zzz-MVS | | | 98.55 24 | 98.25 30 | 99.46 8 | 99.76 1 | 98.64 11 | 98.55 160 | 98.74 83 | 97.27 26 | 98.02 69 | 99.39 9 | 94.81 56 | 99.96 1 | 97.91 31 | 99.79 12 | 99.77 15 |
|
MTAPA | | | 98.58 19 | 98.29 27 | 99.46 8 | 99.76 1 | 98.64 11 | 98.90 78 | 98.74 83 | 97.27 26 | 98.02 69 | 99.39 9 | 94.81 56 | 99.96 1 | 97.91 31 | 99.79 12 | 99.77 15 |
|
HSP-MVS | | | 98.70 6 | 98.52 9 | 99.24 27 | 99.75 3 | 98.23 31 | 99.26 18 | 98.58 124 | 97.52 8 | 99.41 4 | 98.78 90 | 96.00 25 | 99.79 73 | 97.79 40 | 99.59 54 | 99.69 37 |
|
MP-MVS | | | 98.33 40 | 98.01 41 | 99.28 22 | 99.75 3 | 98.18 36 | 99.22 29 | 98.79 73 | 96.13 64 | 97.92 79 | 99.23 32 | 94.54 61 | 99.94 3 | 96.74 86 | 99.78 16 | 99.73 29 |
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo. |
mPP-MVS | | | 98.51 28 | 98.26 29 | 99.25 26 | 99.75 3 | 98.04 42 | 99.28 17 | 98.81 64 | 96.24 60 | 98.35 57 | 99.23 32 | 95.46 40 | 99.94 3 | 97.42 59 | 99.81 9 | 99.77 15 |
|
HPM-MVS_fast | | | 98.38 34 | 98.13 37 | 99.12 42 | 99.75 3 | 97.86 49 | 99.44 4 | 98.82 61 | 94.46 141 | 98.94 25 | 99.20 38 | 95.16 50 | 99.74 89 | 97.58 51 | 99.85 2 | 99.77 15 |
|
region2R | | | 98.61 14 | 98.38 17 | 99.29 20 | 99.74 7 | 98.16 37 | 99.23 23 | 98.93 36 | 96.15 62 | 98.94 25 | 99.17 42 | 95.91 30 | 99.94 3 | 97.55 54 | 99.79 12 | 99.78 8 |
|
ACMMPR | | | 98.59 17 | 98.36 19 | 99.29 20 | 99.74 7 | 98.15 38 | 99.23 23 | 98.95 33 | 96.10 67 | 98.93 29 | 99.19 41 | 95.70 35 | 99.94 3 | 97.62 49 | 99.79 12 | 99.78 8 |
|
HPM-MVS | | | 98.36 36 | 98.10 38 | 99.13 40 | 99.74 7 | 97.82 52 | 99.53 1 | 98.80 71 | 94.63 134 | 98.61 44 | 98.97 68 | 95.13 51 | 99.77 83 | 97.65 47 | 99.83 8 | 99.79 5 |
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023 |
ACMMP | | | 98.23 43 | 97.95 43 | 99.09 44 | 99.74 7 | 97.62 58 | 99.03 63 | 99.41 6 | 95.98 69 | 97.60 97 | 99.36 18 | 94.45 66 | 99.93 10 | 97.14 65 | 98.85 99 | 99.70 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 |
MP-MVS-pluss | | | 98.31 41 | 97.92 44 | 99.49 6 | 99.72 11 | 98.88 7 | 98.43 176 | 98.78 75 | 94.10 147 | 97.69 91 | 99.42 7 | 95.25 47 | 99.92 14 | 98.09 25 | 99.80 11 | 99.67 48 |
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
HFP-MVS | | | 98.63 13 | 98.40 15 | 99.32 18 | 99.72 11 | 98.29 28 | 99.23 23 | 98.96 31 | 96.10 67 | 98.94 25 | 99.17 42 | 96.06 22 | 99.92 14 | 97.62 49 | 99.78 16 | 99.75 22 |
|
#test# | | | 98.54 26 | 98.27 28 | 99.32 18 | 99.72 11 | 98.29 28 | 98.98 70 | 98.96 31 | 95.65 80 | 98.94 25 | 99.17 42 | 96.06 22 | 99.92 14 | 97.21 64 | 99.78 16 | 99.75 22 |
|
PGM-MVS | | | 98.49 29 | 98.23 34 | 99.27 25 | 99.72 11 | 98.08 41 | 98.99 67 | 99.49 5 | 95.43 88 | 99.03 19 | 99.32 22 | 95.56 37 | 99.94 3 | 96.80 84 | 99.77 19 | 99.78 8 |
|
XVS | | | 98.70 6 | 98.49 13 | 99.34 15 | 99.70 15 | 98.35 25 | 99.29 15 | 98.88 48 | 97.40 15 | 98.46 49 | 99.20 38 | 95.90 31 | 99.89 28 | 97.85 36 | 99.74 34 | 99.78 8 |
|
X-MVStestdata | | | 94.06 251 | 92.30 271 | 99.34 15 | 99.70 15 | 98.35 25 | 99.29 15 | 98.88 48 | 97.40 15 | 98.46 49 | 43.50 360 | 95.90 31 | 99.89 28 | 97.85 36 | 99.74 34 | 99.78 8 |
|
TSAR-MVS + MP. | | | 98.78 4 | 98.62 5 | 99.24 27 | 99.69 17 | 98.28 30 | 99.14 45 | 98.66 111 | 96.84 44 | 99.56 2 | 99.31 23 | 96.34 12 | 99.70 95 | 98.32 20 | 99.73 36 | 99.73 29 |
|
CSCG | | | 97.85 54 | 97.74 48 | 98.20 97 | 99.67 18 | 95.16 165 | 99.22 29 | 99.32 7 | 93.04 203 | 97.02 115 | 98.92 79 | 95.36 43 | 99.91 23 | 97.43 58 | 99.64 47 | 99.52 68 |
|
CP-MVS | | | 98.57 22 | 98.36 19 | 99.19 30 | 99.66 19 | 97.86 49 | 99.34 11 | 98.87 51 | 95.96 70 | 98.60 45 | 99.13 47 | 96.05 24 | 99.94 3 | 97.77 41 | 99.86 1 | 99.77 15 |
|
CPTT-MVS | | | 97.72 58 | 97.32 66 | 98.92 55 | 99.64 20 | 97.10 76 | 99.12 51 | 98.81 64 | 92.34 234 | 98.09 63 | 99.08 57 | 93.01 83 | 99.92 14 | 96.06 106 | 99.77 19 | 99.75 22 |
|
test_part2 | | | | | | 99.63 21 | 99.18 2 | | | | 99.27 8 | | | | | | |
|
v1.0 | | | 41.12 337 | 54.83 338 | 0.00 354 | 99.63 21 | 0.00 369 | 0.00 360 | 98.84 56 | 96.40 58 | 99.27 8 | 99.31 23 | 0.00 371 | 0.00 366 | 0.00 363 | 0.00 364 | 0.00 364 |
|
ACMMP_Plus | | | 98.61 14 | 98.30 26 | 99.55 3 | 99.62 23 | 98.95 6 | 98.82 100 | 98.81 64 | 95.80 74 | 99.16 16 | 99.47 5 | 95.37 42 | 99.92 14 | 97.89 34 | 99.75 31 | 99.79 5 |
|
MCST-MVS | | | 98.65 10 | 98.37 18 | 99.48 7 | 99.60 24 | 98.87 8 | 98.41 179 | 98.68 101 | 97.04 39 | 98.52 48 | 98.80 88 | 96.78 5 | 99.83 46 | 97.93 30 | 99.61 50 | 99.74 27 |
|
ESAPD | | | 98.92 2 | 98.67 4 | 99.65 1 | 99.58 25 | 99.20 1 | 98.42 178 | 98.91 42 | 97.58 7 | 99.54 3 | 99.46 6 | 97.10 2 | 99.94 3 | 97.64 48 | 99.84 7 | 99.83 2 |
|
APDe-MVS | | | 99.02 1 | 98.84 1 | 99.55 3 | 99.57 26 | 98.96 5 | 99.39 5 | 98.93 36 | 97.38 18 | 99.41 4 | 99.54 1 | 96.66 6 | 99.84 45 | 98.86 2 | 99.85 2 | 99.87 1 |
|
abl_6 | | | 98.30 42 | 98.03 40 | 99.13 40 | 99.56 27 | 97.76 54 | 99.13 49 | 98.82 61 | 96.14 63 | 99.26 10 | 99.37 14 | 93.33 78 | 99.93 10 | 96.96 71 | 99.67 41 | 99.69 37 |
|
DP-MVS Recon | | | 97.86 53 | 97.46 61 | 99.06 47 | 99.53 28 | 98.35 25 | 98.33 186 | 98.89 45 | 92.62 217 | 98.05 65 | 98.94 76 | 95.34 44 | 99.65 103 | 96.04 107 | 99.42 77 | 99.19 111 |
|
SMA-MVS | | | 98.58 19 | 98.25 30 | 99.56 2 | 99.51 29 | 99.04 4 | 98.95 73 | 98.80 71 | 93.67 177 | 99.37 6 | 99.52 3 | 96.52 10 | 99.89 28 | 98.06 26 | 99.81 9 | 99.76 21 |
|
APD-MVS | | | 98.35 37 | 98.00 42 | 99.42 11 | 99.51 29 | 98.72 10 | 98.80 109 | 98.82 61 | 94.52 137 | 99.23 12 | 99.25 31 | 95.54 39 | 99.80 61 | 96.52 94 | 99.77 19 | 99.74 27 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
HPM-MVS++ | | | 98.58 19 | 98.25 30 | 99.55 3 | 99.50 31 | 99.08 3 | 98.72 130 | 98.66 111 | 97.51 9 | 98.15 60 | 98.83 85 | 95.70 35 | 99.92 14 | 97.53 56 | 99.67 41 | 99.66 50 |
|
APD-MVS_3200maxsize | | | 98.53 27 | 98.33 25 | 99.15 39 | 99.50 31 | 97.92 48 | 99.15 44 | 98.81 64 | 96.24 60 | 99.20 14 | 99.37 14 | 95.30 45 | 99.80 61 | 97.73 43 | 99.67 41 | 99.72 32 |
|
114514_t | | | 96.93 99 | 96.27 110 | 98.92 55 | 99.50 31 | 97.63 57 | 98.85 94 | 98.90 43 | 84.80 333 | 97.77 84 | 99.11 49 | 92.84 84 | 99.66 102 | 94.85 143 | 99.77 19 | 99.47 79 |
|
PAPM_NR | | | 97.46 70 | 97.11 75 | 98.50 78 | 99.50 31 | 96.41 106 | 98.63 147 | 98.60 118 | 95.18 107 | 97.06 112 | 98.06 155 | 94.26 70 | 99.57 119 | 93.80 171 | 98.87 98 | 99.52 68 |
|
CDPH-MVS | | | 97.94 49 | 97.49 58 | 99.28 22 | 99.47 35 | 98.44 17 | 97.91 235 | 98.67 108 | 92.57 220 | 98.77 36 | 98.85 83 | 95.93 29 | 99.72 90 | 95.56 126 | 99.69 40 | 99.68 43 |
|
EI-MVSNet-Vis-set | | | 98.47 30 | 98.39 16 | 98.69 64 | 99.46 36 | 96.49 102 | 98.30 193 | 98.69 98 | 97.21 29 | 98.84 31 | 99.36 18 | 95.41 41 | 99.78 78 | 98.62 6 | 99.65 45 | 99.80 4 |
|
EI-MVSNet-UG-set | | | 98.41 32 | 98.34 22 | 98.61 69 | 99.45 37 | 96.32 110 | 98.28 195 | 98.68 101 | 97.17 32 | 98.74 38 | 99.37 14 | 95.25 47 | 99.79 73 | 98.57 8 | 99.54 66 | 99.73 29 |
|
F-COLMAP | | | 97.09 94 | 96.80 86 | 97.97 111 | 99.45 37 | 94.95 177 | 98.55 160 | 98.62 117 | 93.02 204 | 96.17 164 | 98.58 110 | 94.01 73 | 99.81 54 | 93.95 167 | 98.90 95 | 99.14 120 |
|
Regformer-3 | | | 98.59 17 | 98.50 12 | 98.86 59 | 99.43 39 | 97.05 77 | 98.40 180 | 98.68 101 | 97.43 14 | 99.06 18 | 99.31 23 | 95.80 34 | 99.77 83 | 98.62 6 | 99.76 25 | 99.78 8 |
|
Regformer-4 | | | 98.64 11 | 98.53 8 | 98.99 49 | 99.43 39 | 97.37 66 | 98.40 180 | 98.79 73 | 97.46 13 | 99.09 17 | 99.31 23 | 95.86 33 | 99.80 61 | 98.64 4 | 99.76 25 | 99.79 5 |
|
Regformer-1 | | | 98.66 9 | 98.51 11 | 99.12 42 | 99.35 41 | 97.81 53 | 98.37 182 | 98.76 79 | 97.49 11 | 99.20 14 | 99.21 35 | 96.08 21 | 99.79 73 | 98.42 16 | 99.73 36 | 99.75 22 |
|
Regformer-2 | | | 98.69 8 | 98.52 9 | 99.19 30 | 99.35 41 | 98.01 44 | 98.37 182 | 98.81 64 | 97.48 12 | 99.21 13 | 99.21 35 | 96.13 18 | 99.80 61 | 98.40 18 | 99.73 36 | 99.75 22 |
|
新几何1 | | | | | 99.16 37 | 99.34 43 | 98.01 44 | | 98.69 98 | 90.06 286 | 98.13 61 | 98.95 75 | 94.60 60 | 99.89 28 | 91.97 222 | 99.47 71 | 99.59 63 |
|
1121 | | | 97.37 81 | 96.77 92 | 99.16 37 | 99.34 43 | 97.99 47 | 98.19 205 | 98.68 101 | 90.14 285 | 98.01 72 | 98.97 68 | 94.80 58 | 99.87 37 | 93.36 180 | 99.46 74 | 99.61 58 |
|
DP-MVS | | | 96.59 111 | 95.93 120 | 98.57 71 | 99.34 43 | 96.19 114 | 98.70 134 | 98.39 159 | 89.45 303 | 94.52 191 | 99.35 20 | 91.85 105 | 99.85 42 | 92.89 199 | 98.88 96 | 99.68 43 |
|
SD-MVS | | | 98.64 11 | 98.68 3 | 98.53 76 | 99.33 46 | 98.36 24 | 98.90 78 | 98.85 55 | 97.28 22 | 99.72 1 | 99.39 9 | 96.63 8 | 97.60 305 | 98.17 23 | 99.85 2 | 99.64 55 |
|
HyFIR lowres test | | | 96.90 101 | 96.49 104 | 98.14 100 | 99.33 46 | 95.56 150 | 97.38 274 | 99.65 2 | 92.34 234 | 97.61 96 | 98.20 146 | 89.29 145 | 99.10 173 | 96.97 69 | 97.60 148 | 99.77 15 |
|
OMC-MVS | | | 97.55 69 | 97.34 65 | 98.20 97 | 99.33 46 | 95.92 135 | 98.28 195 | 98.59 119 | 95.52 85 | 97.97 75 | 99.10 51 | 93.28 80 | 99.49 131 | 95.09 140 | 98.88 96 | 99.19 111 |
|
原ACMM1 | | | | | 98.65 67 | 99.32 49 | 96.62 93 | | 98.67 108 | 93.27 198 | 97.81 83 | 98.97 68 | 95.18 49 | 99.83 46 | 93.84 169 | 99.46 74 | 99.50 73 |
|
CNVR-MVS | | | 98.78 4 | 98.56 7 | 99.45 10 | 99.32 49 | 98.87 8 | 98.47 171 | 98.81 64 | 97.72 4 | 98.76 37 | 99.16 45 | 97.05 3 | 99.78 78 | 98.06 26 | 99.66 44 | 99.69 37 |
|
TEST9 | | | | | | 99.31 51 | 98.50 15 | 97.92 232 | 98.73 88 | 92.63 216 | 97.74 87 | 98.68 99 | 96.20 14 | 99.80 61 | | | |
|
train_agg | | | 97.97 46 | 97.52 56 | 99.33 17 | 99.31 51 | 98.50 15 | 97.92 232 | 98.73 88 | 92.98 206 | 97.74 87 | 98.68 99 | 96.20 14 | 99.80 61 | 96.59 90 | 99.57 57 | 99.68 43 |
|
test_prior3 | | | 98.22 44 | 97.90 45 | 99.19 30 | 99.31 51 | 98.22 33 | 97.80 248 | 98.84 56 | 96.12 65 | 97.89 81 | 98.69 97 | 95.96 27 | 99.70 95 | 96.89 75 | 99.60 51 | 99.65 52 |
|
test_prior | | | | | 99.19 30 | 99.31 51 | 98.22 33 | | 98.84 56 | | | | | 99.70 95 | | | 99.65 52 |
|
PatchMatch-RL | | | 96.59 111 | 96.03 118 | 98.27 93 | 99.31 51 | 96.51 101 | 97.91 235 | 99.06 21 | 93.72 169 | 96.92 121 | 98.06 155 | 88.50 182 | 99.65 103 | 91.77 228 | 99.00 92 | 98.66 154 |
|
agg_prior1 | | | 97.95 48 | 97.51 57 | 99.28 22 | 99.30 56 | 98.38 20 | 97.81 247 | 98.72 90 | 93.16 200 | 97.57 99 | 98.66 102 | 96.14 17 | 99.81 54 | 96.63 89 | 99.56 63 | 99.66 50 |
|
agg_prior | | | | | | 99.30 56 | 98.38 20 | | 98.72 90 | | 97.57 99 | | | 99.81 54 | | | |
|
CHOSEN 1792x2688 | | | 97.12 92 | 96.80 86 | 98.08 106 | 99.30 56 | 94.56 217 | 98.05 221 | 99.71 1 | 93.57 181 | 97.09 108 | 98.91 80 | 88.17 187 | 99.89 28 | 96.87 81 | 99.56 63 | 99.81 3 |
|
test_8 | | | | | | 99.29 59 | 98.44 17 | 97.89 240 | 98.72 90 | 92.98 206 | 97.70 90 | 98.66 102 | 96.20 14 | 99.80 61 | | | |
|
agg_prior3 | | | 97.87 52 | 97.42 63 | 99.23 29 | 99.29 59 | 98.23 31 | 97.92 232 | 98.72 90 | 92.38 233 | 97.59 98 | 98.64 104 | 96.09 20 | 99.79 73 | 96.59 90 | 99.57 57 | 99.68 43 |
|
旧先验1 | | | | | | 99.29 59 | 97.48 62 | | 98.70 97 | | | 99.09 55 | 95.56 37 | | | 99.47 71 | 99.61 58 |
|
PLC | | 95.07 4 | 97.20 88 | 96.78 89 | 98.44 83 | 99.29 59 | 96.31 112 | 98.14 211 | 98.76 79 | 92.41 231 | 96.39 160 | 98.31 136 | 94.92 55 | 99.78 78 | 94.06 165 | 98.77 103 | 99.23 107 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
COLMAP_ROB | | 93.27 12 | 95.33 175 | 94.87 166 | 96.71 192 | 99.29 59 | 93.24 255 | 98.58 153 | 98.11 211 | 89.92 291 | 93.57 239 | 99.10 51 | 86.37 227 | 99.79 73 | 90.78 245 | 98.10 131 | 97.09 213 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
NCCC | | | 98.61 14 | 98.35 21 | 99.38 12 | 99.28 64 | 98.61 13 | 98.45 172 | 98.76 79 | 97.82 3 | 98.45 53 | 98.93 77 | 96.65 7 | 99.83 46 | 97.38 61 | 99.41 78 | 99.71 34 |
|
PVSNet_Blended_VisFu | | | 97.70 60 | 97.46 61 | 98.44 83 | 99.27 65 | 95.91 137 | 98.63 147 | 99.16 17 | 94.48 140 | 97.67 92 | 98.88 81 | 92.80 85 | 99.91 23 | 97.11 66 | 99.12 89 | 99.50 73 |
|
MVS_111021_LR | | | 98.34 38 | 98.23 34 | 98.67 66 | 99.27 65 | 96.90 83 | 97.95 230 | 99.58 3 | 97.14 34 | 98.44 54 | 99.01 65 | 95.03 53 | 99.62 110 | 97.91 31 | 99.75 31 | 99.50 73 |
|
MSLP-MVS++ | | | 98.56 23 | 98.57 6 | 98.55 73 | 99.26 67 | 96.80 86 | 98.71 131 | 99.05 23 | 97.28 22 | 98.84 31 | 99.28 28 | 96.47 11 | 99.40 137 | 98.52 14 | 99.70 39 | 99.47 79 |
|
AllTest | | | 95.24 180 | 94.65 180 | 96.99 177 | 99.25 68 | 93.21 256 | 98.59 151 | 98.18 192 | 91.36 260 | 93.52 241 | 98.77 92 | 84.67 260 | 99.72 90 | 89.70 272 | 97.87 138 | 98.02 181 |
|
TestCases | | | | | 96.99 177 | 99.25 68 | 93.21 256 | | 98.18 192 | 91.36 260 | 93.52 241 | 98.77 92 | 84.67 260 | 99.72 90 | 89.70 272 | 97.87 138 | 98.02 181 |
|
PVSNet_BlendedMVS | | | 96.73 106 | 96.60 99 | 97.12 170 | 99.25 68 | 95.35 159 | 98.26 197 | 99.26 8 | 94.28 143 | 97.94 77 | 97.46 202 | 92.74 86 | 99.81 54 | 96.88 78 | 93.32 237 | 96.20 298 |
|
PVSNet_Blended | | | 97.38 80 | 97.12 73 | 98.14 100 | 99.25 68 | 95.35 159 | 97.28 284 | 99.26 8 | 93.13 201 | 97.94 77 | 98.21 145 | 92.74 86 | 99.81 54 | 96.88 78 | 99.40 80 | 99.27 103 |
|
DeepC-MVS | | 95.98 3 | 97.88 51 | 97.58 52 | 98.77 61 | 99.25 68 | 96.93 81 | 98.83 98 | 98.75 82 | 96.96 42 | 96.89 123 | 99.50 4 | 90.46 130 | 99.87 37 | 97.84 38 | 99.76 25 | 99.52 68 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
DeepC-MVS_fast | | 96.70 1 | 98.55 24 | 98.34 22 | 99.18 34 | 99.25 68 | 98.04 42 | 98.50 168 | 98.78 75 | 97.72 4 | 98.92 30 | 99.28 28 | 95.27 46 | 99.82 52 | 97.55 54 | 99.77 19 | 99.69 37 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
test222 | | | | | | 99.23 74 | 97.17 75 | 97.40 272 | 98.66 111 | 88.68 310 | 98.05 65 | 98.96 73 | 94.14 71 | | | 99.53 67 | 99.61 58 |
|
TSAR-MVS + GP. | | | 98.38 34 | 98.24 33 | 98.81 60 | 99.22 75 | 97.25 72 | 98.11 216 | 98.29 174 | 97.19 31 | 98.99 24 | 99.02 61 | 96.22 13 | 99.67 101 | 98.52 14 | 98.56 112 | 99.51 71 |
|
SteuartSystems-ACMMP | | | 98.90 3 | 98.75 2 | 99.36 14 | 99.22 75 | 98.43 19 | 99.10 53 | 98.87 51 | 97.38 18 | 99.35 7 | 99.40 8 | 97.78 1 | 99.87 37 | 97.77 41 | 99.85 2 | 99.78 8 |
Skip Steuart: Steuart Systems R&D Blog. |
MVS_111021_HR | | | 98.47 30 | 98.34 22 | 98.88 58 | 99.22 75 | 97.32 67 | 97.91 235 | 99.58 3 | 97.20 30 | 98.33 58 | 99.00 66 | 95.99 26 | 99.64 105 | 98.05 28 | 99.76 25 | 99.69 37 |
|
testdata | | | | | 98.26 94 | 99.20 78 | 95.36 157 | | 98.68 101 | 91.89 245 | 98.60 45 | 99.10 51 | 94.44 67 | 99.82 52 | 94.27 160 | 99.44 76 | 99.58 65 |
|
PVSNet | | 91.96 18 | 96.35 119 | 96.15 114 | 96.96 180 | 99.17 79 | 92.05 269 | 96.08 321 | 98.68 101 | 93.69 173 | 97.75 86 | 97.80 180 | 88.86 160 | 99.69 99 | 94.26 161 | 99.01 91 | 99.15 118 |
|
test12 | | | | | 99.18 34 | 99.16 80 | 98.19 35 | | 98.53 132 | | 98.07 64 | | 95.13 51 | 99.72 90 | | 99.56 63 | 99.63 57 |
|
AdaColmap | | | 97.15 91 | 96.70 94 | 98.48 80 | 99.16 80 | 96.69 92 | 98.01 225 | 98.89 45 | 94.44 142 | 96.83 125 | 98.68 99 | 90.69 128 | 99.76 85 | 94.36 156 | 99.29 85 | 98.98 135 |
|
PHI-MVS | | | 98.34 38 | 98.06 39 | 99.18 34 | 99.15 82 | 98.12 40 | 99.04 62 | 99.09 19 | 93.32 195 | 98.83 33 | 99.10 51 | 96.54 9 | 99.83 46 | 97.70 45 | 99.76 25 | 99.59 63 |
|
TAPA-MVS | | 93.98 7 | 95.35 173 | 94.56 184 | 97.74 124 | 99.13 83 | 94.83 195 | 98.33 186 | 98.64 116 | 86.62 319 | 96.29 162 | 98.61 105 | 94.00 74 | 99.29 146 | 80.00 332 | 99.41 78 | 99.09 125 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
MG-MVS | | | 97.81 55 | 97.60 51 | 98.44 83 | 99.12 84 | 95.97 121 | 97.75 252 | 98.78 75 | 96.89 43 | 98.46 49 | 99.22 34 | 93.90 75 | 99.68 100 | 94.81 146 | 99.52 68 | 99.67 48 |
|
Anonymous20231211 | | | 94.10 247 | 93.26 256 | 96.61 209 | 99.11 85 | 94.28 227 | 99.01 65 | 98.88 48 | 86.43 321 | 92.81 261 | 97.57 197 | 81.66 294 | 98.68 217 | 94.83 144 | 89.02 284 | 96.88 233 |
|
view600 | | | 95.60 148 | 94.93 160 | 97.62 137 | 99.05 86 | 94.85 184 | 99.09 54 | 97.01 295 | 95.36 95 | 96.52 145 | 97.37 207 | 84.55 263 | 99.59 112 | 89.07 283 | 96.39 171 | 98.40 166 |
|
view800 | | | 95.60 148 | 94.93 160 | 97.62 137 | 99.05 86 | 94.85 184 | 99.09 54 | 97.01 295 | 95.36 95 | 96.52 145 | 97.37 207 | 84.55 263 | 99.59 112 | 89.07 283 | 96.39 171 | 98.40 166 |
|
conf0.05thres1000 | | | 95.60 148 | 94.93 160 | 97.62 137 | 99.05 86 | 94.85 184 | 99.09 54 | 97.01 295 | 95.36 95 | 96.52 145 | 97.37 207 | 84.55 263 | 99.59 112 | 89.07 283 | 96.39 171 | 98.40 166 |
|
tfpn | | | 95.60 148 | 94.93 160 | 97.62 137 | 99.05 86 | 94.85 184 | 99.09 54 | 97.01 295 | 95.36 95 | 96.52 145 | 97.37 207 | 84.55 263 | 99.59 112 | 89.07 283 | 96.39 171 | 98.40 166 |
|
CNLPA | | | 97.45 73 | 97.03 79 | 98.73 62 | 99.05 86 | 97.44 65 | 98.07 220 | 98.53 132 | 95.32 101 | 96.80 129 | 98.53 112 | 93.32 79 | 99.72 90 | 94.31 159 | 99.31 84 | 99.02 131 |
|
Anonymous20240529 | | | 95.10 186 | 94.22 198 | 97.75 123 | 99.01 91 | 94.26 229 | 98.87 86 | 98.83 60 | 85.79 328 | 96.64 133 | 98.97 68 | 78.73 312 | 99.85 42 | 96.27 100 | 94.89 208 | 99.12 122 |
|
Anonymous202405211 | | | 95.28 178 | 94.49 186 | 97.67 133 | 99.00 92 | 93.75 243 | 98.70 134 | 97.04 291 | 90.66 275 | 96.49 156 | 98.80 88 | 78.13 315 | 99.83 46 | 96.21 103 | 95.36 205 | 99.44 86 |
|
tfpn1000 | | | 95.72 139 | 95.11 150 | 97.58 143 | 99.00 92 | 95.73 145 | 99.24 21 | 95.49 337 | 94.08 148 | 96.87 124 | 97.45 204 | 85.81 243 | 99.30 143 | 91.78 227 | 96.22 188 | 97.71 194 |
|
DELS-MVS | | | 98.40 33 | 98.20 36 | 98.99 49 | 99.00 92 | 97.66 55 | 97.75 252 | 98.89 45 | 97.71 6 | 98.33 58 | 98.97 68 | 94.97 54 | 99.88 36 | 98.42 16 | 99.76 25 | 99.42 88 |
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 |
DeepPCF-MVS | | 96.37 2 | 97.93 50 | 98.48 14 | 96.30 239 | 99.00 92 | 89.54 303 | 97.43 271 | 98.87 51 | 98.16 2 | 99.26 10 | 99.38 13 | 96.12 19 | 99.64 105 | 98.30 21 | 99.77 19 | 99.72 32 |
|
tfpn111 | | | 95.43 163 | 94.74 176 | 97.51 147 | 98.98 96 | 94.92 178 | 98.87 86 | 96.90 303 | 95.38 91 | 96.61 135 | 96.88 264 | 84.29 270 | 99.59 112 | 88.43 293 | 96.32 177 | 98.02 181 |
|
conf200view11 | | | 95.40 168 | 94.70 178 | 97.50 152 | 98.98 96 | 94.92 178 | 98.87 86 | 96.90 303 | 95.38 91 | 96.61 135 | 96.88 264 | 84.29 270 | 99.56 121 | 88.11 299 | 96.29 179 | 98.02 181 |
|
thres100view900 | | | 95.38 169 | 94.70 178 | 97.41 156 | 98.98 96 | 94.92 178 | 98.87 86 | 96.90 303 | 95.38 91 | 96.61 135 | 96.88 264 | 84.29 270 | 99.56 121 | 88.11 299 | 96.29 179 | 97.76 189 |
|
thres600view7 | | | 95.49 159 | 94.77 174 | 97.67 133 | 98.98 96 | 95.02 170 | 98.85 94 | 96.90 303 | 95.38 91 | 96.63 134 | 96.90 261 | 84.29 270 | 99.59 112 | 88.65 292 | 96.33 176 | 98.40 166 |
|
tfpn_ndepth | | | 95.53 154 | 94.90 165 | 97.39 161 | 98.96 100 | 95.88 140 | 99.05 59 | 95.27 338 | 93.80 164 | 96.95 116 | 96.93 259 | 85.53 247 | 99.40 137 | 91.54 233 | 96.10 191 | 96.89 231 |
|
tfpn200view9 | | | 95.32 176 | 94.62 181 | 97.43 155 | 98.94 101 | 94.98 174 | 98.68 140 | 96.93 301 | 95.33 99 | 96.55 141 | 96.53 280 | 84.23 275 | 99.56 121 | 88.11 299 | 96.29 179 | 97.76 189 |
|
thres400 | | | 95.38 169 | 94.62 181 | 97.65 136 | 98.94 101 | 94.98 174 | 98.68 140 | 96.93 301 | 95.33 99 | 96.55 141 | 96.53 280 | 84.23 275 | 99.56 121 | 88.11 299 | 96.29 179 | 98.40 166 |
|
conf0.01 | | | 95.56 152 | 94.84 168 | 97.72 125 | 98.90 103 | 95.93 128 | 99.17 36 | 95.70 329 | 93.42 186 | 96.50 150 | 97.16 222 | 86.12 231 | 99.22 152 | 90.51 251 | 96.06 192 | 98.02 181 |
|
conf0.002 | | | 95.56 152 | 94.84 168 | 97.72 125 | 98.90 103 | 95.93 128 | 99.17 36 | 95.70 329 | 93.42 186 | 96.50 150 | 97.16 222 | 86.12 231 | 99.22 152 | 90.51 251 | 96.06 192 | 98.02 181 |
|
thresconf0.02 | | | 95.50 155 | 94.84 168 | 97.51 147 | 98.90 103 | 95.93 128 | 99.17 36 | 95.70 329 | 93.42 186 | 96.50 150 | 97.16 222 | 86.12 231 | 99.22 152 | 90.51 251 | 96.06 192 | 97.37 204 |
|
tfpn_n400 | | | 95.50 155 | 94.84 168 | 97.51 147 | 98.90 103 | 95.93 128 | 99.17 36 | 95.70 329 | 93.42 186 | 96.50 150 | 97.16 222 | 86.12 231 | 99.22 152 | 90.51 251 | 96.06 192 | 97.37 204 |
|
tfpnconf | | | 95.50 155 | 94.84 168 | 97.51 147 | 98.90 103 | 95.93 128 | 99.17 36 | 95.70 329 | 93.42 186 | 96.50 150 | 97.16 222 | 86.12 231 | 99.22 152 | 90.51 251 | 96.06 192 | 97.37 204 |
|
tfpnview11 | | | 95.50 155 | 94.84 168 | 97.51 147 | 98.90 103 | 95.93 128 | 99.17 36 | 95.70 329 | 93.42 186 | 96.50 150 | 97.16 222 | 86.12 231 | 99.22 152 | 90.51 251 | 96.06 192 | 97.37 204 |
|
MVS_0304 | | | 97.70 60 | 97.25 68 | 99.07 45 | 98.90 103 | 97.83 51 | 98.20 201 | 98.74 83 | 97.51 9 | 98.03 68 | 99.06 59 | 86.12 231 | 99.93 10 | 99.02 1 | 99.64 47 | 99.44 86 |
|
MSDG | | | 95.93 131 | 95.30 144 | 97.83 118 | 98.90 103 | 95.36 157 | 96.83 308 | 98.37 162 | 91.32 264 | 94.43 201 | 98.73 96 | 90.27 134 | 99.60 111 | 90.05 264 | 98.82 101 | 98.52 160 |
|
RPSCF | | | 94.87 198 | 95.40 134 | 93.26 316 | 98.89 111 | 82.06 341 | 98.33 186 | 98.06 223 | 90.30 282 | 96.56 139 | 99.26 30 | 87.09 215 | 99.49 131 | 93.82 170 | 96.32 177 | 98.24 176 |
|
VNet | | | 97.79 56 | 97.40 64 | 98.96 53 | 98.88 112 | 97.55 60 | 98.63 147 | 98.93 36 | 96.74 47 | 99.02 20 | 98.84 84 | 90.33 133 | 99.83 46 | 98.53 10 | 96.66 161 | 99.50 73 |
|
LFMVS | | | 95.86 134 | 94.98 156 | 98.47 81 | 98.87 113 | 96.32 110 | 98.84 97 | 96.02 323 | 93.40 192 | 98.62 43 | 99.20 38 | 74.99 330 | 99.63 108 | 97.72 44 | 97.20 152 | 99.46 83 |
|
UA-Net | | | 97.96 47 | 97.62 50 | 98.98 51 | 98.86 114 | 97.47 63 | 98.89 82 | 99.08 20 | 96.67 50 | 98.72 39 | 99.54 1 | 93.15 81 | 99.81 54 | 94.87 142 | 98.83 100 | 99.65 52 |
|
WTY-MVS | | | 97.37 81 | 96.92 83 | 98.72 63 | 98.86 114 | 96.89 85 | 98.31 191 | 98.71 95 | 95.26 103 | 97.67 92 | 98.56 111 | 92.21 96 | 99.78 78 | 95.89 112 | 96.85 157 | 99.48 78 |
|
IS-MVSNet | | | 97.22 86 | 96.88 84 | 98.25 95 | 98.85 116 | 96.36 108 | 99.19 35 | 97.97 228 | 95.39 90 | 97.23 105 | 98.99 67 | 91.11 120 | 98.93 194 | 94.60 150 | 98.59 110 | 99.47 79 |
|
VDD-MVS | | | 95.82 136 | 95.23 146 | 97.61 142 | 98.84 117 | 93.98 235 | 98.68 140 | 97.40 271 | 95.02 117 | 97.95 76 | 99.34 21 | 74.37 335 | 99.78 78 | 98.64 4 | 96.80 158 | 99.08 128 |
|
CHOSEN 280x420 | | | 97.18 89 | 97.18 72 | 97.20 164 | 98.81 118 | 93.27 253 | 95.78 329 | 99.15 18 | 95.25 104 | 96.79 130 | 98.11 151 | 92.29 92 | 99.07 176 | 98.56 9 | 99.85 2 | 99.25 105 |
|
thres200 | | | 95.25 179 | 94.57 183 | 97.28 162 | 98.81 118 | 94.92 178 | 98.20 201 | 97.11 287 | 95.24 106 | 96.54 143 | 96.22 293 | 84.58 262 | 99.53 128 | 87.93 304 | 96.50 168 | 97.39 202 |
|
XVG-OURS-SEG-HR | | | 96.51 114 | 96.34 107 | 97.02 176 | 98.77 120 | 93.76 241 | 97.79 250 | 98.50 141 | 95.45 87 | 96.94 118 | 99.09 55 | 87.87 199 | 99.55 127 | 96.76 85 | 95.83 201 | 97.74 191 |
|
XVG-OURS | | | 96.55 113 | 96.41 105 | 96.99 177 | 98.75 121 | 93.76 241 | 97.50 268 | 98.52 134 | 95.67 78 | 96.83 125 | 99.30 27 | 88.95 157 | 99.53 128 | 95.88 113 | 96.26 184 | 97.69 195 |
|
0601test | | | 97.22 86 | 96.78 89 | 98.54 75 | 98.73 122 | 96.60 96 | 98.45 172 | 98.31 168 | 94.70 127 | 98.02 69 | 98.42 122 | 90.80 126 | 99.70 95 | 96.81 83 | 96.79 159 | 99.34 91 |
|
CANet | | | 98.05 45 | 97.76 47 | 98.90 57 | 98.73 122 | 97.27 69 | 98.35 184 | 98.78 75 | 97.37 20 | 97.72 89 | 98.96 73 | 91.53 115 | 99.92 14 | 98.79 3 | 99.65 45 | 99.51 71 |
|
Vis-MVSNet (Re-imp) | | | 96.87 102 | 96.55 101 | 97.83 118 | 98.73 122 | 95.46 154 | 99.20 33 | 98.30 172 | 94.96 121 | 96.60 138 | 98.87 82 | 90.05 136 | 98.59 224 | 93.67 174 | 98.60 109 | 99.46 83 |
|
PAPR | | | 96.84 103 | 96.24 112 | 98.65 67 | 98.72 125 | 96.92 82 | 97.36 278 | 98.57 125 | 93.33 194 | 96.67 132 | 97.57 197 | 94.30 69 | 99.56 121 | 91.05 243 | 98.59 110 | 99.47 79 |
|
canonicalmvs | | | 97.67 62 | 97.23 70 | 98.98 51 | 98.70 126 | 98.38 20 | 99.34 11 | 98.39 159 | 96.76 46 | 97.67 92 | 97.40 206 | 92.26 93 | 99.49 131 | 98.28 22 | 96.28 183 | 99.08 128 |
|
API-MVS | | | 97.41 78 | 97.25 68 | 97.91 113 | 98.70 126 | 96.80 86 | 98.82 100 | 98.69 98 | 94.53 136 | 98.11 62 | 98.28 138 | 94.50 65 | 99.57 119 | 94.12 164 | 99.49 69 | 97.37 204 |
|
MAR-MVS | | | 96.91 100 | 96.40 106 | 98.45 82 | 98.69 128 | 96.90 83 | 98.66 145 | 98.68 101 | 92.40 232 | 97.07 111 | 97.96 162 | 91.54 114 | 99.75 87 | 93.68 173 | 98.92 94 | 98.69 151 |
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 |
PS-MVSNAJ | | | 97.73 57 | 97.77 46 | 97.62 137 | 98.68 129 | 95.58 148 | 97.34 280 | 98.51 136 | 97.29 21 | 98.66 41 | 97.88 170 | 94.51 62 | 99.90 26 | 97.87 35 | 99.17 88 | 97.39 202 |
|
alignmvs | | | 97.56 68 | 97.07 78 | 99.01 48 | 98.66 130 | 98.37 23 | 98.83 98 | 98.06 223 | 96.74 47 | 98.00 74 | 97.65 190 | 90.80 126 | 99.48 135 | 98.37 19 | 96.56 165 | 99.19 111 |
|
Vis-MVSNet | | | 97.42 76 | 97.11 75 | 98.34 90 | 98.66 130 | 96.23 113 | 99.22 29 | 99.00 26 | 96.63 52 | 98.04 67 | 99.21 35 | 88.05 193 | 99.35 142 | 96.01 109 | 99.21 86 | 99.45 85 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
EPP-MVSNet | | | 97.46 70 | 97.28 67 | 97.99 110 | 98.64 132 | 95.38 156 | 99.33 13 | 98.31 168 | 93.61 180 | 97.19 106 | 99.07 58 | 94.05 72 | 99.23 150 | 96.89 75 | 98.43 119 | 99.37 90 |
|
ab-mvs | | | 96.42 117 | 95.71 128 | 98.55 73 | 98.63 133 | 96.75 89 | 97.88 241 | 98.74 83 | 93.84 161 | 96.54 143 | 98.18 147 | 85.34 252 | 99.75 87 | 95.93 111 | 96.35 175 | 99.15 118 |
|
PCF-MVS | | 93.45 11 | 94.68 215 | 93.43 251 | 98.42 86 | 98.62 134 | 96.77 88 | 95.48 331 | 98.20 187 | 84.63 334 | 93.34 246 | 98.32 135 | 88.55 179 | 99.81 54 | 84.80 323 | 98.96 93 | 98.68 152 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
xiu_mvs_v2_base | | | 97.66 63 | 97.70 49 | 97.56 145 | 98.61 135 | 95.46 154 | 97.44 269 | 98.46 146 | 97.15 33 | 98.65 42 | 98.15 148 | 94.33 68 | 99.80 61 | 97.84 38 | 98.66 108 | 97.41 200 |
|
sss | | | 97.39 79 | 96.98 81 | 98.61 69 | 98.60 136 | 96.61 95 | 98.22 199 | 98.93 36 | 93.97 155 | 98.01 72 | 98.48 117 | 91.98 103 | 99.85 42 | 96.45 96 | 98.15 129 | 99.39 89 |
|
Test_1112_low_res | | | 96.34 120 | 95.66 132 | 98.36 89 | 98.56 137 | 95.94 125 | 97.71 254 | 98.07 221 | 92.10 240 | 94.79 186 | 97.29 215 | 91.75 107 | 99.56 121 | 94.17 162 | 96.50 168 | 99.58 65 |
|
1112_ss | | | 96.63 108 | 96.00 119 | 98.50 78 | 98.56 137 | 96.37 107 | 98.18 209 | 98.10 216 | 92.92 208 | 94.84 182 | 98.43 120 | 92.14 98 | 99.58 118 | 94.35 157 | 96.51 167 | 99.56 67 |
|
BH-untuned | | | 95.95 130 | 95.72 125 | 96.65 203 | 98.55 139 | 92.26 266 | 98.23 198 | 97.79 235 | 93.73 168 | 94.62 188 | 98.01 159 | 88.97 156 | 99.00 185 | 93.04 190 | 98.51 113 | 98.68 152 |
|
LS3D | | | 97.16 90 | 96.66 98 | 98.68 65 | 98.53 140 | 97.19 74 | 98.93 76 | 98.90 43 | 92.83 214 | 95.99 169 | 99.37 14 | 92.12 99 | 99.87 37 | 93.67 174 | 99.57 57 | 98.97 136 |
|
casdiffmvs1 | | | 97.72 58 | 97.49 58 | 98.41 87 | 98.52 141 | 96.71 91 | 99.14 45 | 98.32 167 | 95.15 110 | 98.46 49 | 98.31 136 | 93.10 82 | 99.21 158 | 98.14 24 | 98.27 125 | 99.31 95 |
|
HY-MVS | | 93.96 8 | 96.82 104 | 96.23 113 | 98.57 71 | 98.46 142 | 97.00 78 | 98.14 211 | 98.21 184 | 93.95 156 | 96.72 131 | 97.99 161 | 91.58 110 | 99.76 85 | 94.51 154 | 96.54 166 | 98.95 140 |
|
xiu_mvs_v1_base_debu | | | 97.60 64 | 97.56 53 | 97.72 125 | 98.35 143 | 95.98 117 | 97.86 243 | 98.51 136 | 97.13 35 | 99.01 21 | 98.40 123 | 91.56 111 | 99.80 61 | 98.53 10 | 98.68 104 | 97.37 204 |
|
xiu_mvs_v1_base | | | 97.60 64 | 97.56 53 | 97.72 125 | 98.35 143 | 95.98 117 | 97.86 243 | 98.51 136 | 97.13 35 | 99.01 21 | 98.40 123 | 91.56 111 | 99.80 61 | 98.53 10 | 98.68 104 | 97.37 204 |
|
xiu_mvs_v1_base_debi | | | 97.60 64 | 97.56 53 | 97.72 125 | 98.35 143 | 95.98 117 | 97.86 243 | 98.51 136 | 97.13 35 | 99.01 21 | 98.40 123 | 91.56 111 | 99.80 61 | 98.53 10 | 98.68 104 | 97.37 204 |
|
casdiffmvs | | | 97.42 76 | 97.12 73 | 98.31 92 | 98.35 143 | 96.55 100 | 99.05 59 | 98.20 187 | 94.97 120 | 97.55 101 | 98.11 151 | 92.33 91 | 99.18 161 | 97.70 45 | 97.85 140 | 99.18 115 |
|
BH-w/o | | | 95.38 169 | 95.08 152 | 96.26 241 | 98.34 147 | 91.79 273 | 97.70 255 | 97.43 268 | 92.87 211 | 94.24 215 | 97.22 220 | 88.66 175 | 98.84 205 | 91.55 232 | 97.70 146 | 98.16 178 |
|
MVS_Test | | | 97.28 84 | 97.00 80 | 98.13 102 | 98.33 148 | 95.97 121 | 98.74 125 | 98.07 221 | 94.27 144 | 98.44 54 | 98.07 154 | 92.48 88 | 99.26 147 | 96.43 97 | 98.19 128 | 99.16 117 |
|
BH-RMVSNet | | | 95.92 132 | 95.32 142 | 97.69 131 | 98.32 149 | 94.64 209 | 98.19 205 | 97.45 266 | 94.56 135 | 96.03 167 | 98.61 105 | 85.02 255 | 99.12 166 | 90.68 247 | 99.06 90 | 99.30 99 |
|
Fast-Effi-MVS+ | | | 96.28 123 | 95.70 129 | 98.03 109 | 98.29 150 | 95.97 121 | 98.58 153 | 98.25 180 | 91.74 249 | 95.29 176 | 97.23 219 | 91.03 123 | 99.15 163 | 92.90 197 | 97.96 134 | 98.97 136 |
|
UGNet | | | 96.78 105 | 96.30 109 | 98.19 99 | 98.24 151 | 95.89 139 | 98.88 85 | 98.93 36 | 97.39 17 | 96.81 128 | 97.84 174 | 82.60 289 | 99.90 26 | 96.53 93 | 99.49 69 | 98.79 146 |
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 |
MVSTER | | | 96.06 127 | 95.72 125 | 97.08 174 | 98.23 152 | 95.93 128 | 98.73 128 | 98.27 175 | 94.86 125 | 95.07 177 | 98.09 153 | 88.21 186 | 98.54 229 | 96.59 90 | 93.46 232 | 96.79 242 |
|
GBi-Net | | | 94.49 225 | 93.80 228 | 96.56 217 | 98.21 153 | 95.00 171 | 98.82 100 | 98.18 192 | 92.46 221 | 94.09 223 | 97.07 235 | 81.16 295 | 97.95 291 | 92.08 215 | 92.14 248 | 96.72 250 |
|
test1 | | | 94.49 225 | 93.80 228 | 96.56 217 | 98.21 153 | 95.00 171 | 98.82 100 | 98.18 192 | 92.46 221 | 94.09 223 | 97.07 235 | 81.16 295 | 97.95 291 | 92.08 215 | 92.14 248 | 96.72 250 |
|
FMVSNet2 | | | 94.47 227 | 93.61 241 | 97.04 175 | 98.21 153 | 96.43 105 | 98.79 114 | 98.27 175 | 92.46 221 | 93.50 243 | 97.09 233 | 81.16 295 | 98.00 289 | 91.09 239 | 91.93 252 | 96.70 254 |
|
Effi-MVS+ | | | 97.12 92 | 96.69 95 | 98.39 88 | 98.19 156 | 96.72 90 | 97.37 276 | 98.43 154 | 93.71 170 | 97.65 95 | 98.02 157 | 92.20 97 | 99.25 148 | 96.87 81 | 97.79 142 | 99.19 111 |
|
mvs_anonymous | | | 96.70 107 | 96.53 103 | 97.18 166 | 98.19 156 | 93.78 240 | 98.31 191 | 98.19 189 | 94.01 151 | 94.47 193 | 98.27 141 | 92.08 101 | 98.46 245 | 97.39 60 | 97.91 136 | 99.31 95 |
|
LCM-MVSNet-Re | | | 95.22 181 | 95.32 142 | 94.91 288 | 98.18 158 | 87.85 326 | 98.75 121 | 95.66 335 | 95.11 112 | 88.96 308 | 96.85 268 | 90.26 135 | 97.65 303 | 95.65 124 | 98.44 117 | 99.22 108 |
|
FMVSNet3 | | | 94.97 193 | 94.26 197 | 97.11 171 | 98.18 158 | 96.62 93 | 98.56 158 | 98.26 179 | 93.67 177 | 94.09 223 | 97.10 231 | 84.25 274 | 98.01 288 | 92.08 215 | 92.14 248 | 96.70 254 |
|
CANet_DTU | | | 96.96 98 | 96.55 101 | 98.21 96 | 98.17 160 | 96.07 116 | 97.98 228 | 98.21 184 | 97.24 28 | 97.13 107 | 98.93 77 | 86.88 220 | 99.91 23 | 95.00 141 | 99.37 82 | 98.66 154 |
|
diffmvs | | | 97.03 95 | 96.75 93 | 97.88 115 | 98.14 161 | 95.25 163 | 98.54 162 | 98.13 203 | 95.17 108 | 97.03 114 | 97.94 164 | 91.83 106 | 99.30 143 | 96.01 109 | 97.94 135 | 99.11 123 |
|
IterMVS-LS | | | 95.46 161 | 95.21 147 | 96.22 242 | 98.12 162 | 93.72 245 | 98.32 190 | 98.13 203 | 93.71 170 | 94.26 213 | 97.31 214 | 92.24 94 | 98.10 282 | 94.63 148 | 90.12 267 | 96.84 238 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
VDDNet | | | 95.36 172 | 94.53 185 | 97.86 116 | 98.10 163 | 95.13 167 | 98.85 94 | 97.75 237 | 90.46 278 | 98.36 56 | 99.39 9 | 73.27 337 | 99.64 105 | 97.98 29 | 96.58 164 | 98.81 145 |
|
MVSFormer | | | 97.57 67 | 97.49 58 | 97.84 117 | 98.07 164 | 95.76 143 | 99.47 2 | 98.40 157 | 94.98 118 | 98.79 34 | 98.83 85 | 92.34 89 | 98.41 260 | 96.91 73 | 99.59 54 | 99.34 91 |
|
lupinMVS | | | 97.44 74 | 97.22 71 | 98.12 103 | 98.07 164 | 95.76 143 | 97.68 257 | 97.76 236 | 94.50 138 | 98.79 34 | 98.61 105 | 92.34 89 | 99.30 143 | 97.58 51 | 99.59 54 | 99.31 95 |
|
TAMVS | | | 97.02 96 | 96.79 88 | 97.70 130 | 98.06 166 | 95.31 161 | 98.52 163 | 98.31 168 | 93.95 156 | 97.05 113 | 98.61 105 | 93.49 77 | 98.52 236 | 95.33 132 | 97.81 141 | 99.29 101 |
|
CDS-MVSNet | | | 96.99 97 | 96.69 95 | 97.90 114 | 98.05 167 | 95.98 117 | 98.20 201 | 98.33 166 | 93.67 177 | 96.95 116 | 98.49 116 | 93.54 76 | 98.42 253 | 95.24 138 | 97.74 145 | 99.31 95 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
ADS-MVSNet2 | | | 94.58 222 | 94.40 193 | 95.11 284 | 98.00 168 | 88.74 314 | 96.04 322 | 97.30 279 | 90.15 283 | 96.47 157 | 96.64 277 | 87.89 197 | 97.56 307 | 90.08 262 | 97.06 153 | 99.02 131 |
|
ADS-MVSNet | | | 95.00 189 | 94.45 191 | 96.63 206 | 98.00 168 | 91.91 271 | 96.04 322 | 97.74 238 | 90.15 283 | 96.47 157 | 96.64 277 | 87.89 197 | 98.96 189 | 90.08 262 | 97.06 153 | 99.02 131 |
|
IterMVS | | | 94.09 248 | 93.85 226 | 94.80 294 | 97.99 170 | 90.35 295 | 97.18 289 | 98.12 206 | 93.68 175 | 92.46 272 | 97.34 211 | 84.05 279 | 97.41 310 | 92.51 209 | 91.33 259 | 96.62 269 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
PVSNet_0 | | 88.72 19 | 91.28 295 | 90.03 298 | 95.00 286 | 97.99 170 | 87.29 329 | 94.84 338 | 98.50 141 | 92.06 241 | 89.86 300 | 95.19 310 | 79.81 307 | 99.39 139 | 92.27 212 | 69.79 350 | 98.33 174 |
|
semantic-postprocess | | | | | 94.85 291 | 97.98 172 | 90.56 293 | | 98.11 211 | 93.75 165 | 92.58 266 | 97.48 201 | 83.91 281 | 97.41 310 | 92.48 210 | 91.30 260 | 96.58 274 |
|
EI-MVSNet | | | 95.96 129 | 95.83 123 | 96.36 234 | 97.93 173 | 93.70 246 | 98.12 214 | 98.27 175 | 93.70 172 | 95.07 177 | 99.02 61 | 92.23 95 | 98.54 229 | 94.68 147 | 93.46 232 | 96.84 238 |
|
CVMVSNet | | | 95.43 163 | 96.04 117 | 93.57 312 | 97.93 173 | 83.62 335 | 98.12 214 | 98.59 119 | 95.68 77 | 96.56 139 | 99.02 61 | 87.51 209 | 97.51 308 | 93.56 177 | 97.44 149 | 99.60 61 |
|
PMMVS | | | 96.60 109 | 96.33 108 | 97.41 156 | 97.90 175 | 93.93 236 | 97.35 279 | 98.41 155 | 92.84 213 | 97.76 85 | 97.45 204 | 91.10 121 | 99.20 159 | 96.26 101 | 97.91 136 | 99.11 123 |
|
Effi-MVS+-dtu | | | 96.29 121 | 96.56 100 | 95.51 264 | 97.89 176 | 90.22 296 | 98.80 109 | 98.10 216 | 96.57 53 | 96.45 159 | 96.66 275 | 90.81 124 | 98.91 196 | 95.72 119 | 97.99 133 | 97.40 201 |
|
mvs-test1 | | | 96.60 109 | 96.68 97 | 96.37 233 | 97.89 176 | 91.81 272 | 98.56 158 | 98.10 216 | 96.57 53 | 96.52 145 | 97.94 164 | 90.81 124 | 99.45 136 | 95.72 119 | 98.01 132 | 97.86 188 |
|
QAPM | | | 96.29 121 | 95.40 134 | 98.96 53 | 97.85 178 | 97.60 59 | 99.23 23 | 98.93 36 | 89.76 295 | 93.11 254 | 99.02 61 | 89.11 150 | 99.93 10 | 91.99 221 | 99.62 49 | 99.34 91 |
|
3Dnovator+ | | 94.38 6 | 97.43 75 | 96.78 89 | 99.38 12 | 97.83 179 | 98.52 14 | 99.37 7 | 98.71 95 | 97.09 38 | 92.99 257 | 99.13 47 | 89.36 143 | 99.89 28 | 96.97 69 | 99.57 57 | 99.71 34 |
|
ACMH+ | | 92.99 14 | 94.30 234 | 93.77 231 | 95.88 254 | 97.81 180 | 92.04 270 | 98.71 131 | 98.37 162 | 93.99 153 | 90.60 296 | 98.47 118 | 80.86 300 | 99.05 177 | 92.75 201 | 92.40 247 | 96.55 279 |
|
3Dnovator | | 94.51 5 | 97.46 70 | 96.93 82 | 99.07 45 | 97.78 181 | 97.64 56 | 99.35 10 | 99.06 21 | 97.02 40 | 93.75 236 | 99.16 45 | 89.25 146 | 99.92 14 | 97.22 63 | 99.75 31 | 99.64 55 |
|
TR-MVS | | | 94.94 196 | 94.20 202 | 97.17 167 | 97.75 182 | 94.14 232 | 97.59 263 | 97.02 293 | 92.28 238 | 95.75 171 | 97.64 192 | 83.88 282 | 98.96 189 | 89.77 268 | 96.15 189 | 98.40 166 |
|
Fast-Effi-MVS+-dtu | | | 95.87 133 | 95.85 122 | 95.91 252 | 97.74 183 | 91.74 276 | 98.69 136 | 98.15 200 | 95.56 83 | 94.92 180 | 97.68 189 | 88.98 155 | 98.79 211 | 93.19 185 | 97.78 143 | 97.20 212 |
|
MIMVSNet | | | 93.26 267 | 92.21 272 | 96.41 231 | 97.73 184 | 93.13 258 | 95.65 330 | 97.03 292 | 91.27 268 | 94.04 226 | 96.06 297 | 75.33 328 | 97.19 313 | 86.56 311 | 96.23 186 | 98.92 141 |
|
Patchmatch-test1 | | | 95.32 176 | 94.97 158 | 96.35 235 | 97.67 185 | 91.29 281 | 97.33 281 | 97.60 243 | 94.68 129 | 96.92 121 | 96.95 253 | 83.97 280 | 98.50 239 | 91.33 238 | 98.32 123 | 99.25 105 |
|
ACMP | | 93.49 10 | 95.34 174 | 94.98 156 | 96.43 230 | 97.67 185 | 93.48 249 | 98.73 128 | 98.44 150 | 94.94 124 | 92.53 268 | 98.53 112 | 84.50 268 | 99.14 164 | 95.48 129 | 94.00 222 | 96.66 263 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
ACMH | | 92.88 16 | 94.55 223 | 93.95 220 | 96.34 237 | 97.63 187 | 93.26 254 | 98.81 106 | 98.49 145 | 93.43 185 | 89.74 301 | 98.53 112 | 81.91 292 | 99.08 175 | 93.69 172 | 93.30 238 | 96.70 254 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
tpmp4_e23 | | | 93.91 255 | 93.42 253 | 95.38 276 | 97.62 188 | 88.59 318 | 97.52 267 | 97.34 275 | 87.94 314 | 94.17 220 | 96.79 271 | 82.91 287 | 99.05 177 | 90.62 249 | 95.91 199 | 98.50 161 |
|
ACMM | | 93.85 9 | 95.69 143 | 95.38 138 | 96.61 209 | 97.61 189 | 93.84 239 | 98.91 77 | 98.44 150 | 95.25 104 | 94.28 212 | 98.47 118 | 86.04 241 | 99.12 166 | 95.50 128 | 93.95 224 | 96.87 235 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
Patchmatch-test | | | 94.42 229 | 93.68 238 | 96.63 206 | 97.60 190 | 91.76 274 | 94.83 339 | 97.49 263 | 89.45 303 | 94.14 221 | 97.10 231 | 88.99 152 | 98.83 207 | 85.37 321 | 98.13 130 | 99.29 101 |
|
PatchFormer-LS_test | | | 95.47 160 | 95.27 145 | 96.08 248 | 97.59 191 | 90.66 290 | 98.10 218 | 97.34 275 | 93.98 154 | 96.08 165 | 96.15 295 | 87.65 207 | 99.12 166 | 95.27 136 | 95.24 206 | 98.44 165 |
|
tpm cat1 | | | 93.36 262 | 92.80 262 | 95.07 285 | 97.58 192 | 87.97 324 | 96.76 309 | 97.86 233 | 82.17 341 | 93.53 240 | 96.04 298 | 86.13 230 | 99.13 165 | 89.24 280 | 95.87 200 | 98.10 179 |
|
MVS-HIRNet | | | 89.46 309 | 88.40 311 | 92.64 318 | 97.58 192 | 82.15 340 | 94.16 345 | 93.05 355 | 75.73 349 | 90.90 292 | 82.52 350 | 79.42 309 | 98.33 268 | 83.53 325 | 98.68 104 | 97.43 199 |
|
PatchmatchNet | | | 95.71 141 | 95.52 133 | 96.29 240 | 97.58 192 | 90.72 289 | 96.84 307 | 97.52 251 | 94.06 149 | 97.08 109 | 96.96 252 | 89.24 147 | 98.90 199 | 92.03 219 | 98.37 120 | 99.26 104 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
tpmrst | | | 95.63 145 | 95.69 130 | 95.44 270 | 97.54 195 | 88.54 319 | 96.97 294 | 97.56 245 | 93.50 183 | 97.52 102 | 96.93 259 | 89.49 140 | 99.16 162 | 95.25 137 | 96.42 170 | 98.64 156 |
|
FMVSNet1 | | | 93.19 270 | 92.07 273 | 96.56 217 | 97.54 195 | 95.00 171 | 98.82 100 | 98.18 192 | 90.38 281 | 92.27 275 | 97.07 235 | 73.68 336 | 97.95 291 | 89.36 279 | 91.30 260 | 96.72 250 |
|
CLD-MVS | | | 95.62 146 | 95.34 139 | 96.46 229 | 97.52 197 | 93.75 243 | 97.27 285 | 98.46 146 | 95.53 84 | 94.42 202 | 98.00 160 | 86.21 229 | 98.97 186 | 96.25 102 | 94.37 209 | 96.66 263 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
MDTV_nov1_ep13 | | | | 95.40 134 | | 97.48 198 | 88.34 321 | 96.85 306 | 97.29 280 | 93.74 167 | 97.48 103 | 97.26 216 | 89.18 148 | 99.05 177 | 91.92 224 | 97.43 150 | |
|
IB-MVS | | 91.98 17 | 93.27 266 | 91.97 274 | 97.19 165 | 97.47 199 | 93.41 252 | 97.09 292 | 95.99 324 | 93.32 195 | 92.47 271 | 95.73 304 | 78.06 316 | 99.53 128 | 94.59 151 | 82.98 327 | 98.62 157 |
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 |
tpmvs | | | 94.60 219 | 94.36 194 | 95.33 279 | 97.46 200 | 88.60 317 | 96.88 304 | 97.68 239 | 91.29 266 | 93.80 235 | 96.42 286 | 88.58 176 | 99.24 149 | 91.06 241 | 96.04 198 | 98.17 177 |
|
LPG-MVS_test | | | 95.62 146 | 95.34 139 | 96.47 226 | 97.46 200 | 93.54 247 | 98.99 67 | 98.54 129 | 94.67 130 | 94.36 204 | 98.77 92 | 85.39 249 | 99.11 170 | 95.71 121 | 94.15 217 | 96.76 245 |
|
LGP-MVS_train | | | | | 96.47 226 | 97.46 200 | 93.54 247 | | 98.54 129 | 94.67 130 | 94.36 204 | 98.77 92 | 85.39 249 | 99.11 170 | 95.71 121 | 94.15 217 | 96.76 245 |
|
jason | | | 97.32 83 | 97.08 77 | 98.06 108 | 97.45 203 | 95.59 147 | 97.87 242 | 97.91 231 | 94.79 126 | 98.55 47 | 98.83 85 | 91.12 119 | 99.23 150 | 97.58 51 | 99.60 51 | 99.34 91 |
jason: jason. |
HQP_MVS | | | 96.14 126 | 95.90 121 | 96.85 186 | 97.42 204 | 94.60 215 | 98.80 109 | 98.56 126 | 97.28 22 | 95.34 173 | 98.28 138 | 87.09 215 | 99.03 182 | 96.07 104 | 94.27 211 | 96.92 223 |
|
plane_prior7 | | | | | | 97.42 204 | 94.63 210 | | | | | | | | | | |
|
ITE_SJBPF | | | | | 95.44 270 | 97.42 204 | 91.32 280 | | 97.50 257 | 95.09 115 | 93.59 237 | 98.35 129 | 81.70 293 | 98.88 201 | 89.71 271 | 93.39 236 | 96.12 300 |
|
LTVRE_ROB | | 92.95 15 | 94.60 219 | 93.90 223 | 96.68 198 | 97.41 207 | 94.42 220 | 98.52 163 | 98.59 119 | 91.69 250 | 91.21 287 | 98.35 129 | 84.87 258 | 99.04 181 | 91.06 241 | 93.44 235 | 96.60 272 |
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 |
plane_prior1 | | | | | | 97.37 208 | | | | | | | | | | | |
|
plane_prior6 | | | | | | 97.35 209 | 94.61 213 | | | | | | 87.09 215 | | | | |
|
DWT-MVSNet_test | | | 94.82 202 | 94.36 194 | 96.20 243 | 97.35 209 | 90.79 287 | 98.34 185 | 96.57 318 | 92.91 209 | 95.33 175 | 96.44 285 | 82.00 291 | 99.12 166 | 94.52 153 | 95.78 202 | 98.70 150 |
|
dp | | | 94.15 245 | 93.90 223 | 94.90 289 | 97.31 211 | 86.82 331 | 96.97 294 | 97.19 286 | 91.22 270 | 96.02 168 | 96.61 279 | 85.51 248 | 99.02 184 | 90.00 266 | 94.30 210 | 98.85 142 |
|
NP-MVS | | | | | | 97.28 212 | 94.51 218 | | | | | 97.73 183 | | | | | |
|
CostFormer | | | 94.95 194 | 94.73 177 | 95.60 263 | 97.28 212 | 89.06 310 | 97.53 266 | 96.89 307 | 89.66 299 | 96.82 127 | 96.72 273 | 86.05 239 | 98.95 193 | 95.53 127 | 96.13 190 | 98.79 146 |
|
VPA-MVSNet | | | 95.75 138 | 95.11 150 | 97.69 131 | 97.24 214 | 97.27 69 | 98.94 75 | 99.23 12 | 95.13 111 | 95.51 172 | 97.32 213 | 85.73 244 | 98.91 196 | 97.33 62 | 89.55 275 | 96.89 231 |
|
tpm2 | | | 94.19 240 | 93.76 233 | 95.46 268 | 97.23 215 | 89.04 311 | 97.31 283 | 96.85 310 | 87.08 318 | 96.21 163 | 96.79 271 | 83.75 285 | 98.74 213 | 92.43 211 | 96.23 186 | 98.59 158 |
|
EPMVS | | | 94.99 190 | 94.48 187 | 96.52 222 | 97.22 216 | 91.75 275 | 97.23 286 | 91.66 356 | 94.11 146 | 97.28 104 | 96.81 270 | 85.70 245 | 98.84 205 | 93.04 190 | 97.28 151 | 98.97 136 |
|
FMVSNet5 | | | 91.81 290 | 90.92 284 | 94.49 301 | 97.21 217 | 92.09 268 | 98.00 227 | 97.55 249 | 89.31 306 | 90.86 293 | 95.61 309 | 74.48 333 | 95.32 338 | 85.57 318 | 89.70 271 | 96.07 302 |
|
HQP-NCC | | | | | | 97.20 218 | | 98.05 221 | | 96.43 55 | 94.45 194 | | | | | | |
|
ACMP_Plane | | | | | | 97.20 218 | | 98.05 221 | | 96.43 55 | 94.45 194 | | | | | | |
|
HQP-MVS | | | 95.72 139 | 95.40 134 | 96.69 195 | 97.20 218 | 94.25 230 | 98.05 221 | 98.46 146 | 96.43 55 | 94.45 194 | 97.73 183 | 86.75 221 | 98.96 189 | 95.30 133 | 94.18 215 | 96.86 237 |
|
OpenMVS | | 93.04 13 | 95.83 135 | 95.00 154 | 98.32 91 | 97.18 221 | 97.32 67 | 99.21 32 | 98.97 29 | 89.96 288 | 91.14 289 | 99.05 60 | 86.64 223 | 99.92 14 | 93.38 179 | 99.47 71 | 97.73 192 |
|
VPNet | | | 94.99 190 | 94.19 203 | 97.40 158 | 97.16 222 | 96.57 97 | 98.71 131 | 98.97 29 | 95.67 78 | 94.84 182 | 98.24 144 | 80.36 305 | 98.67 218 | 96.46 95 | 87.32 308 | 96.96 220 |
|
GA-MVS | | | 94.81 203 | 94.03 213 | 97.14 168 | 97.15 223 | 93.86 238 | 96.76 309 | 97.58 244 | 94.00 152 | 94.76 187 | 97.04 243 | 80.91 298 | 98.48 240 | 91.79 226 | 96.25 185 | 99.09 125 |
|
FIs | | | 96.51 114 | 96.12 115 | 97.67 133 | 97.13 224 | 97.54 61 | 99.36 8 | 99.22 14 | 95.89 71 | 94.03 227 | 98.35 129 | 91.98 103 | 98.44 250 | 96.40 98 | 92.76 244 | 97.01 217 |
|
1314 | | | 96.25 125 | 95.73 124 | 97.79 121 | 97.13 224 | 95.55 152 | 98.19 205 | 98.59 119 | 93.47 184 | 92.03 281 | 97.82 178 | 91.33 117 | 99.49 131 | 94.62 149 | 98.44 117 | 98.32 175 |
|
DeepMVS_CX | | | | | 86.78 332 | 97.09 226 | 72.30 352 | | 95.17 342 | 75.92 348 | 84.34 336 | 95.19 310 | 70.58 341 | 95.35 337 | 79.98 333 | 89.04 283 | 92.68 343 |
|
PAPM | | | 94.95 194 | 94.00 216 | 97.78 122 | 97.04 227 | 95.65 146 | 96.03 324 | 98.25 180 | 91.23 269 | 94.19 218 | 97.80 180 | 91.27 118 | 98.86 204 | 82.61 327 | 97.61 147 | 98.84 144 |
|
CR-MVSNet | | | 94.76 206 | 94.15 205 | 96.59 212 | 97.00 228 | 93.43 250 | 94.96 335 | 97.56 245 | 92.46 221 | 96.93 119 | 96.24 289 | 88.15 188 | 97.88 299 | 87.38 306 | 96.65 162 | 98.46 163 |
|
RPMNet | | | 92.52 276 | 91.17 279 | 96.59 212 | 97.00 228 | 93.43 250 | 94.96 335 | 97.26 283 | 82.27 340 | 96.93 119 | 92.12 343 | 86.98 218 | 97.88 299 | 76.32 341 | 96.65 162 | 98.46 163 |
|
UniMVSNet (Re) | | | 95.78 137 | 95.19 148 | 97.58 143 | 96.99 230 | 97.47 63 | 98.79 114 | 99.18 16 | 95.60 81 | 93.92 230 | 97.04 243 | 91.68 108 | 98.48 240 | 95.80 117 | 87.66 305 | 96.79 242 |
|
FC-MVSNet-test | | | 96.42 117 | 96.05 116 | 97.53 146 | 96.95 231 | 97.27 69 | 99.36 8 | 99.23 12 | 95.83 73 | 93.93 229 | 98.37 127 | 92.00 102 | 98.32 269 | 96.02 108 | 92.72 245 | 97.00 218 |
|
tfpnnormal | | | 93.66 258 | 92.70 265 | 96.55 220 | 96.94 232 | 95.94 125 | 98.97 71 | 99.19 15 | 91.04 272 | 91.38 286 | 97.34 211 | 84.94 257 | 98.61 221 | 85.45 320 | 89.02 284 | 95.11 318 |
|
TESTMET0.1,1 | | | 94.18 242 | 93.69 237 | 95.63 262 | 96.92 233 | 89.12 309 | 96.91 298 | 94.78 344 | 93.17 199 | 94.88 181 | 96.45 284 | 78.52 313 | 98.92 195 | 93.09 187 | 98.50 114 | 98.85 142 |
|
TinyColmap | | | 92.31 278 | 91.53 277 | 94.65 298 | 96.92 233 | 89.75 299 | 96.92 296 | 96.68 314 | 90.45 279 | 89.62 302 | 97.85 173 | 76.06 326 | 98.81 209 | 86.74 310 | 92.51 246 | 95.41 315 |
|
cascas | | | 94.63 218 | 93.86 225 | 96.93 183 | 96.91 235 | 94.27 228 | 96.00 325 | 98.51 136 | 85.55 329 | 94.54 190 | 96.23 291 | 84.20 277 | 98.87 202 | 95.80 117 | 96.98 156 | 97.66 196 |
|
nrg030 | | | 96.28 123 | 95.72 125 | 97.96 112 | 96.90 236 | 98.15 38 | 99.39 5 | 98.31 168 | 95.47 86 | 94.42 202 | 98.35 129 | 92.09 100 | 98.69 214 | 97.50 57 | 89.05 282 | 97.04 216 |
|
MVS | | | 94.67 216 | 93.54 245 | 98.08 106 | 96.88 237 | 96.56 98 | 98.19 205 | 98.50 141 | 78.05 347 | 92.69 263 | 98.02 157 | 91.07 122 | 99.63 108 | 90.09 261 | 98.36 121 | 98.04 180 |
|
WR-MVS_H | | | 95.05 188 | 94.46 189 | 96.81 188 | 96.86 238 | 95.82 142 | 99.24 21 | 99.24 10 | 93.87 160 | 92.53 268 | 96.84 269 | 90.37 131 | 98.24 277 | 93.24 183 | 87.93 300 | 96.38 291 |
|
UniMVSNet_NR-MVSNet | | | 95.71 141 | 95.15 149 | 97.40 158 | 96.84 239 | 96.97 79 | 98.74 125 | 99.24 10 | 95.16 109 | 93.88 231 | 97.72 185 | 91.68 108 | 98.31 271 | 95.81 115 | 87.25 310 | 96.92 223 |
|
USDC | | | 93.33 265 | 92.71 264 | 95.21 280 | 96.83 240 | 90.83 286 | 96.91 298 | 97.50 257 | 93.84 161 | 90.72 294 | 98.14 149 | 77.69 318 | 98.82 208 | 89.51 276 | 93.21 241 | 95.97 304 |
|
test-LLR | | | 95.10 186 | 94.87 166 | 95.80 257 | 96.77 241 | 89.70 300 | 96.91 298 | 95.21 339 | 95.11 112 | 94.83 184 | 95.72 306 | 87.71 203 | 98.97 186 | 93.06 188 | 98.50 114 | 98.72 148 |
|
test-mter | | | 94.08 249 | 93.51 248 | 95.80 257 | 96.77 241 | 89.70 300 | 96.91 298 | 95.21 339 | 92.89 210 | 94.83 184 | 95.72 306 | 77.69 318 | 98.97 186 | 93.06 188 | 98.50 114 | 98.72 148 |
|
Patchmtry | | | 93.22 268 | 92.35 270 | 95.84 255 | 96.77 241 | 93.09 259 | 94.66 341 | 97.56 245 | 87.37 317 | 92.90 258 | 96.24 289 | 88.15 188 | 97.90 295 | 87.37 307 | 90.10 268 | 96.53 281 |
|
gg-mvs-nofinetune | | | 92.21 279 | 90.58 293 | 97.13 169 | 96.75 244 | 95.09 168 | 95.85 327 | 89.40 359 | 85.43 330 | 94.50 192 | 81.98 351 | 80.80 301 | 98.40 266 | 92.16 213 | 98.33 122 | 97.88 187 |
|
XXY-MVS | | | 95.20 183 | 94.45 191 | 97.46 153 | 96.75 244 | 96.56 98 | 98.86 93 | 98.65 115 | 93.30 197 | 93.27 247 | 98.27 141 | 84.85 259 | 98.87 202 | 94.82 145 | 91.26 262 | 96.96 220 |
|
CP-MVSNet | | | 94.94 196 | 94.30 196 | 96.83 187 | 96.72 246 | 95.56 150 | 99.11 52 | 98.95 33 | 93.89 158 | 92.42 273 | 97.90 168 | 87.19 214 | 98.12 281 | 94.32 158 | 88.21 297 | 96.82 241 |
|
PatchT | | | 93.06 272 | 91.97 274 | 96.35 235 | 96.69 247 | 92.67 262 | 94.48 342 | 97.08 288 | 86.62 319 | 97.08 109 | 92.23 342 | 87.94 195 | 97.90 295 | 78.89 336 | 96.69 160 | 98.49 162 |
|
PS-CasMVS | | | 94.67 216 | 93.99 218 | 96.71 192 | 96.68 248 | 95.26 162 | 99.13 49 | 99.03 24 | 93.68 175 | 92.33 274 | 97.95 163 | 85.35 251 | 98.10 282 | 93.59 176 | 88.16 299 | 96.79 242 |
|
WR-MVS | | | 95.15 184 | 94.46 189 | 97.22 163 | 96.67 249 | 96.45 104 | 98.21 200 | 98.81 64 | 94.15 145 | 93.16 250 | 97.69 186 | 87.51 209 | 98.30 273 | 95.29 135 | 88.62 294 | 96.90 230 |
|
test_0402 | | | 91.32 294 | 90.27 296 | 94.48 302 | 96.60 250 | 91.12 283 | 98.50 168 | 97.22 285 | 86.10 324 | 88.30 311 | 96.98 250 | 77.65 320 | 97.99 290 | 78.13 338 | 92.94 243 | 94.34 333 |
|
TransMVSNet (Re) | | | 92.67 274 | 91.51 278 | 96.15 244 | 96.58 251 | 94.65 208 | 98.90 78 | 96.73 311 | 90.86 274 | 89.46 304 | 97.86 171 | 85.62 246 | 98.09 284 | 86.45 312 | 81.12 332 | 95.71 310 |
|
Anonymous20240521 | | | 94.80 204 | 94.03 213 | 97.11 171 | 96.56 252 | 96.46 103 | 99.30 14 | 98.44 150 | 92.86 212 | 91.21 287 | 97.01 247 | 89.59 139 | 98.58 226 | 92.03 219 | 89.23 280 | 96.30 295 |
|
XVG-ACMP-BASELINE | | | 94.54 224 | 94.14 206 | 95.75 260 | 96.55 253 | 91.65 277 | 98.11 216 | 98.44 150 | 94.96 121 | 94.22 216 | 97.90 168 | 79.18 311 | 99.11 170 | 94.05 166 | 93.85 225 | 96.48 287 |
|
DU-MVS | | | 95.42 165 | 94.76 175 | 97.40 158 | 96.53 254 | 96.97 79 | 98.66 145 | 98.99 28 | 95.43 88 | 93.88 231 | 97.69 186 | 88.57 177 | 98.31 271 | 95.81 115 | 87.25 310 | 96.92 223 |
|
NR-MVSNet | | | 94.98 192 | 94.16 204 | 97.44 154 | 96.53 254 | 97.22 73 | 98.74 125 | 98.95 33 | 94.96 121 | 89.25 306 | 97.69 186 | 89.32 144 | 98.18 279 | 94.59 151 | 87.40 307 | 96.92 223 |
|
tpm | | | 94.13 246 | 93.80 228 | 95.12 283 | 96.50 256 | 87.91 325 | 97.44 269 | 95.89 328 | 92.62 217 | 96.37 161 | 96.30 288 | 84.13 278 | 98.30 273 | 93.24 183 | 91.66 257 | 99.14 120 |
|
pm-mvs1 | | | 93.94 254 | 93.06 258 | 96.59 212 | 96.49 257 | 95.16 165 | 98.95 73 | 98.03 227 | 92.32 236 | 91.08 290 | 97.84 174 | 84.54 267 | 98.41 260 | 92.16 213 | 86.13 321 | 96.19 299 |
|
JIA-IIPM | | | 93.35 263 | 92.49 268 | 95.92 251 | 96.48 258 | 90.65 291 | 95.01 334 | 96.96 299 | 85.93 326 | 96.08 165 | 87.33 347 | 87.70 205 | 98.78 212 | 91.35 237 | 95.58 203 | 98.34 173 |
|
TranMVSNet+NR-MVSNet | | | 95.14 185 | 94.48 187 | 97.11 171 | 96.45 259 | 96.36 108 | 99.03 63 | 99.03 24 | 95.04 116 | 93.58 238 | 97.93 166 | 88.27 185 | 98.03 287 | 94.13 163 | 86.90 315 | 96.95 222 |
|
testgi | | | 93.06 272 | 92.45 269 | 94.88 290 | 96.43 260 | 89.90 297 | 98.75 121 | 97.54 250 | 95.60 81 | 91.63 285 | 97.91 167 | 74.46 334 | 97.02 315 | 86.10 314 | 93.67 227 | 97.72 193 |
|
v7 | | | 94.69 212 | 94.04 212 | 96.62 208 | 96.41 261 | 94.79 203 | 98.78 116 | 98.13 203 | 91.89 245 | 94.30 210 | 97.16 222 | 88.13 190 | 98.45 247 | 91.96 223 | 89.65 272 | 96.61 270 |
|
v1neww | | | 94.83 199 | 94.22 198 | 96.68 198 | 96.39 262 | 94.85 184 | 98.87 86 | 98.11 211 | 92.45 226 | 94.45 194 | 97.06 238 | 88.82 165 | 98.54 229 | 92.93 194 | 88.91 287 | 96.65 265 |
|
v7new | | | 94.83 199 | 94.22 198 | 96.68 198 | 96.39 262 | 94.85 184 | 98.87 86 | 98.11 211 | 92.45 226 | 94.45 194 | 97.06 238 | 88.82 165 | 98.54 229 | 92.93 194 | 88.91 287 | 96.65 265 |
|
v10 | | | 94.29 235 | 93.55 244 | 96.51 223 | 96.39 262 | 94.80 200 | 98.99 67 | 98.19 189 | 91.35 262 | 93.02 256 | 96.99 249 | 88.09 191 | 98.41 260 | 90.50 257 | 88.41 296 | 96.33 294 |
|
v16 | | | 92.08 282 | 90.94 282 | 95.49 266 | 96.38 265 | 94.84 193 | 98.81 106 | 97.51 254 | 89.94 290 | 85.25 328 | 93.28 324 | 88.86 160 | 96.91 318 | 88.70 290 | 79.78 335 | 94.72 325 |
|
v8 | | | 94.47 227 | 93.77 231 | 96.57 216 | 96.36 266 | 94.83 195 | 99.05 59 | 98.19 189 | 91.92 244 | 93.16 250 | 96.97 251 | 88.82 165 | 98.48 240 | 91.69 230 | 87.79 303 | 96.39 290 |
|
v6 | | | 94.83 199 | 94.21 201 | 96.69 195 | 96.36 266 | 94.85 184 | 98.87 86 | 98.11 211 | 92.46 221 | 94.44 200 | 97.05 242 | 88.76 171 | 98.57 227 | 92.95 193 | 88.92 286 | 96.65 265 |
|
LP | | | 91.12 297 | 89.99 299 | 94.53 300 | 96.35 268 | 88.70 315 | 93.86 346 | 97.35 274 | 84.88 332 | 90.98 291 | 94.77 315 | 84.40 269 | 97.43 309 | 75.41 343 | 91.89 254 | 97.47 198 |
|
GG-mvs-BLEND | | | | | 96.59 212 | 96.34 269 | 94.98 174 | 96.51 319 | 88.58 360 | | 93.10 255 | 94.34 320 | 80.34 306 | 98.05 286 | 89.53 275 | 96.99 155 | 96.74 247 |
|
v18 | | | 92.10 281 | 90.97 281 | 95.50 265 | 96.34 269 | 94.85 184 | 98.82 100 | 97.52 251 | 89.99 287 | 85.31 327 | 93.26 325 | 88.90 159 | 96.92 317 | 88.82 288 | 79.77 336 | 94.73 324 |
|
v17 | | | 92.08 282 | 90.94 282 | 95.48 267 | 96.34 269 | 94.83 195 | 98.81 106 | 97.52 251 | 89.95 289 | 85.32 325 | 93.24 326 | 88.91 158 | 96.91 318 | 88.76 289 | 79.63 337 | 94.71 326 |
|
v11 | | | 91.85 289 | 90.68 291 | 95.36 277 | 96.34 269 | 94.74 207 | 98.80 109 | 97.43 268 | 89.60 301 | 85.09 330 | 93.03 331 | 88.53 180 | 96.75 325 | 87.37 307 | 79.96 334 | 94.58 332 |
|
v13 | | | 91.88 288 | 90.69 290 | 95.43 272 | 96.33 273 | 94.78 205 | 98.75 121 | 97.50 257 | 89.68 298 | 84.93 334 | 92.98 333 | 88.84 163 | 96.83 322 | 88.14 298 | 79.09 340 | 94.69 327 |
|
V14 | | | 91.93 285 | 90.76 287 | 95.42 275 | 96.33 273 | 94.81 199 | 98.77 117 | 97.51 254 | 89.86 293 | 85.09 330 | 93.13 327 | 88.80 169 | 96.83 322 | 88.32 295 | 79.06 341 | 94.60 331 |
|
V42 | | | 94.78 205 | 94.14 206 | 96.70 194 | 96.33 273 | 95.22 164 | 98.97 71 | 98.09 219 | 92.32 236 | 94.31 208 | 97.06 238 | 88.39 183 | 98.55 228 | 92.90 197 | 88.87 289 | 96.34 293 |
|
V9 | | | 91.91 286 | 90.73 288 | 95.45 269 | 96.32 276 | 94.80 200 | 98.77 117 | 97.50 257 | 89.81 294 | 85.03 332 | 93.08 329 | 88.76 171 | 96.86 320 | 88.24 296 | 79.03 342 | 94.69 327 |
|
v15 | | | 91.94 284 | 90.77 286 | 95.43 272 | 96.31 277 | 94.83 195 | 98.77 117 | 97.50 257 | 89.92 291 | 85.13 329 | 93.08 329 | 88.76 171 | 96.86 320 | 88.40 294 | 79.10 339 | 94.61 330 |
|
v12 | | | 91.89 287 | 90.70 289 | 95.43 272 | 96.31 277 | 94.80 200 | 98.76 120 | 97.50 257 | 89.76 295 | 84.95 333 | 93.00 332 | 88.82 165 | 96.82 324 | 88.23 297 | 79.00 343 | 94.68 329 |
|
divwei89l23v2f112 | | | 94.76 206 | 94.12 209 | 96.67 201 | 96.28 279 | 94.85 184 | 98.69 136 | 98.12 206 | 92.44 228 | 94.29 211 | 96.94 255 | 88.85 162 | 98.48 240 | 92.67 202 | 88.79 293 | 96.67 260 |
|
PEN-MVS | | | 94.42 229 | 93.73 235 | 96.49 224 | 96.28 279 | 94.84 193 | 99.17 36 | 99.00 26 | 93.51 182 | 92.23 276 | 97.83 177 | 86.10 238 | 97.90 295 | 92.55 207 | 86.92 314 | 96.74 247 |
|
v1141 | | | 94.75 208 | 94.11 210 | 96.67 201 | 96.27 281 | 94.86 183 | 98.69 136 | 98.12 206 | 92.43 229 | 94.31 208 | 96.94 255 | 88.78 170 | 98.48 240 | 92.63 204 | 88.85 291 | 96.67 260 |
|
v1 | | | 94.75 208 | 94.11 210 | 96.69 195 | 96.27 281 | 94.87 182 | 98.69 136 | 98.12 206 | 92.43 229 | 94.32 207 | 96.94 255 | 88.71 174 | 98.54 229 | 92.66 203 | 88.84 292 | 96.67 260 |
|
v1144 | | | 94.59 221 | 93.92 221 | 96.60 211 | 96.21 283 | 94.78 205 | 98.59 151 | 98.14 202 | 91.86 248 | 94.21 217 | 97.02 245 | 87.97 194 | 98.41 260 | 91.72 229 | 89.57 273 | 96.61 270 |
|
Baseline_NR-MVSNet | | | 94.35 232 | 93.81 227 | 95.96 250 | 96.20 284 | 94.05 234 | 98.61 150 | 96.67 315 | 91.44 256 | 93.85 233 | 97.60 194 | 88.57 177 | 98.14 280 | 94.39 155 | 86.93 313 | 95.68 311 |
|
MS-PatchMatch | | | 93.84 256 | 93.63 239 | 94.46 304 | 96.18 285 | 89.45 304 | 97.76 251 | 98.27 175 | 92.23 239 | 92.13 279 | 97.49 200 | 79.50 308 | 98.69 214 | 89.75 270 | 99.38 81 | 95.25 316 |
|
pcd1.5k->3k | | | 39.42 338 | 41.78 339 | 32.35 350 | 96.17 286 | 0.00 369 | 0.00 360 | 98.54 129 | 0.00 364 | 0.00 366 | 0.00 366 | 87.78 202 | 0.00 366 | 0.00 363 | 93.56 231 | 97.06 214 |
|
v2v482 | | | 94.69 212 | 94.03 213 | 96.65 203 | 96.17 286 | 94.79 203 | 98.67 143 | 98.08 220 | 92.72 215 | 94.00 228 | 97.16 222 | 87.69 206 | 98.45 247 | 92.91 196 | 88.87 289 | 96.72 250 |
|
EPNet_dtu | | | 95.21 182 | 94.95 159 | 95.99 249 | 96.17 286 | 90.45 294 | 98.16 210 | 97.27 282 | 96.77 45 | 93.14 253 | 98.33 134 | 90.34 132 | 98.42 253 | 85.57 318 | 98.81 102 | 99.09 125 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
OPM-MVS | | | 95.69 143 | 95.33 141 | 96.76 190 | 96.16 289 | 94.63 210 | 98.43 176 | 98.39 159 | 96.64 51 | 95.02 179 | 98.78 90 | 85.15 254 | 99.05 177 | 95.21 139 | 94.20 214 | 96.60 272 |
|
v1192 | | | 94.32 233 | 93.58 243 | 96.53 221 | 96.10 290 | 94.45 219 | 98.50 168 | 98.17 197 | 91.54 253 | 94.19 218 | 97.06 238 | 86.95 219 | 98.43 252 | 90.14 260 | 89.57 273 | 96.70 254 |
|
v148 | | | 94.29 235 | 93.76 233 | 95.91 252 | 96.10 290 | 92.93 260 | 98.58 153 | 97.97 228 | 92.59 219 | 93.47 244 | 96.95 253 | 88.53 180 | 98.32 269 | 92.56 206 | 87.06 312 | 96.49 286 |
|
v144192 | | | 94.39 231 | 93.70 236 | 96.48 225 | 96.06 292 | 94.35 224 | 98.58 153 | 98.16 199 | 91.45 255 | 94.33 206 | 97.02 245 | 87.50 211 | 98.45 247 | 91.08 240 | 89.11 281 | 96.63 268 |
|
DTE-MVSNet | | | 93.98 253 | 93.26 256 | 96.14 245 | 96.06 292 | 94.39 222 | 99.20 33 | 98.86 54 | 93.06 202 | 91.78 282 | 97.81 179 | 85.87 242 | 97.58 306 | 90.53 250 | 86.17 319 | 96.46 289 |
|
v1240 | | | 94.06 251 | 93.29 255 | 96.34 237 | 96.03 294 | 93.90 237 | 98.44 174 | 98.17 197 | 91.18 271 | 94.13 222 | 97.01 247 | 86.05 239 | 98.42 253 | 89.13 282 | 89.50 276 | 96.70 254 |
|
v1921920 | | | 94.20 239 | 93.47 250 | 96.40 232 | 95.98 295 | 94.08 233 | 98.52 163 | 98.15 200 | 91.33 263 | 94.25 214 | 97.20 221 | 86.41 226 | 98.42 253 | 90.04 265 | 89.39 278 | 96.69 259 |
|
EU-MVSNet | | | 93.66 258 | 94.14 206 | 92.25 321 | 95.96 296 | 83.38 336 | 98.52 163 | 98.12 206 | 94.69 128 | 92.61 265 | 98.13 150 | 87.36 213 | 96.39 334 | 91.82 225 | 90.00 269 | 96.98 219 |
|
v52 | | | 94.18 242 | 93.52 246 | 96.13 246 | 95.95 297 | 94.29 226 | 99.23 23 | 98.21 184 | 91.42 257 | 92.84 259 | 96.89 262 | 87.85 200 | 98.53 235 | 91.51 234 | 87.81 301 | 95.57 314 |
|
v7n | | | 94.19 240 | 93.43 251 | 96.47 226 | 95.90 298 | 94.38 223 | 99.26 18 | 98.34 165 | 91.99 242 | 92.76 262 | 97.13 230 | 88.31 184 | 98.52 236 | 89.48 277 | 87.70 304 | 96.52 282 |
|
V4 | | | 94.18 242 | 93.52 246 | 96.13 246 | 95.89 299 | 94.31 225 | 99.23 23 | 98.22 183 | 91.42 257 | 92.82 260 | 96.89 262 | 87.93 196 | 98.52 236 | 91.51 234 | 87.81 301 | 95.58 313 |
|
gm-plane-assit | | | | | | 95.88 300 | 87.47 327 | | | 89.74 297 | | 96.94 255 | | 99.19 160 | 93.32 182 | | |
|
LF4IMVS | | | 93.14 271 | 92.79 263 | 94.20 307 | 95.88 300 | 88.67 316 | 97.66 259 | 97.07 289 | 93.81 163 | 91.71 283 | 97.65 190 | 77.96 317 | 98.81 209 | 91.47 236 | 91.92 253 | 95.12 317 |
|
PS-MVSNAJss | | | 96.43 116 | 96.26 111 | 96.92 185 | 95.84 302 | 95.08 169 | 99.16 43 | 98.50 141 | 95.87 72 | 93.84 234 | 98.34 133 | 94.51 62 | 98.61 221 | 96.88 78 | 93.45 234 | 97.06 214 |
|
testpf | | | 88.74 312 | 89.09 305 | 87.69 329 | 95.78 303 | 83.16 338 | 84.05 357 | 94.13 352 | 85.22 331 | 90.30 297 | 94.39 319 | 74.92 331 | 95.80 335 | 89.77 268 | 93.28 240 | 84.10 352 |
|
pmmvs4 | | | 94.69 212 | 93.99 218 | 96.81 188 | 95.74 304 | 95.94 125 | 97.40 272 | 97.67 240 | 90.42 280 | 93.37 245 | 97.59 195 | 89.08 151 | 98.20 278 | 92.97 192 | 91.67 256 | 96.30 295 |
|
v748 | | | 93.75 257 | 93.06 258 | 95.82 256 | 95.73 305 | 92.64 263 | 99.25 20 | 98.24 182 | 91.60 252 | 92.22 277 | 96.52 282 | 87.60 208 | 98.46 245 | 90.64 248 | 85.72 322 | 96.36 292 |
|
test_djsdf | | | 96.00 128 | 95.69 130 | 96.93 183 | 95.72 306 | 95.49 153 | 99.47 2 | 98.40 157 | 94.98 118 | 94.58 189 | 97.86 171 | 89.16 149 | 98.41 260 | 96.91 73 | 94.12 219 | 96.88 233 |
|
SixPastTwentyTwo | | | 93.34 264 | 92.86 261 | 94.75 295 | 95.67 307 | 89.41 306 | 98.75 121 | 96.67 315 | 93.89 158 | 90.15 299 | 98.25 143 | 80.87 299 | 98.27 276 | 90.90 244 | 90.64 264 | 96.57 276 |
|
K. test v3 | | | 92.55 275 | 91.91 276 | 94.48 302 | 95.64 308 | 89.24 307 | 99.07 58 | 94.88 343 | 94.04 150 | 86.78 316 | 97.59 195 | 77.64 321 | 97.64 304 | 92.08 215 | 89.43 277 | 96.57 276 |
|
OurMVSNet-221017-0 | | | 94.21 238 | 94.00 216 | 94.85 291 | 95.60 309 | 89.22 308 | 98.89 82 | 97.43 268 | 95.29 102 | 92.18 278 | 98.52 115 | 82.86 288 | 98.59 224 | 93.46 178 | 91.76 255 | 96.74 247 |
|
mvs_tets | | | 95.41 167 | 95.00 154 | 96.65 203 | 95.58 310 | 94.42 220 | 99.00 66 | 98.55 128 | 95.73 76 | 93.21 249 | 98.38 126 | 83.45 286 | 98.63 220 | 97.09 67 | 94.00 222 | 96.91 228 |
|
Gipuma | | | 78.40 324 | 76.75 325 | 83.38 338 | 95.54 311 | 80.43 342 | 79.42 358 | 97.40 271 | 64.67 352 | 73.46 348 | 80.82 353 | 45.65 356 | 93.14 347 | 66.32 351 | 87.43 306 | 76.56 357 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
test0.0.03 1 | | | 94.08 249 | 93.51 248 | 95.80 257 | 95.53 312 | 92.89 261 | 97.38 274 | 95.97 325 | 95.11 112 | 92.51 270 | 96.66 275 | 87.71 203 | 96.94 316 | 87.03 309 | 93.67 227 | 97.57 197 |
|
pmmvs5 | | | 93.65 260 | 92.97 260 | 95.68 261 | 95.49 313 | 92.37 265 | 98.20 201 | 97.28 281 | 89.66 299 | 92.58 266 | 97.26 216 | 82.14 290 | 98.09 284 | 93.18 186 | 90.95 263 | 96.58 274 |
|
N_pmnet | | | 87.12 317 | 87.77 314 | 85.17 336 | 95.46 314 | 61.92 359 | 97.37 276 | 70.66 367 | 85.83 327 | 88.73 310 | 96.04 298 | 85.33 253 | 97.76 302 | 80.02 331 | 90.48 265 | 95.84 306 |
|
our_test_3 | | | 93.65 260 | 93.30 254 | 94.69 296 | 95.45 315 | 89.68 302 | 96.91 298 | 97.65 241 | 91.97 243 | 91.66 284 | 96.88 264 | 89.67 138 | 97.93 294 | 88.02 303 | 91.49 258 | 96.48 287 |
|
ppachtmachnet_test | | | 93.22 268 | 92.63 266 | 94.97 287 | 95.45 315 | 90.84 285 | 96.88 304 | 97.88 232 | 90.60 276 | 92.08 280 | 97.26 216 | 88.08 192 | 97.86 301 | 85.12 322 | 90.33 266 | 96.22 297 |
|
jajsoiax | | | 95.45 162 | 95.03 153 | 96.73 191 | 95.42 317 | 94.63 210 | 99.14 45 | 98.52 134 | 95.74 75 | 93.22 248 | 98.36 128 | 83.87 283 | 98.65 219 | 96.95 72 | 94.04 220 | 96.91 228 |
|
DI_MVS_plusplus_test | | | 94.74 210 | 93.62 240 | 98.09 105 | 95.34 318 | 95.92 135 | 98.09 219 | 97.34 275 | 94.66 132 | 85.89 320 | 95.91 300 | 80.49 304 | 99.38 140 | 96.66 88 | 98.22 126 | 98.97 136 |
|
test_normal | | | 94.72 211 | 93.59 242 | 98.11 104 | 95.30 319 | 95.95 124 | 97.91 235 | 97.39 273 | 94.64 133 | 85.70 323 | 95.88 301 | 80.52 303 | 99.36 141 | 96.69 87 | 98.30 124 | 99.01 134 |
|
MDA-MVSNet-bldmvs | | | 89.97 306 | 88.35 312 | 94.83 293 | 95.21 320 | 91.34 279 | 97.64 260 | 97.51 254 | 88.36 312 | 71.17 351 | 96.13 296 | 79.22 310 | 96.63 331 | 83.65 324 | 86.27 318 | 96.52 282 |
|
anonymousdsp | | | 95.42 165 | 94.91 164 | 96.94 182 | 95.10 321 | 95.90 138 | 99.14 45 | 98.41 155 | 93.75 165 | 93.16 250 | 97.46 202 | 87.50 211 | 98.41 260 | 95.63 125 | 94.03 221 | 96.50 285 |
|
EPNet | | | 97.28 84 | 96.87 85 | 98.51 77 | 94.98 322 | 96.14 115 | 98.90 78 | 97.02 293 | 98.28 1 | 95.99 169 | 99.11 49 | 91.36 116 | 99.89 28 | 96.98 68 | 99.19 87 | 99.50 73 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
MVP-Stereo | | | 94.28 237 | 93.92 221 | 95.35 278 | 94.95 323 | 92.60 264 | 97.97 229 | 97.65 241 | 91.61 251 | 90.68 295 | 97.09 233 | 86.32 228 | 98.42 253 | 89.70 272 | 99.34 83 | 95.02 321 |
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
lessismore_v0 | | | | | 94.45 305 | 94.93 324 | 88.44 320 | | 91.03 357 | | 86.77 317 | 97.64 192 | 76.23 325 | 98.42 253 | 90.31 259 | 85.64 323 | 96.51 284 |
|
MDA-MVSNet_test_wron | | | 90.71 301 | 89.38 304 | 94.68 297 | 94.83 325 | 90.78 288 | 97.19 288 | 97.46 264 | 87.60 315 | 72.41 350 | 95.72 306 | 86.51 224 | 96.71 329 | 85.92 316 | 86.80 316 | 96.56 278 |
|
YYNet1 | | | 90.70 302 | 89.39 303 | 94.62 299 | 94.79 326 | 90.65 291 | 97.20 287 | 97.46 264 | 87.54 316 | 72.54 349 | 95.74 303 | 86.51 224 | 96.66 330 | 86.00 315 | 86.76 317 | 96.54 280 |
|
EG-PatchMatch MVS | | | 91.13 296 | 90.12 297 | 94.17 309 | 94.73 327 | 89.00 312 | 98.13 213 | 97.81 234 | 89.22 307 | 85.32 325 | 96.46 283 | 67.71 345 | 98.42 253 | 87.89 305 | 93.82 226 | 95.08 319 |
|
pmmvs6 | | | 91.77 291 | 90.63 292 | 95.17 282 | 94.69 328 | 91.24 282 | 98.67 143 | 97.92 230 | 86.14 323 | 89.62 302 | 97.56 199 | 75.79 327 | 98.34 267 | 90.75 246 | 84.56 326 | 95.94 305 |
|
new_pmnet | | | 90.06 305 | 89.00 308 | 93.22 317 | 94.18 329 | 88.32 322 | 96.42 320 | 96.89 307 | 86.19 322 | 85.67 324 | 93.62 322 | 77.18 323 | 97.10 314 | 81.61 329 | 89.29 279 | 94.23 334 |
|
DSMNet-mixed | | | 92.52 276 | 92.58 267 | 92.33 320 | 94.15 330 | 82.65 339 | 98.30 193 | 94.26 349 | 89.08 308 | 92.65 264 | 95.73 304 | 85.01 256 | 95.76 336 | 86.24 313 | 97.76 144 | 98.59 158 |
|
UnsupCasMVSNet_eth | | | 90.99 299 | 89.92 300 | 94.19 308 | 94.08 331 | 89.83 298 | 97.13 291 | 98.67 108 | 93.69 173 | 85.83 322 | 96.19 294 | 75.15 329 | 96.74 326 | 89.14 281 | 79.41 338 | 96.00 303 |
|
Anonymous20231206 | | | 91.66 292 | 91.10 280 | 93.33 314 | 94.02 332 | 87.35 328 | 98.58 153 | 97.26 283 | 90.48 277 | 90.16 298 | 96.31 287 | 83.83 284 | 96.53 332 | 79.36 334 | 89.90 270 | 96.12 300 |
|
test20.03 | | | 90.89 300 | 90.38 294 | 92.43 319 | 93.48 333 | 88.14 323 | 98.33 186 | 97.56 245 | 93.40 192 | 87.96 312 | 96.71 274 | 80.69 302 | 94.13 342 | 79.15 335 | 86.17 319 | 95.01 322 |
|
CMPMVS | | 66.06 21 | 89.70 307 | 89.67 302 | 89.78 325 | 93.19 334 | 76.56 345 | 97.00 293 | 98.35 164 | 80.97 343 | 81.57 340 | 97.75 182 | 74.75 332 | 98.61 221 | 89.85 267 | 93.63 229 | 94.17 335 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
OpenMVS_ROB | | 86.42 20 | 89.00 310 | 87.43 316 | 93.69 311 | 93.08 335 | 89.42 305 | 97.91 235 | 96.89 307 | 78.58 346 | 85.86 321 | 94.69 316 | 69.48 342 | 98.29 275 | 77.13 339 | 93.29 239 | 93.36 342 |
|
Test4 | | | 92.21 279 | 90.34 295 | 97.82 120 | 92.83 336 | 95.87 141 | 97.94 231 | 98.05 226 | 94.50 138 | 82.12 339 | 94.48 317 | 59.54 352 | 98.54 229 | 95.39 131 | 98.22 126 | 99.06 130 |
|
MIMVSNet1 | | | 89.67 308 | 88.28 313 | 93.82 310 | 92.81 337 | 91.08 284 | 98.01 225 | 97.45 266 | 87.95 313 | 87.90 313 | 95.87 302 | 67.63 346 | 94.56 341 | 78.73 337 | 88.18 298 | 95.83 307 |
|
UnsupCasMVSNet_bld | | | 87.17 316 | 85.12 319 | 93.31 315 | 91.94 338 | 88.77 313 | 94.92 337 | 98.30 172 | 84.30 335 | 82.30 338 | 90.04 344 | 63.96 350 | 97.25 312 | 85.85 317 | 74.47 349 | 93.93 340 |
|
testus | | | 88.91 311 | 89.08 306 | 88.40 328 | 91.39 339 | 76.05 346 | 96.56 315 | 96.48 319 | 89.38 305 | 89.39 305 | 95.17 312 | 70.94 340 | 93.56 345 | 77.04 340 | 95.41 204 | 95.61 312 |
|
Patchmatch-RL test | | | 91.49 293 | 90.85 285 | 93.41 313 | 91.37 340 | 84.40 333 | 92.81 347 | 95.93 327 | 91.87 247 | 87.25 314 | 94.87 314 | 88.99 152 | 96.53 332 | 92.54 208 | 82.00 329 | 99.30 99 |
|
pmmvs-eth3d | | | 90.36 304 | 89.05 307 | 94.32 306 | 91.10 341 | 92.12 267 | 97.63 262 | 96.95 300 | 88.86 309 | 84.91 335 | 93.13 327 | 78.32 314 | 96.74 326 | 88.70 290 | 81.81 331 | 94.09 337 |
|
PM-MVS | | | 87.77 315 | 86.55 317 | 91.40 324 | 91.03 342 | 83.36 337 | 96.92 296 | 95.18 341 | 91.28 267 | 86.48 319 | 93.42 323 | 53.27 353 | 96.74 326 | 89.43 278 | 81.97 330 | 94.11 336 |
|
new-patchmatchnet | | | 88.50 314 | 87.45 315 | 91.67 323 | 90.31 343 | 85.89 332 | 97.16 290 | 97.33 278 | 89.47 302 | 83.63 337 | 92.77 337 | 76.38 324 | 95.06 340 | 82.70 326 | 77.29 345 | 94.06 338 |
|
testing_2 | | | 90.61 303 | 88.50 310 | 96.95 181 | 90.08 344 | 95.57 149 | 97.69 256 | 98.06 223 | 93.02 204 | 76.55 345 | 92.48 340 | 61.18 351 | 98.44 250 | 95.45 130 | 91.98 251 | 96.84 238 |
|
test2356 | | | 88.68 313 | 88.61 309 | 88.87 327 | 89.90 345 | 78.23 343 | 95.11 333 | 96.66 317 | 88.66 311 | 89.06 307 | 94.33 321 | 73.14 338 | 92.56 349 | 75.56 342 | 95.11 207 | 95.81 308 |
|
pmmvs3 | | | 86.67 318 | 84.86 320 | 92.11 322 | 88.16 346 | 87.19 330 | 96.63 312 | 94.75 345 | 79.88 345 | 87.22 315 | 92.75 338 | 66.56 347 | 95.20 339 | 81.24 330 | 76.56 347 | 93.96 339 |
|
1111 | | | 84.94 320 | 84.30 321 | 86.86 331 | 87.59 347 | 75.10 348 | 96.63 312 | 96.43 320 | 82.53 338 | 80.75 342 | 92.91 335 | 68.94 343 | 93.79 343 | 68.24 349 | 84.66 325 | 91.70 344 |
|
.test1245 | | | 73.05 328 | 76.31 326 | 63.27 349 | 87.59 347 | 75.10 348 | 96.63 312 | 96.43 320 | 82.53 338 | 80.75 342 | 92.91 335 | 68.94 343 | 93.79 343 | 68.24 349 | 12.72 361 | 20.91 361 |
|
test1235678 | | | 86.26 319 | 85.81 318 | 87.62 330 | 86.97 349 | 75.00 350 | 96.55 317 | 96.32 322 | 86.08 325 | 81.32 341 | 92.98 333 | 73.10 339 | 92.05 350 | 71.64 346 | 87.32 308 | 95.81 308 |
|
ambc | | | | | 89.49 326 | 86.66 350 | 75.78 347 | 92.66 348 | 96.72 312 | | 86.55 318 | 92.50 339 | 46.01 355 | 97.90 295 | 90.32 258 | 82.09 328 | 94.80 323 |
|
TDRefinement | | | 91.06 298 | 89.68 301 | 95.21 280 | 85.35 351 | 91.49 278 | 98.51 167 | 97.07 289 | 91.47 254 | 88.83 309 | 97.84 174 | 77.31 322 | 99.09 174 | 92.79 200 | 77.98 344 | 95.04 320 |
|
test12356 | | | 83.47 321 | 83.37 322 | 83.78 337 | 84.43 352 | 70.09 355 | 95.12 332 | 95.60 336 | 82.98 336 | 78.89 344 | 92.43 341 | 64.99 348 | 91.41 352 | 70.36 347 | 85.55 324 | 89.82 346 |
|
PMMVS2 | | | 77.95 325 | 75.44 328 | 85.46 334 | 82.54 353 | 74.95 351 | 94.23 344 | 93.08 354 | 72.80 350 | 74.68 347 | 87.38 346 | 36.36 360 | 91.56 351 | 73.95 344 | 63.94 351 | 89.87 345 |
|
E-PMN | | | 64.94 333 | 64.25 333 | 67.02 347 | 82.28 354 | 59.36 363 | 91.83 350 | 85.63 363 | 52.69 357 | 60.22 356 | 77.28 356 | 41.06 358 | 80.12 360 | 46.15 358 | 41.14 355 | 61.57 359 |
|
EMVS | | | 64.07 334 | 63.26 335 | 66.53 348 | 81.73 355 | 58.81 364 | 91.85 349 | 84.75 364 | 51.93 359 | 59.09 357 | 75.13 357 | 43.32 357 | 79.09 361 | 42.03 359 | 39.47 356 | 61.69 358 |
|
no-one | | | 74.41 327 | 70.76 329 | 85.35 335 | 79.88 356 | 76.83 344 | 94.68 340 | 94.22 350 | 80.33 344 | 63.81 354 | 79.73 354 | 35.45 361 | 93.36 346 | 71.78 345 | 36.99 358 | 85.86 351 |
|
FPMVS | | | 77.62 326 | 77.14 324 | 79.05 341 | 79.25 357 | 60.97 360 | 95.79 328 | 95.94 326 | 65.96 351 | 67.93 353 | 94.40 318 | 37.73 359 | 88.88 355 | 68.83 348 | 88.46 295 | 87.29 348 |
|
PNet_i23d | | | 67.70 331 | 65.07 332 | 75.60 343 | 78.61 358 | 59.61 362 | 89.14 352 | 88.24 361 | 61.83 353 | 52.37 358 | 80.89 352 | 18.91 364 | 84.91 357 | 62.70 354 | 52.93 353 | 82.28 353 |
|
wuyk23d | | | 30.17 339 | 30.18 341 | 30.16 351 | 78.61 358 | 43.29 366 | 66.79 359 | 14.21 368 | 17.31 361 | 14.82 365 | 11.93 365 | 11.55 367 | 41.43 363 | 37.08 360 | 19.30 360 | 5.76 363 |
|
testmv | | | 78.74 322 | 77.35 323 | 82.89 339 | 78.16 360 | 69.30 356 | 95.87 326 | 94.65 346 | 81.11 342 | 70.98 352 | 87.11 348 | 46.31 354 | 90.42 353 | 65.28 352 | 76.72 346 | 88.95 347 |
|
LCM-MVSNet | | | 78.70 323 | 76.24 327 | 86.08 333 | 77.26 361 | 71.99 353 | 94.34 343 | 96.72 312 | 61.62 354 | 76.53 346 | 89.33 345 | 33.91 362 | 92.78 348 | 81.85 328 | 74.60 348 | 93.46 341 |
|
MVE | | 62.14 22 | 63.28 336 | 59.38 336 | 74.99 344 | 74.33 362 | 65.47 358 | 85.55 355 | 80.50 366 | 52.02 358 | 51.10 359 | 75.00 358 | 10.91 369 | 80.50 359 | 51.60 357 | 53.40 352 | 78.99 355 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
wuykxyi23d | | | 63.73 335 | 58.86 337 | 78.35 342 | 67.62 363 | 67.90 357 | 86.56 354 | 87.81 362 | 58.26 355 | 42.49 362 | 70.28 359 | 11.55 367 | 85.05 356 | 63.66 353 | 41.50 354 | 82.11 354 |
|
ANet_high | | | 69.08 329 | 65.37 331 | 80.22 340 | 65.99 364 | 71.96 354 | 90.91 351 | 90.09 358 | 82.62 337 | 49.93 360 | 78.39 355 | 29.36 363 | 81.75 358 | 62.49 355 | 38.52 357 | 86.95 350 |
|
PMVS | | 61.03 23 | 65.95 332 | 63.57 334 | 73.09 346 | 57.90 365 | 51.22 365 | 85.05 356 | 93.93 353 | 54.45 356 | 44.32 361 | 83.57 349 | 13.22 365 | 89.15 354 | 58.68 356 | 81.00 333 | 78.91 356 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
tmp_tt | | | 68.90 330 | 66.97 330 | 74.68 345 | 50.78 366 | 59.95 361 | 87.13 353 | 83.47 365 | 38.80 360 | 62.21 355 | 96.23 291 | 64.70 349 | 76.91 362 | 88.91 287 | 30.49 359 | 87.19 349 |
|
testmvs | | | 21.48 341 | 24.95 342 | 11.09 353 | 14.89 367 | 6.47 368 | 96.56 315 | 9.87 369 | 7.55 362 | 17.93 363 | 39.02 361 | 9.43 370 | 5.90 365 | 16.56 362 | 12.72 361 | 20.91 361 |
|
test123 | | | 20.95 342 | 23.72 343 | 12.64 352 | 13.54 368 | 8.19 367 | 96.55 317 | 6.13 370 | 7.48 363 | 16.74 364 | 37.98 362 | 12.97 366 | 6.05 364 | 16.69 361 | 5.43 363 | 23.68 360 |
|
cdsmvs_eth3d_5k | | | 23.98 340 | 31.98 340 | 0.00 354 | 0.00 369 | 0.00 369 | 0.00 360 | 98.59 119 | 0.00 364 | 0.00 366 | 98.61 105 | 90.60 129 | 0.00 366 | 0.00 363 | 0.00 364 | 0.00 364 |
|
pcd_1.5k_mvsjas | | | 7.88 344 | 10.50 345 | 0.00 354 | 0.00 369 | 0.00 369 | 0.00 360 | 0.00 371 | 0.00 364 | 0.00 366 | 0.00 366 | 94.51 62 | 0.00 366 | 0.00 363 | 0.00 364 | 0.00 364 |
|
sosnet-low-res | | | 0.00 345 | 0.00 346 | 0.00 354 | 0.00 369 | 0.00 369 | 0.00 360 | 0.00 371 | 0.00 364 | 0.00 366 | 0.00 366 | 0.00 371 | 0.00 366 | 0.00 363 | 0.00 364 | 0.00 364 |
|
sosnet | | | 0.00 345 | 0.00 346 | 0.00 354 | 0.00 369 | 0.00 369 | 0.00 360 | 0.00 371 | 0.00 364 | 0.00 366 | 0.00 366 | 0.00 371 | 0.00 366 | 0.00 363 | 0.00 364 | 0.00 364 |
|
uncertanet | | | 0.00 345 | 0.00 346 | 0.00 354 | 0.00 369 | 0.00 369 | 0.00 360 | 0.00 371 | 0.00 364 | 0.00 366 | 0.00 366 | 0.00 371 | 0.00 366 | 0.00 363 | 0.00 364 | 0.00 364 |
|
Regformer | | | 0.00 345 | 0.00 346 | 0.00 354 | 0.00 369 | 0.00 369 | 0.00 360 | 0.00 371 | 0.00 364 | 0.00 366 | 0.00 366 | 0.00 371 | 0.00 366 | 0.00 363 | 0.00 364 | 0.00 364 |
|
ab-mvs-re | | | 8.20 343 | 10.94 344 | 0.00 354 | 0.00 369 | 0.00 369 | 0.00 360 | 0.00 371 | 0.00 364 | 0.00 366 | 98.43 120 | 0.00 371 | 0.00 366 | 0.00 363 | 0.00 364 | 0.00 364 |
|
uanet | | | 0.00 345 | 0.00 346 | 0.00 354 | 0.00 369 | 0.00 369 | 0.00 360 | 0.00 371 | 0.00 364 | 0.00 366 | 0.00 366 | 0.00 371 | 0.00 366 | 0.00 363 | 0.00 364 | 0.00 364 |
|
GSMVS | | | | | | | | | | | | | | | | | 99.20 109 |
|
test_part1 | | | | | 0.00 354 | | 0.00 369 | 0.00 360 | 98.84 56 | | | | 0.00 371 | 0.00 366 | 0.00 363 | 0.00 364 | 0.00 364 |
|
sam_mvs1 | | | | | | | | | | | | | 89.45 141 | | | | 99.20 109 |
|
sam_mvs | | | | | | | | | | | | | 88.99 152 | | | | |
|
MTGPA | | | | | | | | | 98.74 83 | | | | | | | | |
|
test_post1 | | | | | | | | 96.68 311 | | | | 30.43 364 | 87.85 200 | 98.69 214 | 92.59 205 | | |
|
test_post | | | | | | | | | | | | 31.83 363 | 88.83 164 | 98.91 196 | | | |
|
patchmatchnet-post | | | | | | | | | | | | 95.10 313 | 89.42 142 | 98.89 200 | | | |
|
MTMP | | | | | | | | 98.89 82 | 94.14 351 | | | | | | | | |
|
test9_res | | | | | | | | | | | | | | | 96.39 99 | 99.57 57 | 99.69 37 |
|
agg_prior2 | | | | | | | | | | | | | | | 95.87 114 | 99.57 57 | 99.68 43 |
|
test_prior4 | | | | | | | 98.01 44 | 97.86 243 | | | | | | | | | |
|
test_prior2 | | | | | | | | 97.80 248 | | 96.12 65 | 97.89 81 | 98.69 97 | 95.96 27 | | 96.89 75 | 99.60 51 | |
|
旧先验2 | | | | | | | | 97.57 265 | | 91.30 265 | 98.67 40 | | | 99.80 61 | 95.70 123 | | |
|
新几何2 | | | | | | | | 97.64 260 | | | | | | | | | |
|
无先验 | | | | | | | | 97.58 264 | 98.72 90 | 91.38 259 | | | | 99.87 37 | 93.36 180 | | 99.60 61 |
|
原ACMM2 | | | | | | | | 97.67 258 | | | | | | | | | |
|
testdata2 | | | | | | | | | | | | | | 99.89 28 | 91.65 231 | | |
|
segment_acmp | | | | | | | | | | | | | 96.85 4 | | | | |
|
testdata1 | | | | | | | | 97.32 282 | | 96.34 59 | | | | | | | |
|
plane_prior5 | | | | | | | | | 98.56 126 | | | | | 99.03 182 | 96.07 104 | 94.27 211 | 96.92 223 |
|
plane_prior4 | | | | | | | | | | | | 98.28 138 | | | | | |
|
plane_prior3 | | | | | | | 94.61 213 | | | 97.02 40 | 95.34 173 | | | | | | |
|
plane_prior2 | | | | | | | | 98.80 109 | | 97.28 22 | | | | | | | |
|
plane_prior | | | | | | | 94.60 215 | 98.44 174 | | 96.74 47 | | | | | | 94.22 213 | |
|
n2 | | | | | | | | | 0.00 371 | | | | | | | | |
|
nn | | | | | | | | | 0.00 371 | | | | | | | | |
|
door-mid | | | | | | | | | 94.37 348 | | | | | | | | |
|
test11 | | | | | | | | | 98.66 111 | | | | | | | | |
|
door | | | | | | | | | 94.64 347 | | | | | | | | |
|
HQP5-MVS | | | | | | | 94.25 230 | | | | | | | | | | |
|
BP-MVS | | | | | | | | | | | | | | | 95.30 133 | | |
|
HQP4-MVS | | | | | | | | | | | 94.45 194 | | | 98.96 189 | | | 96.87 235 |
|
HQP3-MVS | | | | | | | | | 98.46 146 | | | | | | | 94.18 215 | |
|
HQP2-MVS | | | | | | | | | | | | | 86.75 221 | | | | |
|
MDTV_nov1_ep13_2view | | | | | | | 84.26 334 | 96.89 303 | | 90.97 273 | 97.90 80 | | 89.89 137 | | 93.91 168 | | 99.18 115 |
|
ACMMP++_ref | | | | | | | | | | | | | | | | 92.97 242 | |
|
ACMMP++ | | | | | | | | | | | | | | | | 93.61 230 | |
|
Test By Simon | | | | | | | | | | | | | 94.64 59 | | | | |
|