | | | 91.44 216 | 90.28 220 | 94.91 210 | 93.50 260 | 93.43 192 | 99.73 125 | 97.06 246 | 87.55 246 | 90.08 202 | 95.11 255 | 81.98 209 | 97.32 229 | 87.41 240 | 80.15 279 | 93.99 255 |
|
mvs_tets | | | 91.81 208 | 91.08 206 | 94.00 243 | 91.63 307 | 90.58 258 | 98.67 246 | 97.43 219 | 92.43 156 | 87.37 256 | 97.05 197 | 71.76 296 | 97.32 229 | 94.75 136 | 88.68 222 | 94.11 242 |
|
v7new | | | 91.44 216 | 90.28 220 | 94.91 210 | 93.50 260 | 93.43 192 | 99.73 125 | 97.06 246 | 87.55 246 | 90.08 202 | 95.11 255 | 81.98 209 | 97.32 229 | 87.41 240 | 80.15 279 | 93.99 255 |
|
EI-MVSNet | | | 93.73 178 | 93.40 176 | 94.74 216 | 96.80 196 | 92.69 216 | 99.06 212 | 97.67 195 | 88.96 227 | 91.39 192 | 99.02 114 | 88.75 155 | 97.30 232 | 91.07 192 | 87.85 232 | 94.22 236 |
|
MVSTER | | | 95.53 140 | 95.22 138 | 96.45 172 | 98.56 124 | 97.72 70 | 99.91 56 | 97.67 195 | 92.38 157 | 91.39 192 | 97.14 191 | 97.24 10 | 97.30 232 | 94.80 133 | 87.85 232 | 94.34 229 |
|
TAMVS | | | 95.85 133 | 95.58 129 | 96.65 169 | 97.07 183 | 93.50 189 | 99.17 199 | 97.82 187 | 91.39 186 | 95.02 163 | 98.01 175 | 92.20 110 | 97.30 232 | 93.75 159 | 95.83 160 | 99.14 171 |
|
PS-MVSNAJss | | | 93.64 181 | 93.31 178 | 94.61 221 | 92.11 297 | 92.19 227 | 99.12 201 | 97.38 226 | 92.51 154 | 88.45 242 | 96.99 200 | 91.20 124 | 97.29 235 | 94.36 142 | 87.71 234 | 94.36 225 |
|
OurMVSNet-221017-0 | | | 89.81 253 | 89.48 243 | 90.83 294 | 91.64 306 | 81.21 320 | 98.17 279 | 95.38 316 | 91.48 182 | 85.65 277 | 97.31 187 | 72.66 293 | 97.29 235 | 88.15 230 | 84.83 252 | 93.97 260 |
|
MVP-Stereo | | | 90.93 230 | 90.45 216 | 92.37 279 | 91.25 311 | 88.76 277 | 98.05 284 | 96.17 294 | 87.27 256 | 84.04 283 | 95.30 247 | 78.46 260 | 97.27 237 | 83.78 276 | 99.70 73 | 91.09 312 |
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
v1141 | | | 91.36 220 | 90.14 228 | 95.00 203 | 93.33 272 | 93.79 182 | 99.78 104 | 97.05 250 | 87.52 250 | 89.75 217 | 94.89 269 | 82.13 205 | 97.21 238 | 86.84 255 | 80.00 283 | 94.00 252 |
|
divwei89l23v2f112 | | | 91.37 219 | 90.15 227 | 95.00 203 | 93.35 270 | 93.78 185 | 99.78 104 | 97.05 250 | 87.54 248 | 89.73 218 | 94.89 269 | 82.24 204 | 97.21 238 | 86.91 252 | 79.90 285 | 94.00 252 |
|
v8 | | | 90.54 240 | 89.17 245 | 94.66 219 | 93.43 265 | 93.40 199 | 99.20 196 | 96.94 270 | 85.76 275 | 87.56 253 | 94.51 279 | 81.96 212 | 97.19 240 | 84.94 268 | 78.25 294 | 93.38 286 |
|
testing_2 | | | 85.10 294 | 81.72 301 | 95.22 196 | 82.25 334 | 94.16 174 | 97.54 290 | 97.01 259 | 88.15 240 | 62.23 336 | 86.43 333 | 44.43 342 | 97.18 241 | 92.28 181 | 85.20 251 | 94.31 230 |
|
v52 | | | 89.55 256 | 88.41 258 | 92.98 262 | 92.32 294 | 90.01 268 | 98.88 229 | 96.89 274 | 84.51 288 | 86.89 260 | 94.22 286 | 79.23 249 | 97.16 242 | 84.46 270 | 78.27 293 | 91.76 307 |
|
mvs_anonymous | | | 95.65 139 | 95.03 143 | 97.53 142 | 98.19 140 | 95.74 141 | 99.33 185 | 97.49 215 | 90.87 200 | 90.47 200 | 97.10 193 | 88.23 159 | 97.16 242 | 95.92 118 | 97.66 125 | 99.68 95 |
|
V4 | | | 89.55 256 | 88.41 258 | 92.98 262 | 92.21 296 | 90.03 267 | 98.87 232 | 96.91 272 | 84.51 288 | 86.84 261 | 94.21 287 | 79.37 248 | 97.15 244 | 84.45 271 | 78.28 292 | 91.76 307 |
|
v2v482 | | | 91.30 222 | 90.07 231 | 95.01 202 | 93.13 280 | 93.79 182 | 99.77 109 | 97.02 256 | 88.05 242 | 89.25 232 | 95.37 244 | 80.73 234 | 97.15 244 | 87.28 244 | 80.04 282 | 94.09 243 |
|
v7 | | | 91.20 227 | 89.99 232 | 94.82 215 | 93.57 257 | 93.41 196 | 99.57 156 | 96.98 262 | 86.83 262 | 89.88 212 | 95.22 252 | 81.01 229 | 97.14 246 | 85.53 262 | 81.31 266 | 93.90 265 |
|
UniMVSNet (Re) | | | 93.07 188 | 92.13 192 | 95.88 185 | 94.84 238 | 96.24 126 | 99.88 66 | 98.98 36 | 92.49 155 | 89.25 232 | 95.40 239 | 87.09 169 | 97.14 246 | 93.13 171 | 78.16 295 | 94.26 233 |
|
v7n | | | 89.65 255 | 88.29 260 | 93.72 250 | 92.22 295 | 90.56 259 | 99.07 210 | 97.10 244 | 85.42 282 | 86.73 263 | 94.72 273 | 80.06 243 | 97.13 248 | 81.14 291 | 78.12 296 | 93.49 282 |
|
CDS-MVSNet | | | 96.34 121 | 96.07 98 | 97.13 155 | 97.37 178 | 94.96 160 | 99.53 163 | 97.91 177 | 91.55 180 | 95.37 149 | 98.32 169 | 95.05 45 | 97.13 248 | 93.80 157 | 95.75 162 | 99.30 150 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
EG-PatchMatch MVS | | | 85.35 293 | 83.81 294 | 89.99 303 | 90.39 316 | 81.89 318 | 98.21 278 | 96.09 296 | 81.78 308 | 74.73 315 | 93.72 295 | 51.56 340 | 97.12 250 | 79.16 302 | 88.61 223 | 90.96 314 |
|
v144192 | | | 90.79 234 | 89.52 240 | 94.59 222 | 93.11 283 | 92.77 213 | 99.56 158 | 96.99 260 | 86.38 267 | 89.82 215 | 94.95 266 | 80.50 239 | 97.10 251 | 83.98 274 | 80.41 275 | 93.90 265 |
|
FIs | | | 94.10 170 | 93.43 172 | 96.11 180 | 94.70 241 | 96.82 108 | 99.58 155 | 98.93 41 | 92.54 152 | 89.34 230 | 97.31 187 | 87.62 163 | 97.10 251 | 94.22 148 | 86.58 241 | 94.40 222 |
|
v1192 | | | 90.62 239 | 89.25 244 | 94.72 218 | 93.13 280 | 93.07 206 | 99.50 166 | 97.02 256 | 86.33 268 | 89.56 226 | 95.01 261 | 79.22 250 | 97.09 253 | 82.34 285 | 81.16 268 | 94.01 249 |
|
v1144 | | | 91.09 228 | 89.83 233 | 94.87 212 | 93.25 277 | 93.69 187 | 99.62 152 | 96.98 262 | 86.83 262 | 89.64 223 | 94.99 264 | 80.94 230 | 97.05 254 | 85.08 267 | 81.16 268 | 93.87 269 |
|
v148 | | | 90.70 235 | 89.63 236 | 93.92 246 | 92.97 286 | 90.97 253 | 99.75 116 | 96.89 274 | 87.51 251 | 88.27 247 | 95.01 261 | 81.67 217 | 97.04 255 | 87.40 242 | 77.17 305 | 93.75 275 |
|
v748 | | | 88.94 265 | 87.72 266 | 92.61 270 | 91.91 300 | 87.50 291 | 99.07 210 | 96.97 265 | 84.76 285 | 85.79 276 | 93.63 296 | 79.19 251 | 97.04 255 | 83.16 280 | 75.03 315 | 93.28 287 |
|
pm-mvs1 | | | 89.36 260 | 87.81 265 | 94.01 242 | 93.40 268 | 91.93 233 | 98.62 250 | 96.48 291 | 86.25 269 | 83.86 285 | 96.14 224 | 73.68 291 | 97.04 255 | 86.16 258 | 75.73 312 | 93.04 293 |
|
v1921920 | | | 90.46 241 | 89.12 246 | 94.50 226 | 92.96 287 | 92.46 222 | 99.49 167 | 96.98 262 | 86.10 270 | 89.61 225 | 95.30 247 | 78.55 259 | 97.03 258 | 82.17 286 | 80.89 274 | 94.01 249 |
|
v1240 | | | 90.20 248 | 88.79 253 | 94.44 228 | 93.05 285 | 92.27 226 | 99.38 180 | 96.92 271 | 85.89 272 | 89.36 229 | 94.87 272 | 77.89 263 | 97.03 258 | 80.66 293 | 81.08 270 | 94.01 249 |
|
v10 | | | 90.25 247 | 88.82 252 | 94.57 224 | 93.53 259 | 93.43 192 | 99.08 206 | 96.87 277 | 85.00 283 | 87.34 257 | 94.51 279 | 80.93 231 | 97.02 260 | 82.85 282 | 79.23 287 | 93.26 288 |
|
lessismore_v0 | | | | | 90.53 295 | 90.58 315 | 80.90 323 | | 95.80 300 | | 77.01 306 | 95.84 228 | 66.15 316 | 96.95 261 | 83.03 281 | 75.05 314 | 93.74 278 |
|
OpenMVS_ROB | | 79.82 20 | 83.77 302 | 81.68 302 | 90.03 302 | 88.30 323 | 82.82 311 | 98.46 260 | 95.22 320 | 73.92 331 | 76.00 311 | 91.29 309 | 55.00 336 | 96.94 262 | 68.40 325 | 88.51 226 | 90.34 317 |
|
anonymousdsp | | | 91.79 212 | 90.92 208 | 94.41 231 | 90.76 314 | 92.93 211 | 98.93 226 | 97.17 240 | 89.08 221 | 87.46 254 | 95.30 247 | 78.43 261 | 96.92 263 | 92.38 175 | 88.73 221 | 93.39 285 |
|
MVSFormer | | | 96.94 88 | 96.60 87 | 97.95 131 | 97.28 180 | 97.70 73 | 99.55 160 | 97.27 233 | 91.17 193 | 99.43 37 | 99.54 86 | 90.92 130 | 96.89 264 | 94.67 137 | 99.62 77 | 99.25 155 |
|
test_djsdf | | | 92.83 192 | 92.29 191 | 94.47 227 | 91.90 301 | 92.46 222 | 99.55 160 | 97.27 233 | 91.17 193 | 89.96 208 | 96.07 227 | 81.10 228 | 96.89 264 | 94.67 137 | 88.91 216 | 94.05 246 |
|
pmmvs6 | | | 85.69 288 | 83.84 293 | 91.26 291 | 90.00 319 | 84.41 307 | 97.82 288 | 96.15 295 | 75.86 324 | 81.29 294 | 95.39 241 | 61.21 328 | 96.87 266 | 83.52 279 | 73.29 318 | 92.50 299 |
|
tpm | | | 93.70 180 | 93.41 175 | 94.58 223 | 95.36 232 | 87.41 292 | 97.01 300 | 96.90 273 | 90.85 201 | 96.72 121 | 94.14 288 | 90.40 134 | 96.84 267 | 90.75 199 | 88.54 225 | 99.51 123 |
|
FC-MVSNet-test | | | 93.81 175 | 93.15 179 | 95.80 188 | 94.30 246 | 96.20 127 | 99.42 175 | 98.89 51 | 92.33 158 | 89.03 237 | 97.27 189 | 87.39 166 | 96.83 268 | 93.20 167 | 86.48 242 | 94.36 225 |
|
pmmvs4 | | | 92.10 205 | 91.07 207 | 95.18 197 | 92.82 289 | 94.96 160 | 99.48 169 | 96.83 279 | 87.45 253 | 88.66 241 | 96.56 215 | 83.78 195 | 96.83 268 | 89.29 221 | 84.77 253 | 93.75 275 |
|
WR-MVS | | | 92.31 202 | 91.25 204 | 95.48 192 | 94.45 243 | 95.29 154 | 99.60 153 | 98.68 64 | 90.10 210 | 88.07 249 | 96.89 202 | 80.68 235 | 96.80 270 | 93.14 170 | 79.67 286 | 94.36 225 |
|
UniMVSNet_NR-MVSNet | | | 92.95 190 | 92.11 193 | 95.49 190 | 94.61 242 | 95.28 155 | 99.83 94 | 99.08 32 | 91.49 181 | 89.21 234 | 96.86 204 | 87.14 168 | 96.73 271 | 93.20 167 | 77.52 301 | 94.46 216 |
|
DU-MVS | | | 92.46 200 | 91.45 203 | 95.49 190 | 94.05 249 | 95.28 155 | 99.81 97 | 98.74 60 | 92.25 159 | 89.21 234 | 96.64 212 | 81.66 218 | 96.73 271 | 93.20 167 | 77.52 301 | 94.46 216 |
|
SixPastTwentyTwo | | | 88.73 267 | 88.01 264 | 90.88 292 | 91.85 303 | 82.24 315 | 98.22 277 | 95.18 322 | 88.97 226 | 82.26 291 | 96.89 202 | 71.75 297 | 96.67 273 | 84.00 273 | 82.98 259 | 93.72 279 |
|
WR-MVS_H | | | 91.30 222 | 90.35 217 | 94.15 236 | 94.17 248 | 92.62 220 | 99.17 199 | 98.94 38 | 88.87 230 | 86.48 268 | 94.46 283 | 84.36 192 | 96.61 274 | 88.19 229 | 78.51 291 | 93.21 290 |
|
NR-MVSNet | | | 91.56 215 | 90.22 224 | 95.60 189 | 94.05 249 | 95.76 140 | 98.25 274 | 98.70 62 | 91.16 195 | 80.78 296 | 96.64 212 | 83.23 200 | 96.57 275 | 91.41 188 | 77.73 299 | 94.46 216 |
|
Baseline_NR-MVSNet | | | 90.33 244 | 89.51 241 | 92.81 266 | 92.84 288 | 89.95 270 | 99.77 109 | 93.94 332 | 84.69 287 | 89.04 236 | 95.66 233 | 81.66 218 | 96.52 276 | 90.99 194 | 76.98 306 | 91.97 305 |
|
pmmvs5 | | | 90.17 250 | 89.09 247 | 93.40 256 | 92.10 298 | 89.77 273 | 99.74 119 | 95.58 305 | 85.88 273 | 87.24 258 | 95.74 230 | 73.41 292 | 96.48 277 | 88.54 226 | 83.56 258 | 93.95 261 |
|
TransMVSNet (Re) | | | 87.25 273 | 85.28 277 | 93.16 259 | 93.56 258 | 91.03 252 | 98.54 255 | 94.05 331 | 83.69 293 | 81.09 295 | 96.16 223 | 75.32 280 | 96.40 278 | 76.69 315 | 68.41 323 | 92.06 303 |
|
CP-MVSNet | | | 91.23 225 | 90.22 224 | 94.26 233 | 93.96 251 | 92.39 224 | 99.09 204 | 98.57 82 | 88.95 228 | 86.42 269 | 96.57 214 | 79.19 251 | 96.37 279 | 90.29 207 | 78.95 288 | 94.02 247 |
|
ambc | | | | | 83.23 317 | 77.17 340 | 62.61 339 | 87.38 342 | 94.55 328 | | 76.72 308 | 86.65 332 | 30.16 347 | 96.36 280 | 84.85 269 | 69.86 319 | 90.73 316 |
|
IterMVS-LS | | | 92.69 195 | 92.11 193 | 94.43 230 | 96.80 196 | 92.74 214 | 99.45 173 | 96.89 274 | 88.98 225 | 89.65 222 | 95.38 242 | 88.77 154 | 96.34 281 | 90.98 195 | 82.04 262 | 94.22 236 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
PS-CasMVS | | | 90.63 238 | 89.51 241 | 93.99 244 | 93.83 253 | 91.70 244 | 98.98 220 | 98.52 91 | 88.48 236 | 86.15 273 | 96.53 216 | 75.46 279 | 96.31 282 | 88.83 225 | 78.86 290 | 93.95 261 |
|
FMVSNet3 | | | 92.69 195 | 91.58 199 | 95.99 182 | 98.29 133 | 97.42 85 | 99.26 193 | 97.62 199 | 89.80 216 | 89.68 219 | 95.32 246 | 81.62 220 | 96.27 283 | 87.01 249 | 85.65 245 | 94.29 232 |
|
test_0402 | | | 85.58 289 | 83.94 292 | 90.50 296 | 93.81 254 | 85.04 304 | 98.55 253 | 95.20 321 | 76.01 323 | 79.72 300 | 95.13 253 | 64.15 322 | 96.26 284 | 66.04 331 | 86.88 240 | 90.21 322 |
|
FMVSNet2 | | | 91.02 229 | 89.56 238 | 95.41 193 | 97.53 174 | 95.74 141 | 98.98 220 | 97.41 223 | 87.05 258 | 88.43 244 | 95.00 263 | 71.34 298 | 96.24 285 | 85.12 266 | 85.21 250 | 94.25 235 |
|
TranMVSNet+NR-MVSNet | | | 91.68 214 | 90.61 211 | 94.87 212 | 93.69 256 | 93.98 178 | 99.69 133 | 98.65 67 | 91.03 197 | 88.44 243 | 96.83 208 | 80.05 244 | 96.18 286 | 90.26 208 | 76.89 308 | 94.45 221 |
|
GBi-Net | | | 90.88 232 | 89.82 234 | 94.08 238 | 97.53 174 | 91.97 230 | 98.43 262 | 96.95 267 | 87.05 258 | 89.68 219 | 94.72 273 | 71.34 298 | 96.11 287 | 87.01 249 | 85.65 245 | 94.17 238 |
|
test1 | | | 90.88 232 | 89.82 234 | 94.08 238 | 97.53 174 | 91.97 230 | 98.43 262 | 96.95 267 | 87.05 258 | 89.68 219 | 94.72 273 | 71.34 298 | 96.11 287 | 87.01 249 | 85.65 245 | 94.17 238 |
|
FMVSNet1 | | | 88.50 268 | 86.64 272 | 94.08 238 | 95.62 229 | 91.97 230 | 98.43 262 | 96.95 267 | 83.00 295 | 86.08 274 | 94.72 273 | 59.09 332 | 96.11 287 | 81.82 289 | 84.07 255 | 94.17 238 |
|
PatchT | | | 90.38 242 | 88.75 254 | 95.25 195 | 95.99 212 | 90.16 265 | 91.22 337 | 97.54 207 | 76.80 322 | 97.26 109 | 86.01 335 | 91.88 116 | 96.07 290 | 66.16 330 | 95.91 158 | 99.51 123 |
|
CR-MVSNet | | | 93.45 185 | 92.62 185 | 95.94 183 | 96.29 205 | 92.66 217 | 92.01 333 | 96.23 292 | 92.62 144 | 96.94 115 | 93.31 299 | 91.04 128 | 96.03 291 | 79.23 301 | 95.96 156 | 99.13 173 |
|
Patchmtry | | | 89.70 254 | 88.49 257 | 93.33 257 | 96.24 207 | 89.94 272 | 91.37 336 | 96.23 292 | 78.22 319 | 87.69 252 | 93.31 299 | 91.04 128 | 96.03 291 | 80.18 295 | 82.10 261 | 94.02 247 |
|
RPMNet | | | 89.39 259 | 87.20 271 | 95.94 183 | 96.29 205 | 92.66 217 | 92.01 333 | 97.63 197 | 70.19 336 | 96.94 115 | 85.87 336 | 87.25 167 | 96.03 291 | 62.69 333 | 95.96 156 | 99.13 173 |
|
PEN-MVS | | | 90.19 249 | 89.06 248 | 93.57 254 | 93.06 284 | 90.90 255 | 99.06 212 | 98.47 103 | 88.11 241 | 85.91 275 | 96.30 220 | 76.67 269 | 95.94 294 | 87.07 246 | 76.91 307 | 93.89 267 |
|
testpf | | | 89.10 263 | 88.73 255 | 90.24 299 | 97.59 173 | 83.48 310 | 74.22 348 | 97.39 225 | 79.66 316 | 89.64 223 | 93.92 289 | 86.38 175 | 95.76 295 | 85.42 263 | 94.31 184 | 91.49 310 |
|
N_pmnet | | | 80.06 307 | 80.78 304 | 77.89 324 | 91.94 299 | 45.28 353 | 98.80 237 | 56.82 357 | 78.10 320 | 80.08 299 | 93.33 297 | 77.03 265 | 95.76 295 | 68.14 326 | 82.81 260 | 92.64 298 |
|
LCM-MVSNet-Re | | | 92.31 202 | 92.60 186 | 91.43 289 | 97.53 174 | 79.27 327 | 99.02 218 | 91.83 341 | 92.07 167 | 80.31 297 | 94.38 284 | 83.50 197 | 95.48 297 | 97.22 99 | 97.58 126 | 99.54 120 |
|
K. test v3 | | | 88.05 271 | 87.24 270 | 90.47 297 | 91.82 305 | 82.23 316 | 98.96 223 | 97.42 221 | 89.05 222 | 76.93 307 | 95.60 234 | 68.49 309 | 95.42 298 | 85.87 261 | 81.01 272 | 93.75 275 |
|
ADS-MVSNet2 | | | 93.80 176 | 93.88 162 | 93.55 255 | 97.87 155 | 85.94 297 | 94.24 321 | 96.84 278 | 90.07 211 | 96.43 127 | 94.48 281 | 90.29 136 | 95.37 299 | 87.44 238 | 97.23 136 | 99.36 143 |
|
CVMVSNet | | | 94.68 159 | 94.94 144 | 93.89 248 | 96.80 196 | 86.92 294 | 99.06 212 | 98.98 36 | 94.45 81 | 94.23 173 | 99.02 114 | 85.60 182 | 95.31 300 | 90.91 197 | 95.39 168 | 99.43 131 |
|
DTE-MVSNet | | | 89.40 258 | 88.24 261 | 92.88 265 | 92.66 292 | 89.95 270 | 99.10 203 | 98.22 146 | 87.29 255 | 85.12 279 | 96.22 222 | 76.27 274 | 95.30 301 | 83.56 278 | 75.74 311 | 93.41 283 |
|
LP | | | 86.76 275 | 84.85 279 | 92.50 273 | 95.08 234 | 85.89 298 | 89.97 338 | 96.97 265 | 75.28 327 | 84.97 280 | 90.68 311 | 80.78 233 | 95.13 302 | 61.64 335 | 88.31 228 | 96.46 204 |
|
IterMVS | | | 90.91 231 | 90.17 226 | 93.12 260 | 96.78 199 | 90.42 262 | 98.89 228 | 97.05 250 | 89.03 223 | 86.49 267 | 95.42 238 | 76.59 270 | 95.02 303 | 87.22 245 | 84.09 254 | 93.93 263 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
semantic-postprocess | | | | | 92.93 264 | 96.72 201 | 89.96 269 | | 96.99 260 | 88.95 228 | 86.63 264 | 95.67 232 | 76.50 271 | 95.00 304 | 87.04 247 | 84.04 257 | 93.84 271 |
|
test0.0.03 1 | | | 93.86 172 | 93.61 164 | 94.64 220 | 95.02 237 | 92.18 228 | 99.93 50 | 98.58 80 | 94.07 95 | 87.96 250 | 98.50 161 | 93.90 80 | 94.96 305 | 81.33 290 | 93.17 203 | 96.78 201 |
|
UnsupCasMVSNet_bld | | | 79.97 308 | 77.03 311 | 88.78 309 | 85.62 329 | 81.98 317 | 93.66 326 | 97.35 228 | 75.51 326 | 70.79 327 | 83.05 337 | 48.70 341 | 94.91 306 | 78.31 307 | 60.29 341 | 89.46 334 |
|
MIMVSNet | | | 90.30 245 | 88.67 256 | 95.17 198 | 96.45 204 | 91.64 246 | 92.39 331 | 97.15 242 | 85.99 271 | 90.50 199 | 93.19 301 | 66.95 314 | 94.86 307 | 82.01 287 | 93.43 199 | 99.01 179 |
|
new_pmnet | | | 84.49 298 | 82.92 298 | 89.21 306 | 90.03 318 | 82.60 312 | 96.89 303 | 95.62 304 | 80.59 313 | 75.77 313 | 89.17 313 | 65.04 320 | 94.79 308 | 72.12 319 | 81.02 271 | 90.23 321 |
|
testgi | | | 89.01 264 | 88.04 263 | 91.90 286 | 93.49 262 | 84.89 305 | 99.73 125 | 95.66 303 | 93.89 107 | 85.14 278 | 98.17 171 | 59.68 331 | 94.66 309 | 77.73 309 | 88.88 217 | 96.16 208 |
|
v18 | | | 86.59 276 | 84.57 280 | 92.65 268 | 93.41 267 | 93.43 192 | 98.69 243 | 95.55 306 | 82.44 299 | 74.71 316 | 87.68 322 | 82.11 206 | 94.21 310 | 80.14 296 | 66.37 329 | 90.32 318 |
|
v16 | | | 86.52 277 | 84.49 281 | 92.60 271 | 93.45 263 | 93.31 201 | 98.60 252 | 95.52 309 | 82.30 301 | 74.59 318 | 87.70 321 | 81.95 213 | 94.18 311 | 79.93 298 | 66.38 328 | 90.30 319 |
|
v17 | | | 86.51 278 | 84.49 281 | 92.57 272 | 93.38 269 | 93.29 202 | 98.61 251 | 95.54 307 | 82.32 300 | 74.69 317 | 87.63 323 | 82.03 207 | 94.17 312 | 80.02 297 | 66.17 330 | 90.26 320 |
|
v15 | | | 86.26 281 | 84.19 284 | 92.47 274 | 93.29 274 | 93.28 203 | 98.53 256 | 95.47 310 | 82.24 303 | 74.34 319 | 87.34 325 | 81.71 216 | 94.07 313 | 79.39 299 | 65.42 331 | 90.06 326 |
|
V9 | | | 86.16 284 | 84.07 286 | 92.43 275 | 93.27 276 | 93.04 209 | 98.40 266 | 95.45 312 | 81.98 306 | 74.18 322 | 87.31 326 | 81.58 222 | 94.06 314 | 79.12 303 | 65.33 334 | 90.20 323 |
|
V14 | | | 86.22 282 | 84.15 285 | 92.41 277 | 93.30 273 | 93.16 204 | 98.47 259 | 95.47 310 | 82.10 304 | 74.27 320 | 87.41 324 | 81.73 215 | 94.02 315 | 79.26 300 | 65.37 333 | 90.04 327 |
|
pmmvs-eth3d | | | 84.03 300 | 81.97 300 | 90.20 300 | 84.15 331 | 87.09 293 | 98.10 282 | 94.73 326 | 83.05 294 | 74.10 323 | 87.77 320 | 65.56 318 | 94.01 316 | 81.08 292 | 69.24 322 | 89.49 333 |
|
v13 | | | 86.06 287 | 83.97 291 | 92.34 281 | 93.25 277 | 92.85 212 | 98.26 273 | 95.44 314 | 81.70 310 | 74.02 325 | 87.11 330 | 81.58 222 | 94.00 317 | 78.94 305 | 65.41 332 | 90.18 324 |
|
v12 | | | 86.10 285 | 84.01 287 | 92.37 279 | 93.23 279 | 92.96 210 | 98.33 269 | 95.45 312 | 81.87 307 | 74.05 324 | 87.15 328 | 81.60 221 | 93.98 318 | 79.09 304 | 65.28 335 | 90.18 324 |
|
UnsupCasMVSNet_eth | | | 85.52 290 | 83.99 288 | 90.10 301 | 89.36 321 | 83.51 309 | 96.65 304 | 97.99 169 | 89.14 220 | 75.89 312 | 93.83 291 | 63.25 324 | 93.92 319 | 81.92 288 | 67.90 325 | 92.88 296 |
|
PM-MVS | | | 80.47 305 | 78.88 307 | 85.26 315 | 83.79 332 | 72.22 330 | 95.89 317 | 91.08 342 | 85.71 279 | 76.56 309 | 88.30 314 | 36.64 344 | 93.90 320 | 82.39 284 | 69.57 321 | 89.66 331 |
|
MDA-MVSNet_test_wron | | | 85.51 291 | 83.32 296 | 92.10 283 | 90.96 312 | 88.58 282 | 99.20 196 | 96.52 289 | 79.70 315 | 57.12 341 | 92.69 303 | 79.11 253 | 93.86 321 | 77.10 313 | 77.46 303 | 93.86 270 |
|
v11 | | | 86.09 286 | 83.98 290 | 92.42 276 | 93.29 274 | 93.41 196 | 98.52 257 | 95.30 317 | 81.73 309 | 74.27 320 | 87.20 327 | 81.24 227 | 93.85 322 | 77.68 310 | 66.61 327 | 90.00 328 |
|
YYNet1 | | | 85.50 292 | 83.33 295 | 92.00 284 | 90.89 313 | 88.38 286 | 99.22 195 | 96.55 288 | 79.60 317 | 57.26 340 | 92.72 302 | 79.09 254 | 93.78 323 | 77.25 312 | 77.37 304 | 93.84 271 |
|
Patchmatch-RL test | | | 86.90 274 | 85.98 274 | 89.67 304 | 84.45 330 | 75.59 328 | 89.71 339 | 92.43 338 | 86.89 261 | 77.83 305 | 90.94 310 | 94.22 68 | 93.63 324 | 87.75 235 | 69.61 320 | 99.79 82 |
|
MDA-MVSNet-bldmvs | | | 84.09 299 | 81.52 303 | 91.81 287 | 91.32 310 | 88.00 289 | 98.67 246 | 95.92 299 | 80.22 314 | 55.60 342 | 93.32 298 | 68.29 311 | 93.60 325 | 73.76 318 | 76.61 309 | 93.82 273 |
|
Anonymous20231206 | | | 86.32 280 | 85.42 276 | 89.02 307 | 89.11 322 | 80.53 325 | 99.05 215 | 95.28 318 | 85.43 281 | 82.82 289 | 93.92 289 | 74.40 287 | 93.44 326 | 66.99 328 | 81.83 264 | 93.08 292 |
|
EU-MVSNet | | | 90.14 251 | 90.34 218 | 89.54 305 | 92.55 293 | 81.06 322 | 98.69 243 | 98.04 166 | 91.41 185 | 86.59 265 | 96.84 207 | 80.83 232 | 93.31 327 | 86.20 257 | 81.91 263 | 94.26 233 |
|
Anonymous20231211 | | | 74.17 312 | 71.17 314 | 83.17 318 | 80.58 335 | 67.02 336 | 96.27 311 | 94.45 329 | 57.31 341 | 69.60 330 | 86.25 334 | 33.67 345 | 92.96 328 | 61.86 334 | 60.50 340 | 89.54 332 |
|
DSMNet-mixed | | | 88.28 270 | 88.24 261 | 88.42 311 | 89.64 320 | 75.38 329 | 98.06 283 | 89.86 346 | 85.59 280 | 88.20 248 | 92.14 306 | 76.15 276 | 91.95 329 | 78.46 306 | 96.05 153 | 97.92 194 |
|
FMVSNet5 | | | 88.32 269 | 87.47 269 | 90.88 292 | 96.90 191 | 88.39 285 | 97.28 296 | 95.68 302 | 82.60 298 | 84.67 281 | 92.40 305 | 79.83 245 | 91.16 330 | 76.39 316 | 81.51 265 | 93.09 291 |
|
pmmvs3 | | | 80.27 306 | 77.77 310 | 87.76 312 | 80.32 336 | 82.43 314 | 98.23 276 | 91.97 340 | 72.74 332 | 78.75 302 | 87.97 317 | 57.30 334 | 90.99 331 | 70.31 321 | 62.37 338 | 89.87 329 |
|
new-patchmatchnet | | | 81.19 304 | 79.34 306 | 86.76 314 | 82.86 333 | 80.36 326 | 97.92 286 | 95.27 319 | 82.09 305 | 72.02 326 | 86.87 331 | 62.81 325 | 90.74 332 | 71.10 320 | 63.08 337 | 89.19 335 |
|
MIMVSNet1 | | | 82.58 303 | 80.51 305 | 88.78 309 | 86.68 326 | 84.20 308 | 96.65 304 | 95.41 315 | 78.75 318 | 78.59 303 | 92.44 304 | 51.88 339 | 89.76 333 | 65.26 332 | 78.95 288 | 92.38 300 |
|
test20.03 | | | 84.72 297 | 83.99 288 | 86.91 313 | 88.19 324 | 80.62 324 | 98.88 229 | 95.94 298 | 88.36 238 | 78.87 301 | 94.62 278 | 68.75 307 | 89.11 334 | 66.52 329 | 75.82 310 | 91.00 313 |
|
1111 | | | 79.11 309 | 78.74 308 | 80.23 322 | 78.33 337 | 67.13 334 | 97.31 294 | 93.65 334 | 71.34 333 | 68.35 332 | 87.87 318 | 85.42 186 | 88.46 335 | 52.93 342 | 73.46 317 | 85.11 338 |
|
.test1245 | | | 71.48 313 | 71.80 313 | 70.51 332 | 78.33 337 | 67.13 334 | 97.31 294 | 93.65 334 | 71.34 333 | 68.35 332 | 87.87 318 | 85.42 186 | 88.46 335 | 52.93 342 | 11.01 352 | 55.94 351 |
|
testus | | | 83.91 301 | 84.49 281 | 82.17 321 | 85.68 328 | 66.11 337 | 99.68 138 | 93.53 336 | 86.55 264 | 82.60 290 | 94.91 267 | 56.70 335 | 88.19 337 | 68.46 324 | 92.31 206 | 92.21 301 |
|
no-one | | | 63.48 320 | 59.26 321 | 76.14 326 | 66.71 346 | 65.06 338 | 92.75 329 | 89.92 345 | 68.96 337 | 46.96 347 | 66.55 347 | 21.74 353 | 87.68 338 | 57.07 340 | 22.69 350 | 75.68 344 |
|
Gipuma | | | 66.95 318 | 65.00 317 | 72.79 329 | 91.52 308 | 67.96 333 | 66.16 349 | 95.15 323 | 47.89 343 | 58.54 339 | 67.99 346 | 29.74 348 | 87.54 339 | 50.20 344 | 77.83 298 | 62.87 349 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
LCM-MVSNet | | | 67.77 315 | 64.73 318 | 76.87 325 | 62.95 351 | 56.25 346 | 89.37 340 | 93.74 333 | 44.53 345 | 61.99 337 | 80.74 338 | 20.42 354 | 86.53 340 | 69.37 323 | 59.50 342 | 87.84 336 |
|
test2356 | | | 86.43 279 | 87.59 268 | 82.95 319 | 85.90 327 | 69.43 332 | 99.79 103 | 96.63 286 | 85.76 275 | 83.44 287 | 94.99 264 | 80.45 242 | 86.52 341 | 68.12 327 | 93.21 202 | 92.90 294 |
|
test1235678 | | | 78.45 310 | 77.88 309 | 80.16 323 | 77.83 339 | 62.18 341 | 98.36 267 | 93.45 337 | 77.46 321 | 69.08 331 | 88.23 315 | 60.33 330 | 85.41 342 | 58.46 338 | 77.68 300 | 92.90 294 |
|
PMMVS2 | | | 67.15 317 | 64.15 319 | 76.14 326 | 70.56 345 | 62.07 342 | 93.89 324 | 87.52 350 | 58.09 340 | 60.02 338 | 78.32 339 | 22.38 352 | 84.54 343 | 59.56 337 | 47.03 343 | 81.80 340 |
|
test12356 | | | 75.26 311 | 75.12 312 | 75.67 328 | 74.02 342 | 60.60 343 | 96.43 307 | 92.15 339 | 74.17 330 | 66.35 334 | 88.11 316 | 52.29 338 | 84.36 344 | 57.41 339 | 75.12 313 | 82.05 339 |
|
FPMVS | | | 68.72 314 | 68.72 315 | 68.71 333 | 65.95 347 | 44.27 355 | 95.97 316 | 94.74 325 | 51.13 342 | 53.26 344 | 90.50 312 | 25.11 351 | 83.00 345 | 60.80 336 | 80.97 273 | 78.87 342 |
|
testmv | | | 67.54 316 | 65.93 316 | 72.37 330 | 64.46 350 | 54.05 347 | 95.09 320 | 90.07 344 | 68.90 338 | 55.16 343 | 77.63 341 | 30.39 346 | 82.61 346 | 49.42 345 | 62.26 339 | 80.45 341 |
|
PMVS | | 49.05 23 | 53.75 323 | 51.34 325 | 60.97 338 | 40.80 356 | 34.68 356 | 74.82 347 | 89.62 348 | 37.55 348 | 28.67 353 | 72.12 342 | 7.09 359 | 81.63 347 | 43.17 350 | 68.21 324 | 66.59 348 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
tmp_tt | | | 65.23 319 | 62.94 320 | 72.13 331 | 44.90 355 | 50.03 351 | 81.05 344 | 89.42 349 | 38.45 347 | 48.51 346 | 99.90 10 | 54.09 337 | 78.70 348 | 91.84 186 | 18.26 351 | 87.64 337 |
|
PNet_i23d | | | 56.44 321 | 53.54 322 | 65.14 336 | 65.34 348 | 50.33 350 | 89.06 341 | 79.57 352 | 45.77 344 | 35.75 351 | 68.95 345 | 10.75 358 | 74.40 349 | 48.48 346 | 38.20 344 | 70.70 345 |
|
wuykxyi23d | | | 50.36 327 | 45.43 328 | 65.16 335 | 51.13 353 | 51.75 348 | 77.46 346 | 78.42 353 | 41.45 346 | 26.98 354 | 54.30 354 | 6.13 360 | 74.03 350 | 46.82 348 | 26.19 346 | 69.71 346 |
|
MVE | | 53.74 22 | 51.54 325 | 47.86 327 | 62.60 337 | 59.56 352 | 50.93 349 | 79.41 345 | 77.69 354 | 35.69 350 | 36.27 350 | 61.76 351 | 5.79 362 | 69.63 351 | 37.97 351 | 36.61 345 | 67.24 347 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
ANet_high | | | 56.10 322 | 52.24 323 | 67.66 334 | 49.27 354 | 56.82 345 | 83.94 343 | 82.02 351 | 70.47 335 | 33.28 352 | 64.54 348 | 17.23 356 | 69.16 352 | 45.59 349 | 23.85 349 | 77.02 343 |
|
E-PMN | | | 52.30 324 | 52.18 324 | 52.67 339 | 71.51 343 | 45.40 352 | 93.62 327 | 76.60 355 | 36.01 349 | 43.50 348 | 64.13 349 | 27.11 350 | 67.31 353 | 31.06 352 | 26.06 347 | 45.30 354 |
|
EMVS | | | 51.44 326 | 51.22 326 | 52.11 340 | 70.71 344 | 44.97 354 | 94.04 323 | 75.66 356 | 35.34 351 | 42.40 349 | 61.56 352 | 28.93 349 | 65.87 354 | 27.64 353 | 24.73 348 | 45.49 353 |
|
wuyk23d | | | 20.37 332 | 20.84 333 | 18.99 344 | 65.34 348 | 27.73 357 | 50.43 350 | 7.67 360 | 9.50 354 | 8.01 355 | 6.34 356 | 6.13 360 | 26.24 355 | 23.40 354 | 10.69 354 | 2.99 355 |
|
test123 | | | 37.68 329 | 39.14 331 | 33.31 341 | 19.94 357 | 24.83 358 | 98.36 267 | 9.75 359 | 15.53 353 | 51.31 345 | 87.14 329 | 19.62 355 | 17.74 356 | 47.10 347 | 3.47 355 | 57.36 350 |
|
testmvs | | | 40.60 328 | 44.45 329 | 29.05 343 | 19.49 358 | 14.11 359 | 99.68 138 | 18.47 358 | 20.74 352 | 64.59 335 | 98.48 165 | 10.95 357 | 17.09 357 | 56.66 341 | 11.01 352 | 55.94 351 |
|
cdsmvs_eth3d_5k | | | 23.43 331 | 31.24 332 | 0.00 345 | 0.00 359 | 0.00 360 | 0.00 351 | 98.09 162 | 0.00 355 | 0.00 356 | 99.67 75 | 83.37 198 | 0.00 358 | 0.00 355 | 0.00 356 | 0.00 356 |
|
pcd_1.5k_mvsjas | | | 7.60 334 | 10.13 335 | 0.00 345 | 0.00 359 | 0.00 360 | 0.00 351 | 0.00 361 | 0.00 355 | 0.00 356 | 0.00 357 | 91.20 124 | 0.00 358 | 0.00 355 | 0.00 356 | 0.00 356 |
|
pcd1.5k->3k | | | 37.58 330 | 39.62 330 | 31.46 342 | 92.73 291 | 0.00 360 | 0.00 351 | 97.52 211 | 0.00 355 | 0.00 356 | 0.00 357 | 78.40 262 | 0.00 358 | 0.00 355 | 87.90 231 | 94.37 224 |
|
sosnet-low-res | | | 0.00 335 | 0.00 336 | 0.00 345 | 0.00 359 | 0.00 360 | 0.00 351 | 0.00 361 | 0.00 355 | 0.00 356 | 0.00 357 | 0.00 363 | 0.00 358 | 0.00 355 | 0.00 356 | 0.00 356 |
|
sosnet | | | 0.00 335 | 0.00 336 | 0.00 345 | 0.00 359 | 0.00 360 | 0.00 351 | 0.00 361 | 0.00 355 | 0.00 356 | 0.00 357 | 0.00 363 | 0.00 358 | 0.00 355 | 0.00 356 | 0.00 356 |
|
uncertanet | | | 0.00 335 | 0.00 336 | 0.00 345 | 0.00 359 | 0.00 360 | 0.00 351 | 0.00 361 | 0.00 355 | 0.00 356 | 0.00 357 | 0.00 363 | 0.00 358 | 0.00 355 | 0.00 356 | 0.00 356 |
|
Regformer | | | 0.00 335 | 0.00 336 | 0.00 345 | 0.00 359 | 0.00 360 | 0.00 351 | 0.00 361 | 0.00 355 | 0.00 356 | 0.00 357 | 0.00 363 | 0.00 358 | 0.00 355 | 0.00 356 | 0.00 356 |
|
ab-mvs-re | | | 8.28 333 | 11.04 334 | 0.00 345 | 0.00 359 | 0.00 360 | 0.00 351 | 0.00 361 | 0.00 355 | 0.00 356 | 99.40 94 | 0.00 363 | 0.00 358 | 0.00 355 | 0.00 356 | 0.00 356 |
|
uanet | | | 0.00 335 | 0.00 336 | 0.00 345 | 0.00 359 | 0.00 360 | 0.00 351 | 0.00 361 | 0.00 355 | 0.00 356 | 0.00 357 | 0.00 363 | 0.00 358 | 0.00 355 | 0.00 356 | 0.00 356 |
|
GSMVS | | | | | | | | | | | | | | | | | 99.59 110 |
|
test_part2 | | | | | | 99.89 36 | 99.25 6 | | | | 99.49 32 | | | | | | |
|
test_part1 | | | | | | | | | 98.41 122 | | | | 97.20 11 | | | 99.99 13 | 99.99 11 |
|
sam_mvs1 | | | | | | | | | | | | | 94.72 55 | | | | 99.59 110 |
|
sam_mvs | | | | | | | | | | | | | 94.25 67 | | | | |
|
MTGPA | | | | | | | | | 98.28 140 | | | | | | | | |
|
MTMP | | | | | | | | | 96.49 290 | | | | | | | | |
|
test9_res | | | | | | | | | | | | | | | 99.71 17 | 99.99 13 | 100.00 1 |
|
agg_prior2 | | | | | | | | | | | | | | | 99.48 23 | 100.00 1 | 100.00 1 |
|
test_prior4 | | | | | | | 98.05 62 | 99.94 45 | | | | | | | | | |
|
test_prior2 | | | | | | | | 99.95 31 | | 95.78 50 | 99.73 13 | 99.76 55 | 96.00 25 | | 99.78 9 | 100.00 1 | |
|
新几何2 | | | | | | | | 99.40 176 | | | | | | | | | |
|
旧先验1 | | | | | | 99.76 53 | 97.52 77 | | 98.64 70 | | | 99.85 20 | 95.63 33 | | | 99.94 43 | 99.99 11 |
|
原ACMM2 | | | | | | | | 99.90 59 | | | | | | | | | |
|
test222 | | | | | | 99.55 73 | 97.41 86 | 99.34 184 | 98.55 88 | 91.86 173 | 99.27 48 | 99.83 36 | 93.84 82 | | | 99.95 39 | 99.99 11 |
|
segment_acmp | | | | | | | | | | | | | 96.68 14 | | | | |
|
testdata1 | | | | | | | | 99.28 191 | | 96.35 38 | | | | | | | |
|
plane_prior7 | | | | | | 95.71 225 | 91.59 248 | | | | | | | | | | |
|
plane_prior6 | | | | | | 95.76 220 | 91.72 243 | | | | | | 80.47 240 | | | | |
|
plane_prior4 | | | | | | | | | | | | 98.59 157 | | | | | |
|
plane_prior3 | | | | | | | 91.64 246 | | | 96.63 29 | 93.01 180 | | | | | | |
|
plane_prior2 | | | | | | | | 99.84 90 | | 96.38 34 | | | | | | | |
|
plane_prior1 | | | | | | 95.73 222 | | | | | | | | | | | |
|
plane_prior | | | | | | | 91.74 240 | 99.86 86 | | 96.76 25 | | | | | | 89.59 209 | |
|
n2 | | | | | | | | | 0.00 361 | | | | | | | | |
|
nn | | | | | | | | | 0.00 361 | | | | | | | | |
|
door-mid | | | | | | | | | 89.69 347 | | | | | | | | |
|
test11 | | | | | | | | | 98.44 107 | | | | | | | | |
|
door | | | | | | | | | 90.31 343 | | | | | | | | |
|
HQP5-MVS | | | | | | | 91.85 235 | | | | | | | | | | |
|
HQP-NCC | | | | | | 95.78 216 | | 99.87 71 | | 96.82 21 | 93.37 176 | | | | | | |
|
ACMP_Plane | | | | | | 95.78 216 | | 99.87 71 | | 96.82 21 | 93.37 176 | | | | | | |
|
BP-MVS | | | | | | | | | | | | | | | 97.92 84 | | |
|
HQP3-MVS | | | | | | | | | 97.89 179 | | | | | | | 89.60 207 | |
|
HQP2-MVS | | | | | | | | | | | | | 80.65 236 | | | | |
|
NP-MVS | | | | | | 95.77 219 | 91.79 237 | | | | | 98.65 153 | | | | | |
|
MDTV_nov1_ep13_2view | | | | | | | 96.26 122 | 96.11 313 | | 91.89 172 | 98.06 95 | | 94.40 59 | | 94.30 145 | | 99.67 96 |
|
ACMMP++_ref | | | | | | | | | | | | | | | | 87.04 239 | |
|
ACMMP++ | | | | | | | | | | | | | | | | 88.23 229 | |
|
Test By Simon | | | | | | | | | | | | | 92.82 101 | | | | |
|