LCM-MVSNet | | | 99.43 1 | 99.49 1 | 99.24 1 | 99.95 1 | 98.13 1 | 99.37 1 | 99.57 1 | 99.82 1 | 99.86 1 | 99.85 1 | 99.52 1 | 99.73 1 | 97.58 1 | 99.94 1 | 99.85 1 |
|
no-one | | | 87.84 257 | 87.21 259 | 89.74 259 | 93.58 288 | 78.64 260 | 81.28 349 | 92.69 267 | 74.36 315 | 92.05 229 | 97.14 90 | 81.86 245 | 96.07 304 | 72.03 325 | 99.90 2 | 94.52 285 |
|
wuykxyi23d | | | 96.76 15 | 96.57 26 | 97.34 21 | 97.75 87 | 96.73 3 | 94.37 112 | 96.48 170 | 91.00 125 | 99.72 2 | 98.99 5 | 96.06 14 | 98.21 206 | 94.86 22 | 99.90 2 | 97.09 197 |
|
UA-Net | | | 97.35 4 | 97.24 12 | 97.69 5 | 98.22 61 | 93.87 26 | 98.42 4 | 98.19 25 | 96.95 12 | 95.46 128 | 99.23 3 | 93.45 59 | 99.57 13 | 95.34 17 | 99.89 4 | 99.63 9 |
|
PS-CasMVS | | | 96.69 19 | 97.43 4 | 94.49 111 | 99.13 4 | 84.09 165 | 96.61 25 | 97.97 50 | 97.91 4 | 98.64 13 | 98.13 40 | 95.24 30 | 99.65 3 | 93.39 60 | 99.84 5 | 99.72 2 |
|
WR-MVS_H | | | 96.60 24 | 97.05 15 | 95.24 82 | 99.02 10 | 86.44 131 | 96.78 22 | 98.08 33 | 97.42 7 | 98.48 18 | 97.86 56 | 91.76 98 | 99.63 6 | 94.23 37 | 99.84 5 | 99.66 6 |
|
FC-MVSNet-test | | | 95.32 69 | 95.88 56 | 93.62 137 | 98.49 46 | 81.77 189 | 95.90 54 | 98.32 12 | 93.93 50 | 97.53 41 | 97.56 66 | 88.48 159 | 99.40 36 | 92.91 78 | 99.83 7 | 99.68 4 |
|
PEN-MVS | | | 96.69 19 | 97.39 7 | 94.61 100 | 99.16 2 | 84.50 158 | 96.54 29 | 98.05 38 | 98.06 3 | 98.64 13 | 98.25 38 | 95.01 40 | 99.65 3 | 92.95 77 | 99.83 7 | 99.68 4 |
|
DTE-MVSNet | | | 96.74 17 | 97.43 4 | 94.67 98 | 99.13 4 | 84.68 157 | 96.51 30 | 97.94 56 | 98.14 2 | 98.67 12 | 98.32 35 | 95.04 37 | 99.69 2 | 93.27 64 | 99.82 9 | 99.62 10 |
|
CP-MVSNet | | | 96.19 45 | 96.80 19 | 94.38 117 | 98.99 12 | 83.82 167 | 96.31 41 | 97.53 89 | 97.60 5 | 98.34 22 | 97.52 69 | 91.98 94 | 99.63 6 | 93.08 75 | 99.81 10 | 99.70 3 |
|
LTVRE_ROB | | 93.87 1 | 97.93 2 | 98.16 2 | 97.26 23 | 98.81 22 | 93.86 27 | 99.07 2 | 98.98 3 | 97.01 11 | 98.92 4 | 98.78 14 | 95.22 31 | 98.61 164 | 96.85 4 | 99.77 11 | 99.31 38 |
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 |
v7n | | | 96.82 10 | 97.31 9 | 95.33 79 | 98.54 39 | 86.81 125 | 96.83 19 | 98.07 36 | 96.59 18 | 98.46 19 | 98.43 32 | 92.91 76 | 99.52 17 | 96.25 8 | 99.76 12 | 99.65 8 |
|
TranMVSNet+NR-MVSNet | | | 96.07 49 | 96.26 35 | 95.50 74 | 98.26 59 | 87.69 113 | 93.75 131 | 97.86 59 | 95.96 29 | 97.48 43 | 97.14 90 | 95.33 26 | 99.44 25 | 90.79 123 | 99.76 12 | 99.38 32 |
|
Anonymous20231211 | | | 96.60 24 | 97.13 13 | 95.00 89 | 97.46 107 | 86.35 135 | 97.11 15 | 98.24 22 | 97.58 6 | 98.72 8 | 98.97 7 | 93.15 71 | 99.15 69 | 93.18 69 | 99.74 14 | 99.50 21 |
|
pmmvs6 | | | 96.80 13 | 97.36 8 | 95.15 86 | 99.12 6 | 87.82 112 | 96.68 23 | 97.86 59 | 96.10 25 | 98.14 25 | 99.28 2 | 97.94 3 | 98.21 206 | 91.38 120 | 99.69 15 | 99.42 27 |
|
FIs | | | 94.90 88 | 95.35 77 | 93.55 140 | 98.28 57 | 81.76 190 | 95.33 71 | 98.14 29 | 93.05 65 | 97.07 56 | 97.18 88 | 87.65 180 | 99.29 54 | 91.72 110 | 99.69 15 | 99.61 11 |
|
OurMVSNet-221017-0 | | | 96.80 13 | 96.75 20 | 96.96 33 | 99.03 9 | 91.85 53 | 97.98 5 | 98.01 44 | 94.15 45 | 98.93 3 | 99.07 4 | 88.07 174 | 99.57 13 | 95.86 11 | 99.69 15 | 99.46 25 |
|
v13 | | | 95.39 66 | 96.12 42 | 93.18 151 | 97.22 113 | 80.81 202 | 95.55 65 | 97.57 84 | 93.42 60 | 98.02 29 | 98.49 26 | 89.62 145 | 99.18 66 | 95.54 12 | 99.68 18 | 99.54 15 |
|
ANet_high | | | 94.83 93 | 96.28 34 | 90.47 244 | 96.65 142 | 73.16 317 | 94.33 114 | 98.74 5 | 96.39 21 | 98.09 26 | 98.93 8 | 93.37 64 | 98.70 156 | 90.38 128 | 99.68 18 | 99.53 16 |
|
DeepC-MVS | | 91.39 4 | 95.43 64 | 95.33 79 | 95.71 68 | 97.67 97 | 90.17 69 | 93.86 129 | 98.02 43 | 87.35 206 | 96.22 92 | 97.99 48 | 94.48 49 | 99.05 84 | 92.73 82 | 99.68 18 | 97.93 147 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
v12 | | | 95.29 72 | 96.02 50 | 93.10 153 | 97.14 119 | 80.63 203 | 95.39 69 | 97.55 88 | 93.19 63 | 97.98 30 | 98.44 30 | 89.40 148 | 99.16 67 | 95.38 16 | 99.67 21 | 99.52 19 |
|
v11 | | | 95.10 80 | 95.88 56 | 92.76 174 | 96.98 125 | 79.64 234 | 95.12 78 | 97.60 82 | 92.64 75 | 98.03 27 | 98.44 30 | 89.06 154 | 99.15 69 | 95.42 15 | 99.67 21 | 99.50 21 |
|
NR-MVSNet | | | 95.28 73 | 95.28 82 | 95.26 81 | 97.75 87 | 87.21 119 | 95.08 80 | 97.37 102 | 93.92 51 | 97.65 38 | 95.90 165 | 90.10 138 | 99.33 52 | 90.11 139 | 99.66 23 | 99.26 40 |
|
Baseline_NR-MVSNet | | | 94.47 108 | 95.09 90 | 92.60 183 | 98.50 45 | 80.82 201 | 92.08 191 | 96.68 160 | 93.82 52 | 96.29 86 | 98.56 22 | 90.10 138 | 97.75 245 | 90.10 141 | 99.66 23 | 99.24 42 |
|
V9 | | | 95.17 78 | 95.89 55 | 93.02 157 | 97.04 122 | 80.42 205 | 95.22 75 | 97.53 89 | 92.92 70 | 97.90 31 | 98.35 33 | 89.15 153 | 99.14 72 | 95.21 18 | 99.65 25 | 99.50 21 |
|
V14 | | | 95.05 81 | 95.75 64 | 92.94 164 | 96.94 127 | 80.21 208 | 95.03 83 | 97.50 93 | 92.62 76 | 97.84 33 | 98.28 37 | 88.87 156 | 99.13 74 | 95.03 20 | 99.64 26 | 99.48 24 |
|
UniMVSNet (Re) | | | 95.32 69 | 95.15 87 | 95.80 63 | 97.79 85 | 88.91 87 | 92.91 156 | 98.07 36 | 93.46 59 | 96.31 84 | 95.97 164 | 90.14 134 | 99.34 49 | 92.11 97 | 99.64 26 | 99.16 47 |
|
WR-MVS | | | 93.49 133 | 93.72 131 | 92.80 173 | 97.57 101 | 80.03 217 | 90.14 259 | 95.68 203 | 93.70 54 | 96.62 74 | 95.39 190 | 87.21 191 | 99.04 87 | 87.50 182 | 99.64 26 | 99.33 36 |
|
v15 | | | 94.93 86 | 95.62 68 | 92.86 169 | 96.83 133 | 80.01 221 | 94.84 91 | 97.48 94 | 92.36 82 | 97.76 35 | 98.20 39 | 88.61 157 | 99.11 77 | 94.86 22 | 99.62 29 | 99.46 25 |
|
v52 | | | 96.93 7 | 97.29 10 | 95.86 60 | 98.12 67 | 88.48 100 | 97.69 6 | 97.74 70 | 94.90 34 | 98.55 15 | 98.72 17 | 93.39 63 | 99.49 22 | 96.92 2 | 99.62 29 | 99.61 11 |
|
V4 | | | 96.93 7 | 97.29 10 | 95.86 60 | 98.11 68 | 88.47 101 | 97.69 6 | 97.74 70 | 94.91 32 | 98.55 15 | 98.72 17 | 93.37 64 | 99.49 22 | 96.92 2 | 99.62 29 | 99.61 11 |
|
MIMVSNet1 | | | 95.52 61 | 95.45 73 | 95.72 67 | 99.14 3 | 89.02 85 | 96.23 46 | 96.87 149 | 93.73 53 | 97.87 32 | 98.49 26 | 90.73 124 | 99.05 84 | 86.43 200 | 99.60 32 | 99.10 55 |
|
ACMH+ | | 88.43 11 | 96.48 30 | 96.82 18 | 95.47 75 | 98.54 39 | 89.06 84 | 95.65 62 | 98.61 6 | 96.10 25 | 98.16 24 | 97.52 69 | 96.90 7 | 98.62 163 | 90.30 133 | 99.60 32 | 98.72 103 |
|
v748 | | | 96.51 28 | 97.05 15 | 94.89 92 | 98.35 55 | 85.82 146 | 96.58 27 | 97.47 95 | 96.25 22 | 98.46 19 | 98.35 33 | 93.27 67 | 99.33 52 | 95.13 19 | 99.59 34 | 99.52 19 |
|
VPA-MVSNet | | | 95.14 79 | 95.67 67 | 93.58 139 | 97.76 86 | 83.15 176 | 94.58 103 | 97.58 83 | 93.39 61 | 97.05 60 | 98.04 43 | 93.25 68 | 98.51 181 | 89.75 146 | 99.59 34 | 99.08 59 |
|
LPG-MVS_test | | | 96.38 39 | 96.23 36 | 96.84 37 | 98.36 53 | 92.13 48 | 95.33 71 | 98.25 19 | 91.78 107 | 97.07 56 | 97.22 86 | 96.38 11 | 99.28 56 | 92.07 100 | 99.59 34 | 99.11 52 |
|
LGP-MVS_train | | | | | 96.84 37 | 98.36 53 | 92.13 48 | | 98.25 19 | 91.78 107 | 97.07 56 | 97.22 86 | 96.38 11 | 99.28 56 | 92.07 100 | 99.59 34 | 99.11 52 |
|
ACMH | | 88.36 12 | 96.59 26 | 97.43 4 | 94.07 124 | 98.56 35 | 85.33 152 | 96.33 39 | 98.30 15 | 94.66 36 | 98.72 8 | 98.30 36 | 97.51 4 | 98.00 219 | 94.87 21 | 99.59 34 | 98.86 87 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
UniMVSNet_NR-MVSNet | | | 95.35 68 | 95.21 85 | 95.76 65 | 97.69 95 | 88.59 95 | 92.26 186 | 97.84 62 | 94.91 32 | 96.80 66 | 95.78 173 | 90.42 130 | 99.41 32 | 91.60 114 | 99.58 39 | 99.29 39 |
|
DU-MVS | | | 95.28 73 | 95.12 89 | 95.75 66 | 97.75 87 | 88.59 95 | 92.58 165 | 97.81 64 | 93.99 47 | 96.80 66 | 95.90 165 | 90.10 138 | 99.41 32 | 91.60 114 | 99.58 39 | 99.26 40 |
|
ACMP | | 88.15 13 | 95.71 56 | 95.43 76 | 96.54 43 | 98.17 65 | 91.73 56 | 94.24 116 | 98.08 33 | 89.46 157 | 96.61 75 | 96.47 128 | 95.85 16 | 99.12 76 | 90.45 125 | 99.56 41 | 98.77 98 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
v10 | | | 94.68 100 | 95.27 83 | 92.90 167 | 96.57 151 | 80.15 210 | 94.65 99 | 97.57 84 | 90.68 134 | 97.43 46 | 98.00 47 | 88.18 166 | 99.15 69 | 94.84 24 | 99.55 42 | 99.41 28 |
|
PS-MVSNAJss | | | 96.01 50 | 96.04 48 | 95.89 59 | 98.82 21 | 88.51 99 | 95.57 64 | 97.88 58 | 88.72 177 | 98.81 6 | 98.86 10 | 90.77 120 | 99.60 8 | 95.43 14 | 99.53 43 | 99.57 14 |
|
TDRefinement | | | 97.68 3 | 97.60 3 | 97.93 2 | 99.02 10 | 95.95 6 | 98.61 3 | 98.81 4 | 97.41 8 | 97.28 50 | 98.46 28 | 94.62 45 | 98.84 124 | 94.64 26 | 99.53 43 | 98.99 70 |
|
pcd1.5k->3k | | | 41.03 342 | 43.65 345 | 33.18 355 | 98.74 25 | 0.00 374 | 0.00 365 | 97.57 84 | 0.00 369 | 0.00 371 | 0.00 371 | 97.01 5 | 0.00 371 | 0.00 368 | 99.52 45 | 99.53 16 |
|
IS-MVSNet | | | 94.49 107 | 94.35 108 | 94.92 91 | 98.25 60 | 86.46 130 | 97.13 14 | 94.31 236 | 96.24 23 | 96.28 89 | 96.36 142 | 82.88 232 | 99.35 48 | 88.19 174 | 99.52 45 | 98.96 76 |
|
nrg030 | | | 96.32 40 | 96.55 27 | 95.62 70 | 97.83 84 | 88.55 97 | 95.77 58 | 98.29 18 | 92.68 72 | 98.03 27 | 97.91 53 | 95.13 34 | 98.95 102 | 93.85 43 | 99.49 47 | 99.36 35 |
|
MP-MVS-pluss | | | 96.08 48 | 95.92 54 | 96.57 42 | 99.06 8 | 91.21 60 | 93.25 147 | 98.32 12 | 87.89 198 | 96.86 64 | 97.38 78 | 95.55 20 | 99.39 40 | 95.47 13 | 99.47 48 | 99.11 52 |
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
mvs_tets | | | 96.83 9 | 96.71 21 | 97.17 25 | 98.83 20 | 92.51 44 | 96.58 27 | 97.61 80 | 87.57 204 | 98.80 7 | 98.90 9 | 96.50 10 | 99.59 12 | 96.15 9 | 99.47 48 | 99.40 31 |
|
v8 | | | 94.65 101 | 95.29 81 | 92.74 175 | 96.65 142 | 79.77 229 | 94.59 101 | 97.17 124 | 91.86 102 | 97.47 44 | 97.93 50 | 88.16 168 | 99.08 79 | 94.32 32 | 99.47 48 | 99.38 32 |
|
CLD-MVS | | | 91.82 185 | 91.41 189 | 93.04 155 | 96.37 165 | 83.65 169 | 86.82 318 | 97.29 116 | 84.65 244 | 92.27 223 | 89.67 320 | 92.20 88 | 97.85 236 | 83.95 226 | 99.47 48 | 97.62 173 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
jajsoiax | | | 96.59 26 | 96.42 29 | 97.12 27 | 98.76 24 | 92.49 45 | 96.44 35 | 97.42 98 | 86.96 214 | 98.71 10 | 98.72 17 | 95.36 25 | 99.56 16 | 95.92 10 | 99.45 52 | 99.32 37 |
|
test_djsdf | | | 96.62 22 | 96.49 28 | 97.01 30 | 98.55 38 | 91.77 55 | 97.15 12 | 97.37 102 | 88.98 165 | 98.26 23 | 98.86 10 | 93.35 66 | 99.60 8 | 96.41 6 | 99.45 52 | 99.66 6 |
|
CP-MVS | | | 96.44 35 | 96.08 45 | 97.54 9 | 98.29 56 | 94.62 10 | 96.80 20 | 98.08 33 | 92.67 74 | 95.08 145 | 96.39 138 | 94.77 44 | 99.42 27 | 93.17 70 | 99.44 54 | 98.58 113 |
|
COLMAP_ROB | ![Method available under an open source license with copyleft or other restrictive terms. copyleft](img/icon_copyleft.png) | 91.06 5 | 96.75 16 | 96.62 24 | 97.13 26 | 98.38 50 | 94.31 12 | 96.79 21 | 98.32 12 | 96.69 15 | 96.86 64 | 97.56 66 | 95.48 21 | 98.77 142 | 90.11 139 | 99.44 54 | 98.31 124 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
zzz-MVS | | | 96.47 31 | 96.14 40 | 97.47 11 | 98.95 14 | 94.05 18 | 93.69 133 | 97.62 77 | 94.46 41 | 96.29 86 | 96.94 99 | 93.56 57 | 99.37 45 | 94.29 35 | 99.42 56 | 98.99 70 |
|
MTAPA | | | 96.65 21 | 96.38 31 | 97.47 11 | 98.95 14 | 94.05 18 | 95.88 55 | 97.62 77 | 94.46 41 | 96.29 86 | 96.94 99 | 93.56 57 | 99.37 45 | 94.29 35 | 99.42 56 | 98.99 70 |
|
pm-mvs1 | | | 95.43 64 | 95.94 52 | 93.93 130 | 98.38 50 | 85.08 154 | 95.46 68 | 97.12 128 | 91.84 103 | 97.28 50 | 98.46 28 | 95.30 28 | 97.71 247 | 90.17 137 | 99.42 56 | 98.99 70 |
|
XVG-ACMP-BASELINE | | | 95.68 57 | 95.34 78 | 96.69 40 | 98.40 48 | 93.04 38 | 94.54 108 | 98.05 38 | 90.45 140 | 96.31 84 | 96.76 112 | 92.91 76 | 98.72 149 | 91.19 121 | 99.42 56 | 98.32 122 |
|
wuyk23d | | | 87.83 258 | 90.79 204 | 78.96 345 | 90.46 331 | 88.63 93 | 92.72 161 | 90.67 291 | 91.65 113 | 98.68 11 | 97.64 63 | 96.06 14 | 77.53 365 | 59.84 355 | 99.41 60 | 70.73 362 |
|
anonymousdsp | | | 96.74 17 | 96.42 29 | 97.68 7 | 98.00 76 | 94.03 21 | 96.97 16 | 97.61 80 | 87.68 203 | 98.45 21 | 98.77 15 | 94.20 52 | 99.50 19 | 96.70 5 | 99.40 61 | 99.53 16 |
|
v17 | | | 94.80 94 | 95.46 72 | 92.83 170 | 96.76 138 | 80.02 219 | 94.85 89 | 97.40 100 | 92.23 89 | 97.45 45 | 98.04 43 | 88.46 161 | 99.06 82 | 94.56 27 | 99.40 61 | 99.41 28 |
|
SixPastTwentyTwo | | | 94.91 87 | 95.21 85 | 93.98 126 | 98.52 42 | 83.19 175 | 95.93 52 | 94.84 222 | 94.86 35 | 98.49 17 | 98.74 16 | 81.45 246 | 99.60 8 | 94.69 25 | 99.39 63 | 99.15 48 |
|
HPM-MVS_fast | | | 97.01 6 | 96.89 17 | 97.39 18 | 99.12 6 | 93.92 24 | 97.16 11 | 98.17 27 | 93.11 64 | 96.48 78 | 97.36 81 | 96.92 6 | 99.34 49 | 94.31 33 | 99.38 64 | 98.92 83 |
|
HPM-MVS | ![Method available under an open source license with copyleft or other restrictive terms. copyleft](img/icon_copyleft.png) | | 96.81 12 | 96.62 24 | 97.36 20 | 98.89 17 | 93.53 34 | 97.51 8 | 98.44 7 | 92.35 84 | 95.95 105 | 96.41 133 | 96.71 8 | 99.42 27 | 93.99 42 | 99.36 65 | 99.13 50 |
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023 |
ACMMP_Plus | | | 96.21 44 | 96.12 42 | 96.49 46 | 98.90 16 | 91.42 58 | 94.57 104 | 98.03 41 | 90.42 142 | 96.37 81 | 97.35 82 | 95.68 18 | 99.25 60 | 94.44 31 | 99.34 66 | 98.80 94 |
|
SteuartSystems-ACMMP | | | 96.40 37 | 96.30 33 | 96.71 39 | 98.63 28 | 91.96 51 | 95.70 59 | 98.01 44 | 93.34 62 | 96.64 73 | 96.57 123 | 94.99 41 | 99.36 47 | 93.48 55 | 99.34 66 | 98.82 92 |
Skip Steuart: Steuart Systems R&D Blog. |
ACMMP | ![Method available under an open source license with copyleft or other restrictive terms. copyleft](img/icon_copyleft.png) | | 96.61 23 | 96.34 32 | 97.43 15 | 98.61 31 | 93.88 25 | 96.95 17 | 98.18 26 | 92.26 87 | 96.33 82 | 96.84 109 | 95.10 36 | 99.40 36 | 93.47 56 | 99.33 68 | 99.02 67 |
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 |
ACMM | | 88.83 9 | 96.30 42 | 96.07 46 | 96.97 32 | 98.39 49 | 92.95 41 | 94.74 95 | 98.03 41 | 90.82 131 | 97.15 54 | 96.85 107 | 96.25 13 | 99.00 94 | 93.10 73 | 99.33 68 | 98.95 77 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
v16 | | | 94.79 96 | 95.44 75 | 92.83 170 | 96.73 139 | 80.03 217 | 94.85 89 | 97.41 99 | 92.23 89 | 97.41 49 | 98.04 43 | 88.40 163 | 99.06 82 | 94.56 27 | 99.30 70 | 99.41 28 |
|
APDe-MVS | | | 96.46 32 | 96.64 23 | 95.93 56 | 97.68 96 | 89.38 81 | 96.90 18 | 98.41 10 | 92.52 78 | 97.43 46 | 97.92 51 | 95.11 35 | 99.50 19 | 94.45 30 | 99.30 70 | 98.92 83 |
|
SMA-MVS | | | 95.77 54 | 95.54 69 | 96.47 47 | 98.27 58 | 91.19 61 | 95.09 79 | 97.79 68 | 86.48 219 | 97.42 48 | 97.51 71 | 94.47 50 | 99.29 54 | 93.55 52 | 99.29 72 | 98.93 79 |
|
MP-MVS | ![Method available under an open source license with copyleft or other restrictive terms. copyleft](img/icon_copyleft.png) | | 96.14 46 | 95.68 66 | 97.51 10 | 98.81 22 | 94.06 16 | 96.10 47 | 97.78 69 | 92.73 71 | 93.48 186 | 96.72 116 | 94.23 51 | 99.42 27 | 91.99 102 | 99.29 72 | 99.05 63 |
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo. |
test_0402 | | | 95.73 55 | 96.22 37 | 94.26 120 | 98.19 64 | 85.77 147 | 93.24 148 | 97.24 120 | 96.88 14 | 97.69 37 | 97.77 59 | 94.12 53 | 99.13 74 | 91.54 117 | 99.29 72 | 97.88 153 |
|
ESAPD | | | 95.89 51 | 95.88 56 | 95.92 58 | 97.93 81 | 89.83 74 | 93.46 137 | 98.30 15 | 92.37 81 | 97.75 36 | 96.95 97 | 95.14 33 | 99.51 18 | 91.74 109 | 99.28 75 | 98.41 119 |
|
mPP-MVS | | | 96.46 32 | 96.05 47 | 97.69 5 | 98.62 29 | 94.65 9 | 96.45 33 | 97.74 70 | 92.59 77 | 95.47 126 | 96.68 118 | 94.50 48 | 99.42 27 | 93.10 73 | 99.26 76 | 98.99 70 |
|
ACMMP++ | | | | | | | | | | | | | | | | 99.25 77 | |
|
v18 | | | 94.63 102 | 95.26 84 | 92.74 175 | 96.60 149 | 79.81 227 | 94.64 100 | 97.37 102 | 91.87 101 | 97.26 52 | 97.91 53 | 88.13 169 | 99.04 87 | 94.30 34 | 99.24 78 | 99.38 32 |
|
CSCG | | | 94.69 99 | 94.75 95 | 94.52 108 | 97.55 102 | 87.87 110 | 95.01 85 | 97.57 84 | 92.68 72 | 96.20 94 | 93.44 253 | 91.92 95 | 98.78 138 | 89.11 160 | 99.24 78 | 96.92 205 |
|
TransMVSNet (Re) | | | 95.27 75 | 96.04 48 | 92.97 161 | 98.37 52 | 81.92 188 | 95.07 81 | 96.76 157 | 93.97 49 | 97.77 34 | 98.57 21 | 95.72 17 | 97.90 222 | 88.89 162 | 99.23 80 | 99.08 59 |
|
abl_6 | | | 97.31 5 | 97.12 14 | 97.86 3 | 98.54 39 | 95.32 8 | 96.61 25 | 98.35 11 | 95.81 30 | 97.55 40 | 97.44 75 | 96.51 9 | 99.40 36 | 94.06 41 | 99.23 80 | 98.85 90 |
|
PGM-MVS | | | 96.32 40 | 95.94 52 | 97.43 15 | 98.59 34 | 93.84 28 | 95.33 71 | 98.30 15 | 91.40 117 | 95.76 116 | 96.87 106 | 95.26 29 | 99.45 24 | 92.77 79 | 99.21 82 | 99.00 68 |
|
SD-MVS | | | 95.19 76 | 95.73 65 | 93.55 140 | 96.62 148 | 88.88 90 | 94.67 97 | 98.05 38 | 91.26 119 | 97.25 53 | 96.40 134 | 95.42 22 | 94.36 330 | 92.72 83 | 99.19 83 | 97.40 184 |
|
Vis-MVSNet (Re-imp) | | | 90.42 208 | 90.16 211 | 91.20 232 | 97.66 98 | 77.32 273 | 94.33 114 | 87.66 309 | 91.20 121 | 92.99 204 | 95.13 196 | 75.40 283 | 98.28 199 | 77.86 287 | 99.19 83 | 97.99 142 |
|
tfpnnormal | | | 94.27 114 | 94.87 94 | 92.48 190 | 97.71 92 | 80.88 200 | 94.55 107 | 95.41 214 | 93.70 54 | 96.67 72 | 97.72 60 | 91.40 104 | 98.18 211 | 87.45 183 | 99.18 85 | 98.36 120 |
|
FMVSNet1 | | | 94.84 92 | 95.13 88 | 93.97 127 | 97.60 99 | 84.29 159 | 95.99 48 | 96.56 164 | 92.38 80 | 97.03 61 | 98.53 23 | 90.12 135 | 98.98 95 | 88.78 164 | 99.16 86 | 98.65 105 |
|
ACMMPR | | | 96.46 32 | 96.14 40 | 97.41 17 | 98.60 32 | 93.82 29 | 96.30 43 | 97.96 51 | 92.35 84 | 95.57 124 | 96.61 121 | 94.93 43 | 99.41 32 | 93.78 45 | 99.15 87 | 99.00 68 |
|
HFP-MVS | | | 96.39 38 | 96.17 39 | 97.04 28 | 98.51 43 | 93.37 35 | 96.30 43 | 97.98 47 | 92.35 84 | 95.63 121 | 96.47 128 | 95.37 23 | 99.27 58 | 93.78 45 | 99.14 88 | 98.48 115 |
|
#test# | | | 95.89 51 | 95.51 70 | 97.04 28 | 98.51 43 | 93.37 35 | 95.14 77 | 97.98 47 | 89.34 159 | 95.63 121 | 96.47 128 | 95.37 23 | 99.27 58 | 91.99 102 | 99.14 88 | 98.48 115 |
|
VDD-MVS | | | 94.37 109 | 94.37 107 | 94.40 116 | 97.49 105 | 86.07 140 | 93.97 123 | 93.28 254 | 94.49 40 | 96.24 90 | 97.78 57 | 87.99 176 | 98.79 134 | 88.92 161 | 99.14 88 | 98.34 121 |
|
region2R | | | 96.41 36 | 96.09 44 | 97.38 19 | 98.62 29 | 93.81 31 | 96.32 40 | 97.96 51 | 92.26 87 | 95.28 134 | 96.57 123 | 95.02 39 | 99.41 32 | 93.63 49 | 99.11 91 | 98.94 78 |
|
Gipuma | ![Method available under an open source license with copyleft or other restrictive terms. copyleft](img/icon_copyleft.png) | | 95.31 71 | 95.80 62 | 93.81 135 | 97.99 79 | 90.91 65 | 96.42 36 | 97.95 53 | 96.69 15 | 91.78 232 | 98.85 12 | 91.77 97 | 95.49 313 | 91.72 110 | 99.08 92 | 95.02 274 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
GST-MVS | | | 96.24 43 | 95.99 51 | 97.00 31 | 98.65 27 | 92.71 43 | 95.69 61 | 98.01 44 | 92.08 96 | 95.74 117 | 96.28 145 | 95.22 31 | 99.42 27 | 93.17 70 | 99.06 93 | 98.88 85 |
|
OPM-MVS | | | 95.61 59 | 95.45 73 | 96.08 50 | 98.49 46 | 91.00 63 | 92.65 164 | 97.33 112 | 90.05 147 | 96.77 68 | 96.85 107 | 95.04 37 | 98.56 172 | 92.77 79 | 99.06 93 | 98.70 104 |
|
VPNet | | | 93.08 150 | 93.76 128 | 91.03 234 | 98.60 32 | 75.83 289 | 91.51 218 | 95.62 204 | 91.84 103 | 95.74 117 | 97.10 93 | 89.31 149 | 98.32 197 | 85.07 216 | 99.06 93 | 98.93 79 |
|
XVS | | | 96.49 29 | 96.18 38 | 97.44 13 | 98.56 35 | 93.99 22 | 96.50 31 | 97.95 53 | 94.58 37 | 94.38 163 | 96.49 125 | 94.56 46 | 99.39 40 | 93.57 50 | 99.05 96 | 98.93 79 |
|
X-MVStestdata | | | 90.70 204 | 88.45 234 | 97.44 13 | 98.56 35 | 93.99 22 | 96.50 31 | 97.95 53 | 94.58 37 | 94.38 163 | 26.89 366 | 94.56 46 | 99.39 40 | 93.57 50 | 99.05 96 | 98.93 79 |
|
test20.03 | | | 90.80 202 | 90.85 202 | 90.63 241 | 95.63 227 | 79.24 243 | 89.81 273 | 92.87 261 | 89.90 151 | 94.39 162 | 96.40 134 | 85.77 215 | 95.27 321 | 73.86 314 | 99.05 96 | 97.39 185 |
|
Anonymous20240529 | | | 95.50 62 | 95.83 60 | 94.50 109 | 97.33 111 | 85.93 143 | 95.19 76 | 96.77 156 | 96.64 17 | 97.61 39 | 98.05 42 | 93.23 69 | 98.79 134 | 88.60 169 | 99.04 99 | 98.78 96 |
|
testing_2 | | | 94.03 120 | 94.38 106 | 93.00 159 | 96.79 137 | 81.41 195 | 92.87 158 | 96.96 137 | 85.88 228 | 97.06 59 | 97.92 51 | 91.18 116 | 98.71 155 | 91.72 110 | 99.04 99 | 98.87 86 |
|
IterMVS-LS | | | 93.78 124 | 94.28 111 | 92.27 196 | 96.27 180 | 79.21 248 | 91.87 203 | 96.78 154 | 91.77 109 | 96.57 77 | 97.07 94 | 87.15 192 | 98.74 147 | 91.99 102 | 99.03 101 | 98.86 87 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
MVS_0304 | | | 92.99 155 | 92.54 164 | 94.35 118 | 94.67 263 | 86.06 141 | 91.16 226 | 97.92 57 | 90.01 148 | 88.33 300 | 94.41 221 | 87.02 195 | 99.22 63 | 90.36 130 | 99.00 102 | 97.76 163 |
|
AllTest | | | 94.88 90 | 94.51 103 | 96.00 51 | 98.02 74 | 92.17 46 | 95.26 74 | 98.43 8 | 90.48 138 | 95.04 146 | 96.74 114 | 92.54 84 | 97.86 233 | 85.11 214 | 98.98 103 | 97.98 143 |
|
TestCases | | | | | 96.00 51 | 98.02 74 | 92.17 46 | | 98.43 8 | 90.48 138 | 95.04 146 | 96.74 114 | 92.54 84 | 97.86 233 | 85.11 214 | 98.98 103 | 97.98 143 |
|
Patchmtry | | | 90.11 218 | 89.92 214 | 90.66 240 | 90.35 333 | 77.00 277 | 92.96 154 | 92.81 262 | 90.25 145 | 94.74 155 | 96.93 101 | 67.11 303 | 97.52 253 | 85.17 209 | 98.98 103 | 97.46 180 |
|
PHI-MVS | | | 94.34 112 | 93.80 125 | 95.95 53 | 95.65 224 | 91.67 57 | 94.82 92 | 97.86 59 | 87.86 199 | 93.04 203 | 94.16 232 | 91.58 100 | 98.78 138 | 90.27 134 | 98.96 106 | 97.41 182 |
|
ambc | | | | | 92.98 160 | 96.88 131 | 83.01 179 | 95.92 53 | 96.38 177 | | 96.41 79 | 97.48 73 | 88.26 164 | 97.80 239 | 89.96 144 | 98.93 107 | 98.12 136 |
|
EPNet | | | 89.80 224 | 88.25 237 | 94.45 114 | 83.91 367 | 86.18 138 | 93.87 128 | 87.07 314 | 91.16 123 | 80.64 354 | 94.72 214 | 78.83 261 | 98.89 108 | 85.17 209 | 98.89 108 | 98.28 126 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
EPP-MVSNet | | | 93.91 122 | 93.68 134 | 94.59 105 | 98.08 71 | 85.55 150 | 97.44 9 | 94.03 241 | 94.22 44 | 94.94 149 | 96.19 156 | 82.07 240 | 99.57 13 | 87.28 187 | 98.89 108 | 98.65 105 |
|
v1192 | | | 93.49 133 | 93.78 126 | 92.62 182 | 96.16 189 | 79.62 235 | 91.83 211 | 97.22 122 | 86.07 224 | 96.10 100 | 96.38 140 | 87.22 190 | 99.02 91 | 94.14 40 | 98.88 110 | 99.22 43 |
|
v1144 | | | 93.50 132 | 93.81 124 | 92.57 184 | 96.28 179 | 79.61 236 | 91.86 207 | 96.96 137 | 86.95 215 | 95.91 111 | 96.32 143 | 87.65 180 | 98.96 100 | 93.51 53 | 98.88 110 | 99.13 50 |
|
APD-MVS_3200maxsize | | | 96.82 10 | 96.65 22 | 97.32 22 | 97.95 80 | 93.82 29 | 96.31 41 | 98.25 19 | 95.51 31 | 96.99 62 | 97.05 96 | 95.63 19 | 99.39 40 | 93.31 63 | 98.88 110 | 98.75 99 |
|
APD-MVS | ![Method available under an open source license with copyleft or other restrictive terms. copyleft](img/icon_copyleft.png) | | 95.00 83 | 94.69 97 | 95.93 56 | 97.38 108 | 90.88 66 | 94.59 101 | 97.81 64 | 89.22 163 | 95.46 128 | 96.17 158 | 93.42 62 | 99.34 49 | 89.30 152 | 98.87 113 | 97.56 177 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
OMC-MVS | | | 94.22 116 | 93.69 133 | 95.81 62 | 97.25 112 | 91.27 59 | 92.27 185 | 97.40 100 | 87.10 212 | 94.56 159 | 95.42 187 | 93.74 55 | 98.11 214 | 86.62 195 | 98.85 114 | 98.06 137 |
|
v144192 | | | 93.20 149 | 93.54 139 | 92.16 201 | 96.05 195 | 78.26 262 | 91.95 195 | 97.14 125 | 84.98 240 | 95.96 104 | 96.11 159 | 87.08 194 | 99.04 87 | 93.79 44 | 98.84 115 | 99.17 46 |
|
v1921920 | | | 93.26 144 | 93.61 136 | 92.19 199 | 96.04 198 | 78.31 261 | 91.88 202 | 97.24 120 | 85.17 234 | 96.19 96 | 96.19 156 | 86.76 203 | 99.05 84 | 94.18 39 | 98.84 115 | 99.22 43 |
|
DP-MVS | | | 95.62 58 | 95.84 59 | 94.97 90 | 97.16 116 | 88.62 94 | 94.54 108 | 97.64 76 | 96.94 13 | 96.58 76 | 97.32 83 | 93.07 73 | 98.72 149 | 90.45 125 | 98.84 115 | 97.57 175 |
|
divwei89l23v2f112 | | | 93.42 137 | 93.76 128 | 92.41 192 | 96.37 165 | 79.24 243 | 91.84 208 | 96.38 177 | 88.33 189 | 95.86 113 | 96.23 151 | 87.41 186 | 98.89 108 | 92.61 88 | 98.83 118 | 99.09 56 |
|
VDDNet | | | 94.03 120 | 94.27 113 | 93.31 148 | 98.87 18 | 82.36 184 | 95.51 67 | 91.78 283 | 97.19 10 | 96.32 83 | 98.60 20 | 84.24 225 | 98.75 144 | 87.09 188 | 98.83 118 | 98.81 93 |
|
v1 | | | 93.43 135 | 93.77 127 | 92.41 192 | 96.37 165 | 79.24 243 | 91.84 208 | 96.38 177 | 88.33 189 | 95.87 112 | 96.22 154 | 87.45 184 | 98.89 108 | 92.61 88 | 98.83 118 | 99.09 56 |
|
v1141 | | | 93.42 137 | 93.76 128 | 92.40 194 | 96.37 165 | 79.24 243 | 91.84 208 | 96.38 177 | 88.33 189 | 95.86 113 | 96.23 151 | 87.41 186 | 98.89 108 | 92.61 88 | 98.82 121 | 99.08 59 |
|
CPTT-MVS | | | 94.74 97 | 94.12 116 | 96.60 41 | 98.15 66 | 93.01 39 | 95.84 56 | 97.66 75 | 89.21 164 | 93.28 193 | 95.46 184 | 88.89 155 | 98.98 95 | 89.80 145 | 98.82 121 | 97.80 161 |
|
ACMMP++_ref | | | | | | | | | | | | | | | | 98.82 121 | |
|
v2v482 | | | 93.29 141 | 93.63 135 | 92.29 195 | 96.35 173 | 78.82 255 | 91.77 214 | 96.28 182 | 88.45 185 | 95.70 120 | 96.26 147 | 86.02 214 | 98.90 106 | 93.02 76 | 98.81 124 | 99.14 49 |
|
USDC | | | 89.02 233 | 89.08 222 | 88.84 283 | 95.07 247 | 74.50 304 | 88.97 292 | 96.39 176 | 73.21 323 | 93.27 194 | 96.28 145 | 82.16 239 | 96.39 297 | 77.55 291 | 98.80 125 | 95.62 259 |
|
tttt0517 | | | 89.81 223 | 88.90 229 | 92.55 188 | 97.00 124 | 79.73 233 | 95.03 83 | 83.65 345 | 89.88 152 | 95.30 132 | 94.79 211 | 53.64 358 | 99.39 40 | 91.99 102 | 98.79 126 | 98.54 114 |
|
PMVS | ![Method available under an open source license with copyleft or other restrictive terms. copyleft](img/icon_copyleft.png) | 87.21 14 | 94.97 84 | 95.33 79 | 93.91 131 | 98.97 13 | 97.16 2 | 95.54 66 | 95.85 198 | 96.47 19 | 93.40 189 | 97.46 74 | 95.31 27 | 95.47 314 | 86.18 203 | 98.78 127 | 89.11 348 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
TinyColmap | | | 92.00 184 | 92.76 157 | 89.71 260 | 95.62 228 | 77.02 276 | 90.72 238 | 96.17 190 | 87.70 202 | 95.26 135 | 96.29 144 | 92.54 84 | 96.45 294 | 81.77 246 | 98.77 128 | 95.66 257 |
|
v1240 | | | 93.29 141 | 93.71 132 | 92.06 204 | 96.01 199 | 77.89 266 | 91.81 212 | 97.37 102 | 85.12 236 | 96.69 71 | 96.40 134 | 86.67 204 | 99.07 81 | 94.51 29 | 98.76 129 | 99.22 43 |
|
DeepPCF-MVS | | 90.46 6 | 94.20 117 | 93.56 138 | 96.14 48 | 95.96 208 | 92.96 40 | 89.48 279 | 97.46 96 | 85.14 235 | 96.23 91 | 95.42 187 | 93.19 70 | 98.08 215 | 90.37 129 | 98.76 129 | 97.38 187 |
|
Anonymous20231206 | | | 88.77 240 | 88.29 236 | 90.20 254 | 96.31 177 | 78.81 256 | 89.56 278 | 93.49 252 | 74.26 317 | 92.38 217 | 95.58 179 | 82.21 238 | 95.43 316 | 72.07 324 | 98.75 131 | 96.34 231 |
|
UGNet | | | 93.08 150 | 92.50 166 | 94.79 96 | 93.87 283 | 87.99 108 | 95.07 81 | 94.26 238 | 90.64 135 | 87.33 314 | 97.67 62 | 86.89 201 | 98.49 182 | 88.10 176 | 98.71 132 | 97.91 150 |
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 |
LFMVS | | | 91.33 197 | 91.16 197 | 91.82 209 | 96.27 180 | 79.36 240 | 95.01 85 | 85.61 326 | 96.04 28 | 94.82 152 | 97.06 95 | 72.03 291 | 98.46 188 | 84.96 217 | 98.70 133 | 97.65 171 |
|
HPM-MVS++ | ![Method available under an open source license with copyleft or other restrictive terms. copyleft](img/icon_copyleft.png) | | 95.02 82 | 94.39 105 | 96.91 35 | 97.88 82 | 93.58 33 | 94.09 119 | 96.99 135 | 91.05 124 | 92.40 216 | 95.22 193 | 91.03 118 | 99.25 60 | 92.11 97 | 98.69 134 | 97.90 151 |
|
FMVSNet2 | | | 92.78 162 | 92.73 159 | 92.95 163 | 95.40 235 | 81.98 187 | 94.18 118 | 95.53 211 | 88.63 178 | 96.05 101 | 97.37 79 | 81.31 249 | 98.81 132 | 87.38 186 | 98.67 135 | 98.06 137 |
|
DeepC-MVS_fast | | 89.96 7 | 93.73 125 | 93.44 142 | 94.60 104 | 96.14 190 | 87.90 109 | 93.36 140 | 97.14 125 | 85.53 232 | 93.90 177 | 95.45 185 | 91.30 108 | 98.59 168 | 89.51 149 | 98.62 136 | 97.31 190 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
testmv | | | 88.46 245 | 88.11 243 | 89.48 264 | 96.00 200 | 76.14 283 | 86.20 324 | 93.75 246 | 84.48 245 | 93.57 184 | 95.52 183 | 80.91 253 | 95.09 322 | 63.97 351 | 98.61 137 | 97.22 194 |
|
114514_t | | | 90.51 206 | 89.80 215 | 92.63 181 | 98.00 76 | 82.24 185 | 93.40 139 | 97.29 116 | 65.84 353 | 89.40 283 | 94.80 210 | 86.99 196 | 98.75 144 | 83.88 227 | 98.61 137 | 96.89 208 |
|
CDPH-MVS | | | 92.67 166 | 91.83 177 | 95.18 85 | 96.94 127 | 88.46 102 | 90.70 239 | 97.07 129 | 77.38 302 | 92.34 221 | 95.08 198 | 92.67 82 | 98.88 112 | 85.74 205 | 98.57 139 | 98.20 131 |
|
test_prior3 | | | 93.29 141 | 92.85 154 | 94.61 100 | 95.95 209 | 87.23 117 | 90.21 255 | 97.36 108 | 89.33 160 | 90.77 253 | 94.81 207 | 90.41 131 | 98.68 158 | 88.21 172 | 98.55 140 | 97.93 147 |
|
test_prior2 | | | | | | | | 90.21 255 | | 89.33 160 | 90.77 253 | 94.81 207 | 90.41 131 | | 88.21 172 | 98.55 140 | |
|
LCM-MVSNet-Re | | | 94.20 117 | 94.58 101 | 93.04 155 | 95.91 212 | 83.13 177 | 93.79 130 | 99.19 2 | 92.00 97 | 98.84 5 | 98.04 43 | 93.64 56 | 99.02 91 | 81.28 251 | 98.54 142 | 96.96 203 |
|
Patchmatch-RL test | | | 88.81 239 | 88.52 233 | 89.69 263 | 95.33 242 | 79.94 222 | 86.22 323 | 92.71 266 | 78.46 296 | 95.80 115 | 94.18 231 | 66.25 311 | 95.33 319 | 89.22 158 | 98.53 143 | 93.78 304 |
|
Anonymous202405211 | | | 92.58 169 | 92.50 166 | 92.83 170 | 96.55 152 | 83.22 174 | 92.43 177 | 91.64 284 | 94.10 46 | 95.59 123 | 96.64 119 | 81.88 244 | 97.50 254 | 85.12 213 | 98.52 144 | 97.77 162 |
|
CNVR-MVS | | | 94.58 104 | 94.29 110 | 95.46 76 | 96.94 127 | 89.35 82 | 91.81 212 | 96.80 152 | 89.66 155 | 93.90 177 | 95.44 186 | 92.80 80 | 98.72 149 | 92.74 81 | 98.52 144 | 98.32 122 |
|
HQP_MVS | | | 94.26 115 | 93.93 119 | 95.23 83 | 97.71 92 | 88.12 106 | 94.56 105 | 97.81 64 | 91.74 111 | 93.31 190 | 95.59 176 | 86.93 198 | 98.95 102 | 89.26 156 | 98.51 146 | 98.60 111 |
|
plane_prior5 | | | | | | | | | 97.81 64 | | | | | 98.95 102 | 89.26 156 | 98.51 146 | 98.60 111 |
|
v1neww | | | 93.58 130 | 93.92 121 | 92.56 185 | 96.64 146 | 79.77 229 | 92.50 172 | 96.41 172 | 88.55 182 | 95.93 108 | 96.24 149 | 88.08 171 | 98.87 118 | 92.45 94 | 98.50 148 | 99.05 63 |
|
v7new | | | 93.58 130 | 93.92 121 | 92.56 185 | 96.64 146 | 79.77 229 | 92.50 172 | 96.41 172 | 88.55 182 | 95.93 108 | 96.24 149 | 88.08 171 | 98.87 118 | 92.45 94 | 98.50 148 | 99.05 63 |
|
v6 | | | 93.59 129 | 93.93 119 | 92.56 185 | 96.65 142 | 79.77 229 | 92.50 172 | 96.40 174 | 88.55 182 | 95.94 107 | 96.23 151 | 88.13 169 | 98.87 118 | 92.46 93 | 98.50 148 | 99.06 62 |
|
thisisatest0530 | | | 88.69 242 | 87.52 254 | 92.20 198 | 96.33 175 | 79.36 240 | 92.81 159 | 84.01 344 | 86.44 220 | 93.67 182 | 92.68 269 | 53.62 359 | 99.25 60 | 89.65 148 | 98.45 151 | 98.00 141 |
|
train_agg | | | 92.71 165 | 91.83 177 | 95.35 77 | 96.45 162 | 89.46 76 | 90.60 242 | 96.92 142 | 79.37 287 | 90.49 260 | 94.39 224 | 91.20 113 | 98.88 112 | 88.66 167 | 98.43 152 | 97.72 165 |
|
agg_prior3 | | | 92.56 172 | 91.62 182 | 95.35 77 | 96.39 164 | 89.45 78 | 90.61 241 | 96.82 150 | 78.82 295 | 90.03 268 | 94.14 233 | 90.72 125 | 98.88 112 | 88.66 167 | 98.43 152 | 97.72 165 |
|
test9_res | | | | | | | | | | | | | | | 88.16 175 | 98.40 154 | 97.83 157 |
|
TSAR-MVS + GP. | | | 93.07 152 | 92.41 168 | 95.06 88 | 95.82 214 | 90.87 67 | 90.97 231 | 92.61 270 | 88.04 195 | 94.61 158 | 93.79 244 | 88.08 171 | 97.81 238 | 89.41 151 | 98.39 155 | 96.50 225 |
|
VNet | | | 92.67 166 | 92.96 151 | 91.79 210 | 96.27 180 | 80.15 210 | 91.95 195 | 94.98 219 | 92.19 92 | 94.52 161 | 96.07 160 | 87.43 185 | 97.39 263 | 84.83 218 | 98.38 156 | 97.83 157 |
|
GBi-Net | | | 93.21 147 | 92.96 151 | 93.97 127 | 95.40 235 | 84.29 159 | 95.99 48 | 96.56 164 | 88.63 178 | 95.10 142 | 98.53 23 | 81.31 249 | 98.98 95 | 86.74 191 | 98.38 156 | 98.65 105 |
|
test1 | | | 93.21 147 | 92.96 151 | 93.97 127 | 95.40 235 | 84.29 159 | 95.99 48 | 96.56 164 | 88.63 178 | 95.10 142 | 98.53 23 | 81.31 249 | 98.98 95 | 86.74 191 | 98.38 156 | 98.65 105 |
|
FMVSNet3 | | | 90.78 203 | 90.32 210 | 92.16 201 | 93.03 296 | 79.92 223 | 92.54 166 | 94.95 220 | 86.17 223 | 95.10 142 | 96.01 162 | 69.97 297 | 98.75 144 | 86.74 191 | 98.38 156 | 97.82 160 |
|
MVS_111021_HR | | | 93.63 128 | 93.42 143 | 94.26 120 | 96.65 142 | 86.96 123 | 89.30 285 | 96.23 186 | 88.36 188 | 93.57 184 | 94.60 217 | 93.45 59 | 97.77 242 | 90.23 135 | 98.38 156 | 98.03 139 |
|
agg_prior1 | | | 92.60 168 | 91.76 180 | 95.10 87 | 96.20 185 | 88.89 88 | 90.37 250 | 96.88 147 | 79.67 284 | 90.21 263 | 94.41 221 | 91.30 108 | 98.78 138 | 88.46 171 | 98.37 161 | 97.64 172 |
|
agg_prior2 | | | | | | | | | | | | | | | 87.06 189 | 98.36 162 | 97.98 143 |
|
TSAR-MVS + MP. | | | 94.96 85 | 94.75 95 | 95.57 72 | 98.86 19 | 88.69 91 | 96.37 38 | 96.81 151 | 85.23 233 | 94.75 154 | 97.12 92 | 91.85 96 | 99.40 36 | 93.45 57 | 98.33 163 | 98.62 109 |
|
pmmvs-eth3d | | | 91.54 189 | 90.73 206 | 93.99 125 | 95.76 218 | 87.86 111 | 90.83 235 | 93.98 243 | 78.23 298 | 94.02 175 | 96.22 154 | 82.62 237 | 96.83 282 | 86.57 196 | 98.33 163 | 97.29 192 |
|
Regformer-1 | | | 94.55 105 | 94.33 109 | 95.19 84 | 92.83 299 | 88.54 98 | 91.87 203 | 95.84 199 | 93.99 47 | 95.95 105 | 95.04 200 | 92.00 92 | 98.79 134 | 93.14 72 | 98.31 165 | 98.23 128 |
|
Regformer-2 | | | 94.86 91 | 94.55 102 | 95.77 64 | 92.83 299 | 89.98 71 | 91.87 203 | 96.40 174 | 94.38 43 | 96.19 96 | 95.04 200 | 92.47 87 | 99.04 87 | 93.49 54 | 98.31 165 | 98.28 126 |
|
v7 | | | 93.66 126 | 93.97 118 | 92.73 177 | 96.55 152 | 80.15 210 | 92.54 166 | 96.99 135 | 87.36 205 | 95.99 102 | 96.48 126 | 88.18 166 | 98.94 105 | 93.35 62 | 98.31 165 | 99.09 56 |
|
3Dnovator+ | | 92.74 2 | 95.86 53 | 95.77 63 | 96.13 49 | 96.81 135 | 90.79 68 | 96.30 43 | 97.82 63 | 96.13 24 | 94.74 155 | 97.23 85 | 91.33 106 | 99.16 67 | 93.25 65 | 98.30 168 | 98.46 117 |
|
MVS_111021_LR | | | 93.66 126 | 93.28 146 | 94.80 95 | 96.25 183 | 90.95 64 | 90.21 255 | 95.43 213 | 87.91 196 | 93.74 181 | 94.40 223 | 92.88 78 | 96.38 298 | 90.39 127 | 98.28 169 | 97.07 198 |
|
CANet | | | 92.38 176 | 91.99 175 | 93.52 144 | 93.82 285 | 83.46 170 | 91.14 227 | 97.00 133 | 89.81 153 | 86.47 319 | 94.04 236 | 87.90 178 | 99.21 64 | 89.50 150 | 98.27 170 | 97.90 151 |
|
EI-MVSNet | | | 92.99 155 | 93.26 148 | 92.19 199 | 92.12 313 | 79.21 248 | 92.32 183 | 94.67 231 | 91.77 109 | 95.24 137 | 95.85 167 | 87.14 193 | 98.49 182 | 91.99 102 | 98.26 171 | 98.86 87 |
|
MVSTER | | | 89.32 228 | 88.75 231 | 91.03 234 | 90.10 335 | 76.62 279 | 90.85 234 | 94.67 231 | 82.27 265 | 95.24 137 | 95.79 171 | 61.09 338 | 98.49 182 | 90.49 124 | 98.26 171 | 97.97 146 |
|
MSLP-MVS++ | | | 93.25 146 | 93.88 123 | 91.37 223 | 96.34 174 | 82.81 180 | 93.11 149 | 97.74 70 | 89.37 158 | 94.08 173 | 95.29 192 | 90.40 133 | 96.35 300 | 90.35 131 | 98.25 173 | 94.96 275 |
|
LF4IMVS | | | 92.72 164 | 92.02 174 | 94.84 94 | 95.65 224 | 91.99 50 | 92.92 155 | 96.60 163 | 85.08 238 | 92.44 215 | 93.62 246 | 86.80 202 | 96.35 300 | 86.81 190 | 98.25 173 | 96.18 238 |
|
EI-MVSNet-UG-set | | | 94.35 111 | 94.27 113 | 94.59 105 | 92.46 305 | 85.87 144 | 92.42 178 | 94.69 229 | 93.67 58 | 96.13 98 | 95.84 169 | 91.20 113 | 98.86 121 | 93.78 45 | 98.23 175 | 99.03 66 |
|
PM-MVS | | | 93.33 140 | 92.67 161 | 95.33 79 | 96.58 150 | 94.06 16 | 92.26 186 | 92.18 275 | 85.92 227 | 96.22 92 | 96.61 121 | 85.64 219 | 95.99 306 | 90.35 131 | 98.23 175 | 95.93 246 |
|
EI-MVSNet-Vis-set | | | 94.36 110 | 94.28 111 | 94.61 100 | 92.55 304 | 85.98 142 | 92.44 176 | 94.69 229 | 93.70 54 | 96.12 99 | 95.81 170 | 91.24 110 | 98.86 121 | 93.76 48 | 98.22 177 | 98.98 75 |
|
V42 | | | 93.43 135 | 93.58 137 | 92.97 161 | 95.34 240 | 81.22 196 | 92.67 163 | 96.49 169 | 87.25 208 | 96.20 94 | 96.37 141 | 87.32 189 | 98.85 123 | 92.39 96 | 98.21 178 | 98.85 90 |
|
TAMVS | | | 90.16 217 | 89.05 223 | 93.49 145 | 96.49 156 | 86.37 133 | 90.34 252 | 92.55 271 | 80.84 275 | 92.99 204 | 94.57 219 | 81.94 243 | 98.20 208 | 73.51 315 | 98.21 178 | 95.90 249 |
|
K. test v3 | | | 93.37 139 | 93.27 147 | 93.66 136 | 98.05 72 | 82.62 181 | 94.35 113 | 86.62 316 | 96.05 27 | 97.51 42 | 98.85 12 | 76.59 281 | 99.65 3 | 93.21 67 | 98.20 180 | 98.73 102 |
|
DELS-MVS | | | 92.05 183 | 92.16 171 | 91.72 212 | 94.44 270 | 80.13 213 | 87.62 305 | 97.25 119 | 87.34 207 | 92.22 224 | 93.18 260 | 89.54 147 | 98.73 148 | 89.67 147 | 98.20 180 | 96.30 233 |
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 |
TAPA-MVS | | 88.58 10 | 92.49 174 | 91.75 181 | 94.73 97 | 96.50 155 | 89.69 75 | 92.91 156 | 97.68 74 | 78.02 299 | 92.79 208 | 94.10 234 | 90.85 119 | 97.96 221 | 84.76 220 | 98.16 182 | 96.54 216 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
LS3D | | | 96.11 47 | 95.83 60 | 96.95 34 | 94.75 256 | 94.20 14 | 97.34 10 | 97.98 47 | 97.31 9 | 95.32 131 | 96.77 110 | 93.08 72 | 99.20 65 | 91.79 108 | 98.16 182 | 97.44 181 |
|
Regformer-3 | | | 94.28 113 | 94.23 115 | 94.46 113 | 92.78 301 | 86.28 136 | 92.39 179 | 94.70 228 | 93.69 57 | 95.97 103 | 95.56 181 | 91.34 105 | 98.48 185 | 93.45 57 | 98.14 184 | 98.62 109 |
|
Regformer-4 | | | 94.90 88 | 94.67 99 | 95.59 71 | 92.78 301 | 89.02 85 | 92.39 179 | 95.91 195 | 94.50 39 | 96.41 79 | 95.56 181 | 92.10 90 | 99.01 93 | 94.23 37 | 98.14 184 | 98.74 100 |
|
DP-MVS Recon | | | 92.31 177 | 91.88 176 | 93.60 138 | 97.18 115 | 86.87 124 | 91.10 229 | 97.37 102 | 84.92 241 | 92.08 227 | 94.08 235 | 88.59 158 | 98.20 208 | 83.50 229 | 98.14 184 | 95.73 253 |
|
EG-PatchMatch MVS | | | 94.54 106 | 94.67 99 | 94.14 122 | 97.87 83 | 86.50 127 | 92.00 194 | 96.74 158 | 88.16 194 | 96.93 63 | 97.61 64 | 93.04 74 | 97.90 222 | 91.60 114 | 98.12 187 | 98.03 139 |
|
PCF-MVS | | 84.52 17 | 89.12 232 | 87.71 251 | 93.34 146 | 96.06 194 | 85.84 145 | 86.58 322 | 97.31 113 | 68.46 345 | 93.61 183 | 93.89 241 | 87.51 183 | 98.52 180 | 67.85 342 | 98.11 188 | 95.66 257 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
3Dnovator | | 92.54 3 | 94.80 94 | 94.90 92 | 94.47 112 | 95.47 233 | 87.06 121 | 96.63 24 | 97.28 118 | 91.82 106 | 94.34 166 | 97.41 76 | 90.60 128 | 98.65 162 | 92.47 92 | 98.11 188 | 97.70 167 |
|
PMMVS2 | | | 81.31 321 | 83.44 303 | 74.92 349 | 90.52 329 | 46.49 366 | 69.19 362 | 85.23 334 | 84.30 246 | 87.95 307 | 94.71 215 | 76.95 278 | 84.36 363 | 64.07 350 | 98.09 190 | 93.89 301 |
|
lessismore_v0 | | | | | 93.87 133 | 98.05 72 | 83.77 168 | | 80.32 362 | | 97.13 55 | 97.91 53 | 77.49 271 | 99.11 77 | 92.62 87 | 98.08 191 | 98.74 100 |
|
new-patchmatchnet | | | 88.97 235 | 90.79 204 | 83.50 334 | 94.28 274 | 55.83 364 | 85.34 328 | 93.56 250 | 86.18 222 | 95.47 126 | 95.73 174 | 83.10 230 | 96.51 291 | 85.40 208 | 98.06 192 | 98.16 132 |
|
plane_prior | | | | | | | 88.12 106 | 93.01 150 | | 88.98 165 | | | | | | 98.06 192 | |
|
PVSNet_BlendedMVS | | | 90.35 212 | 89.96 213 | 91.54 219 | 94.81 253 | 78.80 257 | 90.14 259 | 96.93 140 | 79.43 285 | 88.68 297 | 95.06 199 | 86.27 211 | 98.15 212 | 80.27 261 | 98.04 194 | 97.68 169 |
|
FMVSNet5 | | | 87.82 259 | 86.56 273 | 91.62 215 | 92.31 307 | 79.81 227 | 93.49 136 | 94.81 225 | 83.26 251 | 91.36 237 | 96.93 101 | 52.77 360 | 97.49 256 | 76.07 302 | 98.03 195 | 97.55 178 |
|
原ACMM1 | | | | | 92.87 168 | 96.91 130 | 84.22 162 | | 97.01 132 | 76.84 307 | 89.64 280 | 94.46 220 | 88.00 175 | 98.70 156 | 81.53 249 | 98.01 196 | 95.70 255 |
|
v148 | | | 92.87 160 | 93.29 144 | 91.62 215 | 96.25 183 | 77.72 268 | 91.28 224 | 95.05 218 | 89.69 154 | 95.93 108 | 96.04 161 | 87.34 188 | 98.38 193 | 90.05 142 | 97.99 197 | 98.78 96 |
|
ITE_SJBPF | | | | | 95.95 53 | 97.34 110 | 93.36 37 | | 96.55 167 | 91.93 98 | 94.82 152 | 95.39 190 | 91.99 93 | 97.08 273 | 85.53 207 | 97.96 198 | 97.41 182 |
|
test12 | | | | | 94.43 115 | 95.95 209 | 86.75 126 | | 96.24 185 | | 89.76 278 | | 89.79 143 | 98.79 134 | | 97.95 199 | 97.75 164 |
|
MCST-MVS | | | 92.91 158 | 92.51 165 | 94.10 123 | 97.52 103 | 85.72 148 | 91.36 223 | 97.13 127 | 80.33 277 | 92.91 207 | 94.24 228 | 91.23 111 | 98.72 149 | 89.99 143 | 97.93 200 | 97.86 155 |
|
CDS-MVSNet | | | 89.55 225 | 88.22 240 | 93.53 143 | 95.37 238 | 86.49 128 | 89.26 286 | 93.59 249 | 79.76 282 | 91.15 248 | 92.31 280 | 77.12 275 | 98.38 193 | 77.51 292 | 97.92 201 | 95.71 254 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
旧先验1 | | | | | | 96.20 185 | 84.17 163 | | 94.82 223 | | | 95.57 180 | 89.57 146 | | | 97.89 202 | 96.32 232 |
|
alignmvs | | | 93.26 144 | 92.85 154 | 94.50 109 | 95.70 220 | 87.45 114 | 93.45 138 | 95.76 200 | 91.58 114 | 95.25 136 | 92.42 278 | 81.96 242 | 98.72 149 | 91.61 113 | 97.87 203 | 97.33 189 |
|
testgi | | | 90.38 210 | 91.34 192 | 87.50 305 | 97.49 105 | 71.54 327 | 89.43 280 | 95.16 217 | 88.38 187 | 94.54 160 | 94.68 216 | 92.88 78 | 93.09 340 | 71.60 329 | 97.85 204 | 97.88 153 |
|
新几何1 | | | | | 93.17 152 | 97.16 116 | 87.29 116 | | 94.43 233 | 67.95 346 | 91.29 238 | 94.94 204 | 86.97 197 | 98.23 205 | 81.06 256 | 97.75 205 | 93.98 299 |
|
HQP3-MVS | | | | | | | | | 97.31 113 | | | | | | | 97.73 206 | |
|
HQP-MVS | | | 92.09 182 | 91.49 187 | 93.88 132 | 96.36 170 | 84.89 155 | 91.37 220 | 97.31 113 | 87.16 209 | 88.81 290 | 93.40 254 | 84.76 222 | 98.60 166 | 86.55 197 | 97.73 206 | 98.14 134 |
|
1121 | | | 90.26 215 | 89.23 219 | 93.34 146 | 97.15 118 | 87.40 115 | 91.94 197 | 94.39 234 | 67.88 347 | 91.02 251 | 94.91 205 | 86.91 200 | 98.59 168 | 81.17 254 | 97.71 208 | 94.02 298 |
|
CANet_DTU | | | 89.85 222 | 89.17 221 | 91.87 208 | 92.20 311 | 80.02 219 | 90.79 236 | 95.87 197 | 86.02 225 | 82.53 343 | 91.77 289 | 80.01 257 | 98.57 171 | 85.66 206 | 97.70 209 | 97.01 201 |
|
NCCC | | | 94.08 119 | 93.54 139 | 95.70 69 | 96.49 156 | 89.90 73 | 92.39 179 | 96.91 145 | 90.64 135 | 92.33 222 | 94.60 217 | 90.58 129 | 98.96 100 | 90.21 136 | 97.70 209 | 98.23 128 |
|
Vis-MVSNet | ![Method available under a permissive open source license. permissive](img/icon_permissive.png) | | 95.50 62 | 95.48 71 | 95.56 73 | 98.11 68 | 89.40 80 | 95.35 70 | 98.22 24 | 92.36 82 | 94.11 171 | 98.07 41 | 92.02 91 | 99.44 25 | 93.38 61 | 97.67 211 | 97.85 156 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
AdaColmap | ![Method available as binary. binary](img/icon_binary.png) | | 91.63 187 | 91.36 191 | 92.47 191 | 95.56 230 | 86.36 134 | 92.24 188 | 96.27 183 | 88.88 169 | 89.90 274 | 92.69 268 | 91.65 99 | 98.32 197 | 77.38 294 | 97.64 212 | 92.72 324 |
|
EPNet_dtu | | | 85.63 295 | 84.37 297 | 89.40 272 | 86.30 360 | 74.33 306 | 91.64 215 | 88.26 302 | 84.84 243 | 72.96 365 | 89.85 313 | 71.27 293 | 97.69 248 | 76.60 299 | 97.62 213 | 96.18 238 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
XVG-OURS | | | 94.72 98 | 94.12 116 | 96.50 45 | 98.00 76 | 94.23 13 | 91.48 219 | 98.17 27 | 90.72 132 | 95.30 132 | 96.47 128 | 87.94 177 | 96.98 276 | 91.41 119 | 97.61 214 | 98.30 125 |
|
canonicalmvs | | | 94.59 103 | 94.69 97 | 94.30 119 | 95.60 229 | 87.03 122 | 95.59 63 | 98.24 22 | 91.56 115 | 95.21 139 | 92.04 286 | 94.95 42 | 98.66 160 | 91.45 118 | 97.57 215 | 97.20 195 |
|
casdiffmvs1 | | | 93.02 154 | 93.00 150 | 93.07 154 | 95.65 224 | 82.54 182 | 94.79 94 | 97.35 110 | 80.09 279 | 92.18 225 | 97.51 71 | 89.25 150 | 98.84 124 | 92.65 85 | 97.52 216 | 97.83 157 |
|
XXY-MVS | | | 92.58 169 | 93.16 149 | 90.84 239 | 97.75 87 | 79.84 224 | 91.87 203 | 96.22 188 | 85.94 226 | 95.53 125 | 97.68 61 | 92.69 81 | 94.48 326 | 83.21 232 | 97.51 217 | 98.21 130 |
|
view600 | | | 88.32 248 | 87.94 246 | 89.46 266 | 96.49 156 | 73.31 312 | 93.95 124 | 84.46 339 | 93.02 66 | 94.18 167 | 92.68 269 | 63.33 328 | 98.56 172 | 75.87 305 | 97.50 218 | 96.51 218 |
|
view800 | | | 88.32 248 | 87.94 246 | 89.46 266 | 96.49 156 | 73.31 312 | 93.95 124 | 84.46 339 | 93.02 66 | 94.18 167 | 92.68 269 | 63.33 328 | 98.56 172 | 75.87 305 | 97.50 218 | 96.51 218 |
|
conf0.05thres1000 | | | 88.32 248 | 87.94 246 | 89.46 266 | 96.49 156 | 73.31 312 | 93.95 124 | 84.46 339 | 93.02 66 | 94.18 167 | 92.68 269 | 63.33 328 | 98.56 172 | 75.87 305 | 97.50 218 | 96.51 218 |
|
tfpn | | | 88.32 248 | 87.94 246 | 89.46 266 | 96.49 156 | 73.31 312 | 93.95 124 | 84.46 339 | 93.02 66 | 94.18 167 | 92.68 269 | 63.33 328 | 98.56 172 | 75.87 305 | 97.50 218 | 96.51 218 |
|
Effi-MVS+-dtu | | | 93.90 123 | 92.60 163 | 97.77 4 | 94.74 257 | 96.67 4 | 94.00 121 | 95.41 214 | 89.94 149 | 91.93 231 | 92.13 284 | 90.12 135 | 98.97 99 | 87.68 180 | 97.48 222 | 97.67 170 |
|
OpenMVS | ![Method available under an open source license with copyleft or other restrictive terms. copyleft](img/icon_copyleft.png) | 89.45 8 | 92.27 179 | 92.13 173 | 92.68 179 | 94.53 269 | 84.10 164 | 95.70 59 | 97.03 131 | 82.44 264 | 91.14 249 | 96.42 132 | 88.47 160 | 98.38 193 | 85.95 204 | 97.47 223 | 95.55 264 |
|
ab-mvs | | | 92.40 175 | 92.62 162 | 91.74 211 | 97.02 123 | 81.65 191 | 95.84 56 | 95.50 212 | 86.95 215 | 92.95 206 | 97.56 66 | 90.70 126 | 97.50 254 | 79.63 270 | 97.43 224 | 96.06 242 |
|
1111 | | | 80.36 329 | 81.32 317 | 77.48 346 | 94.61 266 | 44.56 367 | 81.59 347 | 90.66 292 | 86.78 217 | 90.60 258 | 93.52 251 | 30.37 371 | 90.67 349 | 66.36 346 | 97.42 225 | 97.20 195 |
|
thisisatest0515 | | | 84.72 300 | 82.99 307 | 89.90 257 | 92.96 297 | 75.33 297 | 84.36 336 | 83.42 346 | 77.37 303 | 88.27 303 | 86.65 341 | 53.94 357 | 98.72 149 | 82.56 238 | 97.40 226 | 95.67 256 |
|
test1235678 | | | 84.54 301 | 83.85 302 | 86.59 312 | 93.81 286 | 73.41 311 | 82.38 344 | 91.79 282 | 79.43 285 | 89.50 281 | 91.61 293 | 70.59 294 | 92.94 342 | 58.14 357 | 97.40 226 | 93.44 313 |
|
test222 | | | | | | 96.95 126 | 85.27 153 | 88.83 295 | 93.61 248 | 65.09 355 | 90.74 255 | 94.85 206 | 84.62 224 | | | 97.36 228 | 93.91 300 |
|
API-MVS | | | 91.52 190 | 91.61 183 | 91.26 228 | 94.16 275 | 86.26 137 | 94.66 98 | 94.82 223 | 91.17 122 | 92.13 226 | 91.08 299 | 90.03 141 | 97.06 274 | 79.09 275 | 97.35 229 | 90.45 345 |
|
diffmvs1 | | | 92.93 157 | 93.48 141 | 91.27 227 | 92.73 303 | 79.03 251 | 92.35 182 | 96.79 153 | 90.94 126 | 91.04 250 | 96.92 104 | 89.99 142 | 97.48 257 | 93.20 68 | 97.32 230 | 97.31 190 |
|
testdata | | | | | 91.03 234 | 96.87 132 | 82.01 186 | | 94.28 237 | 71.55 330 | 92.46 214 | 95.42 187 | 85.65 218 | 97.38 265 | 82.64 237 | 97.27 231 | 93.70 307 |
|
N_pmnet | | | 88.90 237 | 87.25 258 | 93.83 134 | 94.40 272 | 93.81 31 | 84.73 331 | 87.09 313 | 79.36 289 | 93.26 195 | 92.43 277 | 79.29 260 | 91.68 346 | 77.50 293 | 97.22 232 | 96.00 243 |
|
ppachtmachnet_test | | | 88.61 243 | 88.64 232 | 88.50 293 | 91.76 316 | 70.99 330 | 84.59 334 | 92.98 259 | 79.30 291 | 92.38 217 | 93.53 250 | 79.57 259 | 97.45 258 | 86.50 199 | 97.17 233 | 97.07 198 |
|
CNLPA | | | 91.72 186 | 91.20 195 | 93.26 149 | 96.17 188 | 91.02 62 | 91.14 227 | 95.55 210 | 90.16 146 | 90.87 252 | 93.56 249 | 86.31 210 | 94.40 329 | 79.92 269 | 97.12 234 | 94.37 289 |
|
Test4 | | | 91.41 196 | 91.25 194 | 91.89 207 | 95.35 239 | 80.32 206 | 90.97 231 | 96.92 142 | 81.96 267 | 95.11 141 | 93.81 243 | 81.34 248 | 98.48 185 | 88.71 166 | 97.08 235 | 96.87 210 |
|
jason | | | 89.17 231 | 88.32 235 | 91.70 213 | 95.73 219 | 80.07 214 | 88.10 302 | 93.22 256 | 71.98 329 | 90.09 265 | 92.79 264 | 78.53 265 | 98.56 172 | 87.43 184 | 97.06 236 | 96.46 227 |
jason: jason. |
RPSCF | | | 95.58 60 | 94.89 93 | 97.62 8 | 97.58 100 | 96.30 5 | 95.97 51 | 97.53 89 | 92.42 79 | 93.41 187 | 97.78 57 | 91.21 112 | 97.77 242 | 91.06 122 | 97.06 236 | 98.80 94 |
|
QAPM | | | 92.88 159 | 92.77 156 | 93.22 150 | 95.82 214 | 83.31 172 | 96.45 33 | 97.35 110 | 83.91 248 | 93.75 179 | 96.77 110 | 89.25 150 | 98.88 112 | 84.56 222 | 97.02 238 | 97.49 179 |
|
thres600view7 | | | 87.66 262 | 87.10 264 | 89.36 273 | 96.05 195 | 73.17 316 | 92.72 161 | 85.31 329 | 91.89 100 | 93.29 192 | 90.97 300 | 63.42 324 | 98.39 191 | 73.23 317 | 96.99 239 | 96.51 218 |
|
tfpn111 | | | 87.60 264 | 87.12 262 | 89.04 279 | 96.14 190 | 73.09 318 | 93.00 151 | 85.31 329 | 92.13 93 | 93.26 195 | 90.96 301 | 63.42 324 | 98.48 185 | 72.87 320 | 96.98 240 | 95.56 260 |
|
test_normal | | | 91.49 191 | 91.44 188 | 91.62 215 | 95.21 243 | 79.44 238 | 90.08 262 | 93.84 245 | 82.60 260 | 94.37 165 | 94.74 213 | 86.66 205 | 98.46 188 | 88.58 170 | 96.92 241 | 96.95 204 |
|
tfpn1000 | | | 86.83 284 | 86.23 280 | 88.64 288 | 95.53 231 | 75.25 298 | 93.57 134 | 82.28 356 | 89.27 162 | 91.46 235 | 89.24 323 | 57.22 351 | 97.86 233 | 80.63 259 | 96.88 242 | 92.81 321 |
|
0601test | | | 90.11 218 | 89.73 217 | 91.26 228 | 94.09 278 | 79.82 225 | 90.44 247 | 92.65 268 | 90.90 127 | 93.19 200 | 93.30 256 | 73.90 285 | 98.03 216 | 82.23 242 | 96.87 243 | 95.93 246 |
|
Anonymous20240521 | | | 90.11 218 | 89.73 217 | 91.26 228 | 94.09 278 | 79.82 225 | 90.44 247 | 92.65 268 | 90.90 127 | 93.19 200 | 93.30 256 | 73.90 285 | 98.03 216 | 82.23 242 | 96.87 243 | 95.93 246 |
|
HSP-MVS | | | 95.18 77 | 94.49 104 | 97.23 24 | 98.67 26 | 94.05 18 | 96.41 37 | 97.00 133 | 91.26 119 | 95.12 140 | 95.15 194 | 86.60 207 | 99.50 19 | 93.43 59 | 96.81 245 | 98.13 135 |
|
pmmvs5 | | | 87.87 256 | 87.14 261 | 90.07 255 | 93.26 293 | 76.97 278 | 88.89 294 | 92.18 275 | 73.71 321 | 88.36 299 | 93.89 241 | 76.86 279 | 96.73 285 | 80.32 260 | 96.81 245 | 96.51 218 |
|
PVSNet_Blended_VisFu | | | 91.63 187 | 91.20 195 | 92.94 164 | 97.73 91 | 83.95 166 | 92.14 190 | 97.46 96 | 78.85 294 | 92.35 219 | 94.98 203 | 84.16 226 | 99.08 79 | 86.36 201 | 96.77 247 | 95.79 251 |
|
MVSFormer | | | 92.18 180 | 92.23 170 | 92.04 205 | 94.74 257 | 80.06 215 | 97.15 12 | 97.37 102 | 88.98 165 | 88.83 288 | 92.79 264 | 77.02 276 | 99.60 8 | 96.41 6 | 96.75 248 | 96.46 227 |
|
lupinMVS | | | 88.34 247 | 87.31 256 | 91.45 221 | 94.74 257 | 80.06 215 | 87.23 311 | 92.27 274 | 71.10 333 | 88.83 288 | 91.15 297 | 77.02 276 | 98.53 179 | 86.67 194 | 96.75 248 | 95.76 252 |
|
conf0.01 | | | 86.95 281 | 86.04 281 | 89.70 261 | 95.99 201 | 75.66 290 | 93.28 141 | 82.70 349 | 88.81 170 | 91.26 239 | 88.01 332 | 58.77 343 | 97.89 224 | 78.93 276 | 96.60 250 | 95.56 260 |
|
conf0.002 | | | 86.95 281 | 86.04 281 | 89.70 261 | 95.99 201 | 75.66 290 | 93.28 141 | 82.70 349 | 88.81 170 | 91.26 239 | 88.01 332 | 58.77 343 | 97.89 224 | 78.93 276 | 96.60 250 | 95.56 260 |
|
thresconf0.02 | | | 86.69 286 | 86.04 281 | 88.64 288 | 95.99 201 | 75.66 290 | 93.28 141 | 82.70 349 | 88.81 170 | 91.26 239 | 88.01 332 | 58.77 343 | 97.89 224 | 78.93 276 | 96.60 250 | 92.36 328 |
|
tfpn_n400 | | | 86.69 286 | 86.04 281 | 88.64 288 | 95.99 201 | 75.66 290 | 93.28 141 | 82.70 349 | 88.81 170 | 91.26 239 | 88.01 332 | 58.77 343 | 97.89 224 | 78.93 276 | 96.60 250 | 92.36 328 |
|
tfpnconf | | | 86.69 286 | 86.04 281 | 88.64 288 | 95.99 201 | 75.66 290 | 93.28 141 | 82.70 349 | 88.81 170 | 91.26 239 | 88.01 332 | 58.77 343 | 97.89 224 | 78.93 276 | 96.60 250 | 92.36 328 |
|
tfpnview11 | | | 86.69 286 | 86.04 281 | 88.64 288 | 95.99 201 | 75.66 290 | 93.28 141 | 82.70 349 | 88.81 170 | 91.26 239 | 88.01 332 | 58.77 343 | 97.89 224 | 78.93 276 | 96.60 250 | 92.36 328 |
|
conf200view11 | | | 87.41 268 | 86.89 266 | 88.97 280 | 96.14 190 | 73.09 318 | 93.00 151 | 85.31 329 | 92.13 93 | 93.26 195 | 90.96 301 | 63.42 324 | 98.28 199 | 71.27 332 | 96.54 256 | 95.56 260 |
|
thres100view900 | | | 87.35 270 | 86.89 266 | 88.72 285 | 96.14 190 | 73.09 318 | 93.00 151 | 85.31 329 | 92.13 93 | 93.26 195 | 90.96 301 | 63.42 324 | 98.28 199 | 71.27 332 | 96.54 256 | 94.79 278 |
|
tfpn200view9 | | | 87.05 279 | 86.52 275 | 88.67 286 | 95.77 216 | 72.94 321 | 91.89 200 | 86.00 321 | 90.84 129 | 92.61 211 | 89.80 315 | 63.93 321 | 98.28 199 | 71.27 332 | 96.54 256 | 94.79 278 |
|
thres400 | | | 87.20 275 | 86.52 275 | 89.24 277 | 95.77 216 | 72.94 321 | 91.89 200 | 86.00 321 | 90.84 129 | 92.61 211 | 89.80 315 | 63.93 321 | 98.28 199 | 71.27 332 | 96.54 256 | 96.51 218 |
|
CMPMVS | ![Method available as binary. binary](img/icon_binary.png) | 68.83 22 | 87.28 271 | 85.67 290 | 92.09 203 | 88.77 348 | 85.42 151 | 90.31 253 | 94.38 235 | 70.02 340 | 88.00 306 | 93.30 256 | 73.78 287 | 94.03 334 | 75.96 304 | 96.54 256 | 96.83 212 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
diffmvs | | | 92.17 181 | 92.73 159 | 90.49 243 | 92.22 308 | 77.47 271 | 92.53 168 | 95.74 202 | 90.43 141 | 88.32 301 | 96.48 126 | 89.76 144 | 97.38 265 | 92.63 86 | 96.50 261 | 96.63 215 |
|
DI_MVS_plusplus_test | | | 91.42 195 | 91.41 189 | 91.46 220 | 95.34 240 | 79.06 250 | 90.58 244 | 93.74 247 | 82.59 261 | 94.69 157 | 94.76 212 | 86.54 208 | 98.44 190 | 87.93 178 | 96.49 262 | 96.87 210 |
|
pmmvs4 | | | 88.95 236 | 87.70 252 | 92.70 178 | 94.30 273 | 85.60 149 | 87.22 312 | 92.16 277 | 74.62 313 | 89.75 279 | 94.19 230 | 77.97 269 | 96.41 296 | 82.71 236 | 96.36 263 | 96.09 240 |
|
Fast-Effi-MVS+-dtu | | | 92.77 163 | 92.16 171 | 94.58 107 | 94.66 264 | 88.25 104 | 92.05 192 | 96.65 161 | 89.62 156 | 90.08 266 | 91.23 296 | 92.56 83 | 98.60 166 | 86.30 202 | 96.27 264 | 96.90 207 |
|
tfpn_ndepth | | | 85.85 293 | 85.15 294 | 87.98 299 | 95.19 245 | 75.36 296 | 92.79 160 | 83.18 348 | 86.97 213 | 89.92 272 | 86.43 345 | 57.44 350 | 97.85 236 | 78.18 285 | 96.22 265 | 90.72 343 |
|
MAR-MVS | | | 90.32 214 | 88.87 230 | 94.66 99 | 94.82 252 | 91.85 53 | 94.22 117 | 94.75 226 | 80.91 272 | 87.52 313 | 88.07 331 | 86.63 206 | 97.87 232 | 76.67 298 | 96.21 266 | 94.25 291 |
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 |
PVSNet_Blended | | | 88.74 241 | 88.16 242 | 90.46 245 | 94.81 253 | 78.80 257 | 86.64 320 | 96.93 140 | 74.67 312 | 88.68 297 | 89.18 324 | 86.27 211 | 98.15 212 | 80.27 261 | 96.00 267 | 94.44 288 |
|
F-COLMAP | | | 92.28 178 | 91.06 198 | 95.95 53 | 97.52 103 | 91.90 52 | 93.53 135 | 97.18 123 | 83.98 247 | 88.70 296 | 94.04 236 | 88.41 162 | 98.55 178 | 80.17 264 | 95.99 268 | 97.39 185 |
|
xiu_mvs_v1_base_debu | | | 91.47 192 | 91.52 184 | 91.33 224 | 95.69 221 | 81.56 192 | 89.92 267 | 96.05 192 | 83.22 252 | 91.26 239 | 90.74 305 | 91.55 101 | 98.82 127 | 89.29 153 | 95.91 269 | 93.62 309 |
|
xiu_mvs_v1_base | | | 91.47 192 | 91.52 184 | 91.33 224 | 95.69 221 | 81.56 192 | 89.92 267 | 96.05 192 | 83.22 252 | 91.26 239 | 90.74 305 | 91.55 101 | 98.82 127 | 89.29 153 | 95.91 269 | 93.62 309 |
|
xiu_mvs_v1_base_debi | | | 91.47 192 | 91.52 184 | 91.33 224 | 95.69 221 | 81.56 192 | 89.92 267 | 96.05 192 | 83.22 252 | 91.26 239 | 90.74 305 | 91.55 101 | 98.82 127 | 89.29 153 | 95.91 269 | 93.62 309 |
|
thres200 | | | 85.85 293 | 85.18 293 | 87.88 302 | 94.44 270 | 72.52 323 | 89.08 290 | 86.21 318 | 88.57 181 | 91.44 236 | 88.40 328 | 64.22 319 | 98.00 219 | 68.35 341 | 95.88 272 | 93.12 317 |
|
Patchmatch-test | | | 86.10 292 | 86.01 287 | 86.38 315 | 90.63 327 | 74.22 307 | 89.57 277 | 86.69 315 | 85.73 231 | 89.81 277 | 92.83 263 | 65.24 316 | 91.04 348 | 77.82 290 | 95.78 273 | 93.88 302 |
|
mvs-test1 | | | 93.07 152 | 91.80 179 | 96.89 36 | 94.74 257 | 95.83 7 | 92.17 189 | 95.41 214 | 89.94 149 | 89.85 275 | 90.59 311 | 90.12 135 | 98.88 112 | 87.68 180 | 95.66 274 | 95.97 244 |
|
cascas | | | 87.02 280 | 86.28 279 | 89.25 276 | 91.56 319 | 76.45 280 | 84.33 337 | 96.78 154 | 71.01 334 | 86.89 318 | 85.91 347 | 81.35 247 | 96.94 277 | 83.09 233 | 95.60 275 | 94.35 290 |
|
XVG-OURS-SEG-HR | | | 95.38 67 | 95.00 91 | 96.51 44 | 98.10 70 | 94.07 15 | 92.46 175 | 98.13 32 | 90.69 133 | 93.75 179 | 96.25 148 | 98.03 2 | 97.02 275 | 92.08 99 | 95.55 276 | 98.45 118 |
|
DSMNet-mixed | | | 82.21 315 | 81.56 314 | 84.16 331 | 89.57 340 | 70.00 334 | 90.65 240 | 77.66 365 | 54.99 364 | 83.30 339 | 97.57 65 | 77.89 270 | 90.50 352 | 66.86 345 | 95.54 277 | 91.97 334 |
|
MVS_Test | | | 92.57 171 | 93.29 144 | 90.40 246 | 93.53 289 | 75.85 287 | 92.52 169 | 96.96 137 | 88.73 176 | 92.35 219 | 96.70 117 | 90.77 120 | 98.37 196 | 92.53 91 | 95.49 278 | 96.99 202 |
|
testus | | | 82.09 317 | 81.78 312 | 83.03 336 | 92.35 306 | 64.37 355 | 79.44 352 | 93.27 255 | 73.08 324 | 87.06 316 | 85.21 350 | 76.80 280 | 89.27 356 | 53.30 360 | 95.48 279 | 95.46 266 |
|
MIMVSNet | | | 87.13 278 | 86.54 274 | 88.89 282 | 96.05 195 | 76.11 284 | 94.39 111 | 88.51 300 | 81.37 271 | 88.27 303 | 96.75 113 | 72.38 289 | 95.52 312 | 65.71 349 | 95.47 280 | 95.03 273 |
|
Fast-Effi-MVS+ | | | 91.28 198 | 90.86 201 | 92.53 189 | 95.45 234 | 82.53 183 | 89.25 288 | 96.52 168 | 85.00 239 | 89.91 273 | 88.55 327 | 92.94 75 | 98.84 124 | 84.72 221 | 95.44 281 | 96.22 236 |
|
BH-RMVSNet | | | 90.47 207 | 90.44 208 | 90.56 242 | 95.21 243 | 78.65 259 | 89.15 289 | 93.94 244 | 88.21 192 | 92.74 209 | 94.22 229 | 86.38 209 | 97.88 230 | 78.67 283 | 95.39 282 | 95.14 271 |
|
CHOSEN 1792x2688 | | | 87.19 276 | 85.92 289 | 91.00 237 | 97.13 120 | 79.41 239 | 84.51 335 | 95.60 205 | 64.14 356 | 90.07 267 | 94.81 207 | 78.26 267 | 97.14 272 | 73.34 316 | 95.38 283 | 96.46 227 |
|
Effi-MVS+ | | | 92.79 161 | 92.74 158 | 92.94 164 | 95.10 246 | 83.30 173 | 94.00 121 | 97.53 89 | 91.36 118 | 89.35 284 | 90.65 310 | 94.01 54 | 98.66 160 | 87.40 185 | 95.30 284 | 96.88 209 |
|
MG-MVS | | | 89.54 226 | 89.80 215 | 88.76 284 | 94.88 249 | 72.47 324 | 89.60 276 | 92.44 273 | 85.82 229 | 89.48 282 | 95.98 163 | 82.85 233 | 97.74 246 | 81.87 245 | 95.27 285 | 96.08 241 |
|
HyFIR lowres test | | | 87.19 276 | 85.51 291 | 92.24 197 | 97.12 121 | 80.51 204 | 85.03 329 | 96.06 191 | 66.11 352 | 91.66 233 | 92.98 262 | 70.12 296 | 99.14 72 | 75.29 310 | 95.23 286 | 97.07 198 |
|
BH-untuned | | | 90.68 205 | 90.90 199 | 90.05 256 | 95.98 207 | 79.57 237 | 90.04 263 | 94.94 221 | 87.91 196 | 94.07 174 | 93.00 261 | 87.76 179 | 97.78 241 | 79.19 274 | 95.17 287 | 92.80 322 |
|
pmmvs3 | | | 80.83 325 | 78.96 332 | 86.45 314 | 87.23 356 | 77.48 270 | 84.87 330 | 82.31 355 | 63.83 357 | 85.03 326 | 89.50 322 | 49.66 362 | 93.10 339 | 73.12 319 | 95.10 288 | 88.78 351 |
|
mvs_anonymous | | | 90.37 211 | 91.30 193 | 87.58 304 | 92.17 312 | 68.00 338 | 89.84 272 | 94.73 227 | 83.82 250 | 93.22 199 | 97.40 77 | 87.54 182 | 97.40 262 | 87.94 177 | 95.05 289 | 97.34 188 |
|
semantic-postprocess | | | | | 91.94 206 | 93.89 282 | 79.22 247 | | 93.51 251 | 91.53 116 | 95.37 130 | 96.62 120 | 77.17 274 | 98.90 106 | 91.89 107 | 94.95 290 | 97.70 167 |
|
test-LLR | | | 83.58 306 | 83.17 305 | 84.79 327 | 89.68 338 | 66.86 344 | 83.08 341 | 84.52 337 | 83.07 256 | 82.85 341 | 84.78 351 | 62.86 333 | 93.49 337 | 82.85 234 | 94.86 291 | 94.03 296 |
|
test-mter | | | 81.21 323 | 80.01 329 | 84.79 327 | 89.68 338 | 66.86 344 | 83.08 341 | 84.52 337 | 73.85 320 | 82.85 341 | 84.78 351 | 43.66 368 | 93.49 337 | 82.85 234 | 94.86 291 | 94.03 296 |
|
PatchMatch-RL | | | 89.18 230 | 88.02 245 | 92.64 180 | 95.90 213 | 92.87 42 | 88.67 298 | 91.06 288 | 80.34 276 | 90.03 268 | 91.67 291 | 83.34 228 | 94.42 328 | 76.35 301 | 94.84 293 | 90.64 344 |
|
OpenMVS_ROB | ![Method available under an open source license with copyleft or other restrictive terms. copyleft](img/icon_copyleft.png) | 85.12 16 | 89.52 227 | 89.05 223 | 90.92 238 | 94.58 268 | 81.21 197 | 91.10 229 | 93.41 253 | 77.03 306 | 93.41 187 | 93.99 240 | 83.23 229 | 97.80 239 | 79.93 268 | 94.80 294 | 93.74 306 |
|
our_test_3 | | | 87.55 265 | 87.59 253 | 87.44 306 | 91.76 316 | 70.48 331 | 83.83 340 | 90.55 294 | 79.79 281 | 92.06 228 | 92.17 283 | 78.63 264 | 95.63 310 | 84.77 219 | 94.73 295 | 96.22 236 |
|
CHOSEN 280x420 | | | 80.04 331 | 77.97 335 | 86.23 317 | 90.13 334 | 74.53 303 | 72.87 359 | 89.59 296 | 66.38 351 | 76.29 361 | 85.32 349 | 56.96 352 | 95.36 317 | 69.49 340 | 94.72 296 | 88.79 350 |
|
IterMVS | | | 90.18 216 | 90.16 211 | 90.21 253 | 93.15 294 | 75.98 286 | 87.56 308 | 92.97 260 | 86.43 221 | 94.09 172 | 96.40 134 | 78.32 266 | 97.43 259 | 87.87 179 | 94.69 297 | 97.23 193 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
EMVS | | | 80.35 330 | 80.28 327 | 80.54 342 | 84.73 366 | 69.07 336 | 72.54 360 | 80.73 360 | 87.80 200 | 81.66 350 | 81.73 358 | 62.89 332 | 89.84 354 | 75.79 309 | 94.65 298 | 82.71 358 |
|
PLC | ![Method available under an open source license with copyleft or other restrictive terms. copyleft](img/icon_copyleft.png) | 85.34 15 | 90.40 209 | 88.92 227 | 94.85 93 | 96.53 154 | 90.02 70 | 91.58 216 | 96.48 170 | 80.16 278 | 86.14 321 | 92.18 282 | 85.73 216 | 98.25 204 | 76.87 297 | 94.61 299 | 96.30 233 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
MSDG | | | 90.82 201 | 90.67 207 | 91.26 228 | 94.16 275 | 83.08 178 | 86.63 321 | 96.19 189 | 90.60 137 | 91.94 230 | 91.89 287 | 89.16 152 | 95.75 309 | 80.96 258 | 94.51 300 | 94.95 276 |
|
xiu_mvs_v2_base | | | 89.00 234 | 89.19 220 | 88.46 295 | 94.86 251 | 74.63 301 | 86.97 315 | 95.60 205 | 80.88 273 | 87.83 308 | 88.62 326 | 91.04 117 | 98.81 132 | 82.51 240 | 94.38 301 | 91.93 335 |
|
PS-MVSNAJ | | | 88.86 238 | 88.99 226 | 88.48 294 | 94.88 249 | 74.71 299 | 86.69 319 | 95.60 205 | 80.88 273 | 87.83 308 | 87.37 339 | 90.77 120 | 98.82 127 | 82.52 239 | 94.37 302 | 91.93 335 |
|
EU-MVSNet | | | 87.39 269 | 86.71 271 | 89.44 270 | 93.40 290 | 76.11 284 | 94.93 88 | 90.00 295 | 57.17 362 | 95.71 119 | 97.37 79 | 64.77 318 | 97.68 249 | 92.67 84 | 94.37 302 | 94.52 285 |
|
E-PMN | | | 80.72 327 | 80.86 322 | 80.29 343 | 85.11 364 | 68.77 337 | 72.96 358 | 81.97 357 | 87.76 201 | 83.25 340 | 83.01 357 | 62.22 336 | 89.17 357 | 77.15 296 | 94.31 304 | 82.93 357 |
|
GA-MVS | | | 87.70 260 | 86.82 268 | 90.31 247 | 93.27 292 | 77.22 275 | 84.72 333 | 92.79 264 | 85.11 237 | 89.82 276 | 90.07 312 | 66.80 306 | 97.76 244 | 84.56 222 | 94.27 305 | 95.96 245 |
|
sss | | | 87.23 273 | 86.82 268 | 88.46 295 | 93.96 280 | 77.94 263 | 86.84 317 | 92.78 265 | 77.59 300 | 87.61 312 | 91.83 288 | 78.75 262 | 91.92 345 | 77.84 288 | 94.20 306 | 95.52 265 |
|
MDA-MVSNet-bldmvs | | | 91.04 199 | 90.88 200 | 91.55 218 | 94.68 262 | 80.16 209 | 85.49 327 | 92.14 278 | 90.41 143 | 94.93 150 | 95.79 171 | 85.10 220 | 96.93 278 | 85.15 211 | 94.19 307 | 97.57 175 |
|
casdiffmvs | | | 92.55 173 | 92.40 169 | 93.01 158 | 94.72 261 | 83.36 171 | 94.54 108 | 97.04 130 | 83.00 258 | 89.97 271 | 96.95 97 | 88.23 165 | 98.76 143 | 93.22 66 | 93.95 308 | 96.92 205 |
|
PAPM_NR | | | 91.03 200 | 90.81 203 | 91.68 214 | 96.73 139 | 81.10 198 | 93.72 132 | 96.35 181 | 88.19 193 | 88.77 294 | 92.12 285 | 85.09 221 | 97.25 268 | 82.40 241 | 93.90 309 | 96.68 214 |
|
YYNet1 | | | 88.17 252 | 88.24 238 | 87.93 300 | 92.21 310 | 73.62 309 | 80.75 350 | 88.77 298 | 82.51 263 | 94.99 148 | 95.11 197 | 82.70 235 | 93.70 335 | 83.33 230 | 93.83 310 | 96.48 226 |
|
MDA-MVSNet_test_wron | | | 88.16 253 | 88.23 239 | 87.93 300 | 92.22 308 | 73.71 308 | 80.71 351 | 88.84 297 | 82.52 262 | 94.88 151 | 95.14 195 | 82.70 235 | 93.61 336 | 83.28 231 | 93.80 311 | 96.46 227 |
|
1112_ss | | | 88.42 246 | 87.41 255 | 91.45 221 | 96.69 141 | 80.99 199 | 89.72 274 | 96.72 159 | 73.37 322 | 87.00 317 | 90.69 308 | 77.38 273 | 98.20 208 | 81.38 250 | 93.72 312 | 95.15 270 |
|
PVSNet | | 76.22 20 | 82.89 310 | 82.37 309 | 84.48 329 | 93.96 280 | 64.38 354 | 78.60 354 | 88.61 299 | 71.50 331 | 84.43 332 | 86.36 346 | 74.27 284 | 94.60 325 | 69.87 339 | 93.69 313 | 94.46 287 |
|
TESTMET0.1,1 | | | 79.09 333 | 78.04 334 | 82.25 339 | 87.52 353 | 64.03 356 | 83.08 341 | 80.62 361 | 70.28 339 | 80.16 356 | 83.22 356 | 44.13 367 | 90.56 351 | 79.95 266 | 93.36 314 | 92.15 333 |
|
PAPR | | | 87.65 263 | 86.77 270 | 90.27 249 | 92.85 298 | 77.38 272 | 88.56 299 | 96.23 186 | 76.82 308 | 84.98 327 | 89.75 319 | 86.08 213 | 97.16 271 | 72.33 323 | 93.35 315 | 96.26 235 |
|
Patchmatch-test1 | | | 87.28 271 | 87.30 257 | 87.22 308 | 92.01 315 | 71.98 326 | 89.43 280 | 88.11 306 | 82.26 266 | 88.71 295 | 92.20 281 | 78.65 263 | 95.81 308 | 80.99 257 | 93.30 316 | 93.87 303 |
|
Test_1112_low_res | | | 87.50 267 | 86.58 272 | 90.25 250 | 96.80 136 | 77.75 267 | 87.53 309 | 96.25 184 | 69.73 341 | 86.47 319 | 93.61 247 | 75.67 282 | 97.88 230 | 79.95 266 | 93.20 317 | 95.11 272 |
|
MDTV_nov1_ep13 | | | | 83.88 301 | | 89.42 342 | 61.52 358 | 88.74 296 | 87.41 311 | 73.99 319 | 84.96 328 | 94.01 239 | 65.25 315 | 95.53 311 | 78.02 286 | 93.16 318 | |
|
WTY-MVS | | | 86.93 283 | 86.50 277 | 88.24 297 | 94.96 248 | 74.64 300 | 87.19 313 | 92.07 280 | 78.29 297 | 88.32 301 | 91.59 294 | 78.06 268 | 94.27 331 | 74.88 312 | 93.15 319 | 95.80 250 |
|
PMMVS | | | 83.00 309 | 81.11 318 | 88.66 287 | 83.81 368 | 86.44 131 | 82.24 346 | 85.65 324 | 61.75 360 | 82.07 346 | 85.64 348 | 79.75 258 | 91.59 347 | 75.99 303 | 93.09 320 | 87.94 352 |
|
UnsupCasMVSNet_bld | | | 88.50 244 | 88.03 244 | 89.90 257 | 95.52 232 | 78.88 254 | 87.39 310 | 94.02 242 | 79.32 290 | 93.06 202 | 94.02 238 | 80.72 255 | 94.27 331 | 75.16 311 | 93.08 321 | 96.54 216 |
|
MVS | | | 84.98 299 | 84.30 298 | 87.01 309 | 91.03 321 | 77.69 269 | 91.94 197 | 94.16 239 | 59.36 361 | 84.23 333 | 87.50 338 | 85.66 217 | 96.80 283 | 71.79 326 | 93.05 322 | 86.54 353 |
|
PatchT | | | 87.51 266 | 88.17 241 | 85.55 319 | 90.64 326 | 66.91 342 | 92.02 193 | 86.09 319 | 92.20 91 | 89.05 287 | 97.16 89 | 64.15 320 | 96.37 299 | 89.21 159 | 92.98 323 | 93.37 315 |
|
MS-PatchMatch | | | 88.05 254 | 87.75 250 | 88.95 281 | 93.28 291 | 77.93 264 | 87.88 304 | 92.49 272 | 75.42 311 | 92.57 213 | 93.59 248 | 80.44 256 | 94.24 333 | 81.28 251 | 92.75 324 | 94.69 282 |
|
CR-MVSNet | | | 87.89 255 | 87.12 262 | 90.22 251 | 91.01 322 | 78.93 252 | 92.52 169 | 92.81 262 | 73.08 324 | 89.10 285 | 96.93 101 | 67.11 303 | 97.64 250 | 88.80 163 | 92.70 325 | 94.08 293 |
|
RPMNet | | | 89.30 229 | 89.00 225 | 90.22 251 | 91.01 322 | 78.93 252 | 92.52 169 | 87.85 308 | 91.91 99 | 89.10 285 | 96.89 105 | 68.84 298 | 97.64 250 | 90.17 137 | 92.70 325 | 94.08 293 |
|
BH-w/o | | | 87.21 274 | 87.02 265 | 87.79 303 | 94.77 255 | 77.27 274 | 87.90 303 | 93.21 258 | 81.74 269 | 89.99 270 | 88.39 329 | 83.47 227 | 96.93 278 | 71.29 331 | 92.43 327 | 89.15 347 |
|
test2356 | | | 75.58 336 | 73.13 338 | 82.95 337 | 86.10 361 | 66.42 346 | 75.07 355 | 84.87 336 | 70.91 335 | 80.85 353 | 80.66 359 | 38.02 370 | 88.98 359 | 49.32 363 | 92.35 328 | 93.44 313 |
|
test12356 | | | 76.35 335 | 77.41 336 | 73.19 351 | 90.70 325 | 38.86 370 | 74.56 356 | 91.14 287 | 74.55 314 | 80.54 355 | 88.18 330 | 52.36 361 | 90.49 353 | 52.38 362 | 92.26 329 | 90.21 346 |
|
IB-MVS | | 77.21 19 | 83.11 307 | 81.05 319 | 89.29 274 | 91.15 320 | 75.85 287 | 85.66 326 | 86.00 321 | 79.70 283 | 82.02 348 | 86.61 342 | 48.26 364 | 98.39 191 | 77.84 288 | 92.22 330 | 93.63 308 |
Christian Sormann, Mattia Rossi, Andreas Kuhn and Friedrich Fraundorfer: IB-MVS: An Iterative Algorithm for Deep Multi-View Stereo based on Binary Decisions. BMVC 2021 |
gg-mvs-nofinetune | | | 82.10 316 | 81.02 320 | 85.34 322 | 87.46 355 | 71.04 328 | 94.74 95 | 67.56 368 | 96.44 20 | 79.43 357 | 98.99 5 | 45.24 365 | 96.15 302 | 67.18 344 | 92.17 331 | 88.85 349 |
|
HY-MVS | | 82.50 18 | 86.81 285 | 85.93 288 | 89.47 265 | 93.63 287 | 77.93 264 | 94.02 120 | 91.58 285 | 75.68 309 | 83.64 336 | 93.64 245 | 77.40 272 | 97.42 260 | 71.70 328 | 92.07 332 | 93.05 318 |
|
TR-MVS | | | 87.70 260 | 87.17 260 | 89.27 275 | 94.11 277 | 79.26 242 | 88.69 297 | 91.86 281 | 81.94 268 | 90.69 256 | 89.79 317 | 82.82 234 | 97.42 260 | 72.65 322 | 91.98 333 | 91.14 340 |
|
new_pmnet | | | 81.22 322 | 81.01 321 | 81.86 340 | 90.92 324 | 70.15 333 | 84.03 338 | 80.25 363 | 70.83 336 | 85.97 322 | 89.78 318 | 67.93 302 | 84.65 362 | 67.44 343 | 91.90 334 | 90.78 342 |
|
FPMVS | | | 84.50 302 | 83.28 304 | 88.16 298 | 96.32 176 | 94.49 11 | 85.76 325 | 85.47 327 | 83.09 255 | 85.20 325 | 94.26 227 | 63.79 323 | 86.58 361 | 63.72 352 | 91.88 335 | 83.40 356 |
|
UnsupCasMVSNet_eth | | | 90.33 213 | 90.34 209 | 90.28 248 | 94.64 265 | 80.24 207 | 89.69 275 | 95.88 196 | 85.77 230 | 93.94 176 | 95.69 175 | 81.99 241 | 92.98 341 | 84.21 224 | 91.30 336 | 97.62 173 |
|
MVP-Stereo | | | 90.07 221 | 88.92 227 | 93.54 142 | 96.31 177 | 86.49 128 | 90.93 233 | 95.59 208 | 79.80 280 | 91.48 234 | 95.59 176 | 80.79 254 | 97.39 263 | 78.57 284 | 91.19 337 | 96.76 213 |
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
1314 | | | 86.46 290 | 86.33 278 | 86.87 311 | 91.65 318 | 74.54 302 | 91.94 197 | 94.10 240 | 74.28 316 | 84.78 329 | 87.33 340 | 83.03 231 | 95.00 323 | 78.72 282 | 91.16 338 | 91.06 341 |
|
tpm | | | 84.38 303 | 84.08 299 | 85.30 324 | 90.47 330 | 63.43 357 | 89.34 283 | 85.63 325 | 77.24 305 | 87.62 311 | 95.03 202 | 61.00 339 | 97.30 267 | 79.26 273 | 91.09 339 | 95.16 269 |
|
CVMVSNet | | | 85.16 297 | 84.72 295 | 86.48 313 | 92.12 313 | 70.19 332 | 92.32 183 | 88.17 305 | 56.15 363 | 90.64 257 | 95.85 167 | 67.97 301 | 96.69 286 | 88.78 164 | 90.52 340 | 92.56 325 |
|
test0.0.03 1 | | | 82.48 313 | 81.47 316 | 85.48 320 | 89.70 337 | 73.57 310 | 84.73 331 | 81.64 358 | 83.07 256 | 88.13 305 | 86.61 342 | 62.86 333 | 89.10 358 | 66.24 348 | 90.29 341 | 93.77 305 |
|
PAPM | | | 81.91 318 | 80.11 328 | 87.31 307 | 93.87 283 | 72.32 325 | 84.02 339 | 93.22 256 | 69.47 342 | 76.13 362 | 89.84 314 | 72.15 290 | 97.23 269 | 53.27 361 | 89.02 342 | 92.37 327 |
|
MVS-HIRNet | | | 78.83 334 | 80.60 323 | 73.51 350 | 93.07 295 | 47.37 365 | 87.10 314 | 78.00 364 | 68.94 343 | 77.53 360 | 97.26 84 | 71.45 292 | 94.62 324 | 63.28 353 | 88.74 343 | 78.55 361 |
|
tpmp4_e23 | | | 81.87 319 | 80.41 324 | 86.27 316 | 89.29 343 | 67.84 339 | 91.58 216 | 87.61 310 | 67.42 348 | 78.60 358 | 92.71 267 | 56.42 354 | 96.87 280 | 71.44 330 | 88.63 344 | 94.10 292 |
|
tpm2 | | | 81.46 320 | 80.35 326 | 84.80 326 | 89.90 336 | 65.14 350 | 90.44 247 | 85.36 328 | 65.82 354 | 82.05 347 | 92.44 276 | 57.94 349 | 96.69 286 | 70.71 336 | 88.49 345 | 92.56 325 |
|
CostFormer | | | 83.09 308 | 82.21 310 | 85.73 318 | 89.27 344 | 67.01 341 | 90.35 251 | 86.47 317 | 70.42 338 | 83.52 338 | 93.23 259 | 61.18 337 | 96.85 281 | 77.21 295 | 88.26 346 | 93.34 316 |
|
GG-mvs-BLEND | | | | | 83.24 335 | 85.06 365 | 71.03 329 | 94.99 87 | 65.55 369 | | 74.09 364 | 75.51 363 | 44.57 366 | 94.46 327 | 59.57 356 | 87.54 347 | 84.24 355 |
|
PatchmatchNet | ![Method available under a permissive open source license. permissive](img/icon_permissive.png) | | 85.22 296 | 84.64 296 | 86.98 310 | 89.51 341 | 69.83 335 | 90.52 245 | 87.34 312 | 78.87 293 | 87.22 315 | 92.74 266 | 66.91 305 | 96.53 289 | 81.77 246 | 86.88 348 | 94.58 284 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
tpmvs | | | 84.22 304 | 83.97 300 | 84.94 325 | 87.09 357 | 65.18 349 | 91.21 225 | 88.35 301 | 82.87 259 | 85.21 324 | 90.96 301 | 65.24 316 | 96.75 284 | 79.60 272 | 85.25 349 | 92.90 320 |
|
ADS-MVSNet2 | | | 84.01 305 | 82.20 311 | 89.41 271 | 89.04 345 | 76.37 281 | 87.57 306 | 90.98 290 | 72.71 327 | 84.46 330 | 92.45 274 | 68.08 299 | 96.48 292 | 70.58 337 | 83.97 350 | 95.38 267 |
|
ADS-MVSNet | | | 82.25 314 | 81.55 315 | 84.34 330 | 89.04 345 | 65.30 348 | 87.57 306 | 85.13 335 | 72.71 327 | 84.46 330 | 92.45 274 | 68.08 299 | 92.33 344 | 70.58 337 | 83.97 350 | 95.38 267 |
|
PatchFormer-LS_test | | | 82.62 312 | 81.71 313 | 85.32 323 | 87.92 349 | 67.31 340 | 89.03 291 | 88.20 304 | 77.58 301 | 83.79 335 | 80.50 361 | 60.96 340 | 96.42 295 | 83.86 228 | 83.59 352 | 92.23 332 |
|
JIA-IIPM | | | 85.08 298 | 83.04 306 | 91.19 233 | 87.56 352 | 86.14 139 | 89.40 282 | 84.44 343 | 88.98 165 | 82.20 345 | 97.95 49 | 56.82 353 | 96.15 302 | 76.55 300 | 83.45 353 | 91.30 339 |
|
MVE | ![Method available under a permissive open source license. permissive](img/icon_permissive.png) | 59.87 23 | 73.86 339 | 72.65 340 | 77.47 347 | 87.00 359 | 74.35 305 | 61.37 364 | 60.93 370 | 67.27 349 | 69.69 366 | 86.49 344 | 81.24 252 | 72.33 366 | 56.45 359 | 83.45 353 | 85.74 354 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
DWT-MVSNet_test | | | 80.74 326 | 79.18 331 | 85.43 321 | 87.51 354 | 66.87 343 | 89.87 271 | 86.01 320 | 74.20 318 | 80.86 352 | 80.62 360 | 48.84 363 | 96.68 288 | 81.54 248 | 83.14 355 | 92.75 323 |
|
EPMVS | | | 81.17 324 | 80.37 325 | 83.58 333 | 85.58 363 | 65.08 351 | 90.31 253 | 71.34 367 | 77.31 304 | 85.80 323 | 91.30 295 | 59.38 341 | 92.70 343 | 79.99 265 | 82.34 356 | 92.96 319 |
|
LP | | | 86.29 291 | 85.35 292 | 89.10 278 | 87.80 350 | 76.21 282 | 89.92 267 | 90.99 289 | 84.86 242 | 87.66 310 | 92.32 279 | 70.40 295 | 96.48 292 | 81.94 244 | 82.24 357 | 94.63 283 |
|
tpmrst | | | 82.85 311 | 82.93 308 | 82.64 338 | 87.65 351 | 58.99 361 | 90.14 259 | 87.90 307 | 75.54 310 | 83.93 334 | 91.63 292 | 66.79 308 | 95.36 317 | 81.21 253 | 81.54 358 | 93.57 312 |
|
tpm cat1 | | | 80.61 328 | 79.46 330 | 84.07 332 | 88.78 347 | 65.06 352 | 89.26 286 | 88.23 303 | 62.27 359 | 81.90 349 | 89.66 321 | 62.70 335 | 95.29 320 | 71.72 327 | 80.60 359 | 91.86 337 |
|
testpf | | | 74.01 338 | 76.37 337 | 66.95 352 | 80.56 369 | 60.00 359 | 88.43 301 | 75.07 366 | 81.54 270 | 75.75 363 | 83.73 353 | 38.93 369 | 83.09 364 | 84.01 225 | 79.32 360 | 57.75 363 |
|
dp | | | 79.28 332 | 78.62 333 | 81.24 341 | 85.97 362 | 56.45 363 | 86.91 316 | 85.26 333 | 72.97 326 | 81.45 351 | 89.17 325 | 56.01 356 | 95.45 315 | 73.19 318 | 76.68 361 | 91.82 338 |
|
DeepMVS_CX | ![Method available under an open source license with copyleft or other restrictive terms. copyleft](img/icon_copyleft.png) | | | | 53.83 353 | 70.38 370 | 64.56 353 | | 48.52 372 | 33.01 365 | 65.50 367 | 74.21 364 | 56.19 355 | 46.64 367 | 38.45 365 | 70.07 362 | 50.30 364 |
|
tmp_tt | | | 37.97 344 | 44.33 344 | 18.88 356 | 11.80 371 | 21.54 371 | 63.51 363 | 45.66 373 | 4.23 366 | 51.34 368 | 50.48 365 | 59.08 342 | 22.11 368 | 44.50 364 | 68.35 363 | 13.00 365 |
|
PVSNet_0 | | 70.34 21 | 74.58 337 | 72.96 339 | 79.47 344 | 90.63 327 | 66.24 347 | 73.26 357 | 83.40 347 | 63.67 358 | 78.02 359 | 78.35 362 | 72.53 288 | 89.59 355 | 56.68 358 | 60.05 364 | 82.57 359 |
|
PNet_i23d | | | 72.03 340 | 70.91 341 | 75.38 348 | 90.46 331 | 57.84 362 | 71.73 361 | 81.53 359 | 83.86 249 | 82.21 344 | 83.49 355 | 29.97 373 | 87.80 360 | 60.78 354 | 54.12 365 | 80.51 360 |
|
test123 | | | 9.49 346 | 12.01 347 | 1.91 357 | 2.87 372 | 1.30 372 | 82.38 344 | 1.34 375 | 1.36 367 | 2.84 369 | 6.56 368 | 2.45 374 | 0.97 369 | 2.73 366 | 5.56 366 | 3.47 366 |
|
.test1245 | | | 64.72 341 | 70.88 342 | 46.22 354 | 94.61 266 | 44.56 367 | 81.59 347 | 90.66 292 | 86.78 217 | 90.60 258 | 93.52 251 | 30.37 371 | 90.67 349 | 66.36 346 | 3.45 367 | 3.44 367 |
|
testmvs | | | 9.02 347 | 11.42 348 | 1.81 358 | 2.77 373 | 1.13 373 | 79.44 352 | 1.90 374 | 1.18 368 | 2.65 370 | 6.80 367 | 1.95 375 | 0.87 370 | 2.62 367 | 3.45 367 | 3.44 367 |
|
test_part1 | | | | | 0.00 359 | | 0.00 374 | 0.00 365 | 98.14 29 | | | | 0.00 376 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
v1.0 | | | 40.11 343 | 53.48 343 | 0.00 359 | 98.21 62 | 0.00 374 | 0.00 365 | 98.14 29 | 91.83 105 | 96.72 69 | 96.39 138 | 0.00 376 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
cdsmvs_eth3d_5k | | | 23.35 345 | 31.13 346 | 0.00 359 | 0.00 374 | 0.00 374 | 0.00 365 | 95.58 209 | 0.00 369 | 0.00 371 | 91.15 297 | 93.43 61 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
pcd_1.5k_mvsjas | | | 7.56 348 | 10.09 349 | 0.00 359 | 0.00 374 | 0.00 374 | 0.00 365 | 0.00 376 | 0.00 369 | 0.00 371 | 0.00 371 | 90.77 120 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
sosnet-low-res | | | 0.00 350 | 0.00 351 | 0.00 359 | 0.00 374 | 0.00 374 | 0.00 365 | 0.00 376 | 0.00 369 | 0.00 371 | 0.00 371 | 0.00 376 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
sosnet | | | 0.00 350 | 0.00 351 | 0.00 359 | 0.00 374 | 0.00 374 | 0.00 365 | 0.00 376 | 0.00 369 | 0.00 371 | 0.00 371 | 0.00 376 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
uncertanet | | | 0.00 350 | 0.00 351 | 0.00 359 | 0.00 374 | 0.00 374 | 0.00 365 | 0.00 376 | 0.00 369 | 0.00 371 | 0.00 371 | 0.00 376 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
Regformer | | | 0.00 350 | 0.00 351 | 0.00 359 | 0.00 374 | 0.00 374 | 0.00 365 | 0.00 376 | 0.00 369 | 0.00 371 | 0.00 371 | 0.00 376 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
ab-mvs-re | | | 7.56 348 | 10.08 350 | 0.00 359 | 0.00 374 | 0.00 374 | 0.00 365 | 0.00 376 | 0.00 369 | 0.00 371 | 90.69 308 | 0.00 376 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
uanet | | | 0.00 350 | 0.00 351 | 0.00 359 | 0.00 374 | 0.00 374 | 0.00 365 | 0.00 376 | 0.00 369 | 0.00 371 | 0.00 371 | 0.00 376 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
GSMVS | | | | | | | | | | | | | | | | | 94.75 280 |
|
test_part2 | | | | | | 98.21 62 | 89.41 79 | | | | 96.72 69 | | | | | | |
|
sam_mvs1 | | | | | | | | | | | | | 66.64 309 | | | | 94.75 280 |
|
sam_mvs | | | | | | | | | | | | | 66.41 310 | | | | |
|
MTGPA | ![Method available as binary. binary](img/icon_binary.png) | | | | | | | | 97.62 77 | | | | | | | | |
|
test_post1 | | | | | | | | 90.21 255 | | | | 5.85 370 | 65.36 314 | 96.00 305 | 79.61 271 | | |
|
test_post | | | | | | | | | | | | 6.07 369 | 65.74 313 | 95.84 307 | | | |
|
patchmatchnet-post | | | | | | | | | | | | 91.71 290 | 66.22 312 | 97.59 252 | | | |
|
MTMP | | | | | | | | 94.82 92 | 54.62 371 | | | | | | | | |
|
gm-plane-assit | | | | | | 87.08 358 | 59.33 360 | | | 71.22 332 | | 83.58 354 | | 97.20 270 | 73.95 313 | | |
|
TEST9 | | | | | | 96.45 162 | 89.46 76 | 90.60 242 | 96.92 142 | 79.09 292 | 90.49 260 | 94.39 224 | 91.31 107 | 98.88 112 | | | |
|
test_8 | | | | | | 96.37 165 | 89.14 83 | 90.51 246 | 96.89 146 | 79.37 287 | 90.42 262 | 94.36 226 | 91.20 113 | 98.82 127 | | | |
|
agg_prior | | | | | | 96.20 185 | 88.89 88 | | 96.88 147 | | 90.21 263 | | | 98.78 138 | | | |
|
test_prior4 | | | | | | | 89.91 72 | 90.74 237 | | | | | | | | | |
|
test_prior | | | | | 94.61 100 | 95.95 209 | 87.23 117 | | 97.36 108 | | | | | 98.68 158 | | | 97.93 147 |
|
旧先验2 | | | | | | | | 90.00 265 | | 68.65 344 | 92.71 210 | | | 96.52 290 | 85.15 211 | | |
|
新几何2 | | | | | | | | 90.02 264 | | | | | | | | | |
|
无先验 | | | | | | | | 89.94 266 | 95.75 201 | 70.81 337 | | | | 98.59 168 | 81.17 254 | | 94.81 277 |
|
原ACMM2 | | | | | | | | 89.34 283 | | | | | | | | | |
|
testdata2 | | | | | | | | | | | | | | 98.03 216 | 80.24 263 | | |
|
segment_acmp | | | | | | | | | | | | | 92.14 89 | | | | |
|
testdata1 | | | | | | | | 88.96 293 | | 88.44 186 | | | | | | | |
|
plane_prior7 | | | | | | 97.71 92 | 88.68 92 | | | | | | | | | | |
|
plane_prior6 | | | | | | 97.21 114 | 88.23 105 | | | | | | 86.93 198 | | | | |
|
plane_prior4 | | | | | | | | | | | | 95.59 176 | | | | | |
|
plane_prior3 | | | | | | | 88.43 103 | | | 90.35 144 | 93.31 190 | | | | | | |
|
plane_prior2 | | | | | | | | 94.56 105 | | 91.74 111 | | | | | | | |
|
plane_prior1 | | | | | | 97.38 108 | | | | | | | | | | | |
|
n2 | | | | | | | | | 0.00 376 | | | | | | | | |
|
nn | | | | | | | | | 0.00 376 | | | | | | | | |
|
door-mid | | | | | | | | | 92.13 279 | | | | | | | | |
|
test11 | | | | | | | | | 96.65 161 | | | | | | | | |
|
door | | | | | | | | | 91.26 286 | | | | | | | | |
|
HQP5-MVS | | | | | | | 84.89 155 | | | | | | | | | | |
|
HQP-NCC | | | | | | 96.36 170 | | 91.37 220 | | 87.16 209 | 88.81 290 | | | | | | |
|
ACMP_Plane | | | | | | 96.36 170 | | 91.37 220 | | 87.16 209 | 88.81 290 | | | | | | |
|
BP-MVS | | | | | | | | | | | | | | | 86.55 197 | | |
|
HQP4-MVS | | | | | | | | | | | 88.81 290 | | | 98.61 164 | | | 98.15 133 |
|
HQP2-MVS | | | | | | | | | | | | | 84.76 222 | | | | |
|
NP-MVS | | | | | | 96.82 134 | 87.10 120 | | | | | 93.40 254 | | | | | |
|
MDTV_nov1_ep13_2view | | | | | | | 42.48 369 | 88.45 300 | | 67.22 350 | 83.56 337 | | 66.80 306 | | 72.86 321 | | 94.06 295 |
|
Test By Simon | | | | | | | | | | | | | 90.61 127 | | | | |
|