anonymousdsp | | | 99.51 12 | 99.47 15 | 99.62 6 | 99.88 8 | 99.08 47 | 99.34 15 | 99.69 15 | 98.93 83 | 99.65 23 | 99.72 11 | 98.93 20 | 99.95 13 | 99.11 44 | 100.00 1 | 99.82 10 |
|
PS-MVSNAJss | | | 99.46 14 | 99.49 12 | 99.35 62 | 99.90 5 | 98.15 101 | 99.20 35 | 99.65 20 | 99.48 25 | 99.92 3 | 99.71 14 | 98.07 61 | 99.96 8 | 99.53 21 | 100.00 1 | 99.93 1 |
|
v15 | | | 99.11 41 | 99.27 33 | 98.62 159 | 99.52 81 | 96.43 198 | 99.01 55 | 99.63 25 | 99.18 55 | 99.59 32 | 99.64 26 | 97.13 124 | 99.81 142 | 99.71 10 | 100.00 1 | 99.64 40 |
|
v13 | | | 99.24 31 | 99.39 18 | 98.77 141 | 99.63 52 | 96.79 185 | 99.24 33 | 99.65 20 | 99.39 33 | 99.62 27 | 99.70 16 | 97.50 96 | 99.84 103 | 99.78 5 | 100.00 1 | 99.67 31 |
|
v12 | | | 99.21 32 | 99.37 20 | 98.74 149 | 99.60 55 | 96.72 190 | 99.19 39 | 99.65 20 | 99.35 39 | 99.62 27 | 99.69 17 | 97.43 103 | 99.83 117 | 99.76 6 | 100.00 1 | 99.66 33 |
|
v11 | | | 99.12 40 | 99.31 28 | 98.53 178 | 99.59 56 | 96.11 213 | 99.08 49 | 99.65 20 | 99.15 56 | 99.60 30 | 99.69 17 | 97.26 116 | 99.83 117 | 99.81 3 | 100.00 1 | 99.66 33 |
|
V14 | | | 99.14 37 | 99.30 31 | 98.66 153 | 99.56 69 | 96.53 194 | 99.08 49 | 99.63 25 | 99.24 46 | 99.60 30 | 99.66 22 | 97.23 120 | 99.82 129 | 99.73 8 | 100.00 1 | 99.65 37 |
|
V9 | | | 99.18 34 | 99.34 24 | 98.70 150 | 99.58 57 | 96.63 193 | 99.14 44 | 99.64 24 | 99.30 42 | 99.61 29 | 99.68 19 | 97.33 108 | 99.83 117 | 99.75 7 | 100.00 1 | 99.65 37 |
|
LCM-MVSNet | | | 99.93 1 | 99.92 1 | 99.94 1 | 99.99 1 | 99.97 1 | 99.90 1 | 99.89 2 | 99.98 1 | 99.99 1 | 99.96 1 | 99.77 1 | 100.00 1 | 99.81 3 | 100.00 1 | 99.85 9 |
|
ANet_high | | | 99.57 9 | 99.67 5 | 99.28 71 | 99.89 7 | 98.09 105 | 99.14 44 | 99.93 1 | 99.82 2 | 99.93 2 | 99.81 4 | 99.17 14 | 99.94 20 | 99.31 30 | 100.00 1 | 99.82 10 |
|
pcd1.5k->3k | | | 41.59 331 | 44.35 332 | 33.30 344 | 99.87 12 | 0.00 362 | 0.00 353 | 99.58 36 | 0.00 357 | 0.00 358 | 0.00 359 | 99.70 2 | 0.00 360 | 0.00 357 | 99.99 11 | 99.91 2 |
|
UA-Net | | | 99.47 13 | 99.40 17 | 99.70 3 | 99.49 92 | 99.29 13 | 99.80 3 | 99.72 11 | 99.82 2 | 99.04 118 | 99.81 4 | 98.05 64 | 99.96 8 | 98.85 56 | 99.99 11 | 99.86 8 |
|
jajsoiax | | | 99.58 8 | 99.61 7 | 99.48 45 | 99.87 12 | 98.61 72 | 99.28 29 | 99.66 19 | 99.09 68 | 99.89 8 | 99.68 19 | 99.53 4 | 99.97 3 | 99.50 22 | 99.99 11 | 99.87 6 |
|
mvs_tets | | | 99.63 5 | 99.67 5 | 99.49 44 | 99.88 8 | 98.61 72 | 99.34 15 | 99.71 12 | 99.27 45 | 99.90 5 | 99.74 8 | 99.68 3 | 99.97 3 | 99.55 20 | 99.99 11 | 99.88 5 |
|
v52 | | | 99.59 6 | 99.60 8 | 99.55 20 | 99.87 12 | 99.00 48 | 99.59 7 | 99.56 49 | 99.56 22 | 99.68 20 | 99.72 11 | 98.57 34 | 99.93 26 | 99.85 1 | 99.99 11 | 99.72 24 |
|
v10 | | | 98.97 54 | 99.11 44 | 98.55 174 | 99.44 109 | 96.21 211 | 98.90 67 | 99.55 54 | 98.73 93 | 99.48 46 | 99.60 34 | 96.63 159 | 99.83 117 | 99.70 11 | 99.99 11 | 99.61 49 |
|
V4 | | | 99.59 6 | 99.60 8 | 99.55 20 | 99.87 12 | 99.00 48 | 99.59 7 | 99.56 49 | 99.56 22 | 99.68 20 | 99.72 11 | 98.57 34 | 99.93 26 | 99.85 1 | 99.99 11 | 99.72 24 |
|
no-one | | | 97.98 168 | 98.10 150 | 97.61 243 | 99.55 73 | 93.82 280 | 96.70 253 | 98.94 218 | 96.18 235 | 99.52 39 | 99.41 61 | 95.90 196 | 99.81 142 | 96.72 160 | 99.99 11 | 99.20 203 |
|
v17 | | | 99.07 43 | 99.22 36 | 98.61 162 | 99.50 86 | 96.42 199 | 99.01 55 | 99.60 32 | 99.15 56 | 99.48 46 | 99.61 30 | 97.05 128 | 99.81 142 | 99.64 12 | 99.98 19 | 99.61 49 |
|
v8 | | | 99.01 47 | 99.16 41 | 98.57 169 | 99.47 99 | 96.31 205 | 98.90 67 | 99.47 80 | 99.03 72 | 99.52 39 | 99.57 39 | 96.93 137 | 99.81 142 | 99.60 14 | 99.98 19 | 99.60 52 |
|
test_djsdf | | | 99.52 11 | 99.51 11 | 99.53 32 | 99.86 16 | 98.74 61 | 99.39 13 | 99.56 49 | 99.11 61 | 99.70 15 | 99.73 10 | 99.00 17 | 99.97 3 | 99.26 32 | 99.98 19 | 99.89 3 |
|
wuykxyi23d | | | 99.36 25 | 99.31 28 | 99.50 42 | 99.81 21 | 98.67 68 | 98.08 134 | 99.75 8 | 98.03 126 | 99.90 5 | 99.60 34 | 99.18 12 | 99.94 20 | 99.46 25 | 99.98 19 | 99.89 3 |
|
pmmvs-eth3d | | | 98.47 124 | 98.34 126 | 98.86 129 | 99.30 132 | 97.76 141 | 97.16 229 | 99.28 142 | 95.54 258 | 99.42 57 | 99.19 90 | 97.27 113 | 99.63 262 | 97.89 100 | 99.97 23 | 99.20 203 |
|
v18 | | | 99.02 46 | 99.17 39 | 98.57 169 | 99.45 106 | 96.31 205 | 98.94 64 | 99.58 36 | 99.06 70 | 99.43 55 | 99.58 38 | 96.91 138 | 99.80 154 | 99.60 14 | 99.97 23 | 99.59 58 |
|
v16 | | | 99.07 43 | 99.22 36 | 98.61 162 | 99.50 86 | 96.42 199 | 99.01 55 | 99.60 32 | 99.15 56 | 99.46 50 | 99.61 30 | 97.04 129 | 99.81 142 | 99.64 12 | 99.97 23 | 99.61 49 |
|
IterMVS-LS | | | 98.55 113 | 98.70 74 | 98.09 217 | 99.48 97 | 94.73 250 | 97.22 222 | 99.39 100 | 98.97 78 | 99.38 62 | 99.31 74 | 96.00 187 | 99.93 26 | 98.58 68 | 99.97 23 | 99.60 52 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
LTVRE_ROB | | 98.40 1 | 99.67 3 | 99.71 2 | 99.56 18 | 99.85 18 | 99.11 42 | 99.90 1 | 99.78 5 | 99.63 12 | 99.78 10 | 99.67 21 | 99.48 6 | 99.81 142 | 99.30 31 | 99.97 23 | 99.77 16 |
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 |
v748 | | | 99.44 15 | 99.48 13 | 99.33 67 | 99.88 8 | 98.43 87 | 99.42 11 | 99.53 59 | 99.63 12 | 99.69 17 | 99.60 34 | 97.99 69 | 99.91 43 | 99.60 14 | 99.96 28 | 99.66 33 |
|
v7n | | | 99.53 10 | 99.57 10 | 99.41 53 | 99.88 8 | 98.54 80 | 99.45 10 | 99.61 30 | 99.66 9 | 99.68 20 | 99.66 22 | 98.44 42 | 99.95 13 | 99.73 8 | 99.96 28 | 99.75 21 |
|
MVS_0304 | | | 98.02 162 | 97.88 169 | 98.46 188 | 98.22 297 | 96.39 202 | 96.50 263 | 99.49 71 | 98.03 126 | 97.24 268 | 98.33 231 | 94.80 228 | 99.90 47 | 98.31 84 | 99.95 30 | 99.08 219 |
|
PS-CasMVS | | | 99.40 21 | 99.33 26 | 99.62 6 | 99.71 34 | 99.10 43 | 99.29 25 | 99.53 59 | 99.53 24 | 99.46 50 | 99.41 61 | 98.23 50 | 99.95 13 | 98.89 55 | 99.95 30 | 99.81 12 |
|
CHOSEN 1792x2688 | | | 97.49 199 | 97.14 210 | 98.54 177 | 99.68 43 | 96.09 216 | 96.50 263 | 99.62 28 | 91.58 317 | 98.84 148 | 98.97 139 | 92.36 267 | 99.88 63 | 96.76 157 | 99.95 30 | 99.67 31 |
|
semantic-postprocess | | | | | 96.87 272 | 99.27 134 | 91.16 321 | | 99.25 153 | 99.10 65 | 99.41 58 | 99.35 68 | 92.91 261 | 99.96 8 | 98.65 66 | 99.94 33 | 99.49 111 |
|
Anonymous20231211 | | | 99.71 2 | 99.70 3 | 99.74 2 | 99.97 2 | 99.52 2 | 99.74 4 | 99.82 4 | 99.73 6 | 99.91 4 | 99.89 2 | 99.27 9 | 99.94 20 | 99.02 49 | 99.94 33 | 99.75 21 |
|
FC-MVSNet-test | | | 99.27 29 | 99.25 34 | 99.34 65 | 99.77 25 | 98.37 91 | 99.30 24 | 99.57 43 | 99.61 18 | 99.40 60 | 99.50 46 | 97.12 125 | 99.85 88 | 99.02 49 | 99.94 33 | 99.80 13 |
|
testing_2 | | | 98.93 57 | 98.99 50 | 98.76 143 | 99.57 62 | 97.03 177 | 97.85 166 | 99.13 187 | 98.46 107 | 99.44 54 | 99.44 57 | 98.22 52 | 99.74 214 | 98.85 56 | 99.94 33 | 99.51 99 |
|
UGNet | | | 98.53 118 | 98.45 110 | 98.79 136 | 97.94 307 | 96.96 180 | 99.08 49 | 98.54 262 | 99.10 65 | 96.82 287 | 99.47 51 | 96.55 165 | 99.84 103 | 98.56 73 | 99.94 33 | 99.55 83 |
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 |
IterMVS | | | 97.73 183 | 98.11 148 | 96.57 283 | 99.24 138 | 90.28 322 | 95.52 311 | 99.21 160 | 98.86 85 | 99.33 72 | 99.33 72 | 93.11 257 | 99.94 20 | 98.49 74 | 99.94 33 | 99.48 117 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
CHOSEN 280x420 | | | 95.51 270 | 95.47 262 | 95.65 309 | 98.25 292 | 88.27 329 | 93.25 342 | 98.88 229 | 93.53 294 | 94.65 332 | 97.15 295 | 86.17 293 | 99.93 26 | 97.41 126 | 99.93 39 | 98.73 261 |
|
CANet | | | 97.87 174 | 97.76 173 | 98.19 213 | 97.75 312 | 95.51 235 | 96.76 249 | 99.05 200 | 97.74 147 | 96.93 277 | 98.21 240 | 95.59 204 | 99.89 56 | 97.86 104 | 99.93 39 | 99.19 208 |
|
v1144 | | | 98.60 105 | 98.66 82 | 98.41 193 | 99.36 121 | 95.90 223 | 97.58 196 | 99.34 121 | 97.51 165 | 99.27 82 | 99.15 102 | 96.34 177 | 99.80 154 | 99.47 24 | 99.93 39 | 99.51 99 |
|
testmv | | | 98.51 120 | 98.47 105 | 98.61 162 | 99.24 138 | 96.53 194 | 96.66 256 | 99.73 10 | 98.56 105 | 99.50 44 | 99.23 86 | 97.24 118 | 99.87 72 | 96.16 197 | 99.93 39 | 99.44 135 |
|
PEN-MVS | | | 99.41 20 | 99.34 24 | 99.62 6 | 99.73 28 | 99.14 35 | 99.29 25 | 99.54 58 | 99.62 16 | 99.56 33 | 99.42 59 | 98.16 57 | 99.96 8 | 98.78 59 | 99.93 39 | 99.77 16 |
|
DTE-MVSNet | | | 99.43 18 | 99.35 22 | 99.66 4 | 99.71 34 | 99.30 12 | 99.31 20 | 99.51 64 | 99.64 10 | 99.56 33 | 99.46 52 | 98.23 50 | 99.97 3 | 98.78 59 | 99.93 39 | 99.72 24 |
|
CP-MVSNet | | | 99.21 32 | 99.09 45 | 99.56 18 | 99.65 47 | 98.96 54 | 99.13 46 | 99.34 121 | 99.42 31 | 99.33 72 | 99.26 79 | 97.01 133 | 99.94 20 | 98.74 63 | 99.93 39 | 99.79 14 |
|
WR-MVS_H | | | 99.33 27 | 99.22 36 | 99.65 5 | 99.71 34 | 99.24 20 | 99.32 17 | 99.55 54 | 99.46 28 | 99.50 44 | 99.34 70 | 97.30 110 | 99.93 26 | 98.90 53 | 99.93 39 | 99.77 16 |
|
PVSNet_BlendedMVS | | | 97.55 196 | 97.53 187 | 97.60 244 | 98.92 215 | 93.77 282 | 96.64 257 | 99.43 93 | 94.49 276 | 97.62 240 | 99.18 92 | 96.82 147 | 99.67 246 | 94.73 236 | 99.93 39 | 99.36 164 |
|
Vis-MVSNet | | | 99.34 26 | 99.36 21 | 99.27 74 | 99.73 28 | 98.26 94 | 99.17 41 | 99.78 5 | 99.11 61 | 99.27 82 | 99.48 50 | 98.82 22 | 99.95 13 | 98.94 52 | 99.93 39 | 99.59 58 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
pmmvs6 | | | 99.67 3 | 99.70 3 | 99.60 12 | 99.90 5 | 99.27 16 | 99.53 9 | 99.76 7 | 99.64 10 | 99.84 9 | 99.83 3 | 99.50 5 | 99.87 72 | 99.36 28 | 99.92 49 | 99.64 40 |
|
nrg030 | | | 99.40 21 | 99.35 22 | 99.54 25 | 99.58 57 | 99.13 38 | 98.98 62 | 99.48 74 | 99.68 7 | 99.46 50 | 99.26 79 | 98.62 30 | 99.73 219 | 99.17 43 | 99.92 49 | 99.76 19 |
|
v1192 | | | 98.60 105 | 98.66 82 | 98.41 193 | 99.27 134 | 95.88 224 | 97.52 202 | 99.36 111 | 97.41 177 | 99.33 72 | 99.20 89 | 96.37 176 | 99.82 129 | 99.57 18 | 99.92 49 | 99.55 83 |
|
OurMVSNet-221017-0 | | | 99.37 24 | 99.31 28 | 99.53 32 | 99.91 4 | 98.98 50 | 99.63 6 | 99.58 36 | 99.44 30 | 99.78 10 | 99.76 6 | 96.39 173 | 99.92 34 | 99.44 26 | 99.92 49 | 99.68 30 |
|
DeepC-MVS | | 97.60 4 | 98.97 54 | 98.93 51 | 99.10 93 | 99.35 125 | 97.98 119 | 98.01 150 | 99.46 82 | 97.56 162 | 99.54 35 | 99.50 46 | 98.97 18 | 99.84 103 | 98.06 93 | 99.92 49 | 99.49 111 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
v144192 | | | 98.54 116 | 98.57 93 | 98.45 190 | 99.21 150 | 95.98 218 | 97.63 189 | 99.36 111 | 97.15 202 | 99.32 77 | 99.18 92 | 95.84 198 | 99.84 103 | 99.50 22 | 99.91 54 | 99.54 86 |
|
PVSNet_Blended_VisFu | | | 98.17 156 | 98.15 144 | 98.22 211 | 99.73 28 | 95.15 243 | 97.36 211 | 99.68 16 | 94.45 280 | 98.99 124 | 99.27 77 | 96.87 144 | 99.94 20 | 97.13 138 | 99.91 54 | 99.57 70 |
|
test_0402 | | | 98.76 74 | 98.71 71 | 98.93 119 | 99.56 69 | 98.14 103 | 98.45 110 | 99.34 121 | 99.28 44 | 98.95 131 | 98.91 148 | 98.34 46 | 99.79 174 | 95.63 221 | 99.91 54 | 98.86 246 |
|
v1921920 | | | 98.54 116 | 98.60 91 | 98.38 199 | 99.20 159 | 95.76 228 | 97.56 198 | 99.36 111 | 97.23 196 | 99.38 62 | 99.17 97 | 96.02 185 | 99.84 103 | 99.57 18 | 99.90 57 | 99.54 86 |
|
v1141 | | | 98.63 98 | 98.70 74 | 98.41 193 | 99.39 117 | 95.96 220 | 97.64 186 | 99.21 160 | 97.92 130 | 99.35 68 | 99.08 112 | 96.61 162 | 99.78 184 | 99.25 34 | 99.90 57 | 99.50 104 |
|
divwei89l23v2f112 | | | 98.63 98 | 98.70 74 | 98.41 193 | 99.39 117 | 95.96 220 | 97.64 186 | 99.21 160 | 97.92 130 | 99.35 68 | 99.08 112 | 96.61 162 | 99.78 184 | 99.25 34 | 99.90 57 | 99.50 104 |
|
v2v482 | | | 98.56 109 | 98.62 86 | 98.37 200 | 99.42 114 | 95.81 227 | 97.58 196 | 99.16 183 | 97.90 138 | 99.28 80 | 99.01 131 | 95.98 191 | 99.79 174 | 99.33 29 | 99.90 57 | 99.51 99 |
|
v1 | | | 98.63 98 | 98.70 74 | 98.41 193 | 99.39 117 | 95.96 220 | 97.64 186 | 99.20 164 | 97.92 130 | 99.36 66 | 99.07 117 | 96.63 159 | 99.78 184 | 99.25 34 | 99.90 57 | 99.50 104 |
|
TranMVSNet+NR-MVSNet | | | 99.17 35 | 99.07 47 | 99.46 50 | 99.37 120 | 98.87 56 | 98.39 114 | 99.42 96 | 99.42 31 | 99.36 66 | 99.06 118 | 98.38 44 | 99.95 13 | 98.34 81 | 99.90 57 | 99.57 70 |
|
FMVSNet1 | | | 99.17 35 | 99.17 39 | 99.17 82 | 99.55 73 | 98.24 95 | 99.20 35 | 99.44 88 | 99.21 47 | 99.43 55 | 99.55 41 | 97.82 79 | 99.86 77 | 98.42 78 | 99.89 63 | 99.41 145 |
|
FIs | | | 99.14 37 | 99.09 45 | 99.29 70 | 99.70 40 | 98.28 93 | 99.13 46 | 99.52 63 | 99.48 25 | 99.24 90 | 99.41 61 | 96.79 150 | 99.82 129 | 98.69 65 | 99.88 64 | 99.76 19 |
|
v1240 | | | 98.55 113 | 98.62 86 | 98.32 203 | 99.22 144 | 95.58 232 | 97.51 204 | 99.45 85 | 97.16 200 | 99.45 53 | 99.24 82 | 96.12 182 | 99.85 88 | 99.60 14 | 99.88 64 | 99.55 83 |
|
v7 | | | 98.67 92 | 98.73 67 | 98.50 184 | 99.43 113 | 96.21 211 | 98.00 151 | 99.31 131 | 97.58 158 | 99.17 101 | 99.18 92 | 96.63 159 | 99.80 154 | 99.42 27 | 99.88 64 | 99.48 117 |
|
TAMVS | | | 98.24 150 | 98.05 156 | 98.80 135 | 99.07 182 | 97.18 171 | 97.88 162 | 98.81 242 | 96.66 220 | 99.17 101 | 99.21 87 | 94.81 227 | 99.77 194 | 96.96 145 | 99.88 64 | 99.44 135 |
|
EU-MVSNet | | | 97.66 188 | 98.50 99 | 95.13 315 | 99.63 52 | 85.84 337 | 98.35 115 | 98.21 273 | 98.23 120 | 99.54 35 | 99.46 52 | 95.02 218 | 99.68 240 | 98.24 85 | 99.87 68 | 99.87 6 |
|
1111 | | | 93.99 306 | 93.72 302 | 94.80 318 | 99.33 128 | 85.20 341 | 95.97 286 | 99.39 100 | 97.88 140 | 98.64 166 | 98.56 210 | 57.79 361 | 99.80 154 | 96.02 201 | 99.87 68 | 99.40 150 |
|
MIMVSNet1 | | | 99.38 23 | 99.32 27 | 99.55 20 | 99.86 16 | 99.19 25 | 99.41 12 | 99.59 34 | 99.59 19 | 99.71 14 | 99.57 39 | 97.12 125 | 99.90 47 | 99.21 38 | 99.87 68 | 99.54 86 |
|
v148 | | | 98.45 127 | 98.60 91 | 98.00 226 | 99.44 109 | 94.98 246 | 97.44 208 | 99.06 196 | 98.30 115 | 99.32 77 | 98.97 139 | 96.65 158 | 99.62 264 | 98.37 80 | 99.85 71 | 99.39 151 |
|
WR-MVS | | | 98.40 132 | 98.19 138 | 99.03 106 | 99.00 200 | 97.65 149 | 96.85 245 | 98.94 218 | 98.57 103 | 98.89 140 | 98.50 218 | 95.60 203 | 99.85 88 | 97.54 118 | 99.85 71 | 99.59 58 |
|
CANet_DTU | | | 97.26 215 | 97.06 211 | 97.84 230 | 97.57 319 | 94.65 254 | 96.19 281 | 98.79 245 | 97.23 196 | 95.14 329 | 98.24 237 | 93.22 255 | 99.84 103 | 97.34 128 | 99.84 73 | 99.04 224 |
|
V42 | | | 98.78 72 | 98.78 60 | 98.76 143 | 99.44 109 | 97.04 176 | 98.27 118 | 99.19 170 | 97.87 142 | 99.25 89 | 99.16 98 | 96.84 145 | 99.78 184 | 99.21 38 | 99.84 73 | 99.46 129 |
|
VPA-MVSNet | | | 99.30 28 | 99.30 31 | 99.28 71 | 99.49 92 | 98.36 92 | 99.00 59 | 99.45 85 | 99.63 12 | 99.52 39 | 99.44 57 | 98.25 48 | 99.88 63 | 99.09 45 | 99.84 73 | 99.62 45 |
|
SixPastTwentyTwo | | | 98.75 75 | 98.62 86 | 99.16 85 | 99.83 19 | 97.96 122 | 99.28 29 | 98.20 274 | 99.37 36 | 99.70 15 | 99.65 25 | 92.65 265 | 99.93 26 | 99.04 48 | 99.84 73 | 99.60 52 |
|
HyFIR lowres test | | | 97.19 221 | 96.60 237 | 98.96 115 | 99.62 54 | 97.28 165 | 95.17 319 | 99.50 65 | 94.21 287 | 99.01 121 | 98.32 232 | 86.61 291 | 99.99 2 | 97.10 141 | 99.84 73 | 99.60 52 |
|
TDRefinement | | | 99.42 19 | 99.38 19 | 99.55 20 | 99.76 26 | 99.33 11 | 99.68 5 | 99.71 12 | 99.38 35 | 99.53 37 | 99.61 30 | 98.64 29 | 99.80 154 | 98.24 85 | 99.84 73 | 99.52 97 |
|
pm-mvs1 | | | 99.44 15 | 99.48 13 | 99.33 67 | 99.80 22 | 98.63 69 | 99.29 25 | 99.63 25 | 99.30 42 | 99.65 23 | 99.60 34 | 99.16 16 | 99.82 129 | 99.07 46 | 99.83 79 | 99.56 75 |
|
Baseline_NR-MVSNet | | | 98.98 53 | 98.86 53 | 99.36 57 | 99.82 20 | 98.55 77 | 97.47 207 | 99.57 43 | 99.37 36 | 99.21 95 | 99.61 30 | 96.76 153 | 99.83 117 | 98.06 93 | 99.83 79 | 99.71 27 |
|
Patchmtry | | | 97.35 208 | 96.97 214 | 98.50 184 | 97.31 331 | 96.47 197 | 98.18 124 | 98.92 224 | 98.95 82 | 98.78 155 | 99.37 65 | 85.44 302 | 99.85 88 | 95.96 205 | 99.83 79 | 99.17 213 |
|
ppachtmachnet_test | | | 97.50 197 | 97.74 175 | 96.78 276 | 98.70 253 | 91.23 320 | 94.55 331 | 99.05 200 | 96.36 229 | 99.21 95 | 98.79 172 | 96.39 173 | 99.78 184 | 96.74 158 | 99.82 82 | 99.34 170 |
|
v1neww | | | 98.70 82 | 98.76 63 | 98.52 179 | 99.47 99 | 96.30 207 | 98.03 142 | 99.18 174 | 97.92 130 | 99.26 87 | 99.08 112 | 96.91 138 | 99.78 184 | 99.19 40 | 99.82 82 | 99.47 125 |
|
v7new | | | 98.70 82 | 98.76 63 | 98.52 179 | 99.47 99 | 96.30 207 | 98.03 142 | 99.18 174 | 97.92 130 | 99.26 87 | 99.08 112 | 96.91 138 | 99.78 184 | 99.19 40 | 99.82 82 | 99.47 125 |
|
v6 | | | 98.70 82 | 98.76 63 | 98.52 179 | 99.47 99 | 96.30 207 | 98.03 142 | 99.18 174 | 97.92 130 | 99.27 82 | 99.08 112 | 96.91 138 | 99.78 184 | 99.19 40 | 99.82 82 | 99.48 117 |
|
EI-MVSNet | | | 98.40 132 | 98.51 97 | 98.04 224 | 99.10 175 | 94.73 250 | 97.20 223 | 98.87 230 | 98.97 78 | 99.06 110 | 99.02 129 | 96.00 187 | 99.80 154 | 98.58 68 | 99.82 82 | 99.60 52 |
|
NR-MVSNet | | | 98.95 56 | 98.82 56 | 99.36 57 | 99.16 167 | 98.72 66 | 99.22 34 | 99.20 164 | 99.10 65 | 99.72 13 | 98.76 177 | 96.38 175 | 99.86 77 | 98.00 98 | 99.82 82 | 99.50 104 |
|
MVSTER | | | 96.86 237 | 96.55 240 | 97.79 232 | 97.91 309 | 94.21 267 | 97.56 198 | 98.87 230 | 97.49 168 | 99.06 110 | 99.05 123 | 80.72 322 | 99.80 154 | 98.44 76 | 99.82 82 | 99.37 158 |
|
PMMVS2 | | | 98.07 161 | 98.08 154 | 98.04 224 | 99.41 115 | 94.59 256 | 94.59 330 | 99.40 98 | 97.50 166 | 98.82 152 | 98.83 165 | 96.83 146 | 99.84 103 | 97.50 121 | 99.81 89 | 99.71 27 |
|
K. test v3 | | | 98.00 165 | 97.66 180 | 99.03 106 | 99.79 24 | 97.56 153 | 99.19 39 | 92.47 346 | 99.62 16 | 99.52 39 | 99.66 22 | 89.61 280 | 99.96 8 | 99.25 34 | 99.81 89 | 99.56 75 |
|
CDS-MVSNet | | | 97.69 185 | 97.35 201 | 98.69 151 | 98.73 246 | 97.02 179 | 96.92 240 | 98.75 250 | 95.89 247 | 98.59 175 | 98.67 188 | 92.08 271 | 99.74 214 | 96.72 160 | 99.81 89 | 99.32 176 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
CSCG | | | 98.68 90 | 98.50 99 | 99.20 81 | 99.45 106 | 98.63 69 | 98.56 87 | 99.57 43 | 97.87 142 | 98.85 146 | 98.04 253 | 97.66 84 | 99.84 103 | 96.72 160 | 99.81 89 | 99.13 217 |
|
UniMVSNet (Re) | | | 98.87 62 | 98.71 71 | 99.35 62 | 99.24 138 | 98.73 64 | 97.73 177 | 99.38 103 | 98.93 83 | 99.12 104 | 98.73 179 | 96.77 151 | 99.86 77 | 98.63 67 | 99.80 93 | 99.46 129 |
|
FMVSNet2 | | | 98.49 122 | 98.40 117 | 98.75 145 | 98.90 219 | 97.14 175 | 98.61 82 | 99.13 187 | 98.59 99 | 99.19 97 | 99.28 75 | 94.14 242 | 99.82 129 | 97.97 99 | 99.80 93 | 99.29 186 |
|
XXY-MVS | | | 99.14 37 | 99.15 43 | 99.10 93 | 99.76 26 | 97.74 144 | 98.85 72 | 99.62 28 | 98.48 106 | 99.37 64 | 99.49 49 | 98.75 25 | 99.86 77 | 98.20 88 | 99.80 93 | 99.71 27 |
|
IS-MVSNet | | | 98.19 153 | 97.90 167 | 99.08 96 | 99.57 62 | 97.97 120 | 99.31 20 | 98.32 270 | 99.01 74 | 98.98 126 | 99.03 128 | 91.59 272 | 99.79 174 | 95.49 226 | 99.80 93 | 99.48 117 |
|
EI-MVSNet-UG-set | | | 98.69 87 | 98.71 71 | 98.62 159 | 99.10 175 | 96.37 203 | 97.23 219 | 98.87 230 | 99.20 50 | 99.19 97 | 98.99 134 | 97.30 110 | 99.85 88 | 98.77 62 | 99.79 97 | 99.65 37 |
|
pmmvs4 | | | 97.58 193 | 97.28 203 | 98.51 183 | 98.84 232 | 96.93 182 | 95.40 315 | 98.52 263 | 93.60 293 | 98.61 172 | 98.65 192 | 95.10 217 | 99.60 271 | 96.97 144 | 99.79 97 | 98.99 230 |
|
test20.03 | | | 98.78 72 | 98.77 62 | 98.78 139 | 99.46 103 | 97.20 169 | 97.78 170 | 99.24 157 | 99.04 71 | 99.41 58 | 98.90 151 | 97.65 85 | 99.76 199 | 97.70 112 | 99.79 97 | 99.39 151 |
|
Vis-MVSNet (Re-imp) | | | 97.46 203 | 97.16 208 | 98.34 202 | 99.55 73 | 96.10 214 | 98.94 64 | 98.44 266 | 98.32 114 | 98.16 197 | 98.62 201 | 88.76 285 | 99.73 219 | 93.88 262 | 99.79 97 | 99.18 209 |
|
EI-MVSNet-Vis-set | | | 98.68 90 | 98.70 74 | 98.63 157 | 99.09 178 | 96.40 201 | 97.23 219 | 98.86 234 | 99.20 50 | 99.18 100 | 98.97 139 | 97.29 112 | 99.85 88 | 98.72 64 | 99.78 101 | 99.64 40 |
|
LPG-MVS_test | | | 98.71 80 | 98.46 108 | 99.47 48 | 99.57 62 | 98.97 51 | 98.23 120 | 99.48 74 | 96.60 223 | 99.10 107 | 99.06 118 | 98.71 27 | 99.83 117 | 95.58 224 | 99.78 101 | 99.62 45 |
|
LGP-MVS_train | | | | | 99.47 48 | 99.57 62 | 98.97 51 | | 99.48 74 | 96.60 223 | 99.10 107 | 99.06 118 | 98.71 27 | 99.83 117 | 95.58 224 | 99.78 101 | 99.62 45 |
|
CLD-MVS | | | 97.49 199 | 97.16 208 | 98.48 186 | 99.07 182 | 97.03 177 | 94.71 328 | 99.21 160 | 94.46 278 | 98.06 204 | 97.16 294 | 97.57 90 | 99.48 305 | 94.46 243 | 99.78 101 | 98.95 235 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
new-patchmatchnet | | | 98.35 135 | 98.74 66 | 97.18 260 | 99.24 138 | 92.23 300 | 96.42 269 | 99.48 74 | 98.30 115 | 99.69 17 | 99.53 44 | 97.44 102 | 99.82 129 | 98.84 58 | 99.77 105 | 99.49 111 |
|
Patchmatch-RL test | | | 97.26 215 | 97.02 212 | 97.99 227 | 99.52 81 | 95.53 234 | 96.13 282 | 99.71 12 | 97.47 169 | 99.27 82 | 99.16 98 | 84.30 310 | 99.62 264 | 97.89 100 | 99.77 105 | 98.81 251 |
|
UniMVSNet_NR-MVSNet | | | 98.86 64 | 98.68 79 | 99.40 55 | 99.17 165 | 98.74 61 | 97.68 181 | 99.40 98 | 99.14 59 | 99.06 110 | 98.59 205 | 96.71 156 | 99.93 26 | 98.57 70 | 99.77 105 | 99.53 91 |
|
DU-MVS | | | 98.82 66 | 98.63 85 | 99.39 56 | 99.16 167 | 98.74 61 | 97.54 201 | 99.25 153 | 98.84 86 | 99.06 110 | 98.76 177 | 96.76 153 | 99.93 26 | 98.57 70 | 99.77 105 | 99.50 104 |
|
ACMMP++_ref | | | | | | | | | | | | | | | | 99.77 105 | |
|
wuyk23d | | | 96.06 259 | 97.62 184 | 91.38 338 | 98.65 266 | 98.57 76 | 98.85 72 | 96.95 302 | 96.86 210 | 99.90 5 | 99.16 98 | 99.18 12 | 98.40 349 | 89.23 325 | 99.77 105 | 77.18 354 |
|
ACMP | | 95.32 15 | 98.41 130 | 98.09 151 | 99.36 57 | 99.51 84 | 98.79 60 | 97.68 181 | 99.38 103 | 95.76 249 | 98.81 154 | 98.82 168 | 98.36 45 | 99.82 129 | 94.75 235 | 99.77 105 | 99.48 117 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
ACMH+ | | 96.62 9 | 99.08 42 | 99.00 49 | 99.33 67 | 99.71 34 | 98.83 57 | 98.60 83 | 99.58 36 | 99.11 61 | 99.53 37 | 99.18 92 | 98.81 23 | 99.67 246 | 96.71 163 | 99.77 105 | 99.50 104 |
|
ACMH | | 96.65 7 | 99.25 30 | 99.24 35 | 99.26 76 | 99.72 33 | 98.38 90 | 99.07 52 | 99.55 54 | 98.30 115 | 99.65 23 | 99.45 56 | 99.22 10 | 99.76 199 | 98.44 76 | 99.77 105 | 99.64 40 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
pmmvs5 | | | 97.64 189 | 97.49 189 | 98.08 220 | 99.14 172 | 95.12 245 | 96.70 253 | 99.05 200 | 93.77 291 | 98.62 170 | 98.83 165 | 93.23 254 | 99.75 205 | 98.33 83 | 99.76 114 | 99.36 164 |
|
COLMAP_ROB | | 96.50 10 | 98.99 49 | 98.85 54 | 99.41 53 | 99.58 57 | 99.10 43 | 98.74 75 | 99.56 49 | 99.09 68 | 99.33 72 | 99.19 90 | 98.40 43 | 99.72 228 | 95.98 204 | 99.76 114 | 99.42 143 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
SD-MVS | | | 98.40 132 | 98.68 79 | 97.54 248 | 98.96 206 | 97.99 115 | 97.88 162 | 99.36 111 | 98.20 121 | 99.63 26 | 99.04 125 | 98.76 24 | 95.33 355 | 96.56 175 | 99.74 116 | 99.31 180 |
|
PM-MVS | | | 98.82 66 | 98.72 70 | 99.12 90 | 99.64 50 | 98.54 80 | 97.98 153 | 99.68 16 | 97.62 154 | 99.34 71 | 99.18 92 | 97.54 94 | 99.77 194 | 97.79 105 | 99.74 116 | 99.04 224 |
|
XVG-ACMP-BASELINE | | | 98.56 109 | 98.34 126 | 99.22 80 | 99.54 77 | 98.59 74 | 97.71 178 | 99.46 82 | 97.25 191 | 98.98 126 | 98.99 134 | 97.54 94 | 99.84 103 | 95.88 207 | 99.74 116 | 99.23 197 |
|
Anonymous20231206 | | | 98.21 151 | 98.21 135 | 98.20 212 | 99.51 84 | 95.43 238 | 98.13 128 | 99.32 129 | 96.16 239 | 98.93 136 | 98.82 168 | 96.00 187 | 99.83 117 | 97.32 129 | 99.73 119 | 99.36 164 |
|
jason | | | 97.45 204 | 97.35 201 | 97.76 234 | 99.24 138 | 93.93 274 | 95.86 297 | 98.42 267 | 94.24 286 | 98.50 183 | 98.13 242 | 94.82 225 | 99.91 43 | 97.22 132 | 99.73 119 | 99.43 140 |
jason: jason. |
N_pmnet | | | 97.63 190 | 97.17 207 | 98.99 113 | 99.27 134 | 97.86 131 | 95.98 285 | 93.41 338 | 95.25 263 | 99.47 49 | 98.90 151 | 95.63 202 | 99.85 88 | 96.91 146 | 99.73 119 | 99.27 188 |
|
USDC | | | 97.41 207 | 97.40 195 | 97.44 253 | 98.94 209 | 93.67 284 | 95.17 319 | 99.53 59 | 94.03 289 | 98.97 128 | 99.10 109 | 95.29 212 | 99.34 321 | 95.84 213 | 99.73 119 | 99.30 183 |
|
Gipuma | | | 99.03 45 | 99.16 41 | 98.64 155 | 99.94 3 | 98.51 82 | 99.32 17 | 99.75 8 | 99.58 21 | 98.60 174 | 99.62 28 | 98.22 52 | 99.51 300 | 97.70 112 | 99.73 119 | 97.89 292 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
lessismore_v0 | | | | | 98.97 114 | 99.73 28 | 97.53 155 | | 86.71 355 | | 99.37 64 | 99.52 45 | 89.93 278 | 99.92 34 | 98.99 51 | 99.72 124 | 99.44 135 |
|
CP-MVS | | | 98.70 82 | 98.42 115 | 99.52 38 | 99.36 121 | 99.12 40 | 98.72 77 | 99.36 111 | 97.54 164 | 98.30 194 | 98.40 224 | 97.86 75 | 99.89 56 | 96.53 178 | 99.72 124 | 99.56 75 |
|
SteuartSystems-ACMMP | | | 98.79 69 | 98.54 94 | 99.54 25 | 99.73 28 | 99.16 29 | 98.23 120 | 99.31 131 | 97.92 130 | 98.90 138 | 98.90 151 | 98.00 67 | 99.88 63 | 96.15 198 | 99.72 124 | 99.58 65 |
Skip Steuart: Steuart Systems R&D Blog. |
LF4IMVS | | | 97.90 170 | 97.69 176 | 98.52 179 | 99.17 165 | 97.66 148 | 97.19 226 | 99.47 80 | 96.31 232 | 97.85 217 | 98.20 241 | 96.71 156 | 99.52 295 | 94.62 239 | 99.72 124 | 98.38 280 |
|
HPM-MVS_fast | | | 99.01 47 | 98.82 56 | 99.57 16 | 99.71 34 | 99.35 9 | 99.00 59 | 99.50 65 | 97.33 183 | 98.94 135 | 98.86 160 | 98.75 25 | 99.82 129 | 97.53 119 | 99.71 128 | 99.56 75 |
|
FMVSNet5 | | | 96.01 260 | 95.20 271 | 98.41 193 | 97.53 322 | 96.10 214 | 98.74 75 | 99.50 65 | 97.22 199 | 98.03 207 | 99.04 125 | 69.80 353 | 99.88 63 | 97.27 131 | 99.71 128 | 99.25 193 |
|
RPSCF | | | 98.62 103 | 98.36 123 | 99.42 51 | 99.65 47 | 99.42 5 | 98.55 89 | 99.57 43 | 97.72 149 | 98.90 138 | 99.26 79 | 96.12 182 | 99.52 295 | 95.72 217 | 99.71 128 | 99.32 176 |
|
MP-MVS-pluss | | | 98.57 108 | 98.23 134 | 99.60 12 | 99.69 42 | 99.35 9 | 97.16 229 | 99.38 103 | 94.87 271 | 98.97 128 | 98.99 134 | 98.01 66 | 99.88 63 | 97.29 130 | 99.70 131 | 99.58 65 |
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
zzz-MVS | | | 98.79 69 | 98.52 96 | 99.61 9 | 99.67 44 | 99.36 7 | 97.33 212 | 99.20 164 | 98.83 87 | 98.89 140 | 98.90 151 | 96.98 135 | 99.92 34 | 97.16 134 | 99.70 131 | 99.56 75 |
|
MTAPA | | | 98.88 61 | 98.64 84 | 99.61 9 | 99.67 44 | 99.36 7 | 98.43 111 | 99.20 164 | 98.83 87 | 98.89 140 | 98.90 151 | 96.98 135 | 99.92 34 | 97.16 134 | 99.70 131 | 99.56 75 |
|
Regformer-3 | | | 98.61 104 | 98.61 89 | 98.63 157 | 99.02 197 | 96.53 194 | 97.17 227 | 98.84 236 | 99.13 60 | 99.10 107 | 98.85 162 | 97.24 118 | 99.79 174 | 98.41 79 | 99.70 131 | 99.57 70 |
|
Regformer-4 | | | 98.73 78 | 98.68 79 | 98.89 125 | 99.02 197 | 97.22 168 | 97.17 227 | 99.06 196 | 99.21 47 | 99.17 101 | 98.85 162 | 97.45 101 | 99.86 77 | 98.48 75 | 99.70 131 | 99.60 52 |
|
APDe-MVS | | | 98.99 49 | 98.79 59 | 99.60 12 | 99.21 150 | 99.15 34 | 98.87 69 | 99.48 74 | 97.57 160 | 99.35 68 | 99.24 82 | 97.83 76 | 99.89 56 | 97.88 102 | 99.70 131 | 99.75 21 |
|
test1235678 | | | 97.06 228 | 96.84 222 | 97.73 236 | 98.55 275 | 94.46 263 | 94.80 326 | 99.36 111 | 96.85 211 | 98.83 149 | 98.26 235 | 92.72 264 | 99.82 129 | 92.49 294 | 99.70 131 | 98.91 241 |
|
tfpnnormal | | | 98.90 60 | 98.90 52 | 98.91 122 | 99.67 44 | 97.82 136 | 99.00 59 | 99.44 88 | 99.45 29 | 99.51 43 | 99.24 82 | 98.20 55 | 99.86 77 | 95.92 206 | 99.69 138 | 99.04 224 |
|
GBi-Net | | | 98.65 94 | 98.47 105 | 99.17 82 | 98.90 219 | 98.24 95 | 99.20 35 | 99.44 88 | 98.59 99 | 98.95 131 | 99.55 41 | 94.14 242 | 99.86 77 | 97.77 107 | 99.69 138 | 99.41 145 |
|
test1 | | | 98.65 94 | 98.47 105 | 99.17 82 | 98.90 219 | 98.24 95 | 99.20 35 | 99.44 88 | 98.59 99 | 98.95 131 | 99.55 41 | 94.14 242 | 99.86 77 | 97.77 107 | 99.69 138 | 99.41 145 |
|
FMVSNet3 | | | 97.50 197 | 97.24 204 | 98.29 207 | 98.08 302 | 95.83 226 | 97.86 165 | 98.91 226 | 97.89 139 | 98.95 131 | 98.95 143 | 87.06 289 | 99.81 142 | 97.77 107 | 99.69 138 | 99.23 197 |
|
ACMMP | | | 98.75 75 | 98.50 99 | 99.52 38 | 99.56 69 | 99.16 29 | 98.87 69 | 99.37 107 | 97.16 200 | 98.82 152 | 99.01 131 | 97.71 83 | 99.87 72 | 96.29 190 | 99.69 138 | 99.54 86 |
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 |
SMA-MVS | | | 98.47 124 | 98.11 148 | 99.53 32 | 99.16 167 | 99.27 16 | 98.05 140 | 99.30 138 | 94.34 284 | 99.22 94 | 99.10 109 | 97.72 82 | 99.79 174 | 96.45 183 | 99.68 143 | 99.53 91 |
|
XVG-OURS | | | 98.53 118 | 98.34 126 | 99.11 91 | 99.50 86 | 98.82 59 | 95.97 286 | 99.50 65 | 97.30 187 | 99.05 115 | 98.98 137 | 99.35 7 | 99.32 324 | 95.72 217 | 99.68 143 | 99.18 209 |
|
EPNet | | | 96.14 258 | 95.44 264 | 98.25 209 | 90.76 357 | 95.50 236 | 97.92 158 | 94.65 323 | 98.97 78 | 92.98 344 | 98.85 162 | 89.12 284 | 99.87 72 | 95.99 203 | 99.68 143 | 99.39 151 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
EG-PatchMatch MVS | | | 98.99 49 | 99.01 48 | 98.94 118 | 99.50 86 | 97.47 157 | 98.04 141 | 99.59 34 | 98.15 125 | 99.40 60 | 99.36 67 | 98.58 33 | 99.76 199 | 98.78 59 | 99.68 143 | 99.59 58 |
|
ACMMP++ | | | | | | | | | | | | | | | | 99.68 143 | |
|
EPP-MVSNet | | | 98.30 140 | 98.04 157 | 99.07 97 | 99.56 69 | 97.83 133 | 99.29 25 | 98.07 278 | 99.03 72 | 98.59 175 | 99.13 105 | 92.16 269 | 99.90 47 | 96.87 150 | 99.68 143 | 99.49 111 |
|
ACMMP_Plus | | | 98.75 75 | 98.48 103 | 99.57 16 | 99.58 57 | 99.29 13 | 97.82 169 | 99.25 153 | 96.94 206 | 98.78 155 | 99.12 106 | 98.02 65 | 99.84 103 | 97.13 138 | 99.67 149 | 99.59 58 |
|
HPM-MVS | | | 98.79 69 | 98.53 95 | 99.59 15 | 99.65 47 | 99.29 13 | 99.16 42 | 99.43 93 | 96.74 214 | 98.61 172 | 98.38 225 | 98.62 30 | 99.87 72 | 96.47 181 | 99.67 149 | 99.59 58 |
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023 |
3Dnovator | | 98.27 2 | 98.81 68 | 98.73 67 | 99.05 103 | 98.76 243 | 97.81 138 | 99.25 32 | 99.30 138 | 98.57 103 | 98.55 180 | 99.33 72 | 97.95 73 | 99.90 47 | 97.16 134 | 99.67 149 | 99.44 135 |
|
PMVS | | 91.26 20 | 97.86 175 | 97.94 163 | 97.65 240 | 99.71 34 | 97.94 125 | 98.52 91 | 98.68 256 | 98.99 75 | 97.52 250 | 99.35 68 | 97.41 104 | 98.18 350 | 91.59 304 | 99.67 149 | 96.82 329 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
DP-MVS | | | 98.93 57 | 98.81 58 | 99.28 71 | 99.21 150 | 98.45 86 | 98.46 109 | 99.33 126 | 99.63 12 | 99.48 46 | 99.15 102 | 97.23 120 | 99.75 205 | 97.17 133 | 99.66 153 | 99.63 44 |
|
MVS_111021_LR | | | 98.30 140 | 98.12 147 | 98.83 132 | 99.16 167 | 98.03 113 | 96.09 283 | 99.30 138 | 97.58 158 | 98.10 201 | 98.24 237 | 98.25 48 | 99.34 321 | 96.69 164 | 99.65 154 | 99.12 218 |
|
ACMM | | 96.08 12 | 98.91 59 | 98.73 67 | 99.48 45 | 99.55 73 | 99.14 35 | 98.07 136 | 99.37 107 | 97.62 154 | 99.04 118 | 98.96 142 | 98.84 21 | 99.79 174 | 97.43 125 | 99.65 154 | 99.49 111 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
VDD-MVS | | | 98.56 109 | 98.39 119 | 99.07 97 | 99.13 173 | 98.07 110 | 98.59 85 | 97.01 299 | 99.59 19 | 99.11 105 | 99.27 77 | 94.82 225 | 99.79 174 | 98.34 81 | 99.63 156 | 99.34 170 |
|
TransMVSNet (Re) | | | 99.44 15 | 99.47 15 | 99.36 57 | 99.80 22 | 98.58 75 | 99.27 31 | 99.57 43 | 99.39 33 | 99.75 12 | 99.62 28 | 99.17 14 | 99.83 117 | 99.06 47 | 99.62 157 | 99.66 33 |
|
abl_6 | | | 98.99 49 | 98.78 60 | 99.61 9 | 99.45 106 | 99.46 4 | 98.60 83 | 99.50 65 | 98.59 99 | 99.24 90 | 99.04 125 | 98.54 37 | 99.89 56 | 96.45 183 | 99.62 157 | 99.50 104 |
|
mPP-MVS | | | 98.64 96 | 98.34 126 | 99.54 25 | 99.54 77 | 99.17 27 | 98.63 80 | 99.24 157 | 97.47 169 | 98.09 202 | 98.68 186 | 97.62 89 | 99.89 56 | 96.22 192 | 99.62 157 | 99.57 70 |
|
DeepPCF-MVS | | 96.93 5 | 98.32 138 | 98.01 158 | 99.23 79 | 98.39 286 | 98.97 51 | 95.03 322 | 99.18 174 | 96.88 209 | 99.33 72 | 98.78 173 | 98.16 57 | 99.28 330 | 96.74 158 | 99.62 157 | 99.44 135 |
|
AllTest | | | 98.44 128 | 98.20 136 | 99.16 85 | 99.50 86 | 98.55 77 | 98.25 119 | 99.58 36 | 96.80 212 | 98.88 143 | 99.06 118 | 97.65 85 | 99.57 282 | 94.45 244 | 99.61 161 | 99.37 158 |
|
TestCases | | | | | 99.16 85 | 99.50 86 | 98.55 77 | | 99.58 36 | 96.80 212 | 98.88 143 | 99.06 118 | 97.65 85 | 99.57 282 | 94.45 244 | 99.61 161 | 99.37 158 |
|
MP-MVS | | | 98.46 126 | 98.09 151 | 99.54 25 | 99.57 62 | 99.22 21 | 98.50 96 | 99.19 170 | 97.61 156 | 97.58 244 | 98.66 190 | 97.40 105 | 99.88 63 | 94.72 238 | 99.60 163 | 99.54 86 |
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo. |
HFP-MVS | | | 98.71 80 | 98.44 112 | 99.51 40 | 99.49 92 | 99.16 29 | 98.52 91 | 99.31 131 | 97.47 169 | 98.58 177 | 98.50 218 | 97.97 71 | 99.85 88 | 96.57 172 | 99.59 164 | 99.53 91 |
|
#test# | | | 98.50 121 | 98.16 142 | 99.51 40 | 99.49 92 | 99.16 29 | 98.03 142 | 99.31 131 | 96.30 233 | 98.58 177 | 98.50 218 | 97.97 71 | 99.85 88 | 95.68 220 | 99.59 164 | 99.53 91 |
|
CVMVSNet | | | 96.25 257 | 97.21 205 | 93.38 335 | 99.10 175 | 80.56 355 | 97.20 223 | 98.19 276 | 96.94 206 | 99.00 123 | 99.02 129 | 89.50 282 | 99.80 154 | 96.36 188 | 99.59 164 | 99.78 15 |
|
ACMMPR | | | 98.70 82 | 98.42 115 | 99.54 25 | 99.52 81 | 99.14 35 | 98.52 91 | 99.31 131 | 97.47 169 | 98.56 179 | 98.54 213 | 97.75 81 | 99.88 63 | 96.57 172 | 99.59 164 | 99.58 65 |
|
PGM-MVS | | | 98.66 93 | 98.37 122 | 99.55 20 | 99.53 79 | 99.18 26 | 98.23 120 | 99.49 71 | 97.01 204 | 98.69 162 | 98.88 157 | 98.00 67 | 99.89 56 | 95.87 210 | 99.59 164 | 99.58 65 |
|
DELS-MVS | | | 98.27 144 | 98.20 136 | 98.48 186 | 98.86 226 | 96.70 191 | 95.60 308 | 99.20 164 | 97.73 148 | 98.45 185 | 98.71 181 | 97.50 96 | 99.82 129 | 98.21 87 | 99.59 164 | 98.93 238 |
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 |
region2R | | | 98.69 87 | 98.40 117 | 99.54 25 | 99.53 79 | 99.17 27 | 98.52 91 | 99.31 131 | 97.46 174 | 98.44 186 | 98.51 215 | 97.83 76 | 99.88 63 | 96.46 182 | 99.58 170 | 99.58 65 |
|
114514_t | | | 96.50 252 | 95.77 255 | 98.69 151 | 99.48 97 | 97.43 160 | 97.84 167 | 99.55 54 | 81.42 350 | 96.51 297 | 98.58 206 | 95.53 205 | 99.67 246 | 93.41 276 | 99.58 170 | 98.98 231 |
|
PHI-MVS | | | 98.29 143 | 97.95 161 | 99.34 65 | 98.44 283 | 99.16 29 | 98.12 130 | 99.38 103 | 96.01 245 | 98.06 204 | 98.43 222 | 97.80 80 | 99.67 246 | 95.69 219 | 99.58 170 | 99.20 203 |
|
TinyColmap | | | 97.89 171 | 97.98 159 | 97.60 244 | 98.86 226 | 94.35 264 | 96.21 278 | 99.44 88 | 97.45 176 | 99.06 110 | 98.88 157 | 97.99 69 | 99.28 330 | 94.38 250 | 99.58 170 | 99.18 209 |
|
test_part1 | | | | | | | | | 99.28 142 | | | | 97.56 91 | | | 99.57 174 | 99.53 91 |
|
ESAPD | | | 98.25 148 | 97.83 171 | 99.50 42 | 99.36 121 | 99.10 43 | 97.25 217 | 99.28 142 | 96.66 220 | 99.05 115 | 98.71 181 | 97.56 91 | 99.86 77 | 93.00 281 | 99.57 174 | 99.53 91 |
|
Regformer-1 | | | 98.55 113 | 98.44 112 | 98.87 127 | 98.85 229 | 97.29 163 | 96.91 241 | 98.99 217 | 98.97 78 | 98.99 124 | 98.64 195 | 97.26 116 | 99.81 142 | 97.79 105 | 99.57 174 | 99.51 99 |
|
Regformer-2 | | | 98.60 105 | 98.46 108 | 99.02 109 | 98.85 229 | 97.71 146 | 96.91 241 | 99.09 193 | 98.98 77 | 99.01 121 | 98.64 195 | 97.37 107 | 99.84 103 | 97.75 111 | 99.57 174 | 99.52 97 |
|
MVSFormer | | | 98.26 146 | 98.43 114 | 97.77 233 | 98.88 224 | 93.89 278 | 99.39 13 | 99.56 49 | 99.11 61 | 98.16 197 | 98.13 242 | 93.81 249 | 99.97 3 | 99.26 32 | 99.57 174 | 99.43 140 |
|
lupinMVS | | | 97.06 228 | 96.86 220 | 97.65 240 | 98.88 224 | 93.89 278 | 95.48 312 | 97.97 280 | 93.53 294 | 98.16 197 | 97.58 274 | 93.81 249 | 99.91 43 | 96.77 156 | 99.57 174 | 99.17 213 |
|
MVS_111021_HR | | | 98.25 148 | 98.08 154 | 98.75 145 | 99.09 178 | 97.46 158 | 95.97 286 | 99.27 147 | 97.60 157 | 97.99 208 | 98.25 236 | 98.15 59 | 99.38 318 | 96.87 150 | 99.57 174 | 99.42 143 |
|
OPM-MVS | | | 98.56 109 | 98.32 130 | 99.25 77 | 99.41 115 | 98.73 64 | 97.13 231 | 99.18 174 | 97.10 203 | 98.75 159 | 98.92 147 | 98.18 56 | 99.65 259 | 96.68 165 | 99.56 181 | 99.37 158 |
|
PVSNet_Blended | | | 96.88 236 | 96.68 231 | 97.47 251 | 98.92 215 | 93.77 282 | 94.71 328 | 99.43 93 | 90.98 324 | 97.62 240 | 97.36 290 | 96.82 147 | 99.67 246 | 94.73 236 | 99.56 181 | 98.98 231 |
|
DeepC-MVS_fast | | 96.85 6 | 98.30 140 | 98.15 144 | 98.75 145 | 98.61 268 | 97.23 166 | 97.76 174 | 99.09 193 | 97.31 186 | 98.75 159 | 98.66 190 | 97.56 91 | 99.64 261 | 96.10 200 | 99.55 183 | 99.39 151 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
APD-MVS | | | 98.10 158 | 97.67 177 | 99.42 51 | 99.11 174 | 98.93 55 | 97.76 174 | 99.28 142 | 94.97 268 | 98.72 161 | 98.77 175 | 97.04 129 | 99.85 88 | 93.79 265 | 99.54 184 | 99.49 111 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
DSMNet-mixed | | | 97.42 206 | 97.60 185 | 96.87 272 | 99.15 171 | 91.46 307 | 98.54 90 | 99.12 189 | 92.87 301 | 97.58 244 | 99.63 27 | 96.21 179 | 99.90 47 | 95.74 216 | 99.54 184 | 99.27 188 |
|
CPTT-MVS | | | 97.84 180 | 97.36 199 | 99.27 74 | 99.31 130 | 98.46 85 | 98.29 116 | 99.27 147 | 94.90 270 | 97.83 222 | 98.37 226 | 94.90 220 | 99.84 103 | 93.85 264 | 99.54 184 | 99.51 99 |
|
1112_ss | | | 97.29 214 | 96.86 220 | 98.58 167 | 99.34 127 | 96.32 204 | 96.75 250 | 99.58 36 | 93.14 298 | 96.89 283 | 97.48 281 | 92.11 270 | 99.86 77 | 96.91 146 | 99.54 184 | 99.57 70 |
|
XVS | | | 98.72 79 | 98.45 110 | 99.53 32 | 99.46 103 | 99.21 22 | 98.65 78 | 99.34 121 | 98.62 97 | 97.54 248 | 98.63 199 | 97.50 96 | 99.83 117 | 96.79 154 | 99.53 188 | 99.56 75 |
|
X-MVStestdata | | | 94.32 297 | 92.59 314 | 99.53 32 | 99.46 103 | 99.21 22 | 98.65 78 | 99.34 121 | 98.62 97 | 97.54 248 | 45.85 354 | 97.50 96 | 99.83 117 | 96.79 154 | 99.53 188 | 99.56 75 |
|
Test_1112_low_res | | | 96.99 233 | 96.55 240 | 98.31 205 | 99.35 125 | 95.47 237 | 95.84 300 | 99.53 59 | 91.51 319 | 96.80 288 | 98.48 221 | 91.36 273 | 99.83 117 | 96.58 170 | 99.53 188 | 99.62 45 |
|
HQP_MVS | | | 97.99 167 | 97.67 177 | 98.93 119 | 99.19 160 | 97.65 149 | 97.77 172 | 99.27 147 | 98.20 121 | 97.79 231 | 97.98 256 | 94.90 220 | 99.70 231 | 94.42 246 | 99.51 191 | 99.45 133 |
|
plane_prior5 | | | | | | | | | 99.27 147 | | | | | 99.70 231 | 94.42 246 | 99.51 191 | 99.45 133 |
|
ab-mvs | | | 98.41 130 | 98.36 123 | 98.59 166 | 99.19 160 | 97.23 166 | 99.32 17 | 98.81 242 | 97.66 151 | 98.62 170 | 99.40 64 | 96.82 147 | 99.80 154 | 95.88 207 | 99.51 191 | 98.75 260 |
|
OMC-MVS | | | 97.88 173 | 97.49 189 | 99.04 105 | 98.89 223 | 98.63 69 | 96.94 237 | 99.25 153 | 95.02 266 | 98.53 182 | 98.51 215 | 97.27 113 | 99.47 306 | 93.50 274 | 99.51 191 | 99.01 228 |
|
CMPMVS | | 75.91 23 | 96.29 255 | 95.44 264 | 98.84 131 | 96.25 347 | 98.69 67 | 97.02 233 | 99.12 189 | 88.90 336 | 97.83 222 | 98.86 160 | 89.51 281 | 98.90 344 | 91.92 297 | 99.51 191 | 98.92 239 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
ambc | | | | | 98.24 210 | 98.82 237 | 95.97 219 | 98.62 81 | 99.00 216 | | 99.27 82 | 99.21 87 | 96.99 134 | 99.50 301 | 96.55 176 | 99.50 196 | 99.26 191 |
|
TSAR-MVS + MP. | | | 98.63 98 | 98.49 102 | 99.06 102 | 99.64 50 | 97.90 128 | 98.51 95 | 98.94 218 | 96.96 205 | 99.24 90 | 98.89 156 | 97.83 76 | 99.81 142 | 96.88 149 | 99.49 197 | 99.48 117 |
|
TSAR-MVS + GP. | | | 98.18 154 | 97.98 159 | 98.77 141 | 98.71 249 | 97.88 129 | 96.32 273 | 98.66 257 | 96.33 230 | 99.23 93 | 98.51 215 | 97.48 100 | 99.40 314 | 97.16 134 | 99.46 198 | 99.02 227 |
|
PCF-MVS | | 92.86 18 | 94.36 295 | 93.00 313 | 98.42 192 | 98.70 253 | 97.56 153 | 93.16 343 | 99.11 191 | 79.59 351 | 97.55 247 | 97.43 285 | 92.19 268 | 99.73 219 | 79.85 351 | 99.45 199 | 97.97 291 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
new_pmnet | | | 96.99 233 | 96.76 225 | 97.67 238 | 98.72 247 | 94.89 248 | 95.95 293 | 98.20 274 | 92.62 304 | 98.55 180 | 98.54 213 | 94.88 223 | 99.52 295 | 93.96 259 | 99.44 200 | 98.59 270 |
|
APD-MVS_3200maxsize | | | 98.84 65 | 98.61 89 | 99.53 32 | 99.19 160 | 99.27 16 | 98.49 97 | 99.33 126 | 98.64 95 | 99.03 120 | 98.98 137 | 97.89 74 | 99.85 88 | 96.54 177 | 99.42 201 | 99.46 129 |
|
MSLP-MVS++ | | | 98.02 162 | 98.14 146 | 97.64 242 | 98.58 271 | 95.19 242 | 97.48 205 | 99.23 159 | 97.47 169 | 97.90 212 | 98.62 201 | 97.04 129 | 98.81 347 | 97.55 117 | 99.41 202 | 98.94 237 |
|
QAPM | | | 97.31 211 | 96.81 223 | 98.82 133 | 98.80 241 | 97.49 156 | 99.06 53 | 99.19 170 | 90.22 329 | 97.69 237 | 99.16 98 | 96.91 138 | 99.90 47 | 90.89 318 | 99.41 202 | 99.07 221 |
|
MVS-HIRNet | | | 94.32 297 | 95.62 260 | 90.42 339 | 98.46 281 | 75.36 356 | 96.29 274 | 89.13 354 | 95.25 263 | 95.38 326 | 99.75 7 | 92.88 262 | 99.19 333 | 94.07 257 | 99.39 204 | 96.72 331 |
|
CDPH-MVS | | | 97.26 215 | 96.66 234 | 99.07 97 | 99.00 200 | 98.15 101 | 96.03 284 | 99.01 212 | 91.21 323 | 97.79 231 | 97.85 261 | 96.89 143 | 99.69 235 | 92.75 289 | 99.38 205 | 99.39 151 |
|
VPNet | | | 98.87 62 | 98.83 55 | 99.01 110 | 99.70 40 | 97.62 152 | 98.43 111 | 99.35 117 | 99.47 27 | 99.28 80 | 99.05 123 | 96.72 155 | 99.82 129 | 98.09 91 | 99.36 206 | 99.59 58 |
|
plane_prior | | | | | | | 97.65 149 | 97.07 232 | | 96.72 215 | | | | | | 99.36 206 | |
|
test_normal | | | 97.58 193 | 97.41 194 | 98.10 216 | 99.03 195 | 95.72 229 | 96.21 278 | 97.05 298 | 96.71 217 | 98.65 164 | 98.12 246 | 93.87 246 | 99.69 235 | 97.68 116 | 99.35 208 | 98.88 244 |
|
HPM-MVS++ | | | 98.10 158 | 97.64 182 | 99.48 45 | 99.09 178 | 99.13 38 | 97.52 202 | 98.75 250 | 97.46 174 | 96.90 282 | 97.83 262 | 96.01 186 | 99.84 103 | 95.82 214 | 99.35 208 | 99.46 129 |
|
LS3D | | | 98.63 98 | 98.38 121 | 99.36 57 | 97.25 332 | 99.38 6 | 99.12 48 | 99.32 129 | 99.21 47 | 98.44 186 | 98.88 157 | 97.31 109 | 99.80 154 | 96.58 170 | 99.34 210 | 98.92 239 |
|
test12356 | | | 94.85 283 | 95.12 273 | 94.03 328 | 98.25 292 | 83.12 350 | 93.85 338 | 99.33 126 | 94.17 288 | 97.28 266 | 97.20 291 | 85.83 297 | 99.75 205 | 90.85 319 | 99.33 211 | 99.22 201 |
|
CNVR-MVS | | | 98.17 156 | 97.87 170 | 99.07 97 | 98.67 260 | 98.24 95 | 97.01 234 | 98.93 221 | 97.25 191 | 97.62 240 | 98.34 229 | 97.27 113 | 99.57 282 | 96.42 186 | 99.33 211 | 99.39 151 |
|
sss | | | 97.21 219 | 96.93 215 | 98.06 222 | 98.83 234 | 95.22 241 | 96.75 250 | 98.48 265 | 94.49 276 | 97.27 267 | 97.90 260 | 92.77 263 | 99.80 154 | 96.57 172 | 99.32 213 | 99.16 216 |
|
3Dnovator+ | | 97.89 3 | 98.69 87 | 98.51 97 | 99.24 78 | 98.81 239 | 98.40 88 | 99.02 54 | 99.19 170 | 98.99 75 | 98.07 203 | 99.28 75 | 97.11 127 | 99.84 103 | 96.84 152 | 99.32 213 | 99.47 125 |
|
Patchmatch-test | | | 96.55 249 | 96.34 246 | 97.17 261 | 98.35 288 | 93.06 290 | 98.40 113 | 97.79 283 | 97.33 183 | 98.41 189 | 98.67 188 | 83.68 314 | 99.69 235 | 95.16 228 | 99.31 215 | 98.77 257 |
|
LCM-MVSNet-Re | | | 98.64 96 | 98.48 103 | 99.11 91 | 98.85 229 | 98.51 82 | 98.49 97 | 99.83 3 | 98.37 108 | 99.69 17 | 99.46 52 | 98.21 54 | 99.92 34 | 94.13 255 | 99.30 216 | 98.91 241 |
|
Test4 | | | 97.43 205 | 97.18 206 | 98.18 214 | 99.05 190 | 96.02 217 | 96.62 259 | 99.09 193 | 96.25 234 | 98.63 169 | 97.70 268 | 90.49 276 | 99.68 240 | 97.50 121 | 99.30 216 | 98.83 248 |
|
EPNet_dtu | | | 94.93 278 | 94.78 279 | 95.38 313 | 93.58 356 | 87.68 331 | 96.78 247 | 95.69 320 | 97.35 182 | 89.14 352 | 98.09 250 | 88.15 287 | 99.49 302 | 94.95 233 | 99.30 216 | 98.98 231 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
TAPA-MVS | | 96.21 11 | 96.63 246 | 95.95 253 | 98.65 154 | 98.93 211 | 98.09 105 | 96.93 238 | 99.28 142 | 83.58 348 | 98.13 200 | 97.78 264 | 96.13 181 | 99.40 314 | 93.52 272 | 99.29 219 | 98.45 275 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
PVSNet | | 93.40 17 | 95.67 265 | 95.70 257 | 95.57 311 | 98.83 234 | 88.57 326 | 92.50 345 | 97.72 286 | 92.69 303 | 96.49 300 | 96.44 308 | 93.72 253 | 99.43 312 | 93.61 269 | 99.28 220 | 98.71 262 |
|
LFMVS | | | 97.20 220 | 96.72 227 | 98.64 155 | 98.72 247 | 96.95 181 | 98.93 66 | 94.14 336 | 99.74 5 | 98.78 155 | 99.01 131 | 84.45 307 | 99.73 219 | 97.44 124 | 99.27 221 | 99.25 193 |
|
ITE_SJBPF | | | | | 98.87 127 | 99.22 144 | 98.48 84 | | 99.35 117 | 97.50 166 | 98.28 195 | 98.60 204 | 97.64 88 | 99.35 320 | 93.86 263 | 99.27 221 | 98.79 255 |
|
HQP3-MVS | | | | | | | | | 99.04 203 | | | | | | | 99.26 223 | |
|
HQP-MVS | | | 97.00 232 | 96.49 242 | 98.55 174 | 98.67 260 | 96.79 185 | 96.29 274 | 99.04 203 | 96.05 242 | 95.55 320 | 96.84 299 | 93.84 247 | 99.54 289 | 92.82 286 | 99.26 223 | 99.32 176 |
|
MCST-MVS | | | 98.00 165 | 97.63 183 | 99.10 93 | 99.24 138 | 98.17 100 | 96.89 243 | 98.73 253 | 95.66 250 | 97.92 209 | 97.70 268 | 97.17 123 | 99.66 254 | 96.18 196 | 99.23 225 | 99.47 125 |
|
Patchmatch-test1 | | | 96.44 254 | 96.72 227 | 95.60 310 | 98.24 294 | 88.35 328 | 95.85 299 | 96.88 306 | 96.11 240 | 97.67 238 | 98.57 207 | 93.10 258 | 99.69 235 | 94.79 234 | 99.22 226 | 98.77 257 |
|
MSDG | | | 97.71 184 | 97.52 188 | 98.28 208 | 98.91 218 | 96.82 184 | 94.42 332 | 99.37 107 | 97.65 152 | 98.37 193 | 98.29 234 | 97.40 105 | 99.33 323 | 94.09 256 | 99.22 226 | 98.68 268 |
|
MIMVSNet | | | 96.62 247 | 96.25 250 | 97.71 237 | 99.04 192 | 94.66 253 | 99.16 42 | 96.92 304 | 97.23 196 | 97.87 214 | 99.10 109 | 86.11 295 | 99.65 259 | 91.65 301 | 99.21 228 | 98.82 250 |
|
test_prior3 | | | 97.48 202 | 97.00 213 | 98.95 116 | 98.69 255 | 97.95 123 | 95.74 303 | 99.03 205 | 96.48 225 | 96.11 306 | 97.63 272 | 95.92 194 | 99.59 275 | 94.16 251 | 99.20 229 | 99.30 183 |
|
test_prior2 | | | | | | | | 95.74 303 | | 96.48 225 | 96.11 306 | 97.63 272 | 95.92 194 | | 94.16 251 | 99.20 229 | |
|
VDDNet | | | 98.21 151 | 97.95 161 | 99.01 110 | 99.58 57 | 97.74 144 | 99.01 55 | 97.29 294 | 99.67 8 | 98.97 128 | 99.50 46 | 90.45 277 | 99.80 154 | 97.88 102 | 99.20 229 | 99.48 117 |
|
OpenMVS | | 96.65 7 | 97.09 226 | 96.68 231 | 98.32 203 | 98.32 290 | 97.16 173 | 98.86 71 | 99.37 107 | 89.48 333 | 96.29 303 | 99.15 102 | 96.56 164 | 99.90 47 | 92.90 283 | 99.20 229 | 97.89 292 |
|
HSP-MVS | | | 98.34 136 | 97.94 163 | 99.54 25 | 99.57 62 | 99.25 19 | 98.57 86 | 98.84 236 | 97.55 163 | 99.31 79 | 97.71 267 | 94.61 233 | 99.88 63 | 96.14 199 | 99.19 233 | 99.48 117 |
|
DI_MVS_plusplus_test | | | 97.57 195 | 97.40 195 | 98.07 221 | 99.06 185 | 95.71 230 | 96.58 261 | 96.96 300 | 96.71 217 | 98.69 162 | 98.13 242 | 93.81 249 | 99.68 240 | 97.45 123 | 99.19 233 | 98.80 254 |
|
CNLPA | | | 97.17 222 | 96.71 229 | 98.55 174 | 98.56 273 | 98.05 112 | 96.33 272 | 98.93 221 | 96.91 208 | 97.06 273 | 97.39 287 | 94.38 238 | 99.45 310 | 91.66 300 | 99.18 235 | 98.14 286 |
|
train_agg | | | 97.10 225 | 96.45 243 | 99.07 97 | 98.71 249 | 98.08 108 | 95.96 290 | 99.03 205 | 91.64 314 | 95.85 312 | 97.53 276 | 96.47 169 | 99.76 199 | 93.67 267 | 99.16 236 | 99.36 164 |
|
agg_prior3 | | | 96.95 235 | 96.27 248 | 99.00 112 | 98.68 257 | 97.91 126 | 95.96 290 | 99.01 212 | 90.74 326 | 95.60 315 | 97.45 284 | 96.14 180 | 99.74 214 | 93.67 267 | 99.16 236 | 99.36 164 |
|
agg_prior2 | | | | | | | | | | | | | | | 92.50 293 | 99.16 236 | 99.37 158 |
|
test9_res | | | | | | | | | | | | | | | 93.28 278 | 99.15 239 | 99.38 157 |
|
MS-PatchMatch | | | 97.68 186 | 97.75 174 | 97.45 252 | 98.23 296 | 93.78 281 | 97.29 215 | 98.84 236 | 96.10 241 | 98.64 166 | 98.65 192 | 96.04 184 | 99.36 319 | 96.84 152 | 99.14 240 | 99.20 203 |
|
agg_prior1 | | | 97.06 228 | 96.40 244 | 99.03 106 | 98.68 257 | 97.99 115 | 95.76 301 | 99.01 212 | 91.73 313 | 95.59 316 | 97.50 279 | 96.49 168 | 99.77 194 | 93.71 266 | 99.14 240 | 99.34 170 |
|
AdaColmap | | | 97.14 224 | 96.71 229 | 98.46 188 | 98.34 289 | 97.80 139 | 96.95 236 | 98.93 221 | 95.58 257 | 96.92 278 | 97.66 270 | 95.87 197 | 99.53 291 | 90.97 315 | 99.14 240 | 98.04 289 |
|
VNet | | | 98.42 129 | 98.30 131 | 98.79 136 | 98.79 242 | 97.29 163 | 98.23 120 | 98.66 257 | 99.31 41 | 98.85 146 | 98.80 170 | 94.80 228 | 99.78 184 | 98.13 90 | 99.13 243 | 99.31 180 |
|
test12 | | | | | 98.93 119 | 98.58 271 | 97.83 133 | | 98.66 257 | | 96.53 295 | | 95.51 207 | 99.69 235 | | 99.13 243 | 99.27 188 |
|
DP-MVS Recon | | | 97.33 210 | 96.92 216 | 98.57 169 | 99.09 178 | 97.99 115 | 96.79 246 | 99.35 117 | 93.18 297 | 97.71 235 | 98.07 252 | 95.00 219 | 99.31 325 | 93.97 258 | 99.13 243 | 98.42 278 |
|
pmmvs3 | | | 95.03 276 | 94.40 285 | 96.93 268 | 97.70 316 | 92.53 295 | 95.08 321 | 97.71 287 | 88.57 337 | 97.71 235 | 98.08 251 | 79.39 335 | 99.82 129 | 96.19 194 | 99.11 246 | 98.43 277 |
|
test222 | | | | | | 98.92 215 | 96.93 182 | 95.54 309 | 98.78 246 | 85.72 345 | 96.86 285 | 98.11 247 | 94.43 236 | | | 99.10 247 | 99.23 197 |
|
xiu_mvs_v1_base_debu | | | 97.86 175 | 98.17 139 | 96.92 269 | 98.98 203 | 93.91 275 | 96.45 266 | 99.17 180 | 97.85 144 | 98.41 189 | 97.14 296 | 98.47 39 | 99.92 34 | 98.02 95 | 99.05 248 | 96.92 322 |
|
xiu_mvs_v1_base | | | 97.86 175 | 98.17 139 | 96.92 269 | 98.98 203 | 93.91 275 | 96.45 266 | 99.17 180 | 97.85 144 | 98.41 189 | 97.14 296 | 98.47 39 | 99.92 34 | 98.02 95 | 99.05 248 | 96.92 322 |
|
xiu_mvs_v1_base_debi | | | 97.86 175 | 98.17 139 | 96.92 269 | 98.98 203 | 93.91 275 | 96.45 266 | 99.17 180 | 97.85 144 | 98.41 189 | 97.14 296 | 98.47 39 | 99.92 34 | 98.02 95 | 99.05 248 | 96.92 322 |
|
MG-MVS | | | 96.77 242 | 96.61 236 | 97.26 259 | 98.31 291 | 93.06 290 | 95.93 294 | 98.12 277 | 96.45 227 | 97.92 209 | 98.73 179 | 93.77 252 | 99.39 316 | 91.19 314 | 99.04 251 | 99.33 175 |
|
1121 | | | 96.73 243 | 96.00 251 | 98.91 122 | 98.95 208 | 97.76 141 | 98.07 136 | 98.73 253 | 87.65 340 | 96.54 294 | 98.13 242 | 94.52 235 | 99.73 219 | 92.38 295 | 99.02 252 | 99.24 196 |
|
API-MVS | | | 97.04 231 | 96.91 218 | 97.42 254 | 97.88 311 | 98.23 99 | 98.18 124 | 98.50 264 | 97.57 160 | 97.39 262 | 96.75 301 | 96.77 151 | 99.15 336 | 90.16 322 | 99.02 252 | 94.88 348 |
|
旧先验1 | | | | | | 98.82 237 | 97.45 159 | | 98.76 247 | | | 98.34 229 | 95.50 208 | | | 99.01 254 | 99.23 197 |
|
新几何1 | | | | | 98.91 122 | 98.94 209 | 97.76 141 | | 98.76 247 | 87.58 341 | 96.75 289 | 98.10 248 | 94.80 228 | 99.78 184 | 92.73 290 | 99.00 255 | 99.20 203 |
|
原ACMM1 | | | | | 98.35 201 | 98.90 219 | 96.25 210 | | 98.83 241 | 92.48 305 | 96.07 309 | 98.10 248 | 95.39 211 | 99.71 229 | 92.61 292 | 98.99 256 | 99.08 219 |
|
testgi | | | 98.32 138 | 98.39 119 | 98.13 215 | 99.57 62 | 95.54 233 | 97.78 170 | 99.49 71 | 97.37 180 | 99.19 97 | 97.65 271 | 98.96 19 | 99.49 302 | 96.50 180 | 98.99 256 | 99.34 170 |
|
MVP-Stereo | | | 98.08 160 | 97.92 165 | 98.57 169 | 98.96 206 | 96.79 185 | 97.90 161 | 99.18 174 | 96.41 228 | 98.46 184 | 98.95 143 | 95.93 193 | 99.60 271 | 96.51 179 | 98.98 258 | 99.31 180 |
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
alignmvs | | | 97.35 208 | 96.88 219 | 98.78 139 | 98.54 276 | 98.09 105 | 97.71 178 | 97.69 288 | 99.20 50 | 97.59 243 | 95.90 318 | 88.12 288 | 99.55 288 | 98.18 89 | 98.96 259 | 98.70 264 |
|
testdata | | | | | 98.09 217 | 98.93 211 | 95.40 239 | | 98.80 244 | 90.08 331 | 97.45 255 | 98.37 226 | 95.26 213 | 99.70 231 | 93.58 271 | 98.95 260 | 99.17 213 |
|
Effi-MVS+-dtu | | | 98.26 146 | 97.90 167 | 99.35 62 | 98.02 304 | 99.49 3 | 98.02 149 | 99.16 183 | 98.29 118 | 97.64 239 | 97.99 255 | 96.44 171 | 99.95 13 | 96.66 166 | 98.93 261 | 98.60 269 |
|
MVS_Test | | | 98.18 154 | 98.36 123 | 97.67 238 | 98.48 279 | 94.73 250 | 98.18 124 | 99.02 209 | 97.69 150 | 98.04 206 | 99.11 107 | 97.22 122 | 99.56 285 | 98.57 70 | 98.90 262 | 98.71 262 |
|
Fast-Effi-MVS+ | | | 97.67 187 | 97.38 198 | 98.57 169 | 98.71 249 | 97.43 160 | 97.23 219 | 99.45 85 | 94.82 273 | 96.13 305 | 96.51 304 | 98.52 38 | 99.91 43 | 96.19 194 | 98.83 263 | 98.37 282 |
|
NCCC | | | 97.86 175 | 97.47 193 | 99.05 103 | 98.61 268 | 98.07 110 | 96.98 235 | 98.90 227 | 97.63 153 | 97.04 274 | 97.93 259 | 95.99 190 | 99.66 254 | 95.31 227 | 98.82 264 | 99.43 140 |
|
PatchMatch-RL | | | 97.24 218 | 96.78 224 | 98.61 162 | 99.03 195 | 97.83 133 | 96.36 271 | 99.06 196 | 93.49 296 | 97.36 265 | 97.78 264 | 95.75 199 | 99.49 302 | 93.44 275 | 98.77 265 | 98.52 272 |
|
YYNet1 | | | 97.60 191 | 97.67 177 | 97.39 256 | 99.04 192 | 93.04 292 | 95.27 316 | 98.38 269 | 97.25 191 | 98.92 137 | 98.95 143 | 95.48 209 | 99.73 219 | 96.99 143 | 98.74 266 | 99.41 145 |
|
testus | | | 95.52 268 | 95.32 267 | 96.13 299 | 97.91 309 | 89.49 325 | 93.62 340 | 99.61 30 | 92.41 306 | 97.38 264 | 95.42 330 | 94.72 232 | 99.63 262 | 88.06 329 | 98.72 267 | 99.26 191 |
|
MDA-MVSNet-bldmvs | | | 97.94 169 | 97.91 166 | 98.06 222 | 99.44 109 | 94.96 247 | 96.63 258 | 99.15 186 | 98.35 109 | 98.83 149 | 99.11 107 | 94.31 239 | 99.85 88 | 96.60 169 | 98.72 267 | 99.37 158 |
|
MDA-MVSNet_test_wron | | | 97.60 191 | 97.66 180 | 97.41 255 | 99.04 192 | 93.09 289 | 95.27 316 | 98.42 267 | 97.26 190 | 98.88 143 | 98.95 143 | 95.43 210 | 99.73 219 | 97.02 142 | 98.72 267 | 99.41 145 |
|
Fast-Effi-MVS+-dtu | | | 98.27 144 | 98.09 151 | 98.81 134 | 98.43 284 | 98.11 104 | 97.61 192 | 99.50 65 | 98.64 95 | 97.39 262 | 97.52 278 | 98.12 60 | 99.95 13 | 96.90 148 | 98.71 270 | 98.38 280 |
|
canonicalmvs | | | 98.34 136 | 98.26 133 | 98.58 167 | 98.46 281 | 97.82 136 | 98.96 63 | 99.46 82 | 99.19 54 | 97.46 254 | 95.46 328 | 98.59 32 | 99.46 308 | 98.08 92 | 98.71 270 | 98.46 274 |
|
xiu_mvs_v2_base | | | 97.16 223 | 97.49 189 | 96.17 295 | 98.54 276 | 92.46 296 | 95.45 313 | 98.84 236 | 97.25 191 | 97.48 253 | 96.49 305 | 98.31 47 | 99.90 47 | 96.34 189 | 98.68 272 | 96.15 338 |
|
PS-MVSNAJ | | | 97.08 227 | 97.39 197 | 96.16 297 | 98.56 273 | 92.46 296 | 95.24 318 | 98.85 235 | 97.25 191 | 97.49 252 | 95.99 313 | 98.07 61 | 99.90 47 | 96.37 187 | 98.67 273 | 96.12 339 |
|
PatchmatchNet | | | 95.58 266 | 95.67 259 | 95.30 314 | 97.34 330 | 87.32 332 | 97.65 185 | 96.65 310 | 95.30 262 | 97.07 272 | 98.69 184 | 84.77 304 | 99.75 205 | 94.97 232 | 98.64 274 | 98.83 248 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
MVE | | 83.40 22 | 92.50 319 | 91.92 321 | 94.25 325 | 98.83 234 | 91.64 305 | 92.71 344 | 83.52 357 | 95.92 246 | 86.46 355 | 95.46 328 | 95.20 214 | 95.40 354 | 80.51 350 | 98.64 274 | 95.73 342 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
OpenMVS_ROB | | 95.38 14 | 95.84 263 | 95.18 272 | 97.81 231 | 98.41 285 | 97.15 174 | 97.37 210 | 98.62 260 | 83.86 347 | 98.65 164 | 98.37 226 | 94.29 240 | 99.68 240 | 88.41 327 | 98.62 276 | 96.60 332 |
|
cascas | | | 94.79 287 | 94.33 288 | 96.15 298 | 96.02 350 | 92.36 299 | 92.34 347 | 99.26 152 | 85.34 346 | 95.08 330 | 94.96 339 | 92.96 260 | 98.53 348 | 94.41 249 | 98.59 277 | 97.56 314 |
|
BH-RMVSNet | | | 96.83 238 | 96.58 238 | 97.58 246 | 98.47 280 | 94.05 270 | 96.67 255 | 97.36 292 | 96.70 219 | 97.87 214 | 97.98 256 | 95.14 216 | 99.44 311 | 90.47 321 | 98.58 278 | 99.25 193 |
|
GA-MVS | | | 95.86 262 | 95.32 267 | 97.49 250 | 98.60 270 | 94.15 269 | 93.83 339 | 97.93 281 | 95.49 259 | 96.68 290 | 97.42 286 | 83.21 315 | 99.30 327 | 96.22 192 | 98.55 279 | 99.01 228 |
|
view600 | | | 94.87 279 | 94.41 281 | 96.26 289 | 99.22 144 | 91.37 310 | 98.49 97 | 94.45 325 | 98.75 89 | 97.85 217 | 95.98 314 | 80.38 324 | 99.75 205 | 86.06 335 | 98.49 280 | 97.66 305 |
|
view800 | | | 94.87 279 | 94.41 281 | 96.26 289 | 99.22 144 | 91.37 310 | 98.49 97 | 94.45 325 | 98.75 89 | 97.85 217 | 95.98 314 | 80.38 324 | 99.75 205 | 86.06 335 | 98.49 280 | 97.66 305 |
|
conf0.05thres1000 | | | 94.87 279 | 94.41 281 | 96.26 289 | 99.22 144 | 91.37 310 | 98.49 97 | 94.45 325 | 98.75 89 | 97.85 217 | 95.98 314 | 80.38 324 | 99.75 205 | 86.06 335 | 98.49 280 | 97.66 305 |
|
tfpn | | | 94.87 279 | 94.41 281 | 96.26 289 | 99.22 144 | 91.37 310 | 98.49 97 | 94.45 325 | 98.75 89 | 97.85 217 | 95.98 314 | 80.38 324 | 99.75 205 | 86.06 335 | 98.49 280 | 97.66 305 |
|
F-COLMAP | | | 97.30 212 | 96.68 231 | 99.14 88 | 99.19 160 | 98.39 89 | 97.27 216 | 99.30 138 | 92.93 299 | 96.62 292 | 98.00 254 | 95.73 200 | 99.68 240 | 92.62 291 | 98.46 284 | 99.35 169 |
|
XVG-OURS-SEG-HR | | | 98.49 122 | 98.28 132 | 99.14 88 | 99.49 92 | 98.83 57 | 96.54 262 | 99.48 74 | 97.32 185 | 99.11 105 | 98.61 203 | 99.33 8 | 99.30 327 | 96.23 191 | 98.38 285 | 99.28 187 |
|
tfpn1000 | | | 94.81 286 | 94.25 289 | 96.47 286 | 99.01 199 | 93.47 287 | 98.56 87 | 92.30 349 | 96.17 236 | 97.90 212 | 96.29 310 | 76.70 347 | 99.77 194 | 93.02 280 | 98.29 286 | 96.16 336 |
|
diffmvs | | | 97.49 199 | 97.36 199 | 97.91 228 | 98.38 287 | 95.70 231 | 97.95 156 | 99.31 131 | 94.87 271 | 96.14 304 | 98.78 173 | 94.84 224 | 99.43 312 | 97.69 114 | 98.26 287 | 98.59 270 |
|
thres600view7 | | | 94.45 294 | 93.83 299 | 96.29 287 | 99.06 185 | 91.53 306 | 97.99 152 | 94.24 332 | 98.34 110 | 97.44 256 | 95.01 334 | 79.84 329 | 99.67 246 | 84.33 341 | 98.23 288 | 97.66 305 |
|
MAR-MVS | | | 96.47 253 | 95.70 257 | 98.79 136 | 97.92 308 | 99.12 40 | 98.28 117 | 98.60 261 | 92.16 311 | 95.54 323 | 96.17 311 | 94.77 231 | 99.52 295 | 89.62 324 | 98.23 288 | 97.72 304 |
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 |
tfpn111 | | | 94.33 296 | 93.78 300 | 95.96 301 | 99.06 185 | 91.35 314 | 98.03 142 | 94.24 332 | 98.33 111 | 97.40 259 | 94.98 336 | 79.84 329 | 99.68 240 | 83.94 342 | 98.22 290 | 96.86 325 |
|
Effi-MVS+ | | | 98.02 162 | 97.82 172 | 98.62 159 | 98.53 278 | 97.19 170 | 97.33 212 | 99.68 16 | 97.30 187 | 96.68 290 | 97.46 283 | 98.56 36 | 99.80 154 | 96.63 168 | 98.20 291 | 98.86 246 |
|
test-LLR | | | 93.90 308 | 93.85 298 | 94.04 326 | 96.53 342 | 84.62 345 | 94.05 335 | 92.39 347 | 96.17 236 | 94.12 338 | 95.07 332 | 82.30 319 | 99.67 246 | 95.87 210 | 98.18 292 | 97.82 296 |
|
test-mter | | | 92.33 321 | 91.76 323 | 94.04 326 | 96.53 342 | 84.62 345 | 94.05 335 | 92.39 347 | 94.00 290 | 94.12 338 | 95.07 332 | 65.63 360 | 99.67 246 | 95.87 210 | 98.18 292 | 97.82 296 |
|
mvs_anonymous | | | 97.83 181 | 98.16 142 | 96.87 272 | 98.18 299 | 91.89 302 | 97.31 214 | 98.90 227 | 97.37 180 | 98.83 149 | 99.46 52 | 96.28 178 | 99.79 174 | 98.90 53 | 98.16 294 | 98.95 235 |
|
WTY-MVS | | | 96.67 244 | 96.27 248 | 97.87 229 | 98.81 239 | 94.61 255 | 96.77 248 | 97.92 282 | 94.94 269 | 97.12 269 | 97.74 266 | 91.11 274 | 99.82 129 | 93.89 261 | 98.15 295 | 99.18 209 |
|
thres200 | | | 93.72 310 | 93.14 311 | 95.46 312 | 98.66 265 | 91.29 318 | 96.61 260 | 94.63 324 | 97.39 179 | 96.83 286 | 93.71 348 | 79.88 328 | 99.56 285 | 82.40 348 | 98.13 296 | 95.54 343 |
|
conf0.01 | | | 94.82 284 | 94.07 290 | 97.06 264 | 99.21 150 | 94.53 257 | 98.47 103 | 92.69 340 | 95.61 251 | 97.81 225 | 95.54 321 | 77.71 341 | 99.80 154 | 91.49 306 | 98.11 297 | 96.86 325 |
|
conf0.002 | | | 94.82 284 | 94.07 290 | 97.06 264 | 99.21 150 | 94.53 257 | 98.47 103 | 92.69 340 | 95.61 251 | 97.81 225 | 95.54 321 | 77.71 341 | 99.80 154 | 91.49 306 | 98.11 297 | 96.86 325 |
|
thresconf0.02 | | | 94.70 288 | 94.07 290 | 96.58 279 | 99.21 150 | 94.53 257 | 98.47 103 | 92.69 340 | 95.61 251 | 97.81 225 | 95.54 321 | 77.71 341 | 99.80 154 | 91.49 306 | 98.11 297 | 95.42 344 |
|
tfpn_n400 | | | 94.70 288 | 94.07 290 | 96.58 279 | 99.21 150 | 94.53 257 | 98.47 103 | 92.69 340 | 95.61 251 | 97.81 225 | 95.54 321 | 77.71 341 | 99.80 154 | 91.49 306 | 98.11 297 | 95.42 344 |
|
tfpnconf | | | 94.70 288 | 94.07 290 | 96.58 279 | 99.21 150 | 94.53 257 | 98.47 103 | 92.69 340 | 95.61 251 | 97.81 225 | 95.54 321 | 77.71 341 | 99.80 154 | 91.49 306 | 98.11 297 | 95.42 344 |
|
tfpnview11 | | | 94.70 288 | 94.07 290 | 96.58 279 | 99.21 150 | 94.53 257 | 98.47 103 | 92.69 340 | 95.61 251 | 97.81 225 | 95.54 321 | 77.71 341 | 99.80 154 | 91.49 306 | 98.11 297 | 95.42 344 |
|
TESTMET0.1,1 | | | 92.19 323 | 91.77 322 | 93.46 333 | 96.48 344 | 82.80 352 | 94.05 335 | 91.52 352 | 94.45 280 | 94.00 341 | 94.88 340 | 66.65 357 | 99.56 285 | 95.78 215 | 98.11 297 | 98.02 290 |
|
PMMVS | | | 96.51 250 | 95.98 252 | 98.09 217 | 97.53 322 | 95.84 225 | 94.92 324 | 98.84 236 | 91.58 317 | 96.05 310 | 95.58 320 | 95.68 201 | 99.66 254 | 95.59 223 | 98.09 304 | 98.76 259 |
|
conf200view11 | | | 94.24 299 | 93.67 304 | 95.94 302 | 99.06 185 | 91.35 314 | 98.03 142 | 94.24 332 | 98.33 111 | 97.40 259 | 94.98 336 | 79.84 329 | 99.62 264 | 83.05 344 | 98.08 305 | 96.86 325 |
|
thres100view900 | | | 94.19 300 | 93.67 304 | 95.75 307 | 99.06 185 | 91.35 314 | 98.03 142 | 94.24 332 | 98.33 111 | 97.40 259 | 94.98 336 | 79.84 329 | 99.62 264 | 83.05 344 | 98.08 305 | 96.29 333 |
|
tfpn200view9 | | | 94.03 305 | 93.44 308 | 95.78 306 | 98.93 211 | 91.44 308 | 97.60 193 | 94.29 330 | 97.94 128 | 97.10 270 | 94.31 345 | 79.67 333 | 99.62 264 | 83.05 344 | 98.08 305 | 96.29 333 |
|
thres400 | | | 94.14 302 | 93.44 308 | 96.24 293 | 98.93 211 | 91.44 308 | 97.60 193 | 94.29 330 | 97.94 128 | 97.10 270 | 94.31 345 | 79.67 333 | 99.62 264 | 83.05 344 | 98.08 305 | 97.66 305 |
|
PLC | | 94.65 16 | 96.51 250 | 95.73 256 | 98.85 130 | 98.75 244 | 97.91 126 | 96.42 269 | 99.06 196 | 90.94 325 | 95.59 316 | 97.38 288 | 94.41 237 | 99.59 275 | 90.93 316 | 98.04 309 | 99.05 223 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
MDTV_nov1_ep13 | | | | 95.22 270 | | 97.06 335 | 83.20 349 | 97.74 176 | 96.16 316 | 94.37 282 | 96.99 276 | 98.83 165 | 83.95 312 | 99.53 291 | 93.90 260 | 97.95 310 | |
|
mvs-test1 | | | 97.83 181 | 97.48 192 | 98.89 125 | 98.02 304 | 99.20 24 | 97.20 223 | 99.16 183 | 98.29 118 | 96.46 301 | 97.17 293 | 96.44 171 | 99.92 34 | 96.66 166 | 97.90 311 | 97.54 315 |
|
tfpn_ndepth | | | 94.12 303 | 93.51 307 | 95.94 302 | 98.86 226 | 93.60 286 | 98.16 127 | 91.90 351 | 94.66 275 | 97.41 258 | 95.24 331 | 76.24 348 | 99.73 219 | 91.21 312 | 97.88 312 | 94.50 349 |
|
PAPM_NR | | | 96.82 240 | 96.32 247 | 98.30 206 | 99.07 182 | 96.69 192 | 97.48 205 | 98.76 247 | 95.81 248 | 96.61 293 | 96.47 307 | 94.12 245 | 99.17 334 | 90.82 320 | 97.78 313 | 99.06 222 |
|
EMVS | | | 93.83 309 | 94.02 296 | 93.23 336 | 96.83 340 | 84.96 343 | 89.77 351 | 96.32 315 | 97.92 130 | 97.43 257 | 96.36 309 | 86.17 293 | 98.93 343 | 87.68 330 | 97.73 314 | 95.81 341 |
|
E-PMN | | | 94.17 301 | 94.37 286 | 93.58 332 | 96.86 338 | 85.71 339 | 90.11 350 | 97.07 297 | 98.17 124 | 97.82 224 | 97.19 292 | 84.62 306 | 98.94 342 | 89.77 323 | 97.68 315 | 96.09 340 |
|
PatchT | | | 96.65 245 | 96.35 245 | 97.54 248 | 97.40 328 | 95.32 240 | 97.98 153 | 96.64 311 | 99.33 40 | 96.89 283 | 99.42 59 | 84.32 309 | 99.81 142 | 97.69 114 | 97.49 316 | 97.48 316 |
|
FPMVS | | | 93.44 313 | 92.23 318 | 97.08 262 | 99.25 137 | 97.86 131 | 95.61 307 | 97.16 296 | 92.90 300 | 93.76 343 | 98.65 192 | 75.94 350 | 95.66 353 | 79.30 352 | 97.49 316 | 97.73 303 |
|
BH-untuned | | | 96.83 238 | 96.75 226 | 97.08 262 | 98.74 245 | 93.33 288 | 96.71 252 | 98.26 272 | 96.72 215 | 98.44 186 | 97.37 289 | 95.20 214 | 99.47 306 | 91.89 298 | 97.43 318 | 98.44 276 |
|
UnsupCasMVSNet_bld | | | 97.30 212 | 96.92 216 | 98.45 190 | 99.28 133 | 96.78 189 | 96.20 280 | 99.27 147 | 95.42 261 | 98.28 195 | 98.30 233 | 93.16 256 | 99.71 229 | 94.99 231 | 97.37 319 | 98.87 245 |
|
PAPR | | | 95.29 272 | 94.47 280 | 97.75 235 | 97.50 326 | 95.14 244 | 94.89 325 | 98.71 255 | 91.39 321 | 95.35 327 | 95.48 327 | 94.57 234 | 99.14 337 | 84.95 339 | 97.37 319 | 98.97 234 |
|
CR-MVSNet | | | 96.28 256 | 95.95 253 | 97.28 257 | 97.71 314 | 94.22 265 | 98.11 131 | 98.92 224 | 92.31 308 | 96.91 280 | 99.37 65 | 85.44 302 | 99.81 142 | 97.39 127 | 97.36 321 | 97.81 298 |
|
RPMNet | | | 96.82 240 | 96.66 234 | 97.28 257 | 97.71 314 | 94.22 265 | 98.11 131 | 96.90 305 | 99.37 36 | 96.91 280 | 99.34 70 | 86.72 290 | 99.81 142 | 97.53 119 | 97.36 321 | 97.81 298 |
|
HY-MVS | | 95.94 13 | 95.90 261 | 95.35 266 | 97.55 247 | 97.95 306 | 94.79 249 | 98.81 74 | 96.94 303 | 92.28 309 | 95.17 328 | 98.57 207 | 89.90 279 | 99.75 205 | 91.20 313 | 97.33 323 | 98.10 287 |
|
1314 | | | 95.74 264 | 95.60 261 | 96.17 295 | 97.53 322 | 92.75 293 | 98.07 136 | 98.31 271 | 91.22 322 | 94.25 336 | 96.68 302 | 95.53 205 | 99.03 338 | 91.64 302 | 97.18 324 | 96.74 330 |
|
gg-mvs-nofinetune | | | 92.37 320 | 91.20 324 | 95.85 305 | 95.80 351 | 92.38 298 | 99.31 20 | 81.84 358 | 99.75 4 | 91.83 347 | 99.74 8 | 68.29 354 | 99.02 339 | 87.15 331 | 97.12 325 | 96.16 336 |
|
test2356 | | | 91.64 326 | 90.19 329 | 96.00 300 | 94.30 354 | 89.58 324 | 90.84 348 | 96.68 309 | 91.76 312 | 95.48 325 | 93.69 349 | 67.05 356 | 99.52 295 | 84.83 340 | 97.08 326 | 98.91 241 |
|
ADS-MVSNet2 | | | 95.43 271 | 94.98 276 | 96.76 277 | 98.14 300 | 91.74 303 | 97.92 158 | 97.76 284 | 90.23 327 | 96.51 297 | 98.91 148 | 85.61 299 | 99.85 88 | 92.88 284 | 96.90 327 | 98.69 265 |
|
ADS-MVSNet | | | 95.24 273 | 94.93 277 | 96.18 294 | 98.14 300 | 90.10 323 | 97.92 158 | 97.32 293 | 90.23 327 | 96.51 297 | 98.91 148 | 85.61 299 | 99.74 214 | 92.88 284 | 96.90 327 | 98.69 265 |
|
MVS | | | 93.19 315 | 92.09 319 | 96.50 285 | 96.91 337 | 94.03 271 | 98.07 136 | 98.06 279 | 68.01 352 | 94.56 334 | 96.48 306 | 95.96 192 | 99.30 327 | 83.84 343 | 96.89 329 | 96.17 335 |
|
tpm2 | | | 93.09 316 | 92.58 315 | 94.62 320 | 97.56 320 | 86.53 335 | 97.66 183 | 95.79 319 | 86.15 344 | 94.07 340 | 98.23 239 | 75.95 349 | 99.53 291 | 90.91 317 | 96.86 330 | 97.81 298 |
|
tpmp4_e23 | | | 92.91 317 | 92.45 316 | 94.29 324 | 97.41 327 | 85.62 340 | 97.95 156 | 96.77 308 | 87.55 342 | 91.33 349 | 98.57 207 | 74.21 351 | 99.59 275 | 91.62 303 | 96.64 331 | 97.65 312 |
|
CostFormer | | | 93.97 307 | 93.78 300 | 94.51 322 | 97.53 322 | 85.83 338 | 97.98 153 | 95.96 317 | 89.29 335 | 94.99 331 | 98.63 199 | 78.63 337 | 99.62 264 | 94.54 241 | 96.50 332 | 98.09 288 |
|
EPMVS | | | 93.72 310 | 93.27 310 | 95.09 316 | 96.04 349 | 87.76 330 | 98.13 128 | 85.01 356 | 94.69 274 | 96.92 278 | 98.64 195 | 78.47 339 | 99.31 325 | 95.04 229 | 96.46 333 | 98.20 284 |
|
TR-MVS | | | 95.55 267 | 95.12 273 | 96.86 275 | 97.54 321 | 93.94 273 | 96.49 265 | 96.53 313 | 94.36 283 | 97.03 275 | 96.61 303 | 94.26 241 | 99.16 335 | 86.91 332 | 96.31 334 | 97.47 317 |
|
tpmvs | | | 95.02 277 | 95.25 269 | 94.33 323 | 96.39 346 | 85.87 336 | 98.08 134 | 96.83 307 | 95.46 260 | 95.51 324 | 98.69 184 | 85.91 296 | 99.53 291 | 94.16 251 | 96.23 335 | 97.58 313 |
|
tpmrst | | | 95.07 275 | 95.46 263 | 93.91 329 | 97.11 334 | 84.36 347 | 97.62 190 | 96.96 300 | 94.98 267 | 96.35 302 | 98.80 170 | 85.46 301 | 99.59 275 | 95.60 222 | 96.23 335 | 97.79 301 |
|
BH-w/o | | | 95.13 274 | 94.89 278 | 95.86 304 | 98.20 298 | 91.31 317 | 95.65 306 | 97.37 291 | 93.64 292 | 96.52 296 | 95.70 319 | 93.04 259 | 99.02 339 | 88.10 328 | 95.82 337 | 97.24 320 |
|
LP | | | 96.60 248 | 96.57 239 | 96.68 278 | 97.64 318 | 91.70 304 | 98.11 131 | 97.74 285 | 97.29 189 | 97.91 211 | 99.24 82 | 88.35 286 | 99.85 88 | 97.11 140 | 95.76 338 | 98.49 273 |
|
UnsupCasMVSNet_eth | | | 97.89 171 | 97.60 185 | 98.75 145 | 99.31 130 | 97.17 172 | 97.62 190 | 99.35 117 | 98.72 94 | 98.76 158 | 98.68 186 | 92.57 266 | 99.74 214 | 97.76 110 | 95.60 339 | 99.34 170 |
|
PAPM | | | 91.88 324 | 90.34 326 | 96.51 284 | 98.06 303 | 92.56 294 | 92.44 346 | 97.17 295 | 86.35 343 | 90.38 351 | 96.01 312 | 86.61 291 | 99.21 332 | 70.65 354 | 95.43 340 | 97.75 302 |
|
tpm cat1 | | | 93.29 314 | 93.13 312 | 93.75 330 | 97.39 329 | 84.74 344 | 97.39 209 | 97.65 289 | 83.39 349 | 94.16 337 | 98.41 223 | 82.86 318 | 99.39 316 | 91.56 305 | 95.35 341 | 97.14 321 |
|
tpm | | | 94.67 292 | 94.34 287 | 95.66 308 | 97.68 317 | 88.42 327 | 97.88 162 | 94.90 322 | 94.46 278 | 96.03 311 | 98.56 210 | 78.66 336 | 99.79 174 | 95.88 207 | 95.01 342 | 98.78 256 |
|
JIA-IIPM | | | 95.52 268 | 95.03 275 | 97.00 266 | 96.85 339 | 94.03 271 | 96.93 238 | 95.82 318 | 99.20 50 | 94.63 333 | 99.71 14 | 83.09 316 | 99.60 271 | 94.42 246 | 94.64 343 | 97.36 318 |
|
IB-MVS | | 91.63 19 | 92.24 322 | 90.90 325 | 96.27 288 | 97.22 333 | 91.24 319 | 94.36 333 | 93.33 339 | 92.37 307 | 92.24 346 | 94.58 344 | 66.20 358 | 99.89 56 | 93.16 279 | 94.63 344 | 97.66 305 |
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-BLEND | | | | | 94.76 319 | 94.54 353 | 92.13 301 | 99.31 20 | 80.47 359 | | 88.73 353 | 91.01 353 | 67.59 355 | 98.16 351 | 82.30 349 | 94.53 345 | 93.98 350 |
|
PatchFormer-LS_test | | | 94.08 304 | 93.91 297 | 94.59 321 | 96.93 336 | 86.86 334 | 97.55 200 | 96.57 312 | 94.27 285 | 94.38 335 | 93.64 350 | 80.96 321 | 99.59 275 | 96.44 185 | 94.48 346 | 97.31 319 |
|
DWT-MVSNet_test | | | 92.75 318 | 92.05 320 | 94.85 317 | 96.48 344 | 87.21 333 | 97.83 168 | 94.99 321 | 92.22 310 | 92.72 345 | 94.11 347 | 70.75 352 | 99.46 308 | 95.01 230 | 94.33 347 | 97.87 294 |
|
test0.0.03 1 | | | 94.51 293 | 93.69 303 | 96.99 267 | 96.05 348 | 93.61 285 | 94.97 323 | 93.49 337 | 96.17 236 | 97.57 246 | 94.88 340 | 82.30 319 | 99.01 341 | 93.60 270 | 94.17 348 | 98.37 282 |
|
DeepMVS_CX | | | | | 93.44 334 | 98.24 294 | 94.21 267 | | 94.34 329 | 64.28 353 | 91.34 348 | 94.87 342 | 89.45 283 | 92.77 356 | 77.54 353 | 93.14 349 | 93.35 351 |
|
tmp_tt | | | 78.77 330 | 78.73 331 | 78.90 342 | 58.45 358 | 74.76 358 | 94.20 334 | 78.26 360 | 39.16 354 | 86.71 354 | 92.82 352 | 80.50 323 | 75.19 357 | 86.16 334 | 92.29 350 | 86.74 352 |
|
testpf | | | 89.08 328 | 90.27 328 | 85.50 341 | 94.03 355 | 82.85 351 | 96.87 244 | 91.09 353 | 91.61 316 | 90.96 350 | 94.86 343 | 66.15 359 | 95.83 352 | 94.58 240 | 92.27 351 | 77.82 353 |
|
dp | | | 93.47 312 | 93.59 306 | 93.13 337 | 96.64 341 | 81.62 354 | 97.66 183 | 96.42 314 | 92.80 302 | 96.11 306 | 98.64 195 | 78.55 338 | 99.59 275 | 93.31 277 | 92.18 352 | 98.16 285 |
|
PNet_i23d | | | 91.80 325 | 92.35 317 | 90.14 340 | 98.65 266 | 73.10 359 | 89.22 352 | 99.02 209 | 95.23 265 | 97.87 214 | 97.82 263 | 78.45 340 | 98.89 345 | 88.73 326 | 86.14 353 | 98.42 278 |
|
PVSNet_0 | | 89.98 21 | 91.15 327 | 90.30 327 | 93.70 331 | 97.72 313 | 84.34 348 | 90.24 349 | 97.42 290 | 90.20 330 | 93.79 342 | 93.09 351 | 90.90 275 | 98.89 345 | 86.57 333 | 72.76 354 | 97.87 294 |
|
.test1245 | | | 79.71 329 | 84.30 330 | 65.96 343 | 99.33 128 | 85.20 341 | 95.97 286 | 99.39 100 | 97.88 140 | 98.64 166 | 98.56 210 | 57.79 361 | 99.80 154 | 96.02 201 | 15.07 355 | 12.86 356 |
|
testmvs | | | 17.12 333 | 20.53 334 | 6.87 346 | 12.05 359 | 4.20 361 | 93.62 340 | 6.73 361 | 4.62 356 | 10.41 356 | 24.33 355 | 8.28 364 | 3.56 359 | 9.69 356 | 15.07 355 | 12.86 356 |
|
test123 | | | 17.04 334 | 20.11 335 | 7.82 345 | 10.25 360 | 4.91 360 | 94.80 326 | 4.47 362 | 4.93 355 | 10.00 357 | 24.28 356 | 9.69 363 | 3.64 358 | 10.14 355 | 12.43 357 | 14.92 355 |
|
cdsmvs_eth3d_5k | | | 24.66 332 | 32.88 333 | 0.00 347 | 0.00 361 | 0.00 362 | 0.00 353 | 99.10 192 | 0.00 357 | 0.00 358 | 97.58 274 | 99.21 11 | 0.00 360 | 0.00 357 | 0.00 358 | 0.00 358 |
|
pcd_1.5k_mvsjas | | | 8.17 335 | 10.90 336 | 0.00 347 | 0.00 361 | 0.00 362 | 0.00 353 | 0.00 363 | 0.00 357 | 0.00 358 | 0.00 359 | 98.07 61 | 0.00 360 | 0.00 357 | 0.00 358 | 0.00 358 |
|
sosnet-low-res | | | 0.00 337 | 0.00 338 | 0.00 347 | 0.00 361 | 0.00 362 | 0.00 353 | 0.00 363 | 0.00 357 | 0.00 358 | 0.00 359 | 0.00 365 | 0.00 360 | 0.00 357 | 0.00 358 | 0.00 358 |
|
sosnet | | | 0.00 337 | 0.00 338 | 0.00 347 | 0.00 361 | 0.00 362 | 0.00 353 | 0.00 363 | 0.00 357 | 0.00 358 | 0.00 359 | 0.00 365 | 0.00 360 | 0.00 357 | 0.00 358 | 0.00 358 |
|
uncertanet | | | 0.00 337 | 0.00 338 | 0.00 347 | 0.00 361 | 0.00 362 | 0.00 353 | 0.00 363 | 0.00 357 | 0.00 358 | 0.00 359 | 0.00 365 | 0.00 360 | 0.00 357 | 0.00 358 | 0.00 358 |
|
Regformer | | | 0.00 337 | 0.00 338 | 0.00 347 | 0.00 361 | 0.00 362 | 0.00 353 | 0.00 363 | 0.00 357 | 0.00 358 | 0.00 359 | 0.00 365 | 0.00 360 | 0.00 357 | 0.00 358 | 0.00 358 |
|
ab-mvs-re | | | 8.12 336 | 10.83 337 | 0.00 347 | 0.00 361 | 0.00 362 | 0.00 353 | 0.00 363 | 0.00 357 | 0.00 358 | 97.48 281 | 0.00 365 | 0.00 360 | 0.00 357 | 0.00 358 | 0.00 358 |
|
uanet | | | 0.00 337 | 0.00 338 | 0.00 347 | 0.00 361 | 0.00 362 | 0.00 353 | 0.00 363 | 0.00 357 | 0.00 358 | 0.00 359 | 0.00 365 | 0.00 360 | 0.00 357 | 0.00 358 | 0.00 358 |
|
GSMVS | | | | | | | | | | | | | | | | | 98.81 251 |
|
test_part3 | | | | | | | | 97.25 217 | | 96.66 220 | | 98.71 181 | | 99.86 77 | 93.00 281 | | |
|
test_part2 | | | | | | 99.36 121 | 99.10 43 | | | | 99.05 115 | | | | | | |
|
sam_mvs1 | | | | | | | | | | | | | 84.74 305 | | | | 98.81 251 |
|
sam_mvs | | | | | | | | | | | | | 84.29 311 | | | | |
|
MTGPA | | | | | | | | | 99.20 164 | | | | | | | | |
|
test_post1 | | | | | | | | 97.59 195 | | | | 20.48 358 | 83.07 317 | 99.66 254 | 94.16 251 | | |
|
test_post | | | | | | | | | | | | 21.25 357 | 83.86 313 | 99.70 231 | | | |
|
patchmatchnet-post | | | | | | | | | | | | 98.77 175 | 84.37 308 | 99.85 88 | | | |
|
MTMP | | | | | | | | | 91.91 350 | | | | | | | | |
|
gm-plane-assit | | | | | | 94.83 352 | 81.97 353 | | | 88.07 339 | | 94.99 335 | | 99.60 271 | 91.76 299 | | |
|
TEST9 | | | | | | 98.71 249 | 98.08 108 | 95.96 290 | 99.03 205 | 91.40 320 | 95.85 312 | 97.53 276 | 96.52 166 | 99.76 199 | | | |
|
test_8 | | | | | | 98.67 260 | 98.01 114 | 95.91 296 | 99.02 209 | 91.64 314 | 95.79 314 | 97.50 279 | 96.47 169 | 99.76 199 | | | |
|
agg_prior | | | | | | 98.68 257 | 97.99 115 | | 99.01 212 | | 95.59 316 | | | 99.77 194 | | | |
|
test_prior4 | | | | | | | 97.97 120 | 95.86 297 | | | | | | | | | |
|
test_prior | | | | | 98.95 116 | 98.69 255 | 97.95 123 | | 99.03 205 | | | | | 99.59 275 | | | 99.30 183 |
|
旧先验2 | | | | | | | | 95.76 301 | | 88.56 338 | 97.52 250 | | | 99.66 254 | 94.48 242 | | |
|
新几何2 | | | | | | | | 95.93 294 | | | | | | | | | |
|
无先验 | | | | | | | | 95.74 303 | 98.74 252 | 89.38 334 | | | | 99.73 219 | 92.38 295 | | 99.22 201 |
|
原ACMM2 | | | | | | | | 95.53 310 | | | | | | | | | |
|
testdata2 | | | | | | | | | | | | | | 99.79 174 | 92.80 288 | | |
|
segment_acmp | | | | | | | | | | | | | 97.02 132 | | | | |
|
testdata1 | | | | | | | | 95.44 314 | | 96.32 231 | | | | | | | |
|
plane_prior7 | | | | | | 99.19 160 | 97.87 130 | | | | | | | | | | |
|
plane_prior6 | | | | | | 98.99 202 | 97.70 147 | | | | | | 94.90 220 | | | | |
|
plane_prior4 | | | | | | | | | | | | 97.98 256 | | | | | |
|
plane_prior3 | | | | | | | 97.78 140 | | | 97.41 177 | 97.79 231 | | | | | | |
|
plane_prior2 | | | | | | | | 97.77 172 | | 98.20 121 | | | | | | | |
|
plane_prior1 | | | | | | 99.05 190 | | | | | | | | | | | |
|
n2 | | | | | | | | | 0.00 363 | | | | | | | | |
|
nn | | | | | | | | | 0.00 363 | | | | | | | | |
|
door-mid | | | | | | | | | 99.57 43 | | | | | | | | |
|
test11 | | | | | | | | | 98.87 230 | | | | | | | | |
|
door | | | | | | | | | 99.41 97 | | | | | | | | |
|
HQP5-MVS | | | | | | | 96.79 185 | | | | | | | | | | |
|
HQP-NCC | | | | | | 98.67 260 | | 96.29 274 | | 96.05 242 | 95.55 320 | | | | | | |
|
ACMP_Plane | | | | | | 98.67 260 | | 96.29 274 | | 96.05 242 | 95.55 320 | | | | | | |
|
BP-MVS | | | | | | | | | | | | | | | 92.82 286 | | |
|
HQP4-MVS | | | | | | | | | | | 95.56 319 | | | 99.54 289 | | | 99.32 176 |
|
HQP2-MVS | | | | | | | | | | | | | 93.84 247 | | | | |
|
NP-MVS | | | | | | 98.84 232 | 97.39 162 | | | | | 96.84 299 | | | | | |
|
MDTV_nov1_ep13_2view | | | | | | | 74.92 357 | 97.69 180 | | 90.06 332 | 97.75 234 | | 85.78 298 | | 93.52 272 | | 98.69 265 |
|
Test By Simon | | | | | | | | | | | | | 96.52 166 | | | | |
|