APDe-MVS | | | 99.66 1 | 99.57 1 | 99.92 1 | 99.77 42 | 99.89 1 | 99.75 36 | 99.56 49 | 99.02 10 | 99.88 3 | 99.85 27 | 99.18 5 | 99.96 19 | 99.22 34 | 99.92 12 | 99.90 1 |
|
ESAPD | | | 99.46 21 | 99.32 26 | 99.91 2 | 99.78 36 | 99.88 2 | 99.36 202 | 99.51 86 | 98.73 44 | 99.88 3 | 99.84 36 | 98.72 48 | 99.96 19 | 98.16 139 | 99.87 39 | 99.88 4 |
|
MP-MVS-pluss | | | 99.37 39 | 99.20 48 | 99.88 5 | 99.90 3 | 99.87 3 | 99.30 217 | 99.52 77 | 97.18 187 | 99.60 63 | 99.79 76 | 98.79 36 | 99.95 34 | 98.83 75 | 99.91 17 | 99.83 24 |
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
ACMMP_Plus | | | 99.47 20 | 99.34 24 | 99.88 5 | 99.87 15 | 99.86 4 | 99.47 158 | 99.48 117 | 98.05 100 | 99.76 30 | 99.86 23 | 98.82 33 | 99.93 56 | 98.82 78 | 99.91 17 | 99.84 13 |
|
zzz-MVS | | | 99.49 13 | 99.36 19 | 99.89 3 | 99.90 3 | 99.86 4 | 99.36 202 | 99.47 133 | 98.79 40 | 99.68 39 | 99.81 57 | 98.43 63 | 99.97 11 | 98.88 62 | 99.90 24 | 99.83 24 |
|
MTAPA | | | 99.52 11 | 99.39 15 | 99.89 3 | 99.90 3 | 99.86 4 | 99.66 68 | 99.47 133 | 98.79 40 | 99.68 39 | 99.81 57 | 98.43 63 | 99.97 11 | 98.88 62 | 99.90 24 | 99.83 24 |
|
HPM-MVS++ | | | 99.39 38 | 99.23 47 | 99.87 7 | 99.75 57 | 99.84 7 | 99.43 171 | 99.51 86 | 98.68 48 | 99.27 140 | 99.53 184 | 98.64 54 | 99.96 19 | 98.44 122 | 99.80 70 | 99.79 45 |
|
SMA-MVS | | | 99.44 26 | 99.30 34 | 99.85 18 | 99.73 73 | 99.83 8 | 99.56 116 | 99.47 133 | 97.45 163 | 99.78 23 | 99.82 47 | 99.18 5 | 99.91 75 | 98.79 79 | 99.89 32 | 99.81 35 |
|
test_part2 | | | | | | 99.81 32 | 99.83 8 | | | | 99.77 25 | | | | | | |
|
XVS | | | 99.53 9 | 99.42 11 | 99.87 7 | 99.85 23 | 99.83 8 | 99.69 48 | 99.68 19 | 98.98 19 | 99.37 113 | 99.74 101 | 98.81 34 | 99.94 41 | 98.79 79 | 99.86 50 | 99.84 13 |
|
X-MVStestdata | | | 96.55 280 | 95.45 301 | 99.87 7 | 99.85 23 | 99.83 8 | 99.69 48 | 99.68 19 | 98.98 19 | 99.37 113 | 64.01 365 | 98.81 34 | 99.94 41 | 98.79 79 | 99.86 50 | 99.84 13 |
|
APD-MVS_3200maxsize | | | 99.48 17 | 99.35 22 | 99.85 18 | 99.76 45 | 99.83 8 | 99.63 82 | 99.54 63 | 98.36 66 | 99.79 19 | 99.82 47 | 98.86 30 | 99.95 34 | 98.62 98 | 99.81 68 | 99.78 49 |
|
MP-MVS | | | 99.33 43 | 99.15 52 | 99.87 7 | 99.88 11 | 99.82 13 | 99.66 68 | 99.46 143 | 98.09 91 | 99.48 91 | 99.74 101 | 98.29 72 | 99.96 19 | 97.93 158 | 99.87 39 | 99.82 31 |
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo. |
SteuartSystems-ACMMP | | | 99.54 7 | 99.42 11 | 99.87 7 | 99.82 29 | 99.81 14 | 99.59 96 | 99.51 86 | 98.62 50 | 99.79 19 | 99.83 40 | 99.28 3 | 99.97 11 | 98.48 117 | 99.90 24 | 99.84 13 |
Skip Steuart: Steuart Systems R&D Blog. |
HSP-MVS | | | 99.41 34 | 99.26 45 | 99.85 18 | 99.89 8 | 99.80 15 | 99.67 59 | 99.37 201 | 98.70 46 | 99.77 25 | 99.49 198 | 98.21 75 | 99.95 34 | 98.46 120 | 99.77 76 | 99.81 35 |
|
HFP-MVS | | | 99.49 13 | 99.37 17 | 99.86 13 | 99.87 15 | 99.80 15 | 99.66 68 | 99.67 22 | 98.15 82 | 99.68 39 | 99.69 121 | 99.06 9 | 99.96 19 | 98.69 90 | 99.87 39 | 99.84 13 |
|
region2R | | | 99.48 17 | 99.35 22 | 99.87 7 | 99.88 11 | 99.80 15 | 99.65 78 | 99.66 25 | 98.13 84 | 99.66 50 | 99.68 126 | 98.96 21 | 99.96 19 | 98.62 98 | 99.87 39 | 99.84 13 |
|
#test# | | | 99.43 29 | 99.29 38 | 99.86 13 | 99.87 15 | 99.80 15 | 99.55 122 | 99.67 22 | 97.83 125 | 99.68 39 | 99.69 121 | 99.06 9 | 99.96 19 | 98.39 123 | 99.87 39 | 99.84 13 |
|
ACMMPR | | | 99.49 13 | 99.36 19 | 99.86 13 | 99.87 15 | 99.79 19 | 99.66 68 | 99.67 22 | 98.15 82 | 99.67 45 | 99.69 121 | 98.95 24 | 99.96 19 | 98.69 90 | 99.87 39 | 99.84 13 |
|
mPP-MVS | | | 99.44 26 | 99.30 34 | 99.86 13 | 99.88 11 | 99.79 19 | 99.69 48 | 99.48 117 | 98.12 86 | 99.50 87 | 99.75 96 | 98.78 37 | 99.97 11 | 98.57 106 | 99.89 32 | 99.83 24 |
|
HPM-MVS_fast | | | 99.51 12 | 99.40 14 | 99.85 18 | 99.91 1 | 99.79 19 | 99.76 28 | 99.56 49 | 97.72 138 | 99.76 30 | 99.75 96 | 99.13 7 | 99.92 65 | 99.07 48 | 99.92 12 | 99.85 9 |
|
APD-MVS | | | 99.27 51 | 99.08 59 | 99.84 23 | 99.75 57 | 99.79 19 | 99.50 139 | 99.50 101 | 97.16 189 | 99.77 25 | 99.82 47 | 98.78 37 | 99.94 41 | 97.56 193 | 99.86 50 | 99.80 41 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
PGM-MVS | | | 99.45 23 | 99.31 32 | 99.86 13 | 99.87 15 | 99.78 23 | 99.58 103 | 99.65 30 | 97.84 124 | 99.71 33 | 99.80 68 | 99.12 8 | 99.97 11 | 98.33 130 | 99.87 39 | 99.83 24 |
|
abl_6 | | | 99.44 26 | 99.31 32 | 99.83 24 | 99.85 23 | 99.75 24 | 99.66 68 | 99.59 38 | 98.13 84 | 99.82 15 | 99.81 57 | 98.60 56 | 99.96 19 | 98.46 120 | 99.88 35 | 99.79 45 |
|
CP-MVS | | | 99.45 23 | 99.32 26 | 99.85 18 | 99.83 28 | 99.75 24 | 99.69 48 | 99.52 77 | 98.07 95 | 99.53 81 | 99.63 148 | 98.93 26 | 99.97 11 | 98.74 83 | 99.91 17 | 99.83 24 |
|
LS3D | | | 99.27 51 | 99.12 55 | 99.74 45 | 99.18 210 | 99.75 24 | 99.56 116 | 99.57 44 | 98.45 60 | 99.49 90 | 99.85 27 | 97.77 87 | 99.94 41 | 98.33 130 | 99.84 59 | 99.52 124 |
|
MCST-MVS | | | 99.43 29 | 99.30 34 | 99.82 26 | 99.79 35 | 99.74 27 | 99.29 221 | 99.40 184 | 98.79 40 | 99.52 83 | 99.62 153 | 98.91 27 | 99.90 88 | 98.64 95 | 99.75 79 | 99.82 31 |
|
HPM-MVS | | | 99.42 31 | 99.28 40 | 99.83 24 | 99.90 3 | 99.72 28 | 99.81 15 | 99.54 63 | 97.59 148 | 99.68 39 | 99.63 148 | 98.91 27 | 99.94 41 | 98.58 104 | 99.91 17 | 99.84 13 |
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023 |
CDPH-MVS | | | 99.13 65 | 98.91 84 | 99.80 31 | 99.75 57 | 99.71 29 | 99.15 255 | 99.41 177 | 96.60 235 | 99.60 63 | 99.55 174 | 98.83 32 | 99.90 88 | 97.48 201 | 99.83 63 | 99.78 49 |
|
CNVR-MVS | | | 99.42 31 | 99.30 34 | 99.78 35 | 99.62 116 | 99.71 29 | 99.26 234 | 99.52 77 | 98.82 35 | 99.39 109 | 99.71 112 | 98.96 21 | 99.85 116 | 98.59 103 | 99.80 70 | 99.77 51 |
|
DP-MVS Recon | | | 99.12 70 | 98.95 80 | 99.65 59 | 99.74 68 | 99.70 31 | 99.27 226 | 99.57 44 | 96.40 253 | 99.42 102 | 99.68 126 | 98.75 45 | 99.80 147 | 97.98 154 | 99.72 85 | 99.44 147 |
|
nrg030 | | | 98.64 131 | 98.42 133 | 99.28 125 | 99.05 237 | 99.69 32 | 99.81 15 | 99.46 143 | 98.04 101 | 99.01 199 | 99.82 47 | 96.69 120 | 99.38 232 | 99.34 23 | 94.59 299 | 98.78 209 |
|
SD-MVS | | | 99.41 34 | 99.52 6 | 99.05 153 | 99.74 68 | 99.68 33 | 99.46 161 | 99.52 77 | 99.11 7 | 99.88 3 | 99.91 5 | 99.43 1 | 97.70 338 | 98.72 87 | 99.93 11 | 99.77 51 |
|
3Dnovator+ | | 97.12 13 | 99.18 60 | 98.97 75 | 99.82 26 | 99.17 215 | 99.68 33 | 99.81 15 | 99.51 86 | 99.20 4 | 98.72 237 | 99.89 10 | 95.68 148 | 99.97 11 | 98.86 69 | 99.86 50 | 99.81 35 |
|
QAPM | | | 98.67 128 | 98.30 141 | 99.80 31 | 99.20 205 | 99.67 35 | 99.77 25 | 99.72 11 | 94.74 297 | 98.73 236 | 99.90 7 | 95.78 145 | 99.98 5 | 96.96 233 | 99.88 35 | 99.76 54 |
|
ACMMP | | | 99.45 23 | 99.32 26 | 99.82 26 | 99.89 8 | 99.67 35 | 99.62 85 | 99.69 18 | 98.12 86 | 99.63 55 | 99.84 36 | 98.73 47 | 99.96 19 | 98.55 112 | 99.83 63 | 99.81 35 |
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 |
TSAR-MVS + MP. | | | 99.58 3 | 99.50 7 | 99.81 29 | 99.91 1 | 99.66 37 | 99.63 82 | 99.39 187 | 98.91 29 | 99.78 23 | 99.85 27 | 99.36 2 | 99.94 41 | 98.84 72 | 99.88 35 | 99.82 31 |
|
MAR-MVS | | | 98.86 106 | 98.63 118 | 99.54 78 | 99.37 171 | 99.66 37 | 99.45 162 | 99.54 63 | 96.61 233 | 99.01 199 | 99.40 226 | 97.09 105 | 99.86 110 | 97.68 185 | 99.53 105 | 99.10 169 |
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 |
3Dnovator | | 97.25 9 | 99.24 55 | 99.05 61 | 99.81 29 | 99.12 223 | 99.66 37 | 99.84 9 | 99.74 10 | 99.09 8 | 98.92 214 | 99.90 7 | 95.94 139 | 99.98 5 | 98.95 57 | 99.92 12 | 99.79 45 |
|
TEST9 | | | | | | 99.67 95 | 99.65 40 | 99.05 276 | 99.41 177 | 96.22 266 | 98.95 210 | 99.49 198 | 98.77 40 | 99.91 75 | | | |
|
train_agg | | | 99.02 90 | 98.77 103 | 99.77 37 | 99.67 95 | 99.65 40 | 99.05 276 | 99.41 177 | 96.28 259 | 98.95 210 | 99.49 198 | 98.76 42 | 99.91 75 | 97.63 186 | 99.72 85 | 99.75 55 |
|
NCCC | | | 99.34 42 | 99.19 49 | 99.79 34 | 99.61 120 | 99.65 40 | 99.30 217 | 99.48 117 | 98.86 31 | 99.21 163 | 99.63 148 | 98.72 48 | 99.90 88 | 98.25 134 | 99.63 102 | 99.80 41 |
|
agg_prior1 | | | 99.01 93 | 98.76 105 | 99.76 39 | 99.67 95 | 99.62 43 | 98.99 291 | 99.40 184 | 96.26 262 | 98.87 220 | 99.49 198 | 98.77 40 | 99.91 75 | 97.69 183 | 99.72 85 | 99.75 55 |
|
agg_prior | | | | | | 99.67 95 | 99.62 43 | | 99.40 184 | | 98.87 220 | | | 99.91 75 | | | |
|
test_8 | | | | | | 99.67 95 | 99.61 45 | 99.03 282 | 99.41 177 | 96.28 259 | 98.93 213 | 99.48 204 | 98.76 42 | 99.91 75 | | | |
|
test12 | | | | | 99.75 40 | 99.64 109 | 99.61 45 | | 99.29 236 | | 99.21 163 | | 98.38 67 | 99.89 96 | | 99.74 81 | 99.74 60 |
|
agg_prior3 | | | 98.97 98 | 98.71 109 | 99.75 40 | 99.67 95 | 99.60 47 | 99.04 281 | 99.41 177 | 95.93 283 | 98.87 220 | 99.48 204 | 98.61 55 | 99.91 75 | 97.63 186 | 99.72 85 | 99.75 55 |
|
1121 | | | 99.09 79 | 98.87 89 | 99.75 40 | 99.74 68 | 99.60 47 | 99.27 226 | 99.48 117 | 96.82 222 | 99.25 148 | 99.65 137 | 98.38 67 | 99.93 56 | 97.53 196 | 99.67 96 | 99.73 65 |
|
新几何1 | | | | | 99.75 40 | 99.75 57 | 99.59 49 | | 99.54 63 | 96.76 223 | 99.29 132 | 99.64 144 | 98.43 63 | 99.94 41 | 96.92 237 | 99.66 97 | 99.72 71 |
|
旧先验1 | | | | | | 99.74 68 | 99.59 49 | | 99.54 63 | | | 99.69 121 | 98.47 60 | | | 99.68 95 | 99.73 65 |
|
DeepC-MVS_fast | | 98.69 1 | 99.49 13 | 99.39 15 | 99.77 37 | 99.63 112 | 99.59 49 | 99.36 202 | 99.46 143 | 99.07 9 | 99.79 19 | 99.82 47 | 98.85 31 | 99.92 65 | 98.68 92 | 99.87 39 | 99.82 31 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
test_prior4 | | | | | | | 99.56 52 | 98.99 291 | | | | | | | | | |
|
VNet | | | 99.11 75 | 98.90 85 | 99.73 47 | 99.52 135 | 99.56 52 | 99.41 182 | 99.39 187 | 99.01 13 | 99.74 32 | 99.78 82 | 95.56 149 | 99.92 65 | 99.52 7 | 98.18 189 | 99.72 71 |
|
UA-Net | | | 99.42 31 | 99.29 38 | 99.80 31 | 99.62 116 | 99.55 54 | 99.50 139 | 99.70 15 | 98.79 40 | 99.77 25 | 99.96 1 | 97.45 95 | 99.96 19 | 98.92 60 | 99.90 24 | 99.89 2 |
|
FIs | | | 98.78 120 | 98.63 118 | 99.23 136 | 99.18 210 | 99.54 55 | 99.83 12 | 99.59 38 | 98.28 71 | 98.79 231 | 99.81 57 | 96.75 118 | 99.37 236 | 99.08 47 | 96.38 258 | 98.78 209 |
|
VPA-MVSNet | | | 98.29 149 | 97.95 166 | 99.30 120 | 99.16 217 | 99.54 55 | 99.50 139 | 99.58 43 | 98.27 72 | 99.35 120 | 99.37 235 | 92.53 265 | 99.65 199 | 99.35 19 | 94.46 300 | 98.72 221 |
|
AdaColmap | | | 99.01 93 | 98.80 100 | 99.66 55 | 99.56 131 | 99.54 55 | 99.18 250 | 99.70 15 | 98.18 81 | 99.35 120 | 99.63 148 | 96.32 130 | 99.90 88 | 97.48 201 | 99.77 76 | 99.55 116 |
|
114514_t | | | 98.93 100 | 98.67 113 | 99.72 49 | 99.85 23 | 99.53 58 | 99.62 85 | 99.59 38 | 92.65 330 | 99.71 33 | 99.78 82 | 98.06 80 | 99.90 88 | 98.84 72 | 99.91 17 | 99.74 60 |
|
DP-MVS | | | 99.16 63 | 98.95 80 | 99.78 35 | 99.77 42 | 99.53 58 | 99.41 182 | 99.50 101 | 97.03 208 | 99.04 196 | 99.88 15 | 97.39 96 | 99.92 65 | 98.66 93 | 99.90 24 | 99.87 5 |
|
OpenMVS | | 96.50 16 | 98.47 135 | 98.12 149 | 99.52 87 | 99.04 238 | 99.53 58 | 99.82 13 | 99.72 11 | 94.56 303 | 98.08 284 | 99.88 15 | 94.73 195 | 99.98 5 | 97.47 203 | 99.76 78 | 99.06 179 |
|
Regformer-2 | | | 99.54 7 | 99.47 8 | 99.75 40 | 99.71 83 | 99.52 61 | 99.49 148 | 99.49 106 | 98.94 26 | 99.83 12 | 99.76 91 | 99.01 12 | 99.94 41 | 99.15 42 | 99.87 39 | 99.80 41 |
|
PHI-MVS | | | 99.30 46 | 99.17 51 | 99.70 51 | 99.56 131 | 99.52 61 | 99.58 103 | 99.80 8 | 97.12 193 | 99.62 58 | 99.73 106 | 98.58 57 | 99.90 88 | 98.61 100 | 99.91 17 | 99.68 84 |
|
MVS_111021_LR | | | 99.41 34 | 99.33 25 | 99.65 59 | 99.77 42 | 99.51 63 | 98.94 306 | 99.85 6 | 98.82 35 | 99.65 53 | 99.74 101 | 98.51 58 | 99.80 147 | 98.83 75 | 99.89 32 | 99.64 98 |
|
test222 | | | | | | 99.75 57 | 99.49 64 | 98.91 309 | 99.49 106 | 96.42 250 | 99.34 123 | 99.65 137 | 98.28 73 | | | 99.69 92 | 99.72 71 |
|
test_prior3 | | | 99.21 57 | 99.05 61 | 99.68 52 | 99.67 95 | 99.48 65 | 98.96 300 | 99.56 49 | 98.34 67 | 99.01 199 | 99.52 189 | 98.68 51 | 99.83 130 | 97.96 155 | 99.74 81 | 99.74 60 |
|
test_prior | | | | | 99.68 52 | 99.67 95 | 99.48 65 | | 99.56 49 | | | | | 99.83 130 | | | 99.74 60 |
|
MVS_111021_HR | | | 99.41 34 | 99.32 26 | 99.66 55 | 99.72 77 | 99.47 67 | 98.95 304 | 99.85 6 | 98.82 35 | 99.54 80 | 99.73 106 | 98.51 58 | 99.74 167 | 98.91 61 | 99.88 35 | 99.77 51 |
|
Anonymous20240521 | | | 98.30 147 | 98.00 160 | 99.18 139 | 98.98 248 | 99.46 68 | 99.78 22 | 99.49 106 | 96.91 216 | 98.00 289 | 99.25 265 | 96.51 124 | 99.38 232 | 98.15 141 | 94.95 288 | 98.71 223 |
|
CPTT-MVS | | | 99.11 75 | 98.90 85 | 99.74 45 | 99.80 34 | 99.46 68 | 99.59 96 | 99.49 106 | 97.03 208 | 99.63 55 | 99.69 121 | 97.27 101 | 99.96 19 | 97.82 166 | 99.84 59 | 99.81 35 |
|
FC-MVSNet-test | | | 98.75 123 | 98.62 122 | 99.15 143 | 99.08 231 | 99.45 70 | 99.86 8 | 99.60 35 | 98.23 76 | 98.70 244 | 99.82 47 | 96.80 114 | 99.22 274 | 99.07 48 | 96.38 258 | 98.79 208 |
|
Regformer-1 | | | 99.53 9 | 99.47 8 | 99.72 49 | 99.71 83 | 99.44 71 | 99.49 148 | 99.46 143 | 98.95 24 | 99.83 12 | 99.76 91 | 99.01 12 | 99.93 56 | 99.17 39 | 99.87 39 | 99.80 41 |
|
PAPM_NR | | | 99.04 87 | 98.84 96 | 99.66 55 | 99.74 68 | 99.44 71 | 99.39 191 | 99.38 193 | 97.70 141 | 99.28 136 | 99.28 261 | 98.34 70 | 99.85 116 | 96.96 233 | 99.45 106 | 99.69 80 |
|
alignmvs | | | 98.81 116 | 98.56 129 | 99.58 73 | 99.43 157 | 99.42 73 | 99.51 134 | 98.96 283 | 98.61 51 | 99.35 120 | 98.92 293 | 94.78 188 | 99.77 160 | 99.35 19 | 98.11 205 | 99.54 118 |
|
Regformer-4 | | | 99.59 2 | 99.54 4 | 99.73 47 | 99.76 45 | 99.41 74 | 99.58 103 | 99.49 106 | 99.02 10 | 99.88 3 | 99.80 68 | 99.00 18 | 99.94 41 | 99.45 15 | 99.92 12 | 99.84 13 |
|
CNLPA | | | 99.14 64 | 98.99 72 | 99.59 70 | 99.58 125 | 99.41 74 | 99.16 252 | 99.44 164 | 98.45 60 | 99.19 169 | 99.49 198 | 98.08 79 | 99.89 96 | 97.73 177 | 99.75 79 | 99.48 135 |
|
DELS-MVS | | | 99.48 17 | 99.42 11 | 99.65 59 | 99.72 77 | 99.40 76 | 99.05 276 | 99.66 25 | 99.14 6 | 99.57 70 | 99.80 68 | 98.46 61 | 99.94 41 | 99.57 4 | 99.84 59 | 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 |
HyFIR lowres test | | | 99.11 75 | 98.92 82 | 99.65 59 | 99.90 3 | 99.37 77 | 99.02 285 | 99.91 3 | 97.67 144 | 99.59 66 | 99.75 96 | 95.90 141 | 99.73 174 | 99.53 6 | 99.02 134 | 99.86 6 |
|
MVS_0304 | | | 99.06 84 | 98.86 93 | 99.66 55 | 99.51 137 | 99.36 78 | 99.22 243 | 99.51 86 | 98.95 24 | 99.58 67 | 99.65 137 | 93.74 234 | 99.98 5 | 99.66 1 | 99.95 6 | 99.64 98 |
|
casdiffmvs1 | | | 99.23 56 | 99.11 57 | 99.58 73 | 99.53 133 | 99.36 78 | 99.76 28 | 99.43 172 | 97.99 109 | 99.52 83 | 99.84 36 | 97.50 94 | 99.77 160 | 99.42 17 | 98.97 139 | 99.61 106 |
|
UniMVSNet (Re) | | | 98.29 149 | 98.00 160 | 99.13 147 | 99.00 243 | 99.36 78 | 99.49 148 | 99.51 86 | 97.95 112 | 98.97 209 | 99.13 275 | 96.30 131 | 99.38 232 | 98.36 128 | 93.34 317 | 98.66 260 |
|
原ACMM1 | | | | | 99.65 59 | 99.73 73 | 99.33 81 | | 99.47 133 | 97.46 160 | 99.12 179 | 99.66 136 | 98.67 53 | 99.91 75 | 97.70 182 | 99.69 92 | 99.71 78 |
|
canonicalmvs | | | 99.02 90 | 98.86 93 | 99.51 89 | 99.42 158 | 99.32 82 | 99.80 19 | 99.48 117 | 98.63 49 | 99.31 127 | 98.81 302 | 97.09 105 | 99.75 166 | 99.27 30 | 97.90 211 | 99.47 139 |
|
XXY-MVS | | | 98.38 142 | 98.09 152 | 99.24 134 | 99.26 197 | 99.32 82 | 99.56 116 | 99.55 56 | 97.45 163 | 98.71 238 | 99.83 40 | 93.23 238 | 99.63 206 | 98.88 62 | 96.32 260 | 98.76 214 |
|
IS-MVSNet | | | 99.05 86 | 98.87 89 | 99.57 75 | 99.73 73 | 99.32 82 | 99.75 36 | 99.20 256 | 98.02 104 | 99.56 71 | 99.86 23 | 96.54 123 | 99.67 195 | 98.09 144 | 99.13 125 | 99.73 65 |
|
API-MVS | | | 99.04 87 | 99.03 66 | 99.06 151 | 99.40 166 | 99.31 85 | 99.55 122 | 99.56 49 | 98.54 54 | 99.33 124 | 99.39 230 | 98.76 42 | 99.78 158 | 96.98 231 | 99.78 74 | 98.07 316 |
|
Regformer-3 | | | 99.57 6 | 99.53 5 | 99.68 52 | 99.76 45 | 99.29 86 | 99.58 103 | 99.44 164 | 99.01 13 | 99.87 7 | 99.80 68 | 98.97 20 | 99.91 75 | 99.44 16 | 99.92 12 | 99.83 24 |
|
Fast-Effi-MVS+ | | | 98.70 125 | 98.43 132 | 99.51 89 | 99.51 137 | 99.28 87 | 99.52 130 | 99.47 133 | 96.11 276 | 99.01 199 | 99.34 249 | 96.20 134 | 99.84 122 | 97.88 161 | 98.82 153 | 99.39 153 |
|
PatchMatch-RL | | | 98.84 115 | 98.62 122 | 99.52 87 | 99.71 83 | 99.28 87 | 99.06 274 | 99.77 9 | 97.74 136 | 99.50 87 | 99.53 184 | 95.41 153 | 99.84 122 | 97.17 221 | 99.64 100 | 99.44 147 |
|
F-COLMAP | | | 99.19 58 | 99.04 64 | 99.64 64 | 99.78 36 | 99.27 89 | 99.42 178 | 99.54 63 | 97.29 178 | 99.41 104 | 99.59 162 | 98.42 66 | 99.93 56 | 98.19 136 | 99.69 92 | 99.73 65 |
|
NR-MVSNet | | | 97.97 195 | 97.61 213 | 99.02 155 | 98.87 277 | 99.26 90 | 99.47 158 | 99.42 175 | 97.63 147 | 97.08 306 | 99.50 195 | 95.07 168 | 99.13 284 | 97.86 163 | 93.59 315 | 98.68 238 |
|
WR-MVS | | | 98.06 176 | 97.73 199 | 99.06 151 | 98.86 280 | 99.25 91 | 99.19 249 | 99.35 206 | 97.30 177 | 98.66 247 | 99.43 217 | 93.94 225 | 99.21 278 | 98.58 104 | 94.28 304 | 98.71 223 |
|
CP-MVSNet | | | 98.09 173 | 97.78 188 | 99.01 156 | 98.97 252 | 99.24 92 | 99.67 59 | 99.46 143 | 97.25 181 | 98.48 264 | 99.64 144 | 93.79 230 | 99.06 291 | 98.63 96 | 94.10 308 | 98.74 219 |
|
DeepC-MVS | | 98.35 2 | 99.30 46 | 99.19 49 | 99.64 64 | 99.82 29 | 99.23 93 | 99.62 85 | 99.55 56 | 98.94 26 | 99.63 55 | 99.95 2 | 95.82 144 | 99.94 41 | 99.37 18 | 99.97 3 | 99.73 65 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
tfpnnormal | | | 97.84 213 | 97.47 228 | 98.98 160 | 99.20 205 | 99.22 94 | 99.64 80 | 99.61 32 | 96.32 256 | 98.27 276 | 99.70 115 | 93.35 237 | 99.44 225 | 95.69 275 | 95.40 276 | 98.27 311 |
|
ab-mvs | | | 98.86 106 | 98.63 118 | 99.54 78 | 99.64 109 | 99.19 95 | 99.44 166 | 99.54 63 | 97.77 132 | 99.30 128 | 99.81 57 | 94.20 215 | 99.93 56 | 99.17 39 | 98.82 153 | 99.49 133 |
|
MSDG | | | 98.98 96 | 98.80 100 | 99.53 83 | 99.76 45 | 99.19 95 | 98.75 321 | 99.55 56 | 97.25 181 | 99.47 92 | 99.77 88 | 97.82 85 | 99.87 106 | 96.93 236 | 99.90 24 | 99.54 118 |
|
0601test | | | 98.86 106 | 98.63 118 | 99.54 78 | 99.49 145 | 99.18 97 | 99.50 139 | 99.07 271 | 98.22 77 | 99.61 60 | 99.51 192 | 95.37 154 | 99.84 122 | 98.60 102 | 98.33 175 | 99.59 111 |
|
CANet | | | 99.25 54 | 99.14 53 | 99.59 70 | 99.41 161 | 99.16 98 | 99.35 207 | 99.57 44 | 98.82 35 | 99.51 86 | 99.61 157 | 96.46 125 | 99.95 34 | 99.59 2 | 99.98 2 | 99.65 92 |
|
MSLP-MVS++ | | | 99.46 21 | 99.47 8 | 99.44 103 | 99.60 122 | 99.16 98 | 99.41 182 | 99.71 13 | 98.98 19 | 99.45 95 | 99.78 82 | 99.19 4 | 99.54 215 | 99.28 28 | 99.84 59 | 99.63 102 |
|
WTY-MVS | | | 99.06 84 | 98.88 88 | 99.61 68 | 99.62 116 | 99.16 98 | 99.37 198 | 99.56 49 | 98.04 101 | 99.53 81 | 99.62 153 | 96.84 113 | 99.94 41 | 98.85 71 | 98.49 170 | 99.72 71 |
|
EI-MVSNet-Vis-set | | | 99.58 3 | 99.56 3 | 99.64 64 | 99.78 36 | 99.15 101 | 99.61 91 | 99.45 155 | 99.01 13 | 99.89 2 | 99.82 47 | 99.01 12 | 99.92 65 | 99.56 5 | 99.95 6 | 99.85 9 |
|
EI-MVSNet-UG-set | | | 99.58 3 | 99.57 1 | 99.64 64 | 99.78 36 | 99.14 102 | 99.60 94 | 99.45 155 | 99.01 13 | 99.90 1 | 99.83 40 | 98.98 19 | 99.93 56 | 99.59 2 | 99.95 6 | 99.86 6 |
|
MVS_Test | | | 99.10 78 | 98.97 75 | 99.48 92 | 99.49 145 | 99.14 102 | 99.67 59 | 99.34 214 | 97.31 176 | 99.58 67 | 99.76 91 | 97.65 91 | 99.82 139 | 98.87 66 | 99.07 131 | 99.46 143 |
|
Effi-MVS+ | | | 98.81 116 | 98.59 127 | 99.48 92 | 99.46 151 | 99.12 104 | 98.08 346 | 99.50 101 | 97.50 158 | 99.38 111 | 99.41 222 | 96.37 129 | 99.81 143 | 99.11 45 | 98.54 167 | 99.51 129 |
|
casdiffmvs | | | 99.09 79 | 98.97 75 | 99.47 96 | 99.47 149 | 99.10 105 | 99.74 41 | 99.38 193 | 97.86 119 | 99.32 125 | 99.79 76 | 97.08 107 | 99.77 160 | 99.24 32 | 98.82 153 | 99.54 118 |
|
diffmvs1 | | | 99.12 70 | 99.00 71 | 99.48 92 | 99.51 137 | 99.10 105 | 99.61 91 | 99.49 106 | 97.67 144 | 99.36 116 | 99.74 101 | 97.67 90 | 99.88 103 | 98.95 57 | 98.99 136 | 99.47 139 |
|
Vis-MVSNet | | | 99.12 70 | 98.97 75 | 99.56 77 | 99.78 36 | 99.10 105 | 99.68 57 | 99.66 25 | 98.49 57 | 99.86 8 | 99.87 20 | 94.77 192 | 99.84 122 | 99.19 36 | 99.41 109 | 99.74 60 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
PCF-MVS | | 97.08 14 | 97.66 247 | 97.06 267 | 99.47 96 | 99.61 120 | 99.09 108 | 98.04 347 | 99.25 251 | 91.24 337 | 98.51 261 | 99.70 115 | 94.55 203 | 99.91 75 | 92.76 326 | 99.85 54 | 99.42 150 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
HY-MVS | | 97.30 7 | 98.85 113 | 98.64 117 | 99.47 96 | 99.42 158 | 99.08 109 | 99.62 85 | 99.36 202 | 97.39 171 | 99.28 136 | 99.68 126 | 96.44 127 | 99.92 65 | 98.37 126 | 98.22 185 | 99.40 152 |
|
PVSNet_Blended_VisFu | | | 99.36 40 | 99.28 40 | 99.61 68 | 99.86 20 | 99.07 110 | 99.47 158 | 99.93 2 | 97.66 146 | 99.71 33 | 99.86 23 | 97.73 88 | 99.96 19 | 99.47 13 | 99.82 67 | 99.79 45 |
|
PS-CasMVS | | | 97.93 201 | 97.59 215 | 98.95 165 | 98.99 244 | 99.06 111 | 99.68 57 | 99.52 77 | 97.13 191 | 98.31 273 | 99.68 126 | 92.44 271 | 99.05 292 | 98.51 115 | 94.08 309 | 98.75 216 |
|
EPP-MVSNet | | | 99.13 65 | 98.99 72 | 99.53 83 | 99.65 108 | 99.06 111 | 99.81 15 | 99.33 222 | 97.43 165 | 99.60 63 | 99.88 15 | 97.14 104 | 99.84 122 | 99.13 43 | 98.94 142 | 99.69 80 |
|
conf0.01 | | | 98.21 159 | 97.89 173 | 99.15 143 | 99.76 45 | 99.04 113 | 99.67 59 | 97.71 344 | 97.10 197 | 99.55 74 | 99.54 177 | 92.70 254 | 99.79 150 | 96.90 239 | 98.12 199 | 98.61 283 |
|
conf0.002 | | | 98.21 159 | 97.89 173 | 99.15 143 | 99.76 45 | 99.04 113 | 99.67 59 | 97.71 344 | 97.10 197 | 99.55 74 | 99.54 177 | 92.70 254 | 99.79 150 | 96.90 239 | 98.12 199 | 98.61 283 |
|
thresconf0.02 | | | 98.24 152 | 97.89 173 | 99.27 126 | 99.76 45 | 99.04 113 | 99.67 59 | 97.71 344 | 97.10 197 | 99.55 74 | 99.54 177 | 92.70 254 | 99.79 150 | 96.90 239 | 98.12 199 | 98.97 188 |
|
tfpn_n400 | | | 98.24 152 | 97.89 173 | 99.27 126 | 99.76 45 | 99.04 113 | 99.67 59 | 97.71 344 | 97.10 197 | 99.55 74 | 99.54 177 | 92.70 254 | 99.79 150 | 96.90 239 | 98.12 199 | 98.97 188 |
|
tfpnconf | | | 98.24 152 | 97.89 173 | 99.27 126 | 99.76 45 | 99.04 113 | 99.67 59 | 97.71 344 | 97.10 197 | 99.55 74 | 99.54 177 | 92.70 254 | 99.79 150 | 96.90 239 | 98.12 199 | 98.97 188 |
|
tfpnview11 | | | 98.24 152 | 97.89 173 | 99.27 126 | 99.76 45 | 99.04 113 | 99.67 59 | 97.71 344 | 97.10 197 | 99.55 74 | 99.54 177 | 92.70 254 | 99.79 150 | 96.90 239 | 98.12 199 | 98.97 188 |
|
DI_MVS_plusplus_test | | | 97.45 263 | 96.79 272 | 99.44 103 | 97.76 329 | 99.04 113 | 99.21 246 | 98.61 324 | 97.74 136 | 94.01 331 | 98.83 300 | 87.38 334 | 99.83 130 | 98.63 96 | 98.90 147 | 99.44 147 |
|
PAPR | | | 98.63 132 | 98.34 137 | 99.51 89 | 99.40 166 | 99.03 120 | 98.80 316 | 99.36 202 | 96.33 255 | 99.00 206 | 99.12 278 | 98.46 61 | 99.84 122 | 95.23 285 | 99.37 114 | 99.66 88 |
|
MVSTER | | | 98.49 134 | 98.32 139 | 99.00 158 | 99.35 174 | 99.02 121 | 99.54 125 | 99.38 193 | 97.41 169 | 99.20 166 | 99.73 106 | 93.86 229 | 99.36 240 | 98.87 66 | 97.56 223 | 98.62 274 |
|
1112_ss | | | 98.98 96 | 98.77 103 | 99.59 70 | 99.68 94 | 99.02 121 | 99.25 236 | 99.48 117 | 97.23 184 | 99.13 176 | 99.58 165 | 96.93 112 | 99.90 88 | 98.87 66 | 98.78 157 | 99.84 13 |
|
LFMVS | | | 97.90 206 | 97.35 249 | 99.54 78 | 99.52 135 | 99.01 123 | 99.39 191 | 98.24 333 | 97.10 197 | 99.65 53 | 99.79 76 | 84.79 343 | 99.91 75 | 99.28 28 | 98.38 174 | 99.69 80 |
|
PLC | | 97.94 4 | 99.02 90 | 98.85 95 | 99.53 83 | 99.66 105 | 99.01 123 | 99.24 238 | 99.52 77 | 96.85 219 | 99.27 140 | 99.48 204 | 98.25 74 | 99.91 75 | 97.76 173 | 99.62 103 | 99.65 92 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
testing_2 | | | 94.44 313 | 92.93 319 | 98.98 160 | 94.16 347 | 99.00 125 | 99.42 178 | 99.28 243 | 96.60 235 | 84.86 350 | 96.84 344 | 70.91 352 | 99.27 262 | 98.23 135 | 96.08 264 | 98.68 238 |
|
test_normal | | | 97.44 264 | 96.77 274 | 99.44 103 | 97.75 330 | 99.00 125 | 99.10 267 | 98.64 321 | 97.71 139 | 93.93 334 | 98.82 301 | 87.39 333 | 99.83 130 | 98.61 100 | 98.97 139 | 99.49 133 |
|
UniMVSNet_NR-MVSNet | | | 98.22 156 | 97.97 164 | 98.96 163 | 98.92 267 | 98.98 127 | 99.48 153 | 99.53 73 | 97.76 133 | 98.71 238 | 99.46 212 | 96.43 128 | 99.22 274 | 98.57 106 | 92.87 323 | 98.69 233 |
|
DU-MVS | | | 98.08 175 | 97.79 186 | 98.96 163 | 98.87 277 | 98.98 127 | 99.41 182 | 99.45 155 | 97.87 118 | 98.71 238 | 99.50 195 | 94.82 185 | 99.22 274 | 98.57 106 | 92.87 323 | 98.68 238 |
|
FMVSNet3 | | | 98.03 185 | 97.76 195 | 98.84 204 | 99.39 168 | 98.98 127 | 99.40 189 | 99.38 193 | 96.67 229 | 99.07 190 | 99.28 261 | 92.93 243 | 98.98 301 | 97.10 223 | 96.65 251 | 98.56 296 |
|
xiu_mvs_v1_base_debu | | | 99.29 48 | 99.27 42 | 99.34 111 | 99.63 112 | 98.97 130 | 99.12 259 | 99.51 86 | 98.86 31 | 99.84 9 | 99.47 208 | 98.18 76 | 99.99 1 | 99.50 8 | 99.31 115 | 99.08 174 |
|
xiu_mvs_v1_base | | | 99.29 48 | 99.27 42 | 99.34 111 | 99.63 112 | 98.97 130 | 99.12 259 | 99.51 86 | 98.86 31 | 99.84 9 | 99.47 208 | 98.18 76 | 99.99 1 | 99.50 8 | 99.31 115 | 99.08 174 |
|
xiu_mvs_v1_base_debi | | | 99.29 48 | 99.27 42 | 99.34 111 | 99.63 112 | 98.97 130 | 99.12 259 | 99.51 86 | 98.86 31 | 99.84 9 | 99.47 208 | 98.18 76 | 99.99 1 | 99.50 8 | 99.31 115 | 99.08 174 |
|
sss | | | 99.17 61 | 99.05 61 | 99.53 83 | 99.62 116 | 98.97 130 | 99.36 202 | 99.62 31 | 97.83 125 | 99.67 45 | 99.65 137 | 97.37 99 | 99.95 34 | 99.19 36 | 99.19 122 | 99.68 84 |
|
anonymousdsp | | | 98.44 137 | 98.28 142 | 98.94 166 | 98.50 317 | 98.96 134 | 99.77 25 | 99.50 101 | 97.07 204 | 98.87 220 | 99.77 88 | 94.76 193 | 99.28 259 | 98.66 93 | 97.60 219 | 98.57 295 |
|
testdata | | | | | 99.54 78 | 99.75 57 | 98.95 135 | | 99.51 86 | 97.07 204 | 99.43 99 | 99.70 115 | 98.87 29 | 99.94 41 | 97.76 173 | 99.64 100 | 99.72 71 |
|
MVS | | | 97.28 269 | 96.55 276 | 99.48 92 | 98.78 290 | 98.95 135 | 99.27 226 | 99.39 187 | 83.53 350 | 98.08 284 | 99.54 177 | 96.97 110 | 99.87 106 | 94.23 309 | 99.16 123 | 99.63 102 |
|
Test_1112_low_res | | | 98.89 102 | 98.66 116 | 99.57 75 | 99.69 91 | 98.95 135 | 99.03 282 | 99.47 133 | 96.98 210 | 99.15 175 | 99.23 268 | 96.77 117 | 99.89 96 | 98.83 75 | 98.78 157 | 99.86 6 |
|
PS-MVSNAJ | | | 99.32 44 | 99.32 26 | 99.30 120 | 99.57 127 | 98.94 138 | 98.97 298 | 99.46 143 | 98.92 28 | 99.71 33 | 99.24 267 | 99.01 12 | 99.98 5 | 99.35 19 | 99.66 97 | 98.97 188 |
|
VPNet | | | 97.84 213 | 97.44 237 | 99.01 156 | 99.21 203 | 98.94 138 | 99.48 153 | 99.57 44 | 98.38 65 | 99.28 136 | 99.73 106 | 88.89 317 | 99.39 231 | 99.19 36 | 93.27 318 | 98.71 223 |
|
MVSFormer | | | 99.17 61 | 99.12 55 | 99.29 123 | 99.51 137 | 98.94 138 | 99.88 1 | 99.46 143 | 97.55 153 | 99.80 17 | 99.65 137 | 97.39 96 | 99.28 259 | 99.03 50 | 99.85 54 | 99.65 92 |
|
lupinMVS | | | 99.13 65 | 99.01 70 | 99.46 99 | 99.51 137 | 98.94 138 | 99.05 276 | 99.16 260 | 97.86 119 | 99.80 17 | 99.56 171 | 97.39 96 | 99.86 110 | 98.94 59 | 99.85 54 | 99.58 114 |
|
Test4 | | | 95.05 308 | 93.67 316 | 99.22 137 | 96.07 340 | 98.94 138 | 99.20 248 | 99.27 248 | 97.71 139 | 89.96 348 | 97.59 338 | 66.18 355 | 99.25 268 | 98.06 151 | 98.96 141 | 99.47 139 |
|
xiu_mvs_v2_base | | | 99.26 53 | 99.25 46 | 99.29 123 | 99.53 133 | 98.91 143 | 99.02 285 | 99.45 155 | 98.80 39 | 99.71 33 | 99.26 264 | 98.94 25 | 99.98 5 | 99.34 23 | 99.23 119 | 98.98 187 |
|
test_djsdf | | | 98.67 128 | 98.57 128 | 98.98 160 | 98.70 301 | 98.91 143 | 99.88 1 | 99.46 143 | 97.55 153 | 99.22 160 | 99.88 15 | 95.73 147 | 99.28 259 | 99.03 50 | 97.62 218 | 98.75 216 |
|
Vis-MVSNet (Re-imp) | | | 98.87 103 | 98.72 107 | 99.31 117 | 99.71 83 | 98.88 145 | 99.80 19 | 99.44 164 | 97.91 117 | 99.36 116 | 99.78 82 | 95.49 152 | 99.43 229 | 97.91 159 | 99.11 126 | 99.62 104 |
|
pmmvs4 | | | 98.13 167 | 97.90 169 | 98.81 207 | 98.61 311 | 98.87 146 | 98.99 291 | 99.21 255 | 96.44 248 | 99.06 194 | 99.58 165 | 95.90 141 | 99.11 287 | 97.18 220 | 96.11 263 | 98.46 303 |
|
jason | | | 99.13 65 | 99.03 66 | 99.45 100 | 99.46 151 | 98.87 146 | 99.12 259 | 99.26 249 | 98.03 103 | 99.79 19 | 99.65 137 | 97.02 108 | 99.85 116 | 99.02 52 | 99.90 24 | 99.65 92 |
jason: jason. |
Patchmtry | | | 97.75 232 | 97.40 243 | 98.81 207 | 99.10 228 | 98.87 146 | 99.11 265 | 99.33 222 | 94.83 295 | 98.81 228 | 99.38 231 | 94.33 211 | 99.02 296 | 96.10 266 | 95.57 274 | 98.53 297 |
|
TransMVSNet (Re) | | | 97.15 272 | 96.58 275 | 98.86 200 | 99.12 223 | 98.85 149 | 99.49 148 | 98.91 290 | 95.48 289 | 97.16 305 | 99.80 68 | 93.38 236 | 99.11 287 | 94.16 311 | 91.73 328 | 98.62 274 |
|
V42 | | | 98.06 176 | 97.79 186 | 98.86 200 | 98.98 248 | 98.84 150 | 99.69 48 | 99.34 214 | 96.53 239 | 99.30 128 | 99.37 235 | 94.67 198 | 99.32 250 | 97.57 191 | 94.66 296 | 98.42 304 |
|
WR-MVS_H | | | 98.13 167 | 97.87 180 | 98.90 182 | 99.02 241 | 98.84 150 | 99.70 45 | 99.59 38 | 97.27 179 | 98.40 267 | 99.19 271 | 95.53 150 | 99.23 271 | 98.34 129 | 93.78 314 | 98.61 283 |
|
FMVSNet2 | | | 97.72 237 | 97.36 247 | 98.80 209 | 99.51 137 | 98.84 150 | 99.45 162 | 99.42 175 | 96.49 240 | 98.86 225 | 99.29 260 | 90.26 303 | 98.98 301 | 96.44 261 | 96.56 254 | 98.58 294 |
|
v15 | | | 96.28 288 | 95.62 294 | 98.25 262 | 98.94 260 | 98.83 153 | 99.76 28 | 99.29 236 | 94.52 305 | 94.02 330 | 97.61 335 | 95.02 170 | 98.13 325 | 94.53 296 | 86.92 343 | 97.80 330 |
|
v13 | | | 96.24 291 | 95.58 296 | 98.25 262 | 98.98 248 | 98.83 153 | 99.75 36 | 99.29 236 | 94.35 310 | 93.89 335 | 97.60 336 | 95.17 165 | 98.11 327 | 94.27 308 | 86.86 346 | 97.81 328 |
|
v6 | | | 98.12 169 | 97.84 181 | 98.94 166 | 98.94 260 | 98.83 153 | 99.66 68 | 99.34 214 | 96.49 240 | 99.30 128 | 99.37 235 | 94.95 174 | 99.34 246 | 97.77 172 | 94.74 290 | 98.67 249 |
|
v11 | | | 96.23 293 | 95.57 299 | 98.21 268 | 98.93 265 | 98.83 153 | 99.72 42 | 99.29 236 | 94.29 311 | 94.05 329 | 97.64 333 | 94.88 182 | 98.04 329 | 92.89 324 | 88.43 336 | 97.77 336 |
|
V14 | | | 96.26 289 | 95.60 295 | 98.26 258 | 98.94 260 | 98.83 153 | 99.76 28 | 99.29 236 | 94.49 306 | 93.96 332 | 97.66 332 | 94.99 173 | 98.13 325 | 94.41 299 | 86.90 344 | 97.80 330 |
|
V9 | | | 96.25 290 | 95.58 296 | 98.26 258 | 98.94 260 | 98.83 153 | 99.75 36 | 99.29 236 | 94.45 308 | 93.96 332 | 97.62 334 | 94.94 175 | 98.14 324 | 94.40 300 | 86.87 345 | 97.81 328 |
|
BH-RMVSNet | | | 98.41 140 | 98.08 153 | 99.40 107 | 99.41 161 | 98.83 153 | 99.30 217 | 98.77 304 | 97.70 141 | 98.94 212 | 99.65 137 | 92.91 246 | 99.74 167 | 96.52 259 | 99.55 104 | 99.64 98 |
|
v18 | | | 96.42 284 | 95.80 291 | 98.26 258 | 98.95 257 | 98.82 160 | 99.76 28 | 99.28 243 | 94.58 300 | 94.12 326 | 97.70 329 | 95.22 163 | 98.16 321 | 94.83 292 | 87.80 338 | 97.79 335 |
|
v2v482 | | | 98.06 176 | 97.77 192 | 98.92 174 | 98.90 270 | 98.82 160 | 99.57 109 | 99.36 202 | 96.65 230 | 99.19 169 | 99.35 246 | 94.20 215 | 99.25 268 | 97.72 181 | 94.97 286 | 98.69 233 |
|
v1neww | | | 98.12 169 | 97.84 181 | 98.93 169 | 98.97 252 | 98.81 162 | 99.66 68 | 99.35 206 | 96.49 240 | 99.29 132 | 99.37 235 | 95.02 170 | 99.32 250 | 97.73 177 | 94.73 291 | 98.67 249 |
|
v7new | | | 98.12 169 | 97.84 181 | 98.93 169 | 98.97 252 | 98.81 162 | 99.66 68 | 99.35 206 | 96.49 240 | 99.29 132 | 99.37 235 | 95.02 170 | 99.32 250 | 97.73 177 | 94.73 291 | 98.67 249 |
|
v16 | | | 96.39 286 | 95.76 292 | 98.26 258 | 98.96 255 | 98.81 162 | 99.76 28 | 99.28 243 | 94.57 301 | 94.10 327 | 97.70 329 | 95.04 169 | 98.16 321 | 94.70 294 | 87.77 339 | 97.80 330 |
|
v12 | | | 96.24 291 | 95.58 296 | 98.23 265 | 98.96 255 | 98.81 162 | 99.76 28 | 99.29 236 | 94.42 309 | 93.85 336 | 97.60 336 | 95.12 166 | 98.09 328 | 94.32 305 | 86.85 347 | 97.80 330 |
|
v8 | | | 97.95 200 | 97.63 212 | 98.93 169 | 98.95 257 | 98.81 162 | 99.80 19 | 99.41 177 | 96.03 281 | 99.10 184 | 99.42 219 | 94.92 178 | 99.30 256 | 96.94 235 | 94.08 309 | 98.66 260 |
|
v17 | | | 96.42 284 | 95.81 289 | 98.25 262 | 98.94 260 | 98.80 167 | 99.76 28 | 99.28 243 | 94.57 301 | 94.18 325 | 97.71 328 | 95.23 162 | 98.16 321 | 94.86 290 | 87.73 340 | 97.80 330 |
|
v1 | | | 98.05 182 | 97.76 195 | 98.93 169 | 98.92 267 | 98.80 167 | 99.57 109 | 99.35 206 | 96.39 254 | 99.28 136 | 99.36 242 | 94.86 183 | 99.32 250 | 97.38 209 | 94.72 293 | 98.68 238 |
|
PVSNet_BlendedMVS | | | 98.86 106 | 98.80 100 | 99.03 154 | 99.76 45 | 98.79 169 | 99.28 223 | 99.91 3 | 97.42 168 | 99.67 45 | 99.37 235 | 97.53 92 | 99.88 103 | 98.98 55 | 97.29 242 | 98.42 304 |
|
PVSNet_Blended | | | 99.08 82 | 98.97 75 | 99.42 106 | 99.76 45 | 98.79 169 | 98.78 318 | 99.91 3 | 96.74 224 | 99.67 45 | 99.49 198 | 97.53 92 | 99.88 103 | 98.98 55 | 99.85 54 | 99.60 107 |
|
v1141 | | | 98.05 182 | 97.76 195 | 98.91 178 | 98.91 269 | 98.78 171 | 99.57 109 | 99.35 206 | 96.41 252 | 99.23 158 | 99.36 242 | 94.93 177 | 99.27 262 | 97.38 209 | 94.72 293 | 98.68 238 |
|
divwei89l23v2f112 | | | 98.06 176 | 97.78 188 | 98.91 178 | 98.90 270 | 98.77 172 | 99.57 109 | 99.35 206 | 96.45 247 | 99.24 153 | 99.37 235 | 94.92 178 | 99.27 262 | 97.50 199 | 94.71 295 | 98.68 238 |
|
tfpn_ndepth | | | 98.17 163 | 97.84 181 | 99.15 143 | 99.75 57 | 98.76 173 | 99.61 91 | 97.39 354 | 96.92 215 | 99.61 60 | 99.38 231 | 92.19 274 | 99.86 110 | 97.57 191 | 98.13 197 | 98.82 205 |
|
diffmvs | | | 98.99 95 | 98.87 89 | 99.35 110 | 99.45 155 | 98.74 174 | 99.62 85 | 99.45 155 | 97.43 165 | 99.13 176 | 99.72 110 | 97.23 102 | 99.87 106 | 98.86 69 | 98.90 147 | 99.45 146 |
|
tfpn1000 | | | 98.33 144 | 98.02 158 | 99.25 131 | 99.78 36 | 98.73 175 | 99.70 45 | 97.55 352 | 97.48 159 | 99.69 38 | 99.53 184 | 92.37 272 | 99.85 116 | 97.82 166 | 98.26 184 | 99.16 165 |
|
CDS-MVSNet | | | 99.09 79 | 99.03 66 | 99.25 131 | 99.42 158 | 98.73 175 | 99.45 162 | 99.46 143 | 98.11 88 | 99.46 94 | 99.77 88 | 98.01 81 | 99.37 236 | 98.70 88 | 98.92 145 | 99.66 88 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
UGNet | | | 98.87 103 | 98.69 111 | 99.40 107 | 99.22 202 | 98.72 177 | 99.44 166 | 99.68 19 | 99.24 3 | 99.18 172 | 99.42 219 | 92.74 250 | 99.96 19 | 99.34 23 | 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 |
PMMVS | | | 98.80 119 | 98.62 122 | 99.34 111 | 99.27 195 | 98.70 178 | 98.76 320 | 99.31 229 | 97.34 173 | 99.21 163 | 99.07 280 | 97.20 103 | 99.82 139 | 98.56 109 | 98.87 150 | 99.52 124 |
|
v1192 | | | 97.81 219 | 97.44 237 | 98.91 178 | 98.88 274 | 98.68 179 | 99.51 134 | 99.34 214 | 96.18 269 | 99.20 166 | 99.34 249 | 94.03 223 | 99.36 240 | 95.32 284 | 95.18 280 | 98.69 233 |
|
v7 | | | 98.05 182 | 97.78 188 | 98.87 196 | 98.99 244 | 98.67 180 | 99.64 80 | 99.34 214 | 96.31 258 | 99.29 132 | 99.51 192 | 94.78 188 | 99.27 262 | 97.03 227 | 95.15 282 | 98.66 260 |
|
v10 | | | 97.85 211 | 97.52 219 | 98.86 200 | 98.99 244 | 98.67 180 | 99.75 36 | 99.41 177 | 95.70 287 | 98.98 208 | 99.41 222 | 94.75 194 | 99.23 271 | 96.01 269 | 94.63 298 | 98.67 249 |
|
v1144 | | | 97.98 192 | 97.69 202 | 98.85 203 | 98.87 277 | 98.66 182 | 99.54 125 | 99.35 206 | 96.27 261 | 99.23 158 | 99.35 246 | 94.67 198 | 99.23 271 | 96.73 250 | 95.16 281 | 98.68 238 |
|
v144192 | | | 97.92 204 | 97.60 214 | 98.87 196 | 98.83 283 | 98.65 183 | 99.55 122 | 99.34 214 | 96.20 267 | 99.32 125 | 99.40 226 | 94.36 210 | 99.26 267 | 96.37 264 | 95.03 285 | 98.70 228 |
|
1314 | | | 98.68 127 | 98.54 130 | 99.11 148 | 98.89 273 | 98.65 183 | 99.27 226 | 99.49 106 | 96.89 217 | 97.99 290 | 99.56 171 | 97.72 89 | 99.83 130 | 97.74 176 | 99.27 118 | 98.84 204 |
|
V4 | | | 97.80 222 | 97.51 221 | 98.67 222 | 98.79 286 | 98.63 185 | 99.87 4 | 99.44 164 | 95.87 284 | 99.01 199 | 99.46 212 | 94.52 205 | 99.33 247 | 96.64 258 | 93.97 311 | 98.05 317 |
|
MG-MVS | | | 99.13 65 | 99.02 69 | 99.45 100 | 99.57 127 | 98.63 185 | 99.07 270 | 99.34 214 | 98.99 18 | 99.61 60 | 99.82 47 | 97.98 82 | 99.87 106 | 97.00 229 | 99.80 70 | 99.85 9 |
|
pm-mvs1 | | | 97.68 243 | 97.28 259 | 98.88 192 | 99.06 234 | 98.62 187 | 99.50 139 | 99.45 155 | 96.32 256 | 97.87 293 | 99.79 76 | 92.47 267 | 99.35 243 | 97.54 195 | 93.54 316 | 98.67 249 |
|
v52 | | | 97.79 224 | 97.50 223 | 98.66 223 | 98.80 284 | 98.62 187 | 99.87 4 | 99.44 164 | 95.87 284 | 99.01 199 | 99.46 212 | 94.44 209 | 99.33 247 | 96.65 257 | 93.96 312 | 98.05 317 |
|
TranMVSNet+NR-MVSNet | | | 97.93 201 | 97.66 205 | 98.76 215 | 98.78 290 | 98.62 187 | 99.65 78 | 99.49 106 | 97.76 133 | 98.49 263 | 99.60 160 | 94.23 214 | 98.97 308 | 98.00 153 | 92.90 321 | 98.70 228 |
|
TSAR-MVS + GP. | | | 99.36 40 | 99.36 19 | 99.36 109 | 99.67 95 | 98.61 190 | 99.07 270 | 99.33 222 | 99.00 17 | 99.82 15 | 99.81 57 | 99.06 9 | 99.84 122 | 99.09 46 | 99.42 108 | 99.65 92 |
|
v7n | | | 97.87 209 | 97.52 219 | 98.92 174 | 98.76 294 | 98.58 191 | 99.84 9 | 99.46 143 | 96.20 267 | 98.91 215 | 99.70 115 | 94.89 181 | 99.44 225 | 96.03 268 | 93.89 313 | 98.75 216 |
|
TAMVS | | | 99.12 70 | 99.08 59 | 99.24 134 | 99.46 151 | 98.55 192 | 99.51 134 | 99.46 143 | 98.09 91 | 99.45 95 | 99.82 47 | 98.34 70 | 99.51 216 | 98.70 88 | 98.93 143 | 99.67 87 |
|
PEN-MVS | | | 97.76 228 | 97.44 237 | 98.72 217 | 98.77 293 | 98.54 193 | 99.78 22 | 99.51 86 | 97.06 206 | 98.29 275 | 99.64 144 | 92.63 262 | 98.89 311 | 98.09 144 | 93.16 319 | 98.72 221 |
|
Anonymous20231211 | | | 97.88 207 | 97.54 218 | 98.90 182 | 99.71 83 | 98.53 194 | 99.48 153 | 99.57 44 | 94.16 313 | 98.81 228 | 99.68 126 | 93.23 238 | 99.42 230 | 98.84 72 | 94.42 302 | 98.76 214 |
|
v1921920 | | | 97.80 222 | 97.45 231 | 98.84 204 | 98.80 284 | 98.53 194 | 99.52 130 | 99.34 214 | 96.15 273 | 99.24 153 | 99.47 208 | 93.98 224 | 99.29 258 | 95.40 282 | 95.13 283 | 98.69 233 |
|
PS-MVSNAJss | | | 98.92 101 | 98.92 82 | 98.90 182 | 98.78 290 | 98.53 194 | 99.78 22 | 99.54 63 | 98.07 95 | 99.00 206 | 99.76 91 | 99.01 12 | 99.37 236 | 99.13 43 | 97.23 243 | 98.81 206 |
|
COLMAP_ROB | | 97.56 6 | 98.86 106 | 98.75 106 | 99.17 140 | 99.88 11 | 98.53 194 | 99.34 210 | 99.59 38 | 97.55 153 | 98.70 244 | 99.89 10 | 95.83 143 | 99.90 88 | 98.10 143 | 99.90 24 | 99.08 174 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
mvs_anonymous | | | 99.03 89 | 98.99 72 | 99.16 141 | 99.38 169 | 98.52 198 | 99.51 134 | 99.38 193 | 97.79 130 | 99.38 111 | 99.81 57 | 97.30 100 | 99.45 220 | 99.35 19 | 98.99 136 | 99.51 129 |
|
CHOSEN 1792x2688 | | | 99.19 58 | 99.10 58 | 99.45 100 | 99.89 8 | 98.52 198 | 99.39 191 | 99.94 1 | 98.73 44 | 99.11 181 | 99.89 10 | 95.50 151 | 99.94 41 | 99.50 8 | 99.97 3 | 99.89 2 |
|
mvs_tets | | | 98.40 141 | 98.23 144 | 98.91 178 | 98.67 305 | 98.51 200 | 99.66 68 | 99.53 73 | 98.19 78 | 98.65 253 | 99.81 57 | 92.75 248 | 99.44 225 | 99.31 26 | 97.48 232 | 98.77 212 |
|
CR-MVSNet | | | 98.17 163 | 97.93 168 | 98.87 196 | 99.18 210 | 98.49 201 | 99.22 243 | 99.33 222 | 96.96 211 | 99.56 71 | 99.38 231 | 94.33 211 | 99.00 299 | 94.83 292 | 98.58 163 | 99.14 166 |
|
RPMNet | | | 96.61 279 | 95.85 287 | 98.87 196 | 99.18 210 | 98.49 201 | 99.22 243 | 99.08 268 | 88.72 346 | 99.56 71 | 97.38 341 | 94.08 222 | 99.00 299 | 86.87 344 | 98.58 163 | 99.14 166 |
|
AllTest | | | 98.87 103 | 98.72 107 | 99.31 117 | 99.86 20 | 98.48 203 | 99.56 116 | 99.61 32 | 97.85 122 | 99.36 116 | 99.85 27 | 95.95 137 | 99.85 116 | 96.66 255 | 99.83 63 | 99.59 111 |
|
TestCases | | | | | 99.31 117 | 99.86 20 | 98.48 203 | | 99.61 32 | 97.85 122 | 99.36 116 | 99.85 27 | 95.95 137 | 99.85 116 | 96.66 255 | 99.83 63 | 99.59 111 |
|
Anonymous20240529 | | | 98.09 173 | 97.68 203 | 99.34 111 | 99.66 105 | 98.44 205 | 99.40 189 | 99.43 172 | 93.67 319 | 99.22 160 | 99.89 10 | 90.23 306 | 99.93 56 | 99.26 31 | 98.33 175 | 99.66 88 |
|
jajsoiax | | | 98.43 138 | 98.28 142 | 98.88 192 | 98.60 312 | 98.43 206 | 99.82 13 | 99.53 73 | 98.19 78 | 98.63 255 | 99.80 68 | 93.22 240 | 99.44 225 | 99.22 34 | 97.50 228 | 98.77 212 |
|
v1240 | | | 97.69 241 | 97.32 255 | 98.79 210 | 98.85 281 | 98.43 206 | 99.48 153 | 99.36 202 | 96.11 276 | 99.27 140 | 99.36 242 | 93.76 232 | 99.24 270 | 94.46 298 | 95.23 279 | 98.70 228 |
|
CANet_DTU | | | 98.97 98 | 98.87 89 | 99.25 131 | 99.33 178 | 98.42 208 | 99.08 269 | 99.30 231 | 99.16 5 | 99.43 99 | 99.75 96 | 95.27 158 | 99.97 11 | 98.56 109 | 99.95 6 | 99.36 154 |
|
PatchT | | | 97.03 276 | 96.44 277 | 98.79 210 | 98.99 244 | 98.34 209 | 99.16 252 | 99.07 271 | 92.13 331 | 99.52 83 | 97.31 343 | 94.54 204 | 98.98 301 | 88.54 337 | 98.73 159 | 99.03 181 |
|
Baseline_NR-MVSNet | | | 97.76 228 | 97.45 231 | 98.68 220 | 99.09 230 | 98.29 210 | 99.41 182 | 98.85 296 | 95.65 288 | 98.63 255 | 99.67 131 | 94.82 185 | 99.10 289 | 98.07 150 | 92.89 322 | 98.64 265 |
|
CSCG | | | 99.32 44 | 99.32 26 | 99.32 116 | 99.85 23 | 98.29 210 | 99.71 44 | 99.66 25 | 98.11 88 | 99.41 104 | 99.80 68 | 98.37 69 | 99.96 19 | 98.99 54 | 99.96 5 | 99.72 71 |
|
PAPM | | | 97.59 251 | 97.09 266 | 99.07 150 | 99.06 234 | 98.26 212 | 98.30 341 | 99.10 266 | 94.88 294 | 98.08 284 | 99.34 249 | 96.27 132 | 99.64 201 | 89.87 334 | 98.92 145 | 99.31 158 |
|
OMC-MVS | | | 99.08 82 | 99.04 64 | 99.20 138 | 99.67 95 | 98.22 213 | 99.28 223 | 99.52 77 | 98.07 95 | 99.66 50 | 99.81 57 | 97.79 86 | 99.78 158 | 97.79 169 | 99.81 68 | 99.60 107 |
|
EPNet | | | 98.86 106 | 98.71 109 | 99.30 120 | 97.20 338 | 98.18 214 | 99.62 85 | 98.91 290 | 99.28 2 | 98.63 255 | 99.81 57 | 95.96 136 | 99.99 1 | 99.24 32 | 99.72 85 | 99.73 65 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
Anonymous202405211 | | | 98.30 147 | 97.98 163 | 99.26 130 | 99.57 127 | 98.16 215 | 99.41 182 | 98.55 327 | 96.03 281 | 99.19 169 | 99.74 101 | 91.87 281 | 99.92 65 | 99.16 41 | 98.29 179 | 99.70 79 |
|
GG-mvs-BLEND | | | | | 98.45 241 | 98.55 315 | 98.16 215 | 99.43 171 | 93.68 362 | | 97.23 303 | 98.46 317 | 89.30 314 | 99.22 274 | 95.43 281 | 98.22 185 | 97.98 322 |
|
gg-mvs-nofinetune | | | 96.17 296 | 95.32 303 | 98.73 216 | 98.79 286 | 98.14 217 | 99.38 196 | 94.09 361 | 91.07 339 | 98.07 287 | 91.04 356 | 89.62 312 | 99.35 243 | 96.75 249 | 99.09 129 | 98.68 238 |
|
DTE-MVSNet | | | 97.51 258 | 97.19 264 | 98.46 240 | 98.63 308 | 98.13 218 | 99.84 9 | 99.48 117 | 96.68 228 | 97.97 291 | 99.67 131 | 92.92 244 | 98.56 317 | 96.88 245 | 92.60 326 | 98.70 228 |
|
VDDNet | | | 97.55 252 | 97.02 268 | 99.16 141 | 99.49 145 | 98.12 219 | 99.38 196 | 99.30 231 | 95.35 290 | 99.68 39 | 99.90 7 | 82.62 349 | 99.93 56 | 99.31 26 | 98.13 197 | 99.42 150 |
|
thres200 | | | 97.61 250 | 97.28 259 | 98.62 224 | 99.64 109 | 98.03 220 | 99.26 234 | 98.74 308 | 97.68 143 | 99.09 188 | 98.32 320 | 91.66 291 | 99.81 143 | 92.88 325 | 98.22 185 | 98.03 320 |
|
IterMVS-LS | | | 98.46 136 | 98.42 133 | 98.58 227 | 99.59 124 | 98.00 221 | 99.37 198 | 99.43 172 | 96.94 213 | 99.07 190 | 99.59 162 | 97.87 83 | 99.03 295 | 98.32 132 | 95.62 273 | 98.71 223 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
GA-MVS | | | 97.85 211 | 97.47 228 | 99.00 158 | 99.38 169 | 97.99 222 | 98.57 331 | 99.15 261 | 97.04 207 | 98.90 217 | 99.30 258 | 89.83 309 | 99.38 232 | 96.70 252 | 98.33 175 | 99.62 104 |
|
EI-MVSNet | | | 98.67 128 | 98.67 113 | 98.68 220 | 99.35 174 | 97.97 223 | 99.50 139 | 99.38 193 | 96.93 214 | 99.20 166 | 99.83 40 | 97.87 83 | 99.36 240 | 98.38 125 | 97.56 223 | 98.71 223 |
|
tfpn200view9 | | | 97.72 237 | 97.38 245 | 98.72 217 | 99.69 91 | 97.96 224 | 99.50 139 | 98.73 317 | 97.83 125 | 99.17 173 | 98.45 318 | 91.67 289 | 99.83 130 | 93.22 319 | 98.18 189 | 98.37 308 |
|
thres400 | | | 97.77 227 | 97.38 245 | 98.92 174 | 99.69 91 | 97.96 224 | 99.50 139 | 98.73 317 | 97.83 125 | 99.17 173 | 98.45 318 | 91.67 289 | 99.83 130 | 93.22 319 | 98.18 189 | 98.96 194 |
|
thres600view7 | | | 97.86 210 | 97.51 221 | 98.92 174 | 99.72 77 | 97.95 226 | 99.59 96 | 98.74 308 | 97.94 113 | 99.27 140 | 98.62 309 | 91.75 283 | 99.86 110 | 93.73 314 | 98.19 188 | 98.96 194 |
|
CHOSEN 280x420 | | | 99.12 70 | 99.13 54 | 99.08 149 | 99.66 105 | 97.89 227 | 98.43 336 | 99.71 13 | 98.88 30 | 99.62 58 | 99.76 91 | 96.63 121 | 99.70 190 | 99.46 14 | 99.99 1 | 99.66 88 |
|
TR-MVS | | | 97.76 228 | 97.41 242 | 98.82 206 | 99.06 234 | 97.87 228 | 98.87 312 | 98.56 326 | 96.63 232 | 98.68 246 | 99.22 269 | 92.49 266 | 99.65 199 | 95.40 282 | 97.79 213 | 98.95 201 |
|
tfpn111 | | | 97.81 219 | 97.49 225 | 98.78 212 | 99.72 77 | 97.86 229 | 99.59 96 | 98.74 308 | 97.93 114 | 99.26 144 | 98.62 309 | 91.75 283 | 99.86 110 | 93.57 315 | 98.18 189 | 98.61 283 |
|
conf200view11 | | | 97.78 226 | 97.45 231 | 98.77 213 | 99.72 77 | 97.86 229 | 99.59 96 | 98.74 308 | 97.93 114 | 99.26 144 | 98.62 309 | 91.75 283 | 99.83 130 | 93.22 319 | 98.18 189 | 98.61 283 |
|
thres100view900 | | | 97.76 228 | 97.45 231 | 98.69 219 | 99.72 77 | 97.86 229 | 99.59 96 | 98.74 308 | 97.93 114 | 99.26 144 | 98.62 309 | 91.75 283 | 99.83 130 | 93.22 319 | 98.18 189 | 98.37 308 |
|
test0.0.03 1 | | | 97.71 240 | 97.42 241 | 98.56 230 | 98.41 320 | 97.82 232 | 98.78 318 | 98.63 322 | 97.34 173 | 98.05 288 | 98.98 290 | 94.45 207 | 98.98 301 | 95.04 288 | 97.15 247 | 98.89 202 |
|
view600 | | | 97.97 195 | 97.66 205 | 98.89 185 | 99.75 57 | 97.81 233 | 99.69 48 | 98.80 300 | 98.02 104 | 99.25 148 | 98.88 294 | 91.95 276 | 99.89 96 | 94.36 301 | 98.29 179 | 98.96 194 |
|
view800 | | | 97.97 195 | 97.66 205 | 98.89 185 | 99.75 57 | 97.81 233 | 99.69 48 | 98.80 300 | 98.02 104 | 99.25 148 | 98.88 294 | 91.95 276 | 99.89 96 | 94.36 301 | 98.29 179 | 98.96 194 |
|
conf0.05thres1000 | | | 97.97 195 | 97.66 205 | 98.89 185 | 99.75 57 | 97.81 233 | 99.69 48 | 98.80 300 | 98.02 104 | 99.25 148 | 98.88 294 | 91.95 276 | 99.89 96 | 94.36 301 | 98.29 179 | 98.96 194 |
|
tfpn | | | 97.97 195 | 97.66 205 | 98.89 185 | 99.75 57 | 97.81 233 | 99.69 48 | 98.80 300 | 98.02 104 | 99.25 148 | 98.88 294 | 91.95 276 | 99.89 96 | 94.36 301 | 98.29 179 | 98.96 194 |
|
JIA-IIPM | | | 97.50 259 | 97.02 268 | 98.93 169 | 98.73 296 | 97.80 237 | 99.30 217 | 98.97 281 | 91.73 335 | 98.91 215 | 94.86 350 | 95.10 167 | 99.71 184 | 97.58 189 | 97.98 209 | 99.28 160 |
|
mvs-test1 | | | 98.86 106 | 98.84 96 | 98.89 185 | 99.33 178 | 97.77 238 | 99.44 166 | 99.30 231 | 98.47 58 | 99.10 184 | 99.43 217 | 96.78 115 | 99.95 34 | 98.73 85 | 99.02 134 | 98.96 194 |
|
XVG-OURS-SEG-HR | | | 98.69 126 | 98.62 122 | 98.89 185 | 99.71 83 | 97.74 239 | 99.12 259 | 99.54 63 | 98.44 63 | 99.42 102 | 99.71 112 | 94.20 215 | 99.92 65 | 98.54 114 | 98.90 147 | 99.00 184 |
|
XVG-OURS | | | 98.73 124 | 98.68 112 | 98.88 192 | 99.70 89 | 97.73 240 | 98.92 307 | 99.55 56 | 98.52 56 | 99.45 95 | 99.84 36 | 95.27 158 | 99.91 75 | 98.08 148 | 98.84 152 | 99.00 184 |
|
v148 | | | 97.79 224 | 97.55 216 | 98.50 234 | 98.74 295 | 97.72 241 | 99.54 125 | 99.33 222 | 96.26 262 | 98.90 217 | 99.51 192 | 94.68 197 | 99.14 281 | 97.83 165 | 93.15 320 | 98.63 272 |
|
TAPA-MVS | | 97.07 15 | 97.74 234 | 97.34 252 | 98.94 166 | 99.70 89 | 97.53 242 | 99.25 236 | 99.51 86 | 91.90 334 | 99.30 128 | 99.63 148 | 98.78 37 | 99.64 201 | 88.09 339 | 99.87 39 | 99.65 92 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
MIMVSNet | | | 97.73 235 | 97.45 231 | 98.57 228 | 99.45 155 | 97.50 243 | 99.02 285 | 98.98 280 | 96.11 276 | 99.41 104 | 99.14 274 | 90.28 302 | 98.74 314 | 95.74 273 | 98.93 143 | 99.47 139 |
|
cascas | | | 97.69 241 | 97.43 240 | 98.48 237 | 98.60 312 | 97.30 244 | 98.18 345 | 99.39 187 | 92.96 327 | 98.41 266 | 98.78 305 | 93.77 231 | 99.27 262 | 98.16 139 | 98.61 160 | 98.86 203 |
|
PVSNet | | 96.02 17 | 98.85 113 | 98.84 96 | 98.89 185 | 99.73 73 | 97.28 245 | 98.32 340 | 99.60 35 | 97.86 119 | 99.50 87 | 99.57 169 | 96.75 118 | 99.86 110 | 98.56 109 | 99.70 91 | 99.54 118 |
|
MDA-MVSNet-bldmvs | | | 94.96 309 | 93.98 314 | 97.92 285 | 98.24 323 | 97.27 246 | 99.15 255 | 99.33 222 | 93.80 318 | 80.09 356 | 99.03 285 | 88.31 327 | 97.86 335 | 93.49 317 | 94.36 303 | 98.62 274 |
|
GBi-Net | | | 97.68 243 | 97.48 226 | 98.29 255 | 99.51 137 | 97.26 247 | 99.43 171 | 99.48 117 | 96.49 240 | 99.07 190 | 99.32 255 | 90.26 303 | 98.98 301 | 97.10 223 | 96.65 251 | 98.62 274 |
|
test1 | | | 97.68 243 | 97.48 226 | 98.29 255 | 99.51 137 | 97.26 247 | 99.43 171 | 99.48 117 | 96.49 240 | 99.07 190 | 99.32 255 | 90.26 303 | 98.98 301 | 97.10 223 | 96.65 251 | 98.62 274 |
|
FMVSNet1 | | | 96.84 277 | 96.36 278 | 98.29 255 | 99.32 185 | 97.26 247 | 99.43 171 | 99.48 117 | 95.11 292 | 98.55 260 | 99.32 255 | 83.95 346 | 98.98 301 | 95.81 272 | 96.26 261 | 98.62 274 |
|
v748 | | | 97.52 255 | 97.23 262 | 98.41 246 | 98.69 302 | 97.23 250 | 99.87 4 | 99.45 155 | 95.72 286 | 98.51 261 | 99.53 184 | 94.13 219 | 99.30 256 | 96.78 248 | 92.39 327 | 98.70 228 |
|
MDA-MVSNet_test_wron | | | 95.45 304 | 94.60 309 | 98.01 279 | 98.16 324 | 97.21 251 | 99.11 265 | 99.24 252 | 93.49 323 | 80.73 355 | 98.98 290 | 93.02 241 | 98.18 319 | 94.22 310 | 94.45 301 | 98.64 265 |
|
VDD-MVS | | | 97.73 235 | 97.35 249 | 98.88 192 | 99.47 149 | 97.12 252 | 99.34 210 | 98.85 296 | 98.19 78 | 99.67 45 | 99.85 27 | 82.98 347 | 99.92 65 | 99.49 12 | 98.32 178 | 99.60 107 |
|
test-LLR | | | 98.06 176 | 97.90 169 | 98.55 232 | 98.79 286 | 97.10 253 | 98.67 325 | 97.75 341 | 97.34 173 | 98.61 258 | 98.85 298 | 94.45 207 | 99.45 220 | 97.25 214 | 99.38 110 | 99.10 169 |
|
test-mter | | | 97.49 261 | 97.13 265 | 98.55 232 | 98.79 286 | 97.10 253 | 98.67 325 | 97.75 341 | 96.65 230 | 98.61 258 | 98.85 298 | 88.23 328 | 99.45 220 | 97.25 214 | 99.38 110 | 99.10 169 |
|
YYNet1 | | | 95.36 306 | 94.51 311 | 97.92 285 | 97.89 326 | 97.10 253 | 99.10 267 | 99.23 253 | 93.26 326 | 80.77 354 | 99.04 284 | 92.81 247 | 98.02 330 | 94.30 306 | 94.18 307 | 98.64 265 |
|
ACMM | | 97.58 5 | 98.37 143 | 98.34 137 | 98.48 237 | 99.41 161 | 97.10 253 | 99.56 116 | 99.45 155 | 98.53 55 | 99.04 196 | 99.85 27 | 93.00 242 | 99.71 184 | 98.74 83 | 97.45 233 | 98.64 265 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
OPM-MVS | | | 98.19 162 | 98.10 150 | 98.45 241 | 98.88 274 | 97.07 257 | 99.28 223 | 99.38 193 | 98.57 53 | 99.22 160 | 99.81 57 | 92.12 275 | 99.66 197 | 98.08 148 | 97.54 225 | 98.61 283 |
|
Patchmatch-test | | | 97.93 201 | 97.65 210 | 98.77 213 | 99.18 210 | 97.07 257 | 99.03 282 | 99.14 263 | 96.16 271 | 98.74 235 | 99.57 169 | 94.56 202 | 99.72 178 | 93.36 318 | 99.11 126 | 99.52 124 |
|
LPG-MVS_test | | | 98.22 156 | 98.13 148 | 98.49 235 | 99.33 178 | 97.05 259 | 99.58 103 | 99.55 56 | 97.46 160 | 99.24 153 | 99.83 40 | 92.58 263 | 99.72 178 | 98.09 144 | 97.51 226 | 98.68 238 |
|
LGP-MVS_train | | | | | 98.49 235 | 99.33 178 | 97.05 259 | | 99.55 56 | 97.46 160 | 99.24 153 | 99.83 40 | 92.58 263 | 99.72 178 | 98.09 144 | 97.51 226 | 98.68 238 |
|
plane_prior7 | | | | | | 99.29 190 | 97.03 261 | | | | | | | | | | |
|
ACMP | | 97.20 11 | 98.06 176 | 97.94 167 | 98.45 241 | 99.37 171 | 97.01 262 | 99.44 166 | 99.49 106 | 97.54 156 | 98.45 265 | 99.79 76 | 91.95 276 | 99.72 178 | 97.91 159 | 97.49 231 | 98.62 274 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
plane_prior3 | | | | | | | 97.00 263 | | | 98.69 47 | 99.11 181 | | | | | | |
|
Fast-Effi-MVS+-dtu | | | 98.77 122 | 98.83 99 | 98.60 225 | 99.41 161 | 96.99 264 | 99.52 130 | 99.49 106 | 98.11 88 | 99.24 153 | 99.34 249 | 96.96 111 | 99.79 150 | 97.95 157 | 99.45 106 | 99.02 183 |
|
plane_prior6 | | | | | | 99.27 195 | 96.98 265 | | | | | | 92.71 252 | | | | |
|
HQP_MVS | | | 98.27 151 | 98.22 145 | 98.44 244 | 99.29 190 | 96.97 266 | 99.39 191 | 99.47 133 | 98.97 22 | 99.11 181 | 99.61 157 | 92.71 252 | 99.69 193 | 97.78 170 | 97.63 216 | 98.67 249 |
|
plane_prior | | | | | | | 96.97 266 | 99.21 246 | | 98.45 60 | | | | | | 97.60 219 | |
|
ACMH | | 97.28 8 | 98.10 172 | 97.99 162 | 98.44 244 | 99.41 161 | 96.96 268 | 99.60 94 | 99.56 49 | 98.09 91 | 98.15 281 | 99.91 5 | 90.87 299 | 99.70 190 | 98.88 62 | 97.45 233 | 98.67 249 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
NP-MVS | | | | | | 99.23 200 | 96.92 269 | | | | | 99.40 226 | | | | | |
|
Effi-MVS+-dtu | | | 98.78 120 | 98.89 87 | 98.47 239 | 99.33 178 | 96.91 270 | 99.57 109 | 99.30 231 | 98.47 58 | 99.41 104 | 98.99 287 | 96.78 115 | 99.74 167 | 98.73 85 | 99.38 110 | 98.74 219 |
|
HQP5-MVS | | | | | | | 96.83 271 | | | | | | | | | | |
|
HQP-MVS | | | 98.02 187 | 97.90 169 | 98.37 249 | 99.19 207 | 96.83 271 | 98.98 295 | 99.39 187 | 98.24 73 | 98.66 247 | 99.40 226 | 92.47 267 | 99.64 201 | 97.19 218 | 97.58 221 | 98.64 265 |
|
CLD-MVS | | | 98.16 165 | 98.10 150 | 98.33 251 | 99.29 190 | 96.82 273 | 98.75 321 | 99.44 164 | 97.83 125 | 99.13 176 | 99.55 174 | 92.92 244 | 99.67 195 | 98.32 132 | 97.69 215 | 98.48 300 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
LTVRE_ROB | | 97.16 12 | 98.02 187 | 97.90 169 | 98.40 247 | 99.23 200 | 96.80 274 | 99.70 45 | 99.60 35 | 97.12 193 | 98.18 280 | 99.70 115 | 91.73 287 | 99.72 178 | 98.39 123 | 97.45 233 | 98.68 238 |
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 |
pmmvs5 | | | 97.52 255 | 97.30 257 | 98.16 272 | 98.57 314 | 96.73 275 | 99.27 226 | 98.90 292 | 96.14 274 | 98.37 269 | 99.53 184 | 91.54 293 | 99.14 281 | 97.51 198 | 95.87 268 | 98.63 272 |
|
BH-untuned | | | 98.42 139 | 98.36 135 | 98.59 226 | 99.49 145 | 96.70 276 | 99.27 226 | 99.13 264 | 97.24 183 | 98.80 230 | 99.38 231 | 95.75 146 | 99.74 167 | 97.07 226 | 99.16 123 | 99.33 157 |
|
IB-MVS | | 95.67 18 | 96.22 294 | 95.44 302 | 98.57 228 | 99.21 203 | 96.70 276 | 98.65 328 | 97.74 343 | 96.71 226 | 97.27 302 | 98.54 316 | 86.03 337 | 99.92 65 | 98.47 119 | 86.30 348 | 99.10 169 |
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 |
ACMH+ | | 97.24 10 | 97.92 204 | 97.78 188 | 98.32 252 | 99.46 151 | 96.68 278 | 99.56 116 | 99.54 63 | 98.41 64 | 97.79 297 | 99.87 20 | 90.18 307 | 99.66 197 | 98.05 152 | 97.18 246 | 98.62 274 |
|
EU-MVSNet | | | 97.98 192 | 98.03 157 | 97.81 294 | 98.72 298 | 96.65 279 | 99.66 68 | 99.66 25 | 98.09 91 | 98.35 271 | 99.82 47 | 95.25 161 | 98.01 331 | 97.41 208 | 95.30 278 | 98.78 209 |
|
MVP-Stereo | | | 97.81 219 | 97.75 198 | 97.99 281 | 97.53 331 | 96.60 280 | 98.96 300 | 98.85 296 | 97.22 185 | 97.23 303 | 99.36 242 | 95.28 157 | 99.46 219 | 95.51 279 | 99.78 74 | 97.92 326 |
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
TESTMET0.1,1 | | | 97.55 252 | 97.27 261 | 98.40 247 | 98.93 265 | 96.53 281 | 98.67 325 | 97.61 351 | 96.96 211 | 98.64 254 | 99.28 261 | 88.63 323 | 99.45 220 | 97.30 213 | 99.38 110 | 99.21 163 |
|
OurMVSNet-221017-0 | | | 97.88 207 | 97.77 192 | 98.19 270 | 98.71 300 | 96.53 281 | 99.88 1 | 99.00 278 | 97.79 130 | 98.78 232 | 99.94 3 | 91.68 288 | 99.35 243 | 97.21 216 | 96.99 249 | 98.69 233 |
|
ADS-MVSNet | | | 98.20 161 | 98.08 153 | 98.56 230 | 99.33 178 | 96.48 283 | 99.23 239 | 99.15 261 | 96.24 264 | 99.10 184 | 99.67 131 | 94.11 220 | 99.71 184 | 96.81 246 | 99.05 132 | 99.48 135 |
|
testgi | | | 97.65 248 | 97.50 223 | 98.13 273 | 99.36 173 | 96.45 284 | 99.42 178 | 99.48 117 | 97.76 133 | 97.87 293 | 99.45 215 | 91.09 296 | 98.81 313 | 94.53 296 | 98.52 168 | 99.13 168 |
|
test_0402 | | | 96.64 278 | 96.24 279 | 97.85 290 | 98.85 281 | 96.43 285 | 99.44 166 | 99.26 249 | 93.52 322 | 96.98 309 | 99.52 189 | 88.52 324 | 99.20 279 | 92.58 328 | 97.50 228 | 97.93 325 |
|
ITE_SJBPF | | | | | 98.08 274 | 99.29 190 | 96.37 286 | | 98.92 287 | 98.34 67 | 98.83 227 | 99.75 96 | 91.09 296 | 99.62 207 | 95.82 271 | 97.40 237 | 98.25 313 |
|
semantic-postprocess | | | | | 98.06 275 | 99.57 127 | 96.36 287 | | 99.49 106 | 97.18 187 | 98.71 238 | 99.72 110 | 92.70 254 | 99.14 281 | 97.44 206 | 95.86 269 | 98.67 249 |
|
K. test v3 | | | 97.10 274 | 96.79 272 | 98.01 279 | 98.72 298 | 96.33 288 | 99.87 4 | 97.05 355 | 97.59 148 | 96.16 316 | 99.80 68 | 88.71 319 | 99.04 293 | 96.69 253 | 96.55 255 | 98.65 263 |
|
XVG-ACMP-BASELINE | | | 97.83 215 | 97.71 201 | 98.20 269 | 99.11 225 | 96.33 288 | 99.41 182 | 99.52 77 | 98.06 99 | 99.05 195 | 99.50 195 | 89.64 311 | 99.73 174 | 97.73 177 | 97.38 239 | 98.53 297 |
|
IterMVS | | | 97.83 215 | 97.77 192 | 98.02 278 | 99.58 125 | 96.27 290 | 99.02 285 | 99.48 117 | 97.22 185 | 98.71 238 | 99.70 115 | 92.75 248 | 99.13 284 | 97.46 204 | 96.00 266 | 98.67 249 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
SixPastTwentyTwo | | | 97.50 259 | 97.33 254 | 98.03 276 | 98.65 306 | 96.23 291 | 99.77 25 | 98.68 320 | 97.14 190 | 97.90 292 | 99.93 4 | 90.45 301 | 99.18 280 | 97.00 229 | 96.43 257 | 98.67 249 |
|
BH-w/o | | | 98.00 191 | 97.89 173 | 98.32 252 | 99.35 174 | 96.20 292 | 99.01 289 | 98.90 292 | 96.42 250 | 98.38 268 | 99.00 286 | 95.26 160 | 99.72 178 | 96.06 267 | 98.61 160 | 99.03 181 |
|
TDRefinement | | | 95.42 305 | 94.57 310 | 97.97 282 | 89.83 356 | 96.11 293 | 99.48 153 | 98.75 305 | 96.74 224 | 96.68 311 | 99.88 15 | 88.65 322 | 99.71 184 | 98.37 126 | 82.74 350 | 98.09 315 |
|
EPMVS | | | 97.82 218 | 97.65 210 | 98.35 250 | 98.88 274 | 95.98 294 | 99.49 148 | 94.71 360 | 97.57 151 | 99.26 144 | 99.48 204 | 92.46 270 | 99.71 184 | 97.87 162 | 99.08 130 | 99.35 155 |
|
pmmvs-eth3d | | | 95.34 307 | 94.73 308 | 97.15 309 | 95.53 343 | 95.94 295 | 99.35 207 | 99.10 266 | 95.13 291 | 93.55 337 | 97.54 339 | 88.15 330 | 97.91 333 | 94.58 295 | 89.69 334 | 97.61 338 |
|
FMVSNet5 | | | 96.43 283 | 96.19 280 | 97.15 309 | 99.11 225 | 95.89 296 | 99.32 212 | 99.52 77 | 94.47 307 | 98.34 272 | 99.07 280 | 87.54 332 | 97.07 341 | 92.61 327 | 95.72 271 | 98.47 301 |
|
UnsupCasMVSNet_eth | | | 96.44 282 | 96.12 281 | 97.40 308 | 98.65 306 | 95.65 297 | 99.36 202 | 99.51 86 | 97.13 191 | 96.04 319 | 98.99 287 | 88.40 326 | 98.17 320 | 96.71 251 | 90.27 331 | 98.40 306 |
|
MIMVSNet1 | | | 95.51 303 | 95.04 306 | 96.92 315 | 97.38 333 | 95.60 298 | 99.52 130 | 99.50 101 | 93.65 320 | 96.97 310 | 99.17 272 | 85.28 341 | 96.56 345 | 88.36 338 | 95.55 275 | 98.60 290 |
|
CVMVSNet | | | 98.57 133 | 98.67 113 | 98.30 254 | 99.35 174 | 95.59 299 | 99.50 139 | 99.55 56 | 98.60 52 | 99.39 109 | 99.83 40 | 94.48 206 | 99.45 220 | 98.75 82 | 98.56 166 | 99.85 9 |
|
Patchmatch-test1 | | | 98.16 165 | 98.14 147 | 98.22 267 | 99.30 187 | 95.55 300 | 99.07 270 | 98.97 281 | 97.57 151 | 99.43 99 | 99.60 160 | 92.72 251 | 99.60 209 | 97.38 209 | 99.20 121 | 99.50 132 |
|
LF4IMVS | | | 97.52 255 | 97.46 230 | 97.70 300 | 98.98 248 | 95.55 300 | 99.29 221 | 98.82 299 | 98.07 95 | 98.66 247 | 99.64 144 | 89.97 308 | 99.61 208 | 97.01 228 | 96.68 250 | 97.94 324 |
|
EPNet_dtu | | | 98.03 185 | 97.96 165 | 98.23 265 | 98.27 322 | 95.54 302 | 99.23 239 | 98.75 305 | 99.02 10 | 97.82 295 | 99.71 112 | 96.11 135 | 99.48 217 | 93.04 323 | 99.65 99 | 99.69 80 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
TinyColmap | | | 97.12 273 | 96.89 270 | 97.83 292 | 99.07 232 | 95.52 303 | 98.57 331 | 98.74 308 | 97.58 150 | 97.81 296 | 99.79 76 | 88.16 329 | 99.56 212 | 95.10 286 | 97.21 244 | 98.39 307 |
|
pmmvs6 | | | 96.53 281 | 96.09 282 | 97.82 293 | 98.69 302 | 95.47 304 | 99.37 198 | 99.47 133 | 93.46 324 | 97.41 300 | 99.78 82 | 87.06 335 | 99.33 247 | 96.92 237 | 92.70 325 | 98.65 263 |
|
test20.03 | | | 96.12 297 | 95.96 286 | 96.63 319 | 97.44 332 | 95.45 305 | 99.51 134 | 99.38 193 | 96.55 238 | 96.16 316 | 99.25 265 | 93.76 232 | 96.17 346 | 87.35 342 | 94.22 306 | 98.27 311 |
|
lessismore_v0 | | | | | 97.79 295 | 98.69 302 | 95.44 306 | | 94.75 359 | | 95.71 320 | 99.87 20 | 88.69 320 | 99.32 250 | 95.89 270 | 94.93 289 | 98.62 274 |
|
PatchmatchNet | | | 98.31 146 | 98.36 135 | 98.19 270 | 99.16 217 | 95.32 307 | 99.27 226 | 98.92 287 | 97.37 172 | 99.37 113 | 99.58 165 | 94.90 180 | 99.70 190 | 97.43 207 | 99.21 120 | 99.54 118 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
ppachtmachnet_test | | | 97.49 261 | 97.45 231 | 97.61 301 | 98.62 309 | 95.24 308 | 98.80 316 | 99.46 143 | 96.11 276 | 98.22 277 | 99.62 153 | 96.45 126 | 98.97 308 | 93.77 313 | 95.97 267 | 98.61 283 |
|
LP | | | 97.04 275 | 96.80 271 | 97.77 296 | 98.90 270 | 95.23 309 | 98.97 298 | 99.06 273 | 94.02 314 | 98.09 283 | 99.41 222 | 93.88 227 | 98.82 312 | 90.46 332 | 98.42 173 | 99.26 161 |
|
USDC | | | 97.34 267 | 97.20 263 | 97.75 297 | 99.07 232 | 95.20 310 | 98.51 334 | 99.04 275 | 97.99 109 | 98.31 273 | 99.86 23 | 89.02 315 | 99.55 214 | 95.67 277 | 97.36 240 | 98.49 299 |
|
ADS-MVSNet2 | | | 98.02 187 | 98.07 155 | 97.87 288 | 99.33 178 | 95.19 311 | 99.23 239 | 99.08 268 | 96.24 264 | 99.10 184 | 99.67 131 | 94.11 220 | 98.93 310 | 96.81 246 | 99.05 132 | 99.48 135 |
|
MDTV_nov1_ep13_2view | | | | | | | 95.18 312 | 99.35 207 | | 96.84 220 | 99.58 67 | | 95.19 164 | | 97.82 166 | | 99.46 143 |
|
new_pmnet | | | 96.38 287 | 96.03 283 | 97.41 307 | 98.13 325 | 95.16 313 | 99.05 276 | 99.20 256 | 93.94 316 | 97.39 301 | 98.79 303 | 91.61 292 | 99.04 293 | 90.43 333 | 95.77 270 | 98.05 317 |
|
tpm | | | 97.67 246 | 97.55 216 | 98.03 276 | 99.02 241 | 95.01 314 | 99.43 171 | 98.54 328 | 96.44 248 | 99.12 179 | 99.34 249 | 91.83 282 | 99.60 209 | 97.75 175 | 96.46 256 | 99.48 135 |
|
our_test_3 | | | 97.65 248 | 97.68 203 | 97.55 303 | 98.62 309 | 94.97 315 | 98.84 314 | 99.30 231 | 96.83 221 | 98.19 279 | 99.34 249 | 97.01 109 | 99.02 296 | 95.00 289 | 96.01 265 | 98.64 265 |
|
DWT-MVSNet_test | | | 97.53 254 | 97.40 243 | 97.93 284 | 99.03 240 | 94.86 316 | 99.57 109 | 98.63 322 | 96.59 237 | 98.36 270 | 98.79 303 | 89.32 313 | 99.74 167 | 98.14 142 | 98.16 196 | 99.20 164 |
|
tpmrst | | | 98.33 144 | 98.48 131 | 97.90 287 | 99.16 217 | 94.78 317 | 99.31 215 | 99.11 265 | 97.27 179 | 99.45 95 | 99.59 162 | 95.33 155 | 99.84 122 | 98.48 117 | 98.61 160 | 99.09 173 |
|
PatchFormer-LS_test | | | 98.01 190 | 98.05 156 | 97.87 288 | 99.15 220 | 94.76 318 | 99.42 178 | 98.93 285 | 97.12 193 | 98.84 226 | 98.59 314 | 93.74 234 | 99.80 147 | 98.55 112 | 98.17 195 | 99.06 179 |
|
tpmvs | | | 97.98 192 | 98.02 158 | 97.84 291 | 99.04 238 | 94.73 319 | 99.31 215 | 99.20 256 | 96.10 280 | 98.76 234 | 99.42 219 | 94.94 175 | 99.81 143 | 96.97 232 | 98.45 171 | 98.97 188 |
|
pmmvs3 | | | 94.09 316 | 93.25 318 | 96.60 320 | 94.76 346 | 94.49 320 | 98.92 307 | 98.18 336 | 89.66 341 | 96.48 313 | 98.06 323 | 86.28 336 | 97.33 340 | 89.68 335 | 87.20 342 | 97.97 323 |
|
MDTV_nov1_ep13 | | | | 98.32 139 | | 99.11 225 | 94.44 321 | 99.27 226 | 98.74 308 | 97.51 157 | 99.40 108 | 99.62 153 | 94.78 188 | 99.76 165 | 97.59 188 | 98.81 156 | |
|
tpm2 | | | 97.44 264 | 97.34 252 | 97.74 298 | 99.15 220 | 94.36 322 | 99.45 162 | 98.94 284 | 93.45 325 | 98.90 217 | 99.44 216 | 91.35 294 | 99.59 211 | 97.31 212 | 98.07 206 | 99.29 159 |
|
PVSNet_0 | | 94.43 19 | 96.09 298 | 95.47 300 | 97.94 283 | 99.31 186 | 94.34 323 | 97.81 348 | 99.70 15 | 97.12 193 | 97.46 299 | 98.75 306 | 89.71 310 | 99.79 150 | 97.69 183 | 81.69 351 | 99.68 84 |
|
Anonymous20231206 | | | 96.22 294 | 96.03 283 | 96.79 318 | 97.31 336 | 94.14 324 | 99.63 82 | 99.08 268 | 96.17 270 | 97.04 307 | 99.06 282 | 93.94 225 | 97.76 337 | 86.96 343 | 95.06 284 | 98.47 301 |
|
CostFormer | | | 97.72 237 | 97.73 199 | 97.71 299 | 99.15 220 | 94.02 325 | 99.54 125 | 99.02 277 | 94.67 298 | 99.04 196 | 99.35 246 | 92.35 273 | 99.77 160 | 98.50 116 | 97.94 210 | 99.34 156 |
|
UnsupCasMVSNet_bld | | | 93.53 318 | 92.51 320 | 96.58 321 | 97.38 333 | 93.82 326 | 98.24 342 | 99.48 117 | 91.10 338 | 93.10 339 | 96.66 345 | 74.89 351 | 98.37 318 | 94.03 312 | 87.71 341 | 97.56 340 |
|
tpm cat1 | | | 97.39 266 | 97.36 247 | 97.50 306 | 99.17 215 | 93.73 327 | 99.43 171 | 99.31 229 | 91.27 336 | 98.71 238 | 99.08 279 | 94.31 213 | 99.77 160 | 96.41 263 | 98.50 169 | 99.00 184 |
|
tpmp4_e23 | | | 97.34 267 | 97.29 258 | 97.52 304 | 99.25 199 | 93.73 327 | 99.58 103 | 99.19 259 | 94.00 315 | 98.20 278 | 99.41 222 | 90.74 300 | 99.74 167 | 97.13 222 | 98.07 206 | 99.07 178 |
|
dp | | | 97.75 232 | 97.80 185 | 97.59 302 | 99.10 228 | 93.71 329 | 99.32 212 | 98.88 294 | 96.48 246 | 99.08 189 | 99.55 174 | 92.67 261 | 99.82 139 | 96.52 259 | 98.58 163 | 99.24 162 |
|
MVS-HIRNet | | | 95.75 301 | 95.16 305 | 97.51 305 | 99.30 187 | 93.69 330 | 98.88 311 | 95.78 357 | 85.09 349 | 98.78 232 | 92.65 352 | 91.29 295 | 99.37 236 | 94.85 291 | 99.85 54 | 99.46 143 |
|
DSMNet-mixed | | | 97.25 270 | 97.35 249 | 96.95 314 | 97.84 327 | 93.61 331 | 99.57 109 | 96.63 356 | 96.13 275 | 98.87 220 | 98.61 313 | 94.59 201 | 97.70 338 | 95.08 287 | 98.86 151 | 99.55 116 |
|
MS-PatchMatch | | | 97.24 271 | 97.32 255 | 96.99 312 | 98.45 319 | 93.51 332 | 98.82 315 | 99.32 228 | 97.41 169 | 98.13 282 | 99.30 258 | 88.99 316 | 99.56 212 | 95.68 276 | 99.80 70 | 97.90 327 |
|
OpenMVS_ROB | | 92.34 20 | 94.38 314 | 93.70 315 | 96.41 322 | 97.38 333 | 93.17 333 | 99.06 274 | 98.75 305 | 86.58 347 | 94.84 324 | 98.26 322 | 81.53 350 | 99.32 250 | 89.01 336 | 97.87 212 | 96.76 342 |
|
gm-plane-assit | | | | | | 98.54 316 | 92.96 334 | | | 94.65 299 | | 99.15 273 | | 99.64 201 | 97.56 193 | | |
|
EG-PatchMatch MVS | | | 95.97 299 | 95.69 293 | 96.81 317 | 97.78 328 | 92.79 335 | 99.16 252 | 98.93 285 | 96.16 271 | 94.08 328 | 99.22 269 | 82.72 348 | 99.47 218 | 95.67 277 | 97.50 228 | 98.17 314 |
|
new-patchmatchnet | | | 94.48 312 | 94.08 313 | 95.67 324 | 95.08 345 | 92.41 336 | 99.18 250 | 99.28 243 | 94.55 304 | 93.49 338 | 97.37 342 | 87.86 331 | 97.01 342 | 91.57 329 | 88.36 337 | 97.61 338 |
|
testpf | | | 95.66 302 | 96.02 285 | 94.58 326 | 98.35 321 | 92.32 337 | 97.25 353 | 97.91 340 | 92.83 328 | 97.03 308 | 98.99 287 | 88.69 320 | 98.61 316 | 95.72 274 | 97.40 237 | 92.80 351 |
|
LCM-MVSNet-Re | | | 97.83 215 | 98.15 146 | 96.87 316 | 99.30 187 | 92.25 338 | 99.59 96 | 98.26 332 | 97.43 165 | 96.20 315 | 99.13 275 | 96.27 132 | 98.73 315 | 98.17 138 | 98.99 136 | 99.64 98 |
|
DeepPCF-MVS | | 98.18 3 | 98.81 116 | 99.37 17 | 97.12 311 | 99.60 122 | 91.75 339 | 98.61 329 | 99.44 164 | 99.35 1 | 99.83 12 | 99.85 27 | 98.70 50 | 99.81 143 | 99.02 52 | 99.91 17 | 99.81 35 |
|
RPSCF | | | 98.22 156 | 98.62 122 | 96.99 312 | 99.82 29 | 91.58 340 | 99.72 42 | 99.44 164 | 96.61 233 | 99.66 50 | 99.89 10 | 95.92 140 | 99.82 139 | 97.46 204 | 99.10 128 | 99.57 115 |
|
Patchmatch-RL test | | | 95.84 300 | 95.81 289 | 95.95 323 | 95.61 341 | 90.57 341 | 98.24 342 | 98.39 329 | 95.10 293 | 95.20 321 | 98.67 308 | 94.78 188 | 97.77 336 | 96.28 265 | 90.02 332 | 99.51 129 |
|
Gipuma | | | 90.99 323 | 90.15 324 | 93.51 327 | 98.73 296 | 90.12 342 | 93.98 357 | 99.45 155 | 79.32 352 | 92.28 341 | 94.91 349 | 69.61 353 | 97.98 332 | 87.42 340 | 95.67 272 | 92.45 353 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
PM-MVS | | | 92.96 319 | 92.23 321 | 95.14 325 | 95.61 341 | 89.98 343 | 99.37 198 | 98.21 334 | 94.80 296 | 95.04 323 | 97.69 331 | 65.06 356 | 97.90 334 | 94.30 306 | 89.98 333 | 97.54 341 |
|
1111 | | | 92.30 321 | 92.21 322 | 92.55 331 | 93.30 348 | 86.27 344 | 99.15 255 | 98.74 308 | 91.94 332 | 90.85 345 | 97.82 326 | 84.18 344 | 95.21 348 | 79.65 351 | 94.27 305 | 96.19 345 |
|
.test1245 | | | 83.42 328 | 86.17 326 | 75.15 350 | 93.30 348 | 86.27 344 | 99.15 255 | 98.74 308 | 91.94 332 | 90.85 345 | 97.82 326 | 84.18 344 | 95.21 348 | 79.65 351 | 39.90 361 | 43.98 362 |
|
test2356 | | | 94.07 317 | 94.46 312 | 92.89 330 | 95.18 344 | 86.13 346 | 97.60 351 | 99.06 273 | 93.61 321 | 96.15 318 | 98.28 321 | 85.60 340 | 93.95 352 | 86.68 345 | 98.00 208 | 98.59 291 |
|
no-one | | | 83.04 329 | 80.12 331 | 91.79 335 | 89.44 357 | 85.65 347 | 99.32 212 | 98.32 330 | 89.06 343 | 79.79 358 | 89.16 358 | 44.86 363 | 96.67 344 | 84.33 348 | 46.78 359 | 93.05 350 |
|
testus | | | 94.61 311 | 95.30 304 | 92.54 332 | 96.44 339 | 84.18 348 | 98.36 337 | 99.03 276 | 94.18 312 | 96.49 312 | 98.57 315 | 88.74 318 | 95.09 350 | 87.41 341 | 98.45 171 | 98.36 310 |
|
PMMVS2 | | | 86.87 325 | 85.37 328 | 91.35 338 | 90.21 355 | 83.80 349 | 98.89 310 | 97.45 353 | 83.13 351 | 91.67 344 | 95.03 348 | 48.49 361 | 94.70 351 | 85.86 346 | 77.62 352 | 95.54 347 |
|
test1235678 | | | 92.91 320 | 93.30 317 | 91.71 336 | 93.14 350 | 83.01 350 | 98.75 321 | 98.58 325 | 92.80 329 | 92.45 340 | 97.91 325 | 88.51 325 | 93.54 353 | 82.26 349 | 95.35 277 | 98.59 291 |
|
test12356 | | | 91.74 322 | 92.19 323 | 90.37 339 | 91.22 352 | 82.41 351 | 98.61 329 | 98.28 331 | 90.66 340 | 91.82 343 | 97.92 324 | 84.90 342 | 92.61 354 | 81.64 350 | 94.66 296 | 96.09 346 |
|
ambc | | | | | 93.06 329 | 92.68 351 | 82.36 352 | 98.47 335 | 98.73 317 | | 95.09 322 | 97.41 340 | 55.55 359 | 99.10 289 | 96.42 262 | 91.32 329 | 97.71 337 |
|
DeepMVS_CX | | | | | 93.34 328 | 99.29 190 | 82.27 353 | | 99.22 254 | 85.15 348 | 96.33 314 | 99.05 283 | 90.97 298 | 99.73 174 | 93.57 315 | 97.77 214 | 98.01 321 |
|
LCM-MVSNet | | | 86.80 326 | 85.22 329 | 91.53 337 | 87.81 358 | 80.96 354 | 98.23 344 | 98.99 279 | 71.05 355 | 90.13 347 | 96.51 346 | 48.45 362 | 96.88 343 | 90.51 331 | 85.30 349 | 96.76 342 |
|
CMPMVS | | 69.68 23 | 94.13 315 | 94.90 307 | 91.84 334 | 97.24 337 | 80.01 355 | 98.52 333 | 99.48 117 | 89.01 344 | 91.99 342 | 99.67 131 | 85.67 339 | 99.13 284 | 95.44 280 | 97.03 248 | 96.39 344 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
N_pmnet | | | 94.95 310 | 95.83 288 | 92.31 333 | 98.47 318 | 79.33 356 | 99.12 259 | 92.81 366 | 93.87 317 | 97.68 298 | 99.13 275 | 93.87 228 | 99.01 298 | 91.38 330 | 96.19 262 | 98.59 291 |
|
ANet_high | | | 77.30 334 | 74.86 336 | 84.62 344 | 75.88 365 | 77.61 357 | 97.63 350 | 93.15 365 | 88.81 345 | 64.27 361 | 89.29 357 | 36.51 364 | 83.93 363 | 75.89 356 | 52.31 358 | 92.33 354 |
|
testmv | | | 87.91 324 | 87.80 325 | 88.24 340 | 87.68 359 | 77.50 358 | 99.07 270 | 97.66 350 | 89.27 342 | 86.47 349 | 96.22 347 | 68.35 354 | 92.49 356 | 76.63 355 | 88.82 335 | 94.72 349 |
|
EMVS | | | 80.02 332 | 79.22 333 | 82.43 348 | 91.19 353 | 76.40 359 | 97.55 352 | 92.49 368 | 66.36 360 | 83.01 353 | 91.27 354 | 64.63 357 | 85.79 362 | 65.82 360 | 60.65 356 | 85.08 359 |
|
E-PMN | | | 80.61 331 | 79.88 332 | 82.81 346 | 90.75 354 | 76.38 360 | 97.69 349 | 95.76 358 | 66.44 359 | 83.52 351 | 92.25 353 | 62.54 358 | 87.16 361 | 68.53 359 | 61.40 355 | 84.89 360 |
|
MVE | | 76.82 21 | 76.91 335 | 74.31 337 | 84.70 342 | 85.38 363 | 76.05 361 | 96.88 354 | 93.17 364 | 67.39 358 | 71.28 360 | 89.01 359 | 21.66 371 | 87.69 360 | 71.74 358 | 72.29 354 | 90.35 356 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
wuykxyi23d | | | 74.42 337 | 71.19 338 | 84.14 345 | 76.16 364 | 74.29 362 | 96.00 356 | 92.57 367 | 69.57 356 | 63.84 362 | 87.49 360 | 21.98 368 | 88.86 359 | 75.56 357 | 57.50 357 | 89.26 358 |
|
PNet_i23d | | | 79.43 333 | 77.68 334 | 84.67 343 | 86.18 361 | 71.69 363 | 96.50 355 | 93.68 362 | 75.17 353 | 71.33 359 | 91.18 355 | 32.18 366 | 90.62 358 | 78.57 354 | 74.34 353 | 91.71 355 |
|
tmp_tt | | | 82.80 330 | 81.52 330 | 86.66 341 | 66.61 367 | 68.44 364 | 92.79 359 | 97.92 338 | 68.96 357 | 80.04 357 | 99.85 27 | 85.77 338 | 96.15 347 | 97.86 163 | 43.89 360 | 95.39 348 |
|
FPMVS | | | 84.93 327 | 85.65 327 | 82.75 347 | 86.77 360 | 63.39 365 | 98.35 339 | 98.92 287 | 74.11 354 | 83.39 352 | 98.98 290 | 50.85 360 | 92.40 357 | 84.54 347 | 94.97 286 | 92.46 352 |
|
PMVS | | 70.75 22 | 75.98 336 | 74.97 335 | 79.01 349 | 70.98 366 | 55.18 366 | 93.37 358 | 98.21 334 | 65.08 361 | 61.78 363 | 93.83 351 | 21.74 370 | 92.53 355 | 78.59 353 | 91.12 330 | 89.34 357 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
wuyk23d | | | 40.18 340 | 41.29 343 | 36.84 351 | 86.18 361 | 49.12 367 | 79.73 360 | 22.81 370 | 27.64 362 | 25.46 366 | 28.45 366 | 21.98 368 | 48.89 364 | 55.80 361 | 23.56 364 | 12.51 364 |
|
test123 | | | 39.01 342 | 42.50 342 | 28.53 353 | 39.17 368 | 20.91 368 | 98.75 321 | 19.17 371 | 19.83 364 | 38.57 364 | 66.67 362 | 33.16 365 | 15.42 365 | 37.50 363 | 29.66 363 | 49.26 361 |
|
testmvs | | | 39.17 341 | 43.78 340 | 25.37 354 | 36.04 369 | 16.84 369 | 98.36 337 | 26.56 369 | 20.06 363 | 38.51 365 | 67.32 361 | 29.64 367 | 15.30 366 | 37.59 362 | 39.90 361 | 43.98 362 |
|
test_part1 | | | | | 0.00 355 | | 0.00 370 | 0.00 361 | 99.48 117 | | | | 0.00 372 | 0.00 367 | 0.00 364 | 0.00 365 | 0.00 365 |
|
v1.0 | | | 41.40 338 | 55.20 339 | 0.00 355 | 99.81 32 | 0.00 370 | 0.00 361 | 99.48 117 | 97.97 111 | 99.77 25 | 99.78 82 | 0.00 372 | 0.00 367 | 0.00 364 | 0.00 365 | 0.00 365 |
|
cdsmvs_eth3d_5k | | | 24.64 343 | 32.85 344 | 0.00 355 | 0.00 370 | 0.00 370 | 0.00 361 | 99.51 86 | 0.00 365 | 0.00 367 | 99.56 171 | 96.58 122 | 0.00 367 | 0.00 364 | 0.00 365 | 0.00 365 |
|
pcd_1.5k_mvsjas | | | 8.27 345 | 11.03 346 | 0.00 355 | 0.00 370 | 0.00 370 | 0.00 361 | 0.00 372 | 0.00 365 | 0.00 367 | 0.27 367 | 99.01 12 | 0.00 367 | 0.00 364 | 0.00 365 | 0.00 365 |
|
pcd1.5k->3k | | | 40.85 339 | 43.49 341 | 32.93 352 | 98.95 257 | 0.00 370 | 0.00 361 | 99.53 73 | 0.00 365 | 0.00 367 | 0.27 367 | 95.32 156 | 0.00 367 | 0.00 364 | 97.30 241 | 98.80 207 |
|
sosnet-low-res | | | 0.02 346 | 0.03 347 | 0.00 355 | 0.00 370 | 0.00 370 | 0.00 361 | 0.00 372 | 0.00 365 | 0.00 367 | 0.27 367 | 0.00 372 | 0.00 367 | 0.00 364 | 0.00 365 | 0.00 365 |
|
sosnet | | | 0.02 346 | 0.03 347 | 0.00 355 | 0.00 370 | 0.00 370 | 0.00 361 | 0.00 372 | 0.00 365 | 0.00 367 | 0.27 367 | 0.00 372 | 0.00 367 | 0.00 364 | 0.00 365 | 0.00 365 |
|
uncertanet | | | 0.02 346 | 0.03 347 | 0.00 355 | 0.00 370 | 0.00 370 | 0.00 361 | 0.00 372 | 0.00 365 | 0.00 367 | 0.27 367 | 0.00 372 | 0.00 367 | 0.00 364 | 0.00 365 | 0.00 365 |
|
Regformer | | | 0.02 346 | 0.03 347 | 0.00 355 | 0.00 370 | 0.00 370 | 0.00 361 | 0.00 372 | 0.00 365 | 0.00 367 | 0.27 367 | 0.00 372 | 0.00 367 | 0.00 364 | 0.00 365 | 0.00 365 |
|
ab-mvs-re | | | 8.30 344 | 11.06 345 | 0.00 355 | 0.00 370 | 0.00 370 | 0.00 361 | 0.00 372 | 0.00 365 | 0.00 367 | 99.58 165 | 0.00 372 | 0.00 367 | 0.00 364 | 0.00 365 | 0.00 365 |
|
uanet | | | 0.02 346 | 0.03 347 | 0.00 355 | 0.00 370 | 0.00 370 | 0.00 361 | 0.00 372 | 0.00 365 | 0.00 367 | 0.27 367 | 0.00 372 | 0.00 367 | 0.00 364 | 0.00 365 | 0.00 365 |
|
GSMVS | | | | | | | | | | | | | | | | | 99.52 124 |
|
sam_mvs1 | | | | | | | | | | | | | 94.86 183 | | | | 99.52 124 |
|
sam_mvs | | | | | | | | | | | | | 94.72 196 | | | | |
|
MTGPA | | | | | | | | | 99.47 133 | | | | | | | | |
|
test_post1 | | | | | | | | 99.23 239 | | | | 65.14 364 | 94.18 218 | 99.71 184 | 97.58 189 | | |
|
test_post | | | | | | | | | | | | 65.99 363 | 94.65 200 | 99.73 174 | | | |
|
patchmatchnet-post | | | | | | | | | | | | 98.70 307 | 94.79 187 | 99.74 167 | | | |
|
MTMP | | | | | | | | 99.54 125 | 98.88 294 | | | | | | | | |
|
test9_res | | | | | | | | | | | | | | | 97.49 200 | 99.72 85 | 99.75 55 |
|
agg_prior2 | | | | | | | | | | | | | | | 97.21 216 | 99.73 84 | 99.75 55 |
|
test_prior2 | | | | | | | | 98.96 300 | | 98.34 67 | 99.01 199 | 99.52 189 | 98.68 51 | | 97.96 155 | 99.74 81 | |
|
旧先验2 | | | | | | | | 98.96 300 | | 96.70 227 | 99.47 92 | | | 99.94 41 | 98.19 136 | | |
|
新几何2 | | | | | | | | 99.01 289 | | | | | | | | | |
|
无先验 | | | | | | | | 98.99 291 | 99.51 86 | 96.89 217 | | | | 99.93 56 | 97.53 196 | | 99.72 71 |
|
原ACMM2 | | | | | | | | 98.95 304 | | | | | | | | | |
|
testdata2 | | | | | | | | | | | | | | 99.95 34 | 96.67 254 | | |
|
segment_acmp | | | | | | | | | | | | | 98.96 21 | | | | |
|
testdata1 | | | | | | | | 98.85 313 | | 98.32 70 | | | | | | | |
|
plane_prior5 | | | | | | | | | 99.47 133 | | | | | 99.69 193 | 97.78 170 | 97.63 216 | 98.67 249 |
|
plane_prior4 | | | | | | | | | | | | 99.61 157 | | | | | |
|
plane_prior2 | | | | | | | | 99.39 191 | | 98.97 22 | | | | | | | |
|
plane_prior1 | | | | | | 99.26 197 | | | | | | | | | | | |
|
n2 | | | | | | | | | 0.00 372 | | | | | | | | |
|
nn | | | | | | | | | 0.00 372 | | | | | | | | |
|
door-mid | | | | | | | | | 98.05 337 | | | | | | | | |
|
test11 | | | | | | | | | 99.35 206 | | | | | | | | |
|
door | | | | | | | | | 97.92 338 | | | | | | | | |
|
HQP-NCC | | | | | | 99.19 207 | | 98.98 295 | | 98.24 73 | 98.66 247 | | | | | | |
|
ACMP_Plane | | | | | | 99.19 207 | | 98.98 295 | | 98.24 73 | 98.66 247 | | | | | | |
|
BP-MVS | | | | | | | | | | | | | | | 97.19 218 | | |
|
HQP4-MVS | | | | | | | | | | | 98.66 247 | | | 99.64 201 | | | 98.64 265 |
|
HQP3-MVS | | | | | | | | | 99.39 187 | | | | | | | 97.58 221 | |
|
HQP2-MVS | | | | | | | | | | | | | 92.47 267 | | | | |
|
ACMMP++_ref | | | | | | | | | | | | | | | | 97.19 245 | |
|
ACMMP++ | | | | | | | | | | | | | | | | 97.43 236 | |
|
Test By Simon | | | | | | | | | | | | | 98.75 45 | | | | |
|