APDe-MVS | | | 99.66 1 | 99.57 1 | 99.92 1 | 99.77 29 | 99.89 1 | 99.75 33 | 99.56 43 | 99.02 9 | 99.88 3 | 99.85 24 | 99.18 4 | 99.96 11 | 99.22 22 | 99.92 8 | 99.90 1 |
|
Regformer-4 | | | 99.59 2 | 99.54 4 | 99.73 37 | 99.76 32 | 99.41 62 | 99.58 76 | 99.49 92 | 99.02 9 | 99.88 3 | 99.80 58 | 99.00 16 | 99.94 27 | 99.45 7 | 99.92 8 | 99.84 10 |
|
EI-MVSNet-UG-set | | | 99.58 3 | 99.57 1 | 99.64 52 | 99.78 25 | 99.14 84 | 99.60 71 | 99.45 127 | 99.01 12 | 99.90 1 | 99.83 34 | 98.98 17 | 99.93 40 | 99.59 1 | 99.95 4 | 99.86 4 |
|
EI-MVSNet-Vis-set | | | 99.58 3 | 99.56 3 | 99.64 52 | 99.78 25 | 99.15 83 | 99.61 70 | 99.45 127 | 99.01 12 | 99.89 2 | 99.82 42 | 99.01 10 | 99.92 47 | 99.56 3 | 99.95 4 | 99.85 6 |
|
Regformer-3 | | | 99.57 5 | 99.53 5 | 99.68 42 | 99.76 32 | 99.29 71 | 99.58 76 | 99.44 133 | 99.01 12 | 99.87 6 | 99.80 58 | 98.97 18 | 99.91 56 | 99.44 8 | 99.92 8 | 99.83 20 |
|
Regformer-2 | | | 99.54 6 | 99.47 7 | 99.75 30 | 99.71 54 | 99.52 50 | 99.49 112 | 99.49 92 | 98.94 24 | 99.83 8 | 99.76 75 | 99.01 10 | 99.94 27 | 99.15 29 | 99.87 28 | 99.80 31 |
|
SteuartSystems-ACMMP | | | 99.54 6 | 99.42 10 | 99.87 2 | 99.82 20 | 99.81 7 | 99.59 73 | 99.51 79 | 98.62 36 | 99.79 14 | 99.83 34 | 99.28 2 | 99.97 6 | 98.48 90 | 99.90 18 | 99.84 10 |
Skip Steuart: Steuart Systems R&D Blog. |
Regformer-1 | | | 99.53 8 | 99.47 7 | 99.72 39 | 99.71 54 | 99.44 59 | 99.49 112 | 99.46 116 | 98.95 23 | 99.83 8 | 99.76 75 | 99.01 10 | 99.93 40 | 99.17 27 | 99.87 28 | 99.80 31 |
|
XVS | | | 99.53 8 | 99.42 10 | 99.87 2 | 99.85 15 | 99.83 3 | 99.69 43 | 99.68 16 | 98.98 18 | 99.37 80 | 99.74 82 | 98.81 30 | 99.94 27 | 98.79 58 | 99.86 38 | 99.84 10 |
|
HPM-MVS_fast | | | 99.51 10 | 99.40 13 | 99.85 13 | 99.91 1 | 99.79 11 | 99.76 26 | 99.56 43 | 97.72 105 | 99.76 20 | 99.75 79 | 99.13 5 | 99.92 47 | 99.07 35 | 99.92 8 | 99.85 6 |
|
HFP-MVS | | | 99.49 11 | 99.37 15 | 99.86 8 | 99.87 8 | 99.80 8 | 99.66 52 | 99.67 19 | 98.15 64 | 99.68 26 | 99.69 97 | 99.06 7 | 99.96 11 | 98.69 66 | 99.87 28 | 99.84 10 |
|
ACMMPR | | | 99.49 11 | 99.36 17 | 99.86 8 | 99.87 8 | 99.79 11 | 99.66 52 | 99.67 19 | 98.15 64 | 99.67 30 | 99.69 97 | 98.95 22 | 99.96 11 | 98.69 66 | 99.87 28 | 99.84 10 |
|
DeepC-MVS_fast | | 98.69 1 | 99.49 11 | 99.39 14 | 99.77 28 | 99.63 77 | 99.59 38 | 99.36 158 | 99.46 116 | 99.07 8 | 99.79 14 | 99.82 42 | 98.85 28 | 99.92 47 | 98.68 68 | 99.87 28 | 99.82 24 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
region2R | | | 99.48 14 | 99.35 19 | 99.87 2 | 99.88 4 | 99.80 8 | 99.65 60 | 99.66 22 | 98.13 66 | 99.66 35 | 99.68 102 | 98.96 19 | 99.96 11 | 98.62 73 | 99.87 28 | 99.84 10 |
|
APD-MVS_3200maxsize | | | 99.48 14 | 99.35 19 | 99.85 13 | 99.76 32 | 99.83 3 | 99.63 63 | 99.54 57 | 98.36 49 | 99.79 14 | 99.82 42 | 98.86 27 | 99.95 24 | 98.62 73 | 99.81 56 | 99.78 39 |
|
DELS-MVS | | | 99.48 14 | 99.42 10 | 99.65 48 | 99.72 52 | 99.40 64 | 99.05 218 | 99.66 22 | 99.14 5 | 99.57 49 | 99.80 58 | 98.46 53 | 99.94 27 | 99.57 2 | 99.84 47 | 99.60 92 |
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 |
MSLP-MVS | | | 99.46 17 | 99.47 7 | 99.44 84 | 99.60 84 | 99.16 81 | 99.41 142 | 99.71 11 | 98.98 18 | 99.45 66 | 99.78 69 | 99.19 3 | 99.54 159 | 99.28 18 | 99.84 47 | 99.63 88 |
|
PGM-MVS | | | 99.45 18 | 99.31 27 | 99.86 8 | 99.87 8 | 99.78 15 | 99.58 76 | 99.65 27 | 97.84 93 | 99.71 22 | 99.80 58 | 99.12 6 | 99.97 6 | 98.33 101 | 99.87 28 | 99.83 20 |
|
CP-MVS | | | 99.45 18 | 99.32 22 | 99.85 13 | 99.83 19 | 99.75 16 | 99.69 43 | 99.52 71 | 98.07 75 | 99.53 54 | 99.63 123 | 98.93 23 | 99.97 6 | 98.74 61 | 99.91 13 | 99.83 20 |
|
ACMMP |  | | 99.45 18 | 99.32 22 | 99.82 18 | 99.89 3 | 99.67 26 | 99.62 64 | 99.69 15 | 98.12 67 | 99.63 40 | 99.84 32 | 98.73 41 | 99.96 11 | 98.55 85 | 99.83 51 | 99.81 27 |
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 |
mPP-MVS | | | 99.44 21 | 99.30 28 | 99.86 8 | 99.88 4 | 99.79 11 | 99.69 43 | 99.48 99 | 98.12 67 | 99.50 58 | 99.75 79 | 98.78 32 | 99.97 6 | 98.57 80 | 99.89 24 | 99.83 20 |
|
#test# | | | 99.43 22 | 99.29 31 | 99.86 8 | 99.87 8 | 99.80 8 | 99.55 93 | 99.67 19 | 97.83 94 | 99.68 26 | 99.69 97 | 99.06 7 | 99.96 11 | 98.39 94 | 99.87 28 | 99.84 10 |
|
MCST-MVS | | | 99.43 22 | 99.30 28 | 99.82 18 | 99.79 24 | 99.74 18 | 99.29 172 | 99.40 151 | 98.79 31 | 99.52 56 | 99.62 128 | 98.91 24 | 99.90 67 | 98.64 70 | 99.75 66 | 99.82 24 |
|
UA-Net | | | 99.42 24 | 99.29 31 | 99.80 22 | 99.62 78 | 99.55 43 | 99.50 107 | 99.70 12 | 98.79 31 | 99.77 18 | 99.96 1 | 97.45 79 | 99.96 11 | 98.92 46 | 99.90 18 | 99.89 2 |
|
HPM-MVS | | | 99.42 24 | 99.28 33 | 99.83 17 | 99.90 2 | 99.72 19 | 99.81 15 | 99.54 57 | 97.59 112 | 99.68 26 | 99.63 123 | 98.91 24 | 99.94 27 | 98.58 78 | 99.91 13 | 99.84 10 |
|
CNVR-MVS | | | 99.42 24 | 99.30 28 | 99.78 26 | 99.62 78 | 99.71 20 | 99.26 183 | 99.52 71 | 98.82 28 | 99.39 77 | 99.71 89 | 98.96 19 | 99.85 86 | 98.59 77 | 99.80 58 | 99.77 41 |
|
SD-MVS | | | 99.41 27 | 99.52 6 | 99.05 117 | 99.74 44 | 99.68 24 | 99.46 123 | 99.52 71 | 99.11 6 | 99.88 3 | 99.91 5 | 99.43 1 | 97.70 269 | 98.72 63 | 99.93 7 | 99.77 41 |
|
MVS_111021_LR | | | 99.41 27 | 99.33 21 | 99.65 48 | 99.77 29 | 99.51 52 | 98.94 243 | 99.85 4 | 98.82 28 | 99.65 38 | 99.74 82 | 98.51 50 | 99.80 109 | 98.83 56 | 99.89 24 | 99.64 85 |
|
MVS_111021_HR | | | 99.41 27 | 99.32 22 | 99.66 45 | 99.72 52 | 99.47 56 | 98.95 241 | 99.85 4 | 98.82 28 | 99.54 53 | 99.73 85 | 98.51 50 | 99.74 120 | 98.91 47 | 99.88 26 | 99.77 41 |
|
HPM-MVS++ | | | 99.39 30 | 99.23 35 | 99.87 2 | 99.75 38 | 99.84 2 | 99.43 132 | 99.51 79 | 98.68 34 | 99.27 106 | 99.53 149 | 98.64 47 | 99.96 11 | 98.44 93 | 99.80 58 | 99.79 35 |
|
TSAR-MVS | | | 99.36 31 | 99.36 17 | 99.36 91 | 99.67 64 | 98.61 154 | 99.07 213 | 99.33 185 | 99.00 16 | 99.82 11 | 99.81 51 | 99.06 7 | 99.84 91 | 99.09 32 | 99.42 94 | 99.65 80 |
|
PVSNet_Blended_VisFu | | | 99.36 31 | 99.28 33 | 99.61 56 | 99.86 12 | 99.07 89 | 99.47 121 | 99.93 1 | 97.66 110 | 99.71 22 | 99.86 21 | 97.73 74 | 99.96 11 | 99.47 6 | 99.82 55 | 99.79 35 |
|
NCCC | | | 99.34 33 | 99.19 36 | 99.79 25 | 99.61 82 | 99.65 30 | 99.30 169 | 99.48 99 | 98.86 27 | 99.21 118 | 99.63 123 | 98.72 42 | 99.90 67 | 98.25 105 | 99.63 89 | 99.80 31 |
|
MP-MVS |  | | 99.33 34 | 99.15 39 | 99.87 2 | 99.88 4 | 99.82 6 | 99.66 52 | 99.46 116 | 98.09 71 | 99.48 62 | 99.74 82 | 98.29 62 | 99.96 11 | 97.93 126 | 99.87 28 | 99.82 24 |
|
PS-MVSNAJ | | | 99.32 35 | 99.32 22 | 99.30 97 | 99.57 89 | 98.94 107 | 98.97 235 | 99.46 116 | 98.92 26 | 99.71 22 | 99.24 216 | 99.01 10 | 99.98 2 | 99.35 10 | 99.66 84 | 98.97 157 |
|
CSCG | | | 99.32 35 | 99.32 22 | 99.32 93 | 99.85 15 | 98.29 170 | 99.71 40 | 99.66 22 | 98.11 69 | 99.41 73 | 99.80 58 | 98.37 59 | 99.96 11 | 98.99 41 | 99.96 3 | 99.72 62 |
|
PHI-MVS | | | 99.30 37 | 99.17 38 | 99.70 41 | 99.56 91 | 99.52 50 | 99.58 76 | 99.80 6 | 97.12 150 | 99.62 43 | 99.73 85 | 98.58 49 | 99.90 67 | 98.61 75 | 99.91 13 | 99.68 74 |
|
DeepC-MVS | | 98.35 2 | 99.30 37 | 99.19 36 | 99.64 52 | 99.82 20 | 99.23 77 | 99.62 64 | 99.55 50 | 98.94 24 | 99.63 40 | 99.95 2 | 95.82 116 | 99.94 27 | 99.37 9 | 99.97 2 | 99.73 56 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
APD-MVS |  | | 99.27 39 | 99.08 42 | 99.84 16 | 99.75 38 | 99.79 11 | 99.50 107 | 99.50 89 | 97.16 146 | 99.77 18 | 99.82 42 | 98.78 32 | 99.94 27 | 97.56 157 | 99.86 38 | 99.80 31 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
LS3D | | | 99.27 39 | 99.12 40 | 99.74 35 | 99.18 155 | 99.75 16 | 99.56 88 | 99.57 40 | 98.45 43 | 99.49 61 | 99.85 24 | 97.77 73 | 99.94 27 | 98.33 101 | 99.84 47 | 99.52 108 |
|
3Dnovator | | 97.25 9 | 99.24 41 | 99.05 44 | 99.81 21 | 99.12 167 | 99.66 28 | 99.84 9 | 99.74 8 | 99.09 7 | 98.92 160 | 99.90 7 | 95.94 113 | 99.98 2 | 98.95 44 | 99.92 8 | 99.79 35 |
|
test_prior3 | | | 99.21 42 | 99.05 44 | 99.68 42 | 99.67 64 | 99.48 54 | 98.96 237 | 99.56 43 | 98.34 50 | 99.01 147 | 99.52 152 | 98.68 44 | 99.83 97 | 97.96 124 | 99.74 68 | 99.74 50 |
|
F-COLMAP | | | 99.19 43 | 99.04 47 | 99.64 52 | 99.78 25 | 99.27 73 | 99.42 138 | 99.54 57 | 97.29 137 | 99.41 73 | 99.59 134 | 98.42 56 | 99.93 40 | 98.19 107 | 99.69 79 | 99.73 56 |
|
3Dnovator+ | | 97.12 13 | 99.18 44 | 98.97 57 | 99.82 18 | 99.17 159 | 99.68 24 | 99.81 15 | 99.51 79 | 99.20 4 | 98.72 180 | 99.89 10 | 95.68 120 | 99.97 6 | 98.86 53 | 99.86 38 | 99.81 27 |
|
MVSFormer | | | 99.17 45 | 99.12 40 | 99.29 100 | 99.51 95 | 98.94 107 | 99.88 1 | 99.46 116 | 97.55 116 | 99.80 12 | 99.65 113 | 97.39 80 | 99.28 198 | 99.03 37 | 99.85 42 | 99.65 80 |
|
sss | | | 99.17 45 | 99.05 44 | 99.53 68 | 99.62 78 | 98.97 103 | 99.36 158 | 99.62 28 | 97.83 94 | 99.67 30 | 99.65 113 | 97.37 83 | 99.95 24 | 99.19 24 | 99.19 102 | 99.68 74 |
|
DP-MVS | | | 99.16 47 | 98.95 62 | 99.78 26 | 99.77 29 | 99.53 47 | 99.41 142 | 99.50 89 | 97.03 158 | 99.04 144 | 99.88 13 | 97.39 80 | 99.92 47 | 98.66 69 | 99.90 18 | 99.87 3 |
|
CNLPA | | | 99.14 48 | 98.99 54 | 99.59 58 | 99.58 87 | 99.41 62 | 99.16 197 | 99.44 133 | 98.45 43 | 99.19 125 | 99.49 160 | 98.08 65 | 99.89 75 | 97.73 143 | 99.75 66 | 99.48 113 |
|
CDPH-MVS | | | 99.13 49 | 98.91 65 | 99.80 22 | 99.75 38 | 99.71 20 | 99.15 200 | 99.41 145 | 96.60 182 | 99.60 45 | 99.55 145 | 98.83 29 | 99.90 67 | 97.48 162 | 99.83 51 | 99.78 39 |
|
jason | | | 99.13 49 | 99.03 49 | 99.45 81 | 99.46 105 | 98.87 114 | 99.12 206 | 99.26 208 | 98.03 82 | 99.79 14 | 99.65 113 | 97.02 90 | 99.85 86 | 99.02 39 | 99.90 18 | 99.65 80 |
jason: jason. |
lupinMVS | | | 99.13 49 | 99.01 53 | 99.46 80 | 99.51 95 | 98.94 107 | 99.05 218 | 99.16 218 | 97.86 89 | 99.80 12 | 99.56 142 | 97.39 80 | 99.86 83 | 98.94 45 | 99.85 42 | 99.58 98 |
|
EPP-MVSNet | | | 99.13 49 | 98.99 54 | 99.53 68 | 99.65 74 | 99.06 90 | 99.81 15 | 99.33 185 | 97.43 125 | 99.60 45 | 99.88 13 | 97.14 87 | 99.84 91 | 99.13 30 | 98.94 118 | 99.69 70 |
|
MG-MVS | | | 99.13 49 | 99.02 52 | 99.45 81 | 99.57 89 | 98.63 150 | 99.07 213 | 99.34 177 | 98.99 17 | 99.61 44 | 99.82 42 | 97.98 68 | 99.87 80 | 97.00 187 | 99.80 58 | 99.85 6 |
|
DP-MVS Recon | | | 99.12 54 | 98.95 62 | 99.65 48 | 99.74 44 | 99.70 22 | 99.27 176 | 99.57 40 | 96.40 199 | 99.42 71 | 99.68 102 | 98.75 39 | 99.80 109 | 97.98 123 | 99.72 72 | 99.44 123 |
|
Vis-MVSNet |  | | 99.12 54 | 98.97 57 | 99.56 63 | 99.78 25 | 99.10 86 | 99.68 48 | 99.66 22 | 98.49 42 | 99.86 7 | 99.87 18 | 94.77 158 | 99.84 91 | 99.19 24 | 99.41 95 | 99.74 50 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
TAMVS | | | 99.12 54 | 99.08 42 | 99.24 103 | 99.46 105 | 98.55 156 | 99.51 102 | 99.46 116 | 98.09 71 | 99.45 66 | 99.82 42 | 98.34 60 | 99.51 160 | 98.70 64 | 98.93 119 | 99.67 77 |
|
VNet | | | 99.11 57 | 98.90 66 | 99.73 37 | 99.52 93 | 99.56 41 | 99.41 142 | 99.39 154 | 99.01 12 | 99.74 21 | 99.78 69 | 95.56 121 | 99.92 47 | 99.52 4 | 98.18 151 | 99.72 62 |
|
CPTT-MVS | | | 99.11 57 | 98.90 66 | 99.74 35 | 99.80 23 | 99.46 57 | 99.59 73 | 99.49 92 | 97.03 158 | 99.63 40 | 99.69 97 | 97.27 85 | 99.96 11 | 97.82 133 | 99.84 47 | 99.81 27 |
|
MVS_Test | | | 99.10 59 | 98.97 57 | 99.48 76 | 99.49 100 | 99.14 84 | 99.67 50 | 99.34 177 | 97.31 135 | 99.58 47 | 99.76 75 | 97.65 76 | 99.82 102 | 98.87 50 | 99.07 110 | 99.46 120 |
|
liao | | | 99.09 60 | 98.87 69 | 99.75 30 | 99.74 44 | 99.60 36 | 99.27 176 | 99.48 99 | 96.82 169 | 99.25 110 | 99.65 113 | 98.38 57 | 99.93 40 | 97.53 158 | 99.67 83 | 99.73 56 |
|
HyFIR | | | 99.09 60 | 98.97 57 | 99.45 81 | 99.68 62 | 98.78 138 | 99.14 205 | 99.62 28 | 97.97 85 | 99.20 121 | 99.83 34 | 96.26 107 | 99.82 102 | 99.08 33 | 99.98 1 | 99.74 50 |
|
CDS-MVSNet | | | 99.09 60 | 99.03 49 | 99.25 102 | 99.42 110 | 98.73 141 | 99.45 124 | 99.46 116 | 98.11 69 | 99.46 65 | 99.77 73 | 98.01 67 | 99.37 177 | 98.70 64 | 98.92 122 | 99.66 78 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
PVSNet_Blended | | | 99.08 63 | 98.97 57 | 99.42 88 | 99.76 32 | 98.79 136 | 98.78 253 | 99.91 2 | 96.74 171 | 99.67 30 | 99.49 160 | 97.53 77 | 99.88 78 | 98.98 42 | 99.85 42 | 99.60 92 |
|
OMC-MVS | | | 99.08 63 | 99.04 47 | 99.20 107 | 99.67 64 | 98.22 173 | 99.28 174 | 99.52 71 | 98.07 75 | 99.66 35 | 99.81 51 | 97.79 72 | 99.78 113 | 97.79 135 | 99.81 56 | 99.60 92 |
|
WTY-MVS | | | 99.06 65 | 98.88 68 | 99.61 56 | 99.62 78 | 99.16 81 | 99.37 155 | 99.56 43 | 98.04 80 | 99.53 54 | 99.62 128 | 96.84 93 | 99.94 27 | 98.85 54 | 98.49 143 | 99.72 62 |
|
IS-MVSNet | | | 99.05 66 | 98.87 69 | 99.57 61 | 99.73 49 | 99.32 67 | 99.75 33 | 99.20 214 | 98.02 83 | 99.56 50 | 99.86 21 | 96.54 100 | 99.67 142 | 98.09 114 | 99.13 105 | 99.73 56 |
|
PAPM_NR | | | 99.04 67 | 98.84 73 | 99.66 45 | 99.74 44 | 99.44 59 | 99.39 149 | 99.38 159 | 97.70 108 | 99.28 102 | 99.28 212 | 98.34 60 | 99.85 86 | 96.96 191 | 99.45 93 | 99.69 70 |
|
API-MVS | | | 99.04 67 | 99.03 49 | 99.06 115 | 99.40 116 | 99.31 70 | 99.55 93 | 99.56 43 | 98.54 39 | 99.33 91 | 99.39 185 | 98.76 37 | 99.78 113 | 96.98 189 | 99.78 62 | 98.07 254 |
|
mvs_anonymous | | | 99.03 69 | 98.99 54 | 99.16 109 | 99.38 119 | 98.52 161 | 99.51 102 | 99.38 159 | 97.79 97 | 99.38 79 | 99.81 51 | 97.30 84 | 99.45 164 | 99.35 10 | 98.99 113 | 99.51 110 |
|
canonicalmvs | | | 99.02 70 | 98.86 71 | 99.51 74 | 99.42 110 | 99.32 67 | 99.80 19 | 99.48 99 | 98.63 35 | 99.31 93 | 98.81 244 | 97.09 88 | 99.75 119 | 99.27 20 | 97.90 161 | 99.47 117 |
|
PLC |  | 97.94 4 | 99.02 70 | 98.85 72 | 99.53 68 | 99.66 73 | 99.01 96 | 99.24 186 | 99.52 71 | 96.85 167 | 99.27 106 | 99.48 164 | 98.25 64 | 99.91 56 | 97.76 139 | 99.62 90 | 99.65 80 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
agg_prior1 | | | 99.01 72 | 98.76 79 | 99.76 29 | 99.67 64 | 99.62 32 | 98.99 229 | 99.40 151 | 96.26 205 | 98.87 166 | 99.49 160 | 98.77 35 | 99.91 56 | 97.69 149 | 99.72 72 | 99.75 45 |
|
AdaColmap |  | | 99.01 72 | 98.80 75 | 99.66 45 | 99.56 91 | 99.54 44 | 99.18 196 | 99.70 12 | 98.18 63 | 99.35 87 | 99.63 123 | 96.32 103 | 99.90 67 | 97.48 162 | 99.77 64 | 99.55 100 |
|
1112_ss | | | 98.98 74 | 98.77 78 | 99.59 58 | 99.68 62 | 99.02 94 | 99.25 184 | 99.48 99 | 97.23 143 | 99.13 129 | 99.58 137 | 96.93 92 | 99.90 67 | 98.87 50 | 98.78 131 | 99.84 10 |
|
MSDG | | | 98.98 74 | 98.80 75 | 99.53 68 | 99.76 32 | 99.19 78 | 98.75 256 | 99.55 50 | 97.25 140 | 99.47 63 | 99.77 73 | 97.82 71 | 99.87 80 | 96.93 194 | 99.90 18 | 99.54 102 |
|
agg_prior3 | | | 98.97 76 | 98.71 83 | 99.75 30 | 99.67 64 | 99.60 36 | 99.04 222 | 99.41 145 | 95.93 220 | 98.87 166 | 99.48 164 | 98.61 48 | 99.91 56 | 97.63 152 | 99.72 72 | 99.75 45 |
|
114514_t | | | 98.93 77 | 98.67 87 | 99.72 39 | 99.85 15 | 99.53 47 | 99.62 64 | 99.59 35 | 92.65 263 | 99.71 22 | 99.78 69 | 98.06 66 | 99.90 67 | 98.84 55 | 99.91 13 | 99.74 50 |
|
PS-MVSNAJss | | | 98.92 78 | 98.92 64 | 98.90 142 | 98.78 233 | 98.53 158 | 99.78 22 | 99.54 57 | 98.07 75 | 99.00 153 | 99.76 75 | 99.01 10 | 99.37 177 | 99.13 30 | 97.23 191 | 98.81 163 |
|
Test_1112_low_res | | | 98.89 79 | 98.66 90 | 99.57 61 | 99.69 61 | 98.95 104 | 99.03 223 | 99.47 112 | 96.98 160 | 99.15 128 | 99.23 217 | 96.77 95 | 99.89 75 | 98.83 56 | 98.78 131 | 99.86 4 |
|
AllTest | | | 98.87 80 | 98.72 81 | 99.31 94 | 99.86 12 | 98.48 165 | 99.56 88 | 99.61 30 | 97.85 91 | 99.36 84 | 99.85 24 | 95.95 111 | 99.85 86 | 96.66 207 | 99.83 51 | 99.59 96 |
|
UGNet | | | 98.87 80 | 98.69 85 | 99.40 89 | 99.22 148 | 98.72 142 | 99.44 128 | 99.68 16 | 99.24 3 | 99.18 127 | 99.42 175 | 92.74 208 | 99.96 11 | 99.34 14 | 99.94 6 | 99.53 106 |
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 |
Vis-MVSNet (Re-imp) | | | 98.87 80 | 98.72 81 | 99.31 94 | 99.71 54 | 98.88 113 | 99.80 19 | 99.44 133 | 97.91 87 | 99.36 84 | 99.78 69 | 95.49 123 | 99.43 172 | 97.91 127 | 99.11 106 | 99.62 90 |
|
EPNet | | | 98.86 83 | 98.71 83 | 99.30 97 | 97.20 273 | 98.18 174 | 99.62 64 | 98.91 243 | 99.28 2 | 98.63 197 | 99.81 51 | 95.96 110 | 99.99 1 | 99.24 21 | 99.72 72 | 99.73 56 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
PVSNet_BlendedMVS | | | 98.86 83 | 98.80 75 | 99.03 118 | 99.76 32 | 98.79 136 | 99.28 174 | 99.91 2 | 97.42 127 | 99.67 30 | 99.37 189 | 97.53 77 | 99.88 78 | 98.98 42 | 97.29 190 | 98.42 245 |
|
ab-mvs | | | 98.86 83 | 98.63 92 | 99.54 64 | 99.64 75 | 99.19 78 | 99.44 128 | 99.54 57 | 97.77 99 | 99.30 94 | 99.81 51 | 94.20 178 | 99.93 40 | 99.17 27 | 98.82 129 | 99.49 111 |
|
MAR-MVS | | | 98.86 83 | 98.63 92 | 99.54 64 | 99.37 121 | 99.66 28 | 99.45 124 | 99.54 57 | 96.61 180 | 99.01 147 | 99.40 181 | 97.09 88 | 99.86 83 | 97.68 151 | 99.53 92 | 99.10 143 |
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 |
COLMAP_ROB |  | 97.56 6 | 98.86 83 | 98.75 80 | 99.17 108 | 99.88 4 | 98.53 158 | 99.34 162 | 99.59 35 | 97.55 116 | 98.70 186 | 99.89 10 | 95.83 115 | 99.90 67 | 98.10 113 | 99.90 18 | 99.08 148 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
HY-MVS | | 97.30 7 | 98.85 88 | 98.64 91 | 99.47 78 | 99.42 110 | 99.08 88 | 99.62 64 | 99.36 165 | 97.39 130 | 99.28 102 | 99.68 102 | 96.44 101 | 99.92 47 | 98.37 97 | 98.22 150 | 99.40 128 |
|
PVSNet | | 96.02 17 | 98.85 88 | 98.84 73 | 98.89 144 | 99.73 49 | 97.28 191 | 98.32 274 | 99.60 32 | 97.86 89 | 99.50 58 | 99.57 141 | 96.75 96 | 99.86 83 | 98.56 83 | 99.70 78 | 99.54 102 |
|
PatchMatch-RL | | | 98.84 90 | 98.62 95 | 99.52 72 | 99.71 54 | 99.28 72 | 99.06 216 | 99.77 7 | 97.74 103 | 99.50 58 | 99.53 149 | 95.41 124 | 99.84 91 | 97.17 179 | 99.64 87 | 99.44 123 |
|
alignmvs | | | 98.81 91 | 98.56 101 | 99.58 60 | 99.43 109 | 99.42 61 | 99.51 102 | 98.96 236 | 98.61 37 | 99.35 87 | 98.92 239 | 94.78 155 | 99.77 115 | 99.35 10 | 98.11 155 | 99.54 102 |
|
DeepPCF-MVS | | 98.18 3 | 98.81 91 | 99.37 15 | 97.12 248 | 99.60 84 | 91.75 273 | 98.61 265 | 99.44 133 | 99.35 1 | 99.83 8 | 99.85 24 | 98.70 43 | 99.81 107 | 99.02 39 | 99.91 13 | 99.81 27 |
|
PMMVS | | | 98.80 93 | 98.62 95 | 99.34 92 | 99.27 141 | 98.70 143 | 98.76 255 | 99.31 192 | 97.34 132 | 99.21 118 | 99.07 228 | 97.20 86 | 99.82 102 | 98.56 83 | 98.87 126 | 99.52 108 |
|
FIs | | | 98.78 94 | 98.63 92 | 99.23 105 | 99.18 155 | 99.54 44 | 99.83 12 | 99.59 35 | 98.28 54 | 98.79 175 | 99.81 51 | 96.75 96 | 99.37 177 | 99.08 33 | 96.38 206 | 98.78 166 |
|
FC-MVSNet-test | | | 98.75 95 | 98.62 95 | 99.15 111 | 99.08 176 | 99.45 58 | 99.86 8 | 99.60 32 | 98.23 59 | 98.70 186 | 99.82 42 | 96.80 94 | 99.22 212 | 99.07 35 | 96.38 206 | 98.79 165 |
|
XVG-OURS | | | 98.73 96 | 98.68 86 | 98.88 146 | 99.70 59 | 97.73 186 | 98.92 244 | 99.55 50 | 98.52 41 | 99.45 66 | 99.84 32 | 95.27 128 | 99.91 56 | 98.08 118 | 98.84 128 | 99.00 154 |
|
diffmvs | | | 98.72 97 | 98.49 103 | 99.43 87 | 99.48 103 | 99.19 78 | 99.62 64 | 99.42 142 | 95.58 227 | 99.37 80 | 99.67 106 | 96.14 108 | 99.74 120 | 98.14 111 | 98.96 116 | 99.37 129 |
|
XVG-OURS-SEG-HR | | | 98.69 98 | 98.62 95 | 98.89 144 | 99.71 54 | 97.74 185 | 99.12 206 | 99.54 57 | 98.44 46 | 99.42 71 | 99.71 89 | 94.20 178 | 99.92 47 | 98.54 87 | 98.90 124 | 99.00 154 |
|
liao1 | | | 98.68 99 | 98.54 102 | 99.11 113 | 98.89 217 | 98.65 148 | 99.27 176 | 99.49 92 | 96.89 165 | 97.99 228 | 99.56 142 | 97.72 75 | 99.83 97 | 97.74 142 | 99.27 100 | 98.84 162 |
|
EI-MVSNet | | | 98.67 100 | 98.67 87 | 98.68 167 | 99.35 124 | 97.97 180 | 99.50 107 | 99.38 159 | 96.93 164 | 99.20 121 | 99.83 34 | 97.87 69 | 99.36 181 | 98.38 96 | 97.56 172 | 98.71 178 |
|
test_djsdf | | | 98.67 100 | 98.57 100 | 98.98 124 | 98.70 244 | 98.91 112 | 99.88 1 | 99.46 116 | 97.55 116 | 99.22 117 | 99.88 13 | 95.73 119 | 99.28 198 | 99.03 37 | 97.62 168 | 98.75 172 |
|
QAPM | | | 98.67 100 | 98.30 113 | 99.80 22 | 99.20 151 | 99.67 26 | 99.77 24 | 99.72 9 | 94.74 235 | 98.73 179 | 99.90 7 | 95.78 117 | 99.98 2 | 96.96 191 | 99.88 26 | 99.76 44 |
|
nrg030 | | | 98.64 103 | 98.42 105 | 99.28 101 | 99.05 181 | 99.69 23 | 99.81 15 | 99.46 116 | 98.04 80 | 99.01 147 | 99.82 42 | 96.69 98 | 99.38 174 | 99.34 14 | 94.59 240 | 98.78 166 |
|
PAPR | | | 98.63 104 | 98.34 109 | 99.51 74 | 99.40 116 | 99.03 93 | 98.80 252 | 99.36 165 | 96.33 201 | 99.00 153 | 99.12 226 | 98.46 53 | 99.84 91 | 95.23 234 | 99.37 99 | 99.66 78 |
|
CVMVSNet | | | 98.57 105 | 98.67 87 | 98.30 197 | 99.35 124 | 95.59 239 | 99.50 107 | 99.55 50 | 98.60 38 | 99.39 77 | 99.83 34 | 94.48 169 | 99.45 164 | 98.75 60 | 98.56 140 | 99.85 6 |
|
MVSTER | | | 98.49 106 | 98.32 111 | 99.00 122 | 99.35 124 | 99.02 94 | 99.54 96 | 99.38 159 | 97.41 128 | 99.20 121 | 99.73 85 | 93.86 190 | 99.36 181 | 98.87 50 | 97.56 172 | 98.62 223 |
|
OpenMVS |  | 96.50 16 | 98.47 107 | 98.12 119 | 99.52 72 | 99.04 182 | 99.53 47 | 99.82 13 | 99.72 9 | 94.56 240 | 98.08 223 | 99.88 13 | 94.73 160 | 99.98 2 | 97.47 164 | 99.76 65 | 99.06 150 |
|
IterMVS-LS | | | 98.46 108 | 98.42 105 | 98.58 172 | 99.59 86 | 98.00 178 | 99.37 155 | 99.43 141 | 96.94 163 | 99.07 139 | 99.59 134 | 97.87 69 | 99.03 229 | 98.32 103 | 95.62 216 | 98.71 178 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
jajsoiax | | | 98.43 109 | 98.28 114 | 98.88 146 | 98.60 251 | 98.43 167 | 99.82 13 | 99.53 67 | 98.19 60 | 98.63 197 | 99.80 58 | 93.22 198 | 99.44 169 | 99.22 22 | 97.50 176 | 98.77 169 |
|
BH-untuned | | | 98.42 110 | 98.36 107 | 98.59 171 | 99.49 100 | 96.70 217 | 99.27 176 | 99.13 221 | 97.24 142 | 98.80 174 | 99.38 186 | 95.75 118 | 99.74 120 | 97.07 184 | 99.16 103 | 99.33 132 |
|
BH-RMVSNet | | | 98.41 111 | 98.08 122 | 99.40 89 | 99.41 113 | 98.83 120 | 99.30 169 | 98.77 251 | 97.70 108 | 98.94 158 | 99.65 113 | 92.91 204 | 99.74 120 | 96.52 211 | 99.55 91 | 99.64 85 |
|
mvs_tets | | | 98.40 112 | 98.23 115 | 98.91 138 | 98.67 247 | 98.51 162 | 99.66 52 | 99.53 67 | 98.19 60 | 98.65 195 | 99.81 51 | 92.75 206 | 99.44 169 | 99.31 16 | 97.48 180 | 98.77 169 |
|
XXY-MVS | | | 98.38 113 | 98.09 121 | 99.24 103 | 99.26 143 | 99.32 67 | 99.56 88 | 99.55 50 | 97.45 124 | 98.71 181 | 99.83 34 | 93.23 197 | 99.63 151 | 98.88 48 | 96.32 208 | 98.76 171 |
|
ACMM | | 97.58 5 | 98.37 114 | 98.34 109 | 98.48 183 | 99.41 113 | 97.10 199 | 99.56 88 | 99.45 127 | 98.53 40 | 99.04 144 | 99.85 24 | 93.00 200 | 99.71 133 | 98.74 61 | 97.45 181 | 98.64 216 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
tpmrst | | | 98.33 115 | 98.48 104 | 97.90 227 | 99.16 161 | 94.78 253 | 99.31 167 | 99.11 222 | 97.27 138 | 99.45 66 | 99.59 134 | 95.33 125 | 99.84 91 | 98.48 90 | 98.61 134 | 99.09 147 |
|
PatchmatchNet |  | | 98.31 116 | 98.36 107 | 98.19 212 | 99.16 161 | 95.32 245 | 99.27 176 | 98.92 240 | 97.37 131 | 99.37 80 | 99.58 137 | 94.90 149 | 99.70 138 | 97.43 167 | 99.21 101 | 99.54 102 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
VPA-MVSNet | | | 98.29 117 | 97.95 132 | 99.30 97 | 99.16 161 | 99.54 44 | 99.50 107 | 99.58 39 | 98.27 55 | 99.35 87 | 99.37 189 | 92.53 215 | 99.65 145 | 99.35 10 | 94.46 241 | 98.72 176 |
|
UniMVSNet (Re) | | | 98.29 117 | 98.00 128 | 99.13 112 | 99.00 188 | 99.36 65 | 99.49 112 | 99.51 79 | 97.95 86 | 98.97 156 | 99.13 223 | 96.30 104 | 99.38 174 | 98.36 99 | 93.34 256 | 98.66 212 |
|
HQP_MVS | | | 98.27 119 | 98.22 116 | 98.44 187 | 99.29 136 | 96.97 209 | 99.39 149 | 99.47 112 | 98.97 21 | 99.11 133 | 99.61 131 | 92.71 209 | 99.69 140 | 97.78 136 | 97.63 166 | 98.67 203 |
|
UniMVSNet_NR-MVSNet | | | 98.22 120 | 97.97 130 | 98.96 126 | 98.92 211 | 98.98 100 | 99.48 117 | 99.53 67 | 97.76 100 | 98.71 181 | 99.46 169 | 96.43 102 | 99.22 212 | 98.57 80 | 92.87 262 | 98.69 187 |
|
LPG-MVS_test | | | 98.22 120 | 98.13 118 | 98.49 181 | 99.33 128 | 97.05 203 | 99.58 76 | 99.55 50 | 97.46 121 | 99.24 111 | 99.83 34 | 92.58 213 | 99.72 128 | 98.09 114 | 97.51 174 | 98.68 192 |
|
RPSCF | | | 98.22 120 | 98.62 95 | 96.99 249 | 99.82 20 | 91.58 274 | 99.72 38 | 99.44 133 | 96.61 180 | 99.66 35 | 99.89 10 | 95.92 114 | 99.82 102 | 97.46 165 | 99.10 107 | 99.57 99 |
|
ADS-MVSNet | | | 98.20 123 | 98.08 122 | 98.56 175 | 99.33 128 | 96.48 225 | 99.23 187 | 99.15 219 | 96.24 207 | 99.10 135 | 99.67 106 | 94.11 182 | 99.71 133 | 96.81 197 | 99.05 111 | 99.48 113 |
|
CR-MVSNet | | | 98.17 124 | 97.93 134 | 98.87 149 | 99.18 155 | 98.49 163 | 99.22 190 | 99.33 185 | 96.96 161 | 99.56 50 | 99.38 186 | 94.33 174 | 99.00 232 | 94.83 240 | 98.58 137 | 99.14 140 |
|
CLD-MVS | | | 98.16 125 | 98.10 120 | 98.33 194 | 99.29 136 | 96.82 215 | 98.75 256 | 99.44 133 | 97.83 94 | 99.13 129 | 99.55 145 | 92.92 202 | 99.67 142 | 98.32 103 | 97.69 165 | 98.48 243 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
WR-MVS_H | | | 98.13 126 | 97.87 139 | 98.90 142 | 99.02 186 | 98.84 117 | 99.70 41 | 99.59 35 | 97.27 138 | 98.40 210 | 99.19 220 | 95.53 122 | 99.23 209 | 98.34 100 | 93.78 254 | 98.61 232 |
|
v1neww | | | 98.12 127 | 97.84 140 | 98.93 131 | 98.97 196 | 98.81 129 | 99.66 52 | 99.35 169 | 96.49 187 | 99.29 98 | 99.37 189 | 95.02 139 | 99.32 189 | 97.73 143 | 94.73 232 | 98.67 203 |
|
v7new | | | 98.12 127 | 97.84 140 | 98.93 131 | 98.97 196 | 98.81 129 | 99.66 52 | 99.35 169 | 96.49 187 | 99.29 98 | 99.37 189 | 95.02 139 | 99.32 189 | 97.73 143 | 94.73 232 | 98.67 203 |
|
v6 | | | 98.12 127 | 97.84 140 | 98.94 129 | 98.94 204 | 98.83 120 | 99.66 52 | 99.34 177 | 96.49 187 | 99.30 94 | 99.37 189 | 94.95 143 | 99.34 186 | 97.77 138 | 94.74 231 | 98.67 203 |
|
ACMH | | 97.28 8 | 98.10 130 | 97.99 129 | 98.44 187 | 99.41 113 | 96.96 211 | 99.60 71 | 99.56 43 | 98.09 71 | 98.15 220 | 99.91 5 | 90.87 232 | 99.70 138 | 98.88 48 | 97.45 181 | 98.67 203 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
CP-MVSNet | | | 98.09 131 | 97.78 146 | 99.01 120 | 98.97 196 | 99.24 76 | 99.67 50 | 99.46 116 | 97.25 140 | 98.48 207 | 99.64 119 | 93.79 191 | 99.06 224 | 98.63 71 | 94.10 248 | 98.74 175 |
|
DU-MVS | | | 98.08 132 | 97.79 144 | 98.96 126 | 98.87 220 | 98.98 100 | 99.41 142 | 99.45 127 | 97.87 88 | 98.71 181 | 99.50 157 | 94.82 153 | 99.22 212 | 98.57 80 | 92.87 262 | 98.68 192 |
|
divwei89l23v2f112 | | | 98.06 133 | 97.78 146 | 98.91 138 | 98.90 214 | 98.77 140 | 99.57 82 | 99.35 169 | 96.45 194 | 99.24 111 | 99.37 189 | 94.92 147 | 99.27 200 | 97.50 160 | 94.71 236 | 98.68 192 |
|
v2v482 | | | 98.06 133 | 97.77 150 | 98.92 136 | 98.90 214 | 98.82 127 | 99.57 82 | 99.36 165 | 96.65 177 | 99.19 125 | 99.35 200 | 94.20 178 | 99.25 206 | 97.72 147 | 94.97 228 | 98.69 187 |
|
V42 | | | 98.06 133 | 97.79 144 | 98.86 153 | 98.98 193 | 98.84 117 | 99.69 43 | 99.34 177 | 96.53 186 | 99.30 94 | 99.37 189 | 94.67 162 | 99.32 189 | 97.57 156 | 94.66 237 | 98.42 245 |
|
test-LLR | | | 98.06 133 | 97.90 135 | 98.55 177 | 98.79 229 | 97.10 199 | 98.67 261 | 97.75 281 | 97.34 132 | 98.61 200 | 98.85 240 | 94.45 170 | 99.45 164 | 97.25 173 | 99.38 96 | 99.10 143 |
|
WR-MVS | | | 98.06 133 | 97.73 157 | 99.06 115 | 98.86 223 | 99.25 75 | 99.19 195 | 99.35 169 | 97.30 136 | 98.66 189 | 99.43 174 | 93.94 187 | 99.21 215 | 98.58 78 | 94.28 244 | 98.71 178 |
|
ACMP | | 97.20 11 | 98.06 133 | 97.94 133 | 98.45 186 | 99.37 121 | 97.01 206 | 99.44 128 | 99.49 92 | 97.54 119 | 98.45 208 | 99.79 66 | 91.95 222 | 99.72 128 | 97.91 127 | 97.49 179 | 98.62 223 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
v1141 | | | 98.05 139 | 97.76 153 | 98.91 138 | 98.91 213 | 98.78 138 | 99.57 82 | 99.35 169 | 96.41 198 | 99.23 115 | 99.36 196 | 94.93 146 | 99.27 200 | 97.38 169 | 94.72 234 | 98.68 192 |
|
v7 | | | 98.05 139 | 97.78 146 | 98.87 149 | 98.99 189 | 98.67 145 | 99.64 62 | 99.34 177 | 96.31 202 | 99.29 98 | 99.51 155 | 94.78 155 | 99.27 200 | 97.03 185 | 95.15 225 | 98.66 212 |
|
v1 | | | 98.05 139 | 97.76 153 | 98.93 131 | 98.92 211 | 98.80 134 | 99.57 82 | 99.35 169 | 96.39 200 | 99.28 102 | 99.36 196 | 94.86 152 | 99.32 189 | 97.38 169 | 94.72 234 | 98.68 192 |
|
EPNet_dtu | | | 98.03 142 | 97.96 131 | 98.23 208 | 98.27 258 | 95.54 241 | 99.23 187 | 98.75 252 | 99.02 9 | 97.82 232 | 99.71 89 | 96.11 109 | 99.48 161 | 93.04 258 | 99.65 86 | 99.69 70 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
FMVSNet3 | | | 98.03 142 | 97.76 153 | 98.84 157 | 99.39 118 | 98.98 100 | 99.40 148 | 99.38 159 | 96.67 176 | 99.07 139 | 99.28 212 | 92.93 201 | 98.98 235 | 97.10 181 | 96.65 199 | 98.56 238 |
|
ADS-MVSNet2 | | | 98.02 144 | 98.07 124 | 97.87 228 | 99.33 128 | 95.19 248 | 99.23 187 | 99.08 224 | 96.24 207 | 99.10 135 | 99.67 106 | 94.11 182 | 98.93 243 | 96.81 197 | 99.05 111 | 99.48 113 |
|
HQP-MVS | | | 98.02 144 | 97.90 135 | 98.37 192 | 99.19 152 | 96.83 213 | 98.98 232 | 99.39 154 | 98.24 56 | 98.66 189 | 99.40 181 | 92.47 217 | 99.64 147 | 97.19 177 | 97.58 170 | 98.64 216 |
|
LTVRE_ROB | | 97.16 12 | 98.02 144 | 97.90 135 | 98.40 190 | 99.23 146 | 96.80 216 | 99.70 41 | 99.60 32 | 97.12 150 | 98.18 219 | 99.70 92 | 91.73 224 | 99.72 128 | 98.39 94 | 97.45 181 | 98.68 192 |
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 |
PatchFormer-LS_test | | | 98.01 147 | 98.05 125 | 97.87 228 | 99.15 164 | 94.76 254 | 99.42 138 | 98.93 238 | 97.12 150 | 98.84 171 | 98.59 251 | 93.74 195 | 99.80 109 | 98.55 85 | 98.17 152 | 99.06 150 |
|
BH-w/o | | | 98.00 148 | 97.89 138 | 98.32 195 | 99.35 124 | 96.20 233 | 99.01 227 | 98.90 245 | 96.42 196 | 98.38 211 | 99.00 233 | 95.26 129 | 99.72 128 | 96.06 218 | 98.61 134 | 99.03 152 |
|
v1144 | | | 97.98 149 | 97.69 160 | 98.85 156 | 98.87 220 | 98.66 147 | 99.54 96 | 99.35 169 | 96.27 204 | 99.23 115 | 99.35 200 | 94.67 162 | 99.23 209 | 96.73 202 | 95.16 224 | 98.68 192 |
|
EU-MVSNet | | | 97.98 149 | 98.03 126 | 97.81 233 | 98.72 241 | 96.65 220 | 99.66 52 | 99.66 22 | 98.09 71 | 98.35 213 | 99.82 42 | 95.25 130 | 98.01 264 | 97.41 168 | 95.30 221 | 98.78 166 |
|
tpmvs | | | 97.98 149 | 98.02 127 | 97.84 231 | 99.04 182 | 94.73 255 | 99.31 167 | 99.20 214 | 96.10 218 | 98.76 178 | 99.42 175 | 94.94 144 | 99.81 107 | 96.97 190 | 98.45 144 | 98.97 157 |
|
NR-MVSNet | | | 97.97 152 | 97.61 164 | 99.02 119 | 98.87 220 | 99.26 74 | 99.47 121 | 99.42 142 | 97.63 111 | 97.08 242 | 99.50 157 | 95.07 137 | 99.13 219 | 97.86 130 | 93.59 255 | 98.68 192 |
|
v8 | | | 97.95 153 | 97.63 163 | 98.93 131 | 98.95 201 | 98.81 129 | 99.80 19 | 99.41 145 | 96.03 219 | 99.10 135 | 99.42 175 | 94.92 147 | 99.30 195 | 96.94 193 | 94.08 249 | 98.66 212 |
|
PS-CasMVS | | | 97.93 154 | 97.59 166 | 98.95 128 | 98.99 189 | 99.06 90 | 99.68 48 | 99.52 71 | 97.13 148 | 98.31 215 | 99.68 102 | 92.44 220 | 99.05 225 | 98.51 88 | 94.08 249 | 98.75 172 |
|
TranMVSNet+NR-MVSNet | | | 97.93 154 | 97.66 161 | 98.76 164 | 98.78 233 | 98.62 152 | 99.65 60 | 99.49 92 | 97.76 100 | 98.49 206 | 99.60 133 | 94.23 177 | 98.97 242 | 98.00 122 | 92.90 260 | 98.70 182 |
|
v144192 | | | 97.92 156 | 97.60 165 | 98.87 149 | 98.83 226 | 98.65 148 | 99.55 93 | 99.34 177 | 96.20 210 | 99.32 92 | 99.40 181 | 94.36 173 | 99.26 205 | 96.37 215 | 95.03 227 | 98.70 182 |
|
ACMH+ | | 97.24 10 | 97.92 156 | 97.78 146 | 98.32 195 | 99.46 105 | 96.68 219 | 99.56 88 | 99.54 57 | 98.41 47 | 97.79 234 | 99.87 18 | 90.18 239 | 99.66 144 | 98.05 121 | 97.18 194 | 98.62 223 |
|
LFMVS | | | 97.90 158 | 97.35 192 | 99.54 64 | 99.52 93 | 99.01 96 | 99.39 149 | 98.24 272 | 97.10 154 | 99.65 38 | 99.79 66 | 84.79 271 | 99.91 56 | 99.28 18 | 98.38 147 | 99.69 70 |
|
OurMVSNet-221017-0 | | | 97.88 159 | 97.77 150 | 98.19 212 | 98.71 243 | 96.53 223 | 99.88 1 | 99.00 232 | 97.79 97 | 98.78 176 | 99.94 3 | 91.68 225 | 99.35 184 | 97.21 175 | 96.99 197 | 98.69 187 |
|
v7n | | | 97.87 160 | 97.52 170 | 98.92 136 | 98.76 237 | 98.58 155 | 99.84 9 | 99.46 116 | 96.20 210 | 98.91 161 | 99.70 92 | 94.89 150 | 99.44 169 | 96.03 219 | 93.89 253 | 98.75 172 |
|
v10 | | | 97.85 161 | 97.52 170 | 98.86 153 | 98.99 189 | 98.67 145 | 99.75 33 | 99.41 145 | 95.70 225 | 98.98 155 | 99.41 178 | 94.75 159 | 99.23 209 | 96.01 220 | 94.63 239 | 98.67 203 |
|
GA-MVS | | | 97.85 161 | 97.47 177 | 99.00 122 | 99.38 119 | 97.99 179 | 98.57 267 | 99.15 219 | 97.04 157 | 98.90 163 | 99.30 209 | 89.83 241 | 99.38 174 | 96.70 204 | 98.33 148 | 99.62 90 |
|
VPNet | | | 97.84 163 | 97.44 182 | 99.01 120 | 99.21 149 | 98.94 107 | 99.48 117 | 99.57 40 | 98.38 48 | 99.28 102 | 99.73 85 | 88.89 248 | 99.39 173 | 99.19 24 | 93.27 257 | 98.71 178 |
|
LCM-MVSNet-Re | | | 97.83 164 | 98.15 117 | 96.87 253 | 99.30 134 | 92.25 272 | 99.59 73 | 98.26 271 | 97.43 125 | 96.20 250 | 99.13 223 | 96.27 105 | 98.73 248 | 98.17 109 | 98.99 113 | 99.64 85 |
|
XVG-ACMP-BASELINE | | | 97.83 164 | 97.71 159 | 98.20 211 | 99.11 169 | 96.33 229 | 99.41 142 | 99.52 71 | 98.06 79 | 99.05 143 | 99.50 157 | 89.64 243 | 99.73 126 | 97.73 143 | 97.38 187 | 98.53 240 |
|
IterMVS | | | 97.83 164 | 97.77 150 | 98.02 218 | 99.58 87 | 96.27 231 | 99.02 225 | 99.48 99 | 97.22 144 | 98.71 181 | 99.70 92 | 92.75 206 | 99.13 219 | 97.46 165 | 96.00 212 | 98.67 203 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
EPMVS | | | 97.82 167 | 97.65 162 | 98.35 193 | 98.88 218 | 95.98 235 | 99.49 112 | 94.71 292 | 97.57 115 | 99.26 109 | 99.48 164 | 92.46 219 | 99.71 133 | 97.87 129 | 99.08 109 | 99.35 130 |
|
MV-PatchMatch | | | 97.81 168 | 97.75 156 | 97.99 221 | 97.53 267 | 96.60 221 | 98.96 237 | 98.85 247 | 97.22 144 | 97.23 240 | 99.36 196 | 95.28 127 | 99.46 163 | 95.51 229 | 99.78 62 | 97.92 262 |
|
v1192 | | | 97.81 168 | 97.44 182 | 98.91 138 | 98.88 218 | 98.68 144 | 99.51 102 | 99.34 177 | 96.18 212 | 99.20 121 | 99.34 203 | 94.03 185 | 99.36 181 | 95.32 233 | 95.18 223 | 98.69 187 |
|
v1921920 | | | 97.80 170 | 97.45 179 | 98.84 157 | 98.80 227 | 98.53 158 | 99.52 100 | 99.34 177 | 96.15 214 | 99.24 111 | 99.47 168 | 93.98 186 | 99.29 197 | 95.40 231 | 95.13 226 | 98.69 187 |
|
V4 | | | 97.80 170 | 97.51 172 | 98.67 169 | 98.79 229 | 98.63 150 | 99.87 4 | 99.44 133 | 95.87 221 | 99.01 147 | 99.46 169 | 94.52 167 | 99.33 187 | 96.64 210 | 93.97 251 | 98.05 255 |
|
v148 | | | 97.79 172 | 97.55 167 | 98.50 179 | 98.74 238 | 97.72 187 | 99.54 96 | 99.33 185 | 96.26 205 | 98.90 163 | 99.51 155 | 94.68 161 | 99.14 218 | 97.83 132 | 93.15 259 | 98.63 222 |
|
v52 | | | 97.79 172 | 97.50 173 | 98.66 170 | 98.80 227 | 98.62 152 | 99.87 4 | 99.44 133 | 95.87 221 | 99.01 147 | 99.46 169 | 94.44 172 | 99.33 187 | 96.65 209 | 93.96 252 | 98.05 255 |
|
pm-mvs1 | | | 97.77 174 | 97.53 169 | 98.50 179 | 98.46 254 | 97.92 181 | 99.15 200 | 99.31 192 | 95.87 221 | 98.58 202 | 99.58 137 | 94.51 168 | 99.04 226 | 96.74 201 | 95.59 217 | 98.56 238 |
|
PEN-MVS | | | 97.76 175 | 97.44 182 | 98.72 166 | 98.77 236 | 98.54 157 | 99.78 22 | 99.51 79 | 97.06 156 | 98.29 217 | 99.64 119 | 92.63 212 | 98.89 244 | 98.09 114 | 93.16 258 | 98.72 176 |
|
Baseline_NR-MVSNet | | | 97.76 175 | 97.45 179 | 98.68 167 | 99.09 174 | 98.29 170 | 99.41 142 | 98.85 247 | 95.65 226 | 98.63 197 | 99.67 106 | 94.82 153 | 99.10 223 | 98.07 119 | 92.89 261 | 98.64 216 |
|
TR-MVS | | | 97.76 175 | 97.41 187 | 98.82 159 | 99.06 179 | 97.87 182 | 98.87 249 | 98.56 265 | 96.63 179 | 98.68 188 | 99.22 218 | 92.49 216 | 99.65 145 | 95.40 231 | 97.79 163 | 98.95 159 |
|
Patchmtry | | | 97.75 178 | 97.40 188 | 98.81 160 | 99.10 172 | 98.87 114 | 99.11 209 | 99.33 185 | 94.83 233 | 98.81 173 | 99.38 186 | 94.33 174 | 99.02 230 | 96.10 217 | 95.57 218 | 98.53 240 |
|
dp | | | 97.75 178 | 97.80 143 | 97.59 240 | 99.10 172 | 93.71 264 | 99.32 164 | 98.88 246 | 96.48 193 | 99.08 138 | 99.55 145 | 92.67 211 | 99.82 102 | 96.52 211 | 98.58 137 | 99.24 137 |
|
TAPA-MVS | | 97.07 15 | 97.74 180 | 97.34 195 | 98.94 129 | 99.70 59 | 97.53 188 | 99.25 184 | 99.51 79 | 91.90 267 | 99.30 94 | 99.63 123 | 98.78 32 | 99.64 147 | 88.09 273 | 99.87 28 | 99.65 80 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
VDD-MVS | | | 97.73 181 | 97.35 192 | 98.88 146 | 99.47 104 | 97.12 198 | 99.34 162 | 98.85 247 | 98.19 60 | 99.67 30 | 99.85 24 | 82.98 275 | 99.92 47 | 99.49 5 | 98.32 149 | 99.60 92 |
|
MIMVSNet | | | 97.73 181 | 97.45 179 | 98.57 173 | 99.45 108 | 97.50 189 | 99.02 225 | 98.98 234 | 96.11 216 | 99.41 73 | 99.14 222 | 90.28 235 | 98.74 247 | 95.74 224 | 98.93 119 | 99.47 117 |
|
CostFormer | | | 97.72 183 | 97.73 157 | 97.71 238 | 99.15 164 | 94.02 260 | 99.54 96 | 99.02 231 | 94.67 236 | 99.04 144 | 99.35 200 | 92.35 221 | 99.77 115 | 98.50 89 | 97.94 160 | 99.34 131 |
|
FMVSNet2 | | | 97.72 183 | 97.36 190 | 98.80 161 | 99.51 95 | 98.84 117 | 99.45 124 | 99.42 142 | 96.49 187 | 98.86 170 | 99.29 211 | 90.26 236 | 98.98 235 | 96.44 213 | 96.56 202 | 98.58 237 |
|
test0.0.03 1 | | | 97.71 185 | 97.42 186 | 98.56 175 | 98.41 256 | 97.82 183 | 98.78 253 | 98.63 261 | 97.34 132 | 98.05 227 | 98.98 236 | 94.45 170 | 98.98 235 | 95.04 237 | 97.15 195 | 98.89 160 |
|
v1240 | | | 97.69 186 | 97.32 198 | 98.79 162 | 98.85 224 | 98.43 167 | 99.48 117 | 99.36 165 | 96.11 216 | 99.27 106 | 99.36 196 | 93.76 193 | 99.24 208 | 94.46 245 | 95.23 222 | 98.70 182 |
|
cascas | | | 97.69 186 | 97.43 185 | 98.48 183 | 98.60 251 | 97.30 190 | 98.18 279 | 99.39 154 | 92.96 260 | 98.41 209 | 98.78 247 | 93.77 192 | 99.27 200 | 98.16 110 | 98.61 134 | 98.86 161 |
|
GBi-Net | | | 97.68 188 | 97.48 175 | 98.29 198 | 99.51 95 | 97.26 193 | 99.43 132 | 99.48 99 | 96.49 187 | 99.07 139 | 99.32 206 | 90.26 236 | 98.98 235 | 97.10 181 | 96.65 199 | 98.62 223 |
|
test1 | | | 97.68 188 | 97.48 175 | 98.29 198 | 99.51 95 | 97.26 193 | 99.43 132 | 99.48 99 | 96.49 187 | 99.07 139 | 99.32 206 | 90.26 236 | 98.98 235 | 97.10 181 | 96.65 199 | 98.62 223 |
|
tpm | | | 97.67 190 | 97.55 167 | 98.03 216 | 99.02 186 | 95.01 251 | 99.43 132 | 98.54 266 | 96.44 195 | 99.12 131 | 99.34 203 | 91.83 223 | 99.60 154 | 97.75 141 | 96.46 204 | 99.48 113 |
|
PCF-MVS | | 97.08 14 | 97.66 191 | 97.06 207 | 99.47 78 | 99.61 82 | 99.09 87 | 98.04 280 | 99.25 210 | 91.24 270 | 98.51 204 | 99.70 92 | 94.55 165 | 99.91 56 | 92.76 260 | 99.85 42 | 99.42 126 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
testgi | | | 97.65 192 | 97.50 173 | 98.13 214 | 99.36 123 | 96.45 226 | 99.42 138 | 99.48 99 | 97.76 100 | 97.87 231 | 99.45 172 | 91.09 229 | 98.81 246 | 94.53 243 | 98.52 141 | 99.13 142 |
|
PAPM | | | 97.59 193 | 97.09 206 | 99.07 114 | 99.06 179 | 98.26 172 | 98.30 275 | 99.10 223 | 94.88 232 | 98.08 223 | 99.34 203 | 96.27 105 | 99.64 147 | 89.87 268 | 98.92 122 | 99.31 133 |
|
VDDNet | | | 97.55 194 | 97.02 208 | 99.16 109 | 99.49 100 | 98.12 177 | 99.38 153 | 99.30 195 | 95.35 229 | 99.68 26 | 99.90 7 | 82.62 277 | 99.93 40 | 99.31 16 | 98.13 154 | 99.42 126 |
|
TESTMET0.1,1 | | | 97.55 194 | 97.27 201 | 98.40 190 | 98.93 209 | 96.53 223 | 98.67 261 | 97.61 285 | 96.96 161 | 98.64 196 | 99.28 212 | 88.63 254 | 99.45 164 | 97.30 172 | 99.38 96 | 99.21 138 |
|
DWT-MVSNet_test | | | 97.53 196 | 97.40 188 | 97.93 224 | 99.03 184 | 94.86 252 | 99.57 82 | 98.63 261 | 96.59 184 | 98.36 212 | 98.79 245 | 89.32 245 | 99.74 120 | 98.14 111 | 98.16 153 | 99.20 139 |
|
v748 | | | 97.52 197 | 97.23 202 | 98.41 189 | 98.69 245 | 97.23 196 | 99.87 4 | 99.45 127 | 95.72 224 | 98.51 204 | 99.53 149 | 94.13 181 | 99.30 195 | 96.78 199 | 92.39 265 | 98.70 182 |
|
LF4IMVS | | | 97.52 197 | 97.46 178 | 97.70 239 | 98.98 193 | 95.55 240 | 99.29 172 | 98.82 250 | 98.07 75 | 98.66 189 | 99.64 119 | 89.97 240 | 99.61 153 | 97.01 186 | 96.68 198 | 97.94 260 |
|
DTE-MVSNet | | | 97.51 199 | 97.19 204 | 98.46 185 | 98.63 250 | 98.13 176 | 99.84 9 | 99.48 99 | 96.68 175 | 97.97 229 | 99.67 106 | 92.92 202 | 98.56 250 | 96.88 196 | 92.60 264 | 98.70 182 |
|
SixPastTwentyTwo | | | 97.50 200 | 97.33 197 | 98.03 216 | 98.65 248 | 96.23 232 | 99.77 24 | 98.68 259 | 97.14 147 | 97.90 230 | 99.93 4 | 90.45 234 | 99.18 217 | 97.00 187 | 96.43 205 | 98.67 203 |
|
JIA-IIPM | | | 97.50 200 | 97.02 208 | 98.93 131 | 98.73 239 | 97.80 184 | 99.30 169 | 98.97 235 | 91.73 268 | 98.91 161 | 94.86 283 | 95.10 136 | 99.71 133 | 97.58 155 | 97.98 159 | 99.28 135 |
|
test-mter | | | 97.49 202 | 97.13 205 | 98.55 177 | 98.79 229 | 97.10 199 | 98.67 261 | 97.75 281 | 96.65 177 | 98.61 200 | 98.85 240 | 88.23 259 | 99.45 164 | 97.25 173 | 99.38 96 | 99.10 143 |
|
DI_MVS_test_dynamic | | | 97.45 203 | 96.79 212 | 99.44 84 | 97.76 265 | 99.04 92 | 99.21 192 | 98.61 263 | 97.74 103 | 94.01 266 | 98.83 242 | 87.38 263 | 99.83 97 | 98.63 71 | 98.90 124 | 99.44 123 |
|
DI_MVS_test_normal | | | 97.44 204 | 96.77 214 | 99.44 84 | 97.75 266 | 99.00 98 | 99.10 211 | 98.64 260 | 97.71 106 | 93.93 269 | 98.82 243 | 87.39 262 | 99.83 97 | 98.61 75 | 98.97 115 | 99.49 111 |
|
tpm2 | | | 97.44 204 | 97.34 195 | 97.74 237 | 99.15 164 | 94.36 258 | 99.45 124 | 98.94 237 | 93.45 258 | 98.90 163 | 99.44 173 | 91.35 227 | 99.59 155 | 97.31 171 | 98.07 156 | 99.29 134 |
|
tpm cat1 | | | 97.39 206 | 97.36 190 | 97.50 243 | 99.17 159 | 93.73 262 | 99.43 132 | 99.31 192 | 91.27 269 | 98.71 181 | 99.08 227 | 94.31 176 | 99.77 115 | 96.41 214 | 98.50 142 | 99.00 154 |
|
tpmp4_e23 | | | 97.34 207 | 97.29 200 | 97.52 241 | 99.25 145 | 93.73 262 | 99.58 76 | 99.19 217 | 94.00 250 | 98.20 218 | 99.41 178 | 90.74 233 | 99.74 120 | 97.13 180 | 98.07 156 | 99.07 149 |
|
USDC | | | 97.34 207 | 97.20 203 | 97.75 236 | 99.07 177 | 95.20 247 | 98.51 270 | 99.04 229 | 97.99 84 | 98.31 215 | 99.86 21 | 89.02 246 | 99.55 158 | 95.67 227 | 97.36 188 | 98.49 242 |
|
HC-MVS | | | 97.28 209 | 96.55 216 | 99.48 76 | 98.78 233 | 98.95 104 | 99.27 176 | 99.39 154 | 83.53 284 | 98.08 223 | 99.54 148 | 96.97 91 | 99.87 80 | 94.23 252 | 99.16 103 | 99.63 88 |
|
DSMNet-mixed | | | 97.25 210 | 97.35 192 | 96.95 251 | 97.84 263 | 93.61 266 | 99.57 82 | 96.63 288 | 96.13 215 | 98.87 166 | 98.61 250 | 94.59 164 | 97.70 269 | 95.08 236 | 98.86 127 | 99.55 100 |
|
MS-PatchMatch | | | 97.24 211 | 97.32 198 | 96.99 249 | 98.45 255 | 93.51 267 | 98.82 251 | 99.32 191 | 97.41 128 | 98.13 221 | 99.30 209 | 88.99 247 | 99.56 156 | 95.68 226 | 99.80 58 | 97.90 263 |
|
TransMVSNet (Re) | | | 97.15 212 | 96.58 215 | 98.86 153 | 99.12 167 | 98.85 116 | 99.49 112 | 98.91 243 | 95.48 228 | 97.16 241 | 99.80 58 | 93.38 196 | 99.11 222 | 94.16 254 | 91.73 266 | 98.62 223 |
|
TinyColmap | | | 97.12 213 | 96.89 210 | 97.83 232 | 99.07 177 | 95.52 242 | 98.57 267 | 98.74 255 | 97.58 114 | 97.81 233 | 99.79 66 | 88.16 260 | 99.56 156 | 95.10 235 | 97.21 192 | 98.39 248 |
|
K. test v3 | | | 97.10 214 | 96.79 212 | 98.01 219 | 98.72 241 | 96.33 229 | 99.87 4 | 97.05 287 | 97.59 112 | 96.16 251 | 99.80 58 | 88.71 250 | 99.04 226 | 96.69 205 | 96.55 203 | 98.65 215 |
|
LP | | | 97.04 215 | 96.80 211 | 97.77 235 | 98.90 214 | 95.23 246 | 98.97 235 | 99.06 227 | 94.02 249 | 98.09 222 | 99.41 178 | 93.88 188 | 98.82 245 | 90.46 265 | 98.42 146 | 99.26 136 |
|
PatchT | | | 97.03 216 | 96.44 217 | 98.79 162 | 98.99 189 | 98.34 169 | 99.16 197 | 99.07 226 | 92.13 264 | 99.52 56 | 97.31 275 | 94.54 166 | 98.98 235 | 88.54 271 | 98.73 133 | 99.03 152 |
|
FMVSNet1 | | | 96.84 217 | 96.36 218 | 98.29 198 | 99.32 132 | 97.26 193 | 99.43 132 | 99.48 99 | 95.11 230 | 98.55 203 | 99.32 206 | 83.95 274 | 98.98 235 | 95.81 223 | 96.26 209 | 98.62 223 |
|
test_0402 | | | 96.64 218 | 96.24 219 | 97.85 230 | 98.85 224 | 96.43 227 | 99.44 128 | 99.26 208 | 93.52 256 | 96.98 244 | 99.52 152 | 88.52 255 | 99.20 216 | 92.58 262 | 97.50 176 | 97.93 261 |
|
RPMNet | | | 96.61 219 | 95.85 225 | 98.87 149 | 99.18 155 | 98.49 163 | 99.22 190 | 99.08 224 | 88.72 280 | 99.56 50 | 97.38 274 | 94.08 184 | 99.00 232 | 86.87 277 | 98.58 137 | 99.14 140 |
|
X-MVStestdata | | | 96.55 220 | 95.45 238 | 99.87 2 | 99.85 15 | 99.83 3 | 99.69 43 | 99.68 16 | 98.98 18 | 99.37 80 | 64.01 296 | 98.81 30 | 99.94 27 | 98.79 58 | 99.86 38 | 99.84 10 |
|
UnsupCasMVSNet_eth | | | 96.44 221 | 96.12 221 | 97.40 245 | 98.65 248 | 95.65 237 | 99.36 158 | 99.51 79 | 97.13 148 | 96.04 254 | 98.99 234 | 88.40 257 | 98.17 253 | 96.71 203 | 90.27 268 | 98.40 247 |
|
FMVSNet5 | | | 96.43 222 | 96.19 220 | 97.15 247 | 99.11 169 | 95.89 236 | 99.32 164 | 99.52 71 | 94.47 243 | 98.34 214 | 99.07 228 | 87.54 261 | 97.07 272 | 92.61 261 | 95.72 214 | 98.47 244 |
|
v18 | | | 96.42 223 | 95.80 228 | 98.26 201 | 98.95 201 | 98.82 127 | 99.76 26 | 99.28 203 | 94.58 237 | 94.12 261 | 97.70 263 | 95.22 132 | 98.16 254 | 94.83 240 | 87.80 274 | 97.79 271 |
|
v17 | | | 96.42 223 | 95.81 227 | 98.25 205 | 98.94 204 | 98.80 134 | 99.76 26 | 99.28 203 | 94.57 238 | 94.18 260 | 97.71 262 | 95.23 131 | 98.16 254 | 94.86 238 | 87.73 276 | 97.80 266 |
|
v16 | | | 96.39 225 | 95.76 229 | 98.26 201 | 98.96 199 | 98.81 129 | 99.76 26 | 99.28 203 | 94.57 238 | 94.10 262 | 97.70 263 | 95.04 138 | 98.16 254 | 94.70 242 | 87.77 275 | 97.80 266 |
|
new_pmnet | | | 96.38 226 | 96.03 222 | 97.41 244 | 98.13 261 | 95.16 250 | 99.05 218 | 99.20 214 | 93.94 251 | 97.39 238 | 98.79 245 | 91.61 226 | 99.04 226 | 90.43 266 | 95.77 213 | 98.05 255 |
|
v15 | | | 96.28 227 | 95.62 231 | 98.25 205 | 98.94 204 | 98.83 120 | 99.76 26 | 99.29 196 | 94.52 241 | 94.02 265 | 97.61 270 | 95.02 139 | 98.13 258 | 94.53 243 | 86.92 279 | 97.80 266 |
|
V14 | | | 96.26 228 | 95.60 232 | 98.26 201 | 98.94 204 | 98.83 120 | 99.76 26 | 99.29 196 | 94.49 242 | 93.96 267 | 97.66 267 | 94.99 142 | 98.13 258 | 94.41 246 | 86.90 280 | 97.80 266 |
|
V9 | | | 96.25 229 | 95.58 233 | 98.26 201 | 98.94 204 | 98.83 120 | 99.75 33 | 99.29 196 | 94.45 244 | 93.96 267 | 97.62 269 | 94.94 144 | 98.14 257 | 94.40 247 | 86.87 281 | 97.81 264 |
|
v13 | | | 96.24 230 | 95.58 233 | 98.25 205 | 98.98 193 | 98.83 120 | 99.75 33 | 99.29 196 | 94.35 246 | 93.89 270 | 97.60 271 | 95.17 134 | 98.11 260 | 94.27 251 | 86.86 282 | 97.81 264 |
|
v12 | | | 96.24 230 | 95.58 233 | 98.23 208 | 98.96 199 | 98.81 129 | 99.76 26 | 99.29 196 | 94.42 245 | 93.85 271 | 97.60 271 | 95.12 135 | 98.09 261 | 94.32 248 | 86.85 283 | 97.80 266 |
|
v11 | | | 96.23 232 | 95.57 236 | 98.21 210 | 98.93 209 | 98.83 120 | 99.72 38 | 99.29 196 | 94.29 247 | 94.05 264 | 97.64 268 | 94.88 151 | 98.04 262 | 92.89 259 | 88.43 273 | 97.77 272 |
|
IB-MVS | | 95.67 18 | 96.22 233 | 95.44 239 | 98.57 173 | 99.21 149 | 96.70 217 | 98.65 264 | 97.74 283 | 96.71 173 | 97.27 239 | 98.54 253 | 86.03 265 | 99.92 47 | 98.47 92 | 86.30 284 | 99.10 143 |
Christian Sormann, Mattia Rossi, Andreas Kuhn and Friedrich Fraundorfer: IB-MVS: An Iterative Algorithm for Deep Multi-View Stereo based on Binary Decisions. BMVC 2021 |
gg-mvs-nofinetune | | | 96.17 234 | 95.32 240 | 98.73 165 | 98.79 229 | 98.14 175 | 99.38 153 | 94.09 293 | 91.07 272 | 98.07 226 | 91.04 289 | 89.62 244 | 99.35 184 | 96.75 200 | 99.09 108 | 98.68 192 |
|
test20.03 | | | 96.12 235 | 95.96 224 | 96.63 255 | 97.44 268 | 95.45 243 | 99.51 102 | 99.38 159 | 96.55 185 | 96.16 251 | 99.25 215 | 93.76 193 | 96.17 276 | 87.35 276 | 94.22 246 | 98.27 250 |
|
PVSNet_0 | | 94.43 19 | 96.09 236 | 95.47 237 | 97.94 223 | 99.31 133 | 94.34 259 | 97.81 281 | 99.70 12 | 97.12 150 | 97.46 237 | 98.75 248 | 89.71 242 | 99.79 112 | 97.69 149 | 81.69 287 | 99.68 74 |
|
EG-PatchMatch MVS | | | 95.97 237 | 95.69 230 | 96.81 254 | 97.78 264 | 92.79 270 | 99.16 197 | 98.93 238 | 96.16 213 | 94.08 263 | 99.22 218 | 82.72 276 | 99.47 162 | 95.67 227 | 97.50 176 | 98.17 252 |
|
MVS-HIRNet | | | 95.75 238 | 95.16 242 | 97.51 242 | 99.30 134 | 93.69 265 | 98.88 248 | 95.78 289 | 85.09 283 | 98.78 176 | 92.65 285 | 91.29 228 | 99.37 177 | 94.85 239 | 99.85 42 | 99.46 120 |
|
testpf | | | 95.66 239 | 96.02 223 | 94.58 261 | 98.35 257 | 92.32 271 | 97.25 286 | 97.91 279 | 92.83 261 | 97.03 243 | 98.99 234 | 88.69 251 | 98.61 249 | 95.72 225 | 97.40 185 | 92.80 285 |
|
MIMVSNet1 | | | 95.51 240 | 95.04 243 | 96.92 252 | 97.38 269 | 95.60 238 | 99.52 100 | 99.50 89 | 93.65 254 | 96.97 245 | 99.17 221 | 85.28 269 | 96.56 275 | 88.36 272 | 95.55 219 | 98.60 233 |
|
MDA-MVSNet_test_wron | | | 95.45 241 | 94.60 245 | 98.01 219 | 98.16 260 | 97.21 197 | 99.11 209 | 99.24 211 | 93.49 257 | 80.73 288 | 98.98 236 | 93.02 199 | 98.18 252 | 94.22 253 | 94.45 242 | 98.64 216 |
|
TDRefinement | | | 95.42 242 | 94.57 246 | 97.97 222 | 89.83 289 | 96.11 234 | 99.48 117 | 98.75 252 | 96.74 171 | 96.68 246 | 99.88 13 | 88.65 253 | 99.71 133 | 98.37 97 | 82.74 286 | 98.09 253 |
|
YYNet1 | | | 95.36 243 | 94.51 247 | 97.92 225 | 97.89 262 | 97.10 199 | 99.10 211 | 99.23 212 | 93.26 259 | 80.77 287 | 99.04 231 | 92.81 205 | 98.02 263 | 94.30 249 | 94.18 247 | 98.64 216 |
|
Test4 | | | 95.05 244 | 93.67 251 | 99.22 106 | 96.07 275 | 98.94 107 | 99.20 194 | 99.27 207 | 97.71 106 | 89.96 281 | 97.59 273 | 66.18 285 | 99.25 206 | 98.06 120 | 98.96 116 | 99.47 117 |
|
MDA-MVSNet-bldmvs | | | 94.96 245 | 93.98 249 | 97.92 225 | 98.24 259 | 97.27 192 | 99.15 200 | 99.33 185 | 93.80 253 | 80.09 289 | 99.03 232 | 88.31 258 | 97.86 267 | 93.49 257 | 94.36 243 | 98.62 223 |
|
N_pmnet | | | 94.95 246 | 95.83 226 | 92.31 267 | 98.47 253 | 79.33 290 | 99.12 206 | 92.81 297 | 93.87 252 | 97.68 236 | 99.13 223 | 93.87 189 | 99.01 231 | 91.38 263 | 96.19 210 | 98.59 234 |
|
testus | | | 94.61 247 | 95.30 241 | 92.54 266 | 96.44 274 | 84.18 283 | 98.36 271 | 99.03 230 | 94.18 248 | 96.49 247 | 98.57 252 | 88.74 249 | 95.09 280 | 87.41 275 | 98.45 144 | 98.36 249 |
|
testing_2 | | | 94.44 248 | 92.93 254 | 98.98 124 | 94.16 281 | 99.00 98 | 99.42 138 | 99.28 203 | 96.60 182 | 84.86 283 | 96.84 276 | 70.91 280 | 99.27 200 | 98.23 106 | 96.08 211 | 98.68 192 |
|
OpenMVS_ROB |  | 92.34 20 | 94.38 249 | 93.70 250 | 96.41 258 | 97.38 269 | 93.17 269 | 99.06 216 | 98.75 252 | 86.58 281 | 94.84 259 | 98.26 256 | 81.53 278 | 99.32 189 | 89.01 270 | 97.87 162 | 96.76 276 |
|
CMPMVS |  | 69.68 23 | 94.13 250 | 94.90 244 | 91.84 268 | 97.24 272 | 80.01 289 | 98.52 269 | 99.48 99 | 89.01 278 | 91.99 275 | 99.67 106 | 85.67 267 | 99.13 219 | 95.44 230 | 97.03 196 | 96.39 278 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
pmmvs3 | | | 94.09 251 | 93.25 253 | 96.60 256 | 94.76 280 | 94.49 256 | 98.92 244 | 98.18 275 | 89.66 275 | 96.48 248 | 98.06 257 | 86.28 264 | 97.33 271 | 89.68 269 | 87.20 278 | 97.97 259 |
|
test2356 | | | 94.07 252 | 94.46 248 | 92.89 264 | 95.18 279 | 86.13 281 | 97.60 284 | 99.06 227 | 93.61 255 | 96.15 253 | 98.28 254 | 85.60 268 | 93.95 282 | 86.68 278 | 98.00 158 | 98.59 234 |
|
HyFIR lowres test | | | 93.82 253 | 92.65 256 | 97.33 246 | 99.03 184 | 93.48 268 | 98.72 260 | 97.91 279 | 90.29 274 | 97.72 235 | 98.28 254 | 62.59 288 | 98.99 234 | 90.37 267 | 98.93 119 | 99.53 106 |
|
UnsupCasMVSNet_bld | | | 93.53 254 | 92.51 257 | 96.58 257 | 97.38 269 | 93.82 261 | 98.24 276 | 99.48 99 | 91.10 271 | 93.10 272 | 96.66 277 | 74.89 279 | 98.37 251 | 94.03 255 | 87.71 277 | 97.56 274 |
|
Patchmatch-RL test | | | 93.33 255 | 92.66 255 | 95.32 259 | 95.61 276 | 90.57 276 | 98.24 276 | 98.39 268 | 95.10 231 | 95.20 256 | 97.70 263 | 67.41 284 | 97.77 268 | 96.28 216 | 90.02 270 | 97.62 273 |
|
PM-MVS | | | 92.96 256 | 92.23 258 | 95.14 260 | 95.61 276 | 89.98 278 | 99.37 155 | 98.21 273 | 94.80 234 | 95.04 258 | 97.69 266 | 65.06 286 | 97.90 266 | 94.30 249 | 89.98 271 | 97.54 275 |
|
test1235678 | | | 92.91 257 | 93.30 252 | 91.71 270 | 93.14 284 | 83.01 285 | 98.75 256 | 98.58 264 | 92.80 262 | 92.45 273 | 97.91 259 | 88.51 256 | 93.54 283 | 82.26 282 | 95.35 220 | 98.59 234 |
|
1111 | | | 92.30 258 | 92.21 259 | 92.55 265 | 93.30 282 | 86.27 279 | 99.15 200 | 98.74 255 | 91.94 265 | 90.85 278 | 97.82 260 | 84.18 272 | 95.21 278 | 79.65 284 | 94.27 245 | 96.19 279 |
|
test12356 | | | 91.74 259 | 92.19 260 | 90.37 273 | 91.22 285 | 82.41 286 | 98.61 265 | 98.28 270 | 90.66 273 | 91.82 276 | 97.92 258 | 84.90 270 | 92.61 284 | 81.64 283 | 94.66 237 | 96.09 280 |
|
Gipuma |  | | 90.99 260 | 90.15 261 | 93.51 262 | 98.73 239 | 90.12 277 | 93.98 290 | 99.45 127 | 79.32 286 | 92.28 274 | 94.91 282 | 69.61 281 | 97.98 265 | 87.42 274 | 95.67 215 | 92.45 287 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
testmv | | | 87.91 261 | 87.80 262 | 88.24 274 | 87.68 292 | 77.50 292 | 99.07 213 | 97.66 284 | 89.27 276 | 86.47 282 | 96.22 280 | 68.35 282 | 92.49 286 | 76.63 288 | 88.82 272 | 94.72 283 |
|
PMMVS2 | | | 86.87 262 | 85.37 265 | 91.35 272 | 90.21 288 | 83.80 284 | 98.89 247 | 97.45 286 | 83.13 285 | 91.67 277 | 95.03 281 | 48.49 291 | 94.70 281 | 85.86 279 | 77.62 288 | 95.54 281 |
|
LCM-MVSNet | | | 86.80 263 | 85.22 266 | 91.53 271 | 87.81 291 | 80.96 288 | 98.23 278 | 98.99 233 | 71.05 289 | 90.13 280 | 96.51 278 | 48.45 292 | 96.88 273 | 90.51 264 | 85.30 285 | 96.76 276 |
|
FPMVS | | | 84.93 264 | 85.65 264 | 82.75 281 | 86.77 293 | 63.39 299 | 98.35 273 | 98.92 240 | 74.11 288 | 83.39 285 | 98.98 236 | 50.85 290 | 92.40 287 | 84.54 280 | 94.97 228 | 92.46 286 |
|
.test1245 | | | 83.42 265 | 86.17 263 | 75.15 284 | 93.30 282 | 86.27 279 | 99.15 200 | 98.74 255 | 91.94 265 | 90.85 278 | 97.82 260 | 84.18 272 | 95.21 278 | 79.65 284 | 39.90 297 | 43.98 296 |
|
no-one | | | 83.04 266 | 80.12 268 | 91.79 269 | 89.44 290 | 85.65 282 | 99.32 164 | 98.32 269 | 89.06 277 | 79.79 291 | 89.16 291 | 44.86 293 | 96.67 274 | 84.33 281 | 46.78 295 | 93.05 284 |
|
DUST3R | | | 82.80 267 | 81.52 267 | 86.66 275 | 66.61 300 | 68.44 298 | 92.79 292 | 97.92 277 | 68.96 291 | 80.04 290 | 99.85 24 | 85.77 266 | 96.15 277 | 97.86 130 | 43.89 296 | 95.39 282 |
|
E-PMN | | | 80.61 268 | 79.88 269 | 82.81 280 | 90.75 287 | 76.38 294 | 97.69 282 | 95.76 290 | 66.44 293 | 83.52 284 | 92.25 286 | 62.54 289 | 87.16 291 | 68.53 292 | 61.40 291 | 84.89 294 |
|
EMVS | | | 80.02 269 | 79.22 270 | 82.43 282 | 91.19 286 | 76.40 293 | 97.55 285 | 92.49 299 | 66.36 294 | 83.01 286 | 91.27 287 | 64.63 287 | 85.79 292 | 65.82 293 | 60.65 292 | 85.08 293 |
|
PNet_i23d | | | 79.43 270 | 77.68 271 | 84.67 277 | 86.18 294 | 71.69 297 | 96.50 288 | 93.68 294 | 75.17 287 | 71.33 292 | 91.18 288 | 32.18 296 | 90.62 288 | 78.57 287 | 74.34 289 | 91.71 289 |
|
ANet_high | | | 77.30 271 | 74.86 273 | 84.62 278 | 75.88 298 | 77.61 291 | 97.63 283 | 93.15 296 | 88.81 279 | 64.27 294 | 89.29 290 | 36.51 294 | 83.93 293 | 75.89 289 | 52.31 294 | 92.33 288 |
|
MVE |  | 76.82 21 | 76.91 272 | 74.31 274 | 84.70 276 | 85.38 296 | 76.05 295 | 96.88 287 | 93.17 295 | 67.39 292 | 71.28 293 | 89.01 292 | 21.66 301 | 87.69 290 | 71.74 291 | 72.29 290 | 90.35 290 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
PMVS |  | 70.75 22 | 75.98 273 | 74.97 272 | 79.01 283 | 70.98 299 | 55.18 300 | 93.37 291 | 98.21 273 | 65.08 295 | 61.78 296 | 93.83 284 | 21.74 300 | 92.53 285 | 78.59 286 | 91.12 267 | 89.34 291 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
wuykxyi23d | | | 74.42 274 | 71.19 275 | 84.14 279 | 76.16 297 | 74.29 296 | 96.00 289 | 92.57 298 | 69.57 290 | 63.84 295 | 87.49 293 | 21.98 298 | 88.86 289 | 75.56 290 | 57.50 293 | 89.26 292 |
|
pcd1.5k->3k | | | 40.85 275 | 43.49 277 | 32.93 286 | 98.95 201 | 0.00 304 | 0.00 295 | 99.53 67 | 0.00 299 | 0.00 300 | 0.27 298 | 95.32 126 | 0.00 297 | 0.00 297 | 97.30 189 | 98.80 164 |
|
wuyk23d | | | 40.18 276 | 41.29 279 | 36.84 285 | 86.18 294 | 49.12 301 | 79.73 294 | 22.81 301 | 27.64 296 | 25.46 299 | 28.45 297 | 21.98 298 | 48.89 294 | 55.80 294 | 23.56 300 | 12.51 298 |
|
testmvs | | | 39.17 277 | 43.78 276 | 25.37 288 | 36.04 302 | 16.84 303 | 98.36 271 | 26.56 300 | 20.06 297 | 38.51 298 | 67.32 294 | 29.64 297 | 15.30 296 | 37.59 295 | 39.90 297 | 43.98 296 |
|
test123 | | | 39.01 278 | 42.50 278 | 28.53 287 | 39.17 301 | 20.91 302 | 98.75 256 | 19.17 302 | 19.83 298 | 38.57 297 | 66.67 295 | 33.16 295 | 15.42 295 | 37.50 296 | 29.66 299 | 49.26 295 |
|
cdsmvs_eth3d_5k | | | 24.64 279 | 32.85 280 | 0.00 289 | 0.00 303 | 0.00 304 | 0.00 295 | 99.51 79 | 0.00 299 | 0.00 300 | 99.56 142 | 96.58 99 | 0.00 297 | 0.00 297 | 0.00 301 | 0.00 299 |
|
ab-mvs-re | | | 8.30 280 | 11.06 281 | 0.00 289 | 0.00 303 | 0.00 304 | 0.00 295 | 0.00 303 | 0.00 299 | 0.00 300 | 99.58 137 | 0.00 302 | 0.00 297 | 0.00 297 | 0.00 301 | 0.00 299 |
|
pcd_1.5k_mvsjas | | | 8.27 281 | 11.03 282 | 0.00 289 | 0.00 303 | 0.00 304 | 0.00 295 | 0.00 303 | 0.00 299 | 0.00 300 | 0.27 298 | 99.01 10 | 0.00 297 | 0.00 297 | 0.00 301 | 0.00 299 |
|
sosnet-low-res | | | 0.02 282 | 0.03 283 | 0.00 289 | 0.00 303 | 0.00 304 | 0.00 295 | 0.00 303 | 0.00 299 | 0.00 300 | 0.27 298 | 0.00 302 | 0.00 297 | 0.00 297 | 0.00 301 | 0.00 299 |
|
sosnet | | | 0.02 282 | 0.03 283 | 0.00 289 | 0.00 303 | 0.00 304 | 0.00 295 | 0.00 303 | 0.00 299 | 0.00 300 | 0.27 298 | 0.00 302 | 0.00 297 | 0.00 297 | 0.00 301 | 0.00 299 |
|
uncertanet | | | 0.02 282 | 0.03 283 | 0.00 289 | 0.00 303 | 0.00 304 | 0.00 295 | 0.00 303 | 0.00 299 | 0.00 300 | 0.27 298 | 0.00 302 | 0.00 297 | 0.00 297 | 0.00 301 | 0.00 299 |
|
Regformer | | | 0.02 282 | 0.03 283 | 0.00 289 | 0.00 303 | 0.00 304 | 0.00 295 | 0.00 303 | 0.00 299 | 0.00 300 | 0.27 298 | 0.00 302 | 0.00 297 | 0.00 297 | 0.00 301 | 0.00 299 |
|
uanet | | | 0.02 282 | 0.03 283 | 0.00 289 | 0.00 303 | 0.00 304 | 0.00 295 | 0.00 303 | 0.00 299 | 0.00 300 | 0.27 298 | 0.00 302 | 0.00 297 | 0.00 297 | 0.00 301 | 0.00 299 |
|
test9_res | | | | | | | | | | | | | | | 97.49 161 | 99.72 72 | 99.75 45 |
|
TEST9 | | | | | | 99.67 64 | 99.65 30 | 99.05 218 | 99.41 145 | 96.22 209 | 98.95 157 | 99.49 160 | 98.77 35 | 99.91 56 | | | |
|
train_agg | | | | | | | | | | | | | | | 97.63 152 | 99.72 72 | 99.75 45 |
|
Patchmatch-test1 | | | | | | 95.52 278 | 90.87 275 | 90.46 293 | 98.41 267 | | 95.19 257 | 96.45 279 | 67.48 283 | | | 90.26 269 | |
|
Patchmatch-test | | | | | | 99.09 174 | 96.59 222 | | | | | 98.70 249 | | | | | |
|
test_8 | | | | | | 99.67 64 | 99.61 34 | 99.03 223 | 99.41 145 | 96.28 203 | 98.93 159 | 99.48 164 | 98.76 37 | 99.91 56 | | | |
|
agg_prior2 | | | | | | | | | | | | | | | 97.21 175 | 99.73 71 | 99.75 45 |
|
agg_prior | | | | | | 99.67 64 | 99.62 32 | | 99.40 151 | | 98.87 166 | | | 99.91 56 | | | |
|
TestCases | | | | | 99.31 94 | 99.86 12 | 98.48 165 | | 99.61 30 | 97.85 91 | 99.36 84 | 99.85 24 | 95.95 111 | 99.85 86 | 96.66 207 | 99.83 51 | 99.59 96 |
|
test_prior4 | | | | | | | 99.56 41 | 98.99 229 | | | | | | | | | |
|
test_prior2 | | | | | | | | 98.96 237 | | 98.34 50 | 99.01 147 | 99.52 152 | 98.68 44 | | 97.96 124 | 99.74 68 | |
|
test_prior | | | | | 99.68 42 | 99.67 64 | 99.48 54 | | 99.56 43 | | | | | 99.83 97 | | | 99.74 50 |
|
旧先验2 | | | | | | | | 98.96 237 | | 96.70 174 | 99.47 63 | | | 99.94 27 | 98.19 107 | | |
|
æ–°å‡ ä½•2 | | | | | | | | 99.01 227 | | | | | | | | | |
|
æ–°å‡ ä½•1 | | | | | 99.75 30 | 99.75 38 | 99.59 38 | | 99.54 57 | 96.76 170 | 99.29 98 | 99.64 119 | 98.43 55 | 99.94 27 | 96.92 195 | 99.66 84 | 99.72 62 |
|
旧先验1 | | | | | | 99.74 44 | 99.59 38 | | 99.54 57 | | | 99.69 97 | 98.47 52 | | | 99.68 82 | 99.73 56 |
|
æ— å…ˆéªŒ | | | | | | | | 98.99 229 | 99.51 79 | 96.89 165 | | | | 99.93 40 | 97.53 158 | | 99.72 62 |
|
原ACMM2 | | | | | | | | 98.95 241 | | | | | | | | | |
|
原ACMM1 | | | | | 99.65 48 | 99.73 49 | 99.33 66 | | 99.47 112 | 97.46 121 | 99.12 131 | 99.66 112 | 98.67 46 | 99.91 56 | 97.70 148 | 99.69 79 | 99.71 69 |
|
test222 | | | | | | 99.75 38 | 99.49 53 | 98.91 246 | 99.49 92 | 96.42 196 | 99.34 90 | 99.65 113 | 98.28 63 | | | 99.69 79 | 99.72 62 |
|
testdata2 | | | | | | | | | | | | | | 99.95 24 | 96.67 206 | | |
|
segment_acmp | | | | | | | | | | | | | 98.96 19 | | | | |
|
testdata | | | | | 99.54 64 | 99.75 38 | 98.95 104 | | 99.51 79 | 97.07 155 | 99.43 70 | 99.70 92 | 98.87 26 | 99.94 27 | 97.76 139 | 99.64 87 | 99.72 62 |
|
testdata1 | | | | | | | | 98.85 250 | | 98.32 53 | | | | | | | |
|
test12 | | | | | 99.75 30 | 99.64 75 | 99.61 34 | | 99.29 196 | | 99.21 118 | | 98.38 57 | 99.89 75 | | 99.74 68 | 99.74 50 |
|
plane_prior7 | | | | | | 99.29 136 | 97.03 205 | | | | | | | | | | |
|
plane_prior6 | | | | | | 99.27 141 | 96.98 208 | | | | | | 92.71 209 | | | | |
|
plane_prior5 | | | | | | | | | 99.47 112 | | | | | 99.69 140 | 97.78 136 | 97.63 166 | 98.67 203 |
|
plane_prior4 | | | | | | | | | | | | 99.61 131 | | | | | |
|
plane_prior3 | | | | | | | 97.00 207 | | | 98.69 33 | 99.11 133 | | | | | | |
|
plane_prior2 | | | | | | | | 99.39 149 | | 98.97 21 | | | | | | | |
|
plane_prior1 | | | | | | 99.26 143 | | | | | | | | | | | |
|
plane_prior | | | | | | | 96.97 209 | 99.21 192 | | 98.45 43 | | | | | | 97.60 169 | |
|
abl_6 | | | | | | | | | | | | | | | | | 99.79 35 |
|
n2 | | | | | | | | | 0.00 303 | | | | | | | | |
|
nn | | | | | | | | | 0.00 303 | | | | | | | | |
|
door-mid | | | | | | | | | 98.05 276 | | | | | | | | |
|
lessismore_v0 | | | | | 97.79 234 | 98.69 245 | 95.44 244 | | 94.75 291 | | 95.71 255 | 99.87 18 | 88.69 251 | 99.32 189 | 95.89 221 | 94.93 230 | 98.62 223 |
|
LGP-MVS_train | | | | | 98.49 181 | 99.33 128 | 97.05 203 | | 99.55 50 | 97.46 121 | 99.24 111 | 99.83 34 | 92.58 213 | 99.72 128 | 98.09 114 | 97.51 174 | 98.68 192 |
|
test11 | | | | | | | | | 99.35 169 | | | | | | | | |
|
door | | | | | | | | | 97.92 277 | | | | | | | | |
|
HQP5-MVS | | | | | | | 96.83 213 | | | | | | | | | | |
|
HQP-NCC | | | | | | 99.19 152 | | 98.98 232 | | 98.24 56 | 98.66 189 | | | | | | |
|
ACMP_Plane | | | | | | 99.19 152 | | 98.98 232 | | 98.24 56 | 98.66 189 | | | | | | |
|
BP-MVS | | | | | | | | | | | | | | | 97.19 177 | | |
|
HQP4-MVS | | | | | | | | | | | 98.66 189 | | | 99.64 147 | | | 98.64 216 |
|
HQP3-MVS | | | | | | | | | 99.39 154 | | | | | | | 97.58 170 | |
|
HQP2-MVS | | | | | | | | | | | | | 92.47 217 | | | | |
|
NP-MVS | | | | | | 99.23 146 | 96.92 212 | | | | | 99.40 181 | | | | | |
|
MDTV_nov1_ep13_2view | | | | | | | 95.18 249 | 99.35 161 | |