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 10 | 85.07 37 | 99.27 3 | 99.54 1 |
|
DTE-MVSNet | | | 89.98 38 | 91.91 11 | 84.21 143 | 96.51 7 | 57.84 260 | 88.93 66 | 92.84 65 | 91.92 2 | 96.16 3 | 96.23 20 | 86.95 37 | 95.99 6 | 79.05 115 | 98.57 16 | 98.80 6 |
|
PEN-MVS | | | 90.03 36 | 91.88 12 | 84.48 133 | 96.57 5 | 58.88 255 | 88.95 64 | 93.19 49 | 91.62 3 | 96.01 6 | 96.16 22 | 87.02 36 | 95.60 22 | 78.69 118 | 98.72 10 | 98.97 3 |
|
PS-CasMVS | | | 90.06 35 | 91.92 9 | 84.47 134 | 96.56 6 | 58.83 257 | 89.04 63 | 92.74 68 | 91.40 4 | 96.12 4 | 96.06 25 | 87.23 35 | 95.57 23 | 79.42 113 | 98.74 7 | 99.00 2 |
|
CP-MVSNet | | | 89.27 53 | 90.91 34 | 84.37 138 | 96.34 8 | 58.61 259 | 88.66 72 | 92.06 85 | 90.78 5 | 95.67 9 | 95.17 47 | 81.80 90 | 95.54 26 | 79.00 116 | 98.69 11 | 98.95 4 |
|
LS3D | | | 90.60 28 | 90.34 41 | 91.38 23 | 89.03 153 | 84.23 42 | 93.58 4 | 94.68 10 | 90.65 6 | 90.33 84 | 93.95 93 | 84.50 56 | 95.37 33 | 80.87 89 | 95.50 122 | 94.53 87 |
|
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 43 | 96.29 18 | 88.16 25 | 94.17 68 | 86.07 33 | 98.48 19 | 97.22 25 |
|
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 58 | 95.03 50 | 89.75 14 | 94.93 48 | 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 |
WR-MVS_H | | | 89.91 43 | 91.31 24 | 85.71 110 | 96.32 9 | 62.39 217 | 89.54 54 | 93.31 42 | 90.21 9 | 95.57 11 | 95.66 32 | 81.42 94 | 95.90 11 | 80.94 88 | 98.80 4 | 98.84 5 |
|
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 43 | 91.86 3 | 95.09 43 | 87.54 19 | 98.02 38 | 93.71 113 |
|
3Dnovator+ | | 83.92 2 | 89.97 40 | 89.66 48 | 90.92 32 | 91.27 114 | 81.66 54 | 91.25 32 | 94.13 22 | 88.89 11 | 88.83 122 | 94.26 77 | 77.55 126 | 95.86 14 | 84.88 40 | 95.87 112 | 95.24 73 |
|
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 53 | 93.16 123 | 91.10 1 | 97.53 59 | 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 |
test_0402 | | | 88.65 59 | 89.58 51 | 85.88 107 | 92.55 76 | 72.22 126 | 84.01 144 | 89.44 170 | 88.63 13 | 94.38 20 | 95.77 29 | 86.38 45 | 93.59 93 | 79.84 106 | 95.21 130 | 91.82 169 |
|
PMVS | | 80.48 6 | 90.08 34 | 90.66 36 | 88.34 66 | 96.71 2 | 92.97 2 | 90.31 38 | 89.57 168 | 88.51 14 | 90.11 85 | 95.12 49 | 90.98 7 | 88.92 226 | 77.55 128 | 97.07 68 | 83.13 296 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
UA-Net | | | 91.49 14 | 91.53 17 | 91.39 22 | 94.98 32 | 82.95 50 | 93.52 5 | 92.79 66 | 88.22 15 | 88.53 127 | 97.64 2 | 83.45 64 | 94.55 59 | 86.02 34 | 98.60 14 | 96.67 37 |
|
DP-MVS | | | 88.60 61 | 89.01 55 | 87.36 82 | 91.30 112 | 77.50 85 | 87.55 87 | 92.97 60 | 87.95 16 | 89.62 107 | 92.87 115 | 84.56 55 | 93.89 79 | 77.65 127 | 96.62 80 | 90.70 196 |
|
ACMH+ | | 77.89 11 | 90.73 25 | 91.50 18 | 88.44 64 | 93.00 66 | 76.26 100 | 89.65 50 | 95.55 3 | 87.72 17 | 93.89 27 | 94.94 53 | 91.62 4 | 93.44 109 | 78.35 120 | 98.76 5 | 95.61 65 |
|
APD-MVS_3200maxsize | | | 92.05 7 | 92.24 6 | 91.48 20 | 93.02 65 | 85.17 31 | 92.47 21 | 95.05 8 | 87.65 18 | 93.21 37 | 94.39 74 | 90.09 13 | 95.08 44 | 86.67 25 | 97.60 57 | 94.18 96 |
|
Anonymous20231211 | | | 88.40 63 | 89.62 50 | 84.73 126 | 90.46 132 | 65.27 177 | 88.86 67 | 93.02 58 | 87.15 19 | 93.05 39 | 97.10 6 | 82.28 78 | 92.02 154 | 76.70 139 | 97.99 40 | 96.88 35 |
|
gg-mvs-nofinetune | | | 68.96 300 | 69.11 293 | 68.52 315 | 76.12 332 | 45.32 341 | 83.59 158 | 55.88 359 | 86.68 20 | 64.62 344 | 97.01 7 | 30.36 359 | 83.97 292 | 44.78 336 | 82.94 313 | 76.26 336 |
|
v7n | | | 90.13 33 | 90.96 32 | 87.65 77 | 91.95 94 | 71.06 140 | 89.99 42 | 93.05 54 | 86.53 21 | 94.29 21 | 96.27 19 | 82.69 71 | 94.08 71 | 86.25 30 | 97.63 54 | 97.82 10 |
|
VDDNet | | | 84.35 136 | 85.39 113 | 81.25 203 | 95.13 29 | 59.32 253 | 85.42 123 | 81.11 252 | 86.41 22 | 87.41 143 | 96.21 21 | 73.61 181 | 90.61 193 | 66.33 216 | 96.85 73 | 93.81 111 |
|
IS-MVSNet | | | 86.66 87 | 86.82 92 | 86.17 102 | 92.05 92 | 66.87 168 | 91.21 33 | 88.64 178 | 86.30 23 | 89.60 110 | 92.59 121 | 69.22 220 | 94.91 49 | 73.89 156 | 97.89 44 | 96.72 36 |
|
Anonymous20240529 | | | 86.20 99 | 87.13 81 | 83.42 169 | 90.19 136 | 64.55 184 | 84.55 135 | 90.71 130 | 85.85 24 | 89.94 92 | 95.24 45 | 82.13 80 | 90.40 197 | 69.19 195 | 96.40 89 | 95.31 71 |
|
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 53 | 95.13 48 | 90.65 10 | 95.34 34 | 88.06 10 | 98.15 33 | 95.95 52 |
|
XVS | | | 91.54 12 | 91.36 21 | 92.08 8 | 95.64 21 | 86.25 16 | 92.64 15 | 93.33 40 | 85.07 26 | 89.99 89 | 94.03 86 | 86.57 41 | 95.80 15 | 87.35 20 | 97.62 55 | 94.20 94 |
|
X-MVStestdata | | | 85.04 116 | 82.70 165 | 92.08 8 | 95.64 21 | 86.25 16 | 92.64 15 | 93.33 40 | 85.07 26 | 89.99 89 | 16.05 362 | 86.57 41 | 95.80 15 | 87.35 20 | 97.62 55 | 94.20 94 |
|
TranMVSNet+NR-MVSNet | | | 87.86 69 | 88.76 62 | 85.18 116 | 94.02 43 | 64.13 186 | 84.38 138 | 91.29 119 | 84.88 28 | 92.06 60 | 93.84 96 | 86.45 43 | 93.73 83 | 73.22 163 | 98.66 12 | 97.69 11 |
|
ESAPD | | | 90.53 30 | 91.08 28 | 88.88 59 | 93.38 56 | 78.65 76 | 89.15 62 | 94.05 23 | 84.68 29 | 93.90 25 | 94.11 84 | 88.13 26 | 96.30 3 | 84.51 46 | 97.81 46 | 91.70 173 |
|
v1.0 | | | 38.20 339 | 50.94 338 | 0.00 355 | 93.86 47 | 0.00 370 | 0.00 361 | 93.93 26 | 84.39 30 | 92.84 44 | 93.43 102 | 0.00 372 | 0.00 367 | 0.00 364 | 0.00 365 | 0.00 365 |
|
v748 | | | 88.91 58 | 89.82 46 | 86.19 101 | 90.06 140 | 68.53 156 | 88.81 69 | 91.48 104 | 84.36 31 | 94.19 23 | 95.98 26 | 82.52 74 | 92.67 142 | 84.30 49 | 96.67 79 | 97.37 19 |
|
Gipuma | | | 84.44 130 | 86.33 96 | 78.78 230 | 84.20 267 | 73.57 113 | 89.55 52 | 90.44 138 | 84.24 32 | 84.38 192 | 94.89 54 | 76.35 145 | 80.40 306 | 76.14 142 | 96.80 77 | 82.36 304 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
zzz-MVS | | | 91.27 19 | 91.26 26 | 91.29 25 | 96.59 3 | 86.29 14 | 88.94 65 | 91.81 94 | 84.07 33 | 92.00 61 | 94.40 72 | 86.63 39 | 95.28 37 | 88.59 4 | 98.31 25 | 92.30 155 |
|
MTAPA | | | 91.52 13 | 91.60 15 | 91.29 25 | 96.59 3 | 86.29 14 | 92.02 24 | 91.81 94 | 84.07 33 | 92.00 61 | 94.40 72 | 86.63 39 | 95.28 37 | 88.59 4 | 98.31 25 | 92.30 155 |
|
K. test v3 | | | 85.14 113 | 84.73 123 | 86.37 92 | 91.13 119 | 69.63 148 | 85.45 122 | 76.68 274 | 84.06 35 | 92.44 55 | 96.99 8 | 62.03 246 | 94.65 54 | 80.58 95 | 93.24 186 | 94.83 82 |
|
ANet_high | | | 83.17 165 | 85.68 108 | 75.65 274 | 81.24 291 | 45.26 342 | 79.94 240 | 92.91 61 | 83.83 36 | 91.33 73 | 96.88 10 | 80.25 104 | 85.92 272 | 68.89 198 | 95.89 111 | 95.76 54 |
|
pmmvs6 | | | 86.52 90 | 88.06 67 | 81.90 191 | 92.22 88 | 62.28 223 | 84.66 132 | 89.15 173 | 83.54 37 | 89.85 97 | 97.32 3 | 88.08 28 | 86.80 259 | 70.43 185 | 97.30 63 | 96.62 38 |
|
Regformer-2 | | | 86.74 86 | 86.08 102 | 88.73 61 | 84.18 268 | 79.20 70 | 83.52 162 | 89.33 171 | 83.33 38 | 89.92 96 | 85.07 267 | 83.23 67 | 93.16 123 | 83.39 59 | 92.72 197 | 93.83 106 |
|
APDe-MVS | | | 91.22 20 | 91.92 9 | 89.14 57 | 92.97 67 | 78.04 79 | 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 |
|
CP-MVS | | | 91.67 11 | 91.58 16 | 91.96 12 | 95.29 28 | 87.62 9 | 93.38 7 | 93.36 38 | 83.16 40 | 91.06 75 | 94.00 87 | 88.26 22 | 95.71 20 | 87.28 23 | 98.39 22 | 92.55 148 |
|
mPP-MVS | | | 91.69 10 | 91.47 19 | 92.37 5 | 96.04 11 | 88.48 8 | 92.72 14 | 92.60 73 | 83.09 41 | 91.54 69 | 94.25 78 | 87.67 33 | 95.51 29 | 87.21 24 | 98.11 34 | 93.12 128 |
|
UniMVSNet_NR-MVSNet | | | 86.84 83 | 87.06 83 | 86.17 102 | 92.86 71 | 67.02 166 | 82.55 192 | 91.56 100 | 83.08 42 | 90.92 77 | 91.82 142 | 78.25 119 | 93.99 73 | 74.16 152 | 98.35 23 | 97.49 15 |
|
Anonymous20240521 | | | 87.68 73 | 88.61 63 | 84.87 120 | 91.76 99 | 64.76 181 | 89.28 60 | 91.66 98 | 83.02 43 | 93.29 35 | 96.10 24 | 77.37 128 | 92.89 137 | 77.27 134 | 97.75 50 | 96.97 34 |
|
LFMVS | | | 80.15 205 | 80.56 195 | 78.89 228 | 89.19 151 | 55.93 274 | 85.22 125 | 73.78 290 | 82.96 44 | 84.28 197 | 92.72 120 | 57.38 273 | 90.07 209 | 63.80 232 | 95.75 117 | 90.68 197 |
|
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 66 | 93.94 94 | 90.55 12 | 95.73 19 | 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 |
Regformer-4 | | | 86.41 91 | 85.71 107 | 88.52 63 | 84.27 264 | 77.57 84 | 84.07 142 | 88.00 190 | 82.82 46 | 89.84 98 | 85.48 257 | 82.06 82 | 92.77 139 | 83.83 57 | 91.04 227 | 95.22 76 |
|
SteuartSystems-ACMMP | | | 91.16 22 | 91.36 21 | 90.55 37 | 93.91 46 | 80.97 58 | 91.49 29 | 93.48 37 | 82.82 46 | 92.60 52 | 93.97 88 | 88.19 23 | 96.29 4 | 87.61 16 | 98.20 32 | 94.39 92 |
Skip Steuart: Steuart Systems R&D Blog. |
MP-MVS | | | 91.14 23 | 90.91 34 | 91.83 18 | 96.18 10 | 86.88 11 | 92.20 22 | 93.03 57 | 82.59 48 | 88.52 128 | 94.37 75 | 86.74 38 | 95.41 32 | 86.32 27 | 98.21 31 | 93.19 127 |
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo. |
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 57 | 94.14 82 | 89.15 16 | 95.62 21 | 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 |
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 30 | 94.82 57 | 91.18 5 | 95.52 27 | 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 30 | 94.82 57 | 91.18 5 | 95.52 27 | 85.36 35 | 98.73 8 | 95.23 74 |
|
v52 | | | 89.97 40 | 90.60 37 | 88.07 70 | 88.69 159 | 72.01 128 | 91.35 30 | 92.64 71 | 82.22 52 | 95.97 8 | 96.31 16 | 84.82 52 | 93.98 75 | 88.59 4 | 94.83 145 | 98.23 7 |
|
V4 | | | 89.97 40 | 90.60 37 | 88.07 70 | 88.69 159 | 72.01 128 | 91.35 30 | 92.64 71 | 82.22 52 | 95.98 7 | 96.31 16 | 84.80 54 | 93.98 75 | 88.59 4 | 94.83 145 | 98.23 7 |
|
Regformer-1 | | | 86.00 101 | 85.50 111 | 87.49 79 | 84.18 268 | 76.90 92 | 83.52 162 | 87.94 192 | 82.18 54 | 89.19 116 | 85.07 267 | 82.28 78 | 91.89 158 | 82.40 73 | 92.72 197 | 93.69 114 |
|
HFP-MVS | | | 91.30 18 | 91.39 20 | 91.02 29 | 95.43 25 | 84.66 39 | 92.58 18 | 93.29 45 | 81.99 55 | 91.47 70 | 93.96 90 | 88.35 20 | 95.56 24 | 87.74 12 | 97.74 51 | 92.85 133 |
|
ACMMPR | | | 91.49 14 | 91.35 23 | 91.92 14 | 95.74 18 | 85.88 24 | 92.58 18 | 93.25 47 | 81.99 55 | 91.40 72 | 94.17 81 | 87.51 34 | 95.87 12 | 87.74 12 | 97.76 48 | 93.99 101 |
|
region2R | | | 91.44 17 | 91.30 25 | 91.87 16 | 95.75 17 | 85.90 23 | 92.63 17 | 93.30 43 | 81.91 57 | 90.88 80 | 94.21 79 | 87.75 30 | 95.87 12 | 87.60 17 | 97.71 53 | 93.83 106 |
|
ACMH | | 76.49 14 | 89.34 52 | 91.14 27 | 83.96 150 | 92.50 78 | 70.36 144 | 89.55 52 | 93.84 30 | 81.89 58 | 94.70 15 | 95.44 40 | 90.69 9 | 88.31 239 | 83.33 60 | 98.30 27 | 93.20 126 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
DU-MVS | | | 86.80 84 | 86.99 85 | 86.21 99 | 93.24 60 | 67.02 166 | 83.16 176 | 92.21 81 | 81.73 59 | 90.92 77 | 91.97 136 | 77.20 129 | 93.99 73 | 74.16 152 | 98.35 23 | 97.61 12 |
|
SixPastTwentyTwo | | | 87.20 77 | 87.45 77 | 86.45 91 | 92.52 77 | 69.19 154 | 87.84 84 | 88.05 188 | 81.66 60 | 94.64 16 | 96.53 14 | 65.94 234 | 94.75 52 | 83.02 66 | 96.83 75 | 95.41 68 |
|
ITE_SJBPF | | | | | 90.11 45 | 90.72 127 | 84.97 33 | | 90.30 146 | 81.56 61 | 90.02 88 | 91.20 158 | 82.40 76 | 90.81 186 | 73.58 159 | 94.66 152 | 94.56 83 |
|
EPP-MVSNet | | | 85.47 111 | 85.04 117 | 86.77 86 | 91.52 108 | 69.37 149 | 91.63 28 | 87.98 191 | 81.51 62 | 87.05 150 | 91.83 141 | 66.18 233 | 95.29 35 | 70.75 180 | 96.89 72 | 95.64 60 |
|
WR-MVS | | | 83.56 158 | 84.40 139 | 81.06 206 | 93.43 55 | 54.88 283 | 78.67 266 | 85.02 230 | 81.24 63 | 90.74 81 | 91.56 149 | 72.85 196 | 91.08 177 | 68.00 205 | 98.04 35 | 97.23 24 |
|
Anonymous202405211 | | | 80.51 199 | 81.19 188 | 78.49 236 | 88.48 166 | 57.26 265 | 76.63 283 | 82.49 242 | 81.21 64 | 84.30 196 | 92.24 133 | 67.99 225 | 86.24 268 | 62.22 240 | 95.13 133 | 91.98 166 |
|
OurMVSNet-221017-0 | | | 90.01 37 | 89.74 47 | 90.83 33 | 93.16 62 | 80.37 59 | 91.91 27 | 93.11 51 | 81.10 65 | 95.32 12 | 97.24 5 | 72.94 195 | 94.85 50 | 85.07 37 | 97.78 47 | 97.26 22 |
|
NR-MVSNet | | | 86.00 101 | 86.22 99 | 85.34 114 | 93.24 60 | 64.56 183 | 82.21 203 | 90.46 137 | 80.99 66 | 88.42 130 | 91.97 136 | 77.56 125 | 93.85 80 | 72.46 171 | 98.65 13 | 97.61 12 |
|
APD-MVS | | | 89.54 49 | 89.63 49 | 89.26 56 | 92.57 75 | 81.34 56 | 90.19 39 | 93.08 53 | 80.87 67 | 91.13 74 | 93.19 104 | 86.22 46 | 95.97 8 | 82.23 75 | 97.18 66 | 90.45 204 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
Regformer-3 | | | 85.06 115 | 84.67 128 | 86.22 97 | 84.27 264 | 73.43 114 | 84.07 142 | 85.26 224 | 80.77 68 | 88.62 126 | 85.48 257 | 80.56 102 | 90.39 198 | 81.99 77 | 91.04 227 | 94.85 81 |
|
EI-MVSNet-Vis-set | | | 85.12 114 | 84.53 135 | 86.88 84 | 84.01 270 | 72.76 118 | 83.91 149 | 85.18 226 | 80.44 69 | 88.75 123 | 85.49 256 | 80.08 105 | 91.92 156 | 82.02 76 | 90.85 237 | 95.97 50 |
|
UniMVSNet (Re) | | | 86.87 81 | 86.98 86 | 86.55 89 | 93.11 64 | 68.48 157 | 83.80 153 | 92.87 62 | 80.37 70 | 89.61 109 | 91.81 143 | 77.72 123 | 94.18 66 | 75.00 149 | 98.53 17 | 96.99 33 |
|
CSCG | | | 86.26 95 | 86.47 95 | 85.60 112 | 90.87 124 | 74.26 110 | 87.98 79 | 91.85 92 | 80.35 71 | 89.54 113 | 88.01 224 | 79.09 111 | 92.13 151 | 75.51 145 | 95.06 136 | 90.41 205 |
|
PGM-MVS | | | 91.20 21 | 90.95 33 | 91.93 13 | 95.67 20 | 85.85 25 | 90.00 40 | 93.90 29 | 80.32 72 | 91.74 67 | 94.41 71 | 88.17 24 | 95.98 7 | 86.37 26 | 97.99 40 | 93.96 103 |
|
EI-MVSNet-UG-set | | | 85.04 116 | 84.44 137 | 86.85 85 | 83.87 273 | 72.52 121 | 83.82 151 | 85.15 227 | 80.27 73 | 88.75 123 | 85.45 260 | 79.95 107 | 91.90 157 | 81.92 78 | 90.80 238 | 96.13 44 |
|
XVG-OURS | | | 89.18 54 | 88.83 59 | 90.23 43 | 94.28 41 | 86.11 20 | 85.91 115 | 93.60 35 | 80.16 74 | 89.13 118 | 93.44 101 | 83.82 59 | 90.98 179 | 83.86 56 | 95.30 129 | 93.60 117 |
|
XVG-OURS-SEG-HR | | | 89.59 48 | 89.37 52 | 90.28 42 | 94.47 39 | 85.95 21 | 86.84 99 | 93.91 28 | 80.07 75 | 86.75 153 | 93.26 103 | 93.64 2 | 90.93 181 | 84.60 45 | 90.75 239 | 93.97 102 |
|
VDD-MVS | | | 84.23 140 | 84.58 134 | 83.20 172 | 91.17 118 | 65.16 179 | 83.25 173 | 84.97 232 | 79.79 76 | 87.18 145 | 94.27 76 | 74.77 162 | 90.89 184 | 69.24 192 | 96.54 83 | 93.55 121 |
|
CPTT-MVS | | | 89.39 51 | 88.98 57 | 90.63 36 | 95.09 30 | 86.95 10 | 92.09 23 | 92.30 79 | 79.74 77 | 87.50 142 | 92.38 126 | 81.42 94 | 93.28 118 | 83.07 64 | 97.24 64 | 91.67 174 |
|
XVG-ACMP-BASELINE | | | 89.98 38 | 89.84 45 | 90.41 39 | 94.91 34 | 84.50 41 | 89.49 56 | 93.98 25 | 79.68 78 | 92.09 59 | 93.89 95 | 83.80 60 | 93.10 126 | 82.67 71 | 98.04 35 | 93.64 115 |
|
TransMVSNet (Re) | | | 84.02 148 | 85.74 106 | 78.85 229 | 91.00 121 | 55.20 282 | 82.29 199 | 87.26 198 | 79.65 79 | 88.38 132 | 95.52 38 | 83.00 68 | 86.88 251 | 67.97 206 | 96.60 81 | 94.45 90 |
|
AllTest | | | 87.97 68 | 87.40 79 | 89.68 48 | 91.59 102 | 83.40 45 | 89.50 55 | 95.44 5 | 79.47 80 | 88.00 135 | 93.03 108 | 82.66 72 | 91.47 167 | 70.81 178 | 96.14 100 | 94.16 97 |
|
TestCases | | | | | 89.68 48 | 91.59 102 | 83.40 45 | | 95.44 5 | 79.47 80 | 88.00 135 | 93.03 108 | 82.66 72 | 91.47 167 | 70.81 178 | 96.14 100 | 94.16 97 |
|
HQP_MVS | | | 87.75 72 | 87.43 78 | 88.70 62 | 93.45 53 | 76.42 98 | 89.45 57 | 93.61 33 | 79.44 82 | 86.55 156 | 92.95 112 | 74.84 159 | 95.22 39 | 80.78 91 | 95.83 114 | 94.46 88 |
|
plane_prior2 | | | | | | | | 89.45 57 | | 79.44 82 | | | | | | | |
|
RPSCF | | | 88.00 67 | 86.93 88 | 91.22 27 | 90.08 138 | 89.30 6 | 89.68 49 | 91.11 124 | 79.26 84 | 89.68 102 | 94.81 60 | 82.44 75 | 87.74 243 | 76.54 141 | 88.74 262 | 96.61 39 |
|
ACMM | | 79.39 9 | 90.65 26 | 90.99 31 | 89.63 50 | 95.03 31 | 83.53 44 | 89.62 51 | 93.35 39 | 79.20 85 | 93.83 28 | 93.60 100 | 90.81 8 | 92.96 132 | 85.02 39 | 98.45 20 | 92.41 151 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
v13 | | | 87.31 75 | 88.10 66 | 84.94 118 | 88.84 156 | 63.75 190 | 87.85 83 | 91.47 107 | 79.12 86 | 93.72 29 | 95.82 28 | 75.20 153 | 93.58 96 | 84.76 43 | 96.16 98 | 97.48 16 |
|
CNLPA | | | 83.55 159 | 83.10 162 | 84.90 119 | 89.34 148 | 83.87 43 | 84.54 136 | 88.77 175 | 79.09 87 | 83.54 206 | 88.66 213 | 74.87 158 | 81.73 302 | 66.84 213 | 92.29 202 | 89.11 222 |
|
Baseline_NR-MVSNet | | | 84.00 149 | 85.90 104 | 78.29 239 | 91.47 110 | 53.44 292 | 82.29 199 | 87.00 208 | 79.06 88 | 89.55 111 | 95.72 31 | 77.20 129 | 86.14 270 | 72.30 172 | 98.51 18 | 95.28 72 |
|
ACMP | | 79.16 10 | 90.54 29 | 90.60 37 | 90.35 41 | 94.36 40 | 80.98 57 | 89.16 61 | 94.05 23 | 79.03 89 | 92.87 42 | 93.74 98 | 90.60 11 | 95.21 41 | 82.87 67 | 98.76 5 | 94.87 79 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
SD-MVS | | | 88.96 56 | 89.88 44 | 86.22 97 | 91.63 101 | 77.07 90 | 89.82 46 | 93.77 31 | 78.90 90 | 92.88 41 | 92.29 130 | 86.11 47 | 90.22 202 | 86.24 31 | 97.24 64 | 91.36 181 |
|
Vis-MVSNet | | | 86.86 82 | 86.58 93 | 87.72 75 | 92.09 90 | 77.43 86 | 87.35 90 | 92.09 84 | 78.87 91 | 84.27 198 | 94.05 85 | 78.35 118 | 93.65 86 | 80.54 96 | 91.58 213 | 92.08 162 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
OPM-MVS | | | 89.80 44 | 89.97 43 | 89.27 55 | 94.76 35 | 79.86 64 | 86.76 103 | 92.78 67 | 78.78 92 | 92.51 53 | 93.64 99 | 88.13 26 | 93.84 82 | 84.83 42 | 97.55 58 | 94.10 99 |
|
NCCC | | | 87.36 74 | 86.87 89 | 88.83 60 | 92.32 85 | 78.84 74 | 86.58 110 | 91.09 125 | 78.77 93 | 84.85 181 | 90.89 173 | 80.85 98 | 95.29 35 | 81.14 85 | 95.32 126 | 92.34 154 |
|
v12 | | | 87.15 78 | 87.91 68 | 84.84 121 | 88.69 159 | 63.52 193 | 87.58 86 | 91.46 108 | 78.74 94 | 93.57 32 | 95.66 32 | 74.94 157 | 93.57 97 | 84.50 47 | 96.08 103 | 97.43 17 |
|
Effi-MVS+ | | | 83.90 152 | 84.01 148 | 83.57 163 | 87.22 210 | 65.61 176 | 86.55 111 | 92.40 76 | 78.64 95 | 81.34 236 | 84.18 278 | 83.65 62 | 92.93 134 | 74.22 151 | 87.87 272 | 92.17 161 |
|
FMVSNet1 | | | 84.55 127 | 85.45 112 | 81.85 194 | 90.27 135 | 61.05 238 | 86.83 100 | 88.27 185 | 78.57 96 | 89.66 103 | 95.64 34 | 75.43 150 | 90.68 190 | 69.09 196 | 95.33 125 | 93.82 108 |
|
HSP-MVS | | | 88.63 60 | 87.84 70 | 91.02 29 | 95.76 16 | 86.14 19 | 92.75 13 | 91.01 127 | 78.43 97 | 89.16 117 | 92.25 132 | 72.03 210 | 96.36 2 | 88.21 9 | 90.93 234 | 90.55 202 |
|
API-MVS | | | 82.28 176 | 82.61 168 | 81.30 201 | 86.29 230 | 69.79 145 | 88.71 71 | 87.67 194 | 78.42 98 | 82.15 223 | 84.15 280 | 77.98 120 | 91.59 165 | 65.39 224 | 92.75 195 | 82.51 303 |
|
V9 | | | 86.96 79 | 87.70 73 | 84.74 125 | 88.52 164 | 63.27 199 | 87.31 91 | 91.45 110 | 78.28 99 | 93.43 33 | 95.45 39 | 74.59 165 | 93.57 97 | 84.23 51 | 96.01 106 | 97.38 18 |
|
HPM-MVS++ | | | 88.93 57 | 88.45 65 | 90.38 40 | 94.92 33 | 85.85 25 | 89.70 47 | 91.27 120 | 78.20 100 | 86.69 154 | 92.28 131 | 80.36 103 | 95.06 45 | 86.17 32 | 96.49 86 | 90.22 208 |
|
AdaColmap | | | 83.66 155 | 83.69 153 | 83.57 163 | 90.05 141 | 72.26 125 | 86.29 114 | 90.00 158 | 78.19 101 | 81.65 231 | 87.16 236 | 83.40 65 | 94.24 64 | 61.69 246 | 94.76 150 | 84.21 279 |
|
PAPM_NR | | | 83.23 163 | 83.19 161 | 83.33 170 | 90.90 123 | 65.98 173 | 88.19 77 | 90.78 129 | 78.13 102 | 80.87 241 | 87.92 228 | 73.49 184 | 92.42 146 | 70.07 186 | 88.40 263 | 91.60 176 |
|
v11 | | | 86.96 79 | 87.78 72 | 84.51 131 | 88.50 165 | 62.60 213 | 87.21 92 | 91.63 99 | 78.08 103 | 93.40 34 | 95.56 37 | 75.07 154 | 93.57 97 | 84.46 48 | 96.08 103 | 97.36 20 |
|
plane_prior3 | | | | | | | 76.85 93 | | | 77.79 104 | 86.55 156 | | | | | | |
|
V14 | | | 86.75 85 | 87.46 76 | 84.62 129 | 88.35 169 | 63.00 204 | 87.02 97 | 91.42 113 | 77.78 105 | 93.27 36 | 95.23 46 | 74.22 168 | 93.56 100 | 83.95 54 | 95.93 109 | 97.31 21 |
|
ACMMP_Plus | | | 90.65 26 | 91.07 30 | 89.42 53 | 95.93 14 | 79.54 68 | 89.95 43 | 93.68 32 | 77.65 106 | 91.97 63 | 94.89 54 | 88.38 18 | 95.45 30 | 89.27 3 | 97.87 45 | 93.27 123 |
|
MSDG | | | 80.06 206 | 79.99 204 | 80.25 213 | 83.91 272 | 68.04 160 | 77.51 277 | 89.19 172 | 77.65 106 | 81.94 225 | 83.45 286 | 76.37 144 | 86.31 267 | 63.31 236 | 86.59 283 | 86.41 250 |
|
MIMVSNet1 | | | 83.63 156 | 84.59 133 | 80.74 209 | 94.06 42 | 62.77 208 | 82.72 188 | 84.53 234 | 77.57 108 | 90.34 83 | 95.92 27 | 76.88 141 | 85.83 274 | 61.88 244 | 97.42 60 | 93.62 116 |
|
MVS_0304 | | | 84.88 120 | 83.96 150 | 87.64 78 | 87.43 201 | 74.83 106 | 84.18 140 | 93.30 43 | 77.48 109 | 77.39 278 | 88.46 215 | 74.53 167 | 95.74 18 | 78.09 125 | 94.75 151 | 92.36 153 |
|
view600 | | | 76.79 226 | 76.54 223 | 77.56 249 | 87.91 183 | 50.77 318 | 81.92 209 | 71.35 314 | 77.38 110 | 84.62 184 | 88.40 216 | 45.18 324 | 89.26 219 | 58.58 271 | 93.49 175 | 92.66 141 |
|
view800 | | | 76.79 226 | 76.54 223 | 77.56 249 | 87.91 183 | 50.77 318 | 81.92 209 | 71.35 314 | 77.38 110 | 84.62 184 | 88.40 216 | 45.18 324 | 89.26 219 | 58.58 271 | 93.49 175 | 92.66 141 |
|
conf0.05thres1000 | | | 76.79 226 | 76.54 223 | 77.56 249 | 87.91 183 | 50.77 318 | 81.92 209 | 71.35 314 | 77.38 110 | 84.62 184 | 88.40 216 | 45.18 324 | 89.26 219 | 58.58 271 | 93.49 175 | 92.66 141 |
|
tfpn | | | 76.79 226 | 76.54 223 | 77.56 249 | 87.91 183 | 50.77 318 | 81.92 209 | 71.35 314 | 77.38 110 | 84.62 184 | 88.40 216 | 45.18 324 | 89.26 219 | 58.58 271 | 93.49 175 | 92.66 141 |
|
v15 | | | 86.56 88 | 87.25 80 | 84.51 131 | 88.15 176 | 62.72 209 | 86.72 107 | 91.40 115 | 77.38 110 | 93.11 38 | 95.00 51 | 73.93 173 | 93.55 101 | 83.67 58 | 95.86 113 | 97.26 22 |
|
FC-MVSNet-test | | | 85.93 105 | 87.05 84 | 82.58 182 | 92.25 86 | 56.44 272 | 85.75 118 | 93.09 52 | 77.33 115 | 91.94 64 | 94.65 62 | 74.78 161 | 93.41 112 | 75.11 148 | 98.58 15 | 97.88 9 |
|
CNVR-MVS | | | 87.81 71 | 87.68 74 | 88.21 67 | 92.87 69 | 77.30 89 | 85.25 124 | 91.23 121 | 77.31 116 | 87.07 149 | 91.47 151 | 82.94 69 | 94.71 53 | 84.67 44 | 96.27 95 | 92.62 147 |
|
CANet | | | 83.79 153 | 82.85 164 | 86.63 87 | 86.17 235 | 72.21 127 | 83.76 155 | 91.43 111 | 77.24 117 | 74.39 301 | 87.45 234 | 75.36 151 | 95.42 31 | 77.03 136 | 92.83 194 | 92.25 159 |
|
v17 | | | 86.32 93 | 86.95 87 | 84.44 135 | 88.00 179 | 62.62 212 | 86.74 105 | 91.48 104 | 77.17 118 | 92.74 48 | 94.56 63 | 73.74 177 | 93.53 102 | 83.27 61 | 94.87 144 | 97.18 26 |
|
v16 | | | 86.24 96 | 86.85 90 | 84.43 136 | 87.96 181 | 62.59 214 | 86.73 106 | 91.48 104 | 77.17 118 | 92.67 51 | 94.55 64 | 73.63 178 | 93.52 103 | 83.26 62 | 94.16 159 | 97.17 27 |
|
UGNet | | | 82.78 169 | 81.64 182 | 86.21 99 | 86.20 234 | 76.24 101 | 86.86 98 | 85.68 219 | 77.07 120 | 73.76 304 | 92.82 116 | 69.64 218 | 91.82 161 | 69.04 197 | 93.69 172 | 90.56 201 |
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 |
#test# | | | 90.49 31 | 90.31 42 | 91.02 29 | 95.43 25 | 84.66 39 | 90.65 36 | 93.29 45 | 77.00 121 | 91.47 70 | 93.96 90 | 88.35 20 | 95.56 24 | 84.88 40 | 97.74 51 | 92.85 133 |
|
tfpnnormal | | | 81.79 183 | 82.95 163 | 78.31 238 | 88.93 155 | 55.40 278 | 80.83 232 | 82.85 240 | 76.81 122 | 85.90 168 | 94.14 82 | 74.58 166 | 86.51 264 | 66.82 214 | 95.68 120 | 93.01 130 |
|
v8 | | | 86.22 98 | 86.83 91 | 84.36 139 | 87.82 187 | 62.35 218 | 86.42 112 | 91.33 118 | 76.78 123 | 92.73 49 | 94.48 68 | 73.41 185 | 93.72 84 | 83.10 63 | 95.41 123 | 97.01 32 |
|
v18 | | | 85.99 103 | 86.55 94 | 84.30 141 | 87.73 193 | 62.29 222 | 86.40 113 | 91.49 103 | 76.64 124 | 92.40 56 | 94.20 80 | 73.28 189 | 93.52 103 | 82.87 67 | 93.99 163 | 97.09 29 |
|
LCM-MVSNet-Re | | | 83.48 160 | 85.06 116 | 78.75 231 | 85.94 243 | 55.75 277 | 80.05 237 | 94.27 13 | 76.47 125 | 96.09 5 | 94.54 66 | 83.31 66 | 89.75 212 | 59.95 258 | 94.89 141 | 90.75 195 |
|
VPA-MVSNet | | | 83.47 161 | 84.73 123 | 79.69 221 | 90.29 134 | 57.52 263 | 81.30 223 | 88.69 177 | 76.29 126 | 87.58 140 | 94.44 69 | 80.60 101 | 87.20 247 | 66.60 215 | 96.82 76 | 94.34 93 |
|
EPNet | | | 80.37 200 | 78.41 212 | 86.23 96 | 76.75 327 | 73.28 115 | 87.18 94 | 77.45 268 | 76.24 127 | 68.14 328 | 88.93 209 | 65.41 236 | 93.85 80 | 69.47 190 | 96.12 102 | 91.55 178 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
EI-MVSNet | | | 82.61 171 | 82.42 173 | 83.20 172 | 83.25 277 | 63.66 191 | 83.50 165 | 85.07 228 | 76.06 128 | 86.55 156 | 85.10 265 | 73.41 185 | 90.25 199 | 78.15 124 | 90.67 241 | 95.68 59 |
|
IterMVS-LS | | | 84.73 123 | 84.98 119 | 83.96 150 | 87.35 202 | 63.66 191 | 83.25 173 | 89.88 161 | 76.06 128 | 89.62 107 | 92.37 129 | 73.40 187 | 92.52 145 | 78.16 123 | 94.77 149 | 95.69 58 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
OMC-MVS | | | 88.19 65 | 87.52 75 | 90.19 44 | 91.94 96 | 81.68 53 | 87.49 89 | 93.17 50 | 76.02 130 | 88.64 125 | 91.22 155 | 84.24 58 | 93.37 113 | 77.97 126 | 97.03 69 | 95.52 66 |
|
0601test | | | 78.71 212 | 78.51 211 | 79.32 226 | 84.32 263 | 58.84 256 | 78.38 267 | 85.33 223 | 75.99 131 | 82.49 218 | 86.57 241 | 58.01 267 | 90.02 210 | 62.74 238 | 92.73 196 | 89.10 223 |
|
MSLP-MVS++ | | | 85.00 118 | 86.03 103 | 81.90 191 | 91.84 98 | 71.56 138 | 86.75 104 | 93.02 58 | 75.95 132 | 87.12 146 | 89.39 203 | 77.98 120 | 89.40 217 | 77.46 129 | 94.78 147 | 84.75 272 |
|
plane_prior | | | | | | | 76.42 98 | 87.15 95 | | 75.94 133 | | | | | | 95.03 137 | |
|
FIs | | | 85.35 112 | 86.27 98 | 82.60 181 | 91.86 97 | 57.31 264 | 85.10 126 | 93.05 54 | 75.83 134 | 91.02 76 | 93.97 88 | 73.57 182 | 92.91 136 | 73.97 155 | 98.02 38 | 97.58 14 |
|
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 40 | 94.96 52 | 88.36 19 | 95.01 46 | 90.70 2 | 98.40 21 | 95.09 77 |
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
tfpn111 | | | 76.03 238 | 75.53 236 | 77.53 253 | 87.27 206 | 51.88 304 | 81.07 226 | 73.26 295 | 75.68 136 | 83.25 208 | 86.37 245 | 45.54 314 | 89.38 218 | 55.07 296 | 92.26 204 | 91.34 182 |
|
conf200view11 | | | 75.62 242 | 75.05 240 | 77.34 255 | 87.27 206 | 51.88 304 | 81.07 226 | 73.26 295 | 75.68 136 | 83.25 208 | 86.37 245 | 45.54 314 | 88.80 227 | 51.98 309 | 90.99 229 | 91.34 182 |
|
thres100view900 | | | 75.45 243 | 75.05 240 | 76.66 264 | 87.27 206 | 51.88 304 | 81.07 226 | 73.26 295 | 75.68 136 | 83.25 208 | 86.37 245 | 45.54 314 | 88.80 227 | 51.98 309 | 90.99 229 | 89.31 219 |
|
3Dnovator | | 80.37 7 | 84.80 122 | 84.71 126 | 85.06 117 | 86.36 227 | 74.71 107 | 88.77 70 | 90.00 158 | 75.65 139 | 84.96 177 | 93.17 105 | 74.06 170 | 91.19 174 | 78.28 122 | 91.09 225 | 89.29 221 |
|
pm-mvs1 | | | 83.69 154 | 84.95 120 | 79.91 217 | 90.04 142 | 59.66 250 | 82.43 194 | 87.44 195 | 75.52 140 | 87.85 137 | 95.26 44 | 81.25 96 | 85.65 276 | 68.74 200 | 96.04 105 | 94.42 91 |
|
test_prior3 | | | 86.31 94 | 86.31 97 | 86.32 93 | 90.59 129 | 71.99 130 | 83.37 168 | 92.85 63 | 75.43 141 | 84.58 188 | 91.57 147 | 81.92 88 | 94.17 68 | 79.54 110 | 96.97 70 | 92.80 136 |
|
test_prior2 | | | | | | | | 83.37 168 | | 75.43 141 | 84.58 188 | 91.57 147 | 81.92 88 | | 79.54 110 | 96.97 70 | |
|
v10 | | | 86.54 89 | 87.10 82 | 84.84 121 | 88.16 175 | 63.28 198 | 86.64 109 | 92.20 82 | 75.42 143 | 92.81 47 | 94.50 67 | 74.05 171 | 94.06 72 | 83.88 55 | 96.28 93 | 97.17 27 |
|
SMA-MVS | | | 90.31 32 | 90.48 40 | 89.83 47 | 95.31 27 | 79.52 69 | 90.98 34 | 93.24 48 | 75.37 144 | 92.84 44 | 95.28 42 | 85.58 50 | 96.09 5 | 87.92 11 | 97.76 48 | 93.88 105 |
|
thres600view7 | | | 75.97 239 | 75.35 239 | 77.85 247 | 87.01 217 | 51.84 308 | 80.45 234 | 73.26 295 | 75.20 145 | 83.10 212 | 86.31 250 | 45.54 314 | 89.05 223 | 55.03 297 | 92.24 205 | 92.66 141 |
|
wuyk23d | | | 75.13 245 | 79.30 206 | 62.63 329 | 75.56 335 | 75.18 105 | 80.89 230 | 73.10 299 | 75.06 146 | 94.76 14 | 95.32 41 | 87.73 31 | 52.85 359 | 34.16 353 | 97.11 67 | 59.85 354 |
|
RPMNet | | | 76.06 237 | 75.79 232 | 76.85 261 | 79.58 304 | 62.64 210 | 82.58 190 | 71.75 310 | 74.80 147 | 75.72 290 | 92.59 121 | 48.69 299 | 84.07 289 | 73.48 161 | 82.91 314 | 83.85 283 |
|
TSAR-MVS + GP. | | | 83.95 150 | 82.69 166 | 87.72 75 | 89.27 149 | 81.45 55 | 83.72 156 | 81.58 251 | 74.73 148 | 85.66 170 | 86.06 252 | 72.56 204 | 92.69 141 | 75.44 146 | 95.21 130 | 89.01 227 |
|
diffmvs1 | | | 82.95 168 | 83.63 154 | 80.90 207 | 80.05 303 | 61.05 238 | 82.98 179 | 89.93 160 | 74.72 149 | 82.37 219 | 92.93 114 | 76.47 143 | 88.80 227 | 81.73 80 | 91.54 214 | 92.85 133 |
|
wuykxyi23d | | | 88.46 62 | 88.80 61 | 87.44 81 | 90.96 122 | 93.03 1 | 85.85 117 | 81.96 246 | 74.58 150 | 98.58 2 | 97.29 4 | 87.73 31 | 87.31 246 | 82.84 69 | 99.41 1 | 81.99 309 |
|
Effi-MVS+-dtu | | | 85.82 106 | 83.38 157 | 93.14 3 | 87.13 212 | 91.15 3 | 87.70 85 | 88.42 180 | 74.57 151 | 83.56 205 | 85.65 254 | 78.49 116 | 94.21 65 | 72.04 174 | 92.88 193 | 94.05 100 |
|
mvs-test1 | | | 84.55 127 | 82.12 176 | 91.84 17 | 87.13 212 | 89.54 5 | 85.05 127 | 88.42 180 | 74.57 151 | 80.60 250 | 82.98 291 | 78.49 116 | 93.98 75 | 72.04 174 | 89.77 251 | 92.00 163 |
|
VNet | | | 79.31 208 | 80.27 199 | 76.44 265 | 87.92 182 | 53.95 287 | 75.58 294 | 84.35 235 | 74.39 153 | 82.23 221 | 90.72 178 | 72.84 197 | 84.39 287 | 60.38 257 | 93.98 164 | 90.97 187 |
|
BH-RMVSNet | | | 80.53 198 | 80.22 200 | 81.49 199 | 87.19 211 | 66.21 172 | 77.79 274 | 86.23 213 | 74.21 154 | 83.69 201 | 88.50 214 | 73.25 193 | 90.75 187 | 63.18 237 | 87.90 271 | 87.52 240 |
|
nrg030 | | | 87.85 70 | 88.49 64 | 85.91 105 | 90.07 139 | 69.73 146 | 87.86 81 | 94.20 17 | 74.04 155 | 92.70 50 | 94.66 61 | 85.88 49 | 91.50 166 | 79.72 107 | 97.32 62 | 96.50 41 |
|
Vis-MVSNet (Re-imp) | | | 77.82 216 | 77.79 215 | 77.92 245 | 88.82 157 | 51.29 312 | 83.28 171 | 71.97 306 | 74.04 155 | 82.23 221 | 89.78 197 | 57.38 273 | 89.41 216 | 57.22 282 | 95.41 123 | 93.05 129 |
|
testdata1 | | | | | | | | 79.62 243 | | 73.95 157 | | | | | | | |
|
Patchmtry | | | 76.56 233 | 77.46 216 | 73.83 286 | 79.37 308 | 46.60 339 | 82.41 195 | 76.90 271 | 73.81 158 | 85.56 173 | 92.38 126 | 48.07 301 | 83.98 291 | 63.36 235 | 95.31 128 | 90.92 189 |
|
PatchT | | | 70.52 287 | 72.76 267 | 63.79 328 | 79.38 307 | 33.53 358 | 77.63 275 | 65.37 344 | 73.61 159 | 71.77 313 | 92.79 119 | 44.38 331 | 75.65 320 | 64.53 230 | 85.37 295 | 82.18 307 |
|
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 | 73.53 160 | 89.71 101 | 94.82 57 | 85.09 51 | 95.77 17 | 84.17 52 | 98.03 37 | 93.26 124 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
diffmvs | | | 81.78 184 | 82.36 174 | 80.02 216 | 79.06 311 | 59.93 248 | 83.30 170 | 88.41 182 | 73.47 161 | 78.38 270 | 92.05 135 | 75.85 148 | 88.38 237 | 80.73 93 | 89.98 250 | 91.76 171 |
|
VPNet | | | 80.25 202 | 81.68 181 | 75.94 272 | 92.46 79 | 47.98 337 | 76.70 282 | 81.67 250 | 73.45 162 | 84.87 180 | 92.82 116 | 74.66 164 | 86.51 264 | 61.66 247 | 96.85 73 | 93.33 122 |
|
canonicalmvs | | | 85.50 110 | 86.14 101 | 83.58 162 | 87.97 180 | 67.13 165 | 87.55 87 | 94.32 12 | 73.44 163 | 88.47 129 | 87.54 233 | 86.45 43 | 91.06 178 | 75.76 144 | 93.76 170 | 92.54 149 |
|
MVS_111021_HR | | | 84.63 124 | 84.34 144 | 85.49 113 | 90.18 137 | 75.86 102 | 79.23 260 | 87.13 203 | 73.35 164 | 85.56 173 | 89.34 204 | 83.60 63 | 90.50 195 | 76.64 140 | 94.05 162 | 90.09 213 |
|
tfpn200view9 | | | 74.86 250 | 74.23 248 | 76.74 263 | 86.24 231 | 52.12 301 | 79.24 257 | 73.87 288 | 73.34 165 | 81.82 228 | 84.60 275 | 46.02 308 | 88.80 227 | 51.98 309 | 90.99 229 | 89.31 219 |
|
thres400 | | | 75.14 244 | 74.23 248 | 77.86 246 | 86.24 231 | 52.12 301 | 79.24 257 | 73.87 288 | 73.34 165 | 81.82 228 | 84.60 275 | 46.02 308 | 88.80 227 | 51.98 309 | 90.99 229 | 92.66 141 |
|
HQP-NCC | | | | | | 91.19 115 | | 84.77 128 | | 73.30 167 | 80.55 253 | | | | | | |
|
ACMP_Plane | | | | | | 91.19 115 | | 84.77 128 | | 73.30 167 | 80.55 253 | | | | | | |
|
HQP-MVS | | | 84.61 125 | 84.06 147 | 86.27 95 | 91.19 115 | 70.66 142 | 84.77 128 | 92.68 69 | 73.30 167 | 80.55 253 | 90.17 193 | 72.10 206 | 94.61 55 | 77.30 132 | 94.47 156 | 93.56 119 |
|
alignmvs | | | 83.94 151 | 83.98 149 | 83.80 152 | 87.80 191 | 67.88 162 | 84.54 136 | 91.42 113 | 73.27 170 | 88.41 131 | 87.96 225 | 72.33 205 | 90.83 185 | 76.02 143 | 94.11 160 | 92.69 140 |
|
F-COLMAP | | | 84.97 119 | 83.42 156 | 89.63 50 | 92.39 81 | 83.40 45 | 88.83 68 | 91.92 91 | 73.19 171 | 80.18 258 | 89.15 206 | 77.04 133 | 93.28 118 | 65.82 222 | 92.28 203 | 92.21 160 |
|
MDA-MVSNet-bldmvs | | | 77.47 219 | 76.90 220 | 79.16 227 | 79.03 312 | 64.59 182 | 66.58 333 | 75.67 278 | 73.15 172 | 88.86 120 | 88.99 208 | 66.94 229 | 81.23 303 | 64.71 226 | 88.22 269 | 91.64 175 |
|
PHI-MVS | | | 86.38 92 | 85.81 105 | 88.08 69 | 88.44 168 | 77.34 87 | 89.35 59 | 93.05 54 | 73.15 172 | 84.76 182 | 87.70 230 | 78.87 113 | 94.18 66 | 80.67 94 | 96.29 92 | 92.73 138 |
|
Fast-Effi-MVS+-dtu | | | 82.54 173 | 81.41 185 | 85.90 106 | 85.60 244 | 76.53 97 | 83.07 177 | 89.62 167 | 73.02 174 | 79.11 266 | 83.51 284 | 80.74 100 | 90.24 201 | 68.76 199 | 89.29 254 | 90.94 188 |
|
v148 | | | 82.31 175 | 82.48 172 | 81.81 197 | 85.59 245 | 59.66 250 | 81.47 219 | 86.02 216 | 72.85 175 | 88.05 134 | 90.65 182 | 70.73 216 | 90.91 183 | 75.15 147 | 91.79 209 | 94.87 79 |
|
BH-untuned | | | 80.96 193 | 80.99 191 | 80.84 208 | 88.55 163 | 68.23 158 | 80.33 235 | 88.46 179 | 72.79 176 | 86.55 156 | 86.76 240 | 74.72 163 | 91.77 162 | 61.79 245 | 88.99 258 | 82.52 302 |
|
MVS_111021_LR | | | 84.28 138 | 83.76 152 | 85.83 109 | 89.23 150 | 83.07 48 | 80.99 229 | 83.56 236 | 72.71 177 | 86.07 164 | 89.07 207 | 81.75 91 | 86.19 269 | 77.11 135 | 93.36 179 | 88.24 230 |
|
EG-PatchMatch MVS | | | 84.08 146 | 84.11 146 | 83.98 149 | 92.22 88 | 72.61 120 | 82.20 205 | 87.02 207 | 72.63 178 | 88.86 120 | 91.02 167 | 78.52 115 | 91.11 176 | 73.41 162 | 91.09 225 | 88.21 231 |
|
semantic-postprocess | | | | | 84.34 140 | 83.93 271 | 69.66 147 | | 81.09 253 | 72.43 179 | 86.47 162 | 90.19 191 | 57.56 272 | 93.15 125 | 77.45 130 | 86.39 286 | 90.22 208 |
|
GBi-Net | | | 82.02 180 | 82.07 177 | 81.85 194 | 86.38 224 | 61.05 238 | 86.83 100 | 88.27 185 | 72.43 179 | 86.00 165 | 95.64 34 | 63.78 241 | 90.68 190 | 65.95 218 | 93.34 180 | 93.82 108 |
|
test1 | | | 82.02 180 | 82.07 177 | 81.85 194 | 86.38 224 | 61.05 238 | 86.83 100 | 88.27 185 | 72.43 179 | 86.00 165 | 95.64 34 | 63.78 241 | 90.68 190 | 65.95 218 | 93.34 180 | 93.82 108 |
|
FMVSNet2 | | | 81.31 187 | 81.61 183 | 80.41 212 | 86.38 224 | 58.75 258 | 83.93 148 | 86.58 211 | 72.43 179 | 87.65 139 | 92.98 110 | 63.78 241 | 90.22 202 | 66.86 211 | 93.92 165 | 92.27 157 |
|
tfpn1000 | | | 73.63 265 | 73.58 253 | 73.79 287 | 85.46 248 | 50.31 324 | 79.99 239 | 68.18 333 | 72.33 183 | 80.66 249 | 83.05 289 | 39.80 349 | 86.74 262 | 60.96 253 | 91.78 210 | 84.32 277 |
|
v1neww | | | 84.43 131 | 84.66 129 | 83.75 155 | 87.81 188 | 62.34 219 | 83.59 158 | 90.27 150 | 72.33 183 | 89.93 94 | 91.22 155 | 73.28 189 | 93.29 115 | 80.25 101 | 93.25 184 | 95.62 61 |
|
v7new | | | 84.43 131 | 84.66 129 | 83.75 155 | 87.81 188 | 62.34 219 | 83.59 158 | 90.27 150 | 72.33 183 | 89.93 94 | 91.22 155 | 73.28 189 | 93.29 115 | 80.25 101 | 93.25 184 | 95.62 61 |
|
v6 | | | 84.43 131 | 84.66 129 | 83.75 155 | 87.81 188 | 62.34 219 | 83.59 158 | 90.26 152 | 72.33 183 | 89.94 92 | 91.19 159 | 73.30 188 | 93.29 115 | 80.26 100 | 93.26 183 | 95.62 61 |
|
v2v482 | | | 84.09 145 | 84.24 145 | 83.62 161 | 87.13 212 | 61.40 232 | 82.71 189 | 89.71 165 | 72.19 187 | 89.55 111 | 91.41 152 | 70.70 217 | 93.20 120 | 81.02 86 | 93.76 170 | 96.25 42 |
|
DP-MVS Recon | | | 84.05 147 | 83.22 159 | 86.52 90 | 91.73 100 | 75.27 104 | 83.23 175 | 92.40 76 | 72.04 188 | 82.04 224 | 88.33 220 | 77.91 122 | 93.95 78 | 66.17 217 | 95.12 134 | 90.34 207 |
|
conf0.01 | | | 74.17 256 | 73.53 255 | 76.08 270 | 86.13 236 | 50.06 327 | 79.45 248 | 68.54 327 | 72.01 189 | 80.76 243 | 82.50 301 | 41.39 338 | 86.83 253 | 59.66 261 | 91.36 215 | 91.34 182 |
|
conf0.002 | | | 74.17 256 | 73.53 255 | 76.08 270 | 86.13 236 | 50.06 327 | 79.45 248 | 68.54 327 | 72.01 189 | 80.76 243 | 82.50 301 | 41.39 338 | 86.83 253 | 59.66 261 | 91.36 215 | 91.34 182 |
|
thresconf0.02 | | | 73.65 261 | 73.53 255 | 73.98 281 | 86.13 236 | 50.06 327 | 79.45 248 | 68.54 327 | 72.01 189 | 80.76 243 | 82.50 301 | 41.39 338 | 86.83 253 | 59.66 261 | 91.36 215 | 85.06 265 |
|
tfpn_n400 | | | 73.65 261 | 73.53 255 | 73.98 281 | 86.13 236 | 50.06 327 | 79.45 248 | 68.54 327 | 72.01 189 | 80.76 243 | 82.50 301 | 41.39 338 | 86.83 253 | 59.66 261 | 91.36 215 | 85.06 265 |
|
tfpnconf | | | 73.65 261 | 73.53 255 | 73.98 281 | 86.13 236 | 50.06 327 | 79.45 248 | 68.54 327 | 72.01 189 | 80.76 243 | 82.50 301 | 41.39 338 | 86.83 253 | 59.66 261 | 91.36 215 | 85.06 265 |
|
tfpnview11 | | | 73.65 261 | 73.53 255 | 73.98 281 | 86.13 236 | 50.06 327 | 79.45 248 | 68.54 327 | 72.01 189 | 80.76 243 | 82.50 301 | 41.39 338 | 86.83 253 | 59.66 261 | 91.36 215 | 85.06 265 |
|
MG-MVS | | | 80.32 201 | 80.94 192 | 78.47 237 | 88.18 173 | 52.62 299 | 82.29 199 | 85.01 231 | 72.01 189 | 79.24 265 | 92.54 124 | 69.36 219 | 93.36 114 | 70.65 182 | 89.19 257 | 89.45 216 |
|
FPMVS | | | 72.29 276 | 72.00 275 | 73.14 292 | 88.63 162 | 85.00 32 | 74.65 301 | 67.39 336 | 71.94 196 | 77.80 275 | 87.66 231 | 50.48 295 | 75.83 319 | 49.95 316 | 79.51 328 | 58.58 356 |
|
v1141 | | | 84.16 142 | 84.38 140 | 83.52 165 | 87.32 204 | 61.70 228 | 82.79 185 | 89.74 162 | 71.90 197 | 89.64 104 | 91.12 162 | 72.68 201 | 93.10 126 | 80.39 99 | 93.80 168 | 95.75 55 |
|
divwei89l23v2f112 | | | 84.16 142 | 84.38 140 | 83.52 165 | 87.32 204 | 61.70 228 | 82.79 185 | 89.74 162 | 71.90 197 | 89.64 104 | 91.12 162 | 72.68 201 | 93.10 126 | 80.40 97 | 93.81 167 | 95.75 55 |
|
v1 | | | 84.16 142 | 84.38 140 | 83.52 165 | 87.33 203 | 61.71 226 | 82.79 185 | 89.73 164 | 71.89 199 | 89.64 104 | 91.11 164 | 72.72 198 | 93.10 126 | 80.40 97 | 93.79 169 | 95.75 55 |
|
MVSFormer | | | 82.23 177 | 81.57 184 | 84.19 146 | 85.54 246 | 69.26 151 | 91.98 25 | 90.08 155 | 71.54 200 | 76.23 285 | 85.07 267 | 58.69 264 | 94.27 61 | 86.26 28 | 88.77 260 | 89.03 225 |
|
test_djsdf | | | 89.62 47 | 89.01 55 | 91.45 21 | 92.36 82 | 82.98 49 | 91.98 25 | 90.08 155 | 71.54 200 | 94.28 22 | 96.54 13 | 81.57 92 | 94.27 61 | 86.26 28 | 96.49 86 | 97.09 29 |
|
TinyColmap | | | 81.25 190 | 82.34 175 | 77.99 244 | 85.33 249 | 60.68 243 | 82.32 198 | 88.33 183 | 71.26 202 | 86.97 151 | 92.22 134 | 77.10 132 | 86.98 250 | 62.37 239 | 95.17 132 | 86.31 252 |
|
MVS_Test | | | 82.47 174 | 83.22 159 | 80.22 214 | 82.62 283 | 57.75 262 | 82.54 193 | 91.96 90 | 71.16 203 | 82.89 215 | 92.52 125 | 77.41 127 | 90.50 195 | 80.04 104 | 87.84 273 | 92.40 152 |
|
v7 | | | 84.81 121 | 85.00 118 | 84.23 142 | 88.15 176 | 63.27 199 | 83.79 154 | 91.39 116 | 71.10 204 | 90.07 86 | 91.28 153 | 74.04 172 | 93.63 88 | 81.48 82 | 93.67 173 | 95.79 53 |
|
DELS-MVS | | | 81.44 186 | 81.25 187 | 82.03 189 | 84.27 264 | 62.87 207 | 76.47 287 | 92.49 75 | 70.97 205 | 81.64 232 | 83.83 281 | 75.03 155 | 92.70 140 | 74.29 150 | 92.22 207 | 90.51 203 |
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 |
PS-MVSNAJss | | | 88.31 64 | 87.90 69 | 89.56 52 | 93.31 58 | 77.96 80 | 87.94 80 | 91.97 89 | 70.73 206 | 94.19 23 | 96.67 11 | 76.94 135 | 94.57 57 | 83.07 64 | 96.28 93 | 96.15 43 |
|
DeepC-MVS_fast | | 80.27 8 | 86.23 97 | 85.65 109 | 87.96 74 | 91.30 112 | 76.92 91 | 87.19 93 | 91.99 88 | 70.56 207 | 84.96 177 | 90.69 179 | 80.01 106 | 95.14 42 | 78.37 119 | 95.78 116 | 91.82 169 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
test20.03 | | | 73.75 260 | 74.59 245 | 71.22 303 | 81.11 293 | 51.12 314 | 70.15 320 | 72.10 305 | 70.42 208 | 80.28 257 | 91.50 150 | 64.21 238 | 74.72 323 | 46.96 332 | 94.58 154 | 87.82 239 |
|
JIA-IIPM | | | 69.41 298 | 66.64 308 | 77.70 248 | 73.19 350 | 71.24 139 | 75.67 292 | 65.56 343 | 70.42 208 | 65.18 340 | 92.97 111 | 33.64 356 | 83.06 295 | 53.52 304 | 69.61 353 | 78.79 332 |
|
v1144 | | | 84.54 129 | 84.72 125 | 84.00 148 | 87.67 195 | 62.55 215 | 82.97 180 | 90.93 128 | 70.32 210 | 89.80 99 | 90.99 168 | 73.50 183 | 93.48 107 | 81.69 81 | 94.65 153 | 95.97 50 |
|
DeepPCF-MVS | | 81.24 5 | 87.28 76 | 86.21 100 | 90.49 38 | 91.48 109 | 84.90 34 | 83.41 167 | 92.38 78 | 70.25 211 | 89.35 115 | 90.68 180 | 82.85 70 | 94.57 57 | 79.55 109 | 95.95 108 | 92.00 163 |
|
thres200 | | | 72.34 275 | 71.55 280 | 74.70 279 | 83.48 274 | 51.60 309 | 75.02 298 | 73.71 291 | 70.14 212 | 78.56 268 | 80.57 319 | 46.20 306 | 88.20 240 | 46.99 331 | 89.29 254 | 84.32 277 |
|
mvs_tets | | | 89.78 45 | 89.27 53 | 91.30 24 | 93.51 52 | 84.79 36 | 89.89 45 | 90.63 133 | 70.00 213 | 94.55 17 | 96.67 11 | 87.94 29 | 93.59 93 | 84.27 50 | 95.97 107 | 95.52 66 |
|
anonymousdsp | | | 89.73 46 | 88.88 58 | 92.27 7 | 89.82 144 | 86.67 12 | 90.51 37 | 90.20 154 | 69.87 214 | 95.06 13 | 96.14 23 | 84.28 57 | 93.07 131 | 87.68 14 | 96.34 91 | 97.09 29 |
|
PM-MVS | | | 80.20 204 | 79.00 207 | 83.78 154 | 88.17 174 | 86.66 13 | 81.31 221 | 66.81 342 | 69.64 215 | 88.33 133 | 90.19 191 | 64.58 237 | 83.63 294 | 71.99 176 | 90.03 248 | 81.06 328 |
|
V42 | | | 83.47 161 | 83.37 158 | 83.75 155 | 83.16 279 | 63.33 197 | 81.31 221 | 90.23 153 | 69.51 216 | 90.91 79 | 90.81 176 | 74.16 169 | 92.29 149 | 80.06 103 | 90.22 247 | 95.62 61 |
|
jajsoiax | | | 89.41 50 | 88.81 60 | 91.19 28 | 93.38 56 | 84.72 37 | 89.70 47 | 90.29 149 | 69.27 217 | 94.39 19 | 96.38 15 | 86.02 48 | 93.52 103 | 83.96 53 | 95.92 110 | 95.34 69 |
|
tfpn_ndepth | | | 72.54 272 | 72.30 273 | 73.24 290 | 84.81 255 | 51.42 310 | 79.24 257 | 70.49 320 | 69.26 218 | 78.48 269 | 79.80 325 | 40.16 348 | 86.77 260 | 58.08 280 | 90.43 246 | 81.53 319 |
|
TAPA-MVS | | 77.73 12 | 85.71 109 | 84.83 122 | 88.37 65 | 88.78 158 | 79.72 65 | 87.15 95 | 93.50 36 | 69.17 219 | 85.80 169 | 89.56 201 | 80.76 99 | 92.13 151 | 73.21 167 | 95.51 121 | 93.25 125 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
CANet_DTU | | | 77.81 217 | 77.05 218 | 80.09 215 | 81.37 290 | 59.90 249 | 83.26 172 | 88.29 184 | 69.16 220 | 67.83 331 | 83.72 282 | 60.93 249 | 89.47 213 | 69.22 194 | 89.70 252 | 90.88 191 |
|
v1192 | | | 84.57 126 | 84.69 127 | 84.21 143 | 87.75 192 | 62.88 206 | 83.02 178 | 91.43 111 | 69.08 221 | 89.98 91 | 90.89 173 | 72.70 200 | 93.62 92 | 82.41 72 | 94.97 139 | 96.13 44 |
|
FMVSNet3 | | | 78.80 210 | 78.55 210 | 79.57 223 | 82.89 281 | 56.89 269 | 81.76 213 | 85.77 218 | 69.04 222 | 86.00 165 | 90.44 186 | 51.75 292 | 90.09 208 | 65.95 218 | 93.34 180 | 91.72 172 |
|
ab-mvs | | | 79.67 207 | 80.56 195 | 76.99 257 | 88.48 166 | 56.93 267 | 84.70 131 | 86.06 215 | 68.95 223 | 80.78 242 | 93.08 106 | 75.30 152 | 84.62 285 | 56.78 284 | 90.90 235 | 89.43 218 |
|
GA-MVS | | | 75.83 240 | 74.61 243 | 79.48 225 | 81.87 286 | 59.25 254 | 73.42 309 | 82.88 239 | 68.68 224 | 79.75 259 | 81.80 312 | 50.62 294 | 89.46 214 | 66.85 212 | 85.64 292 | 89.72 214 |
|
CLD-MVS | | | 83.18 164 | 82.64 167 | 84.79 123 | 89.05 152 | 67.82 163 | 77.93 272 | 92.52 74 | 68.33 225 | 85.07 176 | 81.54 315 | 82.06 82 | 92.96 132 | 69.35 191 | 97.91 43 | 93.57 118 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
PLC | | 73.85 16 | 82.09 179 | 80.31 198 | 87.45 80 | 90.86 125 | 80.29 60 | 85.88 116 | 90.65 132 | 68.17 226 | 76.32 284 | 86.33 248 | 73.12 194 | 92.61 144 | 61.40 250 | 90.02 249 | 89.44 217 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
Fast-Effi-MVS+ | | | 81.04 192 | 80.57 194 | 82.46 186 | 87.50 199 | 63.22 201 | 78.37 268 | 89.63 166 | 68.01 227 | 81.87 226 | 82.08 310 | 82.31 77 | 92.65 143 | 67.10 209 | 88.30 268 | 91.51 179 |
|
LF4IMVS | | | 82.75 170 | 81.93 180 | 85.19 115 | 82.08 284 | 80.15 61 | 85.53 121 | 88.76 176 | 68.01 227 | 85.58 172 | 87.75 229 | 71.80 211 | 86.85 252 | 74.02 154 | 93.87 166 | 88.58 229 |
|
QAPM | | | 82.59 172 | 82.59 169 | 82.58 182 | 86.44 222 | 66.69 169 | 89.94 44 | 90.36 141 | 67.97 229 | 84.94 179 | 92.58 123 | 72.71 199 | 92.18 150 | 70.63 183 | 87.73 274 | 88.85 228 |
|
v1921920 | | | 84.23 140 | 84.37 143 | 83.79 153 | 87.64 197 | 61.71 226 | 82.91 182 | 91.20 122 | 67.94 230 | 90.06 87 | 90.34 187 | 72.04 209 | 93.59 93 | 82.32 74 | 94.91 140 | 96.07 46 |
|
v1240 | | | 84.30 137 | 84.51 136 | 83.65 160 | 87.65 196 | 61.26 235 | 82.85 183 | 91.54 101 | 67.94 230 | 90.68 82 | 90.65 182 | 71.71 212 | 93.64 87 | 82.84 69 | 94.78 147 | 96.07 46 |
|
TSAR-MVS + MP. | | | 88.14 66 | 87.82 71 | 89.09 58 | 95.72 19 | 76.74 94 | 92.49 20 | 91.19 123 | 67.85 232 | 86.63 155 | 94.84 56 | 79.58 109 | 95.96 9 | 87.62 15 | 94.50 155 | 94.56 83 |
|
v144192 | | | 84.24 139 | 84.41 138 | 83.71 159 | 87.59 198 | 61.57 231 | 82.95 181 | 91.03 126 | 67.82 233 | 89.80 99 | 90.49 185 | 73.28 189 | 93.51 106 | 81.88 79 | 94.89 141 | 96.04 48 |
|
EMVS | | | 61.10 325 | 60.81 325 | 61.99 331 | 65.96 362 | 55.86 275 | 53.10 355 | 58.97 355 | 67.06 234 | 56.89 360 | 63.33 357 | 40.98 345 | 67.03 340 | 54.79 298 | 86.18 288 | 63.08 351 |
|
PNet_i23d | | | 52.13 335 | 51.24 337 | 54.79 344 | 75.56 335 | 45.26 342 | 54.54 353 | 52.55 362 | 66.95 235 | 57.19 359 | 65.82 355 | 13.15 369 | 63.40 351 | 36.39 351 | 39.04 360 | 55.71 358 |
|
OpenMVS | | 76.72 13 | 81.98 182 | 82.00 179 | 81.93 190 | 84.42 261 | 68.22 159 | 88.50 75 | 89.48 169 | 66.92 236 | 81.80 230 | 91.86 138 | 72.59 203 | 90.16 204 | 71.19 177 | 91.25 223 | 87.40 242 |
|
testgi | | | 72.36 274 | 74.61 243 | 65.59 322 | 80.56 301 | 42.82 350 | 68.29 325 | 73.35 294 | 66.87 237 | 81.84 227 | 89.93 195 | 72.08 208 | 66.92 341 | 46.05 334 | 92.54 199 | 87.01 246 |
|
E-PMN | | | 61.59 322 | 61.62 322 | 61.49 333 | 66.81 360 | 55.40 278 | 53.77 354 | 60.34 353 | 66.80 238 | 58.90 356 | 65.50 356 | 40.48 347 | 66.12 345 | 55.72 289 | 86.25 287 | 62.95 352 |
|
EPNet_dtu | | | 72.87 269 | 71.33 282 | 77.49 254 | 77.72 321 | 60.55 244 | 82.35 197 | 75.79 276 | 66.49 239 | 58.39 358 | 81.06 318 | 53.68 288 | 85.98 271 | 53.55 303 | 92.97 192 | 85.95 255 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
agg_prior1 | | | 85.72 108 | 85.20 115 | 87.28 83 | 91.58 105 | 77.69 82 | 83.69 157 | 90.30 146 | 66.29 240 | 84.32 194 | 91.07 166 | 82.13 80 | 93.18 121 | 81.02 86 | 96.36 90 | 90.98 186 |
|
testing_2 | | | 84.36 134 | 84.64 132 | 83.50 168 | 86.74 221 | 63.97 189 | 84.56 134 | 90.31 144 | 66.22 241 | 91.62 68 | 94.55 64 | 75.88 147 | 91.95 155 | 77.02 137 | 94.89 141 | 94.56 83 |
|
1111 | | | 61.71 320 | 63.77 316 | 55.55 343 | 78.05 318 | 25.74 362 | 60.62 341 | 67.52 334 | 66.09 242 | 74.68 298 | 86.50 242 | 16.00 367 | 59.22 356 | 38.79 345 | 85.65 291 | 81.70 314 |
|
.test1245 | | | 48.02 337 | 54.41 336 | 28.84 350 | 78.05 318 | 25.74 362 | 60.62 341 | 67.52 334 | 66.09 242 | 74.68 298 | 86.50 242 | 16.00 367 | 59.22 356 | 38.79 345 | 1.47 362 | 1.55 363 |
|
CDPH-MVS | | | 86.17 100 | 85.54 110 | 88.05 73 | 92.25 86 | 75.45 103 | 83.85 150 | 92.01 87 | 65.91 244 | 86.19 163 | 91.75 145 | 83.77 61 | 94.98 47 | 77.43 131 | 96.71 78 | 93.73 112 |
|
train_agg | | | 85.98 104 | 85.28 114 | 88.07 70 | 92.34 83 | 79.70 66 | 83.94 146 | 90.32 142 | 65.79 245 | 84.49 190 | 90.97 169 | 81.93 86 | 93.63 88 | 81.21 83 | 96.54 83 | 90.88 191 |
|
test_8 | | | | | | 92.09 90 | 78.87 73 | 83.82 151 | 90.31 144 | 65.79 245 | 84.36 193 | 90.96 171 | 81.93 86 | 93.44 109 | | | |
|
BH-w/o | | | 76.57 232 | 76.07 231 | 78.10 242 | 86.88 219 | 65.92 174 | 77.63 275 | 86.33 212 | 65.69 247 | 80.89 240 | 79.95 324 | 68.97 223 | 90.74 188 | 53.01 305 | 85.25 297 | 77.62 333 |
|
MAR-MVS | | | 80.24 203 | 78.74 209 | 84.73 126 | 86.87 220 | 78.18 78 | 85.75 118 | 87.81 193 | 65.67 248 | 77.84 273 | 78.50 330 | 73.79 176 | 90.53 194 | 61.59 249 | 90.87 236 | 85.49 261 |
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 |
xiu_mvs_v1_base_debu | | | 80.84 195 | 80.14 201 | 82.93 177 | 88.31 170 | 71.73 133 | 79.53 244 | 87.17 200 | 65.43 249 | 79.59 260 | 82.73 298 | 76.94 135 | 90.14 205 | 73.22 163 | 88.33 264 | 86.90 247 |
|
xiu_mvs_v1_base | | | 80.84 195 | 80.14 201 | 82.93 177 | 88.31 170 | 71.73 133 | 79.53 244 | 87.17 200 | 65.43 249 | 79.59 260 | 82.73 298 | 76.94 135 | 90.14 205 | 73.22 163 | 88.33 264 | 86.90 247 |
|
xiu_mvs_v1_base_debi | | | 80.84 195 | 80.14 201 | 82.93 177 | 88.31 170 | 71.73 133 | 79.53 244 | 87.17 200 | 65.43 249 | 79.59 260 | 82.73 298 | 76.94 135 | 90.14 205 | 73.22 163 | 88.33 264 | 86.90 247 |
|
TEST9 | | | | | | 92.34 83 | 79.70 66 | 83.94 146 | 90.32 142 | 65.41 252 | 84.49 190 | 90.97 169 | 82.03 84 | 93.63 88 | | | |
|
TR-MVS | | | 76.77 230 | 75.79 232 | 79.72 220 | 86.10 242 | 65.79 175 | 77.14 279 | 83.02 238 | 65.20 253 | 81.40 234 | 82.10 309 | 66.30 231 | 90.73 189 | 55.57 291 | 85.27 296 | 82.65 298 |
|
agg_prior3 | | | 85.76 107 | 84.95 120 | 88.16 68 | 92.43 80 | 79.92 62 | 83.98 145 | 90.03 157 | 65.11 254 | 83.66 203 | 90.64 184 | 81.00 97 | 93.67 85 | 81.21 83 | 96.54 83 | 90.88 191 |
|
tpmvs | | | 70.16 290 | 69.56 292 | 71.96 301 | 74.71 345 | 48.13 335 | 79.63 242 | 75.45 280 | 65.02 255 | 70.26 321 | 81.88 311 | 45.34 321 | 85.68 275 | 58.34 276 | 75.39 340 | 82.08 308 |
|
IterMVS | | | 76.91 225 | 76.34 229 | 78.64 233 | 80.91 295 | 64.03 187 | 76.30 288 | 79.03 261 | 64.88 256 | 83.11 211 | 89.16 205 | 59.90 257 | 84.46 286 | 68.61 202 | 85.15 299 | 87.42 241 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
testpf | | | 58.55 329 | 61.58 324 | 49.48 346 | 66.03 361 | 40.05 352 | 74.40 302 | 58.07 357 | 64.72 257 | 59.36 353 | 72.67 345 | 22.76 365 | 66.92 341 | 67.07 210 | 69.15 354 | 41.46 359 |
|
PatchMatch-RL | | | 74.48 253 | 73.22 263 | 78.27 240 | 87.70 194 | 85.26 30 | 75.92 290 | 70.09 321 | 64.34 258 | 76.09 287 | 81.25 317 | 65.87 235 | 78.07 312 | 53.86 302 | 83.82 308 | 71.48 344 |
|
DI_MVS_plusplus_test | | | 81.27 189 | 81.26 186 | 81.29 202 | 84.98 251 | 61.65 230 | 81.98 208 | 87.25 199 | 63.56 259 | 87.56 141 | 89.60 200 | 73.62 179 | 91.83 160 | 72.20 173 | 90.59 245 | 90.38 206 |
|
LP | | | 69.42 297 | 68.30 299 | 72.77 294 | 71.48 358 | 56.84 271 | 73.66 308 | 74.84 282 | 63.52 260 | 70.95 320 | 83.35 288 | 49.55 298 | 77.15 315 | 57.13 283 | 70.21 349 | 84.33 276 |
|
testmv | | | 70.47 288 | 70.70 283 | 69.77 306 | 86.22 233 | 53.89 288 | 67.32 330 | 71.91 307 | 63.32 261 | 78.16 271 | 89.47 202 | 56.12 279 | 73.10 324 | 36.43 350 | 87.33 277 | 82.33 305 |
|
FMVSNet5 | | | 72.10 277 | 71.69 277 | 73.32 288 | 81.57 289 | 53.02 295 | 76.77 281 | 78.37 264 | 63.31 262 | 76.37 282 | 91.85 139 | 36.68 352 | 78.98 310 | 47.87 327 | 92.45 200 | 87.95 236 |
|
IB-MVS | | 62.13 19 | 71.64 280 | 68.97 294 | 79.66 222 | 80.80 298 | 62.26 224 | 73.94 305 | 76.90 271 | 63.27 263 | 68.63 327 | 76.79 336 | 33.83 355 | 91.84 159 | 59.28 269 | 87.26 278 | 84.88 270 |
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 |
test_normal | | | 81.23 191 | 81.16 189 | 81.43 200 | 84.77 256 | 61.99 225 | 81.46 220 | 86.95 209 | 63.16 264 | 87.22 144 | 89.63 199 | 73.62 179 | 91.65 164 | 72.92 168 | 90.70 240 | 90.65 199 |
|
new-patchmatchnet | | | 70.10 291 | 73.37 262 | 60.29 337 | 81.23 292 | 16.95 365 | 59.54 344 | 74.62 284 | 62.93 265 | 80.97 238 | 87.93 227 | 62.83 245 | 71.90 327 | 55.24 294 | 95.01 138 | 92.00 163 |
|
PVSNet_Blended_VisFu | | | 81.55 185 | 80.49 197 | 84.70 128 | 91.58 105 | 73.24 116 | 84.21 139 | 91.67 97 | 62.86 266 | 80.94 239 | 87.16 236 | 67.27 228 | 92.87 138 | 69.82 188 | 88.94 259 | 87.99 235 |
|
Test4 | | | 81.31 187 | 81.13 190 | 81.88 193 | 84.89 253 | 63.05 203 | 82.37 196 | 90.50 136 | 62.75 267 | 89.00 119 | 88.29 221 | 67.55 227 | 91.68 163 | 73.55 160 | 91.24 224 | 90.89 190 |
|
原ACMM1 | | | | | 84.60 130 | 92.81 73 | 74.01 111 | | 91.50 102 | 62.59 268 | 82.73 217 | 90.67 181 | 76.53 142 | 94.25 63 | 69.24 192 | 95.69 119 | 85.55 259 |
|
PAPR | | | 78.84 209 | 78.10 213 | 81.07 205 | 85.17 250 | 60.22 246 | 82.21 203 | 90.57 135 | 62.51 269 | 75.32 294 | 84.61 274 | 74.99 156 | 92.30 148 | 59.48 268 | 88.04 270 | 90.68 197 |
|
Patchmatch-test | | | 65.91 311 | 67.38 302 | 61.48 334 | 75.51 337 | 43.21 349 | 68.84 323 | 63.79 346 | 62.48 270 | 72.80 308 | 83.42 287 | 44.89 329 | 59.52 355 | 48.27 326 | 86.45 284 | 81.70 314 |
|
OpenMVS_ROB | | 70.19 17 | 77.77 218 | 77.46 216 | 78.71 232 | 84.39 262 | 61.15 236 | 81.18 225 | 82.52 241 | 62.45 271 | 83.34 207 | 87.37 235 | 66.20 232 | 88.66 235 | 64.69 227 | 85.02 300 | 86.32 251 |
|
test-LLR | | | 67.21 305 | 66.74 306 | 68.63 313 | 76.45 330 | 55.21 280 | 67.89 326 | 67.14 339 | 62.43 272 | 65.08 341 | 72.39 346 | 43.41 332 | 69.37 331 | 61.00 251 | 84.89 301 | 81.31 321 |
|
test0.0.03 1 | | | 64.66 315 | 64.36 314 | 65.57 323 | 75.03 343 | 46.89 338 | 64.69 336 | 61.58 352 | 62.43 272 | 71.18 318 | 77.54 332 | 43.41 332 | 68.47 336 | 40.75 343 | 82.65 316 | 81.35 320 |
|
MCST-MVS | | | 84.36 134 | 83.93 151 | 85.63 111 | 91.59 102 | 71.58 137 | 83.52 162 | 92.13 83 | 61.82 274 | 83.96 199 | 89.75 198 | 79.93 108 | 93.46 108 | 78.33 121 | 94.34 158 | 91.87 168 |
|
Patchmatch-test1 | | | 72.75 270 | 72.61 269 | 73.19 291 | 81.62 288 | 55.86 275 | 78.89 263 | 71.37 313 | 61.73 275 | 74.93 297 | 82.15 308 | 60.46 252 | 81.80 300 | 59.68 260 | 82.63 318 | 81.92 312 |
|
TAMVS | | | 78.08 215 | 76.36 228 | 83.23 171 | 90.62 128 | 72.87 117 | 79.08 261 | 80.01 259 | 61.72 276 | 81.35 235 | 86.92 239 | 63.96 240 | 88.78 232 | 50.61 314 | 93.01 191 | 88.04 234 |
|
PVSNet_BlendedMVS | | | 78.80 210 | 77.84 214 | 81.65 198 | 84.43 259 | 63.41 194 | 79.49 247 | 90.44 138 | 61.70 277 | 75.43 292 | 87.07 238 | 69.11 221 | 91.44 169 | 60.68 255 | 92.24 205 | 90.11 212 |
|
mvs_anonymous | | | 78.13 214 | 78.76 208 | 76.23 269 | 79.24 309 | 50.31 324 | 78.69 265 | 84.82 233 | 61.60 278 | 83.09 213 | 92.82 116 | 73.89 175 | 87.01 248 | 68.33 204 | 86.41 285 | 91.37 180 |
|
PS-MVSNAJ | | | 77.04 224 | 76.53 227 | 78.56 234 | 87.09 216 | 61.40 232 | 75.26 296 | 87.13 203 | 61.25 279 | 74.38 302 | 77.22 335 | 76.94 135 | 90.94 180 | 64.63 228 | 84.83 303 | 83.35 291 |
|
xiu_mvs_v2_base | | | 77.19 222 | 76.75 221 | 78.52 235 | 87.01 217 | 61.30 234 | 75.55 295 | 87.12 205 | 61.24 280 | 74.45 300 | 78.79 329 | 77.20 129 | 90.93 181 | 64.62 229 | 84.80 304 | 83.32 292 |
|
casdiffmvs | | | 82.99 167 | 82.51 171 | 84.42 137 | 86.34 228 | 67.92 161 | 87.86 81 | 92.28 80 | 60.95 281 | 81.12 237 | 93.08 106 | 76.07 146 | 93.43 111 | 79.41 114 | 85.45 293 | 91.93 167 |
|
CDS-MVSNet | | | 77.32 221 | 75.40 237 | 83.06 174 | 89.00 154 | 72.48 122 | 77.90 273 | 82.17 245 | 60.81 282 | 78.94 267 | 83.49 285 | 59.30 261 | 88.76 233 | 54.64 300 | 92.37 201 | 87.93 237 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
MVSTER | | | 77.09 223 | 75.70 235 | 81.25 203 | 75.27 341 | 61.08 237 | 77.49 278 | 85.07 228 | 60.78 283 | 86.55 156 | 88.68 212 | 43.14 334 | 90.25 199 | 73.69 158 | 90.67 241 | 92.42 150 |
|
XXY-MVS | | | 74.44 255 | 76.19 230 | 69.21 309 | 84.61 257 | 52.43 300 | 71.70 314 | 77.18 269 | 60.73 284 | 80.60 250 | 90.96 171 | 75.44 149 | 69.35 333 | 56.13 287 | 88.33 264 | 85.86 257 |
|
MVP-Stereo | | | 75.81 241 | 73.51 261 | 82.71 180 | 89.35 147 | 73.62 112 | 80.06 236 | 85.20 225 | 60.30 285 | 73.96 303 | 87.94 226 | 57.89 270 | 89.45 215 | 52.02 308 | 74.87 341 | 85.06 265 |
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
MIMVSNet | | | 71.09 284 | 71.59 278 | 69.57 308 | 87.23 209 | 50.07 326 | 78.91 262 | 71.83 308 | 60.20 286 | 71.26 316 | 91.76 144 | 55.08 285 | 76.09 317 | 41.06 342 | 87.02 281 | 82.54 301 |
|
testdata | | | | | 79.54 224 | 92.87 69 | 72.34 123 | | 80.14 258 | 59.91 287 | 85.47 175 | 91.75 145 | 67.96 226 | 85.24 278 | 68.57 203 | 92.18 208 | 81.06 328 |
|
UnsupCasMVSNet_eth | | | 71.63 281 | 72.30 273 | 69.62 307 | 76.47 329 | 52.70 298 | 70.03 321 | 80.97 254 | 59.18 288 | 79.36 263 | 88.21 222 | 60.50 251 | 69.12 334 | 58.33 277 | 77.62 336 | 87.04 245 |
|
our_test_3 | | | 71.85 278 | 71.59 278 | 72.62 297 | 80.71 299 | 53.78 289 | 69.72 322 | 71.71 312 | 58.80 289 | 78.03 272 | 80.51 320 | 56.61 276 | 78.84 311 | 62.20 241 | 86.04 289 | 85.23 262 |
|
casdiffmvs1 | | | 83.63 156 | 83.44 155 | 84.20 145 | 88.08 178 | 66.53 171 | 88.62 73 | 92.02 86 | 58.66 290 | 82.94 214 | 93.84 96 | 78.76 114 | 93.10 126 | 76.73 138 | 91.29 222 | 92.96 132 |
|
MDA-MVSNet_test_wron | | | 70.05 293 | 70.44 285 | 68.88 311 | 73.84 346 | 53.47 291 | 58.93 349 | 67.28 337 | 58.43 291 | 87.09 148 | 85.40 261 | 59.80 259 | 67.25 339 | 59.66 261 | 83.54 309 | 85.92 256 |
|
YYNet1 | | | 70.06 292 | 70.44 285 | 68.90 310 | 73.76 347 | 53.42 293 | 58.99 348 | 67.20 338 | 58.42 292 | 87.10 147 | 85.39 262 | 59.82 258 | 67.32 338 | 59.79 259 | 83.50 310 | 85.96 254 |
|
ppachtmachnet_test | | | 74.73 252 | 74.00 250 | 76.90 259 | 80.71 299 | 56.89 269 | 71.53 315 | 78.42 263 | 58.24 293 | 79.32 264 | 82.92 295 | 57.91 269 | 84.26 288 | 65.60 223 | 91.36 215 | 89.56 215 |
|
无先验 | | | | | | | | 82.81 184 | 85.62 220 | 58.09 294 | | | | 91.41 171 | 67.95 207 | | 84.48 273 |
|
Patchmatch-RL test | | | 74.48 253 | 73.68 252 | 76.89 260 | 84.83 254 | 66.54 170 | 72.29 312 | 69.16 326 | 57.70 295 | 86.76 152 | 86.33 248 | 45.79 313 | 82.59 298 | 69.63 189 | 90.65 243 | 81.54 318 |
|
PatchmatchNet | | | 69.71 295 | 68.83 295 | 72.33 299 | 77.66 322 | 53.60 290 | 79.29 255 | 69.99 322 | 57.66 296 | 72.53 309 | 82.93 294 | 46.45 305 | 80.08 309 | 60.91 254 | 72.09 346 | 83.31 293 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
PVSNet_Blended | | | 76.49 234 | 75.40 237 | 79.76 219 | 84.43 259 | 63.41 194 | 75.14 297 | 90.44 138 | 57.36 297 | 75.43 292 | 78.30 331 | 69.11 221 | 91.44 169 | 60.68 255 | 87.70 275 | 84.42 275 |
|
PCF-MVS | | 74.62 15 | 82.15 178 | 80.92 193 | 85.84 108 | 89.43 146 | 72.30 124 | 80.53 233 | 91.82 93 | 57.36 297 | 87.81 138 | 89.92 196 | 77.67 124 | 93.63 88 | 58.69 270 | 95.08 135 | 91.58 177 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
PatchFormer-LS_test | | | 67.91 303 | 66.49 309 | 72.17 300 | 75.29 340 | 51.85 307 | 75.68 291 | 73.62 293 | 57.23 299 | 68.64 325 | 68.13 354 | 42.19 336 | 82.76 297 | 64.06 231 | 73.51 343 | 81.89 313 |
|
test1235678 | | | 65.57 313 | 65.73 310 | 65.06 325 | 82.84 282 | 50.90 316 | 62.90 338 | 69.26 324 | 57.17 300 | 72.36 310 | 83.04 290 | 46.02 308 | 70.10 330 | 32.79 355 | 85.24 298 | 74.19 340 |
|
旧先验2 | | | | | | | | 81.73 214 | | 56.88 301 | 86.54 161 | | | 84.90 282 | 72.81 169 | | |
|
HY-MVS | | 64.64 18 | 73.03 268 | 72.47 272 | 74.71 278 | 83.36 276 | 54.19 285 | 82.14 206 | 81.96 246 | 56.76 302 | 69.57 324 | 86.21 251 | 60.03 255 | 84.83 284 | 49.58 320 | 82.65 316 | 85.11 264 |
|
cascas | | | 76.29 236 | 74.81 242 | 80.72 211 | 84.47 258 | 62.94 205 | 73.89 306 | 87.34 196 | 55.94 303 | 75.16 296 | 76.53 338 | 63.97 239 | 91.16 175 | 65.00 225 | 90.97 233 | 88.06 233 |
|
pmmvs-eth3d | | | 78.42 213 | 77.04 219 | 82.57 184 | 87.44 200 | 74.41 109 | 80.86 231 | 79.67 260 | 55.68 304 | 84.69 183 | 90.31 190 | 60.91 250 | 85.42 277 | 62.20 241 | 91.59 212 | 87.88 238 |
|
新几何1 | | | | | 82.95 176 | 93.96 44 | 78.56 77 | | 80.24 256 | 55.45 305 | 83.93 200 | 91.08 165 | 71.19 215 | 88.33 238 | 65.84 221 | 93.07 188 | 81.95 311 |
|
1121 | | | 80.86 194 | 79.81 205 | 84.02 147 | 93.93 45 | 78.70 75 | 81.64 216 | 80.18 257 | 55.43 306 | 83.67 202 | 91.15 160 | 71.29 214 | 91.41 171 | 67.95 207 | 93.06 189 | 81.96 310 |
|
N_pmnet | | | 70.20 289 | 68.80 296 | 74.38 280 | 80.91 295 | 84.81 35 | 59.12 347 | 76.45 275 | 55.06 307 | 75.31 295 | 82.36 307 | 55.74 280 | 54.82 358 | 47.02 330 | 87.24 279 | 83.52 287 |
|
tpm | | | 67.95 302 | 68.08 301 | 67.55 317 | 78.74 315 | 43.53 348 | 75.60 293 | 67.10 341 | 54.92 308 | 72.23 311 | 88.10 223 | 42.87 335 | 75.97 318 | 52.21 307 | 80.95 326 | 83.15 295 |
|
114514_t | | | 83.10 166 | 82.54 170 | 84.77 124 | 92.90 68 | 69.10 155 | 86.65 108 | 90.62 134 | 54.66 309 | 81.46 233 | 90.81 176 | 76.98 134 | 94.38 60 | 72.62 170 | 96.18 97 | 90.82 194 |
|
1112_ss | | | 74.82 251 | 73.74 251 | 78.04 243 | 89.57 145 | 60.04 247 | 76.49 286 | 87.09 206 | 54.31 310 | 73.66 305 | 79.80 325 | 60.25 254 | 86.76 261 | 58.37 275 | 84.15 307 | 87.32 243 |
|
UnsupCasMVSNet_bld | | | 69.21 299 | 69.68 291 | 67.82 316 | 79.42 306 | 51.15 313 | 67.82 329 | 75.79 276 | 54.15 311 | 77.47 277 | 85.36 264 | 59.26 262 | 70.64 329 | 48.46 324 | 79.35 330 | 81.66 316 |
|
DWT-MVSNet_test | | | 66.43 308 | 64.37 313 | 72.63 296 | 74.86 344 | 50.86 317 | 76.52 285 | 72.74 300 | 54.06 312 | 65.50 338 | 68.30 353 | 32.13 357 | 84.84 283 | 61.63 248 | 73.59 342 | 82.19 306 |
|
EPMVS | | | 62.47 316 | 62.63 320 | 62.01 330 | 70.63 359 | 38.74 354 | 74.76 299 | 52.86 361 | 53.91 313 | 67.71 332 | 80.01 323 | 39.40 350 | 66.60 343 | 55.54 292 | 68.81 355 | 80.68 330 |
|
WTY-MVS | | | 67.91 303 | 68.35 298 | 66.58 320 | 80.82 297 | 48.12 336 | 65.96 334 | 72.60 301 | 53.67 314 | 71.20 317 | 81.68 314 | 58.97 263 | 69.06 335 | 48.57 323 | 81.67 320 | 82.55 300 |
|
PAPM | | | 71.77 279 | 70.06 290 | 76.92 258 | 86.39 223 | 53.97 286 | 76.62 284 | 86.62 210 | 53.44 315 | 63.97 345 | 84.73 273 | 57.79 271 | 92.34 147 | 39.65 344 | 81.33 323 | 84.45 274 |
|
PMMVS2 | | | 55.64 333 | 59.27 330 | 44.74 348 | 64.30 364 | 12.32 366 | 40.60 358 | 49.79 364 | 53.19 316 | 65.06 343 | 84.81 271 | 53.60 289 | 49.76 360 | 32.68 356 | 89.41 253 | 72.15 343 |
|
tpmrst | | | 66.28 310 | 66.69 307 | 65.05 326 | 72.82 354 | 39.33 353 | 78.20 269 | 70.69 319 | 53.16 317 | 67.88 330 | 80.36 321 | 48.18 300 | 74.75 322 | 58.13 278 | 70.79 348 | 81.08 326 |
|
pmmvs4 | | | 74.92 249 | 72.98 266 | 80.73 210 | 84.95 252 | 71.71 136 | 76.23 289 | 77.59 267 | 52.83 318 | 77.73 276 | 86.38 244 | 56.35 277 | 84.97 281 | 57.72 281 | 87.05 280 | 85.51 260 |
|
test222 | | | | | | 93.31 58 | 76.54 95 | 79.38 254 | 77.79 266 | 52.59 319 | 82.36 220 | 90.84 175 | 66.83 230 | | | 91.69 211 | 81.25 323 |
|
Anonymous20231206 | | | 71.38 283 | 71.88 276 | 69.88 304 | 86.31 229 | 54.37 284 | 70.39 319 | 74.62 284 | 52.57 320 | 76.73 280 | 88.76 210 | 59.94 256 | 72.06 326 | 44.35 337 | 93.23 187 | 83.23 294 |
|
MS-PatchMatch | | | 70.93 285 | 70.22 288 | 73.06 293 | 81.85 287 | 62.50 216 | 73.82 307 | 77.90 265 | 52.44 321 | 75.92 288 | 81.27 316 | 55.67 281 | 81.75 301 | 55.37 293 | 77.70 335 | 74.94 338 |
|
gm-plane-assit | | | | | | 75.42 339 | 44.97 345 | | | 52.17 322 | | 72.36 348 | | 87.90 241 | 54.10 301 | | |
|
MDTV_nov1_ep13 | | | | 68.29 300 | | 78.03 320 | 43.87 347 | 74.12 304 | 72.22 304 | 52.17 322 | 67.02 333 | 85.54 255 | 45.36 320 | 80.85 304 | 55.73 288 | 84.42 306 | |
|
USDC | | | 76.63 231 | 76.73 222 | 76.34 267 | 83.46 275 | 57.20 266 | 80.02 238 | 88.04 189 | 52.14 324 | 83.65 204 | 91.25 154 | 63.24 244 | 86.65 263 | 54.66 299 | 94.11 160 | 85.17 263 |
|
sss | | | 66.92 306 | 67.26 304 | 65.90 321 | 77.23 323 | 51.10 315 | 64.79 335 | 71.72 311 | 52.12 325 | 70.13 322 | 80.18 322 | 57.96 268 | 65.36 348 | 50.21 315 | 81.01 325 | 81.25 323 |
|
CostFormer | | | 69.98 294 | 68.68 297 | 73.87 285 | 77.14 324 | 50.72 322 | 79.26 256 | 74.51 286 | 51.94 326 | 70.97 319 | 84.75 272 | 45.16 328 | 87.49 244 | 55.16 295 | 79.23 331 | 83.40 290 |
|
1314 | | | 73.22 266 | 72.56 271 | 75.20 275 | 80.41 302 | 57.84 260 | 81.64 216 | 85.36 222 | 51.68 327 | 73.10 307 | 76.65 337 | 61.45 248 | 85.19 279 | 63.54 233 | 79.21 332 | 82.59 299 |
|
test12356 | | | 54.91 334 | 57.14 332 | 48.22 347 | 75.83 334 | 17.47 364 | 52.31 356 | 69.20 325 | 51.66 328 | 60.11 351 | 75.40 341 | 29.77 361 | 62.62 354 | 27.64 358 | 72.37 345 | 64.59 350 |
|
jason | | | 77.42 220 | 75.75 234 | 82.43 187 | 87.10 215 | 69.27 150 | 77.99 271 | 81.94 248 | 51.47 329 | 77.84 273 | 85.07 267 | 60.32 253 | 89.00 224 | 70.74 181 | 89.27 256 | 89.03 225 |
jason: jason. |
no-one | | | 71.52 282 | 70.43 287 | 74.81 277 | 78.45 317 | 63.41 194 | 57.73 350 | 77.03 270 | 51.46 330 | 77.17 279 | 90.33 188 | 54.96 286 | 80.35 307 | 47.41 328 | 99.29 2 | 80.68 330 |
|
dp | | | 60.70 327 | 60.29 328 | 61.92 332 | 72.04 356 | 38.67 355 | 70.83 316 | 64.08 345 | 51.28 331 | 60.75 349 | 77.28 334 | 36.59 353 | 71.58 328 | 47.41 328 | 62.34 357 | 75.52 337 |
|
PVSNet | | 58.17 21 | 66.41 309 | 65.63 311 | 68.75 312 | 81.96 285 | 49.88 333 | 62.19 340 | 72.51 303 | 51.03 332 | 68.04 329 | 75.34 342 | 50.84 293 | 74.77 321 | 45.82 335 | 82.96 312 | 81.60 317 |
|
test-mter | | | 65.00 314 | 63.79 315 | 68.63 313 | 76.45 330 | 55.21 280 | 67.89 326 | 67.14 339 | 50.98 333 | 65.08 341 | 72.39 346 | 28.27 362 | 69.37 331 | 61.00 251 | 84.89 301 | 81.31 321 |
|
CMPMVS | | 59.41 20 | 75.12 246 | 73.57 254 | 79.77 218 | 75.84 333 | 67.22 164 | 81.21 224 | 82.18 244 | 50.78 334 | 76.50 281 | 87.66 231 | 55.20 284 | 82.99 296 | 62.17 243 | 90.64 244 | 89.09 224 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
Test_1112_low_res | | | 73.90 259 | 73.08 264 | 76.35 266 | 90.35 133 | 55.95 273 | 73.40 310 | 86.17 214 | 50.70 335 | 73.14 306 | 85.94 253 | 58.31 266 | 85.90 273 | 56.51 285 | 83.22 311 | 87.20 244 |
|
lupinMVS | | | 76.37 235 | 74.46 246 | 82.09 188 | 85.54 246 | 69.26 151 | 76.79 280 | 80.77 255 | 50.68 336 | 76.23 285 | 82.82 296 | 58.69 264 | 88.94 225 | 69.85 187 | 88.77 260 | 88.07 232 |
|
CR-MVSNet | | | 74.00 258 | 73.04 265 | 76.85 261 | 79.58 304 | 62.64 210 | 82.58 190 | 76.90 271 | 50.50 337 | 75.72 290 | 92.38 126 | 48.07 301 | 84.07 289 | 68.72 201 | 82.91 314 | 83.85 283 |
|
pmmvs5 | | | 70.73 286 | 70.07 289 | 72.72 295 | 77.03 326 | 52.73 297 | 74.14 303 | 75.65 279 | 50.36 338 | 72.17 312 | 85.37 263 | 55.42 283 | 80.67 305 | 52.86 306 | 87.59 276 | 84.77 271 |
|
ADS-MVSNet2 | | | 65.87 312 | 63.64 317 | 72.55 298 | 73.16 351 | 56.92 268 | 67.10 331 | 74.81 283 | 49.74 339 | 66.04 336 | 82.97 292 | 46.71 303 | 77.26 313 | 42.29 339 | 69.96 351 | 83.46 288 |
|
ADS-MVSNet | | | 61.90 319 | 62.19 321 | 61.03 336 | 73.16 351 | 36.42 356 | 67.10 331 | 61.75 350 | 49.74 339 | 66.04 336 | 82.97 292 | 46.71 303 | 63.21 352 | 42.29 339 | 69.96 351 | 83.46 288 |
|
testus | | | 62.33 318 | 63.03 318 | 60.20 338 | 78.78 314 | 40.74 351 | 59.14 345 | 69.80 323 | 49.26 341 | 71.41 315 | 74.72 344 | 52.33 291 | 63.52 350 | 29.84 357 | 82.01 319 | 76.36 335 |
|
tpmp4_e23 | | | 69.43 296 | 67.33 303 | 75.72 273 | 78.53 316 | 52.75 296 | 82.13 207 | 74.91 281 | 49.23 342 | 66.37 334 | 84.17 279 | 41.28 344 | 88.67 234 | 49.73 319 | 79.63 327 | 85.75 258 |
|
test2356 | | | 56.69 330 | 55.15 334 | 61.32 335 | 73.20 349 | 44.11 346 | 54.95 352 | 62.52 347 | 48.75 343 | 62.45 347 | 68.42 351 | 21.10 366 | 65.67 347 | 26.86 359 | 78.08 334 | 74.19 340 |
|
tpm2 | | | 68.45 301 | 66.83 305 | 73.30 289 | 78.93 313 | 48.50 334 | 79.76 241 | 71.76 309 | 47.50 344 | 69.92 323 | 83.60 283 | 42.07 337 | 88.40 236 | 48.44 325 | 79.51 328 | 83.01 297 |
|
HyFIR lowres test | | | 75.12 246 | 72.66 268 | 82.50 185 | 91.44 111 | 65.19 178 | 72.47 311 | 87.31 197 | 46.79 345 | 80.29 256 | 84.30 277 | 52.70 290 | 92.10 153 | 51.88 313 | 86.73 282 | 90.22 208 |
|
MVS-HIRNet | | | 61.16 324 | 62.92 319 | 55.87 341 | 79.09 310 | 35.34 357 | 71.83 313 | 57.98 358 | 46.56 346 | 59.05 355 | 91.14 161 | 49.95 296 | 76.43 316 | 38.74 347 | 71.92 347 | 55.84 357 |
|
MDTV_nov1_ep13_2view | | | | | | | 27.60 361 | 70.76 317 | | 46.47 347 | 61.27 348 | | 45.20 322 | | 49.18 321 | | 83.75 285 |
|
MVS | | | 73.21 267 | 72.59 270 | 75.06 276 | 80.97 294 | 60.81 242 | 81.64 216 | 85.92 217 | 46.03 348 | 71.68 314 | 77.54 332 | 68.47 224 | 89.77 211 | 55.70 290 | 85.39 294 | 74.60 339 |
|
TESTMET0.1,1 | | | 61.29 323 | 60.32 327 | 64.19 327 | 72.06 355 | 51.30 311 | 67.89 326 | 62.09 348 | 45.27 349 | 60.65 350 | 69.01 349 | 27.93 363 | 64.74 349 | 56.31 286 | 81.65 322 | 76.53 334 |
|
tpm cat1 | | | 66.76 307 | 65.21 312 | 71.42 302 | 77.09 325 | 50.62 323 | 78.01 270 | 73.68 292 | 44.89 350 | 68.64 325 | 79.00 328 | 45.51 318 | 82.42 299 | 49.91 317 | 70.15 350 | 81.23 325 |
|
PVSNet_0 | | 51.08 22 | 56.10 331 | 54.97 335 | 59.48 339 | 75.12 342 | 53.28 294 | 55.16 351 | 61.89 349 | 44.30 351 | 59.16 354 | 62.48 358 | 54.22 287 | 65.91 346 | 35.40 352 | 47.01 358 | 59.25 355 |
|
CHOSEN 280x420 | | | 59.08 328 | 56.52 333 | 66.76 319 | 76.51 328 | 64.39 185 | 49.62 357 | 59.00 354 | 43.86 352 | 55.66 361 | 68.41 352 | 35.55 354 | 68.21 337 | 43.25 338 | 76.78 339 | 67.69 349 |
|
new_pmnet | | | 55.69 332 | 57.66 331 | 49.76 345 | 75.47 338 | 30.59 359 | 59.56 343 | 51.45 363 | 43.62 353 | 62.49 346 | 75.48 340 | 40.96 346 | 49.15 361 | 37.39 349 | 72.52 344 | 69.55 347 |
|
CHOSEN 1792x2688 | | | 72.45 273 | 70.56 284 | 78.13 241 | 90.02 143 | 63.08 202 | 68.72 324 | 83.16 237 | 42.99 354 | 75.92 288 | 85.46 259 | 57.22 275 | 85.18 280 | 49.87 318 | 81.67 320 | 86.14 253 |
|
MVE | | 40.22 23 | 51.82 336 | 50.47 339 | 55.87 341 | 62.66 365 | 51.91 303 | 31.61 360 | 39.28 366 | 40.65 355 | 50.76 362 | 74.98 343 | 56.24 278 | 44.67 362 | 33.94 354 | 64.11 356 | 71.04 346 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
pmmvs3 | | | 62.47 316 | 60.02 329 | 69.80 305 | 71.58 357 | 64.00 188 | 70.52 318 | 58.44 356 | 39.77 356 | 66.05 335 | 75.84 339 | 27.10 364 | 72.28 325 | 46.15 333 | 84.77 305 | 73.11 342 |
|
EU-MVSNet | | | 75.12 246 | 74.43 247 | 77.18 256 | 83.11 280 | 59.48 252 | 85.71 120 | 82.43 243 | 39.76 357 | 85.64 171 | 88.76 210 | 44.71 330 | 87.88 242 | 73.86 157 | 85.88 290 | 84.16 280 |
|
CVMVSNet | | | 72.62 271 | 71.41 281 | 76.28 268 | 83.25 277 | 60.34 245 | 83.50 165 | 79.02 262 | 37.77 358 | 76.33 283 | 85.10 265 | 49.60 297 | 87.41 245 | 70.54 184 | 77.54 337 | 81.08 326 |
|
PMMVS | | | 61.65 321 | 60.38 326 | 65.47 324 | 65.40 363 | 69.26 151 | 63.97 337 | 61.73 351 | 36.80 359 | 60.11 351 | 68.43 350 | 59.42 260 | 66.35 344 | 48.97 322 | 78.57 333 | 60.81 353 |
|
DSMNet-mixed | | | 60.98 326 | 61.61 323 | 59.09 340 | 72.88 353 | 45.05 344 | 74.70 300 | 46.61 365 | 26.20 360 | 65.34 339 | 90.32 189 | 55.46 282 | 63.12 353 | 41.72 341 | 81.30 324 | 69.09 348 |
|
DeepMVS_CX | | | | | 24.13 351 | 32.95 366 | 29.49 360 | | 21.63 369 | 12.07 361 | 37.95 363 | 45.07 360 | 30.84 358 | 19.21 363 | 17.94 361 | 33.06 361 | 23.69 360 |
|
tmp_tt | | | 20.25 341 | 24.50 342 | 7.49 352 | 4.47 367 | 8.70 367 | 34.17 359 | 25.16 368 | 1.00 362 | 32.43 364 | 18.49 361 | 39.37 351 | 9.21 364 | 21.64 360 | 43.75 359 | 4.57 361 |
|
test123 | | | 6.27 344 | 8.08 345 | 0.84 353 | 1.11 369 | 0.57 368 | 62.90 338 | 0.82 370 | 0.54 363 | 1.07 366 | 2.75 366 | 1.26 370 | 0.30 365 | 1.04 362 | 1.26 364 | 1.66 362 |
|
testmvs | | | 5.91 345 | 7.65 346 | 0.72 354 | 1.20 368 | 0.37 369 | 59.14 345 | 0.67 371 | 0.49 364 | 1.11 365 | 2.76 365 | 0.94 371 | 0.24 366 | 1.02 363 | 1.47 362 | 1.55 363 |
|
cdsmvs_eth3d_5k | | | 20.81 340 | 27.75 341 | 0.00 355 | 0.00 370 | 0.00 370 | 0.00 361 | 85.44 221 | 0.00 365 | 0.00 367 | 82.82 296 | 81.46 93 | 0.00 367 | 0.00 364 | 0.00 365 | 0.00 365 |
|
pcd_1.5k_mvsjas | | | 6.41 343 | 8.55 344 | 0.00 355 | 0.00 370 | 0.00 370 | 0.00 361 | 0.00 372 | 0.00 365 | 0.00 367 | 0.00 367 | 76.94 135 | 0.00 367 | 0.00 364 | 0.00 365 | 0.00 365 |
|
pcd1.5k->3k | | | 38.83 338 | 41.11 340 | 32.01 349 | 93.13 63 | 0.00 370 | 0.00 361 | 91.38 117 | 0.00 365 | 0.00 367 | 0.00 367 | 89.24 15 | 0.00 367 | 0.00 364 | 96.24 96 | 96.02 49 |
|
sosnet-low-res | | | 0.00 346 | 0.00 347 | 0.00 355 | 0.00 370 | 0.00 370 | 0.00 361 | 0.00 372 | 0.00 365 | 0.00 367 | 0.00 367 | 0.00 372 | 0.00 367 | 0.00 364 | 0.00 365 | 0.00 365 |
|
sosnet | | | 0.00 346 | 0.00 347 | 0.00 355 | 0.00 370 | 0.00 370 | 0.00 361 | 0.00 372 | 0.00 365 | 0.00 367 | 0.00 367 | 0.00 372 | 0.00 367 | 0.00 364 | 0.00 365 | 0.00 365 |
|
uncertanet | | | 0.00 346 | 0.00 347 | 0.00 355 | 0.00 370 | 0.00 370 | 0.00 361 | 0.00 372 | 0.00 365 | 0.00 367 | 0.00 367 | 0.00 372 | 0.00 367 | 0.00 364 | 0.00 365 | 0.00 365 |
|
Regformer | | | 0.00 346 | 0.00 347 | 0.00 355 | 0.00 370 | 0.00 370 | 0.00 361 | 0.00 372 | 0.00 365 | 0.00 367 | 0.00 367 | 0.00 372 | 0.00 367 | 0.00 364 | 0.00 365 | 0.00 365 |
|
ab-mvs-re | | | 6.65 342 | 8.87 343 | 0.00 355 | 0.00 370 | 0.00 370 | 0.00 361 | 0.00 372 | 0.00 365 | 0.00 367 | 79.80 325 | 0.00 372 | 0.00 367 | 0.00 364 | 0.00 365 | 0.00 365 |
|
uanet | | | 0.00 346 | 0.00 347 | 0.00 355 | 0.00 370 | 0.00 370 | 0.00 361 | 0.00 372 | 0.00 365 | 0.00 367 | 0.00 367 | 0.00 372 | 0.00 367 | 0.00 364 | 0.00 365 | 0.00 365 |
|
GSMVS | | | | | | | | | | | | | | | | | 83.88 281 |
|
test_part2 | | | | | | 93.86 47 | 77.77 81 | | | | 92.84 44 | | | | | | |
|
test_part1 | | | | | 0.00 355 | | 0.00 370 | 0.00 361 | 93.93 26 | | | | 0.00 372 | 0.00 367 | 0.00 364 | 0.00 365 | 0.00 365 |
|
sam_mvs1 | | | | | | | | | | | | | 46.11 307 | | | | 83.88 281 |
|
sam_mvs | | | | | | | | | | | | | 45.92 312 | | | | |
|
ambc | | | | | 82.98 175 | 90.55 131 | 64.86 180 | 88.20 76 | 89.15 173 | | 89.40 114 | 93.96 90 | 71.67 213 | 91.38 173 | 78.83 117 | 96.55 82 | 92.71 139 |
|
MTGPA | | | | | | | | | 91.81 94 | | | | | | | | |
|
test_post1 | | | | | | | | 78.85 264 | | | | 3.13 363 | 45.19 323 | 80.13 308 | 58.11 279 | | |
|
test_post | | | | | | | | | | | | 3.10 364 | 45.43 319 | 77.22 314 | | | |
|
patchmatchnet-post | | | | | | | | | | | | 81.71 313 | 45.93 311 | 87.01 248 | | | |
|
GG-mvs-BLEND | | | | | 67.16 318 | 73.36 348 | 46.54 340 | 84.15 141 | 55.04 360 | | 58.64 357 | 61.95 359 | 29.93 360 | 83.87 293 | 38.71 348 | 76.92 338 | 71.07 345 |
|
MTMP | | | | | | | | 90.66 35 | 33.14 367 | | | | | | | | |
|
test9_res | | | | | | | | | | | | | | | 80.83 90 | 96.45 88 | 90.57 200 |
|
agg_prior2 | | | | | | | | | | | | | | | 79.68 108 | 96.16 98 | 90.22 208 |
|
agg_prior | | | | | | 91.58 105 | 77.69 82 | | 90.30 146 | | 84.32 194 | | | 93.18 121 | | | |
|
test_prior4 | | | | | | | 78.97 72 | 84.59 133 | | | | | | | | | |
|
test_prior | | | | | 86.32 93 | 90.59 129 | 71.99 130 | | 92.85 63 | | | | | 94.17 68 | | | 92.80 136 |
|
新几何2 | | | | | | | | 81.72 215 | | | | | | | | | |
|
旧先验1 | | | | | | 91.97 93 | 71.77 132 | | 81.78 249 | | | 91.84 140 | 73.92 174 | | | 93.65 174 | 83.61 286 |
|
原ACMM2 | | | | | | | | 82.26 202 | | | | | | | | | |
|
testdata2 | | | | | | | | | | | | | | 86.43 266 | 63.52 234 | | |
|
segment_acmp | | | | | | | | | | | | | 81.94 85 | | | | |
|
test12 | | | | | 86.57 88 | 90.74 126 | 72.63 119 | | 90.69 131 | | 82.76 216 | | 79.20 110 | 94.80 51 | | 95.32 126 | 92.27 157 |
|
plane_prior7 | | | | | | 93.45 53 | 77.31 88 | | | | | | | | | | |
|
plane_prior6 | | | | | | 92.61 74 | 76.54 95 | | | | | | 74.84 159 | | | | |
|
plane_prior5 | | | | | | | | | 93.61 33 | | | | | 95.22 39 | 80.78 91 | 95.83 114 | 94.46 88 |
|
plane_prior4 | | | | | | | | | | | | 92.95 112 | | | | | |
|
plane_prior1 | | | | | | 92.83 72 | | | | | | | | | | | |
|
n2 | | | | | | | | | 0.00 372 | | | | | | | | |
|
nn | | | | | | | | | 0.00 372 | | | | | | | | |
|
door-mid | | | | | | | | | 74.45 287 | | | | | | | | |
|
lessismore_v0 | | | | | 85.95 104 | 91.10 120 | 70.99 141 | | 70.91 318 | | 91.79 65 | 94.42 70 | 61.76 247 | 92.93 134 | 79.52 112 | 93.03 190 | 93.93 104 |
|
test11 | | | | | | | | | 91.46 108 | | | | | | | | |
|
door | | | | | | | | | 72.57 302 | | | | | | | | |
|
HQP5-MVS | | | | | | | 70.66 142 | | | | | | | | | | |
|
BP-MVS | | | | | | | | | | | | | | | 77.30 132 | | |
|
HQP4-MVS | | | | | | | | | | | 80.56 252 | | | 94.61 55 | | | 93.56 119 |
|
HQP3-MVS | | | | | | | | | 92.68 69 | | | | | | | 94.47 156 | |
|
HQP2-MVS | | | | | | | | | | | | | 72.10 206 | | | | |
|
NP-MVS | | | | | | 91.95 94 | 74.55 108 | | | | | 90.17 193 | | | | | |
|
ACMMP++_ref | | | | | | | | | | | | | | | | 95.74 118 | |
|
ACMMP++ | | | | | | | | | | | | | | | | 97.35 61 | |
|
Test By Simon | | | | | | | | | | | | | 79.09 111 | | | | |
|