LCM-MVSNet | | | 95.70 1 | 96.40 1 | 93.61 2 | 98.67 1 | 85.39 29 | 95.54 3 | 97.36 1 | 96.97 1 | 99.04 1 | 99.05 1 | 96.61 1 | 95.92 11 | 85.07 37 | 99.27 3 | 99.54 1 |
|
TDRefinement | | | 93.52 2 | 93.39 3 | 93.88 1 | 95.94 13 | 90.26 4 | 95.70 2 | 96.46 2 | 90.58 7 | 92.86 42 | 96.29 18 | 88.16 25 | 94.17 69 | 86.07 33 | 98.48 19 | 97.22 25 |
|
ACMH+ | | 77.89 11 | 90.73 25 | 91.50 18 | 88.44 64 | 93.00 65 | 76.26 100 | 89.65 50 | 95.55 3 | 87.72 17 | 93.89 26 | 94.94 52 | 91.62 4 | 93.44 110 | 78.35 120 | 98.76 5 | 95.61 65 |
|
LTVRE_ROB | | 86.10 1 | 93.04 3 | 93.44 2 | 91.82 19 | 93.73 49 | 85.72 28 | 96.79 1 | 95.51 4 | 88.86 12 | 95.63 10 | 96.99 8 | 84.81 54 | 93.16 124 | 91.10 1 | 97.53 60 | 96.58 40 |
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 |
AllTest | | | 87.97 68 | 87.40 79 | 89.68 47 | 91.59 101 | 83.40 45 | 89.50 57 | 95.44 5 | 79.47 80 | 88.00 134 | 93.03 107 | 82.66 73 | 91.47 167 | 70.81 177 | 96.14 101 | 94.16 97 |
|
TestCases | | | | | 89.68 47 | 91.59 101 | 83.40 45 | | 95.44 5 | 79.47 80 | 88.00 134 | 93.03 107 | 82.66 73 | 91.47 167 | 70.81 177 | 96.14 101 | 94.16 97 |
|
COLMAP_ROB | | 83.01 3 | 91.97 8 | 91.95 8 | 92.04 10 | 93.68 50 | 86.15 18 | 93.37 8 | 95.10 7 | 90.28 8 | 92.11 57 | 95.03 49 | 89.75 14 | 94.93 49 | 79.95 105 | 98.27 28 | 95.04 78 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
APD-MVS_3200maxsize | | | 92.05 7 | 92.24 6 | 91.48 20 | 93.02 64 | 85.17 31 | 92.47 21 | 95.05 8 | 87.65 18 | 93.21 36 | 94.39 74 | 90.09 13 | 95.08 45 | 86.67 25 | 97.60 58 | 94.18 96 |
|
HPM-MVS | | | 92.13 6 | 92.20 7 | 91.91 15 | 95.58 23 | 84.67 38 | 93.51 6 | 94.85 9 | 82.88 45 | 91.77 65 | 93.94 93 | 90.55 12 | 95.73 20 | 88.50 8 | 98.23 30 | 95.33 70 |
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023 |
LS3D | | | 90.60 28 | 90.34 41 | 91.38 23 | 89.03 152 | 84.23 42 | 93.58 4 | 94.68 10 | 90.65 6 | 90.33 83 | 93.95 92 | 84.50 57 | 95.37 34 | 80.87 89 | 95.50 123 | 94.53 87 |
|
MP-MVS-pluss | | | 90.81 24 | 91.08 28 | 89.99 46 | 95.97 12 | 79.88 63 | 88.13 78 | 94.51 11 | 75.79 135 | 92.94 39 | 94.96 51 | 88.36 19 | 95.01 47 | 90.70 2 | 98.40 21 | 95.09 77 |
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
canonicalmvs | | | 85.50 110 | 86.14 101 | 83.58 161 | 87.97 178 | 67.13 165 | 87.55 87 | 94.32 12 | 73.44 162 | 88.47 128 | 87.54 231 | 86.45 44 | 91.06 178 | 75.76 143 | 93.76 171 | 92.54 147 |
|
LCM-MVSNet-Re | | | 83.48 159 | 85.06 116 | 78.75 229 | 85.94 241 | 55.75 275 | 80.05 236 | 94.27 13 | 76.47 125 | 96.09 5 | 94.54 66 | 83.31 67 | 89.75 212 | 59.95 257 | 94.89 142 | 90.75 194 |
|
LPG-MVS_test | | | 91.47 16 | 91.68 14 | 90.82 34 | 94.75 36 | 81.69 51 | 90.00 40 | 94.27 13 | 82.35 50 | 93.67 29 | 94.82 57 | 91.18 5 | 95.52 28 | 85.36 35 | 98.73 8 | 95.23 74 |
|
LGP-MVS_train | | | | | 90.82 34 | 94.75 36 | 81.69 51 | | 94.27 13 | 82.35 50 | 93.67 29 | 94.82 57 | 91.18 5 | 95.52 28 | 85.36 35 | 98.73 8 | 95.23 74 |
|
HPM-MVS_fast | | | 92.50 5 | 92.54 5 | 92.37 5 | 95.93 14 | 85.81 27 | 92.99 11 | 94.23 16 | 85.21 25 | 92.51 52 | 95.13 47 | 90.65 10 | 95.34 35 | 88.06 10 | 98.15 33 | 95.95 52 |
|
nrg030 | | | 87.85 70 | 88.49 64 | 85.91 105 | 90.07 138 | 69.73 146 | 87.86 81 | 94.20 17 | 74.04 154 | 92.70 49 | 94.66 61 | 85.88 50 | 91.50 166 | 79.72 107 | 97.32 63 | 96.50 41 |
|
DeepC-MVS | | 82.31 4 | 89.15 55 | 89.08 54 | 89.37 54 | 93.64 51 | 79.07 71 | 88.54 74 | 94.20 17 | 73.53 159 | 89.71 100 | 94.82 57 | 85.09 52 | 95.77 18 | 84.17 51 | 98.03 37 | 93.26 123 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
abl_6 | | | 93.02 4 | 93.16 4 | 92.60 4 | 94.73 38 | 88.99 7 | 93.26 10 | 94.19 19 | 89.11 10 | 94.43 18 | 95.27 42 | 91.86 3 | 95.09 44 | 87.54 19 | 98.02 38 | 93.71 112 |
|
ACMMP | | | 91.91 9 | 91.87 13 | 92.03 11 | 95.53 24 | 85.91 22 | 93.35 9 | 94.16 20 | 82.52 49 | 92.39 56 | 94.14 82 | 89.15 16 | 95.62 22 | 87.35 20 | 98.24 29 | 94.56 83 |
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 |
APDe-MVS | | | 91.22 20 | 91.92 9 | 89.14 57 | 92.97 66 | 78.04 78 | 92.84 12 | 94.14 21 | 83.33 38 | 93.90 25 | 95.73 30 | 88.77 17 | 96.41 1 | 87.60 17 | 97.98 42 | 92.98 131 |
|
3Dnovator+ | | 83.92 2 | 89.97 40 | 89.66 48 | 90.92 32 | 91.27 113 | 81.66 54 | 91.25 32 | 94.13 22 | 88.89 11 | 88.83 121 | 94.26 77 | 77.55 126 | 95.86 15 | 84.88 40 | 95.87 113 | 95.24 73 |
|
ACMP | | 79.16 10 | 90.54 29 | 90.60 36 | 90.35 41 | 94.36 40 | 80.98 57 | 89.16 63 | 94.05 23 | 79.03 89 | 92.87 41 | 93.74 96 | 90.60 11 | 95.21 42 | 82.87 66 | 98.76 5 | 94.87 79 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
XVG-ACMP-BASELINE | | | 89.98 38 | 89.84 45 | 90.41 39 | 94.91 34 | 84.50 41 | 89.49 58 | 93.98 24 | 79.68 78 | 92.09 58 | 93.89 94 | 83.80 61 | 93.10 127 | 82.67 70 | 98.04 35 | 93.64 114 |
|
test_part1 | | | | | | | | | 93.93 25 | | | | 87.19 35 | | | 97.61 56 | 91.48 177 |
|
ESAPD | | | 90.05 35 | 90.56 39 | 88.50 63 | 93.86 47 | 77.77 80 | 89.63 51 | 93.93 25 | 84.39 29 | 92.84 43 | 93.43 100 | 87.19 35 | 96.26 4 | 82.18 75 | 97.61 56 | 91.48 177 |
|
XVG-OURS-SEG-HR | | | 89.59 48 | 89.37 52 | 90.28 42 | 94.47 39 | 85.95 21 | 86.84 99 | 93.91 27 | 80.07 75 | 86.75 152 | 93.26 102 | 93.64 2 | 90.93 181 | 84.60 45 | 90.75 238 | 93.97 102 |
|
PGM-MVS | | | 91.20 21 | 90.95 32 | 91.93 13 | 95.67 20 | 85.85 25 | 90.00 40 | 93.90 28 | 80.32 72 | 91.74 66 | 94.41 71 | 88.17 24 | 95.98 8 | 86.37 26 | 97.99 40 | 93.96 103 |
|
ACMH | | 76.49 14 | 89.34 52 | 91.14 27 | 83.96 149 | 92.50 77 | 70.36 144 | 89.55 54 | 93.84 29 | 81.89 58 | 94.70 15 | 95.44 40 | 90.69 9 | 88.31 238 | 83.33 59 | 98.30 27 | 93.20 125 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
SD-MVS | | | 88.96 56 | 89.88 44 | 86.22 97 | 91.63 100 | 77.07 90 | 89.82 46 | 93.77 30 | 78.90 90 | 92.88 40 | 92.29 128 | 86.11 48 | 90.22 202 | 86.24 31 | 97.24 65 | 91.36 180 |
|
ACMMP_Plus | | | 90.65 26 | 91.07 29 | 89.42 53 | 95.93 14 | 79.54 68 | 89.95 43 | 93.68 31 | 77.65 106 | 91.97 62 | 94.89 54 | 88.38 18 | 95.45 31 | 89.27 3 | 97.87 45 | 93.27 122 |
|
HQP_MVS | | | 87.75 72 | 87.43 78 | 88.70 61 | 93.45 53 | 76.42 98 | 89.45 59 | 93.61 32 | 79.44 82 | 86.55 155 | 92.95 111 | 74.84 158 | 95.22 40 | 80.78 91 | 95.83 115 | 94.46 88 |
|
plane_prior5 | | | | | | | | | 93.61 32 | | | | | 95.22 40 | 80.78 91 | 95.83 115 | 94.46 88 |
|
XVG-OURS | | | 89.18 54 | 88.83 59 | 90.23 43 | 94.28 41 | 86.11 20 | 85.91 115 | 93.60 34 | 80.16 74 | 89.13 117 | 93.44 99 | 83.82 60 | 90.98 179 | 83.86 55 | 95.30 130 | 93.60 116 |
|
TAPA-MVS | | 77.73 12 | 85.71 109 | 84.83 122 | 88.37 65 | 88.78 157 | 79.72 65 | 87.15 95 | 93.50 35 | 69.17 218 | 85.80 168 | 89.56 199 | 80.76 100 | 92.13 151 | 73.21 166 | 95.51 122 | 93.25 124 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
SteuartSystems-ACMMP | | | 91.16 22 | 91.36 21 | 90.55 37 | 93.91 46 | 80.97 58 | 91.49 29 | 93.48 36 | 82.82 46 | 92.60 51 | 93.97 87 | 88.19 23 | 96.29 3 | 87.61 15 | 98.20 32 | 94.39 92 |
Skip Steuart: Steuart Systems R&D Blog. |
CP-MVS | | | 91.67 11 | 91.58 16 | 91.96 12 | 95.29 27 | 87.62 9 | 93.38 7 | 93.36 37 | 83.16 40 | 91.06 74 | 94.00 86 | 88.26 22 | 95.71 21 | 87.28 23 | 98.39 22 | 92.55 146 |
|
ACMM | | 79.39 9 | 90.65 26 | 90.99 30 | 89.63 49 | 95.03 31 | 83.53 44 | 89.62 53 | 93.35 38 | 79.20 85 | 93.83 27 | 93.60 98 | 90.81 8 | 92.96 132 | 85.02 39 | 98.45 20 | 92.41 149 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
XVS | | | 91.54 12 | 91.36 21 | 92.08 8 | 95.64 21 | 86.25 16 | 92.64 15 | 93.33 39 | 85.07 26 | 89.99 88 | 94.03 85 | 86.57 42 | 95.80 16 | 87.35 20 | 97.62 54 | 94.20 94 |
|
X-MVStestdata | | | 85.04 116 | 82.70 163 | 92.08 8 | 95.64 21 | 86.25 16 | 92.64 15 | 93.33 39 | 85.07 26 | 89.99 88 | 16.05 360 | 86.57 42 | 95.80 16 | 87.35 20 | 97.62 54 | 94.20 94 |
|
WR-MVS_H | | | 89.91 43 | 91.31 24 | 85.71 110 | 96.32 9 | 62.39 216 | 89.54 56 | 93.31 41 | 90.21 9 | 95.57 11 | 95.66 32 | 81.42 95 | 95.90 12 | 80.94 88 | 98.80 4 | 98.84 5 |
|
MVS_0304 | | | 84.88 120 | 83.96 150 | 87.64 78 | 87.43 199 | 74.83 106 | 84.18 140 | 93.30 42 | 77.48 109 | 77.39 275 | 88.46 213 | 74.53 166 | 95.74 19 | 78.09 125 | 94.75 152 | 92.36 151 |
|
region2R | | | 91.44 17 | 91.30 25 | 91.87 16 | 95.75 17 | 85.90 23 | 92.63 17 | 93.30 42 | 81.91 57 | 90.88 79 | 94.21 79 | 87.75 29 | 95.87 13 | 87.60 17 | 97.71 52 | 93.83 105 |
|
HFP-MVS | | | 91.30 18 | 91.39 20 | 91.02 29 | 95.43 25 | 84.66 39 | 92.58 18 | 93.29 44 | 81.99 55 | 91.47 69 | 93.96 89 | 88.35 20 | 95.56 25 | 87.74 11 | 97.74 50 | 92.85 132 |
|
#test# | | | 90.49 30 | 90.31 42 | 91.02 29 | 95.43 25 | 84.66 39 | 90.65 36 | 93.29 44 | 77.00 121 | 91.47 69 | 93.96 89 | 88.35 20 | 95.56 25 | 84.88 40 | 97.74 50 | 92.85 132 |
|
ACMMPR | | | 91.49 14 | 91.35 23 | 91.92 14 | 95.74 18 | 85.88 24 | 92.58 18 | 93.25 46 | 81.99 55 | 91.40 71 | 94.17 81 | 87.51 33 | 95.87 13 | 87.74 11 | 97.76 47 | 93.99 101 |
|
SMA-MVS | | | 90.18 31 | 90.38 40 | 89.55 52 | 95.15 28 | 79.52 69 | 90.98 34 | 93.24 47 | 75.37 144 | 92.84 43 | 94.93 53 | 85.58 51 | 96.00 6 | 87.61 15 | 97.76 47 | 93.12 127 |
|
PEN-MVS | | | 90.03 36 | 91.88 12 | 84.48 133 | 96.57 5 | 58.88 253 | 88.95 65 | 93.19 48 | 91.62 3 | 96.01 6 | 96.16 22 | 87.02 37 | 95.60 23 | 78.69 118 | 98.72 10 | 98.97 3 |
|
OMC-MVS | | | 88.19 65 | 87.52 75 | 90.19 44 | 91.94 95 | 81.68 53 | 87.49 89 | 93.17 49 | 76.02 130 | 88.64 124 | 91.22 153 | 84.24 59 | 93.37 114 | 77.97 126 | 97.03 70 | 95.52 66 |
|
OurMVSNet-221017-0 | | | 90.01 37 | 89.74 47 | 90.83 33 | 93.16 61 | 80.37 59 | 91.91 27 | 93.11 50 | 81.10 65 | 95.32 12 | 97.24 5 | 72.94 194 | 94.85 51 | 85.07 37 | 97.78 46 | 97.26 22 |
|
FC-MVSNet-test | | | 85.93 105 | 87.05 84 | 82.58 181 | 92.25 85 | 56.44 270 | 85.75 118 | 93.09 51 | 77.33 115 | 91.94 63 | 94.65 62 | 74.78 160 | 93.41 113 | 75.11 147 | 98.58 15 | 97.88 9 |
|
APD-MVS | | | 89.54 49 | 89.63 49 | 89.26 56 | 92.57 74 | 81.34 56 | 90.19 39 | 93.08 52 | 80.87 67 | 91.13 73 | 93.19 103 | 86.22 47 | 95.97 9 | 82.23 74 | 97.18 67 | 90.45 203 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
FIs | | | 85.35 112 | 86.27 98 | 82.60 180 | 91.86 96 | 57.31 262 | 85.10 126 | 93.05 53 | 75.83 134 | 91.02 75 | 93.97 87 | 73.57 181 | 92.91 136 | 73.97 154 | 98.02 38 | 97.58 14 |
|
v7n | | | 90.13 32 | 90.96 31 | 87.65 77 | 91.95 93 | 71.06 140 | 89.99 42 | 93.05 53 | 86.53 21 | 94.29 21 | 96.27 19 | 82.69 72 | 94.08 72 | 86.25 30 | 97.63 53 | 97.82 10 |
|
PHI-MVS | | | 86.38 92 | 85.81 105 | 88.08 69 | 88.44 167 | 77.34 87 | 89.35 61 | 93.05 53 | 73.15 171 | 84.76 181 | 87.70 228 | 78.87 114 | 94.18 67 | 80.67 94 | 96.29 93 | 92.73 136 |
|
MP-MVS | | | 91.14 23 | 90.91 33 | 91.83 18 | 96.18 10 | 86.88 11 | 92.20 22 | 93.03 56 | 82.59 48 | 88.52 127 | 94.37 75 | 86.74 39 | 95.41 33 | 86.32 27 | 98.21 31 | 93.19 126 |
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo. |
Anonymous20231211 | | | 88.40 63 | 89.62 50 | 84.73 126 | 90.46 131 | 65.27 176 | 88.86 68 | 93.02 57 | 87.15 19 | 93.05 38 | 97.10 6 | 82.28 79 | 92.02 154 | 76.70 138 | 97.99 40 | 96.88 35 |
|
MSLP-MVS++ | | | 85.00 118 | 86.03 103 | 81.90 190 | 91.84 97 | 71.56 138 | 86.75 104 | 93.02 57 | 75.95 132 | 87.12 145 | 89.39 201 | 77.98 120 | 89.40 217 | 77.46 129 | 94.78 148 | 84.75 271 |
|
DP-MVS | | | 88.60 61 | 89.01 55 | 87.36 82 | 91.30 111 | 77.50 85 | 87.55 87 | 92.97 59 | 87.95 16 | 89.62 106 | 92.87 113 | 84.56 56 | 93.89 80 | 77.65 127 | 96.62 81 | 90.70 195 |
|
ANet_high | | | 83.17 164 | 85.68 108 | 75.65 272 | 81.24 289 | 45.26 340 | 79.94 239 | 92.91 60 | 83.83 36 | 91.33 72 | 96.88 10 | 80.25 105 | 85.92 271 | 68.89 197 | 95.89 112 | 95.76 54 |
|
UniMVSNet (Re) | | | 86.87 81 | 86.98 86 | 86.55 89 | 93.11 63 | 68.48 157 | 83.80 153 | 92.87 61 | 80.37 70 | 89.61 108 | 91.81 141 | 77.72 123 | 94.18 67 | 75.00 148 | 98.53 17 | 96.99 33 |
|
test_prior3 | | | 86.31 94 | 86.31 97 | 86.32 93 | 90.59 128 | 71.99 130 | 83.37 168 | 92.85 62 | 75.43 141 | 84.58 187 | 91.57 145 | 81.92 89 | 94.17 69 | 79.54 110 | 96.97 71 | 92.80 134 |
|
test_prior | | | | | 86.32 93 | 90.59 128 | 71.99 130 | | 92.85 62 | | | | | 94.17 69 | | | 92.80 134 |
|
DTE-MVSNet | | | 89.98 38 | 91.91 11 | 84.21 143 | 96.51 7 | 57.84 258 | 88.93 67 | 92.84 64 | 91.92 2 | 96.16 3 | 96.23 20 | 86.95 38 | 95.99 7 | 79.05 115 | 98.57 16 | 98.80 6 |
|
UA-Net | | | 91.49 14 | 91.53 17 | 91.39 22 | 94.98 32 | 82.95 50 | 93.52 5 | 92.79 65 | 88.22 15 | 88.53 126 | 97.64 2 | 83.45 65 | 94.55 60 | 86.02 34 | 98.60 14 | 96.67 37 |
|
OPM-MVS | | | 89.80 44 | 89.97 43 | 89.27 55 | 94.76 35 | 79.86 64 | 86.76 103 | 92.78 66 | 78.78 92 | 92.51 52 | 93.64 97 | 88.13 26 | 93.84 83 | 84.83 42 | 97.55 59 | 94.10 99 |
|
PS-CasMVS | | | 90.06 34 | 91.92 9 | 84.47 134 | 96.56 6 | 58.83 255 | 89.04 64 | 92.74 67 | 91.40 4 | 96.12 4 | 96.06 25 | 87.23 34 | 95.57 24 | 79.42 113 | 98.74 7 | 99.00 2 |
|
HQP3-MVS | | | | | | | | | 92.68 68 | | | | | | | 94.47 157 | |
|
HQP-MVS | | | 84.61 125 | 84.06 147 | 86.27 95 | 91.19 114 | 70.66 142 | 84.77 128 | 92.68 68 | 73.30 166 | 80.55 250 | 90.17 191 | 72.10 205 | 94.61 56 | 77.30 132 | 94.47 157 | 93.56 118 |
|
v52 | | | 89.97 40 | 90.60 36 | 88.07 70 | 88.69 158 | 72.01 128 | 91.35 30 | 92.64 70 | 82.22 52 | 95.97 8 | 96.31 16 | 84.82 53 | 93.98 76 | 88.59 4 | 94.83 146 | 98.23 7 |
|
V4 | | | 89.97 40 | 90.60 36 | 88.07 70 | 88.69 158 | 72.01 128 | 91.35 30 | 92.64 70 | 82.22 52 | 95.98 7 | 96.31 16 | 84.80 55 | 93.98 76 | 88.59 4 | 94.83 146 | 98.23 7 |
|
mPP-MVS | | | 91.69 10 | 91.47 19 | 92.37 5 | 96.04 11 | 88.48 8 | 92.72 14 | 92.60 72 | 83.09 41 | 91.54 68 | 94.25 78 | 87.67 32 | 95.51 30 | 87.21 24 | 98.11 34 | 93.12 127 |
|
CLD-MVS | | | 83.18 163 | 82.64 165 | 84.79 123 | 89.05 151 | 67.82 163 | 77.93 271 | 92.52 73 | 68.33 224 | 85.07 175 | 81.54 313 | 82.06 83 | 92.96 132 | 69.35 190 | 97.91 43 | 93.57 117 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
DELS-MVS | | | 81.44 184 | 81.25 185 | 82.03 188 | 84.27 262 | 62.87 206 | 76.47 286 | 92.49 74 | 70.97 204 | 81.64 229 | 83.83 279 | 75.03 154 | 92.70 140 | 74.29 149 | 92.22 208 | 90.51 202 |
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 |
Effi-MVS+ | | | 83.90 152 | 84.01 148 | 83.57 162 | 87.22 208 | 65.61 175 | 86.55 111 | 92.40 75 | 78.64 95 | 81.34 233 | 84.18 276 | 83.65 63 | 92.93 134 | 74.22 150 | 87.87 271 | 92.17 159 |
|
DP-MVS Recon | | | 84.05 147 | 83.22 157 | 86.52 90 | 91.73 99 | 75.27 104 | 83.23 175 | 92.40 75 | 72.04 187 | 82.04 221 | 88.33 218 | 77.91 122 | 93.95 79 | 66.17 216 | 95.12 135 | 90.34 206 |
|
DeepPCF-MVS | | 81.24 5 | 87.28 76 | 86.21 100 | 90.49 38 | 91.48 108 | 84.90 34 | 83.41 167 | 92.38 77 | 70.25 210 | 89.35 114 | 90.68 178 | 82.85 71 | 94.57 58 | 79.55 109 | 95.95 109 | 92.00 161 |
|
CPTT-MVS | | | 89.39 51 | 88.98 57 | 90.63 36 | 95.09 30 | 86.95 10 | 92.09 23 | 92.30 78 | 79.74 77 | 87.50 141 | 92.38 124 | 81.42 95 | 93.28 119 | 83.07 63 | 97.24 65 | 91.67 171 |
|
casdiffmvs | | | 82.99 166 | 82.51 169 | 84.42 137 | 86.34 226 | 67.92 161 | 87.86 81 | 92.28 79 | 60.95 280 | 81.12 234 | 93.08 105 | 76.07 145 | 93.43 112 | 79.41 114 | 85.45 292 | 91.93 165 |
|
DU-MVS | | | 86.80 84 | 86.99 85 | 86.21 99 | 93.24 59 | 67.02 166 | 83.16 176 | 92.21 80 | 81.73 59 | 90.92 76 | 91.97 134 | 77.20 129 | 93.99 74 | 74.16 151 | 98.35 23 | 97.61 12 |
|
v10 | | | 86.54 89 | 87.10 82 | 84.84 121 | 88.16 174 | 63.28 197 | 86.64 109 | 92.20 81 | 75.42 143 | 92.81 46 | 94.50 67 | 74.05 170 | 94.06 73 | 83.88 54 | 96.28 94 | 97.17 27 |
|
MCST-MVS | | | 84.36 134 | 83.93 151 | 85.63 111 | 91.59 101 | 71.58 137 | 83.52 162 | 92.13 82 | 61.82 273 | 83.96 198 | 89.75 196 | 79.93 109 | 93.46 109 | 78.33 121 | 94.34 159 | 91.87 166 |
|
Vis-MVSNet | | | 86.86 82 | 86.58 93 | 87.72 75 | 92.09 89 | 77.43 86 | 87.35 90 | 92.09 83 | 78.87 91 | 84.27 197 | 94.05 84 | 78.35 118 | 93.65 87 | 80.54 96 | 91.58 214 | 92.08 160 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
CP-MVSNet | | | 89.27 53 | 90.91 33 | 84.37 138 | 96.34 8 | 58.61 257 | 88.66 73 | 92.06 84 | 90.78 5 | 95.67 9 | 95.17 46 | 81.80 91 | 95.54 27 | 79.00 116 | 98.69 11 | 98.95 4 |
|
CDPH-MVS | | | 86.17 100 | 85.54 110 | 88.05 73 | 92.25 85 | 75.45 103 | 83.85 150 | 92.01 85 | 65.91 243 | 86.19 162 | 91.75 143 | 83.77 62 | 94.98 48 | 77.43 131 | 96.71 79 | 93.73 111 |
|
DeepC-MVS_fast | | 80.27 8 | 86.23 97 | 85.65 109 | 87.96 74 | 91.30 111 | 76.92 91 | 87.19 93 | 91.99 86 | 70.56 206 | 84.96 176 | 90.69 177 | 80.01 107 | 95.14 43 | 78.37 119 | 95.78 117 | 91.82 167 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
PS-MVSNAJss | | | 88.31 64 | 87.90 69 | 89.56 51 | 93.31 57 | 77.96 79 | 87.94 80 | 91.97 87 | 70.73 205 | 94.19 23 | 96.67 11 | 76.94 135 | 94.57 58 | 83.07 63 | 96.28 94 | 96.15 43 |
|
MVS_Test | | | 82.47 172 | 83.22 157 | 80.22 212 | 82.62 281 | 57.75 260 | 82.54 192 | 91.96 88 | 71.16 202 | 82.89 213 | 92.52 123 | 77.41 127 | 90.50 195 | 80.04 104 | 87.84 272 | 92.40 150 |
|
F-COLMAP | | | 84.97 119 | 83.42 154 | 89.63 49 | 92.39 80 | 83.40 45 | 88.83 69 | 91.92 89 | 73.19 170 | 80.18 255 | 89.15 204 | 77.04 133 | 93.28 119 | 65.82 221 | 92.28 204 | 92.21 158 |
|
CSCG | | | 86.26 95 | 86.47 95 | 85.60 112 | 90.87 123 | 74.26 110 | 87.98 79 | 91.85 90 | 80.35 71 | 89.54 112 | 88.01 222 | 79.09 112 | 92.13 151 | 75.51 144 | 95.06 137 | 90.41 204 |
|
PCF-MVS | | 74.62 15 | 82.15 176 | 80.92 191 | 85.84 108 | 89.43 145 | 72.30 124 | 80.53 232 | 91.82 91 | 57.36 295 | 87.81 137 | 89.92 194 | 77.67 124 | 93.63 89 | 58.69 269 | 95.08 136 | 91.58 174 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
zzz-MVS | | | 91.27 19 | 91.26 26 | 91.29 25 | 96.59 3 | 86.29 14 | 88.94 66 | 91.81 92 | 84.07 33 | 92.00 60 | 94.40 72 | 86.63 40 | 95.28 38 | 88.59 4 | 98.31 25 | 92.30 153 |
|
MTGPA | | | | | | | | | 91.81 92 | | | | | | | | |
|
MTAPA | | | 91.52 13 | 91.60 15 | 91.29 25 | 96.59 3 | 86.29 14 | 92.02 24 | 91.81 92 | 84.07 33 | 92.00 60 | 94.40 72 | 86.63 40 | 95.28 38 | 88.59 4 | 98.31 25 | 92.30 153 |
|
PVSNet_Blended_VisFu | | | 81.55 183 | 80.49 195 | 84.70 128 | 91.58 104 | 73.24 116 | 84.21 139 | 91.67 95 | 62.86 265 | 80.94 236 | 87.16 234 | 67.27 227 | 92.87 138 | 69.82 187 | 88.94 258 | 87.99 234 |
|
Anonymous20240521 | | | 87.68 73 | 88.61 63 | 84.87 120 | 91.76 98 | 64.76 180 | 89.28 62 | 91.66 96 | 83.02 43 | 93.29 34 | 96.10 24 | 77.37 128 | 92.89 137 | 77.27 134 | 97.75 49 | 96.97 34 |
|
v11 | | | 86.96 79 | 87.78 72 | 84.51 131 | 88.50 164 | 62.60 212 | 87.21 92 | 91.63 97 | 78.08 103 | 93.40 33 | 95.56 37 | 75.07 153 | 93.57 98 | 84.46 47 | 96.08 104 | 97.36 20 |
|
UniMVSNet_NR-MVSNet | | | 86.84 83 | 87.06 83 | 86.17 102 | 92.86 70 | 67.02 166 | 82.55 191 | 91.56 98 | 83.08 42 | 90.92 76 | 91.82 140 | 78.25 119 | 93.99 74 | 74.16 151 | 98.35 23 | 97.49 15 |
|
v1240 | | | 84.30 137 | 84.51 136 | 83.65 159 | 87.65 194 | 61.26 234 | 82.85 182 | 91.54 99 | 67.94 229 | 90.68 81 | 90.65 180 | 71.71 211 | 93.64 88 | 82.84 68 | 94.78 148 | 96.07 46 |
|
原ACMM1 | | | | | 84.60 130 | 92.81 72 | 74.01 111 | | 91.50 100 | 62.59 267 | 82.73 215 | 90.67 179 | 76.53 142 | 94.25 64 | 69.24 191 | 95.69 120 | 85.55 258 |
|
v18 | | | 85.99 103 | 86.55 94 | 84.30 141 | 87.73 191 | 62.29 221 | 86.40 113 | 91.49 101 | 76.64 124 | 92.40 55 | 94.20 80 | 73.28 188 | 93.52 104 | 82.87 66 | 93.99 164 | 97.09 29 |
|
v748 | | | 88.91 58 | 89.82 46 | 86.19 101 | 90.06 139 | 68.53 156 | 88.81 70 | 91.48 102 | 84.36 31 | 94.19 23 | 95.98 26 | 82.52 75 | 92.67 142 | 84.30 48 | 96.67 80 | 97.37 19 |
|
v17 | | | 86.32 93 | 86.95 87 | 84.44 135 | 88.00 177 | 62.62 211 | 86.74 105 | 91.48 102 | 77.17 118 | 92.74 47 | 94.56 63 | 73.74 176 | 93.53 103 | 83.27 60 | 94.87 145 | 97.18 26 |
|
v16 | | | 86.24 96 | 86.85 90 | 84.43 136 | 87.96 179 | 62.59 213 | 86.73 106 | 91.48 102 | 77.17 118 | 92.67 50 | 94.55 64 | 73.63 177 | 93.52 104 | 83.26 61 | 94.16 160 | 97.17 27 |
|
v13 | | | 87.31 75 | 88.10 66 | 84.94 118 | 88.84 155 | 63.75 189 | 87.85 83 | 91.47 105 | 79.12 86 | 93.72 28 | 95.82 28 | 75.20 152 | 93.58 97 | 84.76 43 | 96.16 99 | 97.48 16 |
|
v12 | | | 87.15 78 | 87.91 68 | 84.84 121 | 88.69 158 | 63.52 192 | 87.58 86 | 91.46 106 | 78.74 94 | 93.57 31 | 95.66 32 | 74.94 156 | 93.57 98 | 84.50 46 | 96.08 104 | 97.43 17 |
|
test11 | | | | | | | | | 91.46 106 | | | | | | | | |
|
V9 | | | 86.96 79 | 87.70 73 | 84.74 125 | 88.52 163 | 63.27 198 | 87.31 91 | 91.45 108 | 78.28 99 | 93.43 32 | 95.45 39 | 74.59 164 | 93.57 98 | 84.23 50 | 96.01 107 | 97.38 18 |
|
CANet | | | 83.79 153 | 82.85 162 | 86.63 87 | 86.17 233 | 72.21 127 | 83.76 155 | 91.43 109 | 77.24 117 | 74.39 298 | 87.45 232 | 75.36 150 | 95.42 32 | 77.03 136 | 92.83 195 | 92.25 157 |
|
v1192 | | | 84.57 126 | 84.69 127 | 84.21 143 | 87.75 190 | 62.88 205 | 83.02 178 | 91.43 109 | 69.08 220 | 89.98 90 | 90.89 171 | 72.70 199 | 93.62 93 | 82.41 71 | 94.97 140 | 96.13 44 |
|
alignmvs | | | 83.94 151 | 83.98 149 | 83.80 151 | 87.80 189 | 67.88 162 | 84.54 136 | 91.42 111 | 73.27 169 | 88.41 130 | 87.96 223 | 72.33 204 | 90.83 185 | 76.02 142 | 94.11 161 | 92.69 138 |
|
V14 | | | 86.75 85 | 87.46 76 | 84.62 129 | 88.35 168 | 63.00 203 | 87.02 97 | 91.42 111 | 77.78 105 | 93.27 35 | 95.23 45 | 74.22 167 | 93.56 101 | 83.95 53 | 95.93 110 | 97.31 21 |
|
v15 | | | 86.56 88 | 87.25 80 | 84.51 131 | 88.15 175 | 62.72 208 | 86.72 107 | 91.40 113 | 77.38 110 | 93.11 37 | 95.00 50 | 73.93 172 | 93.55 102 | 83.67 57 | 95.86 114 | 97.26 22 |
|
v7 | | | 84.81 121 | 85.00 118 | 84.23 142 | 88.15 175 | 63.27 198 | 83.79 154 | 91.39 114 | 71.10 203 | 90.07 85 | 91.28 151 | 74.04 171 | 93.63 89 | 81.48 82 | 93.67 174 | 95.79 53 |
|
pcd1.5k->3k | | | 38.83 336 | 41.11 337 | 32.01 347 | 93.13 62 | 0.00 368 | 0.00 360 | 91.38 115 | 0.00 363 | 0.00 364 | 0.00 365 | 89.24 15 | 0.00 366 | 0.00 363 | 96.24 97 | 96.02 49 |
|
v8 | | | 86.22 98 | 86.83 91 | 84.36 139 | 87.82 185 | 62.35 217 | 86.42 112 | 91.33 116 | 76.78 123 | 92.73 48 | 94.48 68 | 73.41 184 | 93.72 85 | 83.10 62 | 95.41 124 | 97.01 32 |
|
TranMVSNet+NR-MVSNet | | | 87.86 69 | 88.76 62 | 85.18 116 | 94.02 43 | 64.13 185 | 84.38 138 | 91.29 117 | 84.88 28 | 92.06 59 | 93.84 95 | 86.45 44 | 93.73 84 | 73.22 162 | 98.66 12 | 97.69 11 |
|
HPM-MVS++ | | | 88.93 57 | 88.45 65 | 90.38 40 | 94.92 33 | 85.85 25 | 89.70 47 | 91.27 118 | 78.20 100 | 86.69 153 | 92.28 129 | 80.36 104 | 95.06 46 | 86.17 32 | 96.49 87 | 90.22 207 |
|
CNVR-MVS | | | 87.81 71 | 87.68 74 | 88.21 67 | 92.87 68 | 77.30 89 | 85.25 124 | 91.23 119 | 77.31 116 | 87.07 148 | 91.47 149 | 82.94 70 | 94.71 54 | 84.67 44 | 96.27 96 | 92.62 145 |
|
v1921920 | | | 84.23 140 | 84.37 143 | 83.79 152 | 87.64 195 | 61.71 225 | 82.91 181 | 91.20 120 | 67.94 229 | 90.06 86 | 90.34 185 | 72.04 208 | 93.59 94 | 82.32 73 | 94.91 141 | 96.07 46 |
|
TSAR-MVS + MP. | | | 88.14 66 | 87.82 71 | 89.09 58 | 95.72 19 | 76.74 94 | 92.49 20 | 91.19 121 | 67.85 231 | 86.63 154 | 94.84 56 | 79.58 110 | 95.96 10 | 87.62 14 | 94.50 156 | 94.56 83 |
|
RPSCF | | | 88.00 67 | 86.93 88 | 91.22 27 | 90.08 137 | 89.30 6 | 89.68 49 | 91.11 122 | 79.26 84 | 89.68 101 | 94.81 60 | 82.44 76 | 87.74 242 | 76.54 140 | 88.74 261 | 96.61 39 |
|
NCCC | | | 87.36 74 | 86.87 89 | 88.83 59 | 92.32 84 | 78.84 74 | 86.58 110 | 91.09 123 | 78.77 93 | 84.85 180 | 90.89 171 | 80.85 99 | 95.29 36 | 81.14 85 | 95.32 127 | 92.34 152 |
|
v144192 | | | 84.24 139 | 84.41 138 | 83.71 158 | 87.59 196 | 61.57 230 | 82.95 180 | 91.03 124 | 67.82 232 | 89.80 98 | 90.49 183 | 73.28 188 | 93.51 107 | 81.88 80 | 94.89 142 | 96.04 48 |
|
HSP-MVS | | | 88.63 60 | 87.84 70 | 91.02 29 | 95.76 16 | 86.14 19 | 92.75 13 | 91.01 125 | 78.43 97 | 89.16 116 | 92.25 130 | 72.03 209 | 96.36 2 | 88.21 9 | 90.93 233 | 90.55 201 |
|
v1144 | | | 84.54 129 | 84.72 125 | 84.00 147 | 87.67 193 | 62.55 214 | 82.97 179 | 90.93 126 | 70.32 209 | 89.80 98 | 90.99 166 | 73.50 182 | 93.48 108 | 81.69 81 | 94.65 154 | 95.97 50 |
|
PAPM_NR | | | 83.23 162 | 83.19 159 | 83.33 169 | 90.90 122 | 65.98 172 | 88.19 77 | 90.78 127 | 78.13 102 | 80.87 238 | 87.92 226 | 73.49 183 | 92.42 146 | 70.07 185 | 88.40 262 | 91.60 173 |
|
Anonymous20240529 | | | 86.20 99 | 87.13 81 | 83.42 168 | 90.19 135 | 64.55 183 | 84.55 135 | 90.71 128 | 85.85 24 | 89.94 91 | 95.24 44 | 82.13 81 | 90.40 197 | 69.19 194 | 96.40 90 | 95.31 71 |
|
test12 | | | | | 86.57 88 | 90.74 125 | 72.63 119 | | 90.69 129 | | 82.76 214 | | 79.20 111 | 94.80 52 | | 95.32 127 | 92.27 155 |
|
PLC | | 73.85 16 | 82.09 177 | 80.31 196 | 87.45 80 | 90.86 124 | 80.29 60 | 85.88 116 | 90.65 130 | 68.17 225 | 76.32 281 | 86.33 246 | 73.12 193 | 92.61 144 | 61.40 249 | 90.02 248 | 89.44 216 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
mvs_tets | | | 89.78 45 | 89.27 53 | 91.30 24 | 93.51 52 | 84.79 36 | 89.89 45 | 90.63 131 | 70.00 212 | 94.55 17 | 96.67 11 | 87.94 28 | 93.59 94 | 84.27 49 | 95.97 108 | 95.52 66 |
|
114514_t | | | 83.10 165 | 82.54 168 | 84.77 124 | 92.90 67 | 69.10 155 | 86.65 108 | 90.62 132 | 54.66 307 | 81.46 230 | 90.81 174 | 76.98 134 | 94.38 61 | 72.62 169 | 96.18 98 | 90.82 193 |
|
PAPR | | | 78.84 207 | 78.10 211 | 81.07 204 | 85.17 248 | 60.22 244 | 82.21 202 | 90.57 133 | 62.51 268 | 75.32 291 | 84.61 272 | 74.99 155 | 92.30 148 | 59.48 267 | 88.04 269 | 90.68 196 |
|
Test4 | | | 81.31 185 | 81.13 188 | 81.88 192 | 84.89 251 | 63.05 202 | 82.37 195 | 90.50 134 | 62.75 266 | 89.00 118 | 88.29 219 | 67.55 226 | 91.68 163 | 73.55 159 | 91.24 223 | 90.89 189 |
|
NR-MVSNet | | | 86.00 101 | 86.22 99 | 85.34 114 | 93.24 59 | 64.56 182 | 82.21 202 | 90.46 135 | 80.99 66 | 88.42 129 | 91.97 134 | 77.56 125 | 93.85 81 | 72.46 170 | 98.65 13 | 97.61 12 |
|
PVSNet_BlendedMVS | | | 78.80 208 | 77.84 212 | 81.65 197 | 84.43 257 | 63.41 193 | 79.49 246 | 90.44 136 | 61.70 276 | 75.43 289 | 87.07 236 | 69.11 220 | 91.44 169 | 60.68 254 | 92.24 206 | 90.11 211 |
|
PVSNet_Blended | | | 76.49 232 | 75.40 235 | 79.76 217 | 84.43 257 | 63.41 193 | 75.14 296 | 90.44 136 | 57.36 295 | 75.43 289 | 78.30 329 | 69.11 220 | 91.44 169 | 60.68 254 | 87.70 274 | 84.42 274 |
|
Gipuma | | | 84.44 130 | 86.33 96 | 78.78 228 | 84.20 265 | 73.57 113 | 89.55 54 | 90.44 136 | 84.24 32 | 84.38 191 | 94.89 54 | 76.35 144 | 80.40 305 | 76.14 141 | 96.80 78 | 82.36 303 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
QAPM | | | 82.59 170 | 82.59 167 | 82.58 181 | 86.44 220 | 66.69 169 | 89.94 44 | 90.36 139 | 67.97 228 | 84.94 178 | 92.58 121 | 72.71 198 | 92.18 150 | 70.63 182 | 87.73 273 | 88.85 227 |
|
TEST9 | | | | | | 92.34 82 | 79.70 66 | 83.94 146 | 90.32 140 | 65.41 251 | 84.49 189 | 90.97 167 | 82.03 85 | 93.63 89 | | | |
|
train_agg | | | 85.98 104 | 85.28 114 | 88.07 70 | 92.34 82 | 79.70 66 | 83.94 146 | 90.32 140 | 65.79 244 | 84.49 189 | 90.97 167 | 81.93 87 | 93.63 89 | 81.21 83 | 96.54 84 | 90.88 190 |
|
test_8 | | | | | | 92.09 89 | 78.87 73 | 83.82 151 | 90.31 142 | 65.79 244 | 84.36 192 | 90.96 169 | 81.93 87 | 93.44 110 | | | |
|
testing_2 | | | 84.36 134 | 84.64 132 | 83.50 167 | 86.74 219 | 63.97 188 | 84.56 134 | 90.31 142 | 66.22 240 | 91.62 67 | 94.55 64 | 75.88 146 | 91.95 155 | 77.02 137 | 94.89 142 | 94.56 83 |
|
agg_prior1 | | | 85.72 108 | 85.20 115 | 87.28 83 | 91.58 104 | 77.69 82 | 83.69 157 | 90.30 144 | 66.29 239 | 84.32 193 | 91.07 164 | 82.13 81 | 93.18 122 | 81.02 86 | 96.36 91 | 90.98 185 |
|
agg_prior | | | | | | 91.58 104 | 77.69 82 | | 90.30 144 | | 84.32 193 | | | 93.18 122 | | | |
|
ITE_SJBPF | | | | | 90.11 45 | 90.72 126 | 84.97 33 | | 90.30 144 | 81.56 61 | 90.02 87 | 91.20 156 | 82.40 77 | 90.81 186 | 73.58 158 | 94.66 153 | 94.56 83 |
|
jajsoiax | | | 89.41 50 | 88.81 60 | 91.19 28 | 93.38 56 | 84.72 37 | 89.70 47 | 90.29 147 | 69.27 216 | 94.39 19 | 96.38 15 | 86.02 49 | 93.52 104 | 83.96 52 | 95.92 111 | 95.34 69 |
|
v1neww | | | 84.43 131 | 84.66 129 | 83.75 154 | 87.81 186 | 62.34 218 | 83.59 158 | 90.27 148 | 72.33 182 | 89.93 93 | 91.22 153 | 73.28 188 | 93.29 116 | 80.25 101 | 93.25 185 | 95.62 61 |
|
v7new | | | 84.43 131 | 84.66 129 | 83.75 154 | 87.81 186 | 62.34 218 | 83.59 158 | 90.27 148 | 72.33 182 | 89.93 93 | 91.22 153 | 73.28 188 | 93.29 116 | 80.25 101 | 93.25 185 | 95.62 61 |
|
v6 | | | 84.43 131 | 84.66 129 | 83.75 154 | 87.81 186 | 62.34 218 | 83.59 158 | 90.26 150 | 72.33 182 | 89.94 91 | 91.19 157 | 73.30 187 | 93.29 116 | 80.26 100 | 93.26 184 | 95.62 61 |
|
V42 | | | 83.47 160 | 83.37 156 | 83.75 154 | 83.16 277 | 63.33 196 | 81.31 220 | 90.23 151 | 69.51 215 | 90.91 78 | 90.81 174 | 74.16 168 | 92.29 149 | 80.06 103 | 90.22 246 | 95.62 61 |
|
anonymousdsp | | | 89.73 46 | 88.88 58 | 92.27 7 | 89.82 143 | 86.67 12 | 90.51 37 | 90.20 152 | 69.87 213 | 95.06 13 | 96.14 23 | 84.28 58 | 93.07 131 | 87.68 13 | 96.34 92 | 97.09 29 |
|
MVSFormer | | | 82.23 175 | 81.57 182 | 84.19 145 | 85.54 244 | 69.26 151 | 91.98 25 | 90.08 153 | 71.54 199 | 76.23 282 | 85.07 265 | 58.69 263 | 94.27 62 | 86.26 28 | 88.77 259 | 89.03 224 |
|
test_djsdf | | | 89.62 47 | 89.01 55 | 91.45 21 | 92.36 81 | 82.98 49 | 91.98 25 | 90.08 153 | 71.54 199 | 94.28 22 | 96.54 13 | 81.57 93 | 94.27 62 | 86.26 28 | 96.49 87 | 97.09 29 |
|
agg_prior3 | | | 85.76 107 | 84.95 120 | 88.16 68 | 92.43 79 | 79.92 62 | 83.98 145 | 90.03 155 | 65.11 253 | 83.66 202 | 90.64 182 | 81.00 98 | 93.67 86 | 81.21 83 | 96.54 84 | 90.88 190 |
|
AdaColmap | | | 83.66 155 | 83.69 153 | 83.57 162 | 90.05 140 | 72.26 125 | 86.29 114 | 90.00 156 | 78.19 101 | 81.65 228 | 87.16 234 | 83.40 66 | 94.24 65 | 61.69 245 | 94.76 151 | 84.21 278 |
|
3Dnovator | | 80.37 7 | 84.80 122 | 84.71 126 | 85.06 117 | 86.36 225 | 74.71 107 | 88.77 71 | 90.00 156 | 75.65 139 | 84.96 176 | 93.17 104 | 74.06 169 | 91.19 174 | 78.28 122 | 91.09 224 | 89.29 220 |
|
IterMVS-LS | | | 84.73 123 | 84.98 119 | 83.96 149 | 87.35 200 | 63.66 190 | 83.25 173 | 89.88 158 | 76.06 128 | 89.62 106 | 92.37 127 | 73.40 186 | 92.52 145 | 78.16 123 | 94.77 150 | 95.69 58 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
v1141 | | | 84.16 142 | 84.38 140 | 83.52 164 | 87.32 202 | 61.70 227 | 82.79 184 | 89.74 159 | 71.90 196 | 89.64 103 | 91.12 160 | 72.68 200 | 93.10 127 | 80.39 99 | 93.80 169 | 95.75 55 |
|
divwei89l23v2f112 | | | 84.16 142 | 84.38 140 | 83.52 164 | 87.32 202 | 61.70 227 | 82.79 184 | 89.74 159 | 71.90 196 | 89.64 103 | 91.12 160 | 72.68 200 | 93.10 127 | 80.40 97 | 93.81 168 | 95.75 55 |
|
v1 | | | 84.16 142 | 84.38 140 | 83.52 164 | 87.33 201 | 61.71 225 | 82.79 184 | 89.73 161 | 71.89 198 | 89.64 103 | 91.11 162 | 72.72 197 | 93.10 127 | 80.40 97 | 93.79 170 | 95.75 55 |
|
v2v482 | | | 84.09 145 | 84.24 145 | 83.62 160 | 87.13 210 | 61.40 231 | 82.71 188 | 89.71 162 | 72.19 186 | 89.55 110 | 91.41 150 | 70.70 216 | 93.20 121 | 81.02 86 | 93.76 171 | 96.25 42 |
|
Fast-Effi-MVS+ | | | 81.04 190 | 80.57 192 | 82.46 185 | 87.50 197 | 63.22 200 | 78.37 267 | 89.63 163 | 68.01 226 | 81.87 223 | 82.08 308 | 82.31 78 | 92.65 143 | 67.10 208 | 88.30 267 | 91.51 176 |
|
Fast-Effi-MVS+-dtu | | | 82.54 171 | 81.41 183 | 85.90 106 | 85.60 242 | 76.53 97 | 83.07 177 | 89.62 164 | 73.02 173 | 79.11 263 | 83.51 282 | 80.74 101 | 90.24 201 | 68.76 198 | 89.29 253 | 90.94 187 |
|
PMVS | | 80.48 6 | 90.08 33 | 90.66 35 | 88.34 66 | 96.71 2 | 92.97 2 | 90.31 38 | 89.57 165 | 88.51 14 | 90.11 84 | 95.12 48 | 90.98 7 | 88.92 226 | 77.55 128 | 97.07 69 | 83.13 295 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
OpenMVS | | 76.72 13 | 81.98 180 | 82.00 177 | 81.93 189 | 84.42 259 | 68.22 159 | 88.50 75 | 89.48 166 | 66.92 235 | 81.80 227 | 91.86 136 | 72.59 202 | 90.16 204 | 71.19 176 | 91.25 222 | 87.40 241 |
|
test_0402 | | | 88.65 59 | 89.58 51 | 85.88 107 | 92.55 75 | 72.22 126 | 84.01 144 | 89.44 167 | 88.63 13 | 94.38 20 | 95.77 29 | 86.38 46 | 93.59 94 | 79.84 106 | 95.21 131 | 91.82 167 |
|
Regformer-2 | | | 86.74 86 | 86.08 102 | 88.73 60 | 84.18 266 | 79.20 70 | 83.52 162 | 89.33 168 | 83.33 38 | 89.92 95 | 85.07 265 | 83.23 68 | 93.16 124 | 83.39 58 | 92.72 198 | 93.83 105 |
|
MSDG | | | 80.06 204 | 79.99 202 | 80.25 211 | 83.91 270 | 68.04 160 | 77.51 276 | 89.19 169 | 77.65 106 | 81.94 222 | 83.45 284 | 76.37 143 | 86.31 266 | 63.31 235 | 86.59 282 | 86.41 249 |
|
ambc | | | | | 82.98 174 | 90.55 130 | 64.86 179 | 88.20 76 | 89.15 170 | | 89.40 113 | 93.96 89 | 71.67 212 | 91.38 173 | 78.83 117 | 96.55 83 | 92.71 137 |
|
pmmvs6 | | | 86.52 90 | 88.06 67 | 81.90 190 | 92.22 87 | 62.28 222 | 84.66 132 | 89.15 170 | 83.54 37 | 89.85 96 | 97.32 3 | 88.08 27 | 86.80 258 | 70.43 184 | 97.30 64 | 96.62 38 |
|
CNLPA | | | 83.55 158 | 83.10 160 | 84.90 119 | 89.34 147 | 83.87 43 | 84.54 136 | 88.77 172 | 79.09 87 | 83.54 205 | 88.66 211 | 74.87 157 | 81.73 301 | 66.84 212 | 92.29 203 | 89.11 221 |
|
LF4IMVS | | | 82.75 168 | 81.93 178 | 85.19 115 | 82.08 282 | 80.15 61 | 85.53 121 | 88.76 173 | 68.01 226 | 85.58 171 | 87.75 227 | 71.80 210 | 86.85 251 | 74.02 153 | 93.87 167 | 88.58 228 |
|
VPA-MVSNet | | | 83.47 160 | 84.73 123 | 79.69 219 | 90.29 133 | 57.52 261 | 81.30 222 | 88.69 174 | 76.29 126 | 87.58 139 | 94.44 69 | 80.60 102 | 87.20 246 | 66.60 214 | 96.82 77 | 94.34 93 |
|
IS-MVSNet | | | 86.66 87 | 86.82 92 | 86.17 102 | 92.05 91 | 66.87 168 | 91.21 33 | 88.64 175 | 86.30 23 | 89.60 109 | 92.59 119 | 69.22 219 | 94.91 50 | 73.89 155 | 97.89 44 | 96.72 36 |
|
BH-untuned | | | 80.96 191 | 80.99 189 | 80.84 206 | 88.55 162 | 68.23 158 | 80.33 234 | 88.46 176 | 72.79 175 | 86.55 155 | 86.76 238 | 74.72 162 | 91.77 162 | 61.79 244 | 88.99 257 | 82.52 301 |
|
Effi-MVS+-dtu | | | 85.82 106 | 83.38 155 | 93.14 3 | 87.13 210 | 91.15 3 | 87.70 85 | 88.42 177 | 74.57 150 | 83.56 204 | 85.65 252 | 78.49 116 | 94.21 66 | 72.04 173 | 92.88 194 | 94.05 100 |
|
mvs-test1 | | | 84.55 127 | 82.12 174 | 91.84 17 | 87.13 210 | 89.54 5 | 85.05 127 | 88.42 177 | 74.57 150 | 80.60 247 | 82.98 289 | 78.49 116 | 93.98 76 | 72.04 173 | 89.77 250 | 92.00 161 |
|
diffmvs | | | 81.78 182 | 82.36 172 | 80.02 214 | 79.06 308 | 59.93 246 | 83.30 170 | 88.41 179 | 73.47 160 | 78.38 267 | 92.05 133 | 75.85 147 | 88.38 236 | 80.73 93 | 89.98 249 | 91.76 169 |
|
TinyColmap | | | 81.25 188 | 82.34 173 | 77.99 242 | 85.33 247 | 60.68 241 | 82.32 197 | 88.33 180 | 71.26 201 | 86.97 150 | 92.22 132 | 77.10 132 | 86.98 249 | 62.37 238 | 95.17 133 | 86.31 251 |
|
CANet_DTU | | | 77.81 215 | 77.05 216 | 80.09 213 | 81.37 288 | 59.90 247 | 83.26 172 | 88.29 181 | 69.16 219 | 67.83 328 | 83.72 280 | 60.93 248 | 89.47 213 | 69.22 193 | 89.70 251 | 90.88 190 |
|
GBi-Net | | | 82.02 178 | 82.07 175 | 81.85 193 | 86.38 222 | 61.05 237 | 86.83 100 | 88.27 182 | 72.43 178 | 86.00 164 | 95.64 34 | 63.78 240 | 90.68 190 | 65.95 217 | 93.34 181 | 93.82 107 |
|
test1 | | | 82.02 178 | 82.07 175 | 81.85 193 | 86.38 222 | 61.05 237 | 86.83 100 | 88.27 182 | 72.43 178 | 86.00 164 | 95.64 34 | 63.78 240 | 90.68 190 | 65.95 217 | 93.34 181 | 93.82 107 |
|
FMVSNet1 | | | 84.55 127 | 85.45 112 | 81.85 193 | 90.27 134 | 61.05 237 | 86.83 100 | 88.27 182 | 78.57 96 | 89.66 102 | 95.64 34 | 75.43 149 | 90.68 190 | 69.09 195 | 95.33 126 | 93.82 107 |
|
SixPastTwentyTwo | | | 87.20 77 | 87.45 77 | 86.45 91 | 92.52 76 | 69.19 154 | 87.84 84 | 88.05 185 | 81.66 60 | 94.64 16 | 96.53 14 | 65.94 233 | 94.75 53 | 83.02 65 | 96.83 76 | 95.41 68 |
|
USDC | | | 76.63 229 | 76.73 220 | 76.34 265 | 83.46 273 | 57.20 264 | 80.02 237 | 88.04 186 | 52.14 322 | 83.65 203 | 91.25 152 | 63.24 243 | 86.65 262 | 54.66 298 | 94.11 161 | 85.17 262 |
|
Regformer-4 | | | 86.41 91 | 85.71 107 | 88.52 62 | 84.27 262 | 77.57 84 | 84.07 142 | 88.00 187 | 82.82 46 | 89.84 97 | 85.48 255 | 82.06 83 | 92.77 139 | 83.83 56 | 91.04 226 | 95.22 76 |
|
EPP-MVSNet | | | 85.47 111 | 85.04 117 | 86.77 86 | 91.52 107 | 69.37 149 | 91.63 28 | 87.98 188 | 81.51 62 | 87.05 149 | 91.83 139 | 66.18 232 | 95.29 36 | 70.75 179 | 96.89 73 | 95.64 60 |
|
Regformer-1 | | | 86.00 101 | 85.50 111 | 87.49 79 | 84.18 266 | 76.90 92 | 83.52 162 | 87.94 189 | 82.18 54 | 89.19 115 | 85.07 265 | 82.28 79 | 91.89 158 | 82.40 72 | 92.72 198 | 93.69 113 |
|
MAR-MVS | | | 80.24 201 | 78.74 207 | 84.73 126 | 86.87 218 | 78.18 77 | 85.75 118 | 87.81 190 | 65.67 247 | 77.84 270 | 78.50 328 | 73.79 175 | 90.53 194 | 61.59 248 | 90.87 235 | 85.49 260 |
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 |
API-MVS | | | 82.28 174 | 82.61 166 | 81.30 200 | 86.29 228 | 69.79 145 | 88.71 72 | 87.67 191 | 78.42 98 | 82.15 220 | 84.15 278 | 77.98 120 | 91.59 165 | 65.39 223 | 92.75 196 | 82.51 302 |
|
pm-mvs1 | | | 83.69 154 | 84.95 120 | 79.91 215 | 90.04 141 | 59.66 248 | 82.43 193 | 87.44 192 | 75.52 140 | 87.85 136 | 95.26 43 | 81.25 97 | 85.65 275 | 68.74 199 | 96.04 106 | 94.42 91 |
|
cascas | | | 76.29 234 | 74.81 240 | 80.72 209 | 84.47 256 | 62.94 204 | 73.89 305 | 87.34 193 | 55.94 301 | 75.16 293 | 76.53 336 | 63.97 238 | 91.16 175 | 65.00 224 | 90.97 232 | 88.06 232 |
|
HyFIR lowres test | | | 75.12 244 | 72.66 266 | 82.50 184 | 91.44 110 | 65.19 177 | 72.47 310 | 87.31 194 | 46.79 343 | 80.29 253 | 84.30 275 | 52.70 289 | 92.10 153 | 51.88 312 | 86.73 281 | 90.22 207 |
|
TransMVSNet (Re) | | | 84.02 148 | 85.74 106 | 78.85 227 | 91.00 120 | 55.20 280 | 82.29 198 | 87.26 195 | 79.65 79 | 88.38 131 | 95.52 38 | 83.00 69 | 86.88 250 | 67.97 205 | 96.60 82 | 94.45 90 |
|
DI_MVS_plusplus_test | | | 81.27 187 | 81.26 184 | 81.29 201 | 84.98 249 | 61.65 229 | 81.98 207 | 87.25 196 | 63.56 258 | 87.56 140 | 89.60 198 | 73.62 178 | 91.83 160 | 72.20 172 | 90.59 244 | 90.38 205 |
|
xiu_mvs_v1_base_debu | | | 80.84 193 | 80.14 199 | 82.93 176 | 88.31 169 | 71.73 133 | 79.53 243 | 87.17 197 | 65.43 248 | 79.59 257 | 82.73 296 | 76.94 135 | 90.14 205 | 73.22 162 | 88.33 263 | 86.90 246 |
|
xiu_mvs_v1_base | | | 80.84 193 | 80.14 199 | 82.93 176 | 88.31 169 | 71.73 133 | 79.53 243 | 87.17 197 | 65.43 248 | 79.59 257 | 82.73 296 | 76.94 135 | 90.14 205 | 73.22 162 | 88.33 263 | 86.90 246 |
|
xiu_mvs_v1_base_debi | | | 80.84 193 | 80.14 199 | 82.93 176 | 88.31 169 | 71.73 133 | 79.53 243 | 87.17 197 | 65.43 248 | 79.59 257 | 82.73 296 | 76.94 135 | 90.14 205 | 73.22 162 | 88.33 263 | 86.90 246 |
|
PS-MVSNAJ | | | 77.04 222 | 76.53 225 | 78.56 232 | 87.09 214 | 61.40 231 | 75.26 295 | 87.13 200 | 61.25 278 | 74.38 299 | 77.22 333 | 76.94 135 | 90.94 180 | 64.63 227 | 84.83 302 | 83.35 290 |
|
MVS_111021_HR | | | 84.63 124 | 84.34 144 | 85.49 113 | 90.18 136 | 75.86 102 | 79.23 259 | 87.13 200 | 73.35 163 | 85.56 172 | 89.34 202 | 83.60 64 | 90.50 195 | 76.64 139 | 94.05 163 | 90.09 212 |
|
xiu_mvs_v2_base | | | 77.19 220 | 76.75 219 | 78.52 233 | 87.01 215 | 61.30 233 | 75.55 294 | 87.12 202 | 61.24 279 | 74.45 297 | 78.79 327 | 77.20 129 | 90.93 181 | 64.62 228 | 84.80 303 | 83.32 291 |
|
1112_ss | | | 74.82 249 | 73.74 249 | 78.04 241 | 89.57 144 | 60.04 245 | 76.49 285 | 87.09 203 | 54.31 308 | 73.66 302 | 79.80 323 | 60.25 253 | 86.76 260 | 58.37 274 | 84.15 306 | 87.32 242 |
|
EG-PatchMatch MVS | | | 84.08 146 | 84.11 146 | 83.98 148 | 92.22 87 | 72.61 120 | 82.20 204 | 87.02 204 | 72.63 177 | 88.86 119 | 91.02 165 | 78.52 115 | 91.11 176 | 73.41 161 | 91.09 224 | 88.21 230 |
|
Baseline_NR-MVSNet | | | 84.00 149 | 85.90 104 | 78.29 237 | 91.47 109 | 53.44 290 | 82.29 198 | 87.00 205 | 79.06 88 | 89.55 110 | 95.72 31 | 77.20 129 | 86.14 269 | 72.30 171 | 98.51 18 | 95.28 72 |
|
test_normal | | | 81.23 189 | 81.16 187 | 81.43 199 | 84.77 254 | 61.99 224 | 81.46 219 | 86.95 206 | 63.16 263 | 87.22 143 | 89.63 197 | 73.62 178 | 91.65 164 | 72.92 167 | 90.70 239 | 90.65 198 |
|
PAPM | | | 71.77 277 | 70.06 288 | 76.92 256 | 86.39 221 | 53.97 284 | 76.62 283 | 86.62 207 | 53.44 313 | 63.97 342 | 84.73 271 | 57.79 270 | 92.34 147 | 39.65 343 | 81.33 322 | 84.45 273 |
|
FMVSNet2 | | | 81.31 185 | 81.61 181 | 80.41 210 | 86.38 222 | 58.75 256 | 83.93 148 | 86.58 208 | 72.43 178 | 87.65 138 | 92.98 109 | 63.78 240 | 90.22 202 | 66.86 210 | 93.92 166 | 92.27 155 |
|
BH-w/o | | | 76.57 230 | 76.07 229 | 78.10 240 | 86.88 217 | 65.92 173 | 77.63 274 | 86.33 209 | 65.69 246 | 80.89 237 | 79.95 322 | 68.97 222 | 90.74 188 | 53.01 304 | 85.25 296 | 77.62 332 |
|
BH-RMVSNet | | | 80.53 196 | 80.22 198 | 81.49 198 | 87.19 209 | 66.21 171 | 77.79 273 | 86.23 210 | 74.21 153 | 83.69 200 | 88.50 212 | 73.25 192 | 90.75 187 | 63.18 236 | 87.90 270 | 87.52 239 |
|
Test_1112_low_res | | | 73.90 257 | 73.08 262 | 76.35 264 | 90.35 132 | 55.95 271 | 73.40 309 | 86.17 211 | 50.70 333 | 73.14 303 | 85.94 251 | 58.31 265 | 85.90 272 | 56.51 284 | 83.22 310 | 87.20 243 |
|
ab-mvs | | | 79.67 205 | 80.56 193 | 76.99 255 | 88.48 165 | 56.93 265 | 84.70 131 | 86.06 212 | 68.95 222 | 80.78 239 | 93.08 105 | 75.30 151 | 84.62 284 | 56.78 283 | 90.90 234 | 89.43 217 |
|
v148 | | | 82.31 173 | 82.48 170 | 81.81 196 | 85.59 243 | 59.66 248 | 81.47 218 | 86.02 213 | 72.85 174 | 88.05 133 | 90.65 180 | 70.73 215 | 90.91 183 | 75.15 146 | 91.79 210 | 94.87 79 |
|
MVS | | | 73.21 265 | 72.59 268 | 75.06 274 | 80.97 292 | 60.81 240 | 81.64 215 | 85.92 214 | 46.03 346 | 71.68 311 | 77.54 330 | 68.47 223 | 89.77 211 | 55.70 289 | 85.39 293 | 74.60 338 |
|
FMVSNet3 | | | 78.80 208 | 78.55 208 | 79.57 221 | 82.89 279 | 56.89 267 | 81.76 212 | 85.77 215 | 69.04 221 | 86.00 164 | 90.44 184 | 51.75 291 | 90.09 208 | 65.95 217 | 93.34 181 | 91.72 170 |
|
UGNet | | | 82.78 167 | 81.64 180 | 86.21 99 | 86.20 232 | 76.24 101 | 86.86 98 | 85.68 216 | 77.07 120 | 73.76 301 | 92.82 114 | 69.64 217 | 91.82 161 | 69.04 196 | 93.69 173 | 90.56 200 |
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 |
无先验 | | | | | | | | 82.81 183 | 85.62 217 | 58.09 292 | | | | 91.41 171 | 67.95 206 | | 84.48 272 |
|
cdsmvs_eth3d_5k | | | 20.81 337 | 27.75 338 | 0.00 353 | 0.00 367 | 0.00 368 | 0.00 360 | 85.44 218 | 0.00 363 | 0.00 364 | 82.82 294 | 81.46 94 | 0.00 366 | 0.00 363 | 0.00 364 | 0.00 364 |
|
1314 | | | 73.22 264 | 72.56 269 | 75.20 273 | 80.41 300 | 57.84 258 | 81.64 215 | 85.36 219 | 51.68 325 | 73.10 304 | 76.65 335 | 61.45 247 | 85.19 278 | 63.54 232 | 79.21 331 | 82.59 298 |
|
0601test | | | 78.71 210 | 78.51 209 | 79.32 224 | 84.32 261 | 58.84 254 | 78.38 266 | 85.33 220 | 75.99 131 | 82.49 216 | 86.57 239 | 58.01 266 | 90.02 210 | 62.74 237 | 92.73 197 | 89.10 222 |
|
Regformer-3 | | | 85.06 115 | 84.67 128 | 86.22 97 | 84.27 262 | 73.43 114 | 84.07 142 | 85.26 221 | 80.77 68 | 88.62 125 | 85.48 255 | 80.56 103 | 90.39 198 | 81.99 78 | 91.04 226 | 94.85 81 |
|
MVP-Stereo | | | 75.81 239 | 73.51 259 | 82.71 179 | 89.35 146 | 73.62 112 | 80.06 235 | 85.20 222 | 60.30 284 | 73.96 300 | 87.94 224 | 57.89 269 | 89.45 215 | 52.02 307 | 74.87 340 | 85.06 264 |
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
EI-MVSNet-Vis-set | | | 85.12 114 | 84.53 135 | 86.88 84 | 84.01 268 | 72.76 118 | 83.91 149 | 85.18 223 | 80.44 69 | 88.75 122 | 85.49 254 | 80.08 106 | 91.92 156 | 82.02 77 | 90.85 236 | 95.97 50 |
|
EI-MVSNet-UG-set | | | 85.04 116 | 84.44 137 | 86.85 85 | 83.87 271 | 72.52 121 | 83.82 151 | 85.15 224 | 80.27 73 | 88.75 122 | 85.45 258 | 79.95 108 | 91.90 157 | 81.92 79 | 90.80 237 | 96.13 44 |
|
EI-MVSNet | | | 82.61 169 | 82.42 171 | 83.20 171 | 83.25 275 | 63.66 190 | 83.50 165 | 85.07 225 | 76.06 128 | 86.55 155 | 85.10 263 | 73.41 184 | 90.25 199 | 78.15 124 | 90.67 240 | 95.68 59 |
|
MVSTER | | | 77.09 221 | 75.70 233 | 81.25 202 | 75.27 338 | 61.08 236 | 77.49 277 | 85.07 225 | 60.78 282 | 86.55 155 | 88.68 210 | 43.14 333 | 90.25 199 | 73.69 157 | 90.67 240 | 92.42 148 |
|
WR-MVS | | | 83.56 157 | 84.40 139 | 81.06 205 | 93.43 55 | 54.88 281 | 78.67 265 | 85.02 227 | 81.24 63 | 90.74 80 | 91.56 147 | 72.85 195 | 91.08 177 | 68.00 204 | 98.04 35 | 97.23 24 |
|
MG-MVS | | | 80.32 199 | 80.94 190 | 78.47 235 | 88.18 172 | 52.62 297 | 82.29 198 | 85.01 228 | 72.01 188 | 79.24 262 | 92.54 122 | 69.36 218 | 93.36 115 | 70.65 181 | 89.19 256 | 89.45 215 |
|
VDD-MVS | | | 84.23 140 | 84.58 134 | 83.20 171 | 91.17 117 | 65.16 178 | 83.25 173 | 84.97 229 | 79.79 76 | 87.18 144 | 94.27 76 | 74.77 161 | 90.89 184 | 69.24 191 | 96.54 84 | 93.55 120 |
|
mvs_anonymous | | | 78.13 212 | 78.76 206 | 76.23 267 | 79.24 306 | 50.31 322 | 78.69 264 | 84.82 230 | 61.60 277 | 83.09 212 | 92.82 114 | 73.89 174 | 87.01 247 | 68.33 203 | 86.41 284 | 91.37 179 |
|
MIMVSNet1 | | | 83.63 156 | 84.59 133 | 80.74 207 | 94.06 42 | 62.77 207 | 82.72 187 | 84.53 231 | 77.57 108 | 90.34 82 | 95.92 27 | 76.88 141 | 85.83 273 | 61.88 243 | 97.42 61 | 93.62 115 |
|
VNet | | | 79.31 206 | 80.27 197 | 76.44 263 | 87.92 180 | 53.95 285 | 75.58 293 | 84.35 232 | 74.39 152 | 82.23 218 | 90.72 176 | 72.84 196 | 84.39 286 | 60.38 256 | 93.98 165 | 90.97 186 |
|
MVS_111021_LR | | | 84.28 138 | 83.76 152 | 85.83 109 | 89.23 149 | 83.07 48 | 80.99 228 | 83.56 233 | 72.71 176 | 86.07 163 | 89.07 205 | 81.75 92 | 86.19 268 | 77.11 135 | 93.36 180 | 88.24 229 |
|
CHOSEN 1792x2688 | | | 72.45 271 | 70.56 282 | 78.13 239 | 90.02 142 | 63.08 201 | 68.72 323 | 83.16 234 | 42.99 352 | 75.92 285 | 85.46 257 | 57.22 274 | 85.18 279 | 49.87 317 | 81.67 319 | 86.14 252 |
|
TR-MVS | | | 76.77 228 | 75.79 230 | 79.72 218 | 86.10 240 | 65.79 174 | 77.14 278 | 83.02 235 | 65.20 252 | 81.40 231 | 82.10 307 | 66.30 230 | 90.73 189 | 55.57 290 | 85.27 295 | 82.65 297 |
|
GA-MVS | | | 75.83 238 | 74.61 241 | 79.48 223 | 81.87 284 | 59.25 252 | 73.42 308 | 82.88 236 | 68.68 223 | 79.75 256 | 81.80 310 | 50.62 293 | 89.46 214 | 66.85 211 | 85.64 291 | 89.72 213 |
|
tfpnnormal | | | 81.79 181 | 82.95 161 | 78.31 236 | 88.93 154 | 55.40 276 | 80.83 231 | 82.85 237 | 76.81 122 | 85.90 167 | 94.14 82 | 74.58 165 | 86.51 263 | 66.82 213 | 95.68 121 | 93.01 130 |
|
OpenMVS_ROB | | 70.19 17 | 77.77 216 | 77.46 214 | 78.71 230 | 84.39 260 | 61.15 235 | 81.18 224 | 82.52 238 | 62.45 270 | 83.34 206 | 87.37 233 | 66.20 231 | 88.66 234 | 64.69 226 | 85.02 299 | 86.32 250 |
|
Anonymous202405211 | | | 80.51 197 | 81.19 186 | 78.49 234 | 88.48 165 | 57.26 263 | 76.63 282 | 82.49 239 | 81.21 64 | 84.30 195 | 92.24 131 | 67.99 224 | 86.24 267 | 62.22 239 | 95.13 134 | 91.98 164 |
|
EU-MVSNet | | | 75.12 244 | 74.43 245 | 77.18 254 | 83.11 278 | 59.48 250 | 85.71 120 | 82.43 240 | 39.76 355 | 85.64 170 | 88.76 208 | 44.71 329 | 87.88 241 | 73.86 156 | 85.88 289 | 84.16 279 |
|
CMPMVS | | 59.41 20 | 75.12 244 | 73.57 252 | 79.77 216 | 75.84 330 | 67.22 164 | 81.21 223 | 82.18 241 | 50.78 332 | 76.50 278 | 87.66 229 | 55.20 283 | 82.99 295 | 62.17 242 | 90.64 243 | 89.09 223 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
CDS-MVSNet | | | 77.32 219 | 75.40 235 | 83.06 173 | 89.00 153 | 72.48 122 | 77.90 272 | 82.17 242 | 60.81 281 | 78.94 264 | 83.49 283 | 59.30 260 | 88.76 232 | 54.64 299 | 92.37 202 | 87.93 236 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
HY-MVS | | 64.64 18 | 73.03 266 | 72.47 270 | 74.71 276 | 83.36 274 | 54.19 283 | 82.14 205 | 81.96 243 | 56.76 300 | 69.57 321 | 86.21 249 | 60.03 254 | 84.83 283 | 49.58 319 | 82.65 315 | 85.11 263 |
|
wuykxyi23d | | | 88.46 62 | 88.80 61 | 87.44 81 | 90.96 121 | 93.03 1 | 85.85 117 | 81.96 243 | 74.58 149 | 98.58 2 | 97.29 4 | 87.73 30 | 87.31 245 | 82.84 68 | 99.41 1 | 81.99 308 |
|
jason | | | 77.42 218 | 75.75 232 | 82.43 186 | 87.10 213 | 69.27 150 | 77.99 270 | 81.94 245 | 51.47 327 | 77.84 270 | 85.07 265 | 60.32 252 | 89.00 224 | 70.74 180 | 89.27 255 | 89.03 224 |
jason: jason. |
旧先验1 | | | | | | 91.97 92 | 71.77 132 | | 81.78 246 | | | 91.84 138 | 73.92 173 | | | 93.65 175 | 83.61 285 |
|
VPNet | | | 80.25 200 | 81.68 179 | 75.94 270 | 92.46 78 | 47.98 335 | 76.70 281 | 81.67 247 | 73.45 161 | 84.87 179 | 92.82 114 | 74.66 163 | 86.51 263 | 61.66 246 | 96.85 74 | 93.33 121 |
|
TSAR-MVS + GP. | | | 83.95 150 | 82.69 164 | 87.72 75 | 89.27 148 | 81.45 55 | 83.72 156 | 81.58 248 | 74.73 148 | 85.66 169 | 86.06 250 | 72.56 203 | 92.69 141 | 75.44 145 | 95.21 131 | 89.01 226 |
|
VDDNet | | | 84.35 136 | 85.39 113 | 81.25 202 | 95.13 29 | 59.32 251 | 85.42 123 | 81.11 249 | 86.41 22 | 87.41 142 | 96.21 21 | 73.61 180 | 90.61 193 | 66.33 215 | 96.85 74 | 93.81 110 |
|
semantic-postprocess | | | | | 84.34 140 | 83.93 269 | 69.66 147 | | 81.09 250 | 72.43 178 | 86.47 161 | 90.19 189 | 57.56 271 | 93.15 126 | 77.45 130 | 86.39 285 | 90.22 207 |
|
UnsupCasMVSNet_eth | | | 71.63 279 | 72.30 271 | 69.62 305 | 76.47 326 | 52.70 296 | 70.03 320 | 80.97 251 | 59.18 287 | 79.36 260 | 88.21 220 | 60.50 250 | 69.12 333 | 58.33 276 | 77.62 335 | 87.04 244 |
|
lupinMVS | | | 76.37 233 | 74.46 244 | 82.09 187 | 85.54 244 | 69.26 151 | 76.79 279 | 80.77 252 | 50.68 334 | 76.23 282 | 82.82 294 | 58.69 263 | 88.94 225 | 69.85 186 | 88.77 259 | 88.07 231 |
|
新几何1 | | | | | 82.95 175 | 93.96 44 | 78.56 76 | | 80.24 253 | 55.45 303 | 83.93 199 | 91.08 163 | 71.19 214 | 88.33 237 | 65.84 220 | 93.07 189 | 81.95 310 |
|
1121 | | | 80.86 192 | 79.81 203 | 84.02 146 | 93.93 45 | 78.70 75 | 81.64 215 | 80.18 254 | 55.43 304 | 83.67 201 | 91.15 158 | 71.29 213 | 91.41 171 | 67.95 206 | 93.06 190 | 81.96 309 |
|
testdata | | | | | 79.54 222 | 92.87 68 | 72.34 123 | | 80.14 255 | 59.91 286 | 85.47 174 | 91.75 143 | 67.96 225 | 85.24 277 | 68.57 202 | 92.18 209 | 81.06 327 |
|
TAMVS | | | 78.08 213 | 76.36 226 | 83.23 170 | 90.62 127 | 72.87 117 | 79.08 260 | 80.01 256 | 61.72 275 | 81.35 232 | 86.92 237 | 63.96 239 | 88.78 231 | 50.61 313 | 93.01 192 | 88.04 233 |
|
pmmvs-eth3d | | | 78.42 211 | 77.04 217 | 82.57 183 | 87.44 198 | 74.41 109 | 80.86 230 | 79.67 257 | 55.68 302 | 84.69 182 | 90.31 188 | 60.91 249 | 85.42 276 | 62.20 240 | 91.59 213 | 87.88 237 |
|
IterMVS | | | 76.91 223 | 76.34 227 | 78.64 231 | 80.91 293 | 64.03 186 | 76.30 287 | 79.03 258 | 64.88 255 | 83.11 210 | 89.16 203 | 59.90 256 | 84.46 285 | 68.61 201 | 85.15 298 | 87.42 240 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
CVMVSNet | | | 72.62 269 | 71.41 279 | 76.28 266 | 83.25 275 | 60.34 243 | 83.50 165 | 79.02 259 | 37.77 356 | 76.33 280 | 85.10 263 | 49.60 296 | 87.41 244 | 70.54 183 | 77.54 336 | 81.08 325 |
|
ppachtmachnet_test | | | 74.73 250 | 74.00 248 | 76.90 257 | 80.71 297 | 56.89 267 | 71.53 314 | 78.42 260 | 58.24 291 | 79.32 261 | 82.92 293 | 57.91 268 | 84.26 287 | 65.60 222 | 91.36 215 | 89.56 214 |
|
FMVSNet5 | | | 72.10 275 | 71.69 275 | 73.32 286 | 81.57 287 | 53.02 293 | 76.77 280 | 78.37 261 | 63.31 261 | 76.37 279 | 91.85 137 | 36.68 351 | 78.98 309 | 47.87 326 | 92.45 201 | 87.95 235 |
|
MS-PatchMatch | | | 70.93 283 | 70.22 286 | 73.06 291 | 81.85 285 | 62.50 215 | 73.82 306 | 77.90 262 | 52.44 319 | 75.92 285 | 81.27 314 | 55.67 280 | 81.75 300 | 55.37 292 | 77.70 334 | 74.94 337 |
|
test222 | | | | | | 93.31 57 | 76.54 95 | 79.38 253 | 77.79 263 | 52.59 317 | 82.36 217 | 90.84 173 | 66.83 229 | | | 91.69 212 | 81.25 322 |
|
pmmvs4 | | | 74.92 247 | 72.98 264 | 80.73 208 | 84.95 250 | 71.71 136 | 76.23 288 | 77.59 264 | 52.83 316 | 77.73 273 | 86.38 242 | 56.35 276 | 84.97 280 | 57.72 280 | 87.05 279 | 85.51 259 |
|
EPNet | | | 80.37 198 | 78.41 210 | 86.23 96 | 76.75 324 | 73.28 115 | 87.18 94 | 77.45 265 | 76.24 127 | 68.14 325 | 88.93 207 | 65.41 235 | 93.85 81 | 69.47 189 | 96.12 103 | 91.55 175 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
XXY-MVS | | | 74.44 253 | 76.19 228 | 69.21 307 | 84.61 255 | 52.43 298 | 71.70 313 | 77.18 266 | 60.73 283 | 80.60 247 | 90.96 169 | 75.44 148 | 69.35 332 | 56.13 286 | 88.33 263 | 85.86 256 |
|
no-one | | | 71.52 280 | 70.43 285 | 74.81 275 | 78.45 314 | 63.41 193 | 57.73 349 | 77.03 267 | 51.46 328 | 77.17 276 | 90.33 186 | 54.96 285 | 80.35 306 | 47.41 327 | 99.29 2 | 80.68 329 |
|
CR-MVSNet | | | 74.00 256 | 73.04 263 | 76.85 259 | 79.58 301 | 62.64 209 | 82.58 189 | 76.90 268 | 50.50 335 | 75.72 287 | 92.38 124 | 48.07 300 | 84.07 288 | 68.72 200 | 82.91 313 | 83.85 282 |
|
Patchmtry | | | 76.56 231 | 77.46 214 | 73.83 284 | 79.37 305 | 46.60 337 | 82.41 194 | 76.90 268 | 73.81 157 | 85.56 172 | 92.38 124 | 48.07 300 | 83.98 290 | 63.36 234 | 95.31 129 | 90.92 188 |
|
IB-MVS | | 62.13 19 | 71.64 278 | 68.97 292 | 79.66 220 | 80.80 296 | 62.26 223 | 73.94 304 | 76.90 268 | 63.27 262 | 68.63 324 | 76.79 334 | 33.83 354 | 91.84 159 | 59.28 268 | 87.26 277 | 84.88 269 |
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 |
K. test v3 | | | 85.14 113 | 84.73 123 | 86.37 92 | 91.13 118 | 69.63 148 | 85.45 122 | 76.68 271 | 84.06 35 | 92.44 54 | 96.99 8 | 62.03 245 | 94.65 55 | 80.58 95 | 93.24 187 | 94.83 82 |
|
N_pmnet | | | 70.20 287 | 68.80 294 | 74.38 278 | 80.91 293 | 84.81 35 | 59.12 346 | 76.45 272 | 55.06 305 | 75.31 292 | 82.36 305 | 55.74 279 | 54.82 357 | 47.02 329 | 87.24 278 | 83.52 286 |
|
EPNet_dtu | | | 72.87 267 | 71.33 280 | 77.49 252 | 77.72 318 | 60.55 242 | 82.35 196 | 75.79 273 | 66.49 238 | 58.39 355 | 81.06 316 | 53.68 287 | 85.98 270 | 53.55 302 | 92.97 193 | 85.95 254 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
UnsupCasMVSNet_bld | | | 69.21 297 | 69.68 289 | 67.82 314 | 79.42 303 | 51.15 311 | 67.82 328 | 75.79 273 | 54.15 309 | 77.47 274 | 85.36 262 | 59.26 261 | 70.64 328 | 48.46 323 | 79.35 329 | 81.66 315 |
|
MDA-MVSNet-bldmvs | | | 77.47 217 | 76.90 218 | 79.16 225 | 79.03 309 | 64.59 181 | 66.58 332 | 75.67 275 | 73.15 171 | 88.86 119 | 88.99 206 | 66.94 228 | 81.23 302 | 64.71 225 | 88.22 268 | 91.64 172 |
|
pmmvs5 | | | 70.73 284 | 70.07 287 | 72.72 293 | 77.03 323 | 52.73 295 | 74.14 302 | 75.65 276 | 50.36 336 | 72.17 309 | 85.37 261 | 55.42 282 | 80.67 304 | 52.86 305 | 87.59 275 | 84.77 270 |
|
tpmvs | | | 70.16 288 | 69.56 290 | 71.96 299 | 74.71 342 | 48.13 333 | 79.63 241 | 75.45 277 | 65.02 254 | 70.26 318 | 81.88 309 | 45.34 320 | 85.68 274 | 58.34 275 | 75.39 339 | 82.08 307 |
|
tpmp4_e23 | | | 69.43 294 | 67.33 301 | 75.72 271 | 78.53 313 | 52.75 294 | 82.13 206 | 74.91 278 | 49.23 340 | 66.37 331 | 84.17 277 | 41.28 343 | 88.67 233 | 49.73 318 | 79.63 326 | 85.75 257 |
|
LP | | | 69.42 295 | 68.30 297 | 72.77 292 | 71.48 355 | 56.84 269 | 73.66 307 | 74.84 279 | 63.52 259 | 70.95 317 | 83.35 286 | 49.55 297 | 77.15 314 | 57.13 282 | 70.21 348 | 84.33 275 |
|
ADS-MVSNet2 | | | 65.87 310 | 63.64 315 | 72.55 296 | 73.16 348 | 56.92 266 | 67.10 330 | 74.81 280 | 49.74 337 | 66.04 333 | 82.97 290 | 46.71 302 | 77.26 312 | 42.29 338 | 69.96 350 | 83.46 287 |
|
new-patchmatchnet | | | 70.10 289 | 73.37 260 | 60.29 335 | 81.23 290 | 16.95 363 | 59.54 343 | 74.62 281 | 62.93 264 | 80.97 235 | 87.93 225 | 62.83 244 | 71.90 326 | 55.24 293 | 95.01 139 | 92.00 161 |
|
Anonymous20231206 | | | 71.38 281 | 71.88 274 | 69.88 302 | 86.31 227 | 54.37 282 | 70.39 318 | 74.62 281 | 52.57 318 | 76.73 277 | 88.76 208 | 59.94 255 | 72.06 325 | 44.35 336 | 93.23 188 | 83.23 293 |
|
CostFormer | | | 69.98 292 | 68.68 295 | 73.87 283 | 77.14 321 | 50.72 320 | 79.26 255 | 74.51 283 | 51.94 324 | 70.97 316 | 84.75 270 | 45.16 327 | 87.49 243 | 55.16 294 | 79.23 330 | 83.40 289 |
|
door-mid | | | | | | | | | 74.45 284 | | | | | | | | |
|
tfpn200view9 | | | 74.86 248 | 74.23 246 | 76.74 261 | 86.24 229 | 52.12 299 | 79.24 256 | 73.87 285 | 73.34 164 | 81.82 225 | 84.60 273 | 46.02 307 | 88.80 227 | 51.98 308 | 90.99 228 | 89.31 218 |
|
thres400 | | | 75.14 242 | 74.23 246 | 77.86 244 | 86.24 229 | 52.12 299 | 79.24 256 | 73.87 285 | 73.34 164 | 81.82 225 | 84.60 273 | 46.02 307 | 88.80 227 | 51.98 308 | 90.99 228 | 92.66 139 |
|
LFMVS | | | 80.15 203 | 80.56 193 | 78.89 226 | 89.19 150 | 55.93 272 | 85.22 125 | 73.78 287 | 82.96 44 | 84.28 196 | 92.72 118 | 57.38 272 | 90.07 209 | 63.80 231 | 95.75 118 | 90.68 196 |
|
thres200 | | | 72.34 273 | 71.55 278 | 74.70 277 | 83.48 272 | 51.60 307 | 75.02 297 | 73.71 288 | 70.14 211 | 78.56 265 | 80.57 317 | 46.20 305 | 88.20 239 | 46.99 330 | 89.29 253 | 84.32 276 |
|
tpm cat1 | | | 66.76 305 | 65.21 310 | 71.42 300 | 77.09 322 | 50.62 321 | 78.01 269 | 73.68 289 | 44.89 348 | 68.64 322 | 79.00 326 | 45.51 317 | 82.42 298 | 49.91 316 | 70.15 349 | 81.23 324 |
|
PatchFormer-LS_test | | | 67.91 301 | 66.49 307 | 72.17 298 | 75.29 337 | 51.85 305 | 75.68 290 | 73.62 290 | 57.23 297 | 68.64 322 | 68.13 352 | 42.19 335 | 82.76 296 | 64.06 230 | 73.51 342 | 81.89 312 |
|
testgi | | | 72.36 272 | 74.61 241 | 65.59 320 | 80.56 299 | 42.82 348 | 68.29 324 | 73.35 291 | 66.87 236 | 81.84 224 | 89.93 193 | 72.08 207 | 66.92 340 | 46.05 333 | 92.54 200 | 87.01 245 |
|
tfpn111 | | | 76.03 236 | 75.53 234 | 77.53 251 | 87.27 204 | 51.88 302 | 81.07 225 | 73.26 292 | 75.68 136 | 83.25 207 | 86.37 243 | 45.54 313 | 89.38 218 | 55.07 295 | 92.26 205 | 91.34 181 |
|
conf200view11 | | | 75.62 240 | 75.05 238 | 77.34 253 | 87.27 204 | 51.88 302 | 81.07 225 | 73.26 292 | 75.68 136 | 83.25 207 | 86.37 243 | 45.54 313 | 88.80 227 | 51.98 308 | 90.99 228 | 91.34 181 |
|
thres100view900 | | | 75.45 241 | 75.05 238 | 76.66 262 | 87.27 204 | 51.88 302 | 81.07 225 | 73.26 292 | 75.68 136 | 83.25 207 | 86.37 243 | 45.54 313 | 88.80 227 | 51.98 308 | 90.99 228 | 89.31 218 |
|
thres600view7 | | | 75.97 237 | 75.35 237 | 77.85 245 | 87.01 215 | 51.84 306 | 80.45 233 | 73.26 292 | 75.20 145 | 83.10 211 | 86.31 248 | 45.54 313 | 89.05 223 | 55.03 296 | 92.24 206 | 92.66 139 |
|
wuyk23d | | | 75.13 243 | 79.30 204 | 62.63 327 | 75.56 332 | 75.18 105 | 80.89 229 | 73.10 296 | 75.06 146 | 94.76 14 | 95.32 41 | 87.73 30 | 52.85 358 | 34.16 352 | 97.11 68 | 59.85 353 |
|
DWT-MVSNet_test | | | 66.43 306 | 64.37 311 | 72.63 294 | 74.86 341 | 50.86 315 | 76.52 284 | 72.74 297 | 54.06 310 | 65.50 335 | 68.30 351 | 32.13 356 | 84.84 282 | 61.63 247 | 73.59 341 | 82.19 305 |
|
WTY-MVS | | | 67.91 301 | 68.35 296 | 66.58 318 | 80.82 295 | 48.12 334 | 65.96 333 | 72.60 298 | 53.67 312 | 71.20 314 | 81.68 312 | 58.97 262 | 69.06 334 | 48.57 322 | 81.67 319 | 82.55 299 |
|
door | | | | | | | | | 72.57 299 | | | | | | | | |
|
PVSNet | | 58.17 21 | 66.41 307 | 65.63 309 | 68.75 310 | 81.96 283 | 49.88 331 | 62.19 339 | 72.51 300 | 51.03 330 | 68.04 326 | 75.34 340 | 50.84 292 | 74.77 320 | 45.82 334 | 82.96 311 | 81.60 316 |
|
MDTV_nov1_ep13 | | | | 68.29 298 | | 78.03 317 | 43.87 345 | 74.12 303 | 72.22 301 | 52.17 320 | 67.02 330 | 85.54 253 | 45.36 319 | 80.85 303 | 55.73 287 | 84.42 305 | |
|
test20.03 | | | 73.75 258 | 74.59 243 | 71.22 301 | 81.11 291 | 51.12 312 | 70.15 319 | 72.10 302 | 70.42 207 | 80.28 254 | 91.50 148 | 64.21 237 | 74.72 322 | 46.96 331 | 94.58 155 | 87.82 238 |
|
Vis-MVSNet (Re-imp) | | | 77.82 214 | 77.79 213 | 77.92 243 | 88.82 156 | 51.29 310 | 83.28 171 | 71.97 303 | 74.04 154 | 82.23 218 | 89.78 195 | 57.38 272 | 89.41 216 | 57.22 281 | 95.41 124 | 93.05 129 |
|
testmv | | | 70.47 286 | 70.70 281 | 69.77 304 | 86.22 231 | 53.89 286 | 67.32 329 | 71.91 304 | 63.32 260 | 78.16 268 | 89.47 200 | 56.12 278 | 73.10 323 | 36.43 349 | 87.33 276 | 82.33 304 |
|
MIMVSNet | | | 71.09 282 | 71.59 276 | 69.57 306 | 87.23 207 | 50.07 324 | 78.91 261 | 71.83 305 | 60.20 285 | 71.26 313 | 91.76 142 | 55.08 284 | 76.09 316 | 41.06 341 | 87.02 280 | 82.54 300 |
|
tpm2 | | | 68.45 299 | 66.83 303 | 73.30 287 | 78.93 310 | 48.50 332 | 79.76 240 | 71.76 306 | 47.50 342 | 69.92 320 | 83.60 281 | 42.07 336 | 88.40 235 | 48.44 324 | 79.51 327 | 83.01 296 |
|
RPMNet | | | 76.06 235 | 75.79 230 | 76.85 259 | 79.58 301 | 62.64 209 | 82.58 189 | 71.75 307 | 74.80 147 | 75.72 287 | 92.59 119 | 48.69 298 | 84.07 288 | 73.48 160 | 82.91 313 | 83.85 282 |
|
sss | | | 66.92 304 | 67.26 302 | 65.90 319 | 77.23 320 | 51.10 313 | 64.79 334 | 71.72 308 | 52.12 323 | 70.13 319 | 80.18 320 | 57.96 267 | 65.36 347 | 50.21 314 | 81.01 324 | 81.25 322 |
|
our_test_3 | | | 71.85 276 | 71.59 276 | 72.62 295 | 80.71 297 | 53.78 287 | 69.72 321 | 71.71 309 | 58.80 288 | 78.03 269 | 80.51 318 | 56.61 275 | 78.84 310 | 62.20 240 | 86.04 288 | 85.23 261 |
|
Patchmatch-test1 | | | 72.75 268 | 72.61 267 | 73.19 289 | 81.62 286 | 55.86 273 | 78.89 262 | 71.37 310 | 61.73 274 | 74.93 294 | 82.15 306 | 60.46 251 | 81.80 299 | 59.68 259 | 82.63 317 | 81.92 311 |
|
view600 | | | 76.79 224 | 76.54 221 | 77.56 247 | 87.91 181 | 50.77 316 | 81.92 208 | 71.35 311 | 77.38 110 | 84.62 183 | 88.40 214 | 45.18 323 | 89.26 219 | 58.58 270 | 93.49 176 | 92.66 139 |
|
view800 | | | 76.79 224 | 76.54 221 | 77.56 247 | 87.91 181 | 50.77 316 | 81.92 208 | 71.35 311 | 77.38 110 | 84.62 183 | 88.40 214 | 45.18 323 | 89.26 219 | 58.58 270 | 93.49 176 | 92.66 139 |
|
conf0.05thres1000 | | | 76.79 224 | 76.54 221 | 77.56 247 | 87.91 181 | 50.77 316 | 81.92 208 | 71.35 311 | 77.38 110 | 84.62 183 | 88.40 214 | 45.18 323 | 89.26 219 | 58.58 270 | 93.49 176 | 92.66 139 |
|
tfpn | | | 76.79 224 | 76.54 221 | 77.56 247 | 87.91 181 | 50.77 316 | 81.92 208 | 71.35 311 | 77.38 110 | 84.62 183 | 88.40 214 | 45.18 323 | 89.26 219 | 58.58 270 | 93.49 176 | 92.66 139 |
|
lessismore_v0 | | | | | 85.95 104 | 91.10 119 | 70.99 141 | | 70.91 315 | | 91.79 64 | 94.42 70 | 61.76 246 | 92.93 134 | 79.52 112 | 93.03 191 | 93.93 104 |
|
tpmrst | | | 66.28 308 | 66.69 305 | 65.05 324 | 72.82 351 | 39.33 351 | 78.20 268 | 70.69 316 | 53.16 315 | 67.88 327 | 80.36 319 | 48.18 299 | 74.75 321 | 58.13 277 | 70.79 347 | 81.08 325 |
|
tfpn_ndepth | | | 72.54 270 | 72.30 271 | 73.24 288 | 84.81 253 | 51.42 308 | 79.24 256 | 70.49 317 | 69.26 217 | 78.48 266 | 79.80 323 | 40.16 347 | 86.77 259 | 58.08 279 | 90.43 245 | 81.53 318 |
|
PatchMatch-RL | | | 74.48 251 | 73.22 261 | 78.27 238 | 87.70 192 | 85.26 30 | 75.92 289 | 70.09 318 | 64.34 257 | 76.09 284 | 81.25 315 | 65.87 234 | 78.07 311 | 53.86 301 | 83.82 307 | 71.48 343 |
|
PatchmatchNet | | | 69.71 293 | 68.83 293 | 72.33 297 | 77.66 319 | 53.60 288 | 79.29 254 | 69.99 319 | 57.66 294 | 72.53 306 | 82.93 292 | 46.45 304 | 80.08 308 | 60.91 253 | 72.09 345 | 83.31 292 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
testus | | | 62.33 316 | 63.03 316 | 60.20 336 | 78.78 311 | 40.74 349 | 59.14 344 | 69.80 320 | 49.26 339 | 71.41 312 | 74.72 342 | 52.33 290 | 63.52 349 | 29.84 356 | 82.01 318 | 76.36 334 |
|
test1235678 | | | 65.57 311 | 65.73 308 | 65.06 323 | 82.84 280 | 50.90 314 | 62.90 337 | 69.26 321 | 57.17 298 | 72.36 307 | 83.04 288 | 46.02 307 | 70.10 329 | 32.79 354 | 85.24 297 | 74.19 339 |
|
test12356 | | | 54.91 332 | 57.14 330 | 48.22 345 | 75.83 331 | 17.47 362 | 52.31 355 | 69.20 322 | 51.66 326 | 60.11 348 | 75.40 339 | 29.77 360 | 62.62 353 | 27.64 357 | 72.37 344 | 64.59 349 |
|
Patchmatch-RL test | | | 74.48 251 | 73.68 250 | 76.89 258 | 84.83 252 | 66.54 170 | 72.29 311 | 69.16 323 | 57.70 293 | 86.76 151 | 86.33 246 | 45.79 312 | 82.59 297 | 69.63 188 | 90.65 242 | 81.54 317 |
|
conf0.01 | | | 74.17 254 | 73.53 253 | 76.08 268 | 86.13 234 | 50.06 325 | 79.45 247 | 68.54 324 | 72.01 188 | 80.76 240 | 82.50 299 | 41.39 337 | 86.83 252 | 59.66 260 | 91.36 215 | 91.34 181 |
|
conf0.002 | | | 74.17 254 | 73.53 253 | 76.08 268 | 86.13 234 | 50.06 325 | 79.45 247 | 68.54 324 | 72.01 188 | 80.76 240 | 82.50 299 | 41.39 337 | 86.83 252 | 59.66 260 | 91.36 215 | 91.34 181 |
|
thresconf0.02 | | | 73.65 259 | 73.53 253 | 73.98 279 | 86.13 234 | 50.06 325 | 79.45 247 | 68.54 324 | 72.01 188 | 80.76 240 | 82.50 299 | 41.39 337 | 86.83 252 | 59.66 260 | 91.36 215 | 85.06 264 |
|
tfpn_n400 | | | 73.65 259 | 73.53 253 | 73.98 279 | 86.13 234 | 50.06 325 | 79.45 247 | 68.54 324 | 72.01 188 | 80.76 240 | 82.50 299 | 41.39 337 | 86.83 252 | 59.66 260 | 91.36 215 | 85.06 264 |
|
tfpnconf | | | 73.65 259 | 73.53 253 | 73.98 279 | 86.13 234 | 50.06 325 | 79.45 247 | 68.54 324 | 72.01 188 | 80.76 240 | 82.50 299 | 41.39 337 | 86.83 252 | 59.66 260 | 91.36 215 | 85.06 264 |
|
tfpnview11 | | | 73.65 259 | 73.53 253 | 73.98 279 | 86.13 234 | 50.06 325 | 79.45 247 | 68.54 324 | 72.01 188 | 80.76 240 | 82.50 299 | 41.39 337 | 86.83 252 | 59.66 260 | 91.36 215 | 85.06 264 |
|
tfpn1000 | | | 73.63 263 | 73.58 251 | 73.79 285 | 85.46 246 | 50.31 322 | 79.99 238 | 68.18 330 | 72.33 182 | 80.66 246 | 83.05 287 | 39.80 348 | 86.74 261 | 60.96 252 | 91.78 211 | 84.32 276 |
|
1111 | | | 61.71 318 | 63.77 314 | 55.55 341 | 78.05 315 | 25.74 360 | 60.62 340 | 67.52 331 | 66.09 241 | 74.68 295 | 86.50 240 | 16.00 366 | 59.22 355 | 38.79 344 | 85.65 290 | 81.70 313 |
|
.test1245 | | | 48.02 335 | 54.41 334 | 28.84 348 | 78.05 315 | 25.74 360 | 60.62 340 | 67.52 331 | 66.09 241 | 74.68 295 | 86.50 240 | 16.00 366 | 59.22 355 | 38.79 344 | 1.47 361 | 1.55 362 |
|
FPMVS | | | 72.29 274 | 72.00 273 | 73.14 290 | 88.63 161 | 85.00 32 | 74.65 300 | 67.39 333 | 71.94 195 | 77.80 272 | 87.66 229 | 50.48 294 | 75.83 318 | 49.95 315 | 79.51 327 | 58.58 355 |
|
MDA-MVSNet_test_wron | | | 70.05 291 | 70.44 283 | 68.88 309 | 73.84 343 | 53.47 289 | 58.93 348 | 67.28 334 | 58.43 289 | 87.09 147 | 85.40 259 | 59.80 258 | 67.25 338 | 59.66 260 | 83.54 308 | 85.92 255 |
|
YYNet1 | | | 70.06 290 | 70.44 283 | 68.90 308 | 73.76 344 | 53.42 291 | 58.99 347 | 67.20 335 | 58.42 290 | 87.10 146 | 85.39 260 | 59.82 257 | 67.32 337 | 59.79 258 | 83.50 309 | 85.96 253 |
|
test-LLR | | | 67.21 303 | 66.74 304 | 68.63 311 | 76.45 327 | 55.21 278 | 67.89 325 | 67.14 336 | 62.43 271 | 65.08 338 | 72.39 344 | 43.41 331 | 69.37 330 | 61.00 250 | 84.89 300 | 81.31 320 |
|
test-mter | | | 65.00 312 | 63.79 313 | 68.63 311 | 76.45 327 | 55.21 278 | 67.89 325 | 67.14 336 | 50.98 331 | 65.08 338 | 72.39 344 | 28.27 361 | 69.37 330 | 61.00 250 | 84.89 300 | 81.31 320 |
|
tpm | | | 67.95 300 | 68.08 299 | 67.55 315 | 78.74 312 | 43.53 346 | 75.60 292 | 67.10 338 | 54.92 306 | 72.23 308 | 88.10 221 | 42.87 334 | 75.97 317 | 52.21 306 | 80.95 325 | 83.15 294 |
|
PM-MVS | | | 80.20 202 | 79.00 205 | 83.78 153 | 88.17 173 | 86.66 13 | 81.31 220 | 66.81 339 | 69.64 214 | 88.33 132 | 90.19 189 | 64.58 236 | 83.63 293 | 71.99 175 | 90.03 247 | 81.06 327 |
|
JIA-IIPM | | | 69.41 296 | 66.64 306 | 77.70 246 | 73.19 347 | 71.24 139 | 75.67 291 | 65.56 340 | 70.42 207 | 65.18 337 | 92.97 110 | 33.64 355 | 83.06 294 | 53.52 303 | 69.61 352 | 78.79 331 |
|
PatchT | | | 70.52 285 | 72.76 265 | 63.79 326 | 79.38 304 | 33.53 356 | 77.63 274 | 65.37 341 | 73.61 158 | 71.77 310 | 92.79 117 | 44.38 330 | 75.65 319 | 64.53 229 | 85.37 294 | 82.18 306 |
|
dp | | | 60.70 325 | 60.29 326 | 61.92 330 | 72.04 353 | 38.67 353 | 70.83 315 | 64.08 342 | 51.28 329 | 60.75 346 | 77.28 332 | 36.59 352 | 71.58 327 | 47.41 327 | 62.34 356 | 75.52 336 |
|
Patchmatch-test | | | 65.91 309 | 67.38 300 | 61.48 332 | 75.51 334 | 43.21 347 | 68.84 322 | 63.79 343 | 62.48 269 | 72.80 305 | 83.42 285 | 44.89 328 | 59.52 354 | 48.27 325 | 86.45 283 | 81.70 313 |
|
test2356 | | | 56.69 328 | 55.15 332 | 61.32 333 | 73.20 346 | 44.11 344 | 54.95 351 | 62.52 344 | 48.75 341 | 62.45 344 | 68.42 349 | 21.10 365 | 65.67 346 | 26.86 358 | 78.08 333 | 74.19 339 |
|
TESTMET0.1,1 | | | 61.29 321 | 60.32 325 | 64.19 325 | 72.06 352 | 51.30 309 | 67.89 325 | 62.09 345 | 45.27 347 | 60.65 347 | 69.01 347 | 27.93 362 | 64.74 348 | 56.31 285 | 81.65 321 | 76.53 333 |
|
PVSNet_0 | | 51.08 22 | 56.10 329 | 54.97 333 | 59.48 337 | 75.12 339 | 53.28 292 | 55.16 350 | 61.89 346 | 44.30 349 | 59.16 351 | 62.48 356 | 54.22 286 | 65.91 345 | 35.40 351 | 47.01 357 | 59.25 354 |
|
ADS-MVSNet | | | 61.90 317 | 62.19 319 | 61.03 334 | 73.16 348 | 36.42 354 | 67.10 330 | 61.75 347 | 49.74 337 | 66.04 333 | 82.97 290 | 46.71 302 | 63.21 351 | 42.29 338 | 69.96 350 | 83.46 287 |
|
PMMVS | | | 61.65 319 | 60.38 324 | 65.47 322 | 65.40 360 | 69.26 151 | 63.97 336 | 61.73 348 | 36.80 357 | 60.11 348 | 68.43 348 | 59.42 259 | 66.35 343 | 48.97 321 | 78.57 332 | 60.81 352 |
|
test0.0.03 1 | | | 64.66 313 | 64.36 312 | 65.57 321 | 75.03 340 | 46.89 336 | 64.69 335 | 61.58 349 | 62.43 271 | 71.18 315 | 77.54 330 | 43.41 331 | 68.47 335 | 40.75 342 | 82.65 315 | 81.35 319 |
|
E-PMN | | | 61.59 320 | 61.62 320 | 61.49 331 | 66.81 357 | 55.40 276 | 53.77 353 | 60.34 350 | 66.80 237 | 58.90 353 | 65.50 354 | 40.48 346 | 66.12 344 | 55.72 288 | 86.25 286 | 62.95 351 |
|
CHOSEN 280x420 | | | 59.08 326 | 56.52 331 | 66.76 317 | 76.51 325 | 64.39 184 | 49.62 356 | 59.00 351 | 43.86 350 | 55.66 358 | 68.41 350 | 35.55 353 | 68.21 336 | 43.25 337 | 76.78 338 | 67.69 348 |
|
EMVS | | | 61.10 323 | 60.81 323 | 61.99 329 | 65.96 359 | 55.86 273 | 53.10 354 | 58.97 352 | 67.06 233 | 56.89 357 | 63.33 355 | 40.98 344 | 67.03 339 | 54.79 297 | 86.18 287 | 63.08 350 |
|
pmmvs3 | | | 62.47 314 | 60.02 327 | 69.80 303 | 71.58 354 | 64.00 187 | 70.52 317 | 58.44 353 | 39.77 354 | 66.05 332 | 75.84 337 | 27.10 363 | 72.28 324 | 46.15 332 | 84.77 304 | 73.11 341 |
|
testpf | | | 58.55 327 | 61.58 322 | 49.48 344 | 66.03 358 | 40.05 350 | 74.40 301 | 58.07 354 | 64.72 256 | 59.36 350 | 72.67 343 | 22.76 364 | 66.92 340 | 67.07 209 | 69.15 353 | 41.46 358 |
|
MVS-HIRNet | | | 61.16 322 | 62.92 317 | 55.87 339 | 79.09 307 | 35.34 355 | 71.83 312 | 57.98 355 | 46.56 344 | 59.05 352 | 91.14 159 | 49.95 295 | 76.43 315 | 38.74 346 | 71.92 346 | 55.84 356 |
|
gg-mvs-nofinetune | | | 68.96 298 | 69.11 291 | 68.52 313 | 76.12 329 | 45.32 339 | 83.59 158 | 55.88 356 | 86.68 20 | 64.62 341 | 97.01 7 | 30.36 358 | 83.97 291 | 44.78 335 | 82.94 312 | 76.26 335 |
|
GG-mvs-BLEND | | | | | 67.16 316 | 73.36 345 | 46.54 338 | 84.15 141 | 55.04 357 | | 58.64 354 | 61.95 357 | 29.93 359 | 83.87 292 | 38.71 347 | 76.92 337 | 71.07 344 |
|
EPMVS | | | 62.47 314 | 62.63 318 | 62.01 328 | 70.63 356 | 38.74 352 | 74.76 298 | 52.86 358 | 53.91 311 | 67.71 329 | 80.01 321 | 39.40 349 | 66.60 342 | 55.54 291 | 68.81 354 | 80.68 329 |
|
PNet_i23d | | | 52.13 333 | 51.24 335 | 54.79 342 | 75.56 332 | 45.26 340 | 54.54 352 | 52.55 359 | 66.95 234 | 57.19 356 | 65.82 353 | 13.15 368 | 63.40 350 | 36.39 350 | 39.04 359 | 55.71 357 |
|
new_pmnet | | | 55.69 330 | 57.66 329 | 49.76 343 | 75.47 335 | 30.59 357 | 59.56 342 | 51.45 360 | 43.62 351 | 62.49 343 | 75.48 338 | 40.96 345 | 49.15 360 | 37.39 348 | 72.52 343 | 69.55 346 |
|
PMMVS2 | | | 55.64 331 | 59.27 328 | 44.74 346 | 64.30 361 | 12.32 364 | 40.60 357 | 49.79 361 | 53.19 314 | 65.06 340 | 84.81 269 | 53.60 288 | 49.76 359 | 32.68 355 | 89.41 252 | 72.15 342 |
|
DSMNet-mixed | | | 60.98 324 | 61.61 321 | 59.09 338 | 72.88 350 | 45.05 342 | 74.70 299 | 46.61 362 | 26.20 358 | 65.34 336 | 90.32 187 | 55.46 281 | 63.12 352 | 41.72 340 | 81.30 323 | 69.09 347 |
|
MVE | | 40.22 23 | 51.82 334 | 50.47 336 | 55.87 339 | 62.66 362 | 51.91 301 | 31.61 359 | 39.28 363 | 40.65 353 | 50.76 359 | 74.98 341 | 56.24 277 | 44.67 361 | 33.94 353 | 64.11 355 | 71.04 345 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
MTMP | | | | | | | | 90.66 35 | 33.14 364 | | | | | | | | |
|
tmp_tt | | | 20.25 338 | 24.50 339 | 7.49 350 | 4.47 364 | 8.70 365 | 34.17 358 | 25.16 365 | 1.00 360 | 32.43 361 | 18.49 359 | 39.37 350 | 9.21 363 | 21.64 359 | 43.75 358 | 4.57 360 |
|
DeepMVS_CX | | | | | 24.13 349 | 32.95 363 | 29.49 358 | | 21.63 366 | 12.07 359 | 37.95 360 | 45.07 358 | 30.84 357 | 19.21 362 | 17.94 360 | 33.06 360 | 23.69 359 |
|
test123 | | | 6.27 341 | 8.08 342 | 0.84 351 | 1.11 366 | 0.57 366 | 62.90 337 | 0.82 367 | 0.54 361 | 1.07 363 | 2.75 364 | 1.26 369 | 0.30 364 | 1.04 361 | 1.26 363 | 1.66 361 |
|
testmvs | | | 5.91 342 | 7.65 343 | 0.72 352 | 1.20 365 | 0.37 367 | 59.14 344 | 0.67 368 | 0.49 362 | 1.11 362 | 2.76 363 | 0.94 370 | 0.24 365 | 1.02 362 | 1.47 361 | 1.55 362 |
|
pcd_1.5k_mvsjas | | | 6.41 340 | 8.55 341 | 0.00 353 | 0.00 367 | 0.00 368 | 0.00 360 | 0.00 369 | 0.00 363 | 0.00 364 | 0.00 365 | 76.94 135 | 0.00 366 | 0.00 363 | 0.00 364 | 0.00 364 |
|
sosnet-low-res | | | 0.00 343 | 0.00 344 | 0.00 353 | 0.00 367 | 0.00 368 | 0.00 360 | 0.00 369 | 0.00 363 | 0.00 364 | 0.00 365 | 0.00 371 | 0.00 366 | 0.00 363 | 0.00 364 | 0.00 364 |
|
sosnet | | | 0.00 343 | 0.00 344 | 0.00 353 | 0.00 367 | 0.00 368 | 0.00 360 | 0.00 369 | 0.00 363 | 0.00 364 | 0.00 365 | 0.00 371 | 0.00 366 | 0.00 363 | 0.00 364 | 0.00 364 |
|
uncertanet | | | 0.00 343 | 0.00 344 | 0.00 353 | 0.00 367 | 0.00 368 | 0.00 360 | 0.00 369 | 0.00 363 | 0.00 364 | 0.00 365 | 0.00 371 | 0.00 366 | 0.00 363 | 0.00 364 | 0.00 364 |
|
Regformer | | | 0.00 343 | 0.00 344 | 0.00 353 | 0.00 367 | 0.00 368 | 0.00 360 | 0.00 369 | 0.00 363 | 0.00 364 | 0.00 365 | 0.00 371 | 0.00 366 | 0.00 363 | 0.00 364 | 0.00 364 |
|
n2 | | | | | | | | | 0.00 369 | | | | | | | | |
|
nn | | | | | | | | | 0.00 369 | | | | | | | | |
|
ab-mvs-re | | | 6.65 339 | 8.87 340 | 0.00 353 | 0.00 367 | 0.00 368 | 0.00 360 | 0.00 369 | 0.00 363 | 0.00 364 | 79.80 323 | 0.00 371 | 0.00 366 | 0.00 363 | 0.00 364 | 0.00 364 |
|
uanet | | | 0.00 343 | 0.00 344 | 0.00 353 | 0.00 367 | 0.00 368 | 0.00 360 | 0.00 369 | 0.00 363 | 0.00 364 | 0.00 365 | 0.00 371 | 0.00 366 | 0.00 363 | 0.00 364 | 0.00 364 |
|
GSMVS | | | | | | | | | | | | | | | | | 83.88 280 |
|
test_part3 | | | | | | | | 89.63 51 | | 84.39 29 | | 93.43 100 | | 96.26 4 | 82.18 75 | | |
|
test_part2 | | | | | | 93.86 47 | 77.77 80 | | | | 92.84 43 | | | | | | |
|
sam_mvs1 | | | | | | | | | | | | | 46.11 306 | | | | 83.88 280 |
|
sam_mvs | | | | | | | | | | | | | 45.92 311 | | | | |
|
test_post1 | | | | | | | | 78.85 263 | | | | 3.13 361 | 45.19 322 | 80.13 307 | 58.11 278 | | |
|
test_post | | | | | | | | | | | | 3.10 362 | 45.43 318 | 77.22 313 | | | |
|
patchmatchnet-post | | | | | | | | | | | | 81.71 311 | 45.93 310 | 87.01 247 | | | |
|
gm-plane-assit | | | | | | 75.42 336 | 44.97 343 | | | 52.17 320 | | 72.36 346 | | 87.90 240 | 54.10 300 | | |
|
test9_res | | | | | | | | | | | | | | | 80.83 90 | 96.45 89 | 90.57 199 |
|
agg_prior2 | | | | | | | | | | | | | | | 79.68 108 | 96.16 99 | 90.22 207 |
|
test_prior4 | | | | | | | 78.97 72 | 84.59 133 | | | | | | | | | |
|
test_prior2 | | | | | | | | 83.37 168 | | 75.43 141 | 84.58 187 | 91.57 145 | 81.92 89 | | 79.54 110 | 96.97 71 | |
|
旧先验2 | | | | | | | | 81.73 213 | | 56.88 299 | 86.54 160 | | | 84.90 281 | 72.81 168 | | |
|
新几何2 | | | | | | | | 81.72 214 | | | | | | | | | |
|
原ACMM2 | | | | | | | | 82.26 201 | | | | | | | | | |
|
testdata2 | | | | | | | | | | | | | | 86.43 265 | 63.52 233 | | |
|
segment_acmp | | | | | | | | | | | | | 81.94 86 | | | | |
|
testdata1 | | | | | | | | 79.62 242 | | 73.95 156 | | | | | | | |
|
plane_prior7 | | | | | | 93.45 53 | 77.31 88 | | | | | | | | | | |
|
plane_prior6 | | | | | | 92.61 73 | 76.54 95 | | | | | | 74.84 158 | | | | |
|
plane_prior4 | | | | | | | | | | | | 92.95 111 | | | | | |
|
plane_prior3 | | | | | | | 76.85 93 | | | 77.79 104 | 86.55 155 | | | | | | |
|
plane_prior2 | | | | | | | | 89.45 59 | | 79.44 82 | | | | | | | |
|
plane_prior1 | | | | | | 92.83 71 | | | | | | | | | | | |
|
plane_prior | | | | | | | 76.42 98 | 87.15 95 | | 75.94 133 | | | | | | 95.03 138 | |
|
HQP5-MVS | | | | | | | 70.66 142 | | | | | | | | | | |
|
HQP-NCC | | | | | | 91.19 114 | | 84.77 128 | | 73.30 166 | 80.55 250 | | | | | | |
|
ACMP_Plane | | | | | | 91.19 114 | | 84.77 128 | | 73.30 166 | 80.55 250 | | | | | | |
|
BP-MVS | | | | | | | | | | | | | | | 77.30 132 | | |
|
HQP4-MVS | | | | | | | | | | | 80.56 249 | | | 94.61 56 | | | 93.56 118 |
|
HQP2-MVS | | | | | | | | | | | | | 72.10 205 | | | | |
|
NP-MVS | | | | | | 91.95 93 | 74.55 108 | | | | | 90.17 191 | | | | | |
|
MDTV_nov1_ep13_2view | | | | | | | 27.60 359 | 70.76 316 | | 46.47 345 | 61.27 345 | | 45.20 321 | | 49.18 320 | | 83.75 284 |
|
ACMMP++_ref | | | | | | | | | | | | | | | | 95.74 119 | |
|
ACMMP++ | | | | | | | | | | | | | | | | 97.35 62 | |
|
Test By Simon | | | | | | | | | | | | | 79.09 112 | | | | |
|