CHOSEN 1792x2688 | | | 99.19 57 | 99.10 57 | 99.45 98 | 99.89 8 | 98.52 196 | 99.39 189 | 99.94 1 | 98.73 44 | 99.11 178 | 99.89 10 | 95.50 150 | 99.94 42 | 99.50 8 | 99.97 3 | 99.89 2 |
|
PVSNet_Blended_VisFu | | | 99.36 39 | 99.28 39 | 99.61 68 | 99.86 20 | 99.07 108 | 99.47 156 | 99.93 2 | 97.66 144 | 99.71 32 | 99.86 23 | 97.73 89 | 99.96 19 | 99.47 13 | 99.82 68 | 99.79 46 |
|
PVSNet_BlendedMVS | | | 98.86 104 | 98.80 98 | 99.03 152 | 99.76 44 | 98.79 167 | 99.28 222 | 99.91 3 | 97.42 166 | 99.67 44 | 99.37 233 | 97.53 92 | 99.88 104 | 98.98 54 | 97.29 241 | 98.42 303 |
|
PVSNet_Blended | | | 99.08 80 | 98.97 73 | 99.42 104 | 99.76 44 | 98.79 167 | 98.78 317 | 99.91 3 | 96.74 222 | 99.67 44 | 99.49 196 | 97.53 92 | 99.88 104 | 98.98 54 | 99.85 53 | 99.60 107 |
|
HyFIR lowres test | | | 99.11 73 | 98.92 80 | 99.65 59 | 99.90 3 | 99.37 77 | 99.02 284 | 99.91 3 | 97.67 143 | 99.59 65 | 99.75 95 | 95.90 140 | 99.73 173 | 99.53 6 | 99.02 135 | 99.86 5 |
|
MVS_111021_LR | | | 99.41 33 | 99.33 25 | 99.65 59 | 99.77 41 | 99.51 63 | 98.94 305 | 99.85 6 | 98.82 35 | 99.65 52 | 99.74 100 | 98.51 59 | 99.80 147 | 98.83 73 | 99.89 32 | 99.64 99 |
|
MVS_111021_HR | | | 99.41 33 | 99.32 26 | 99.66 55 | 99.72 75 | 99.47 67 | 98.95 303 | 99.85 6 | 98.82 35 | 99.54 79 | 99.73 104 | 98.51 59 | 99.74 166 | 98.91 59 | 99.88 35 | 99.77 52 |
|
PHI-MVS | | | 99.30 46 | 99.17 50 | 99.70 51 | 99.56 130 | 99.52 61 | 99.58 101 | 99.80 8 | 97.12 191 | 99.62 57 | 99.73 104 | 98.58 58 | 99.90 89 | 98.61 98 | 99.91 17 | 99.68 85 |
|
PatchMatch-RL | | | 98.84 113 | 98.62 120 | 99.52 86 | 99.71 81 | 99.28 86 | 99.06 273 | 99.77 9 | 97.74 135 | 99.50 85 | 99.53 182 | 95.41 152 | 99.84 122 | 97.17 218 | 99.64 101 | 99.44 146 |
|
3Dnovator | | 97.25 9 | 99.24 55 | 99.05 60 | 99.81 29 | 99.12 220 | 99.66 37 | 99.84 9 | 99.74 10 | 99.09 8 | 98.92 211 | 99.90 7 | 95.94 138 | 99.98 5 | 98.95 56 | 99.92 12 | 99.79 46 |
|
QAPM | | | 98.67 126 | 98.30 139 | 99.80 31 | 99.20 202 | 99.67 35 | 99.77 25 | 99.72 11 | 94.74 295 | 98.73 233 | 99.90 7 | 95.78 144 | 99.98 5 | 96.96 232 | 99.88 35 | 99.76 55 |
|
OpenMVS | | 96.50 16 | 98.47 133 | 98.12 147 | 99.52 86 | 99.04 235 | 99.53 58 | 99.82 13 | 99.72 11 | 94.56 301 | 98.08 281 | 99.88 15 | 94.73 194 | 99.98 5 | 97.47 200 | 99.76 79 | 99.06 178 |
|
CHOSEN 280x420 | | | 99.12 69 | 99.13 53 | 99.08 147 | 99.66 104 | 97.89 225 | 98.43 335 | 99.71 13 | 98.88 30 | 99.62 57 | 99.76 90 | 96.63 120 | 99.70 189 | 99.46 14 | 99.99 1 | 99.66 89 |
|
MSLP-MVS++ | | | 99.46 21 | 99.47 8 | 99.44 101 | 99.60 121 | 99.16 97 | 99.41 180 | 99.71 13 | 98.98 19 | 99.45 93 | 99.78 80 | 99.19 4 | 99.54 214 | 99.28 27 | 99.84 58 | 99.63 103 |
|
UA-Net | | | 99.42 30 | 99.29 37 | 99.80 31 | 99.62 115 | 99.55 54 | 99.50 137 | 99.70 15 | 98.79 40 | 99.77 24 | 99.96 1 | 97.45 94 | 99.96 19 | 98.92 58 | 99.90 24 | 99.89 2 |
|
PVSNet_0 | | 94.43 19 | 96.09 296 | 95.47 298 | 97.94 281 | 99.31 183 | 94.34 321 | 97.81 347 | 99.70 15 | 97.12 191 | 97.46 296 | 98.75 304 | 89.71 309 | 99.79 150 | 97.69 180 | 81.69 350 | 99.68 85 |
|
AdaColmap | | | 99.01 91 | 98.80 98 | 99.66 55 | 99.56 130 | 99.54 55 | 99.18 249 | 99.70 15 | 98.18 80 | 99.35 117 | 99.63 146 | 96.32 129 | 99.90 89 | 97.48 198 | 99.77 77 | 99.55 116 |
|
ACMMP | | | 99.45 22 | 99.32 26 | 99.82 26 | 99.89 8 | 99.67 35 | 99.62 84 | 99.69 18 | 98.12 85 | 99.63 54 | 99.84 36 | 98.73 49 | 99.96 19 | 98.55 110 | 99.83 64 | 99.81 36 |
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 |
XVS | | | 99.53 9 | 99.42 11 | 99.87 6 | 99.85 23 | 99.83 7 | 99.69 47 | 99.68 19 | 98.98 19 | 99.37 111 | 99.74 100 | 98.81 36 | 99.94 42 | 98.79 78 | 99.86 49 | 99.84 12 |
|
X-MVStestdata | | | 96.55 278 | 95.45 299 | 99.87 6 | 99.85 23 | 99.83 7 | 99.69 47 | 99.68 19 | 98.98 19 | 99.37 111 | 64.01 363 | 98.81 36 | 99.94 42 | 98.79 78 | 99.86 49 | 99.84 12 |
|
UGNet | | | 98.87 101 | 98.69 109 | 99.40 105 | 99.22 199 | 98.72 175 | 99.44 164 | 99.68 19 | 99.24 3 | 99.18 169 | 99.42 217 | 92.74 249 | 99.96 19 | 99.34 22 | 99.94 10 | 99.53 123 |
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 |
HFP-MVS | | | 99.49 13 | 99.37 17 | 99.86 13 | 99.87 15 | 99.80 15 | 99.66 67 | 99.67 22 | 98.15 81 | 99.68 38 | 99.69 119 | 99.06 9 | 99.96 19 | 98.69 88 | 99.87 39 | 99.84 12 |
|
#test# | | | 99.43 28 | 99.29 37 | 99.86 13 | 99.87 15 | 99.80 15 | 99.55 120 | 99.67 22 | 97.83 124 | 99.68 38 | 99.69 119 | 99.06 9 | 99.96 19 | 98.39 121 | 99.87 39 | 99.84 12 |
|
ACMMPR | | | 99.49 13 | 99.36 19 | 99.86 13 | 99.87 15 | 99.79 19 | 99.66 67 | 99.67 22 | 98.15 81 | 99.67 44 | 99.69 119 | 98.95 26 | 99.96 19 | 98.69 88 | 99.87 39 | 99.84 12 |
|
region2R | | | 99.48 17 | 99.35 22 | 99.87 6 | 99.88 11 | 99.80 15 | 99.65 77 | 99.66 25 | 98.13 83 | 99.66 49 | 99.68 124 | 98.96 21 | 99.96 19 | 98.62 96 | 99.87 39 | 99.84 12 |
|
EU-MVSNet | | | 97.98 190 | 98.03 155 | 97.81 292 | 98.72 295 | 96.65 277 | 99.66 67 | 99.66 25 | 98.09 90 | 98.35 268 | 99.82 45 | 95.25 160 | 98.01 330 | 97.41 205 | 95.30 277 | 98.78 208 |
|
DELS-MVS | | | 99.48 17 | 99.42 11 | 99.65 59 | 99.72 75 | 99.40 76 | 99.05 275 | 99.66 25 | 99.14 6 | 99.57 69 | 99.80 66 | 98.46 62 | 99.94 42 | 99.57 4 | 99.84 58 | 99.60 107 |
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 |
Vis-MVSNet | | | 99.12 69 | 98.97 73 | 99.56 76 | 99.78 36 | 99.10 104 | 99.68 56 | 99.66 25 | 98.49 56 | 99.86 7 | 99.87 20 | 94.77 191 | 99.84 122 | 99.19 35 | 99.41 110 | 99.74 61 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
CSCG | | | 99.32 43 | 99.32 26 | 99.32 114 | 99.85 23 | 98.29 208 | 99.71 43 | 99.66 25 | 98.11 87 | 99.41 102 | 99.80 66 | 98.37 70 | 99.96 19 | 98.99 53 | 99.96 5 | 99.72 72 |
|
PGM-MVS | | | 99.45 22 | 99.31 31 | 99.86 13 | 99.87 15 | 99.78 23 | 99.58 101 | 99.65 30 | 97.84 123 | 99.71 32 | 99.80 66 | 99.12 8 | 99.97 11 | 98.33 128 | 99.87 39 | 99.83 23 |
|
sss | | | 99.17 60 | 99.05 60 | 99.53 82 | 99.62 115 | 98.97 128 | 99.36 202 | 99.62 31 | 97.83 124 | 99.67 44 | 99.65 135 | 97.37 98 | 99.95 33 | 99.19 35 | 99.19 123 | 99.68 85 |
|
tfpnnormal | | | 97.84 211 | 97.47 226 | 98.98 158 | 99.20 202 | 99.22 93 | 99.64 79 | 99.61 32 | 96.32 254 | 98.27 273 | 99.70 113 | 93.35 236 | 99.44 224 | 95.69 274 | 95.40 275 | 98.27 310 |
|
AllTest | | | 98.87 101 | 98.72 105 | 99.31 115 | 99.86 20 | 98.48 201 | 99.56 114 | 99.61 32 | 97.85 121 | 99.36 114 | 99.85 27 | 95.95 136 | 99.85 116 | 96.66 254 | 99.83 64 | 99.59 111 |
|
TestCases | | | | | 99.31 115 | 99.86 20 | 98.48 201 | | 99.61 32 | 97.85 121 | 99.36 114 | 99.85 27 | 95.95 136 | 99.85 116 | 96.66 254 | 99.83 64 | 99.59 111 |
|
FC-MVSNet-test | | | 98.75 121 | 98.62 120 | 99.15 141 | 99.08 228 | 99.45 70 | 99.86 8 | 99.60 35 | 98.23 75 | 98.70 241 | 99.82 45 | 96.80 113 | 99.22 273 | 99.07 47 | 96.38 257 | 98.79 207 |
|
PVSNet | | 96.02 17 | 98.85 111 | 98.84 94 | 98.89 183 | 99.73 72 | 97.28 243 | 98.32 339 | 99.60 35 | 97.86 118 | 99.50 85 | 99.57 167 | 96.75 117 | 99.86 110 | 98.56 107 | 99.70 92 | 99.54 118 |
|
LTVRE_ROB | | 97.16 12 | 98.02 185 | 97.90 167 | 98.40 245 | 99.23 197 | 96.80 272 | 99.70 44 | 99.60 35 | 97.12 191 | 98.18 277 | 99.70 113 | 91.73 286 | 99.72 177 | 98.39 121 | 97.45 232 | 98.68 237 |
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 |
FIs | | | 98.78 118 | 98.63 116 | 99.23 134 | 99.18 207 | 99.54 55 | 99.83 12 | 99.59 38 | 98.28 70 | 98.79 228 | 99.81 55 | 96.75 117 | 99.37 235 | 99.08 46 | 96.38 257 | 98.78 208 |
|
WR-MVS_H | | | 98.13 165 | 97.87 178 | 98.90 180 | 99.02 238 | 98.84 148 | 99.70 44 | 99.59 38 | 97.27 177 | 98.40 264 | 99.19 269 | 95.53 149 | 99.23 270 | 98.34 127 | 93.78 313 | 98.61 282 |
|
abl_6 | | | 99.44 25 | 99.31 31 | 99.83 24 | 99.85 23 | 99.75 24 | 99.66 67 | 99.59 38 | 98.13 83 | 99.82 14 | 99.81 55 | 98.60 57 | 99.96 19 | 98.46 118 | 99.88 35 | 99.79 46 |
|
114514_t | | | 98.93 98 | 98.67 111 | 99.72 49 | 99.85 23 | 99.53 58 | 99.62 84 | 99.59 38 | 92.65 328 | 99.71 32 | 99.78 80 | 98.06 81 | 99.90 89 | 98.84 70 | 99.91 17 | 99.74 61 |
|
COLMAP_ROB | | 97.56 6 | 98.86 104 | 98.75 104 | 99.17 138 | 99.88 11 | 98.53 192 | 99.34 209 | 99.59 38 | 97.55 151 | 98.70 241 | 99.89 10 | 95.83 142 | 99.90 89 | 98.10 140 | 99.90 24 | 99.08 173 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
VPA-MVSNet | | | 98.29 147 | 97.95 164 | 99.30 118 | 99.16 214 | 99.54 55 | 99.50 137 | 99.58 43 | 98.27 71 | 99.35 117 | 99.37 233 | 92.53 264 | 99.65 198 | 99.35 18 | 94.46 299 | 98.72 220 |
|
CANet | | | 99.25 54 | 99.14 52 | 99.59 70 | 99.41 158 | 99.16 97 | 99.35 206 | 99.57 44 | 98.82 35 | 99.51 84 | 99.61 155 | 96.46 124 | 99.95 33 | 99.59 2 | 99.98 2 | 99.65 93 |
|
Anonymous20231211 | | | 97.88 205 | 97.54 216 | 98.90 180 | 99.71 81 | 98.53 192 | 99.48 151 | 99.57 44 | 94.16 311 | 98.81 225 | 99.68 124 | 93.23 237 | 99.42 229 | 98.84 70 | 94.42 301 | 98.76 213 |
|
VPNet | | | 97.84 211 | 97.44 235 | 99.01 154 | 99.21 200 | 98.94 136 | 99.48 151 | 99.57 44 | 98.38 64 | 99.28 133 | 99.73 104 | 88.89 316 | 99.39 230 | 99.19 35 | 93.27 317 | 98.71 222 |
|
DP-MVS Recon | | | 99.12 69 | 98.95 78 | 99.65 59 | 99.74 67 | 99.70 31 | 99.27 225 | 99.57 44 | 96.40 251 | 99.42 100 | 99.68 124 | 98.75 47 | 99.80 147 | 97.98 151 | 99.72 86 | 99.44 146 |
|
LS3D | | | 99.27 51 | 99.12 55 | 99.74 45 | 99.18 207 | 99.75 24 | 99.56 114 | 99.57 44 | 98.45 59 | 99.49 88 | 99.85 27 | 97.77 88 | 99.94 42 | 98.33 128 | 99.84 58 | 99.52 124 |
|
test_prior3 | | | 99.21 56 | 99.05 60 | 99.68 52 | 99.67 94 | 99.48 65 | 98.96 299 | 99.56 49 | 98.34 66 | 99.01 196 | 99.52 187 | 98.68 52 | 99.83 130 | 97.96 152 | 99.74 82 | 99.74 61 |
|
test_prior | | | | | 99.68 52 | 99.67 94 | 99.48 65 | | 99.56 49 | | | | | 99.83 130 | | | 99.74 61 |
|
APDe-MVS | | | 99.66 1 | 99.57 1 | 99.92 1 | 99.77 41 | 99.89 1 | 99.75 35 | 99.56 49 | 99.02 10 | 99.88 3 | 99.85 27 | 99.18 5 | 99.96 19 | 99.22 33 | 99.92 12 | 99.90 1 |
|
HPM-MVS_fast | | | 99.51 12 | 99.40 14 | 99.85 18 | 99.91 1 | 99.79 19 | 99.76 28 | 99.56 49 | 97.72 137 | 99.76 29 | 99.75 95 | 99.13 7 | 99.92 66 | 99.07 47 | 99.92 12 | 99.85 8 |
|
WTY-MVS | | | 99.06 82 | 98.88 86 | 99.61 68 | 99.62 115 | 99.16 97 | 99.37 196 | 99.56 49 | 98.04 100 | 99.53 80 | 99.62 151 | 96.84 112 | 99.94 42 | 98.85 69 | 98.49 169 | 99.72 72 |
|
API-MVS | | | 99.04 85 | 99.03 65 | 99.06 149 | 99.40 163 | 99.31 84 | 99.55 120 | 99.56 49 | 98.54 53 | 99.33 121 | 99.39 228 | 98.76 44 | 99.78 158 | 96.98 230 | 99.78 75 | 98.07 315 |
|
ACMH | | 97.28 8 | 98.10 170 | 97.99 160 | 98.44 242 | 99.41 158 | 96.96 266 | 99.60 92 | 99.56 49 | 98.09 90 | 98.15 278 | 99.91 5 | 90.87 298 | 99.70 189 | 98.88 60 | 97.45 232 | 98.67 248 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
CVMVSNet | | | 98.57 131 | 98.67 111 | 98.30 252 | 99.35 171 | 95.59 297 | 99.50 137 | 99.55 56 | 98.60 51 | 99.39 107 | 99.83 38 | 94.48 205 | 99.45 219 | 98.75 80 | 98.56 165 | 99.85 8 |
|
XVG-OURS | | | 98.73 122 | 98.68 110 | 98.88 190 | 99.70 87 | 97.73 238 | 98.92 306 | 99.55 56 | 98.52 55 | 99.45 93 | 99.84 36 | 95.27 157 | 99.91 76 | 98.08 145 | 98.84 151 | 99.00 183 |
|
LPG-MVS_test | | | 98.22 154 | 98.13 146 | 98.49 233 | 99.33 175 | 97.05 257 | 99.58 101 | 99.55 56 | 97.46 158 | 99.24 150 | 99.83 38 | 92.58 262 | 99.72 177 | 98.09 141 | 97.51 225 | 98.68 237 |
|
LGP-MVS_train | | | | | 98.49 233 | 99.33 175 | 97.05 257 | | 99.55 56 | 97.46 158 | 99.24 150 | 99.83 38 | 92.58 262 | 99.72 177 | 98.09 141 | 97.51 225 | 98.68 237 |
|
XXY-MVS | | | 98.38 140 | 98.09 150 | 99.24 132 | 99.26 194 | 99.32 81 | 99.56 114 | 99.55 56 | 97.45 161 | 98.71 235 | 99.83 38 | 93.23 237 | 99.63 205 | 98.88 60 | 96.32 259 | 98.76 213 |
|
DeepC-MVS | | 98.35 2 | 99.30 46 | 99.19 48 | 99.64 64 | 99.82 29 | 99.23 92 | 99.62 84 | 99.55 56 | 98.94 26 | 99.63 54 | 99.95 2 | 95.82 143 | 99.94 42 | 99.37 17 | 99.97 3 | 99.73 66 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
MSDG | | | 98.98 94 | 98.80 98 | 99.53 82 | 99.76 44 | 99.19 94 | 98.75 320 | 99.55 56 | 97.25 179 | 99.47 90 | 99.77 87 | 97.82 86 | 99.87 106 | 96.93 235 | 99.90 24 | 99.54 118 |
|
PS-MVSNAJss | | | 98.92 99 | 98.92 80 | 98.90 180 | 98.78 287 | 98.53 192 | 99.78 22 | 99.54 63 | 98.07 94 | 99.00 203 | 99.76 90 | 99.01 12 | 99.37 235 | 99.13 42 | 97.23 242 | 98.81 205 |
|
新几何1 | | | | | 99.75 40 | 99.75 56 | 99.59 49 | | 99.54 63 | 96.76 221 | 99.29 129 | 99.64 142 | 98.43 64 | 99.94 42 | 96.92 236 | 99.66 98 | 99.72 72 |
|
旧先验1 | | | | | | 99.74 67 | 99.59 49 | | 99.54 63 | | | 99.69 119 | 98.47 61 | | | 99.68 96 | 99.73 66 |
|
APD-MVS_3200maxsize | | | 99.48 17 | 99.35 22 | 99.85 18 | 99.76 44 | 99.83 7 | 99.63 81 | 99.54 63 | 98.36 65 | 99.79 18 | 99.82 45 | 98.86 32 | 99.95 33 | 98.62 96 | 99.81 69 | 99.78 50 |
|
XVG-OURS-SEG-HR | | | 98.69 124 | 98.62 120 | 98.89 183 | 99.71 81 | 97.74 237 | 99.12 258 | 99.54 63 | 98.44 62 | 99.42 100 | 99.71 110 | 94.20 214 | 99.92 66 | 98.54 112 | 98.90 146 | 99.00 183 |
|
HPM-MVS | | | 99.42 30 | 99.28 39 | 99.83 24 | 99.90 3 | 99.72 28 | 99.81 15 | 99.54 63 | 97.59 146 | 99.68 38 | 99.63 146 | 98.91 29 | 99.94 42 | 98.58 102 | 99.91 17 | 99.84 12 |
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023 |
ab-mvs | | | 98.86 104 | 98.63 116 | 99.54 77 | 99.64 108 | 99.19 94 | 99.44 164 | 99.54 63 | 97.77 131 | 99.30 125 | 99.81 55 | 94.20 214 | 99.93 57 | 99.17 38 | 98.82 152 | 99.49 133 |
|
F-COLMAP | | | 99.19 57 | 99.04 63 | 99.64 64 | 99.78 36 | 99.27 88 | 99.42 176 | 99.54 63 | 97.29 176 | 99.41 102 | 99.59 160 | 98.42 67 | 99.93 57 | 98.19 134 | 99.69 93 | 99.73 66 |
|
ACMH+ | | 97.24 10 | 97.92 202 | 97.78 186 | 98.32 250 | 99.46 148 | 96.68 276 | 99.56 114 | 99.54 63 | 98.41 63 | 97.79 294 | 99.87 20 | 90.18 306 | 99.66 196 | 98.05 149 | 97.18 245 | 98.62 273 |
|
MAR-MVS | | | 98.86 104 | 98.63 116 | 99.54 77 | 99.37 168 | 99.66 37 | 99.45 160 | 99.54 63 | 96.61 231 | 99.01 196 | 99.40 224 | 97.09 104 | 99.86 110 | 97.68 182 | 99.53 106 | 99.10 168 |
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 |
pcd1.5k->3k | | | 40.85 336 | 43.49 338 | 32.93 350 | 98.95 254 | 0.00 368 | 0.00 360 | 99.53 73 | 0.00 363 | 0.00 364 | 0.27 365 | 95.32 155 | 0.00 366 | 0.00 363 | 97.30 240 | 98.80 206 |
|
jajsoiax | | | 98.43 136 | 98.28 140 | 98.88 190 | 98.60 309 | 98.43 204 | 99.82 13 | 99.53 73 | 98.19 77 | 98.63 252 | 99.80 66 | 93.22 239 | 99.44 224 | 99.22 33 | 97.50 227 | 98.77 211 |
|
mvs_tets | | | 98.40 139 | 98.23 142 | 98.91 176 | 98.67 302 | 98.51 198 | 99.66 67 | 99.53 73 | 98.19 77 | 98.65 250 | 99.81 55 | 92.75 247 | 99.44 224 | 99.31 25 | 97.48 231 | 98.77 211 |
|
UniMVSNet_NR-MVSNet | | | 98.22 154 | 97.97 162 | 98.96 161 | 98.92 264 | 98.98 125 | 99.48 151 | 99.53 73 | 97.76 132 | 98.71 235 | 99.46 210 | 96.43 127 | 99.22 273 | 98.57 104 | 92.87 322 | 98.69 232 |
|
MP-MVS-pluss | | | 99.37 38 | 99.20 47 | 99.88 4 | 99.90 3 | 99.87 2 | 99.30 216 | 99.52 77 | 97.18 185 | 99.60 62 | 99.79 74 | 98.79 38 | 99.95 33 | 98.83 73 | 99.91 17 | 99.83 23 |
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
SD-MVS | | | 99.41 33 | 99.52 6 | 99.05 151 | 99.74 67 | 99.68 33 | 99.46 159 | 99.52 77 | 99.11 7 | 99.88 3 | 99.91 5 | 99.43 1 | 97.70 337 | 98.72 85 | 99.93 11 | 99.77 52 |
|
PS-CasMVS | | | 97.93 199 | 97.59 213 | 98.95 163 | 98.99 241 | 99.06 109 | 99.68 56 | 99.52 77 | 97.13 189 | 98.31 270 | 99.68 124 | 92.44 270 | 99.05 291 | 98.51 113 | 94.08 308 | 98.75 215 |
|
XVG-ACMP-BASELINE | | | 97.83 213 | 97.71 199 | 98.20 267 | 99.11 222 | 96.33 286 | 99.41 180 | 99.52 77 | 98.06 98 | 99.05 192 | 99.50 193 | 89.64 310 | 99.73 173 | 97.73 174 | 97.38 238 | 98.53 296 |
|
CNVR-MVS | | | 99.42 30 | 99.30 33 | 99.78 35 | 99.62 115 | 99.71 29 | 99.26 233 | 99.52 77 | 98.82 35 | 99.39 107 | 99.71 110 | 98.96 21 | 99.85 116 | 98.59 101 | 99.80 71 | 99.77 52 |
|
CP-MVS | | | 99.45 22 | 99.32 26 | 99.85 18 | 99.83 28 | 99.75 24 | 99.69 47 | 99.52 77 | 98.07 94 | 99.53 80 | 99.63 146 | 98.93 28 | 99.97 11 | 98.74 81 | 99.91 17 | 99.83 23 |
|
FMVSNet5 | | | 96.43 281 | 96.19 278 | 97.15 307 | 99.11 222 | 95.89 294 | 99.32 211 | 99.52 77 | 94.47 305 | 98.34 269 | 99.07 278 | 87.54 331 | 97.07 340 | 92.61 326 | 95.72 270 | 98.47 300 |
|
OMC-MVS | | | 99.08 80 | 99.04 63 | 99.20 136 | 99.67 94 | 98.22 211 | 99.28 222 | 99.52 77 | 98.07 94 | 99.66 49 | 99.81 55 | 97.79 87 | 99.78 158 | 97.79 166 | 99.81 69 | 99.60 107 |
|
PLC | | 97.94 4 | 99.02 88 | 98.85 93 | 99.53 82 | 99.66 104 | 99.01 121 | 99.24 237 | 99.52 77 | 96.85 217 | 99.27 137 | 99.48 202 | 98.25 75 | 99.91 76 | 97.76 170 | 99.62 104 | 99.65 93 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
MVS_0304 | | | 99.06 82 | 98.86 91 | 99.66 55 | 99.51 135 | 99.36 78 | 99.22 242 | 99.51 86 | 98.95 24 | 99.58 66 | 99.65 135 | 93.74 233 | 99.98 5 | 99.66 1 | 99.95 6 | 99.64 99 |
|
xiu_mvs_v1_base_debu | | | 99.29 48 | 99.27 41 | 99.34 109 | 99.63 111 | 98.97 128 | 99.12 258 | 99.51 86 | 98.86 31 | 99.84 8 | 99.47 206 | 98.18 77 | 99.99 1 | 99.50 8 | 99.31 116 | 99.08 173 |
|
xiu_mvs_v1_base | | | 99.29 48 | 99.27 41 | 99.34 109 | 99.63 111 | 98.97 128 | 99.12 258 | 99.51 86 | 98.86 31 | 99.84 8 | 99.47 206 | 98.18 77 | 99.99 1 | 99.50 8 | 99.31 116 | 99.08 173 |
|
xiu_mvs_v1_base_debi | | | 99.29 48 | 99.27 41 | 99.34 109 | 99.63 111 | 98.97 128 | 99.12 258 | 99.51 86 | 98.86 31 | 99.84 8 | 99.47 206 | 98.18 77 | 99.99 1 | 99.50 8 | 99.31 116 | 99.08 173 |
|
cdsmvs_eth3d_5k | | | 24.64 340 | 32.85 341 | 0.00 353 | 0.00 367 | 0.00 368 | 0.00 360 | 99.51 86 | 0.00 363 | 0.00 364 | 99.56 169 | 96.58 121 | 0.00 366 | 0.00 363 | 0.00 364 | 0.00 364 |
|
HPM-MVS++ | | | 99.39 37 | 99.23 46 | 99.87 6 | 99.75 56 | 99.84 6 | 99.43 169 | 99.51 86 | 98.68 47 | 99.27 137 | 99.53 182 | 98.64 55 | 99.96 19 | 98.44 120 | 99.80 71 | 99.79 46 |
|
无先验 | | | | | | | | 98.99 290 | 99.51 86 | 96.89 215 | | | | 99.93 57 | 97.53 193 | | 99.72 72 |
|
testdata | | | | | 99.54 77 | 99.75 56 | 98.95 133 | | 99.51 86 | 97.07 202 | 99.43 97 | 99.70 113 | 98.87 31 | 99.94 42 | 97.76 170 | 99.64 101 | 99.72 72 |
|
PEN-MVS | | | 97.76 226 | 97.44 235 | 98.72 215 | 98.77 290 | 98.54 191 | 99.78 22 | 99.51 86 | 97.06 204 | 98.29 272 | 99.64 142 | 92.63 261 | 98.89 310 | 98.09 141 | 93.16 318 | 98.72 220 |
|
UniMVSNet (Re) | | | 98.29 147 | 98.00 158 | 99.13 145 | 99.00 240 | 99.36 78 | 99.49 146 | 99.51 86 | 97.95 111 | 98.97 206 | 99.13 273 | 96.30 130 | 99.38 231 | 98.36 126 | 93.34 316 | 98.66 259 |
|
SteuartSystems-ACMMP | | | 99.54 7 | 99.42 11 | 99.87 6 | 99.82 29 | 99.81 14 | 99.59 94 | 99.51 86 | 98.62 49 | 99.79 18 | 99.83 38 | 99.28 3 | 99.97 11 | 98.48 115 | 99.90 24 | 99.84 12 |
Skip Steuart: Steuart Systems R&D Blog. |
UnsupCasMVSNet_eth | | | 96.44 280 | 96.12 279 | 97.40 306 | 98.65 303 | 95.65 295 | 99.36 202 | 99.51 86 | 97.13 189 | 96.04 316 | 98.99 285 | 88.40 325 | 98.17 319 | 96.71 250 | 90.27 330 | 98.40 305 |
|
3Dnovator+ | | 97.12 13 | 99.18 59 | 98.97 73 | 99.82 26 | 99.17 212 | 99.68 33 | 99.81 15 | 99.51 86 | 99.20 4 | 98.72 234 | 99.89 10 | 95.68 147 | 99.97 11 | 98.86 67 | 99.86 49 | 99.81 36 |
|
TAPA-MVS | | 97.07 15 | 97.74 232 | 97.34 250 | 98.94 164 | 99.70 87 | 97.53 240 | 99.25 235 | 99.51 86 | 91.90 332 | 99.30 125 | 99.63 146 | 98.78 39 | 99.64 200 | 88.09 338 | 99.87 39 | 99.65 93 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
Effi-MVS+ | | | 98.81 114 | 98.59 125 | 99.48 91 | 99.46 148 | 99.12 103 | 98.08 345 | 99.50 100 | 97.50 156 | 99.38 109 | 99.41 220 | 96.37 128 | 99.81 143 | 99.11 44 | 98.54 166 | 99.51 129 |
|
anonymousdsp | | | 98.44 135 | 98.28 140 | 98.94 164 | 98.50 314 | 98.96 132 | 99.77 25 | 99.50 100 | 97.07 202 | 98.87 217 | 99.77 87 | 94.76 192 | 99.28 258 | 98.66 91 | 97.60 218 | 98.57 294 |
|
APD-MVS | | | 99.27 51 | 99.08 58 | 99.84 23 | 99.75 56 | 99.79 19 | 99.50 137 | 99.50 100 | 97.16 187 | 99.77 24 | 99.82 45 | 98.78 39 | 99.94 42 | 97.56 190 | 99.86 49 | 99.80 41 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
MIMVSNet1 | | | 95.51 301 | 95.04 304 | 96.92 313 | 97.38 330 | 95.60 296 | 99.52 128 | 99.50 100 | 93.65 318 | 96.97 307 | 99.17 270 | 85.28 340 | 96.56 344 | 88.36 337 | 95.55 274 | 98.60 289 |
|
DP-MVS | | | 99.16 62 | 98.95 78 | 99.78 35 | 99.77 41 | 99.53 58 | 99.41 180 | 99.50 100 | 97.03 206 | 99.04 193 | 99.88 15 | 97.39 95 | 99.92 66 | 98.66 91 | 99.90 24 | 99.87 4 |
|
Anonymous20240521 | | | 98.30 145 | 98.00 158 | 99.18 137 | 98.98 245 | 99.46 68 | 99.78 22 | 99.49 105 | 96.91 214 | 98.00 286 | 99.25 263 | 96.51 123 | 99.38 231 | 98.15 138 | 94.95 287 | 98.71 222 |
|
Fast-Effi-MVS+-dtu | | | 98.77 120 | 98.83 97 | 98.60 223 | 99.41 158 | 96.99 262 | 99.52 128 | 99.49 105 | 98.11 87 | 99.24 150 | 99.34 247 | 96.96 110 | 99.79 150 | 97.95 154 | 99.45 107 | 99.02 182 |
|
semantic-postprocess | | | | | 98.06 273 | 99.57 126 | 96.36 285 | | 99.49 105 | 97.18 185 | 98.71 235 | 99.72 108 | 92.70 253 | 99.14 280 | 97.44 203 | 95.86 268 | 98.67 248 |
|
Regformer-4 | | | 99.59 2 | 99.54 4 | 99.73 47 | 99.76 44 | 99.41 74 | 99.58 101 | 99.49 105 | 99.02 10 | 99.88 3 | 99.80 66 | 99.00 18 | 99.94 42 | 99.45 15 | 99.92 12 | 99.84 12 |
|
Regformer-2 | | | 99.54 7 | 99.47 8 | 99.75 40 | 99.71 81 | 99.52 61 | 99.49 146 | 99.49 105 | 98.94 26 | 99.83 11 | 99.76 90 | 99.01 12 | 99.94 42 | 99.15 41 | 99.87 39 | 99.80 41 |
|
test222 | | | | | | 99.75 56 | 99.49 64 | 98.91 308 | 99.49 105 | 96.42 248 | 99.34 120 | 99.65 135 | 98.28 74 | | | 99.69 93 | 99.72 72 |
|
1314 | | | 98.68 125 | 98.54 128 | 99.11 146 | 98.89 270 | 98.65 181 | 99.27 225 | 99.49 105 | 96.89 215 | 97.99 287 | 99.56 169 | 97.72 90 | 99.83 130 | 97.74 173 | 99.27 119 | 98.84 203 |
|
TranMVSNet+NR-MVSNet | | | 97.93 199 | 97.66 203 | 98.76 213 | 98.78 287 | 98.62 185 | 99.65 77 | 99.49 105 | 97.76 132 | 98.49 260 | 99.60 158 | 94.23 213 | 98.97 307 | 98.00 150 | 92.90 320 | 98.70 227 |
|
CPTT-MVS | | | 99.11 73 | 98.90 83 | 99.74 45 | 99.80 34 | 99.46 68 | 99.59 94 | 99.49 105 | 97.03 206 | 99.63 54 | 99.69 119 | 97.27 100 | 99.96 19 | 97.82 163 | 99.84 58 | 99.81 36 |
|
ACMP | | 97.20 11 | 98.06 174 | 97.94 165 | 98.45 239 | 99.37 168 | 97.01 260 | 99.44 164 | 99.49 105 | 97.54 154 | 98.45 262 | 99.79 74 | 91.95 275 | 99.72 177 | 97.91 156 | 97.49 230 | 98.62 273 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
test_part1 | | | | | | | | | 99.48 115 | | | | 98.96 21 | | | 99.84 58 | 99.83 23 |
|
ESAPD | | | 99.31 45 | 99.13 53 | 99.87 6 | 99.81 32 | 99.83 7 | 99.37 196 | 99.48 115 | 97.97 109 | 99.77 24 | 99.78 80 | 98.96 21 | 99.95 33 | 97.15 219 | 99.84 58 | 99.83 23 |
|
ACMMP_Plus | | | 99.47 20 | 99.34 24 | 99.88 4 | 99.87 15 | 99.86 3 | 99.47 156 | 99.48 115 | 98.05 99 | 99.76 29 | 99.86 23 | 98.82 35 | 99.93 57 | 98.82 77 | 99.91 17 | 99.84 12 |
|
canonicalmvs | | | 99.02 88 | 98.86 91 | 99.51 88 | 99.42 155 | 99.32 81 | 99.80 19 | 99.48 115 | 98.63 48 | 99.31 124 | 98.81 300 | 97.09 104 | 99.75 165 | 99.27 29 | 97.90 210 | 99.47 139 |
|
1121 | | | 99.09 77 | 98.87 87 | 99.75 40 | 99.74 67 | 99.60 47 | 99.27 225 | 99.48 115 | 96.82 220 | 99.25 145 | 99.65 135 | 98.38 68 | 99.93 57 | 97.53 193 | 99.67 97 | 99.73 66 |
|
testgi | | | 97.65 246 | 97.50 221 | 98.13 271 | 99.36 170 | 96.45 282 | 99.42 176 | 99.48 115 | 97.76 132 | 97.87 290 | 99.45 213 | 91.09 295 | 98.81 312 | 94.53 295 | 98.52 167 | 99.13 167 |
|
DTE-MVSNet | | | 97.51 256 | 97.19 262 | 98.46 238 | 98.63 305 | 98.13 216 | 99.84 9 | 99.48 115 | 96.68 226 | 97.97 288 | 99.67 129 | 92.92 243 | 98.56 316 | 96.88 244 | 92.60 325 | 98.70 227 |
|
mPP-MVS | | | 99.44 25 | 99.30 33 | 99.86 13 | 99.88 11 | 99.79 19 | 99.69 47 | 99.48 115 | 98.12 85 | 99.50 85 | 99.75 95 | 98.78 39 | 99.97 11 | 98.57 104 | 99.89 32 | 99.83 23 |
|
NCCC | | | 99.34 41 | 99.19 48 | 99.79 34 | 99.61 119 | 99.65 40 | 99.30 216 | 99.48 115 | 98.86 31 | 99.21 160 | 99.63 146 | 98.72 50 | 99.90 89 | 98.25 132 | 99.63 103 | 99.80 41 |
|
GBi-Net | | | 97.68 241 | 97.48 224 | 98.29 253 | 99.51 135 | 97.26 245 | 99.43 169 | 99.48 115 | 96.49 238 | 99.07 187 | 99.32 253 | 90.26 302 | 98.98 300 | 97.10 222 | 96.65 250 | 98.62 273 |
|
UnsupCasMVSNet_bld | | | 93.53 316 | 92.51 318 | 96.58 319 | 97.38 330 | 93.82 324 | 98.24 341 | 99.48 115 | 91.10 336 | 93.10 336 | 96.66 343 | 74.89 350 | 98.37 317 | 94.03 311 | 87.71 340 | 97.56 339 |
|
test1 | | | 97.68 241 | 97.48 224 | 98.29 253 | 99.51 135 | 97.26 245 | 99.43 169 | 99.48 115 | 96.49 238 | 99.07 187 | 99.32 253 | 90.26 302 | 98.98 300 | 97.10 222 | 96.65 250 | 98.62 273 |
|
FMVSNet1 | | | 96.84 275 | 96.36 276 | 98.29 253 | 99.32 182 | 97.26 245 | 99.43 169 | 99.48 115 | 95.11 290 | 98.55 257 | 99.32 253 | 83.95 345 | 98.98 300 | 95.81 271 | 96.26 260 | 98.62 273 |
|
1112_ss | | | 98.98 94 | 98.77 101 | 99.59 70 | 99.68 93 | 99.02 119 | 99.25 235 | 99.48 115 | 97.23 182 | 99.13 173 | 99.58 163 | 96.93 111 | 99.90 89 | 98.87 64 | 98.78 156 | 99.84 12 |
|
IterMVS | | | 97.83 213 | 97.77 190 | 98.02 276 | 99.58 124 | 96.27 288 | 99.02 284 | 99.48 115 | 97.22 183 | 98.71 235 | 99.70 113 | 92.75 247 | 99.13 283 | 97.46 201 | 96.00 265 | 98.67 248 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
CMPMVS | | 69.68 23 | 94.13 313 | 94.90 305 | 91.84 332 | 97.24 334 | 80.01 353 | 98.52 332 | 99.48 115 | 89.01 342 | 91.99 339 | 99.67 129 | 85.67 338 | 99.13 283 | 95.44 279 | 97.03 247 | 96.39 343 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
SMA-MVS | | | 99.44 25 | 99.30 33 | 99.85 18 | 99.70 87 | 99.83 7 | 99.56 114 | 99.47 131 | 97.45 161 | 99.78 22 | 99.82 45 | 99.18 5 | 99.91 76 | 98.83 73 | 99.89 32 | 99.80 41 |
|
zzz-MVS | | | 99.49 13 | 99.36 19 | 99.89 2 | 99.90 3 | 99.86 3 | 99.36 202 | 99.47 131 | 98.79 40 | 99.68 38 | 99.81 55 | 98.43 64 | 99.97 11 | 98.88 60 | 99.90 24 | 99.83 23 |
|
MTGPA | | | | | | | | | 99.47 131 | | | | | | | | |
|
pmmvs6 | | | 96.53 279 | 96.09 280 | 97.82 291 | 98.69 299 | 95.47 302 | 99.37 196 | 99.47 131 | 93.46 322 | 97.41 297 | 99.78 80 | 87.06 334 | 99.33 246 | 96.92 236 | 92.70 324 | 98.65 262 |
|
Fast-Effi-MVS+ | | | 98.70 123 | 98.43 130 | 99.51 88 | 99.51 135 | 99.28 86 | 99.52 128 | 99.47 131 | 96.11 274 | 99.01 196 | 99.34 247 | 96.20 133 | 99.84 122 | 97.88 158 | 98.82 152 | 99.39 152 |
|
MTAPA | | | 99.52 11 | 99.39 15 | 99.89 2 | 99.90 3 | 99.86 3 | 99.66 67 | 99.47 131 | 98.79 40 | 99.68 38 | 99.81 55 | 98.43 64 | 99.97 11 | 98.88 60 | 99.90 24 | 99.83 23 |
|
原ACMM1 | | | | | 99.65 59 | 99.73 72 | 99.33 80 | | 99.47 131 | 97.46 158 | 99.12 176 | 99.66 134 | 98.67 54 | 99.91 76 | 97.70 179 | 99.69 93 | 99.71 79 |
|
HQP_MVS | | | 98.27 149 | 98.22 143 | 98.44 242 | 99.29 187 | 96.97 264 | 99.39 189 | 99.47 131 | 98.97 22 | 99.11 178 | 99.61 155 | 92.71 251 | 99.69 192 | 97.78 167 | 97.63 215 | 98.67 248 |
|
plane_prior5 | | | | | | | | | 99.47 131 | | | | | 99.69 192 | 97.78 167 | 97.63 215 | 98.67 248 |
|
Test_1112_low_res | | | 98.89 100 | 98.66 114 | 99.57 74 | 99.69 90 | 98.95 133 | 99.03 281 | 99.47 131 | 96.98 208 | 99.15 172 | 99.23 266 | 96.77 116 | 99.89 97 | 98.83 73 | 98.78 156 | 99.86 5 |
|
ppachtmachnet_test | | | 97.49 259 | 97.45 229 | 97.61 299 | 98.62 306 | 95.24 306 | 98.80 315 | 99.46 141 | 96.11 274 | 98.22 274 | 99.62 151 | 96.45 125 | 98.97 307 | 93.77 312 | 95.97 266 | 98.61 282 |
|
nrg030 | | | 98.64 129 | 98.42 131 | 99.28 123 | 99.05 234 | 99.69 32 | 99.81 15 | 99.46 141 | 98.04 100 | 99.01 196 | 99.82 45 | 96.69 119 | 99.38 231 | 99.34 22 | 94.59 298 | 98.78 208 |
|
v7n | | | 97.87 207 | 97.52 217 | 98.92 172 | 98.76 291 | 98.58 189 | 99.84 9 | 99.46 141 | 96.20 265 | 98.91 212 | 99.70 113 | 94.89 180 | 99.44 224 | 96.03 267 | 93.89 312 | 98.75 215 |
|
PS-MVSNAJ | | | 99.32 43 | 99.32 26 | 99.30 118 | 99.57 126 | 98.94 136 | 98.97 297 | 99.46 141 | 98.92 28 | 99.71 32 | 99.24 265 | 99.01 12 | 99.98 5 | 99.35 18 | 99.66 98 | 98.97 187 |
|
Regformer-1 | | | 99.53 9 | 99.47 8 | 99.72 49 | 99.71 81 | 99.44 71 | 99.49 146 | 99.46 141 | 98.95 24 | 99.83 11 | 99.76 90 | 99.01 12 | 99.93 57 | 99.17 38 | 99.87 39 | 99.80 41 |
|
MP-MVS | | | 99.33 42 | 99.15 51 | 99.87 6 | 99.88 11 | 99.82 13 | 99.66 67 | 99.46 141 | 98.09 90 | 99.48 89 | 99.74 100 | 98.29 73 | 99.96 19 | 97.93 155 | 99.87 39 | 99.82 32 |
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo. |
CP-MVSNet | | | 98.09 171 | 97.78 186 | 99.01 154 | 98.97 249 | 99.24 91 | 99.67 58 | 99.46 141 | 97.25 179 | 98.48 261 | 99.64 142 | 93.79 229 | 99.06 290 | 98.63 94 | 94.10 307 | 98.74 218 |
|
MVSFormer | | | 99.17 60 | 99.12 55 | 99.29 121 | 99.51 135 | 98.94 136 | 99.88 1 | 99.46 141 | 97.55 151 | 99.80 16 | 99.65 135 | 97.39 95 | 99.28 258 | 99.03 49 | 99.85 53 | 99.65 93 |
|
test_djsdf | | | 98.67 126 | 98.57 126 | 98.98 158 | 98.70 298 | 98.91 141 | 99.88 1 | 99.46 141 | 97.55 151 | 99.22 157 | 99.88 15 | 95.73 146 | 99.28 258 | 99.03 49 | 97.62 217 | 98.75 215 |
|
CDS-MVSNet | | | 99.09 77 | 99.03 65 | 99.25 129 | 99.42 155 | 98.73 173 | 99.45 160 | 99.46 141 | 98.11 87 | 99.46 92 | 99.77 87 | 98.01 82 | 99.37 235 | 98.70 86 | 98.92 144 | 99.66 89 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
TAMVS | | | 99.12 69 | 99.08 58 | 99.24 132 | 99.46 148 | 98.55 190 | 99.51 132 | 99.46 141 | 98.09 90 | 99.45 93 | 99.82 45 | 98.34 71 | 99.51 215 | 98.70 86 | 98.93 142 | 99.67 88 |
|
DeepC-MVS_fast | | 98.69 1 | 99.49 13 | 99.39 15 | 99.77 37 | 99.63 111 | 99.59 49 | 99.36 202 | 99.46 141 | 99.07 9 | 99.79 18 | 99.82 45 | 98.85 33 | 99.92 66 | 98.68 90 | 99.87 39 | 99.82 32 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
xiu_mvs_v2_base | | | 99.26 53 | 99.25 45 | 99.29 121 | 99.53 132 | 98.91 141 | 99.02 284 | 99.45 153 | 98.80 39 | 99.71 32 | 99.26 262 | 98.94 27 | 99.98 5 | 99.34 22 | 99.23 120 | 98.98 186 |
|
v748 | | | 97.52 253 | 97.23 260 | 98.41 244 | 98.69 299 | 97.23 248 | 99.87 4 | 99.45 153 | 95.72 284 | 98.51 258 | 99.53 182 | 94.13 218 | 99.30 255 | 96.78 247 | 92.39 326 | 98.70 227 |
|
EI-MVSNet-UG-set | | | 99.58 3 | 99.57 1 | 99.64 64 | 99.78 36 | 99.14 101 | 99.60 92 | 99.45 153 | 99.01 13 | 99.90 1 | 99.83 38 | 98.98 19 | 99.93 57 | 99.59 2 | 99.95 6 | 99.86 5 |
|
EI-MVSNet-Vis-set | | | 99.58 3 | 99.56 3 | 99.64 64 | 99.78 36 | 99.15 100 | 99.61 90 | 99.45 153 | 99.01 13 | 99.89 2 | 99.82 45 | 99.01 12 | 99.92 66 | 99.56 5 | 99.95 6 | 99.85 8 |
|
pm-mvs1 | | | 97.68 241 | 97.28 257 | 98.88 190 | 99.06 231 | 98.62 185 | 99.50 137 | 99.45 153 | 96.32 254 | 97.87 290 | 99.79 74 | 92.47 266 | 99.35 242 | 97.54 192 | 93.54 315 | 98.67 248 |
|
diffmvs | | | 98.99 93 | 98.87 87 | 99.35 108 | 99.45 152 | 98.74 172 | 99.62 84 | 99.45 153 | 97.43 163 | 99.13 173 | 99.72 108 | 97.23 101 | 99.87 106 | 98.86 67 | 98.90 146 | 99.45 145 |
|
DU-MVS | | | 98.08 173 | 97.79 184 | 98.96 161 | 98.87 274 | 98.98 125 | 99.41 180 | 99.45 153 | 97.87 117 | 98.71 235 | 99.50 193 | 94.82 184 | 99.22 273 | 98.57 104 | 92.87 322 | 98.68 237 |
|
ACMM | | 97.58 5 | 98.37 141 | 98.34 135 | 98.48 235 | 99.41 158 | 97.10 251 | 99.56 114 | 99.45 153 | 98.53 54 | 99.04 193 | 99.85 27 | 93.00 241 | 99.71 183 | 98.74 81 | 97.45 232 | 98.64 264 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
Gipuma | | | 90.99 321 | 90.15 322 | 93.51 325 | 98.73 293 | 90.12 340 | 93.98 356 | 99.45 153 | 79.32 350 | 92.28 338 | 94.91 347 | 69.61 352 | 97.98 331 | 87.42 339 | 95.67 271 | 92.45 352 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
Regformer-3 | | | 99.57 6 | 99.53 5 | 99.68 52 | 99.76 44 | 99.29 85 | 99.58 101 | 99.44 162 | 99.01 13 | 99.87 6 | 99.80 66 | 98.97 20 | 99.91 76 | 99.44 16 | 99.92 12 | 99.83 23 |
|
v52 | | | 97.79 222 | 97.50 221 | 98.66 221 | 98.80 281 | 98.62 185 | 99.87 4 | 99.44 162 | 95.87 282 | 99.01 196 | 99.46 210 | 94.44 208 | 99.33 246 | 96.65 256 | 93.96 311 | 98.05 316 |
|
V4 | | | 97.80 220 | 97.51 219 | 98.67 220 | 98.79 283 | 98.63 183 | 99.87 4 | 99.44 162 | 95.87 282 | 99.01 196 | 99.46 210 | 94.52 204 | 99.33 246 | 96.64 257 | 93.97 310 | 98.05 316 |
|
RPSCF | | | 98.22 154 | 98.62 120 | 96.99 310 | 99.82 29 | 91.58 338 | 99.72 41 | 99.44 162 | 96.61 231 | 99.66 49 | 99.89 10 | 95.92 139 | 99.82 139 | 97.46 201 | 99.10 129 | 99.57 115 |
|
Vis-MVSNet (Re-imp) | | | 98.87 101 | 98.72 105 | 99.31 115 | 99.71 81 | 98.88 143 | 99.80 19 | 99.44 162 | 97.91 116 | 99.36 114 | 99.78 80 | 95.49 151 | 99.43 228 | 97.91 156 | 99.11 127 | 99.62 105 |
|
CNLPA | | | 99.14 63 | 98.99 70 | 99.59 70 | 99.58 124 | 99.41 74 | 99.16 251 | 99.44 162 | 98.45 59 | 99.19 166 | 99.49 196 | 98.08 80 | 99.89 97 | 97.73 174 | 99.75 80 | 99.48 135 |
|
DeepPCF-MVS | | 98.18 3 | 98.81 114 | 99.37 17 | 97.12 309 | 99.60 121 | 91.75 337 | 98.61 328 | 99.44 162 | 99.35 1 | 99.83 11 | 99.85 27 | 98.70 51 | 99.81 143 | 99.02 51 | 99.91 17 | 99.81 36 |
|
CLD-MVS | | | 98.16 163 | 98.10 148 | 98.33 249 | 99.29 187 | 96.82 271 | 98.75 320 | 99.44 162 | 97.83 124 | 99.13 173 | 99.55 172 | 92.92 243 | 99.67 194 | 98.32 130 | 97.69 214 | 98.48 299 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
Anonymous20240529 | | | 98.09 171 | 97.68 201 | 99.34 109 | 99.66 104 | 98.44 203 | 99.40 187 | 99.43 170 | 93.67 317 | 99.22 157 | 99.89 10 | 90.23 305 | 99.93 57 | 99.26 30 | 98.33 174 | 99.66 89 |
|
IterMVS-LS | | | 98.46 134 | 98.42 131 | 98.58 225 | 99.59 123 | 98.00 219 | 99.37 196 | 99.43 170 | 96.94 211 | 99.07 187 | 99.59 160 | 97.87 84 | 99.03 294 | 98.32 130 | 95.62 272 | 98.71 222 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
NR-MVSNet | | | 97.97 193 | 97.61 211 | 99.02 153 | 98.87 274 | 99.26 89 | 99.47 156 | 99.42 172 | 97.63 145 | 97.08 303 | 99.50 193 | 95.07 167 | 99.13 283 | 97.86 160 | 93.59 314 | 98.68 237 |
|
FMVSNet2 | | | 97.72 235 | 97.36 245 | 98.80 207 | 99.51 135 | 98.84 148 | 99.45 160 | 99.42 172 | 96.49 238 | 98.86 222 | 99.29 258 | 90.26 302 | 98.98 300 | 96.44 260 | 96.56 253 | 98.58 293 |
|
TEST9 | | | | | | 99.67 94 | 99.65 40 | 99.05 275 | 99.41 174 | 96.22 264 | 98.95 207 | 99.49 196 | 98.77 42 | 99.91 76 | | | |
|
train_agg | | | 99.02 88 | 98.77 101 | 99.77 37 | 99.67 94 | 99.65 40 | 99.05 275 | 99.41 174 | 96.28 257 | 98.95 207 | 99.49 196 | 98.76 44 | 99.91 76 | 97.63 183 | 99.72 86 | 99.75 56 |
|
test_8 | | | | | | 99.67 94 | 99.61 45 | 99.03 281 | 99.41 174 | 96.28 257 | 98.93 210 | 99.48 202 | 98.76 44 | 99.91 76 | | | |
|
agg_prior3 | | | 98.97 96 | 98.71 107 | 99.75 40 | 99.67 94 | 99.60 47 | 99.04 280 | 99.41 174 | 95.93 281 | 98.87 217 | 99.48 202 | 98.61 56 | 99.91 76 | 97.63 183 | 99.72 86 | 99.75 56 |
|
v8 | | | 97.95 198 | 97.63 210 | 98.93 167 | 98.95 254 | 98.81 160 | 99.80 19 | 99.41 174 | 96.03 279 | 99.10 181 | 99.42 217 | 94.92 177 | 99.30 255 | 96.94 234 | 94.08 308 | 98.66 259 |
|
v10 | | | 97.85 209 | 97.52 217 | 98.86 198 | 98.99 241 | 98.67 178 | 99.75 35 | 99.41 174 | 95.70 285 | 98.98 205 | 99.41 220 | 94.75 193 | 99.23 270 | 96.01 268 | 94.63 297 | 98.67 248 |
|
CDPH-MVS | | | 99.13 64 | 98.91 82 | 99.80 31 | 99.75 56 | 99.71 29 | 99.15 254 | 99.41 174 | 96.60 233 | 99.60 62 | 99.55 172 | 98.83 34 | 99.90 89 | 97.48 198 | 99.83 64 | 99.78 50 |
|
agg_prior1 | | | 99.01 91 | 98.76 103 | 99.76 39 | 99.67 94 | 99.62 43 | 98.99 290 | 99.40 181 | 96.26 260 | 98.87 217 | 99.49 196 | 98.77 42 | 99.91 76 | 97.69 180 | 99.72 86 | 99.75 56 |
|
agg_prior | | | | | | 99.67 94 | 99.62 43 | | 99.40 181 | | 98.87 217 | | | 99.91 76 | | | |
|
MCST-MVS | | | 99.43 28 | 99.30 33 | 99.82 26 | 99.79 35 | 99.74 27 | 99.29 220 | 99.40 181 | 98.79 40 | 99.52 82 | 99.62 151 | 98.91 29 | 99.90 89 | 98.64 93 | 99.75 80 | 99.82 32 |
|
TSAR-MVS + MP. | | | 99.58 3 | 99.50 7 | 99.81 29 | 99.91 1 | 99.66 37 | 99.63 81 | 99.39 184 | 98.91 29 | 99.78 22 | 99.85 27 | 99.36 2 | 99.94 42 | 98.84 70 | 99.88 35 | 99.82 32 |
|
MVS | | | 97.28 267 | 96.55 274 | 99.48 91 | 98.78 287 | 98.95 133 | 99.27 225 | 99.39 184 | 83.53 348 | 98.08 281 | 99.54 175 | 96.97 109 | 99.87 106 | 94.23 308 | 99.16 124 | 99.63 103 |
|
VNet | | | 99.11 73 | 98.90 83 | 99.73 47 | 99.52 133 | 99.56 52 | 99.41 180 | 99.39 184 | 99.01 13 | 99.74 31 | 99.78 80 | 95.56 148 | 99.92 66 | 99.52 7 | 98.18 188 | 99.72 72 |
|
HQP3-MVS | | | | | | | | | 99.39 184 | | | | | | | 97.58 220 | |
|
cascas | | | 97.69 239 | 97.43 238 | 98.48 235 | 98.60 309 | 97.30 242 | 98.18 344 | 99.39 184 | 92.96 325 | 98.41 263 | 98.78 303 | 93.77 230 | 99.27 261 | 98.16 137 | 98.61 159 | 98.86 202 |
|
HQP-MVS | | | 98.02 185 | 97.90 167 | 98.37 247 | 99.19 204 | 96.83 269 | 98.98 294 | 99.39 184 | 98.24 72 | 98.66 244 | 99.40 224 | 92.47 266 | 99.64 200 | 97.19 215 | 97.58 220 | 98.64 264 |
|
OPM-MVS | | | 98.19 160 | 98.10 148 | 98.45 239 | 98.88 271 | 97.07 255 | 99.28 222 | 99.38 190 | 98.57 52 | 99.22 157 | 99.81 55 | 92.12 274 | 99.66 196 | 98.08 145 | 97.54 224 | 98.61 282 |
|
EI-MVSNet | | | 98.67 126 | 98.67 111 | 98.68 218 | 99.35 171 | 97.97 221 | 99.50 137 | 99.38 190 | 96.93 212 | 99.20 163 | 99.83 38 | 97.87 84 | 99.36 239 | 98.38 123 | 97.56 222 | 98.71 222 |
|
test20.03 | | | 96.12 295 | 95.96 284 | 96.63 317 | 97.44 329 | 95.45 303 | 99.51 132 | 99.38 190 | 96.55 236 | 96.16 313 | 99.25 263 | 93.76 231 | 96.17 345 | 87.35 341 | 94.22 305 | 98.27 310 |
|
mvs_anonymous | | | 99.03 87 | 98.99 70 | 99.16 139 | 99.38 166 | 98.52 196 | 99.51 132 | 99.38 190 | 97.79 129 | 99.38 109 | 99.81 55 | 97.30 99 | 99.45 219 | 99.35 18 | 98.99 137 | 99.51 129 |
|
casdiffmvs | | | 99.09 77 | 98.97 73 | 99.47 94 | 99.47 146 | 99.10 104 | 99.74 40 | 99.38 190 | 97.86 118 | 99.32 122 | 99.79 74 | 97.08 106 | 99.77 160 | 99.24 31 | 98.82 152 | 99.54 118 |
|
MVSTER | | | 98.49 132 | 98.32 137 | 99.00 156 | 99.35 171 | 99.02 119 | 99.54 123 | 99.38 190 | 97.41 167 | 99.20 163 | 99.73 104 | 93.86 228 | 99.36 239 | 98.87 64 | 97.56 222 | 98.62 273 |
|
FMVSNet3 | | | 98.03 183 | 97.76 193 | 98.84 202 | 99.39 165 | 98.98 125 | 99.40 187 | 99.38 190 | 96.67 227 | 99.07 187 | 99.28 259 | 92.93 242 | 98.98 300 | 97.10 222 | 96.65 250 | 98.56 295 |
|
PAPM_NR | | | 99.04 85 | 98.84 94 | 99.66 55 | 99.74 67 | 99.44 71 | 99.39 189 | 99.38 190 | 97.70 140 | 99.28 133 | 99.28 259 | 98.34 71 | 99.85 116 | 96.96 232 | 99.45 107 | 99.69 81 |
|
HSP-MVS | | | 99.41 33 | 99.26 44 | 99.85 18 | 99.89 8 | 99.80 15 | 99.67 58 | 99.37 198 | 98.70 45 | 99.77 24 | 99.49 196 | 98.21 76 | 99.95 33 | 98.46 118 | 99.77 77 | 99.81 36 |
|
v1240 | | | 97.69 239 | 97.32 253 | 98.79 208 | 98.85 278 | 98.43 204 | 99.48 151 | 99.36 199 | 96.11 274 | 99.27 137 | 99.36 240 | 93.76 231 | 99.24 269 | 94.46 297 | 95.23 278 | 98.70 227 |
|
v2v482 | | | 98.06 174 | 97.77 190 | 98.92 172 | 98.90 267 | 98.82 158 | 99.57 107 | 99.36 199 | 96.65 228 | 99.19 166 | 99.35 244 | 94.20 214 | 99.25 267 | 97.72 178 | 94.97 285 | 98.69 232 |
|
HY-MVS | | 97.30 7 | 98.85 111 | 98.64 115 | 99.47 94 | 99.42 155 | 99.08 107 | 99.62 84 | 99.36 199 | 97.39 169 | 99.28 133 | 99.68 124 | 96.44 126 | 99.92 66 | 98.37 124 | 98.22 184 | 99.40 151 |
|
PAPR | | | 98.63 130 | 98.34 135 | 99.51 88 | 99.40 163 | 99.03 118 | 98.80 315 | 99.36 199 | 96.33 253 | 99.00 203 | 99.12 276 | 98.46 62 | 99.84 122 | 95.23 284 | 99.37 115 | 99.66 89 |
|
v1144 | | | 97.98 190 | 97.69 200 | 98.85 201 | 98.87 274 | 98.66 180 | 99.54 123 | 99.35 203 | 96.27 259 | 99.23 155 | 99.35 244 | 94.67 197 | 99.23 270 | 96.73 249 | 95.16 280 | 98.68 237 |
|
v1141 | | | 98.05 180 | 97.76 193 | 98.91 176 | 98.91 266 | 98.78 169 | 99.57 107 | 99.35 203 | 96.41 250 | 99.23 155 | 99.36 240 | 94.93 176 | 99.27 261 | 97.38 206 | 94.72 292 | 98.68 237 |
|
v1neww | | | 98.12 167 | 97.84 179 | 98.93 167 | 98.97 249 | 98.81 160 | 99.66 67 | 99.35 203 | 96.49 238 | 99.29 129 | 99.37 233 | 95.02 169 | 99.32 249 | 97.73 174 | 94.73 290 | 98.67 248 |
|
v7new | | | 98.12 167 | 97.84 179 | 98.93 167 | 98.97 249 | 98.81 160 | 99.66 67 | 99.35 203 | 96.49 238 | 99.29 129 | 99.37 233 | 95.02 169 | 99.32 249 | 97.73 174 | 94.73 290 | 98.67 248 |
|
divwei89l23v2f112 | | | 98.06 174 | 97.78 186 | 98.91 176 | 98.90 267 | 98.77 170 | 99.57 107 | 99.35 203 | 96.45 245 | 99.24 150 | 99.37 233 | 94.92 177 | 99.27 261 | 97.50 196 | 94.71 294 | 98.68 237 |
|
v1 | | | 98.05 180 | 97.76 193 | 98.93 167 | 98.92 264 | 98.80 165 | 99.57 107 | 99.35 203 | 96.39 252 | 99.28 133 | 99.36 240 | 94.86 182 | 99.32 249 | 97.38 206 | 94.72 292 | 98.68 237 |
|
WR-MVS | | | 98.06 174 | 97.73 197 | 99.06 149 | 98.86 277 | 99.25 90 | 99.19 248 | 99.35 203 | 97.30 175 | 98.66 244 | 99.43 215 | 93.94 224 | 99.21 277 | 98.58 102 | 94.28 303 | 98.71 222 |
|
test11 | | | | | | | | | 99.35 203 | | | | | | | | |
|
v144192 | | | 97.92 202 | 97.60 212 | 98.87 194 | 98.83 280 | 98.65 181 | 99.55 120 | 99.34 211 | 96.20 265 | 99.32 122 | 99.40 224 | 94.36 209 | 99.26 266 | 96.37 263 | 95.03 284 | 98.70 227 |
|
v1921920 | | | 97.80 220 | 97.45 229 | 98.84 202 | 98.80 281 | 98.53 192 | 99.52 128 | 99.34 211 | 96.15 271 | 99.24 150 | 99.47 206 | 93.98 223 | 99.29 257 | 95.40 281 | 95.13 282 | 98.69 232 |
|
v1192 | | | 97.81 217 | 97.44 235 | 98.91 176 | 98.88 271 | 98.68 177 | 99.51 132 | 99.34 211 | 96.18 267 | 99.20 163 | 99.34 247 | 94.03 222 | 99.36 239 | 95.32 283 | 95.18 279 | 98.69 232 |
|
v7 | | | 98.05 180 | 97.78 186 | 98.87 194 | 98.99 241 | 98.67 178 | 99.64 79 | 99.34 211 | 96.31 256 | 99.29 129 | 99.51 190 | 94.78 187 | 99.27 261 | 97.03 226 | 95.15 281 | 98.66 259 |
|
v6 | | | 98.12 167 | 97.84 179 | 98.94 164 | 98.94 257 | 98.83 151 | 99.66 67 | 99.34 211 | 96.49 238 | 99.30 125 | 99.37 233 | 94.95 173 | 99.34 245 | 97.77 169 | 94.74 289 | 98.67 248 |
|
V42 | | | 98.06 174 | 97.79 184 | 98.86 198 | 98.98 245 | 98.84 148 | 99.69 47 | 99.34 211 | 96.53 237 | 99.30 125 | 99.37 233 | 94.67 197 | 99.32 249 | 97.57 188 | 94.66 295 | 98.42 303 |
|
MVS_Test | | | 99.10 76 | 98.97 73 | 99.48 91 | 99.49 142 | 99.14 101 | 99.67 58 | 99.34 211 | 97.31 174 | 99.58 66 | 99.76 90 | 97.65 91 | 99.82 139 | 98.87 64 | 99.07 132 | 99.46 142 |
|
MG-MVS | | | 99.13 64 | 99.02 68 | 99.45 98 | 99.57 126 | 98.63 183 | 99.07 269 | 99.34 211 | 98.99 18 | 99.61 59 | 99.82 45 | 97.98 83 | 99.87 106 | 97.00 228 | 99.80 71 | 99.85 8 |
|
v148 | | | 97.79 222 | 97.55 214 | 98.50 232 | 98.74 292 | 97.72 239 | 99.54 123 | 99.33 219 | 96.26 260 | 98.90 214 | 99.51 190 | 94.68 196 | 99.14 280 | 97.83 162 | 93.15 319 | 98.63 271 |
|
MDA-MVSNet-bldmvs | | | 94.96 307 | 93.98 312 | 97.92 283 | 98.24 320 | 97.27 244 | 99.15 254 | 99.33 219 | 93.80 316 | 80.09 353 | 99.03 283 | 88.31 326 | 97.86 334 | 93.49 316 | 94.36 302 | 98.62 273 |
|
TSAR-MVS + GP. | | | 99.36 39 | 99.36 19 | 99.36 107 | 99.67 94 | 98.61 188 | 99.07 269 | 99.33 219 | 99.00 17 | 99.82 14 | 99.81 55 | 99.06 9 | 99.84 122 | 99.09 45 | 99.42 109 | 99.65 93 |
|
CR-MVSNet | | | 98.17 161 | 97.93 166 | 98.87 194 | 99.18 207 | 98.49 199 | 99.22 242 | 99.33 219 | 96.96 209 | 99.56 70 | 99.38 229 | 94.33 210 | 99.00 298 | 94.83 291 | 98.58 162 | 99.14 165 |
|
Patchmtry | | | 97.75 230 | 97.40 241 | 98.81 205 | 99.10 225 | 98.87 144 | 99.11 264 | 99.33 219 | 94.83 293 | 98.81 225 | 99.38 229 | 94.33 210 | 99.02 295 | 96.10 265 | 95.57 273 | 98.53 296 |
|
EPP-MVSNet | | | 99.13 64 | 98.99 70 | 99.53 82 | 99.65 107 | 99.06 109 | 99.81 15 | 99.33 219 | 97.43 163 | 99.60 62 | 99.88 15 | 97.14 103 | 99.84 122 | 99.13 42 | 98.94 141 | 99.69 81 |
|
MS-PatchMatch | | | 97.24 269 | 97.32 253 | 96.99 310 | 98.45 316 | 93.51 330 | 98.82 314 | 99.32 225 | 97.41 167 | 98.13 279 | 99.30 256 | 88.99 315 | 99.56 211 | 95.68 275 | 99.80 71 | 97.90 326 |
|
tpm cat1 | | | 97.39 264 | 97.36 245 | 97.50 304 | 99.17 212 | 93.73 325 | 99.43 169 | 99.31 226 | 91.27 334 | 98.71 235 | 99.08 277 | 94.31 212 | 99.77 160 | 96.41 262 | 98.50 168 | 99.00 183 |
|
PMMVS | | | 98.80 117 | 98.62 120 | 99.34 109 | 99.27 192 | 98.70 176 | 98.76 319 | 99.31 226 | 97.34 171 | 99.21 160 | 99.07 278 | 97.20 102 | 99.82 139 | 98.56 107 | 98.87 149 | 99.52 124 |
|
our_test_3 | | | 97.65 246 | 97.68 201 | 97.55 301 | 98.62 306 | 94.97 313 | 98.84 313 | 99.30 228 | 96.83 219 | 98.19 276 | 99.34 247 | 97.01 108 | 99.02 295 | 95.00 288 | 96.01 264 | 98.64 264 |
|
Effi-MVS+-dtu | | | 98.78 118 | 98.89 85 | 98.47 237 | 99.33 175 | 96.91 268 | 99.57 107 | 99.30 228 | 98.47 57 | 99.41 102 | 98.99 285 | 96.78 114 | 99.74 166 | 98.73 83 | 99.38 111 | 98.74 218 |
|
CANet_DTU | | | 98.97 96 | 98.87 87 | 99.25 129 | 99.33 175 | 98.42 206 | 99.08 268 | 99.30 228 | 99.16 5 | 99.43 97 | 99.75 95 | 95.27 157 | 99.97 11 | 98.56 107 | 99.95 6 | 99.36 153 |
|
mvs-test1 | | | 98.86 104 | 98.84 94 | 98.89 183 | 99.33 175 | 97.77 236 | 99.44 164 | 99.30 228 | 98.47 57 | 99.10 181 | 99.43 215 | 96.78 114 | 99.95 33 | 98.73 83 | 99.02 135 | 98.96 193 |
|
VDDNet | | | 97.55 250 | 97.02 266 | 99.16 139 | 99.49 142 | 98.12 217 | 99.38 194 | 99.30 228 | 95.35 288 | 99.68 38 | 99.90 7 | 82.62 348 | 99.93 57 | 99.31 25 | 98.13 196 | 99.42 149 |
|
v15 | | | 96.28 286 | 95.62 292 | 98.25 260 | 98.94 257 | 98.83 151 | 99.76 28 | 99.29 233 | 94.52 303 | 94.02 327 | 97.61 333 | 95.02 169 | 98.13 324 | 94.53 295 | 86.92 342 | 97.80 329 |
|
v13 | | | 96.24 289 | 95.58 294 | 98.25 260 | 98.98 245 | 98.83 151 | 99.75 35 | 99.29 233 | 94.35 308 | 93.89 332 | 97.60 334 | 95.17 164 | 98.11 326 | 94.27 307 | 86.86 345 | 97.81 327 |
|
v12 | | | 96.24 289 | 95.58 294 | 98.23 263 | 98.96 252 | 98.81 160 | 99.76 28 | 99.29 233 | 94.42 307 | 93.85 333 | 97.60 334 | 95.12 165 | 98.09 327 | 94.32 304 | 86.85 346 | 97.80 329 |
|
v11 | | | 96.23 291 | 95.57 297 | 98.21 266 | 98.93 262 | 98.83 151 | 99.72 41 | 99.29 233 | 94.29 309 | 94.05 326 | 97.64 331 | 94.88 181 | 98.04 328 | 92.89 323 | 88.43 335 | 97.77 335 |
|
V14 | | | 96.26 287 | 95.60 293 | 98.26 256 | 98.94 257 | 98.83 151 | 99.76 28 | 99.29 233 | 94.49 304 | 93.96 329 | 97.66 330 | 94.99 172 | 98.13 324 | 94.41 298 | 86.90 343 | 97.80 329 |
|
V9 | | | 96.25 288 | 95.58 294 | 98.26 256 | 98.94 257 | 98.83 151 | 99.75 35 | 99.29 233 | 94.45 306 | 93.96 329 | 97.62 332 | 94.94 174 | 98.14 323 | 94.40 299 | 86.87 344 | 97.81 327 |
|
test12 | | | | | 99.75 40 | 99.64 108 | 99.61 45 | | 99.29 233 | | 99.21 160 | | 98.38 68 | 99.89 97 | | 99.74 82 | 99.74 61 |
|
new-patchmatchnet | | | 94.48 310 | 94.08 311 | 95.67 322 | 95.08 342 | 92.41 334 | 99.18 249 | 99.28 240 | 94.55 302 | 93.49 335 | 97.37 340 | 87.86 330 | 97.01 341 | 91.57 328 | 88.36 336 | 97.61 337 |
|
testing_2 | | | 94.44 311 | 92.93 317 | 98.98 158 | 94.16 344 | 99.00 123 | 99.42 176 | 99.28 240 | 96.60 233 | 84.86 347 | 96.84 342 | 70.91 351 | 99.27 261 | 98.23 133 | 96.08 263 | 98.68 237 |
|
v18 | | | 96.42 282 | 95.80 289 | 98.26 256 | 98.95 254 | 98.82 158 | 99.76 28 | 99.28 240 | 94.58 298 | 94.12 323 | 97.70 327 | 95.22 162 | 98.16 320 | 94.83 291 | 87.80 337 | 97.79 334 |
|
v17 | | | 96.42 282 | 95.81 287 | 98.25 260 | 98.94 257 | 98.80 165 | 99.76 28 | 99.28 240 | 94.57 299 | 94.18 322 | 97.71 326 | 95.23 161 | 98.16 320 | 94.86 289 | 87.73 339 | 97.80 329 |
|
v16 | | | 96.39 284 | 95.76 290 | 98.26 256 | 98.96 252 | 98.81 160 | 99.76 28 | 99.28 240 | 94.57 299 | 94.10 324 | 97.70 327 | 95.04 168 | 98.16 320 | 94.70 293 | 87.77 338 | 97.80 329 |
|
Test4 | | | 95.05 306 | 93.67 314 | 99.22 135 | 96.07 337 | 98.94 136 | 99.20 247 | 99.27 245 | 97.71 138 | 89.96 345 | 97.59 336 | 66.18 354 | 99.25 267 | 98.06 148 | 98.96 140 | 99.47 139 |
|
jason | | | 99.13 64 | 99.03 65 | 99.45 98 | 99.46 148 | 98.87 144 | 99.12 258 | 99.26 246 | 98.03 102 | 99.79 18 | 99.65 135 | 97.02 107 | 99.85 116 | 99.02 51 | 99.90 24 | 99.65 93 |
jason: jason. |
test_0402 | | | 96.64 276 | 96.24 277 | 97.85 288 | 98.85 278 | 96.43 283 | 99.44 164 | 99.26 246 | 93.52 320 | 96.98 306 | 99.52 187 | 88.52 323 | 99.20 278 | 92.58 327 | 97.50 227 | 97.93 324 |
|
PCF-MVS | | 97.08 14 | 97.66 245 | 97.06 265 | 99.47 94 | 99.61 119 | 99.09 106 | 98.04 346 | 99.25 248 | 91.24 335 | 98.51 258 | 99.70 113 | 94.55 202 | 99.91 76 | 92.76 325 | 99.85 53 | 99.42 149 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
MDA-MVSNet_test_wron | | | 95.45 302 | 94.60 307 | 98.01 277 | 98.16 321 | 97.21 249 | 99.11 264 | 99.24 249 | 93.49 321 | 80.73 352 | 98.98 288 | 93.02 240 | 98.18 318 | 94.22 309 | 94.45 300 | 98.64 264 |
|
YYNet1 | | | 95.36 304 | 94.51 309 | 97.92 283 | 97.89 323 | 97.10 251 | 99.10 266 | 99.23 250 | 93.26 324 | 80.77 351 | 99.04 282 | 92.81 246 | 98.02 329 | 94.30 305 | 94.18 306 | 98.64 264 |
|
DeepMVS_CX | | | | | 93.34 326 | 99.29 187 | 82.27 351 | | 99.22 251 | 85.15 346 | 96.33 311 | 99.05 281 | 90.97 297 | 99.73 173 | 93.57 314 | 97.77 213 | 98.01 320 |
|
pmmvs4 | | | 98.13 165 | 97.90 167 | 98.81 205 | 98.61 308 | 98.87 144 | 98.99 290 | 99.21 252 | 96.44 246 | 99.06 191 | 99.58 163 | 95.90 140 | 99.11 286 | 97.18 217 | 96.11 262 | 98.46 302 |
|
tpmvs | | | 97.98 190 | 98.02 156 | 97.84 289 | 99.04 235 | 94.73 317 | 99.31 214 | 99.20 253 | 96.10 278 | 98.76 231 | 99.42 217 | 94.94 174 | 99.81 143 | 96.97 231 | 98.45 170 | 98.97 187 |
|
new_pmnet | | | 96.38 285 | 96.03 281 | 97.41 305 | 98.13 322 | 95.16 311 | 99.05 275 | 99.20 253 | 93.94 314 | 97.39 298 | 98.79 301 | 91.61 291 | 99.04 292 | 90.43 332 | 95.77 269 | 98.05 316 |
|
IS-MVSNet | | | 99.05 84 | 98.87 87 | 99.57 74 | 99.73 72 | 99.32 81 | 99.75 35 | 99.20 253 | 98.02 103 | 99.56 70 | 99.86 23 | 96.54 122 | 99.67 194 | 98.09 141 | 99.13 126 | 99.73 66 |
|
tpmp4_e23 | | | 97.34 265 | 97.29 256 | 97.52 302 | 99.25 196 | 93.73 325 | 99.58 101 | 99.19 256 | 94.00 313 | 98.20 275 | 99.41 220 | 90.74 299 | 99.74 166 | 97.13 221 | 98.07 205 | 99.07 177 |
|
lupinMVS | | | 99.13 64 | 99.01 69 | 99.46 97 | 99.51 135 | 98.94 136 | 99.05 275 | 99.16 257 | 97.86 118 | 99.80 16 | 99.56 169 | 97.39 95 | 99.86 110 | 98.94 57 | 99.85 53 | 99.58 114 |
|
GA-MVS | | | 97.85 209 | 97.47 226 | 99.00 156 | 99.38 166 | 97.99 220 | 98.57 330 | 99.15 258 | 97.04 205 | 98.90 214 | 99.30 256 | 89.83 308 | 99.38 231 | 96.70 251 | 98.33 174 | 99.62 105 |
|
ADS-MVSNet | | | 98.20 159 | 98.08 151 | 98.56 228 | 99.33 175 | 96.48 281 | 99.23 238 | 99.15 258 | 96.24 262 | 99.10 181 | 99.67 129 | 94.11 219 | 99.71 183 | 96.81 245 | 99.05 133 | 99.48 135 |
|
Patchmatch-test | | | 97.93 199 | 97.65 208 | 98.77 211 | 99.18 207 | 97.07 255 | 99.03 281 | 99.14 260 | 96.16 269 | 98.74 232 | 99.57 167 | 94.56 201 | 99.72 177 | 93.36 317 | 99.11 127 | 99.52 124 |
|
BH-untuned | | | 98.42 137 | 98.36 133 | 98.59 224 | 99.49 142 | 96.70 274 | 99.27 225 | 99.13 261 | 97.24 181 | 98.80 227 | 99.38 229 | 95.75 145 | 99.74 166 | 97.07 225 | 99.16 124 | 99.33 156 |
|
tpmrst | | | 98.33 142 | 98.48 129 | 97.90 285 | 99.16 214 | 94.78 315 | 99.31 214 | 99.11 262 | 97.27 177 | 99.45 93 | 99.59 160 | 95.33 154 | 99.84 122 | 98.48 115 | 98.61 159 | 99.09 172 |
|
pmmvs-eth3d | | | 95.34 305 | 94.73 306 | 97.15 307 | 95.53 340 | 95.94 293 | 99.35 206 | 99.10 263 | 95.13 289 | 93.55 334 | 97.54 337 | 88.15 329 | 97.91 332 | 94.58 294 | 89.69 333 | 97.61 337 |
|
PAPM | | | 97.59 249 | 97.09 264 | 99.07 148 | 99.06 231 | 98.26 210 | 98.30 340 | 99.10 263 | 94.88 292 | 98.08 281 | 99.34 247 | 96.27 131 | 99.64 200 | 89.87 333 | 98.92 144 | 99.31 157 |
|
Anonymous20231206 | | | 96.22 292 | 96.03 281 | 96.79 316 | 97.31 333 | 94.14 322 | 99.63 81 | 99.08 265 | 96.17 268 | 97.04 304 | 99.06 280 | 93.94 224 | 97.76 336 | 86.96 342 | 95.06 283 | 98.47 300 |
|
ADS-MVSNet2 | | | 98.02 185 | 98.07 153 | 97.87 286 | 99.33 175 | 95.19 309 | 99.23 238 | 99.08 265 | 96.24 262 | 99.10 181 | 99.67 129 | 94.11 219 | 98.93 309 | 96.81 245 | 99.05 133 | 99.48 135 |
|
RPMNet | | | 96.61 277 | 95.85 285 | 98.87 194 | 99.18 207 | 98.49 199 | 99.22 242 | 99.08 265 | 88.72 344 | 99.56 70 | 97.38 339 | 94.08 221 | 99.00 298 | 86.87 343 | 98.58 162 | 99.14 165 |
|
0601test | | | 98.86 104 | 98.63 116 | 99.54 77 | 99.49 142 | 99.18 96 | 99.50 137 | 99.07 268 | 98.22 76 | 99.61 59 | 99.51 190 | 95.37 153 | 99.84 122 | 98.60 100 | 98.33 174 | 99.59 111 |
|
PatchT | | | 97.03 274 | 96.44 275 | 98.79 208 | 98.99 241 | 98.34 207 | 99.16 251 | 99.07 268 | 92.13 329 | 99.52 82 | 97.31 341 | 94.54 203 | 98.98 300 | 88.54 336 | 98.73 158 | 99.03 180 |
|
test2356 | | | 94.07 315 | 94.46 310 | 92.89 328 | 95.18 341 | 86.13 344 | 97.60 350 | 99.06 270 | 93.61 319 | 96.15 315 | 98.28 319 | 85.60 339 | 93.95 351 | 86.68 344 | 98.00 207 | 98.59 290 |
|
LP | | | 97.04 273 | 96.80 269 | 97.77 294 | 98.90 267 | 95.23 307 | 98.97 297 | 99.06 270 | 94.02 312 | 98.09 280 | 99.41 220 | 93.88 226 | 98.82 311 | 90.46 331 | 98.42 172 | 99.26 160 |
|
USDC | | | 97.34 265 | 97.20 261 | 97.75 295 | 99.07 229 | 95.20 308 | 98.51 333 | 99.04 272 | 97.99 108 | 98.31 270 | 99.86 23 | 89.02 314 | 99.55 213 | 95.67 276 | 97.36 239 | 98.49 298 |
|
testus | | | 94.61 309 | 95.30 302 | 92.54 330 | 96.44 336 | 84.18 346 | 98.36 336 | 99.03 273 | 94.18 310 | 96.49 309 | 98.57 313 | 88.74 317 | 95.09 349 | 87.41 340 | 98.45 170 | 98.36 309 |
|
CostFormer | | | 97.72 235 | 97.73 197 | 97.71 297 | 99.15 217 | 94.02 323 | 99.54 123 | 99.02 274 | 94.67 296 | 99.04 193 | 99.35 244 | 92.35 272 | 99.77 160 | 98.50 114 | 97.94 209 | 99.34 155 |
|
OurMVSNet-221017-0 | | | 97.88 205 | 97.77 190 | 98.19 268 | 98.71 297 | 96.53 279 | 99.88 1 | 99.00 275 | 97.79 129 | 98.78 229 | 99.94 3 | 91.68 287 | 99.35 242 | 97.21 213 | 96.99 248 | 98.69 232 |
|
LCM-MVSNet | | | 86.80 324 | 85.22 327 | 91.53 335 | 87.81 355 | 80.96 352 | 98.23 343 | 98.99 276 | 71.05 353 | 90.13 344 | 96.51 344 | 48.45 361 | 96.88 342 | 90.51 330 | 85.30 348 | 96.76 341 |
|
MIMVSNet | | | 97.73 233 | 97.45 229 | 98.57 226 | 99.45 152 | 97.50 241 | 99.02 284 | 98.98 277 | 96.11 274 | 99.41 102 | 99.14 272 | 90.28 301 | 98.74 313 | 95.74 272 | 98.93 142 | 99.47 139 |
|
Patchmatch-test1 | | | 98.16 163 | 98.14 145 | 98.22 265 | 99.30 184 | 95.55 298 | 99.07 269 | 98.97 278 | 97.57 149 | 99.43 97 | 99.60 158 | 92.72 250 | 99.60 208 | 97.38 206 | 99.20 122 | 99.50 132 |
|
JIA-IIPM | | | 97.50 257 | 97.02 266 | 98.93 167 | 98.73 293 | 97.80 235 | 99.30 216 | 98.97 278 | 91.73 333 | 98.91 212 | 94.86 348 | 95.10 166 | 99.71 183 | 97.58 186 | 97.98 208 | 99.28 159 |
|
alignmvs | | | 98.81 114 | 98.56 127 | 99.58 73 | 99.43 154 | 99.42 73 | 99.51 132 | 98.96 280 | 98.61 50 | 99.35 117 | 98.92 291 | 94.78 187 | 99.77 160 | 99.35 18 | 98.11 204 | 99.54 118 |
|
tpm2 | | | 97.44 262 | 97.34 250 | 97.74 296 | 99.15 217 | 94.36 320 | 99.45 160 | 98.94 281 | 93.45 323 | 98.90 214 | 99.44 214 | 91.35 293 | 99.59 210 | 97.31 209 | 98.07 205 | 99.29 158 |
|
PatchFormer-LS_test | | | 98.01 188 | 98.05 154 | 97.87 286 | 99.15 217 | 94.76 316 | 99.42 176 | 98.93 282 | 97.12 191 | 98.84 223 | 98.59 312 | 93.74 233 | 99.80 147 | 98.55 110 | 98.17 194 | 99.06 178 |
|
EG-PatchMatch MVS | | | 95.97 297 | 95.69 291 | 96.81 315 | 97.78 325 | 92.79 333 | 99.16 251 | 98.93 282 | 96.16 269 | 94.08 325 | 99.22 267 | 82.72 347 | 99.47 217 | 95.67 276 | 97.50 227 | 98.17 313 |
|
PatchmatchNet | | | 98.31 144 | 98.36 133 | 98.19 268 | 99.16 214 | 95.32 305 | 99.27 225 | 98.92 284 | 97.37 170 | 99.37 111 | 99.58 163 | 94.90 179 | 99.70 189 | 97.43 204 | 99.21 121 | 99.54 118 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
ITE_SJBPF | | | | | 98.08 272 | 99.29 187 | 96.37 284 | | 98.92 284 | 98.34 66 | 98.83 224 | 99.75 95 | 91.09 295 | 99.62 206 | 95.82 270 | 97.40 236 | 98.25 312 |
|
FPMVS | | | 84.93 325 | 85.65 325 | 82.75 345 | 86.77 357 | 63.39 363 | 98.35 338 | 98.92 284 | 74.11 352 | 83.39 349 | 98.98 288 | 50.85 359 | 92.40 356 | 84.54 346 | 94.97 285 | 92.46 351 |
|
TransMVSNet (Re) | | | 97.15 270 | 96.58 273 | 98.86 198 | 99.12 220 | 98.85 147 | 99.49 146 | 98.91 287 | 95.48 287 | 97.16 302 | 99.80 66 | 93.38 235 | 99.11 286 | 94.16 310 | 91.73 327 | 98.62 273 |
|
EPNet | | | 98.86 104 | 98.71 107 | 99.30 118 | 97.20 335 | 98.18 212 | 99.62 84 | 98.91 287 | 99.28 2 | 98.63 252 | 99.81 55 | 95.96 135 | 99.99 1 | 99.24 31 | 99.72 86 | 99.73 66 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
pmmvs5 | | | 97.52 253 | 97.30 255 | 98.16 270 | 98.57 311 | 96.73 273 | 99.27 225 | 98.90 289 | 96.14 272 | 98.37 266 | 99.53 182 | 91.54 292 | 99.14 280 | 97.51 195 | 95.87 267 | 98.63 271 |
|
BH-w/o | | | 98.00 189 | 97.89 171 | 98.32 250 | 99.35 171 | 96.20 290 | 99.01 288 | 98.90 289 | 96.42 248 | 98.38 265 | 99.00 284 | 95.26 159 | 99.72 177 | 96.06 266 | 98.61 159 | 99.03 180 |
|
MTMP | | | | | | | | 99.54 123 | 98.88 291 | | | | | | | | |
|
dp | | | 97.75 230 | 97.80 183 | 97.59 300 | 99.10 225 | 93.71 327 | 99.32 211 | 98.88 291 | 96.48 244 | 99.08 186 | 99.55 172 | 92.67 260 | 99.82 139 | 96.52 258 | 98.58 162 | 99.24 161 |
|
MVP-Stereo | | | 97.81 217 | 97.75 196 | 97.99 279 | 97.53 328 | 96.60 278 | 98.96 299 | 98.85 293 | 97.22 183 | 97.23 300 | 99.36 240 | 95.28 156 | 99.46 218 | 95.51 278 | 99.78 75 | 97.92 325 |
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
VDD-MVS | | | 97.73 233 | 97.35 247 | 98.88 190 | 99.47 146 | 97.12 250 | 99.34 209 | 98.85 293 | 98.19 77 | 99.67 44 | 99.85 27 | 82.98 346 | 99.92 66 | 99.49 12 | 98.32 177 | 99.60 107 |
|
Baseline_NR-MVSNet | | | 97.76 226 | 97.45 229 | 98.68 218 | 99.09 227 | 98.29 208 | 99.41 180 | 98.85 293 | 95.65 286 | 98.63 252 | 99.67 129 | 94.82 184 | 99.10 288 | 98.07 147 | 92.89 321 | 98.64 264 |
|
LF4IMVS | | | 97.52 253 | 97.46 228 | 97.70 298 | 98.98 245 | 95.55 298 | 99.29 220 | 98.82 296 | 98.07 94 | 98.66 244 | 99.64 142 | 89.97 307 | 99.61 207 | 97.01 227 | 96.68 249 | 97.94 323 |
|
view600 | | | 97.97 193 | 97.66 203 | 98.89 183 | 99.75 56 | 97.81 231 | 99.69 47 | 98.80 297 | 98.02 103 | 99.25 145 | 98.88 292 | 91.95 275 | 99.89 97 | 94.36 300 | 98.29 178 | 98.96 193 |
|
view800 | | | 97.97 193 | 97.66 203 | 98.89 183 | 99.75 56 | 97.81 231 | 99.69 47 | 98.80 297 | 98.02 103 | 99.25 145 | 98.88 292 | 91.95 275 | 99.89 97 | 94.36 300 | 98.29 178 | 98.96 193 |
|
conf0.05thres1000 | | | 97.97 193 | 97.66 203 | 98.89 183 | 99.75 56 | 97.81 231 | 99.69 47 | 98.80 297 | 98.02 103 | 99.25 145 | 98.88 292 | 91.95 275 | 99.89 97 | 94.36 300 | 98.29 178 | 98.96 193 |
|
tfpn | | | 97.97 193 | 97.66 203 | 98.89 183 | 99.75 56 | 97.81 231 | 99.69 47 | 98.80 297 | 98.02 103 | 99.25 145 | 98.88 292 | 91.95 275 | 99.89 97 | 94.36 300 | 98.29 178 | 98.96 193 |
|
BH-RMVSNet | | | 98.41 138 | 98.08 151 | 99.40 105 | 99.41 158 | 98.83 151 | 99.30 216 | 98.77 301 | 97.70 140 | 98.94 209 | 99.65 135 | 92.91 245 | 99.74 166 | 96.52 258 | 99.55 105 | 99.64 99 |
|
EPNet_dtu | | | 98.03 183 | 97.96 163 | 98.23 263 | 98.27 319 | 95.54 300 | 99.23 238 | 98.75 302 | 99.02 10 | 97.82 292 | 99.71 110 | 96.11 134 | 99.48 216 | 93.04 322 | 99.65 100 | 99.69 81 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
TDRefinement | | | 95.42 303 | 94.57 308 | 97.97 280 | 89.83 353 | 96.11 291 | 99.48 151 | 98.75 302 | 96.74 222 | 96.68 308 | 99.88 15 | 88.65 321 | 99.71 183 | 98.37 124 | 82.74 349 | 98.09 314 |
|
OpenMVS_ROB | | 92.34 20 | 94.38 312 | 93.70 313 | 96.41 320 | 97.38 330 | 93.17 331 | 99.06 273 | 98.75 302 | 86.58 345 | 94.84 321 | 98.26 320 | 81.53 349 | 99.32 249 | 89.01 335 | 97.87 211 | 96.76 341 |
|
tfpn111 | | | 97.81 217 | 97.49 223 | 98.78 210 | 99.72 75 | 97.86 227 | 99.59 94 | 98.74 305 | 97.93 113 | 99.26 141 | 98.62 307 | 91.75 282 | 99.86 110 | 93.57 314 | 98.18 188 | 98.61 282 |
|
conf200view11 | | | 97.78 224 | 97.45 229 | 98.77 211 | 99.72 75 | 97.86 227 | 99.59 94 | 98.74 305 | 97.93 113 | 99.26 141 | 98.62 307 | 91.75 282 | 99.83 130 | 93.22 318 | 98.18 188 | 98.61 282 |
|
thres100view900 | | | 97.76 226 | 97.45 229 | 98.69 217 | 99.72 75 | 97.86 227 | 99.59 94 | 98.74 305 | 97.93 113 | 99.26 141 | 98.62 307 | 91.75 282 | 99.83 130 | 93.22 318 | 98.18 188 | 98.37 307 |
|
thres600view7 | | | 97.86 208 | 97.51 219 | 98.92 172 | 99.72 75 | 97.95 224 | 99.59 94 | 98.74 305 | 97.94 112 | 99.27 137 | 98.62 307 | 91.75 282 | 99.86 110 | 93.73 313 | 98.19 187 | 98.96 193 |
|
1111 | | | 92.30 319 | 92.21 320 | 92.55 329 | 93.30 345 | 86.27 342 | 99.15 254 | 98.74 305 | 91.94 330 | 90.85 342 | 97.82 324 | 84.18 343 | 95.21 347 | 79.65 350 | 94.27 304 | 96.19 344 |
|
.test1245 | | | 83.42 326 | 86.17 324 | 75.15 348 | 93.30 345 | 86.27 342 | 99.15 254 | 98.74 305 | 91.94 330 | 90.85 342 | 97.82 324 | 84.18 343 | 95.21 347 | 79.65 350 | 39.90 360 | 43.98 361 |
|
thres200 | | | 97.61 248 | 97.28 257 | 98.62 222 | 99.64 108 | 98.03 218 | 99.26 233 | 98.74 305 | 97.68 142 | 99.09 185 | 98.32 318 | 91.66 290 | 99.81 143 | 92.88 324 | 98.22 184 | 98.03 319 |
|
MDTV_nov1_ep13 | | | | 98.32 137 | | 99.11 222 | 94.44 319 | 99.27 225 | 98.74 305 | 97.51 155 | 99.40 106 | 99.62 151 | 94.78 187 | 99.76 164 | 97.59 185 | 98.81 155 | |
|
TinyColmap | | | 97.12 271 | 96.89 268 | 97.83 290 | 99.07 229 | 95.52 301 | 98.57 330 | 98.74 305 | 97.58 148 | 97.81 293 | 99.79 74 | 88.16 328 | 99.56 211 | 95.10 285 | 97.21 243 | 98.39 306 |
|
tfpn200view9 | | | 97.72 235 | 97.38 243 | 98.72 215 | 99.69 90 | 97.96 222 | 99.50 137 | 98.73 314 | 97.83 124 | 99.17 170 | 98.45 316 | 91.67 288 | 99.83 130 | 93.22 318 | 98.18 188 | 98.37 307 |
|
ambc | | | | | 93.06 327 | 92.68 348 | 82.36 350 | 98.47 334 | 98.73 314 | | 95.09 319 | 97.41 338 | 55.55 358 | 99.10 288 | 96.42 261 | 91.32 328 | 97.71 336 |
|
thres400 | | | 97.77 225 | 97.38 243 | 98.92 172 | 99.69 90 | 97.96 222 | 99.50 137 | 98.73 314 | 97.83 124 | 99.17 170 | 98.45 316 | 91.67 288 | 99.83 130 | 93.22 318 | 98.18 188 | 98.96 193 |
|
SixPastTwentyTwo | | | 97.50 257 | 97.33 252 | 98.03 274 | 98.65 303 | 96.23 289 | 99.77 25 | 98.68 317 | 97.14 188 | 97.90 289 | 99.93 4 | 90.45 300 | 99.18 279 | 97.00 228 | 96.43 256 | 98.67 248 |
|
test_normal | | | 97.44 262 | 96.77 272 | 99.44 101 | 97.75 327 | 99.00 123 | 99.10 266 | 98.64 318 | 97.71 138 | 93.93 331 | 98.82 299 | 87.39 332 | 99.83 130 | 98.61 98 | 98.97 139 | 99.49 133 |
|
test0.0.03 1 | | | 97.71 238 | 97.42 239 | 98.56 228 | 98.41 317 | 97.82 230 | 98.78 317 | 98.63 319 | 97.34 171 | 98.05 285 | 98.98 288 | 94.45 206 | 98.98 300 | 95.04 287 | 97.15 246 | 98.89 201 |
|
DWT-MVSNet_test | | | 97.53 252 | 97.40 241 | 97.93 282 | 99.03 237 | 94.86 314 | 99.57 107 | 98.63 319 | 96.59 235 | 98.36 267 | 98.79 301 | 89.32 312 | 99.74 166 | 98.14 139 | 98.16 195 | 99.20 163 |
|
DI_MVS_plusplus_test | | | 97.45 261 | 96.79 270 | 99.44 101 | 97.76 326 | 99.04 111 | 99.21 245 | 98.61 321 | 97.74 135 | 94.01 328 | 98.83 298 | 87.38 333 | 99.83 130 | 98.63 94 | 98.90 146 | 99.44 146 |
|
test1235678 | | | 92.91 318 | 93.30 315 | 91.71 334 | 93.14 347 | 83.01 348 | 98.75 320 | 98.58 322 | 92.80 327 | 92.45 337 | 97.91 323 | 88.51 324 | 93.54 352 | 82.26 348 | 95.35 276 | 98.59 290 |
|
TR-MVS | | | 97.76 226 | 97.41 240 | 98.82 204 | 99.06 231 | 97.87 226 | 98.87 311 | 98.56 323 | 96.63 230 | 98.68 243 | 99.22 267 | 92.49 265 | 99.65 198 | 95.40 281 | 97.79 212 | 98.95 200 |
|
Anonymous202405211 | | | 98.30 145 | 97.98 161 | 99.26 128 | 99.57 126 | 98.16 213 | 99.41 180 | 98.55 324 | 96.03 279 | 99.19 166 | 99.74 100 | 91.87 280 | 99.92 66 | 99.16 40 | 98.29 178 | 99.70 80 |
|
tpm | | | 97.67 244 | 97.55 214 | 98.03 274 | 99.02 238 | 95.01 312 | 99.43 169 | 98.54 325 | 96.44 246 | 99.12 176 | 99.34 247 | 91.83 281 | 99.60 208 | 97.75 172 | 96.46 255 | 99.48 135 |
|
Patchmatch-RL test | | | 95.84 298 | 95.81 287 | 95.95 321 | 95.61 338 | 90.57 339 | 98.24 341 | 98.39 326 | 95.10 291 | 95.20 318 | 98.67 306 | 94.78 187 | 97.77 335 | 96.28 264 | 90.02 331 | 99.51 129 |
|
no-one | | | 83.04 327 | 80.12 329 | 91.79 333 | 89.44 354 | 85.65 345 | 99.32 211 | 98.32 327 | 89.06 341 | 79.79 355 | 89.16 356 | 44.86 362 | 96.67 343 | 84.33 347 | 46.78 358 | 93.05 349 |
|
test12356 | | | 91.74 320 | 92.19 321 | 90.37 337 | 91.22 349 | 82.41 349 | 98.61 328 | 98.28 328 | 90.66 338 | 91.82 340 | 97.92 322 | 84.90 341 | 92.61 353 | 81.64 349 | 94.66 295 | 96.09 345 |
|
LCM-MVSNet-Re | | | 97.83 213 | 98.15 144 | 96.87 314 | 99.30 184 | 92.25 336 | 99.59 94 | 98.26 329 | 97.43 163 | 96.20 312 | 99.13 273 | 96.27 131 | 98.73 314 | 98.17 136 | 98.99 137 | 99.64 99 |
|
LFMVS | | | 97.90 204 | 97.35 247 | 99.54 77 | 99.52 133 | 99.01 121 | 99.39 189 | 98.24 330 | 97.10 195 | 99.65 52 | 99.79 74 | 84.79 342 | 99.91 76 | 99.28 27 | 98.38 173 | 99.69 81 |
|
PM-MVS | | | 92.96 317 | 92.23 319 | 95.14 323 | 95.61 338 | 89.98 341 | 99.37 196 | 98.21 331 | 94.80 294 | 95.04 320 | 97.69 329 | 65.06 355 | 97.90 333 | 94.30 305 | 89.98 332 | 97.54 340 |
|
PMVS | | 70.75 22 | 75.98 334 | 74.97 333 | 79.01 347 | 70.98 363 | 55.18 364 | 93.37 357 | 98.21 331 | 65.08 359 | 61.78 360 | 93.83 349 | 21.74 369 | 92.53 354 | 78.59 352 | 91.12 329 | 89.34 356 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
pmmvs3 | | | 94.09 314 | 93.25 316 | 96.60 318 | 94.76 343 | 94.49 318 | 98.92 306 | 98.18 333 | 89.66 339 | 96.48 310 | 98.06 321 | 86.28 335 | 97.33 339 | 89.68 334 | 87.20 341 | 97.97 322 |
|
door-mid | | | | | | | | | 98.05 334 | | | | | | | | |
|
tmp_tt | | | 82.80 328 | 81.52 328 | 86.66 339 | 66.61 364 | 68.44 362 | 92.79 358 | 97.92 335 | 68.96 355 | 80.04 354 | 99.85 27 | 85.77 337 | 96.15 346 | 97.86 160 | 43.89 359 | 95.39 347 |
|
door | | | | | | | | | 97.92 335 | | | | | | | | |
|
testpf | | | 95.66 300 | 96.02 283 | 94.58 324 | 98.35 318 | 92.32 335 | 97.25 352 | 97.91 337 | 92.83 326 | 97.03 305 | 98.99 285 | 88.69 319 | 98.61 315 | 95.72 273 | 97.40 236 | 92.80 350 |
|
test-LLR | | | 98.06 174 | 97.90 167 | 98.55 230 | 98.79 283 | 97.10 251 | 98.67 324 | 97.75 338 | 97.34 171 | 98.61 255 | 98.85 296 | 94.45 206 | 99.45 219 | 97.25 211 | 99.38 111 | 99.10 168 |
|
test-mter | | | 97.49 259 | 97.13 263 | 98.55 230 | 98.79 283 | 97.10 251 | 98.67 324 | 97.75 338 | 96.65 228 | 98.61 255 | 98.85 296 | 88.23 327 | 99.45 219 | 97.25 211 | 99.38 111 | 99.10 168 |
|
IB-MVS | | 95.67 18 | 96.22 292 | 95.44 300 | 98.57 226 | 99.21 200 | 96.70 274 | 98.65 327 | 97.74 340 | 96.71 224 | 97.27 299 | 98.54 314 | 86.03 336 | 99.92 66 | 98.47 117 | 86.30 347 | 99.10 168 |
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 |
conf0.01 | | | 98.21 157 | 97.89 171 | 99.15 141 | 99.76 44 | 99.04 111 | 99.67 58 | 97.71 341 | 97.10 195 | 99.55 73 | 99.54 175 | 92.70 253 | 99.79 150 | 96.90 238 | 98.12 198 | 98.61 282 |
|
conf0.002 | | | 98.21 157 | 97.89 171 | 99.15 141 | 99.76 44 | 99.04 111 | 99.67 58 | 97.71 341 | 97.10 195 | 99.55 73 | 99.54 175 | 92.70 253 | 99.79 150 | 96.90 238 | 98.12 198 | 98.61 282 |
|
thresconf0.02 | | | 98.24 150 | 97.89 171 | 99.27 124 | 99.76 44 | 99.04 111 | 99.67 58 | 97.71 341 | 97.10 195 | 99.55 73 | 99.54 175 | 92.70 253 | 99.79 150 | 96.90 238 | 98.12 198 | 98.97 187 |
|
tfpn_n400 | | | 98.24 150 | 97.89 171 | 99.27 124 | 99.76 44 | 99.04 111 | 99.67 58 | 97.71 341 | 97.10 195 | 99.55 73 | 99.54 175 | 92.70 253 | 99.79 150 | 96.90 238 | 98.12 198 | 98.97 187 |
|
tfpnconf | | | 98.24 150 | 97.89 171 | 99.27 124 | 99.76 44 | 99.04 111 | 99.67 58 | 97.71 341 | 97.10 195 | 99.55 73 | 99.54 175 | 92.70 253 | 99.79 150 | 96.90 238 | 98.12 198 | 98.97 187 |
|
tfpnview11 | | | 98.24 150 | 97.89 171 | 99.27 124 | 99.76 44 | 99.04 111 | 99.67 58 | 97.71 341 | 97.10 195 | 99.55 73 | 99.54 175 | 92.70 253 | 99.79 150 | 96.90 238 | 98.12 198 | 98.97 187 |
|
testmv | | | 87.91 322 | 87.80 323 | 88.24 338 | 87.68 356 | 77.50 356 | 99.07 269 | 97.66 347 | 89.27 340 | 86.47 346 | 96.22 345 | 68.35 353 | 92.49 355 | 76.63 354 | 88.82 334 | 94.72 348 |
|
TESTMET0.1,1 | | | 97.55 250 | 97.27 259 | 98.40 245 | 98.93 262 | 96.53 279 | 98.67 324 | 97.61 348 | 96.96 209 | 98.64 251 | 99.28 259 | 88.63 322 | 99.45 219 | 97.30 210 | 99.38 111 | 99.21 162 |
|
tfpn1000 | | | 98.33 142 | 98.02 156 | 99.25 129 | 99.78 36 | 98.73 173 | 99.70 44 | 97.55 349 | 97.48 157 | 99.69 37 | 99.53 182 | 92.37 271 | 99.85 116 | 97.82 163 | 98.26 183 | 99.16 164 |
|
PMMVS2 | | | 86.87 323 | 85.37 326 | 91.35 336 | 90.21 352 | 83.80 347 | 98.89 309 | 97.45 350 | 83.13 349 | 91.67 341 | 95.03 346 | 48.49 360 | 94.70 350 | 85.86 345 | 77.62 351 | 95.54 346 |
|
tfpn_ndepth | | | 98.17 161 | 97.84 179 | 99.15 141 | 99.75 56 | 98.76 171 | 99.61 90 | 97.39 351 | 96.92 213 | 99.61 59 | 99.38 229 | 92.19 273 | 99.86 110 | 97.57 188 | 98.13 196 | 98.82 204 |
|
K. test v3 | | | 97.10 272 | 96.79 270 | 98.01 277 | 98.72 295 | 96.33 286 | 99.87 4 | 97.05 352 | 97.59 146 | 96.16 313 | 99.80 66 | 88.71 318 | 99.04 292 | 96.69 252 | 96.55 254 | 98.65 262 |
|
DSMNet-mixed | | | 97.25 268 | 97.35 247 | 96.95 312 | 97.84 324 | 93.61 329 | 99.57 107 | 96.63 353 | 96.13 273 | 98.87 217 | 98.61 311 | 94.59 200 | 97.70 337 | 95.08 286 | 98.86 150 | 99.55 116 |
|
MVS-HIRNet | | | 95.75 299 | 95.16 303 | 97.51 303 | 99.30 184 | 93.69 328 | 98.88 310 | 95.78 354 | 85.09 347 | 98.78 229 | 92.65 350 | 91.29 294 | 99.37 235 | 94.85 290 | 99.85 53 | 99.46 142 |
|
E-PMN | | | 80.61 329 | 79.88 330 | 82.81 344 | 90.75 351 | 76.38 358 | 97.69 348 | 95.76 355 | 66.44 357 | 83.52 348 | 92.25 351 | 62.54 357 | 87.16 360 | 68.53 358 | 61.40 354 | 84.89 359 |
|
lessismore_v0 | | | | | 97.79 293 | 98.69 299 | 95.44 304 | | 94.75 356 | | 95.71 317 | 99.87 20 | 88.69 319 | 99.32 249 | 95.89 269 | 94.93 288 | 98.62 273 |
|
EPMVS | | | 97.82 216 | 97.65 208 | 98.35 248 | 98.88 271 | 95.98 292 | 99.49 146 | 94.71 357 | 97.57 149 | 99.26 141 | 99.48 202 | 92.46 269 | 99.71 183 | 97.87 159 | 99.08 131 | 99.35 154 |
|
gg-mvs-nofinetune | | | 96.17 294 | 95.32 301 | 98.73 214 | 98.79 283 | 98.14 215 | 99.38 194 | 94.09 358 | 91.07 337 | 98.07 284 | 91.04 354 | 89.62 311 | 99.35 242 | 96.75 248 | 99.09 130 | 98.68 237 |
|
GG-mvs-BLEND | | | | | 98.45 239 | 98.55 312 | 98.16 213 | 99.43 169 | 93.68 359 | | 97.23 300 | 98.46 315 | 89.30 313 | 99.22 273 | 95.43 280 | 98.22 184 | 97.98 321 |
|
PNet_i23d | | | 79.43 331 | 77.68 332 | 84.67 341 | 86.18 358 | 71.69 361 | 96.50 354 | 93.68 359 | 75.17 351 | 71.33 356 | 91.18 353 | 32.18 365 | 90.62 357 | 78.57 353 | 74.34 352 | 91.71 354 |
|
MVE | | 76.82 21 | 76.91 333 | 74.31 335 | 84.70 340 | 85.38 360 | 76.05 359 | 96.88 353 | 93.17 361 | 67.39 356 | 71.28 357 | 89.01 357 | 21.66 370 | 87.69 359 | 71.74 357 | 72.29 353 | 90.35 355 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
ANet_high | | | 77.30 332 | 74.86 334 | 84.62 342 | 75.88 362 | 77.61 355 | 97.63 349 | 93.15 362 | 88.81 343 | 64.27 358 | 89.29 355 | 36.51 363 | 83.93 362 | 75.89 355 | 52.31 357 | 92.33 353 |
|
N_pmnet | | | 94.95 308 | 95.83 286 | 92.31 331 | 98.47 315 | 79.33 354 | 99.12 258 | 92.81 363 | 93.87 315 | 97.68 295 | 99.13 273 | 93.87 227 | 99.01 297 | 91.38 329 | 96.19 261 | 98.59 290 |
|
wuykxyi23d | | | 74.42 335 | 71.19 336 | 84.14 343 | 76.16 361 | 74.29 360 | 96.00 355 | 92.57 364 | 69.57 354 | 63.84 359 | 87.49 358 | 21.98 367 | 88.86 358 | 75.56 356 | 57.50 356 | 89.26 357 |
|
EMVS | | | 80.02 330 | 79.22 331 | 82.43 346 | 91.19 350 | 76.40 357 | 97.55 351 | 92.49 365 | 66.36 358 | 83.01 350 | 91.27 352 | 64.63 356 | 85.79 361 | 65.82 359 | 60.65 355 | 85.08 358 |
|
testmvs | | | 39.17 338 | 43.78 337 | 25.37 352 | 36.04 366 | 16.84 367 | 98.36 336 | 26.56 366 | 20.06 361 | 38.51 362 | 67.32 359 | 29.64 366 | 15.30 365 | 37.59 361 | 39.90 360 | 43.98 361 |
|
wuyk23d | | | 40.18 337 | 41.29 340 | 36.84 349 | 86.18 358 | 49.12 365 | 79.73 359 | 22.81 367 | 27.64 360 | 25.46 363 | 28.45 364 | 21.98 367 | 48.89 363 | 55.80 360 | 23.56 363 | 12.51 363 |
|
test123 | | | 39.01 339 | 42.50 339 | 28.53 351 | 39.17 365 | 20.91 366 | 98.75 320 | 19.17 368 | 19.83 362 | 38.57 361 | 66.67 360 | 33.16 364 | 15.42 364 | 37.50 362 | 29.66 362 | 49.26 360 |
|
pcd_1.5k_mvsjas | | | 8.27 342 | 11.03 343 | 0.00 353 | 0.00 367 | 0.00 368 | 0.00 360 | 0.00 369 | 0.00 363 | 0.00 364 | 0.27 365 | 99.01 12 | 0.00 366 | 0.00 363 | 0.00 364 | 0.00 364 |
|
sosnet-low-res | | | 0.02 343 | 0.03 344 | 0.00 353 | 0.00 367 | 0.00 368 | 0.00 360 | 0.00 369 | 0.00 363 | 0.00 364 | 0.27 365 | 0.00 371 | 0.00 366 | 0.00 363 | 0.00 364 | 0.00 364 |
|
sosnet | | | 0.02 343 | 0.03 344 | 0.00 353 | 0.00 367 | 0.00 368 | 0.00 360 | 0.00 369 | 0.00 363 | 0.00 364 | 0.27 365 | 0.00 371 | 0.00 366 | 0.00 363 | 0.00 364 | 0.00 364 |
|
uncertanet | | | 0.02 343 | 0.03 344 | 0.00 353 | 0.00 367 | 0.00 368 | 0.00 360 | 0.00 369 | 0.00 363 | 0.00 364 | 0.27 365 | 0.00 371 | 0.00 366 | 0.00 363 | 0.00 364 | 0.00 364 |
|
Regformer | | | 0.02 343 | 0.03 344 | 0.00 353 | 0.00 367 | 0.00 368 | 0.00 360 | 0.00 369 | 0.00 363 | 0.00 364 | 0.27 365 | 0.00 371 | 0.00 366 | 0.00 363 | 0.00 364 | 0.00 364 |
|
n2 | | | | | | | | | 0.00 369 | | | | | | | | |
|
nn | | | | | | | | | 0.00 369 | | | | | | | | |
|
ab-mvs-re | | | 8.30 341 | 11.06 342 | 0.00 353 | 0.00 367 | 0.00 368 | 0.00 360 | 0.00 369 | 0.00 363 | 0.00 364 | 99.58 163 | 0.00 371 | 0.00 366 | 0.00 363 | 0.00 364 | 0.00 364 |
|
uanet | | | 0.02 343 | 0.03 344 | 0.00 353 | 0.00 367 | 0.00 368 | 0.00 360 | 0.00 369 | 0.00 363 | 0.00 364 | 0.27 365 | 0.00 371 | 0.00 366 | 0.00 363 | 0.00 364 | 0.00 364 |
|
GSMVS | | | | | | | | | | | | | | | | | 99.52 124 |
|
test_part3 | | | | | | | | 99.37 196 | | 97.97 109 | | 99.78 80 | | 99.95 33 | 97.15 219 | | |
|
test_part2 | | | | | | 99.81 32 | 99.83 7 | | | | 99.77 24 | | | | | | |
|
sam_mvs1 | | | | | | | | | | | | | 94.86 182 | | | | 99.52 124 |
|
sam_mvs | | | | | | | | | | | | | 94.72 195 | | | | |
|
test_post1 | | | | | | | | 99.23 238 | | | | 65.14 362 | 94.18 217 | 99.71 183 | 97.58 186 | | |
|
test_post | | | | | | | | | | | | 65.99 361 | 94.65 199 | 99.73 173 | | | |
|
patchmatchnet-post | | | | | | | | | | | | 98.70 305 | 94.79 186 | 99.74 166 | | | |
|
gm-plane-assit | | | | | | 98.54 313 | 92.96 332 | | | 94.65 297 | | 99.15 271 | | 99.64 200 | 97.56 190 | | |
|
test9_res | | | | | | | | | | | | | | | 97.49 197 | 99.72 86 | 99.75 56 |
|
agg_prior2 | | | | | | | | | | | | | | | 97.21 213 | 99.73 85 | 99.75 56 |
|
test_prior4 | | | | | | | 99.56 52 | 98.99 290 | | | | | | | | | |
|
test_prior2 | | | | | | | | 98.96 299 | | 98.34 66 | 99.01 196 | 99.52 187 | 98.68 52 | | 97.96 152 | 99.74 82 | |
|
旧先验2 | | | | | | | | 98.96 299 | | 96.70 225 | 99.47 90 | | | 99.94 42 | 98.19 134 | | |
|
新几何2 | | | | | | | | 99.01 288 | | | | | | | | | |
|
原ACMM2 | | | | | | | | 98.95 303 | | | | | | | | | |
|
testdata2 | | | | | | | | | | | | | | 99.95 33 | 96.67 253 | | |
|
segment_acmp | | | | | | | | | | | | | 98.96 21 | | | | |
|
testdata1 | | | | | | | | 98.85 312 | | 98.32 69 | | | | | | | |
|
plane_prior7 | | | | | | 99.29 187 | 97.03 259 | | | | | | | | | | |
|
plane_prior6 | | | | | | 99.27 192 | 96.98 263 | | | | | | 92.71 251 | | | | |
|
plane_prior4 | | | | | | | | | | | | 99.61 155 | | | | | |
|
plane_prior3 | | | | | | | 97.00 261 | | | 98.69 46 | 99.11 178 | | | | | | |
|
plane_prior2 | | | | | | | | 99.39 189 | | 98.97 22 | | | | | | | |
|
plane_prior1 | | | | | | 99.26 194 | | | | | | | | | | | |
|
plane_prior | | | | | | | 96.97 264 | 99.21 245 | | 98.45 59 | | | | | | 97.60 218 | |
|
HQP5-MVS | | | | | | | 96.83 269 | | | | | | | | | | |
|
HQP-NCC | | | | | | 99.19 204 | | 98.98 294 | | 98.24 72 | 98.66 244 | | | | | | |
|
ACMP_Plane | | | | | | 99.19 204 | | 98.98 294 | | 98.24 72 | 98.66 244 | | | | | | |
|
BP-MVS | | | | | | | | | | | | | | | 97.19 215 | | |
|
HQP4-MVS | | | | | | | | | | | 98.66 244 | | | 99.64 200 | | | 98.64 264 |
|
HQP2-MVS | | | | | | | | | | | | | 92.47 266 | | | | |
|
NP-MVS | | | | | | 99.23 197 | 96.92 267 | | | | | 99.40 224 | | | | | |
|
MDTV_nov1_ep13_2view | | | | | | | 95.18 310 | 99.35 206 | | 96.84 218 | 99.58 66 | | 95.19 163 | | 97.82 163 | | 99.46 142 |
|
ACMMP++_ref | | | | | | | | | | | | | | | | 97.19 244 | |
|
ACMMP++ | | | | | | | | | | | | | | | | 97.43 235 | |
|
Test By Simon | | | | | | | | | | | | | 98.75 47 | | | | |
|