MPTG | | | 98.55 22 | 98.25 29 | 99.46 6 | 99.76 1 | 98.64 8 | 98.55 140 | 98.74 77 | 97.27 25 | 98.02 64 | 99.39 7 | 94.81 54 | 99.96 1 | 97.91 29 | 99.79 10 | 99.77 14 |
|
MTAPA | | | 98.58 18 | 98.29 26 | 99.46 6 | 99.76 1 | 98.64 8 | 98.90 64 | 98.74 77 | 97.27 25 | 98.02 64 | 99.39 7 | 94.81 54 | 99.96 1 | 97.91 29 | 99.79 10 | 99.77 14 |
|
HSP-MVS | | | 98.70 5 | 98.52 8 | 99.24 25 | 99.75 3 | 98.23 28 | 99.26 17 | 98.58 118 | 97.52 7 | 99.41 3 | 98.78 85 | 96.00 23 | 99.79 69 | 97.79 38 | 99.59 52 | 99.69 35 |
|
MP-MVS | | | 98.33 38 | 98.01 39 | 99.28 20 | 99.75 3 | 98.18 33 | 99.22 27 | 98.79 67 | 96.13 62 | 97.92 73 | 99.23 29 | 94.54 59 | 99.94 3 | 96.74 81 | 99.78 14 | 99.73 27 |
|
mPP-MVS | | | 98.51 26 | 98.26 28 | 99.25 24 | 99.75 3 | 98.04 39 | 99.28 16 | 98.81 59 | 96.24 58 | 98.35 52 | 99.23 29 | 95.46 38 | 99.94 3 | 97.42 55 | 99.81 8 | 99.77 14 |
|
HPM-MVS_fast | | | 98.38 32 | 98.13 35 | 99.12 40 | 99.75 3 | 97.86 46 | 99.44 4 | 98.82 56 | 94.46 132 | 98.94 21 | 99.20 35 | 95.16 48 | 99.74 85 | 97.58 47 | 99.85 2 | 99.77 14 |
|
region2R | | | 98.61 13 | 98.38 16 | 99.29 18 | 99.74 7 | 98.16 34 | 99.23 21 | 98.93 35 | 96.15 60 | 98.94 21 | 99.17 39 | 95.91 28 | 99.94 3 | 97.55 50 | 99.79 10 | 99.78 7 |
|
ACMMPR | | | 98.59 16 | 98.36 18 | 99.29 18 | 99.74 7 | 98.15 35 | 99.23 21 | 98.95 32 | 96.10 65 | 98.93 25 | 99.19 38 | 95.70 33 | 99.94 3 | 97.62 45 | 99.79 10 | 99.78 7 |
|
HPM-MVS | | | 98.36 34 | 98.10 36 | 99.13 38 | 99.74 7 | 97.82 49 | 99.53 1 | 98.80 66 | 94.63 125 | 98.61 40 | 98.97 65 | 95.13 49 | 99.77 79 | 97.65 44 | 99.83 7 | 99.79 4 |
|
ACMMP | | | 98.23 41 | 97.95 41 | 99.09 42 | 99.74 7 | 97.62 55 | 99.03 52 | 99.41 6 | 95.98 67 | 97.60 91 | 99.36 16 | 94.45 64 | 99.93 9 | 97.14 61 | 98.85 97 | 99.70 34 |
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 39 | 97.92 42 | 99.49 4 | 99.72 11 | 98.88 4 | 98.43 155 | 98.78 69 | 94.10 138 | 97.69 85 | 99.42 5 | 95.25 45 | 99.92 13 | 98.09 24 | 99.80 9 | 99.67 46 |
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
HFP-MVS | | | 98.63 12 | 98.40 14 | 99.32 16 | 99.72 11 | 98.29 25 | 99.23 21 | 98.96 30 | 96.10 65 | 98.94 21 | 99.17 39 | 96.06 20 | 99.92 13 | 97.62 45 | 99.78 14 | 99.75 20 |
|
#test# | | | 98.54 24 | 98.27 27 | 99.32 16 | 99.72 11 | 98.29 25 | 98.98 58 | 98.96 30 | 95.65 78 | 98.94 21 | 99.17 39 | 96.06 20 | 99.92 13 | 97.21 60 | 99.78 14 | 99.75 20 |
|
PGM-MVS | | | 98.49 27 | 98.23 32 | 99.27 23 | 99.72 11 | 98.08 38 | 98.99 55 | 99.49 5 | 95.43 86 | 99.03 15 | 99.32 20 | 95.56 35 | 99.94 3 | 96.80 79 | 99.77 17 | 99.78 7 |
|
XVS | | | 98.70 5 | 98.49 12 | 99.34 13 | 99.70 15 | 98.35 22 | 99.29 14 | 98.88 46 | 97.40 14 | 98.46 45 | 99.20 35 | 95.90 29 | 99.89 27 | 97.85 34 | 99.74 32 | 99.78 7 |
|
X-MVStestdata | | | 94.06 231 | 92.30 248 | 99.34 13 | 99.70 15 | 98.35 22 | 99.29 14 | 98.88 46 | 97.40 14 | 98.46 45 | 43.50 337 | 95.90 29 | 99.89 27 | 97.85 34 | 99.74 32 | 99.78 7 |
|
TSAR-MVS + MP. | | | 98.78 3 | 98.62 4 | 99.24 25 | 99.69 17 | 98.28 27 | 99.14 37 | 98.66 105 | 96.84 43 | 99.56 2 | 99.31 21 | 96.34 10 | 99.70 91 | 98.32 20 | 99.73 34 | 99.73 27 |
|
CSCG | | | 97.85 52 | 97.74 46 | 98.20 92 | 99.67 18 | 95.16 149 | 99.22 27 | 99.32 7 | 93.04 185 | 97.02 107 | 98.92 75 | 95.36 41 | 99.91 22 | 97.43 54 | 99.64 45 | 99.52 66 |
|
CP-MVS | | | 98.57 20 | 98.36 18 | 99.19 28 | 99.66 19 | 97.86 46 | 99.34 11 | 98.87 48 | 95.96 68 | 98.60 41 | 99.13 44 | 96.05 22 | 99.94 3 | 97.77 39 | 99.86 1 | 99.77 14 |
|
CPTT-MVS | | | 97.72 56 | 97.32 63 | 98.92 53 | 99.64 20 | 97.10 73 | 99.12 42 | 98.81 59 | 92.34 215 | 98.09 58 | 99.08 54 | 93.01 80 | 99.92 13 | 96.06 99 | 99.77 17 | 99.75 20 |
|
ACMMP_Plus | | | 98.61 13 | 98.30 25 | 99.55 1 | 99.62 21 | 98.95 3 | 98.82 81 | 98.81 59 | 95.80 72 | 99.16 12 | 99.47 4 | 95.37 40 | 99.92 13 | 97.89 32 | 99.75 29 | 99.79 4 |
|
MCST-MVS | | | 98.65 9 | 98.37 17 | 99.48 5 | 99.60 22 | 98.87 5 | 98.41 157 | 98.68 95 | 97.04 38 | 98.52 44 | 98.80 84 | 96.78 4 | 99.83 43 | 97.93 28 | 99.61 48 | 99.74 25 |
|
APDe-MVS | | | 99.02 1 | 98.84 1 | 99.55 1 | 99.57 23 | 98.96 2 | 99.39 5 | 98.93 35 | 97.38 17 | 99.41 3 | 99.54 1 | 96.66 5 | 99.84 42 | 98.86 2 | 99.85 2 | 99.87 1 |
|
abl_6 | | | 98.30 40 | 98.03 38 | 99.13 38 | 99.56 24 | 97.76 51 | 99.13 40 | 98.82 56 | 96.14 61 | 99.26 6 | 99.37 12 | 93.33 76 | 99.93 9 | 96.96 67 | 99.67 39 | 99.69 35 |
|
DP-MVS Recon | | | 97.86 51 | 97.46 58 | 99.06 45 | 99.53 25 | 98.35 22 | 98.33 164 | 98.89 43 | 92.62 198 | 98.05 60 | 98.94 72 | 95.34 42 | 99.65 98 | 96.04 100 | 99.42 75 | 99.19 104 |
|
APD-MVS | | | 98.35 35 | 98.00 40 | 99.42 9 | 99.51 26 | 98.72 7 | 98.80 90 | 98.82 56 | 94.52 128 | 99.23 8 | 99.25 28 | 95.54 37 | 99.80 57 | 96.52 89 | 99.77 17 | 99.74 25 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
HPM-MVS++ | | | 98.58 18 | 98.25 29 | 99.55 1 | 99.50 27 | 99.08 1 | 98.72 111 | 98.66 105 | 97.51 8 | 98.15 55 | 98.83 81 | 95.70 33 | 99.92 13 | 97.53 52 | 99.67 39 | 99.66 48 |
|
APD-MVS_3200maxsize | | | 98.53 25 | 98.33 24 | 99.15 37 | 99.50 27 | 97.92 45 | 99.15 36 | 98.81 59 | 96.24 58 | 99.20 10 | 99.37 12 | 95.30 43 | 99.80 57 | 97.73 41 | 99.67 39 | 99.72 30 |
|
114514_t | | | 96.93 93 | 96.27 104 | 98.92 53 | 99.50 27 | 97.63 54 | 98.85 75 | 98.90 41 | 84.80 309 | 97.77 78 | 99.11 46 | 92.84 81 | 99.66 97 | 94.85 135 | 99.77 17 | 99.47 77 |
|
PAPM_NR | | | 97.46 67 | 97.11 71 | 98.50 75 | 99.50 27 | 96.41 99 | 98.63 127 | 98.60 112 | 95.18 102 | 97.06 105 | 98.06 147 | 94.26 68 | 99.57 113 | 93.80 163 | 98.87 96 | 99.52 66 |
|
CDPH-MVS | | | 97.94 47 | 97.49 56 | 99.28 20 | 99.47 31 | 98.44 14 | 97.91 214 | 98.67 102 | 92.57 201 | 98.77 32 | 98.85 79 | 95.93 27 | 99.72 86 | 95.56 118 | 99.69 38 | 99.68 41 |
|
EI-MVSNet-Vis-set | | | 98.47 28 | 98.39 15 | 98.69 62 | 99.46 32 | 96.49 96 | 98.30 171 | 98.69 92 | 97.21 28 | 98.84 27 | 99.36 16 | 95.41 39 | 99.78 74 | 98.62 6 | 99.65 43 | 99.80 3 |
|
EI-MVSNet-UG-set | | | 98.41 30 | 98.34 21 | 98.61 67 | 99.45 33 | 96.32 103 | 98.28 173 | 98.68 95 | 97.17 31 | 98.74 34 | 99.37 12 | 95.25 45 | 99.79 69 | 98.57 8 | 99.54 64 | 99.73 27 |
|
F-COLMAP | | | 97.09 89 | 96.80 82 | 97.97 107 | 99.45 33 | 94.95 161 | 98.55 140 | 98.62 111 | 93.02 186 | 96.17 144 | 98.58 105 | 94.01 71 | 99.81 50 | 93.95 158 | 98.90 93 | 99.14 112 |
|
Regformer-3 | | | 98.59 16 | 98.50 11 | 98.86 57 | 99.43 35 | 97.05 74 | 98.40 158 | 98.68 95 | 97.43 13 | 99.06 14 | 99.31 21 | 95.80 32 | 99.77 79 | 98.62 6 | 99.76 23 | 99.78 7 |
|
Regformer-4 | | | 98.64 10 | 98.53 7 | 98.99 47 | 99.43 35 | 97.37 63 | 98.40 158 | 98.79 67 | 97.46 12 | 99.09 13 | 99.31 21 | 95.86 31 | 99.80 57 | 98.64 4 | 99.76 23 | 99.79 4 |
|
Regformer-1 | | | 98.66 8 | 98.51 10 | 99.12 40 | 99.35 37 | 97.81 50 | 98.37 160 | 98.76 73 | 97.49 10 | 99.20 10 | 99.21 32 | 96.08 19 | 99.79 69 | 98.42 16 | 99.73 34 | 99.75 20 |
|
Regformer-2 | | | 98.69 7 | 98.52 8 | 99.19 28 | 99.35 37 | 98.01 41 | 98.37 160 | 98.81 59 | 97.48 11 | 99.21 9 | 99.21 32 | 96.13 16 | 99.80 57 | 98.40 18 | 99.73 34 | 99.75 20 |
|
新几何1 | | | | | 99.16 35 | 99.34 39 | 98.01 41 | | 98.69 92 | 90.06 264 | 98.13 56 | 98.95 71 | 94.60 58 | 99.89 27 | 91.97 213 | 99.47 69 | 99.59 61 |
|
1121 | | | 97.37 77 | 96.77 87 | 99.16 35 | 99.34 39 | 97.99 44 | 98.19 183 | 98.68 95 | 90.14 262 | 98.01 66 | 98.97 65 | 94.80 56 | 99.87 35 | 93.36 172 | 99.46 72 | 99.61 56 |
|
DP-MVS | | | 96.59 105 | 95.93 114 | 98.57 69 | 99.34 39 | 96.19 107 | 98.70 115 | 98.39 152 | 89.45 281 | 94.52 171 | 99.35 18 | 91.85 101 | 99.85 40 | 92.89 191 | 98.88 94 | 99.68 41 |
|
SD-MVS | | | 98.64 10 | 98.68 3 | 98.53 73 | 99.33 42 | 98.36 21 | 98.90 64 | 98.85 52 | 97.28 21 | 99.72 1 | 99.39 7 | 96.63 7 | 97.60 282 | 98.17 23 | 99.85 2 | 99.64 53 |
|
HyFIR lowres test | | | 96.90 95 | 96.49 98 | 98.14 95 | 99.33 42 | 95.56 135 | 97.38 253 | 99.65 2 | 92.34 215 | 97.61 90 | 98.20 139 | 89.29 138 | 99.10 155 | 96.97 65 | 97.60 144 | 99.77 14 |
|
OMC-MVS | | | 97.55 66 | 97.34 62 | 98.20 92 | 99.33 42 | 95.92 122 | 98.28 173 | 98.59 113 | 95.52 83 | 97.97 69 | 99.10 48 | 93.28 78 | 99.49 123 | 95.09 132 | 98.88 94 | 99.19 104 |
|
原ACMM1 | | | | | 98.65 65 | 99.32 45 | 96.62 89 | | 98.67 102 | 93.27 180 | 97.81 77 | 98.97 65 | 95.18 47 | 99.83 43 | 93.84 161 | 99.46 72 | 99.50 71 |
|
CNVR-MVS | | | 98.78 3 | 98.56 6 | 99.45 8 | 99.32 45 | 98.87 5 | 98.47 151 | 98.81 59 | 97.72 4 | 98.76 33 | 99.16 42 | 97.05 2 | 99.78 74 | 98.06 25 | 99.66 42 | 99.69 35 |
|
TEST9 | | | | | | 99.31 47 | 98.50 12 | 97.92 211 | 98.73 82 | 92.63 197 | 97.74 81 | 98.68 94 | 96.20 12 | 99.80 57 | | | |
|
train_agg | | | 97.97 44 | 97.52 54 | 99.33 15 | 99.31 47 | 98.50 12 | 97.92 211 | 98.73 82 | 92.98 188 | 97.74 81 | 98.68 94 | 96.20 12 | 99.80 57 | 96.59 85 | 99.57 55 | 99.68 41 |
|
test_prior3 | | | 98.22 42 | 97.90 43 | 99.19 28 | 99.31 47 | 98.22 30 | 97.80 227 | 98.84 53 | 96.12 63 | 97.89 75 | 98.69 92 | 95.96 25 | 99.70 91 | 96.89 71 | 99.60 49 | 99.65 50 |
|
test_prior | | | | | 99.19 28 | 99.31 47 | 98.22 30 | | 98.84 53 | | | | | 99.70 91 | | | 99.65 50 |
|
PatchMatch-RL | | | 96.59 105 | 96.03 112 | 98.27 88 | 99.31 47 | 96.51 95 | 97.91 214 | 99.06 20 | 93.72 158 | 96.92 112 | 98.06 147 | 88.50 175 | 99.65 98 | 91.77 218 | 99.00 90 | 98.66 145 |
|
agg_prior1 | | | 97.95 46 | 97.51 55 | 99.28 20 | 99.30 52 | 98.38 17 | 97.81 226 | 98.72 84 | 93.16 182 | 97.57 93 | 98.66 97 | 96.14 15 | 99.81 50 | 96.63 84 | 99.56 61 | 99.66 48 |
|
agg_prior | | | | | | 99.30 52 | 98.38 17 | | 98.72 84 | | 97.57 93 | | | 99.81 50 | | | |
|
CHOSEN 1792x2688 | | | 97.12 87 | 96.80 82 | 98.08 101 | 99.30 52 | 94.56 198 | 98.05 199 | 99.71 1 | 93.57 169 | 97.09 101 | 98.91 76 | 88.17 180 | 99.89 27 | 96.87 77 | 99.56 61 | 99.81 2 |
|
test_8 | | | | | | 99.29 55 | 98.44 14 | 97.89 219 | 98.72 84 | 92.98 188 | 97.70 84 | 98.66 97 | 96.20 12 | 99.80 57 | | | |
|
agg_prior3 | | | 97.87 50 | 97.42 60 | 99.23 27 | 99.29 55 | 98.23 28 | 97.92 211 | 98.72 84 | 92.38 214 | 97.59 92 | 98.64 99 | 96.09 18 | 99.79 69 | 96.59 85 | 99.57 55 | 99.68 41 |
|
旧先验1 | | | | | | 99.29 55 | 97.48 59 | | 98.70 91 | | | 99.09 52 | 95.56 35 | | | 99.47 69 | 99.61 56 |
|
PLC | | 95.07 4 | 97.20 83 | 96.78 85 | 98.44 80 | 99.29 55 | 96.31 105 | 98.14 189 | 98.76 73 | 92.41 212 | 96.39 140 | 98.31 130 | 94.92 53 | 99.78 74 | 94.06 156 | 98.77 101 | 99.23 102 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
COLMAP_ROB | | 93.27 12 | 95.33 159 | 94.87 159 | 96.71 173 | 99.29 55 | 93.24 233 | 98.58 133 | 98.11 201 | 89.92 269 | 93.57 219 | 99.10 48 | 86.37 219 | 99.79 69 | 90.78 234 | 98.10 128 | 97.09 194 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
NCCC | | | 98.61 13 | 98.35 20 | 99.38 10 | 99.28 60 | 98.61 10 | 98.45 152 | 98.76 73 | 97.82 3 | 98.45 48 | 98.93 73 | 96.65 6 | 99.83 43 | 97.38 57 | 99.41 76 | 99.71 32 |
|
PVSNet_Blended_VisFu | | | 97.70 57 | 97.46 58 | 98.44 80 | 99.27 61 | 95.91 124 | 98.63 127 | 99.16 16 | 94.48 131 | 97.67 86 | 98.88 77 | 92.80 82 | 99.91 22 | 97.11 62 | 99.12 87 | 99.50 71 |
|
MVS_111021_LR | | | 98.34 36 | 98.23 32 | 98.67 64 | 99.27 61 | 96.90 80 | 97.95 209 | 99.58 3 | 97.14 33 | 98.44 49 | 99.01 62 | 95.03 51 | 99.62 105 | 97.91 29 | 99.75 29 | 99.50 71 |
|
MSLP-MVS++ | | | 98.56 21 | 98.57 5 | 98.55 71 | 99.26 63 | 96.80 83 | 98.71 112 | 99.05 22 | 97.28 21 | 98.84 27 | 99.28 25 | 96.47 9 | 99.40 129 | 98.52 14 | 99.70 37 | 99.47 77 |
|
AllTest | | | 95.24 163 | 94.65 164 | 96.99 158 | 99.25 64 | 93.21 234 | 98.59 131 | 98.18 183 | 91.36 240 | 93.52 221 | 98.77 87 | 84.67 243 | 99.72 86 | 89.70 255 | 97.87 134 | 98.02 172 |
|
TestCases | | | | | 96.99 158 | 99.25 64 | 93.21 234 | | 98.18 183 | 91.36 240 | 93.52 221 | 98.77 87 | 84.67 243 | 99.72 86 | 89.70 255 | 97.87 134 | 98.02 172 |
|
PVSNet_BlendedMVS | | | 96.73 100 | 96.60 93 | 97.12 152 | 99.25 64 | 95.35 144 | 98.26 175 | 99.26 8 | 94.28 134 | 97.94 71 | 97.46 193 | 92.74 83 | 99.81 50 | 96.88 74 | 93.32 219 | 96.20 274 |
|
PVSNet_Blended | | | 97.38 76 | 97.12 70 | 98.14 95 | 99.25 64 | 95.35 144 | 97.28 263 | 99.26 8 | 93.13 183 | 97.94 71 | 98.21 138 | 92.74 83 | 99.81 50 | 96.88 74 | 99.40 78 | 99.27 98 |
|
DeepC-MVS | | 95.98 3 | 97.88 49 | 97.58 50 | 98.77 59 | 99.25 64 | 96.93 78 | 98.83 79 | 98.75 76 | 96.96 41 | 96.89 114 | 99.50 3 | 90.46 124 | 99.87 35 | 97.84 36 | 99.76 23 | 99.52 66 |
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 22 | 98.34 21 | 99.18 32 | 99.25 64 | 98.04 39 | 98.50 148 | 98.78 69 | 97.72 4 | 98.92 26 | 99.28 25 | 95.27 44 | 99.82 48 | 97.55 50 | 99.77 17 | 99.69 35 |
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 70 | 97.17 72 | 97.40 251 | 98.66 105 | 88.68 288 | 98.05 60 | 98.96 69 | 94.14 69 | | | 99.53 65 | 99.61 56 |
|
TSAR-MVS + GP. | | | 98.38 32 | 98.24 31 | 98.81 58 | 99.22 71 | 97.25 69 | 98.11 194 | 98.29 165 | 97.19 30 | 98.99 20 | 99.02 58 | 96.22 11 | 99.67 96 | 98.52 14 | 98.56 110 | 99.51 69 |
|
SteuartSystems-ACMMP | | | 98.90 2 | 98.75 2 | 99.36 12 | 99.22 71 | 98.43 16 | 99.10 44 | 98.87 48 | 97.38 17 | 99.35 5 | 99.40 6 | 97.78 1 | 99.87 35 | 97.77 39 | 99.85 2 | 99.78 7 |
Skip Steuart: Steuart Systems R&D Blog. |
MVS_111021_HR | | | 98.47 28 | 98.34 21 | 98.88 56 | 99.22 71 | 97.32 64 | 97.91 214 | 99.58 3 | 97.20 29 | 98.33 53 | 99.00 63 | 95.99 24 | 99.64 100 | 98.05 26 | 99.76 23 | 99.69 35 |
|
testdata | | | | | 98.26 89 | 99.20 74 | 95.36 142 | | 98.68 95 | 91.89 225 | 98.60 41 | 99.10 48 | 94.44 65 | 99.82 48 | 94.27 151 | 99.44 74 | 99.58 63 |
|
PVSNet | | 91.96 18 | 96.35 113 | 96.15 108 | 96.96 161 | 99.17 75 | 92.05 247 | 96.08 298 | 98.68 95 | 93.69 162 | 97.75 80 | 97.80 171 | 88.86 153 | 99.69 94 | 94.26 152 | 99.01 89 | 99.15 110 |
|
test12 | | | | | 99.18 32 | 99.16 76 | 98.19 32 | | 98.53 126 | | 98.07 59 | | 95.13 49 | 99.72 86 | | 99.56 61 | 99.63 55 |
|
AdaColmap | | | 97.15 86 | 96.70 88 | 98.48 77 | 99.16 76 | 96.69 88 | 98.01 203 | 98.89 43 | 94.44 133 | 96.83 116 | 98.68 94 | 90.69 122 | 99.76 81 | 94.36 147 | 99.29 83 | 98.98 125 |
|
PHI-MVS | | | 98.34 36 | 98.06 37 | 99.18 32 | 99.15 78 | 98.12 37 | 99.04 51 | 99.09 18 | 93.32 177 | 98.83 29 | 99.10 48 | 96.54 8 | 99.83 43 | 97.70 43 | 99.76 23 | 99.59 61 |
|
TAPA-MVS | | 93.98 7 | 95.35 157 | 94.56 168 | 97.74 118 | 99.13 79 | 94.83 176 | 98.33 164 | 98.64 110 | 86.62 297 | 96.29 142 | 98.61 100 | 94.00 72 | 99.29 135 | 80.00 309 | 99.41 76 | 99.09 115 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
MG-MVS | | | 97.81 53 | 97.60 49 | 98.44 80 | 99.12 80 | 95.97 115 | 97.75 231 | 98.78 69 | 96.89 42 | 98.46 45 | 99.22 31 | 93.90 73 | 99.68 95 | 94.81 137 | 99.52 66 | 99.67 46 |
|
view600 | | | 95.60 142 | 94.93 154 | 97.62 128 | 99.05 81 | 94.85 165 | 99.09 45 | 97.01 283 | 95.36 90 | 96.52 132 | 97.37 197 | 84.55 246 | 99.59 107 | 89.07 266 | 96.39 166 | 98.40 157 |
|
view800 | | | 95.60 142 | 94.93 154 | 97.62 128 | 99.05 81 | 94.85 165 | 99.09 45 | 97.01 283 | 95.36 90 | 96.52 132 | 97.37 197 | 84.55 246 | 99.59 107 | 89.07 266 | 96.39 166 | 98.40 157 |
|
conf0.05thres1000 | | | 95.60 142 | 94.93 154 | 97.62 128 | 99.05 81 | 94.85 165 | 99.09 45 | 97.01 283 | 95.36 90 | 96.52 132 | 97.37 197 | 84.55 246 | 99.59 107 | 89.07 266 | 96.39 166 | 98.40 157 |
|
tfpn | | | 95.60 142 | 94.93 154 | 97.62 128 | 99.05 81 | 94.85 165 | 99.09 45 | 97.01 283 | 95.36 90 | 96.52 132 | 97.37 197 | 84.55 246 | 99.59 107 | 89.07 266 | 96.39 166 | 98.40 157 |
|
CNLPA | | | 97.45 70 | 97.03 75 | 98.73 60 | 99.05 81 | 97.44 62 | 98.07 198 | 98.53 126 | 95.32 96 | 96.80 120 | 98.53 107 | 93.32 77 | 99.72 86 | 94.31 150 | 99.31 82 | 99.02 121 |
|
DELS-MVS | | | 98.40 31 | 98.20 34 | 98.99 47 | 99.00 86 | 97.66 52 | 97.75 231 | 98.89 43 | 97.71 6 | 98.33 53 | 98.97 65 | 94.97 52 | 99.88 34 | 98.42 16 | 99.76 23 | 99.42 85 |
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 48 | 98.48 13 | 96.30 218 | 99.00 86 | 89.54 279 | 97.43 250 | 98.87 48 | 98.16 2 | 99.26 6 | 99.38 11 | 96.12 17 | 99.64 100 | 98.30 21 | 99.77 17 | 99.72 30 |
|
thres600view7 | | | 95.49 146 | 94.77 161 | 97.67 125 | 98.98 88 | 95.02 154 | 98.85 75 | 96.90 291 | 95.38 89 | 96.63 124 | 96.90 241 | 84.29 253 | 99.59 107 | 88.65 275 | 96.33 171 | 98.40 157 |
|
tfpn200view9 | | | 95.32 160 | 94.62 165 | 97.43 139 | 98.94 89 | 94.98 158 | 98.68 120 | 96.93 289 | 95.33 94 | 96.55 128 | 96.53 256 | 84.23 255 | 99.56 115 | 88.11 281 | 96.29 173 | 97.76 176 |
|
thres400 | | | 95.38 154 | 94.62 165 | 97.65 127 | 98.94 89 | 94.98 158 | 98.68 120 | 96.93 289 | 95.33 94 | 96.55 128 | 96.53 256 | 84.23 255 | 99.56 115 | 88.11 281 | 96.29 173 | 98.40 157 |
|
MVS_0304 | | | 97.70 57 | 97.25 65 | 99.07 43 | 98.90 91 | 97.83 48 | 98.20 179 | 98.74 77 | 97.51 8 | 98.03 63 | 99.06 56 | 86.12 223 | 99.93 9 | 99.02 1 | 99.64 45 | 99.44 84 |
|
MSDG | | | 95.93 126 | 95.30 139 | 97.83 113 | 98.90 91 | 95.36 142 | 96.83 285 | 98.37 155 | 91.32 244 | 94.43 181 | 98.73 91 | 90.27 128 | 99.60 106 | 90.05 247 | 98.82 99 | 98.52 151 |
|
RPSCF | | | 94.87 180 | 95.40 129 | 93.26 293 | 98.89 93 | 82.06 317 | 98.33 164 | 98.06 213 | 90.30 259 | 96.56 126 | 99.26 27 | 87.09 207 | 99.49 123 | 93.82 162 | 96.32 172 | 98.24 167 |
|
VNet | | | 97.79 54 | 97.40 61 | 98.96 51 | 98.88 94 | 97.55 57 | 98.63 127 | 98.93 35 | 96.74 46 | 99.02 16 | 98.84 80 | 90.33 127 | 99.83 43 | 98.53 10 | 96.66 156 | 99.50 71 |
|
LFMVS | | | 95.86 129 | 94.98 150 | 98.47 78 | 98.87 95 | 96.32 103 | 98.84 78 | 96.02 308 | 93.40 174 | 98.62 39 | 99.20 35 | 74.99 307 | 99.63 103 | 97.72 42 | 97.20 148 | 99.46 81 |
|
UA-Net | | | 97.96 45 | 97.62 48 | 98.98 49 | 98.86 96 | 97.47 60 | 98.89 68 | 99.08 19 | 96.67 49 | 98.72 35 | 99.54 1 | 93.15 79 | 99.81 50 | 94.87 134 | 98.83 98 | 99.65 50 |
|
WTY-MVS | | | 97.37 77 | 96.92 79 | 98.72 61 | 98.86 96 | 96.89 82 | 98.31 169 | 98.71 89 | 95.26 98 | 97.67 86 | 98.56 106 | 92.21 92 | 99.78 74 | 95.89 104 | 96.85 153 | 99.48 76 |
|
IS-MVSNet | | | 97.22 82 | 96.88 80 | 98.25 90 | 98.85 98 | 96.36 101 | 99.19 33 | 97.97 218 | 95.39 88 | 97.23 98 | 98.99 64 | 91.11 115 | 98.93 176 | 94.60 141 | 98.59 108 | 99.47 77 |
|
VDD-MVS | | | 95.82 131 | 95.23 141 | 97.61 133 | 98.84 99 | 93.98 214 | 98.68 120 | 97.40 259 | 95.02 110 | 97.95 70 | 99.34 19 | 74.37 312 | 99.78 74 | 98.64 4 | 96.80 154 | 99.08 118 |
|
CHOSEN 280x420 | | | 97.18 84 | 97.18 69 | 97.20 146 | 98.81 100 | 93.27 231 | 95.78 306 | 99.15 17 | 95.25 99 | 96.79 121 | 98.11 144 | 92.29 88 | 99.07 158 | 98.56 9 | 99.85 2 | 99.25 100 |
|
thres200 | | | 95.25 162 | 94.57 167 | 97.28 144 | 98.81 100 | 94.92 162 | 98.20 179 | 97.11 275 | 95.24 101 | 96.54 130 | 96.22 269 | 84.58 245 | 99.53 120 | 87.93 283 | 96.50 163 | 97.39 187 |
|
XVG-OURS-SEG-HR | | | 96.51 108 | 96.34 101 | 97.02 157 | 98.77 102 | 93.76 220 | 97.79 229 | 98.50 135 | 95.45 85 | 96.94 109 | 99.09 52 | 87.87 191 | 99.55 119 | 96.76 80 | 95.83 185 | 97.74 177 |
|
XVG-OURS | | | 96.55 107 | 96.41 99 | 96.99 158 | 98.75 103 | 93.76 220 | 97.50 247 | 98.52 128 | 95.67 76 | 96.83 116 | 99.30 24 | 88.95 150 | 99.53 120 | 95.88 105 | 96.26 176 | 97.69 180 |
|
CANet | | | 98.05 43 | 97.76 45 | 98.90 55 | 98.73 104 | 97.27 66 | 98.35 162 | 98.78 69 | 97.37 19 | 97.72 83 | 98.96 69 | 91.53 110 | 99.92 13 | 98.79 3 | 99.65 43 | 99.51 69 |
|
Vis-MVSNet (Re-imp) | | | 96.87 96 | 96.55 95 | 97.83 113 | 98.73 104 | 95.46 139 | 99.20 31 | 98.30 163 | 94.96 113 | 96.60 125 | 98.87 78 | 90.05 131 | 98.59 204 | 93.67 166 | 98.60 107 | 99.46 81 |
|
PAPR | | | 96.84 97 | 96.24 106 | 98.65 65 | 98.72 106 | 96.92 79 | 97.36 257 | 98.57 119 | 93.33 176 | 96.67 123 | 97.57 189 | 94.30 67 | 99.56 115 | 91.05 232 | 98.59 108 | 99.47 77 |
|
canonicalmvs | | | 97.67 59 | 97.23 67 | 98.98 49 | 98.70 107 | 98.38 17 | 99.34 11 | 98.39 152 | 96.76 45 | 97.67 86 | 97.40 196 | 92.26 89 | 99.49 123 | 98.28 22 | 96.28 175 | 99.08 118 |
|
API-MVS | | | 97.41 74 | 97.25 65 | 97.91 109 | 98.70 107 | 96.80 83 | 98.82 81 | 98.69 92 | 94.53 127 | 98.11 57 | 98.28 131 | 94.50 63 | 99.57 113 | 94.12 155 | 99.49 67 | 97.37 189 |
|
MAR-MVS | | | 96.91 94 | 96.40 100 | 98.45 79 | 98.69 109 | 96.90 80 | 98.66 125 | 98.68 95 | 92.40 213 | 97.07 104 | 97.96 154 | 91.54 109 | 99.75 83 | 93.68 165 | 98.92 92 | 98.69 142 |
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 55 | 97.77 44 | 97.62 128 | 98.68 110 | 95.58 133 | 97.34 259 | 98.51 130 | 97.29 20 | 98.66 37 | 97.88 161 | 94.51 60 | 99.90 25 | 97.87 33 | 99.17 86 | 97.39 187 |
|
alignmvs | | | 97.56 65 | 97.07 74 | 99.01 46 | 98.66 111 | 98.37 20 | 98.83 79 | 98.06 213 | 96.74 46 | 98.00 68 | 97.65 182 | 90.80 121 | 99.48 127 | 98.37 19 | 96.56 160 | 99.19 104 |
|
Vis-MVSNet | | | 97.42 73 | 97.11 71 | 98.34 86 | 98.66 111 | 96.23 106 | 99.22 27 | 99.00 25 | 96.63 51 | 98.04 62 | 99.21 32 | 88.05 185 | 99.35 133 | 96.01 102 | 99.21 84 | 99.45 83 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
EPP-MVSNet | | | 97.46 67 | 97.28 64 | 97.99 106 | 98.64 113 | 95.38 141 | 99.33 13 | 98.31 160 | 93.61 168 | 97.19 99 | 99.07 55 | 94.05 70 | 99.23 139 | 96.89 71 | 98.43 117 | 99.37 87 |
|
ab-mvs | | | 96.42 111 | 95.71 123 | 98.55 71 | 98.63 114 | 96.75 86 | 97.88 220 | 98.74 77 | 93.84 151 | 96.54 130 | 98.18 140 | 85.34 236 | 99.75 83 | 95.93 103 | 96.35 170 | 99.15 110 |
|
PCF-MVS | | 93.45 11 | 94.68 196 | 93.43 232 | 98.42 83 | 98.62 115 | 96.77 85 | 95.48 308 | 98.20 179 | 84.63 310 | 93.34 226 | 98.32 129 | 88.55 172 | 99.81 50 | 84.80 300 | 98.96 91 | 98.68 143 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
xiu_mvs_v2_base | | | 97.66 60 | 97.70 47 | 97.56 135 | 98.61 116 | 95.46 139 | 97.44 248 | 98.46 140 | 97.15 32 | 98.65 38 | 98.15 141 | 94.33 66 | 99.80 57 | 97.84 36 | 98.66 106 | 97.41 185 |
|
sss | | | 97.39 75 | 96.98 77 | 98.61 67 | 98.60 117 | 96.61 91 | 98.22 177 | 98.93 35 | 93.97 145 | 98.01 66 | 98.48 112 | 91.98 99 | 99.85 40 | 96.45 91 | 98.15 126 | 99.39 86 |
|
Test_1112_low_res | | | 96.34 114 | 95.66 127 | 98.36 85 | 98.56 118 | 95.94 119 | 97.71 233 | 98.07 211 | 92.10 221 | 94.79 166 | 97.29 204 | 91.75 102 | 99.56 115 | 94.17 153 | 96.50 163 | 99.58 63 |
|
1112_ss | | | 96.63 102 | 96.00 113 | 98.50 75 | 98.56 118 | 96.37 100 | 98.18 187 | 98.10 206 | 92.92 190 | 94.84 162 | 98.43 115 | 92.14 94 | 99.58 112 | 94.35 148 | 96.51 162 | 99.56 65 |
|
BH-untuned | | | 95.95 125 | 95.72 120 | 96.65 184 | 98.55 120 | 92.26 244 | 98.23 176 | 97.79 224 | 93.73 157 | 94.62 168 | 98.01 151 | 88.97 149 | 99.00 167 | 93.04 182 | 98.51 111 | 98.68 143 |
|
LS3D | | | 97.16 85 | 96.66 92 | 98.68 63 | 98.53 121 | 97.19 71 | 98.93 62 | 98.90 41 | 92.83 195 | 95.99 149 | 99.37 12 | 92.12 95 | 99.87 35 | 93.67 166 | 99.57 55 | 98.97 126 |
|
HY-MVS | | 93.96 8 | 96.82 98 | 96.23 107 | 98.57 69 | 98.46 122 | 97.00 75 | 98.14 189 | 98.21 176 | 93.95 146 | 96.72 122 | 97.99 153 | 91.58 105 | 99.76 81 | 94.51 145 | 96.54 161 | 98.95 130 |
|
xiu_mvs_v1_base_debu | | | 97.60 61 | 97.56 51 | 97.72 119 | 98.35 123 | 95.98 111 | 97.86 222 | 98.51 130 | 97.13 34 | 99.01 17 | 98.40 117 | 91.56 106 | 99.80 57 | 98.53 10 | 98.68 102 | 97.37 189 |
|
xiu_mvs_v1_base | | | 97.60 61 | 97.56 51 | 97.72 119 | 98.35 123 | 95.98 111 | 97.86 222 | 98.51 130 | 97.13 34 | 99.01 17 | 98.40 117 | 91.56 106 | 99.80 57 | 98.53 10 | 98.68 102 | 97.37 189 |
|
xiu_mvs_v1_base_debi | | | 97.60 61 | 97.56 51 | 97.72 119 | 98.35 123 | 95.98 111 | 97.86 222 | 98.51 130 | 97.13 34 | 99.01 17 | 98.40 117 | 91.56 106 | 99.80 57 | 98.53 10 | 98.68 102 | 97.37 189 |
|
BH-w/o | | | 95.38 154 | 95.08 146 | 96.26 220 | 98.34 126 | 91.79 251 | 97.70 234 | 97.43 256 | 92.87 193 | 94.24 195 | 97.22 208 | 88.66 168 | 98.84 187 | 91.55 222 | 97.70 142 | 98.16 169 |
|
MVS_Test | | | 97.28 80 | 97.00 76 | 98.13 97 | 98.33 127 | 95.97 115 | 98.74 106 | 98.07 211 | 94.27 135 | 98.44 49 | 98.07 146 | 92.48 85 | 99.26 136 | 96.43 92 | 98.19 125 | 99.16 109 |
|
BH-RMVSNet | | | 95.92 127 | 95.32 137 | 97.69 123 | 98.32 128 | 94.64 190 | 98.19 183 | 97.45 254 | 94.56 126 | 96.03 147 | 98.61 100 | 85.02 239 | 99.12 148 | 90.68 236 | 99.06 88 | 99.30 94 |
|
Fast-Effi-MVS+ | | | 96.28 118 | 95.70 124 | 98.03 105 | 98.29 129 | 95.97 115 | 98.58 133 | 98.25 171 | 91.74 229 | 95.29 156 | 97.23 207 | 91.03 118 | 99.15 144 | 92.90 189 | 97.96 131 | 98.97 126 |
|
diffmvs | | | 96.32 115 | 95.74 118 | 98.07 103 | 98.26 130 | 96.14 108 | 98.53 142 | 98.23 174 | 90.10 263 | 96.88 115 | 97.73 174 | 90.16 130 | 99.15 144 | 93.90 160 | 97.85 136 | 98.91 132 |
|
UGNet | | | 96.78 99 | 96.30 103 | 98.19 94 | 98.24 131 | 95.89 126 | 98.88 70 | 98.93 35 | 97.39 16 | 96.81 119 | 97.84 165 | 82.60 269 | 99.90 25 | 96.53 88 | 99.49 67 | 98.79 137 |
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 | | | 96.06 122 | 95.72 120 | 97.08 155 | 98.23 132 | 95.93 121 | 98.73 109 | 98.27 166 | 94.86 117 | 95.07 157 | 98.09 145 | 88.21 179 | 98.54 208 | 96.59 85 | 93.46 214 | 96.79 221 |
|
GBi-Net | | | 94.49 206 | 93.80 209 | 96.56 197 | 98.21 133 | 95.00 155 | 98.82 81 | 98.18 183 | 92.46 202 | 94.09 203 | 97.07 217 | 81.16 274 | 97.95 270 | 92.08 207 | 92.14 230 | 96.72 229 |
|
test1 | | | 94.49 206 | 93.80 209 | 96.56 197 | 98.21 133 | 95.00 155 | 98.82 81 | 98.18 183 | 92.46 202 | 94.09 203 | 97.07 217 | 81.16 274 | 97.95 270 | 92.08 207 | 92.14 230 | 96.72 229 |
|
FMVSNet2 | | | 94.47 208 | 93.61 222 | 97.04 156 | 98.21 133 | 96.43 98 | 98.79 95 | 98.27 166 | 92.46 202 | 93.50 223 | 97.09 215 | 81.16 274 | 98.00 268 | 91.09 228 | 91.93 234 | 96.70 233 |
|
Effi-MVS+ | | | 97.12 87 | 96.69 89 | 98.39 84 | 98.19 136 | 96.72 87 | 97.37 255 | 98.43 147 | 93.71 159 | 97.65 89 | 98.02 149 | 92.20 93 | 99.25 137 | 96.87 77 | 97.79 138 | 99.19 104 |
|
mvs_anonymous | | | 96.70 101 | 96.53 97 | 97.18 148 | 98.19 136 | 93.78 219 | 98.31 169 | 98.19 180 | 94.01 141 | 94.47 173 | 98.27 134 | 92.08 97 | 98.46 224 | 97.39 56 | 97.91 132 | 99.31 91 |
|
LCM-MVSNet-Re | | | 95.22 164 | 95.32 137 | 94.91 266 | 98.18 138 | 87.85 302 | 98.75 102 | 95.66 314 | 95.11 105 | 88.96 283 | 96.85 244 | 90.26 129 | 97.65 280 | 95.65 116 | 98.44 115 | 99.22 103 |
|
FMVSNet3 | | | 94.97 175 | 94.26 180 | 97.11 153 | 98.18 138 | 96.62 89 | 98.56 138 | 98.26 170 | 93.67 166 | 94.09 203 | 97.10 213 | 84.25 254 | 98.01 267 | 92.08 207 | 92.14 230 | 96.70 233 |
|
CANet_DTU | | | 96.96 92 | 96.55 95 | 98.21 91 | 98.17 140 | 96.07 110 | 97.98 206 | 98.21 176 | 97.24 27 | 97.13 100 | 98.93 73 | 86.88 212 | 99.91 22 | 95.00 133 | 99.37 80 | 98.66 145 |
|
IterMVS-LS | | | 95.46 148 | 95.21 142 | 96.22 221 | 98.12 141 | 93.72 223 | 98.32 168 | 98.13 194 | 93.71 159 | 94.26 193 | 97.31 203 | 92.24 90 | 98.10 261 | 94.63 139 | 90.12 247 | 96.84 217 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
VDDNet | | | 95.36 156 | 94.53 169 | 97.86 111 | 98.10 142 | 95.13 151 | 98.85 75 | 97.75 226 | 90.46 255 | 98.36 51 | 99.39 7 | 73.27 314 | 99.64 100 | 97.98 27 | 96.58 159 | 98.81 136 |
|
MVSFormer | | | 97.57 64 | 97.49 56 | 97.84 112 | 98.07 143 | 95.76 129 | 99.47 2 | 98.40 150 | 94.98 111 | 98.79 30 | 98.83 81 | 92.34 86 | 98.41 239 | 96.91 69 | 99.59 52 | 99.34 88 |
|
lupinMVS | | | 97.44 71 | 97.22 68 | 98.12 98 | 98.07 143 | 95.76 129 | 97.68 236 | 97.76 225 | 94.50 129 | 98.79 30 | 98.61 100 | 92.34 86 | 99.30 134 | 97.58 47 | 99.59 52 | 99.31 91 |
|
TAMVS | | | 97.02 90 | 96.79 84 | 97.70 122 | 98.06 145 | 95.31 146 | 98.52 143 | 98.31 160 | 93.95 146 | 97.05 106 | 98.61 100 | 93.49 75 | 98.52 215 | 95.33 124 | 97.81 137 | 99.29 96 |
|
CDS-MVSNet | | | 96.99 91 | 96.69 89 | 97.90 110 | 98.05 146 | 95.98 111 | 98.20 179 | 98.33 159 | 93.67 166 | 96.95 108 | 98.49 111 | 93.54 74 | 98.42 232 | 95.24 130 | 97.74 141 | 99.31 91 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
ADS-MVSNet2 | | | 94.58 203 | 94.40 176 | 95.11 263 | 98.00 147 | 88.74 290 | 96.04 299 | 97.30 267 | 90.15 260 | 96.47 137 | 96.64 253 | 87.89 189 | 97.56 284 | 90.08 245 | 97.06 149 | 99.02 121 |
|
ADS-MVSNet | | | 95.00 171 | 94.45 174 | 96.63 187 | 98.00 147 | 91.91 249 | 96.04 299 | 97.74 227 | 90.15 260 | 96.47 137 | 96.64 253 | 87.89 189 | 98.96 171 | 90.08 245 | 97.06 149 | 99.02 121 |
|
IterMVS | | | 94.09 228 | 93.85 207 | 94.80 272 | 97.99 149 | 90.35 272 | 97.18 268 | 98.12 196 | 93.68 164 | 92.46 251 | 97.34 201 | 84.05 259 | 97.41 287 | 92.51 201 | 91.33 240 | 96.62 248 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
PVSNet_0 | | 88.72 19 | 91.28 272 | 90.03 275 | 95.00 265 | 97.99 149 | 87.29 305 | 94.84 315 | 98.50 135 | 92.06 222 | 89.86 275 | 95.19 286 | 79.81 286 | 99.39 130 | 92.27 204 | 69.79 328 | 98.33 165 |
|
semantic-postprocess | | | | | 94.85 269 | 97.98 151 | 90.56 270 | | 98.11 201 | 93.75 154 | 92.58 245 | 97.48 192 | 83.91 261 | 97.41 287 | 92.48 202 | 91.30 241 | 96.58 253 |
|
EI-MVSNet | | | 95.96 124 | 95.83 117 | 96.36 213 | 97.93 152 | 93.70 224 | 98.12 192 | 98.27 166 | 93.70 161 | 95.07 157 | 99.02 58 | 92.23 91 | 98.54 208 | 94.68 138 | 93.46 214 | 96.84 217 |
|
CVMVSNet | | | 95.43 150 | 96.04 111 | 93.57 289 | 97.93 152 | 83.62 311 | 98.12 192 | 98.59 113 | 95.68 75 | 96.56 126 | 99.02 58 | 87.51 201 | 97.51 285 | 93.56 169 | 97.44 145 | 99.60 59 |
|
PMMVS | | | 96.60 103 | 96.33 102 | 97.41 140 | 97.90 154 | 93.93 215 | 97.35 258 | 98.41 148 | 92.84 194 | 97.76 79 | 97.45 195 | 91.10 116 | 99.20 141 | 96.26 95 | 97.91 132 | 99.11 114 |
|
Effi-MVS+-dtu | | | 96.29 116 | 96.56 94 | 95.51 243 | 97.89 155 | 90.22 273 | 98.80 90 | 98.10 206 | 96.57 52 | 96.45 139 | 96.66 251 | 90.81 119 | 98.91 178 | 95.72 111 | 97.99 130 | 97.40 186 |
|
mvs-test1 | | | 96.60 103 | 96.68 91 | 96.37 212 | 97.89 155 | 91.81 250 | 98.56 138 | 98.10 206 | 96.57 52 | 96.52 132 | 97.94 156 | 90.81 119 | 99.45 128 | 95.72 111 | 98.01 129 | 97.86 175 |
|
QAPM | | | 96.29 116 | 95.40 129 | 98.96 51 | 97.85 157 | 97.60 56 | 99.23 21 | 98.93 35 | 89.76 273 | 93.11 234 | 99.02 58 | 89.11 143 | 99.93 9 | 91.99 212 | 99.62 47 | 99.34 88 |
|
3Dnovator+ | | 94.38 6 | 97.43 72 | 96.78 85 | 99.38 10 | 97.83 158 | 98.52 11 | 99.37 7 | 98.71 89 | 97.09 37 | 92.99 237 | 99.13 44 | 89.36 136 | 99.89 27 | 96.97 65 | 99.57 55 | 99.71 32 |
|
ACMH+ | | 92.99 14 | 94.30 215 | 93.77 212 | 95.88 233 | 97.81 159 | 92.04 248 | 98.71 112 | 98.37 155 | 93.99 143 | 90.60 271 | 98.47 113 | 80.86 279 | 99.05 159 | 92.75 193 | 92.40 229 | 96.55 258 |
|
3Dnovator | | 94.51 5 | 97.46 67 | 96.93 78 | 99.07 43 | 97.78 160 | 97.64 53 | 99.35 10 | 99.06 20 | 97.02 39 | 93.75 216 | 99.16 42 | 89.25 139 | 99.92 13 | 97.22 59 | 99.75 29 | 99.64 53 |
|
TR-MVS | | | 94.94 178 | 94.20 184 | 97.17 149 | 97.75 161 | 94.14 211 | 97.59 242 | 97.02 281 | 92.28 219 | 95.75 151 | 97.64 184 | 83.88 262 | 98.96 171 | 89.77 251 | 96.15 180 | 98.40 157 |
|
Fast-Effi-MVS+-dtu | | | 95.87 128 | 95.85 116 | 95.91 231 | 97.74 162 | 91.74 254 | 98.69 116 | 98.15 191 | 95.56 81 | 94.92 160 | 97.68 181 | 88.98 148 | 98.79 193 | 93.19 177 | 97.78 139 | 97.20 193 |
|
MIMVSNet | | | 93.26 245 | 92.21 249 | 96.41 210 | 97.73 163 | 93.13 236 | 95.65 307 | 97.03 280 | 91.27 248 | 94.04 206 | 96.06 273 | 75.33 305 | 97.19 290 | 86.56 290 | 96.23 178 | 98.92 131 |
|
Patchmatch-test1 | | | 95.32 160 | 94.97 152 | 96.35 214 | 97.67 164 | 91.29 259 | 97.33 260 | 97.60 231 | 94.68 120 | 96.92 112 | 96.95 234 | 83.97 260 | 98.50 218 | 91.33 227 | 98.32 121 | 99.25 100 |
|
ACMP | | 93.49 10 | 95.34 158 | 94.98 150 | 96.43 209 | 97.67 164 | 93.48 227 | 98.73 109 | 98.44 144 | 94.94 116 | 92.53 247 | 98.53 107 | 84.50 251 | 99.14 146 | 95.48 121 | 94.00 204 | 96.66 242 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
ACMH | | 92.88 16 | 94.55 204 | 93.95 201 | 96.34 216 | 97.63 166 | 93.26 232 | 98.81 87 | 98.49 139 | 93.43 173 | 89.74 276 | 98.53 107 | 81.91 272 | 99.08 157 | 93.69 164 | 93.30 220 | 96.70 233 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
tpmp4_e23 | | | 93.91 235 | 93.42 234 | 95.38 255 | 97.62 167 | 88.59 294 | 97.52 246 | 97.34 263 | 87.94 292 | 94.17 200 | 96.79 247 | 82.91 267 | 99.05 159 | 90.62 238 | 95.91 183 | 98.50 152 |
|
ACMM | | 93.85 9 | 95.69 137 | 95.38 133 | 96.61 190 | 97.61 168 | 93.84 218 | 98.91 63 | 98.44 144 | 95.25 99 | 94.28 192 | 98.47 113 | 86.04 227 | 99.12 148 | 95.50 120 | 93.95 206 | 96.87 214 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
Patchmatch-test | | | 94.42 210 | 93.68 219 | 96.63 187 | 97.60 169 | 91.76 252 | 94.83 316 | 97.49 251 | 89.45 281 | 94.14 201 | 97.10 213 | 88.99 145 | 98.83 189 | 85.37 299 | 98.13 127 | 99.29 96 |
|
PatchFormer-LS_test | | | 95.47 147 | 95.27 140 | 96.08 227 | 97.59 170 | 90.66 267 | 98.10 196 | 97.34 263 | 93.98 144 | 96.08 145 | 96.15 271 | 87.65 199 | 99.12 148 | 95.27 128 | 95.24 189 | 98.44 156 |
|
tpm cat1 | | | 93.36 240 | 92.80 241 | 95.07 264 | 97.58 171 | 87.97 300 | 96.76 286 | 97.86 222 | 82.17 317 | 93.53 220 | 96.04 274 | 86.13 222 | 99.13 147 | 89.24 263 | 95.87 184 | 98.10 170 |
|
MVS-HIRNet | | | 89.46 286 | 88.40 288 | 92.64 295 | 97.58 171 | 82.15 316 | 94.16 322 | 93.05 332 | 75.73 325 | 90.90 267 | 82.52 327 | 79.42 288 | 98.33 247 | 83.53 302 | 98.68 102 | 97.43 184 |
|
PatchmatchNet | | | 95.71 135 | 95.52 128 | 96.29 219 | 97.58 171 | 90.72 266 | 96.84 284 | 97.52 239 | 94.06 139 | 97.08 102 | 96.96 233 | 89.24 140 | 98.90 181 | 92.03 211 | 98.37 118 | 99.26 99 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
tpmrst | | | 95.63 139 | 95.69 125 | 95.44 249 | 97.54 174 | 88.54 295 | 96.97 273 | 97.56 233 | 93.50 171 | 97.52 95 | 96.93 240 | 89.49 133 | 99.16 143 | 95.25 129 | 96.42 165 | 98.64 147 |
|
FMVSNet1 | | | 93.19 247 | 92.07 250 | 96.56 197 | 97.54 174 | 95.00 155 | 98.82 81 | 98.18 183 | 90.38 258 | 92.27 254 | 97.07 217 | 73.68 313 | 97.95 270 | 89.36 262 | 91.30 241 | 96.72 229 |
|
CLD-MVS | | | 95.62 140 | 95.34 134 | 96.46 208 | 97.52 176 | 93.75 222 | 97.27 264 | 98.46 140 | 95.53 82 | 94.42 182 | 98.00 152 | 86.21 221 | 98.97 168 | 96.25 96 | 94.37 191 | 96.66 242 |
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 | | | | 95.40 129 | | 97.48 177 | 88.34 297 | 96.85 283 | 97.29 268 | 93.74 156 | 97.48 96 | 97.26 205 | 89.18 141 | 99.05 159 | 91.92 215 | 97.43 146 | |
|
IB-MVS | | 91.98 17 | 93.27 244 | 91.97 251 | 97.19 147 | 97.47 178 | 93.41 230 | 97.09 271 | 95.99 309 | 93.32 177 | 92.47 250 | 95.73 280 | 78.06 293 | 99.53 120 | 94.59 142 | 82.98 304 | 98.62 148 |
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 | | | 94.60 200 | 94.36 177 | 95.33 258 | 97.46 179 | 88.60 293 | 96.88 282 | 97.68 228 | 91.29 246 | 93.80 215 | 96.42 262 | 88.58 169 | 99.24 138 | 91.06 230 | 96.04 182 | 98.17 168 |
|
LPG-MVS_test | | | 95.62 140 | 95.34 134 | 96.47 205 | 97.46 179 | 93.54 225 | 98.99 55 | 98.54 123 | 94.67 121 | 94.36 184 | 98.77 87 | 85.39 233 | 99.11 152 | 95.71 113 | 94.15 199 | 96.76 224 |
|
LGP-MVS_train | | | | | 96.47 205 | 97.46 179 | 93.54 225 | | 98.54 123 | 94.67 121 | 94.36 184 | 98.77 87 | 85.39 233 | 99.11 152 | 95.71 113 | 94.15 199 | 96.76 224 |
|
jason | | | 97.32 79 | 97.08 73 | 98.06 104 | 97.45 182 | 95.59 132 | 97.87 221 | 97.91 221 | 94.79 118 | 98.55 43 | 98.83 81 | 91.12 114 | 99.23 139 | 97.58 47 | 99.60 49 | 99.34 88 |
jason: jason. |
HQP_MVS | | | 96.14 121 | 95.90 115 | 96.85 167 | 97.42 183 | 94.60 196 | 98.80 90 | 98.56 120 | 97.28 21 | 95.34 153 | 98.28 131 | 87.09 207 | 99.03 164 | 96.07 97 | 94.27 193 | 96.92 204 |
|
plane_prior7 | | | | | | 97.42 183 | 94.63 191 | | | | | | | | | | |
|
ITE_SJBPF | | | | | 95.44 249 | 97.42 183 | 91.32 258 | | 97.50 245 | 95.09 108 | 93.59 217 | 98.35 123 | 81.70 273 | 98.88 183 | 89.71 254 | 93.39 218 | 96.12 276 |
|
LTVRE_ROB | | 92.95 15 | 94.60 200 | 93.90 204 | 96.68 179 | 97.41 186 | 94.42 201 | 98.52 143 | 98.59 113 | 91.69 230 | 91.21 263 | 98.35 123 | 84.87 241 | 99.04 163 | 91.06 230 | 93.44 217 | 96.60 251 |
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 | | | | | | 97.37 187 | | | | | | | | | | | |
|
plane_prior6 | | | | | | 97.35 188 | 94.61 194 | | | | | | 87.09 207 | | | | |
|
DWT-MVSNet_test | | | 94.82 184 | 94.36 177 | 96.20 222 | 97.35 188 | 90.79 264 | 98.34 163 | 96.57 303 | 92.91 191 | 95.33 155 | 96.44 261 | 82.00 271 | 99.12 148 | 94.52 144 | 95.78 186 | 98.70 141 |
|
dp | | | 94.15 226 | 93.90 204 | 94.90 267 | 97.31 190 | 86.82 307 | 96.97 273 | 97.19 274 | 91.22 250 | 96.02 148 | 96.61 255 | 85.51 232 | 99.02 166 | 90.00 249 | 94.30 192 | 98.85 133 |
|
NP-MVS | | | | | | 97.28 191 | 94.51 199 | | | | | 97.73 174 | | | | | |
|
CostFormer | | | 94.95 176 | 94.73 163 | 95.60 242 | 97.28 191 | 89.06 286 | 97.53 245 | 96.89 292 | 89.66 277 | 96.82 118 | 96.72 249 | 86.05 225 | 98.95 175 | 95.53 119 | 96.13 181 | 98.79 137 |
|
VPA-MVSNet | | | 95.75 133 | 95.11 145 | 97.69 123 | 97.24 193 | 97.27 66 | 98.94 61 | 99.23 12 | 95.13 104 | 95.51 152 | 97.32 202 | 85.73 229 | 98.91 178 | 97.33 58 | 89.55 255 | 96.89 212 |
|
tpm2 | | | 94.19 221 | 93.76 214 | 95.46 247 | 97.23 194 | 89.04 287 | 97.31 262 | 96.85 295 | 87.08 296 | 96.21 143 | 96.79 247 | 83.75 265 | 98.74 195 | 92.43 203 | 96.23 178 | 98.59 149 |
|
EPMVS | | | 94.99 172 | 94.48 170 | 96.52 201 | 97.22 195 | 91.75 253 | 97.23 265 | 91.66 333 | 94.11 137 | 97.28 97 | 96.81 246 | 85.70 230 | 98.84 187 | 93.04 182 | 97.28 147 | 98.97 126 |
|
FMVSNet5 | | | 91.81 267 | 90.92 261 | 94.49 278 | 97.21 196 | 92.09 246 | 98.00 205 | 97.55 237 | 89.31 284 | 90.86 268 | 95.61 285 | 74.48 310 | 95.32 316 | 85.57 297 | 89.70 251 | 96.07 278 |
|
HQP-NCC | | | | | | 97.20 197 | | 98.05 199 | | 96.43 54 | 94.45 174 | | | | | | |
|
ACMP_Plane | | | | | | 97.20 197 | | 98.05 199 | | 96.43 54 | 94.45 174 | | | | | | |
|
HQP-MVS | | | 95.72 134 | 95.40 129 | 96.69 176 | 97.20 197 | 94.25 209 | 98.05 199 | 98.46 140 | 96.43 54 | 94.45 174 | 97.73 174 | 86.75 213 | 98.96 171 | 95.30 125 | 94.18 197 | 96.86 216 |
|
OpenMVS | | 93.04 13 | 95.83 130 | 95.00 148 | 98.32 87 | 97.18 200 | 97.32 64 | 99.21 30 | 98.97 28 | 89.96 266 | 91.14 264 | 99.05 57 | 86.64 215 | 99.92 13 | 93.38 171 | 99.47 69 | 97.73 178 |
|
VPNet | | | 94.99 172 | 94.19 185 | 97.40 141 | 97.16 201 | 96.57 92 | 98.71 112 | 98.97 28 | 95.67 76 | 94.84 162 | 98.24 137 | 80.36 284 | 98.67 199 | 96.46 90 | 87.32 285 | 96.96 201 |
|
GA-MVS | | | 94.81 185 | 94.03 195 | 97.14 150 | 97.15 202 | 93.86 217 | 96.76 286 | 97.58 232 | 94.00 142 | 94.76 167 | 97.04 225 | 80.91 277 | 98.48 219 | 91.79 217 | 96.25 177 | 99.09 115 |
|
FIs | | | 96.51 108 | 96.12 109 | 97.67 125 | 97.13 203 | 97.54 58 | 99.36 8 | 99.22 14 | 95.89 69 | 94.03 207 | 98.35 123 | 91.98 99 | 98.44 229 | 96.40 93 | 92.76 226 | 97.01 198 |
|
1314 | | | 96.25 120 | 95.73 119 | 97.79 116 | 97.13 203 | 95.55 137 | 98.19 183 | 98.59 113 | 93.47 172 | 92.03 259 | 97.82 169 | 91.33 112 | 99.49 123 | 94.62 140 | 98.44 115 | 98.32 166 |
|
DeepMVS_CX | | | | | 86.78 310 | 97.09 205 | 72.30 329 | | 95.17 319 | 75.92 324 | 84.34 311 | 95.19 286 | 70.58 318 | 95.35 315 | 79.98 310 | 89.04 262 | 92.68 319 |
|
PAPM | | | 94.95 176 | 94.00 197 | 97.78 117 | 97.04 206 | 95.65 131 | 96.03 301 | 98.25 171 | 91.23 249 | 94.19 198 | 97.80 171 | 91.27 113 | 98.86 186 | 82.61 304 | 97.61 143 | 98.84 135 |
|
CR-MVSNet | | | 94.76 187 | 94.15 187 | 96.59 192 | 97.00 207 | 93.43 228 | 94.96 312 | 97.56 233 | 92.46 202 | 96.93 110 | 96.24 265 | 88.15 181 | 97.88 277 | 87.38 285 | 96.65 157 | 98.46 154 |
|
RPMNet | | | 92.52 253 | 91.17 256 | 96.59 192 | 97.00 207 | 93.43 228 | 94.96 312 | 97.26 271 | 82.27 316 | 96.93 110 | 92.12 320 | 86.98 210 | 97.88 277 | 76.32 318 | 96.65 157 | 98.46 154 |
|
UniMVSNet (Re) | | | 95.78 132 | 95.19 143 | 97.58 134 | 96.99 209 | 97.47 60 | 98.79 95 | 99.18 15 | 95.60 79 | 93.92 210 | 97.04 225 | 91.68 103 | 98.48 219 | 95.80 109 | 87.66 282 | 96.79 221 |
|
FC-MVSNet-test | | | 96.42 111 | 96.05 110 | 97.53 136 | 96.95 210 | 97.27 66 | 99.36 8 | 99.23 12 | 95.83 71 | 93.93 209 | 98.37 121 | 92.00 98 | 98.32 248 | 96.02 101 | 92.72 227 | 97.00 199 |
|
TESTMET0.1,1 | | | 94.18 223 | 93.69 218 | 95.63 241 | 96.92 211 | 89.12 285 | 96.91 277 | 94.78 321 | 93.17 181 | 94.88 161 | 96.45 260 | 78.52 291 | 98.92 177 | 93.09 179 | 98.50 112 | 98.85 133 |
|
TinyColmap | | | 92.31 255 | 91.53 254 | 94.65 275 | 96.92 211 | 89.75 276 | 96.92 275 | 96.68 299 | 90.45 256 | 89.62 277 | 97.85 164 | 76.06 303 | 98.81 191 | 86.74 289 | 92.51 228 | 95.41 291 |
|
cascas | | | 94.63 199 | 93.86 206 | 96.93 164 | 96.91 213 | 94.27 208 | 96.00 302 | 98.51 130 | 85.55 305 | 94.54 170 | 96.23 267 | 84.20 257 | 98.87 184 | 95.80 109 | 96.98 152 | 97.66 181 |
|
nrg030 | | | 96.28 118 | 95.72 120 | 97.96 108 | 96.90 214 | 98.15 35 | 99.39 5 | 98.31 160 | 95.47 84 | 94.42 182 | 98.35 123 | 92.09 96 | 98.69 196 | 97.50 53 | 89.05 261 | 97.04 197 |
|
MVS | | | 94.67 197 | 93.54 226 | 98.08 101 | 96.88 215 | 96.56 93 | 98.19 183 | 98.50 135 | 78.05 323 | 92.69 242 | 98.02 149 | 91.07 117 | 99.63 103 | 90.09 244 | 98.36 119 | 98.04 171 |
|
WR-MVS_H | | | 95.05 170 | 94.46 172 | 96.81 169 | 96.86 216 | 95.82 128 | 99.24 20 | 99.24 10 | 93.87 150 | 92.53 247 | 96.84 245 | 90.37 125 | 98.24 256 | 93.24 175 | 87.93 277 | 96.38 269 |
|
UniMVSNet_NR-MVSNet | | | 95.71 135 | 95.15 144 | 97.40 141 | 96.84 217 | 96.97 76 | 98.74 106 | 99.24 10 | 95.16 103 | 93.88 211 | 97.72 177 | 91.68 103 | 98.31 250 | 95.81 107 | 87.25 287 | 96.92 204 |
|
USDC | | | 93.33 243 | 92.71 243 | 95.21 259 | 96.83 218 | 90.83 263 | 96.91 277 | 97.50 245 | 93.84 151 | 90.72 269 | 98.14 142 | 77.69 295 | 98.82 190 | 89.51 259 | 93.21 223 | 95.97 280 |
|
test-LLR | | | 95.10 169 | 94.87 159 | 95.80 236 | 96.77 219 | 89.70 277 | 96.91 277 | 95.21 316 | 95.11 105 | 94.83 164 | 95.72 282 | 87.71 195 | 98.97 168 | 93.06 180 | 98.50 112 | 98.72 139 |
|
test-mter | | | 94.08 229 | 93.51 229 | 95.80 236 | 96.77 219 | 89.70 277 | 96.91 277 | 95.21 316 | 92.89 192 | 94.83 164 | 95.72 282 | 77.69 295 | 98.97 168 | 93.06 180 | 98.50 112 | 98.72 139 |
|
Patchmtry | | | 93.22 246 | 92.35 247 | 95.84 234 | 96.77 219 | 93.09 237 | 94.66 318 | 97.56 233 | 87.37 295 | 92.90 238 | 96.24 265 | 88.15 181 | 97.90 273 | 87.37 286 | 90.10 248 | 96.53 260 |
|
gg-mvs-nofinetune | | | 92.21 256 | 90.58 270 | 97.13 151 | 96.75 222 | 95.09 152 | 95.85 304 | 89.40 336 | 85.43 306 | 94.50 172 | 81.98 328 | 80.80 280 | 98.40 245 | 92.16 205 | 98.33 120 | 97.88 174 |
|
XXY-MVS | | | 95.20 166 | 94.45 174 | 97.46 137 | 96.75 222 | 96.56 93 | 98.86 74 | 98.65 109 | 93.30 179 | 93.27 227 | 98.27 134 | 84.85 242 | 98.87 184 | 94.82 136 | 91.26 243 | 96.96 201 |
|
CP-MVSNet | | | 94.94 178 | 94.30 179 | 96.83 168 | 96.72 224 | 95.56 135 | 99.11 43 | 98.95 32 | 93.89 148 | 92.42 252 | 97.90 159 | 87.19 206 | 98.12 260 | 94.32 149 | 88.21 274 | 96.82 220 |
|
PatchT | | | 93.06 249 | 91.97 251 | 96.35 214 | 96.69 225 | 92.67 240 | 94.48 319 | 97.08 276 | 86.62 297 | 97.08 102 | 92.23 319 | 87.94 187 | 97.90 273 | 78.89 313 | 96.69 155 | 98.49 153 |
|
PS-CasMVS | | | 94.67 197 | 93.99 199 | 96.71 173 | 96.68 226 | 95.26 147 | 99.13 40 | 99.03 23 | 93.68 164 | 92.33 253 | 97.95 155 | 85.35 235 | 98.10 261 | 93.59 168 | 88.16 276 | 96.79 221 |
|
WR-MVS | | | 95.15 167 | 94.46 172 | 97.22 145 | 96.67 227 | 96.45 97 | 98.21 178 | 98.81 59 | 94.15 136 | 93.16 230 | 97.69 178 | 87.51 201 | 98.30 252 | 95.29 127 | 88.62 271 | 96.90 211 |
|
test_0402 | | | 91.32 271 | 90.27 273 | 94.48 279 | 96.60 228 | 91.12 261 | 98.50 148 | 97.22 273 | 86.10 301 | 88.30 286 | 96.98 231 | 77.65 297 | 97.99 269 | 78.13 315 | 92.94 225 | 94.34 309 |
|
TransMVSNet (Re) | | | 92.67 251 | 91.51 255 | 96.15 223 | 96.58 229 | 94.65 189 | 98.90 64 | 96.73 296 | 90.86 253 | 89.46 279 | 97.86 162 | 85.62 231 | 98.09 263 | 86.45 291 | 81.12 309 | 95.71 286 |
|
XVG-ACMP-BASELINE | | | 94.54 205 | 94.14 188 | 95.75 239 | 96.55 230 | 91.65 255 | 98.11 194 | 98.44 144 | 94.96 113 | 94.22 196 | 97.90 159 | 79.18 290 | 99.11 152 | 94.05 157 | 93.85 207 | 96.48 266 |
|
DU-MVS | | | 95.42 151 | 94.76 162 | 97.40 141 | 96.53 231 | 96.97 76 | 98.66 125 | 98.99 27 | 95.43 86 | 93.88 211 | 97.69 178 | 88.57 170 | 98.31 250 | 95.81 107 | 87.25 287 | 96.92 204 |
|
NR-MVSNet | | | 94.98 174 | 94.16 186 | 97.44 138 | 96.53 231 | 97.22 70 | 98.74 106 | 98.95 32 | 94.96 113 | 89.25 281 | 97.69 178 | 89.32 137 | 98.18 258 | 94.59 142 | 87.40 284 | 96.92 204 |
|
tpm | | | 94.13 227 | 93.80 209 | 95.12 262 | 96.50 233 | 87.91 301 | 97.44 248 | 95.89 313 | 92.62 198 | 96.37 141 | 96.30 264 | 84.13 258 | 98.30 252 | 93.24 175 | 91.66 239 | 99.14 112 |
|
pm-mvs1 | | | 93.94 234 | 93.06 237 | 96.59 192 | 96.49 234 | 95.16 149 | 98.95 60 | 98.03 217 | 92.32 217 | 91.08 265 | 97.84 165 | 84.54 250 | 98.41 239 | 92.16 205 | 86.13 298 | 96.19 275 |
|
JIA-IIPM | | | 93.35 241 | 92.49 245 | 95.92 230 | 96.48 235 | 90.65 268 | 95.01 311 | 96.96 287 | 85.93 303 | 96.08 145 | 87.33 324 | 87.70 197 | 98.78 194 | 91.35 226 | 95.58 187 | 98.34 164 |
|
TranMVSNet+NR-MVSNet | | | 95.14 168 | 94.48 170 | 97.11 153 | 96.45 236 | 96.36 101 | 99.03 52 | 99.03 23 | 95.04 109 | 93.58 218 | 97.93 157 | 88.27 178 | 98.03 266 | 94.13 154 | 86.90 292 | 96.95 203 |
|
testgi | | | 93.06 249 | 92.45 246 | 94.88 268 | 96.43 237 | 89.90 274 | 98.75 102 | 97.54 238 | 95.60 79 | 91.63 262 | 97.91 158 | 74.46 311 | 97.02 292 | 86.10 293 | 93.67 209 | 97.72 179 |
|
v7 | | | 94.69 193 | 94.04 194 | 96.62 189 | 96.41 238 | 94.79 184 | 98.78 97 | 98.13 194 | 91.89 225 | 94.30 190 | 97.16 210 | 88.13 183 | 98.45 226 | 91.96 214 | 89.65 252 | 96.61 249 |
|
v1neww | | | 94.83 181 | 94.22 181 | 96.68 179 | 96.39 239 | 94.85 165 | 98.87 71 | 98.11 201 | 92.45 207 | 94.45 174 | 97.06 220 | 88.82 158 | 98.54 208 | 92.93 186 | 88.91 264 | 96.65 244 |
|
v7new | | | 94.83 181 | 94.22 181 | 96.68 179 | 96.39 239 | 94.85 165 | 98.87 71 | 98.11 201 | 92.45 207 | 94.45 174 | 97.06 220 | 88.82 158 | 98.54 208 | 92.93 186 | 88.91 264 | 96.65 244 |
|
v10 | | | 94.29 216 | 93.55 225 | 96.51 202 | 96.39 239 | 94.80 181 | 98.99 55 | 98.19 180 | 91.35 242 | 93.02 236 | 96.99 230 | 88.09 184 | 98.41 239 | 90.50 240 | 88.41 273 | 96.33 272 |
|
v16 | | | 92.08 259 | 90.94 259 | 95.49 245 | 96.38 242 | 94.84 174 | 98.81 87 | 97.51 242 | 89.94 268 | 85.25 303 | 93.28 300 | 88.86 153 | 96.91 295 | 88.70 273 | 79.78 312 | 94.72 300 |
|
v8 | | | 94.47 208 | 93.77 212 | 96.57 196 | 96.36 243 | 94.83 176 | 99.05 50 | 98.19 180 | 91.92 224 | 93.16 230 | 96.97 232 | 88.82 158 | 98.48 219 | 91.69 220 | 87.79 280 | 96.39 268 |
|
v6 | | | 94.83 181 | 94.21 183 | 96.69 176 | 96.36 243 | 94.85 165 | 98.87 71 | 98.11 201 | 92.46 202 | 94.44 180 | 97.05 224 | 88.76 164 | 98.57 206 | 92.95 185 | 88.92 263 | 96.65 244 |
|
LP | | | 91.12 274 | 89.99 276 | 94.53 277 | 96.35 245 | 88.70 291 | 93.86 323 | 97.35 262 | 84.88 308 | 90.98 266 | 94.77 291 | 84.40 252 | 97.43 286 | 75.41 321 | 91.89 236 | 97.47 183 |
|
GG-mvs-BLEND | | | | | 96.59 192 | 96.34 246 | 94.98 158 | 96.51 296 | 88.58 337 | | 93.10 235 | 94.34 296 | 80.34 285 | 98.05 265 | 89.53 258 | 96.99 151 | 96.74 226 |
|
v18 | | | 92.10 258 | 90.97 258 | 95.50 244 | 96.34 246 | 94.85 165 | 98.82 81 | 97.52 239 | 89.99 265 | 85.31 302 | 93.26 301 | 88.90 152 | 96.92 294 | 88.82 271 | 79.77 313 | 94.73 299 |
|
v17 | | | 92.08 259 | 90.94 259 | 95.48 246 | 96.34 246 | 94.83 176 | 98.81 87 | 97.52 239 | 89.95 267 | 85.32 300 | 93.24 302 | 88.91 151 | 96.91 295 | 88.76 272 | 79.63 314 | 94.71 301 |
|
v11 | | | 91.85 266 | 90.68 268 | 95.36 256 | 96.34 246 | 94.74 188 | 98.80 90 | 97.43 256 | 89.60 279 | 85.09 305 | 93.03 307 | 88.53 173 | 96.75 302 | 87.37 286 | 79.96 311 | 94.58 307 |
|
v13 | | | 91.88 265 | 90.69 267 | 95.43 251 | 96.33 250 | 94.78 186 | 98.75 102 | 97.50 245 | 89.68 276 | 84.93 309 | 92.98 309 | 88.84 156 | 96.83 299 | 88.14 280 | 79.09 317 | 94.69 302 |
|
V14 | | | 91.93 262 | 90.76 264 | 95.42 254 | 96.33 250 | 94.81 180 | 98.77 98 | 97.51 242 | 89.86 271 | 85.09 305 | 93.13 303 | 88.80 162 | 96.83 299 | 88.32 277 | 79.06 318 | 94.60 306 |
|
V42 | | | 94.78 186 | 94.14 188 | 96.70 175 | 96.33 250 | 95.22 148 | 98.97 59 | 98.09 209 | 92.32 217 | 94.31 188 | 97.06 220 | 88.39 176 | 98.55 207 | 92.90 189 | 88.87 266 | 96.34 271 |
|
V9 | | | 91.91 263 | 90.73 265 | 95.45 248 | 96.32 253 | 94.80 181 | 98.77 98 | 97.50 245 | 89.81 272 | 85.03 307 | 93.08 305 | 88.76 164 | 96.86 297 | 88.24 278 | 79.03 319 | 94.69 302 |
|
v15 | | | 91.94 261 | 90.77 263 | 95.43 251 | 96.31 254 | 94.83 176 | 98.77 98 | 97.50 245 | 89.92 269 | 85.13 304 | 93.08 305 | 88.76 164 | 96.86 297 | 88.40 276 | 79.10 316 | 94.61 305 |
|
v12 | | | 91.89 264 | 90.70 266 | 95.43 251 | 96.31 254 | 94.80 181 | 98.76 101 | 97.50 245 | 89.76 273 | 84.95 308 | 93.00 308 | 88.82 158 | 96.82 301 | 88.23 279 | 79.00 320 | 94.68 304 |
|
divwei89l23v2f112 | | | 94.76 187 | 94.12 191 | 96.67 182 | 96.28 256 | 94.85 165 | 98.69 116 | 98.12 196 | 92.44 209 | 94.29 191 | 96.94 236 | 88.85 155 | 98.48 219 | 92.67 194 | 88.79 270 | 96.67 239 |
|
PEN-MVS | | | 94.42 210 | 93.73 216 | 96.49 203 | 96.28 256 | 94.84 174 | 99.17 34 | 99.00 25 | 93.51 170 | 92.23 255 | 97.83 168 | 86.10 224 | 97.90 273 | 92.55 199 | 86.92 291 | 96.74 226 |
|
v1141 | | | 94.75 189 | 94.11 192 | 96.67 182 | 96.27 258 | 94.86 164 | 98.69 116 | 98.12 196 | 92.43 210 | 94.31 188 | 96.94 236 | 88.78 163 | 98.48 219 | 92.63 196 | 88.85 268 | 96.67 239 |
|
v1 | | | 94.75 189 | 94.11 192 | 96.69 176 | 96.27 258 | 94.87 163 | 98.69 116 | 98.12 196 | 92.43 210 | 94.32 187 | 96.94 236 | 88.71 167 | 98.54 208 | 92.66 195 | 88.84 269 | 96.67 239 |
|
v1144 | | | 94.59 202 | 93.92 202 | 96.60 191 | 96.21 260 | 94.78 186 | 98.59 131 | 98.14 193 | 91.86 228 | 94.21 197 | 97.02 227 | 87.97 186 | 98.41 239 | 91.72 219 | 89.57 253 | 96.61 249 |
|
Baseline_NR-MVSNet | | | 94.35 213 | 93.81 208 | 95.96 229 | 96.20 261 | 94.05 213 | 98.61 130 | 96.67 300 | 91.44 236 | 93.85 213 | 97.60 186 | 88.57 170 | 98.14 259 | 94.39 146 | 86.93 290 | 95.68 287 |
|
MS-PatchMatch | | | 93.84 236 | 93.63 220 | 94.46 281 | 96.18 262 | 89.45 280 | 97.76 230 | 98.27 166 | 92.23 220 | 92.13 258 | 97.49 191 | 79.50 287 | 98.69 196 | 89.75 253 | 99.38 79 | 95.25 292 |
|
pcd1.5k->3k | | | 39.42 315 | 41.78 316 | 32.35 328 | 96.17 263 | 0.00 346 | 0.00 337 | 98.54 123 | 0.00 341 | 0.00 342 | 0.00 343 | 87.78 194 | 0.00 344 | 0.00 341 | 93.56 213 | 97.06 195 |
|
v2v482 | | | 94.69 193 | 94.03 195 | 96.65 184 | 96.17 263 | 94.79 184 | 98.67 123 | 98.08 210 | 92.72 196 | 94.00 208 | 97.16 210 | 87.69 198 | 98.45 226 | 92.91 188 | 88.87 266 | 96.72 229 |
|
EPNet_dtu | | | 95.21 165 | 94.95 153 | 95.99 228 | 96.17 263 | 90.45 271 | 98.16 188 | 97.27 270 | 96.77 44 | 93.14 233 | 98.33 128 | 90.34 126 | 98.42 232 | 85.57 297 | 98.81 100 | 99.09 115 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
OPM-MVS | | | 95.69 137 | 95.33 136 | 96.76 171 | 96.16 266 | 94.63 191 | 98.43 155 | 98.39 152 | 96.64 50 | 95.02 159 | 98.78 85 | 85.15 238 | 99.05 159 | 95.21 131 | 94.20 196 | 96.60 251 |
|
v1192 | | | 94.32 214 | 93.58 224 | 96.53 200 | 96.10 267 | 94.45 200 | 98.50 148 | 98.17 188 | 91.54 233 | 94.19 198 | 97.06 220 | 86.95 211 | 98.43 231 | 90.14 243 | 89.57 253 | 96.70 233 |
|
v148 | | | 94.29 216 | 93.76 214 | 95.91 231 | 96.10 267 | 92.93 238 | 98.58 133 | 97.97 218 | 92.59 200 | 93.47 224 | 96.95 234 | 88.53 173 | 98.32 248 | 92.56 198 | 87.06 289 | 96.49 265 |
|
v144192 | | | 94.39 212 | 93.70 217 | 96.48 204 | 96.06 269 | 94.35 205 | 98.58 133 | 98.16 190 | 91.45 235 | 94.33 186 | 97.02 227 | 87.50 203 | 98.45 226 | 91.08 229 | 89.11 260 | 96.63 247 |
|
DTE-MVSNet | | | 93.98 233 | 93.26 236 | 96.14 224 | 96.06 269 | 94.39 203 | 99.20 31 | 98.86 51 | 93.06 184 | 91.78 260 | 97.81 170 | 85.87 228 | 97.58 283 | 90.53 239 | 86.17 296 | 96.46 267 |
|
v1240 | | | 94.06 231 | 93.29 235 | 96.34 216 | 96.03 271 | 93.90 216 | 98.44 153 | 98.17 188 | 91.18 251 | 94.13 202 | 97.01 229 | 86.05 225 | 98.42 232 | 89.13 265 | 89.50 256 | 96.70 233 |
|
v1921920 | | | 94.20 220 | 93.47 231 | 96.40 211 | 95.98 272 | 94.08 212 | 98.52 143 | 98.15 191 | 91.33 243 | 94.25 194 | 97.20 209 | 86.41 218 | 98.42 232 | 90.04 248 | 89.39 258 | 96.69 238 |
|
EU-MVSNet | | | 93.66 238 | 94.14 188 | 92.25 298 | 95.96 273 | 83.38 312 | 98.52 143 | 98.12 196 | 94.69 119 | 92.61 244 | 98.13 143 | 87.36 205 | 96.39 311 | 91.82 216 | 90.00 249 | 96.98 200 |
|
v52 | | | 94.18 223 | 93.52 227 | 96.13 225 | 95.95 274 | 94.29 207 | 99.23 21 | 98.21 176 | 91.42 237 | 92.84 239 | 96.89 242 | 87.85 192 | 98.53 214 | 91.51 223 | 87.81 278 | 95.57 290 |
|
v7n | | | 94.19 221 | 93.43 232 | 96.47 205 | 95.90 275 | 94.38 204 | 99.26 17 | 98.34 158 | 91.99 223 | 92.76 241 | 97.13 212 | 88.31 177 | 98.52 215 | 89.48 260 | 87.70 281 | 96.52 261 |
|
V4 | | | 94.18 223 | 93.52 227 | 96.13 225 | 95.89 276 | 94.31 206 | 99.23 21 | 98.22 175 | 91.42 237 | 92.82 240 | 96.89 242 | 87.93 188 | 98.52 215 | 91.51 223 | 87.81 278 | 95.58 289 |
|
gm-plane-assit | | | | | | 95.88 277 | 87.47 303 | | | 89.74 275 | | 96.94 236 | | 99.19 142 | 93.32 174 | | |
|
LF4IMVS | | | 93.14 248 | 92.79 242 | 94.20 284 | 95.88 277 | 88.67 292 | 97.66 238 | 97.07 277 | 93.81 153 | 91.71 261 | 97.65 182 | 77.96 294 | 98.81 191 | 91.47 225 | 91.92 235 | 95.12 293 |
|
PS-MVSNAJss | | | 96.43 110 | 96.26 105 | 96.92 166 | 95.84 279 | 95.08 153 | 99.16 35 | 98.50 135 | 95.87 70 | 93.84 214 | 98.34 127 | 94.51 60 | 98.61 202 | 96.88 74 | 93.45 216 | 97.06 195 |
|
testpf | | | 88.74 289 | 89.09 282 | 87.69 307 | 95.78 280 | 83.16 314 | 84.05 334 | 94.13 329 | 85.22 307 | 90.30 272 | 94.39 295 | 74.92 308 | 95.80 313 | 89.77 251 | 93.28 222 | 84.10 328 |
|
pmmvs4 | | | 94.69 193 | 93.99 199 | 96.81 169 | 95.74 281 | 95.94 119 | 97.40 251 | 97.67 229 | 90.42 257 | 93.37 225 | 97.59 187 | 89.08 144 | 98.20 257 | 92.97 184 | 91.67 238 | 96.30 273 |
|
v748 | | | 93.75 237 | 93.06 237 | 95.82 235 | 95.73 282 | 92.64 241 | 99.25 19 | 98.24 173 | 91.60 232 | 92.22 256 | 96.52 258 | 87.60 200 | 98.46 224 | 90.64 237 | 85.72 299 | 96.36 270 |
|
test_djsdf | | | 96.00 123 | 95.69 125 | 96.93 164 | 95.72 283 | 95.49 138 | 99.47 2 | 98.40 150 | 94.98 111 | 94.58 169 | 97.86 162 | 89.16 142 | 98.41 239 | 96.91 69 | 94.12 201 | 96.88 213 |
|
SixPastTwentyTwo | | | 93.34 242 | 92.86 240 | 94.75 273 | 95.67 284 | 89.41 282 | 98.75 102 | 96.67 300 | 93.89 148 | 90.15 274 | 98.25 136 | 80.87 278 | 98.27 255 | 90.90 233 | 90.64 245 | 96.57 255 |
|
K. test v3 | | | 92.55 252 | 91.91 253 | 94.48 279 | 95.64 285 | 89.24 283 | 99.07 49 | 94.88 320 | 94.04 140 | 86.78 291 | 97.59 187 | 77.64 298 | 97.64 281 | 92.08 207 | 89.43 257 | 96.57 255 |
|
OurMVSNet-221017-0 | | | 94.21 219 | 94.00 197 | 94.85 269 | 95.60 286 | 89.22 284 | 98.89 68 | 97.43 256 | 95.29 97 | 92.18 257 | 98.52 110 | 82.86 268 | 98.59 204 | 93.46 170 | 91.76 237 | 96.74 226 |
|
mvs_tets | | | 95.41 153 | 95.00 148 | 96.65 184 | 95.58 287 | 94.42 201 | 99.00 54 | 98.55 122 | 95.73 74 | 93.21 229 | 98.38 120 | 83.45 266 | 98.63 201 | 97.09 63 | 94.00 204 | 96.91 209 |
|
Gipuma | | | 78.40 302 | 76.75 303 | 83.38 316 | 95.54 288 | 80.43 318 | 79.42 335 | 97.40 259 | 64.67 329 | 73.46 324 | 80.82 330 | 45.65 334 | 93.14 325 | 66.32 329 | 87.43 283 | 76.56 333 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
test0.0.03 1 | | | 94.08 229 | 93.51 229 | 95.80 236 | 95.53 289 | 92.89 239 | 97.38 253 | 95.97 310 | 95.11 105 | 92.51 249 | 96.66 251 | 87.71 195 | 96.94 293 | 87.03 288 | 93.67 209 | 97.57 182 |
|
pmmvs5 | | | 93.65 239 | 92.97 239 | 95.68 240 | 95.49 290 | 92.37 243 | 98.20 179 | 97.28 269 | 89.66 277 | 92.58 245 | 97.26 205 | 82.14 270 | 98.09 263 | 93.18 178 | 90.95 244 | 96.58 253 |
|
N_pmnet | | | 87.12 294 | 87.77 291 | 85.17 314 | 95.46 291 | 61.92 336 | 97.37 255 | 70.66 344 | 85.83 304 | 88.73 285 | 96.04 274 | 85.33 237 | 97.76 279 | 80.02 308 | 90.48 246 | 95.84 282 |
|
jajsoiax | | | 95.45 149 | 95.03 147 | 96.73 172 | 95.42 292 | 94.63 191 | 99.14 37 | 98.52 128 | 95.74 73 | 93.22 228 | 98.36 122 | 83.87 263 | 98.65 200 | 96.95 68 | 94.04 202 | 96.91 209 |
|
DI_MVS_plusplus_test | | | 94.74 191 | 93.62 221 | 98.09 100 | 95.34 293 | 95.92 122 | 98.09 197 | 97.34 263 | 94.66 123 | 85.89 295 | 95.91 276 | 80.49 283 | 99.38 131 | 96.66 83 | 98.22 123 | 98.97 126 |
|
test_normal | | | 94.72 192 | 93.59 223 | 98.11 99 | 95.30 294 | 95.95 118 | 97.91 214 | 97.39 261 | 94.64 124 | 85.70 298 | 95.88 277 | 80.52 282 | 99.36 132 | 96.69 82 | 98.30 122 | 99.01 124 |
|
MDA-MVSNet-bldmvs | | | 89.97 283 | 88.35 289 | 94.83 271 | 95.21 295 | 91.34 257 | 97.64 239 | 97.51 242 | 88.36 290 | 71.17 327 | 96.13 272 | 79.22 289 | 96.63 308 | 83.65 301 | 86.27 295 | 96.52 261 |
|
anonymousdsp | | | 95.42 151 | 94.91 158 | 96.94 163 | 95.10 296 | 95.90 125 | 99.14 37 | 98.41 148 | 93.75 154 | 93.16 230 | 97.46 193 | 87.50 203 | 98.41 239 | 95.63 117 | 94.03 203 | 96.50 264 |
|
EPNet | | | 97.28 80 | 96.87 81 | 98.51 74 | 94.98 297 | 96.14 108 | 98.90 64 | 97.02 281 | 98.28 1 | 95.99 149 | 99.11 46 | 91.36 111 | 99.89 27 | 96.98 64 | 99.19 85 | 99.50 71 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
MVP-Stereo | | | 94.28 218 | 93.92 202 | 95.35 257 | 94.95 298 | 92.60 242 | 97.97 207 | 97.65 230 | 91.61 231 | 90.68 270 | 97.09 215 | 86.32 220 | 98.42 232 | 89.70 255 | 99.34 81 | 95.02 296 |
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
lessismore_v0 | | | | | 94.45 282 | 94.93 299 | 88.44 296 | | 91.03 334 | | 86.77 292 | 97.64 184 | 76.23 302 | 98.42 232 | 90.31 242 | 85.64 300 | 96.51 263 |
|
MDA-MVSNet_test_wron | | | 90.71 278 | 89.38 281 | 94.68 274 | 94.83 300 | 90.78 265 | 97.19 267 | 97.46 252 | 87.60 293 | 72.41 326 | 95.72 282 | 86.51 216 | 96.71 306 | 85.92 295 | 86.80 293 | 96.56 257 |
|
YYNet1 | | | 90.70 279 | 89.39 280 | 94.62 276 | 94.79 301 | 90.65 268 | 97.20 266 | 97.46 252 | 87.54 294 | 72.54 325 | 95.74 279 | 86.51 216 | 96.66 307 | 86.00 294 | 86.76 294 | 96.54 259 |
|
EG-PatchMatch MVS | | | 91.13 273 | 90.12 274 | 94.17 286 | 94.73 302 | 89.00 288 | 98.13 191 | 97.81 223 | 89.22 285 | 85.32 300 | 96.46 259 | 67.71 322 | 98.42 232 | 87.89 284 | 93.82 208 | 95.08 294 |
|
pmmvs6 | | | 91.77 268 | 90.63 269 | 95.17 261 | 94.69 303 | 91.24 260 | 98.67 123 | 97.92 220 | 86.14 300 | 89.62 277 | 97.56 190 | 75.79 304 | 98.34 246 | 90.75 235 | 84.56 303 | 95.94 281 |
|
new_pmnet | | | 90.06 282 | 89.00 285 | 93.22 294 | 94.18 304 | 88.32 298 | 96.42 297 | 96.89 292 | 86.19 299 | 85.67 299 | 93.62 298 | 77.18 300 | 97.10 291 | 81.61 306 | 89.29 259 | 94.23 310 |
|
DSMNet-mixed | | | 92.52 253 | 92.58 244 | 92.33 297 | 94.15 305 | 82.65 315 | 98.30 171 | 94.26 326 | 89.08 286 | 92.65 243 | 95.73 280 | 85.01 240 | 95.76 314 | 86.24 292 | 97.76 140 | 98.59 149 |
|
UnsupCasMVSNet_eth | | | 90.99 276 | 89.92 277 | 94.19 285 | 94.08 306 | 89.83 275 | 97.13 270 | 98.67 102 | 93.69 162 | 85.83 297 | 96.19 270 | 75.15 306 | 96.74 303 | 89.14 264 | 79.41 315 | 96.00 279 |
|
Anonymous20231206 | | | 91.66 269 | 91.10 257 | 93.33 291 | 94.02 307 | 87.35 304 | 98.58 133 | 97.26 271 | 90.48 254 | 90.16 273 | 96.31 263 | 83.83 264 | 96.53 309 | 79.36 311 | 89.90 250 | 96.12 276 |
|
test20.03 | | | 90.89 277 | 90.38 271 | 92.43 296 | 93.48 308 | 88.14 299 | 98.33 164 | 97.56 233 | 93.40 174 | 87.96 287 | 96.71 250 | 80.69 281 | 94.13 320 | 79.15 312 | 86.17 296 | 95.01 297 |
|
CMPMVS | | 66.06 21 | 89.70 284 | 89.67 279 | 89.78 303 | 93.19 309 | 76.56 322 | 97.00 272 | 98.35 157 | 80.97 319 | 81.57 316 | 97.75 173 | 74.75 309 | 98.61 202 | 89.85 250 | 93.63 211 | 94.17 311 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
OpenMVS_ROB | | 86.42 20 | 89.00 287 | 87.43 293 | 93.69 288 | 93.08 310 | 89.42 281 | 97.91 214 | 96.89 292 | 78.58 322 | 85.86 296 | 94.69 292 | 69.48 319 | 98.29 254 | 77.13 316 | 93.29 221 | 93.36 318 |
|
Test4 | | | 92.21 256 | 90.34 272 | 97.82 115 | 92.83 311 | 95.87 127 | 97.94 210 | 98.05 216 | 94.50 129 | 82.12 314 | 94.48 293 | 59.54 329 | 98.54 208 | 95.39 123 | 98.22 123 | 99.06 120 |
|
MIMVSNet1 | | | 89.67 285 | 88.28 290 | 93.82 287 | 92.81 312 | 91.08 262 | 98.01 203 | 97.45 254 | 87.95 291 | 87.90 288 | 95.87 278 | 67.63 323 | 94.56 319 | 78.73 314 | 88.18 275 | 95.83 283 |
|
UnsupCasMVSNet_bld | | | 87.17 293 | 85.12 296 | 93.31 292 | 91.94 313 | 88.77 289 | 94.92 314 | 98.30 163 | 84.30 311 | 82.30 313 | 90.04 321 | 63.96 327 | 97.25 289 | 85.85 296 | 74.47 327 | 93.93 316 |
|
testus | | | 88.91 288 | 89.08 283 | 88.40 306 | 91.39 314 | 76.05 323 | 96.56 292 | 96.48 304 | 89.38 283 | 89.39 280 | 95.17 288 | 70.94 317 | 93.56 323 | 77.04 317 | 95.41 188 | 95.61 288 |
|
Patchmatch-RL test | | | 91.49 270 | 90.85 262 | 93.41 290 | 91.37 315 | 84.40 309 | 92.81 324 | 95.93 312 | 91.87 227 | 87.25 289 | 94.87 290 | 88.99 145 | 96.53 309 | 92.54 200 | 82.00 306 | 99.30 94 |
|
pmmvs-eth3d | | | 90.36 281 | 89.05 284 | 94.32 283 | 91.10 316 | 92.12 245 | 97.63 241 | 96.95 288 | 88.86 287 | 84.91 310 | 93.13 303 | 78.32 292 | 96.74 303 | 88.70 273 | 81.81 308 | 94.09 313 |
|
PM-MVS | | | 87.77 292 | 86.55 294 | 91.40 301 | 91.03 317 | 83.36 313 | 96.92 275 | 95.18 318 | 91.28 247 | 86.48 294 | 93.42 299 | 53.27 330 | 96.74 303 | 89.43 261 | 81.97 307 | 94.11 312 |
|
new-patchmatchnet | | | 88.50 291 | 87.45 292 | 91.67 300 | 90.31 318 | 85.89 308 | 97.16 269 | 97.33 266 | 89.47 280 | 83.63 312 | 92.77 313 | 76.38 301 | 95.06 318 | 82.70 303 | 77.29 322 | 94.06 314 |
|
testing_2 | | | 90.61 280 | 88.50 287 | 96.95 162 | 90.08 319 | 95.57 134 | 97.69 235 | 98.06 213 | 93.02 186 | 76.55 321 | 92.48 317 | 61.18 328 | 98.44 229 | 95.45 122 | 91.98 233 | 96.84 217 |
|
test2356 | | | 88.68 290 | 88.61 286 | 88.87 305 | 89.90 320 | 78.23 320 | 95.11 310 | 96.66 302 | 88.66 289 | 89.06 282 | 94.33 297 | 73.14 315 | 92.56 327 | 75.56 320 | 95.11 190 | 95.81 284 |
|
Anonymous20231211 | | | 83.69 298 | 81.50 300 | 90.26 302 | 89.23 321 | 80.10 319 | 97.97 207 | 97.06 279 | 72.79 327 | 82.05 315 | 92.57 315 | 50.28 331 | 96.32 312 | 76.15 319 | 75.38 325 | 94.37 308 |
|
pmmvs3 | | | 86.67 295 | 84.86 297 | 92.11 299 | 88.16 322 | 87.19 306 | 96.63 289 | 94.75 322 | 79.88 321 | 87.22 290 | 92.75 314 | 66.56 324 | 95.20 317 | 81.24 307 | 76.56 324 | 93.96 315 |
|
1111 | | | 84.94 297 | 84.30 298 | 86.86 309 | 87.59 323 | 75.10 325 | 96.63 289 | 96.43 305 | 82.53 314 | 80.75 318 | 92.91 311 | 68.94 320 | 93.79 321 | 68.24 327 | 84.66 302 | 91.70 320 |
|
.test1245 | | | 73.05 306 | 76.31 304 | 63.27 327 | 87.59 323 | 75.10 325 | 96.63 289 | 96.43 305 | 82.53 314 | 80.75 318 | 92.91 311 | 68.94 320 | 93.79 321 | 68.24 327 | 12.72 339 | 20.91 337 |
|
test1235678 | | | 86.26 296 | 85.81 295 | 87.62 308 | 86.97 325 | 75.00 327 | 96.55 294 | 96.32 307 | 86.08 302 | 81.32 317 | 92.98 309 | 73.10 316 | 92.05 328 | 71.64 324 | 87.32 285 | 95.81 284 |
|
ambc | | | | | 89.49 304 | 86.66 326 | 75.78 324 | 92.66 325 | 96.72 297 | | 86.55 293 | 92.50 316 | 46.01 333 | 97.90 273 | 90.32 241 | 82.09 305 | 94.80 298 |
|
TDRefinement | | | 91.06 275 | 89.68 278 | 95.21 259 | 85.35 327 | 91.49 256 | 98.51 147 | 97.07 277 | 91.47 234 | 88.83 284 | 97.84 165 | 77.31 299 | 99.09 156 | 92.79 192 | 77.98 321 | 95.04 295 |
|
test12356 | | | 83.47 299 | 83.37 299 | 83.78 315 | 84.43 328 | 70.09 332 | 95.12 309 | 95.60 315 | 82.98 312 | 78.89 320 | 92.43 318 | 64.99 325 | 91.41 330 | 70.36 325 | 85.55 301 | 89.82 322 |
|
PMMVS2 | | | 77.95 303 | 75.44 306 | 85.46 312 | 82.54 329 | 74.95 328 | 94.23 321 | 93.08 331 | 72.80 326 | 74.68 323 | 87.38 323 | 36.36 338 | 91.56 329 | 73.95 322 | 63.94 329 | 89.87 321 |
|
E-PMN | | | 64.94 311 | 64.25 311 | 67.02 325 | 82.28 330 | 59.36 340 | 91.83 327 | 85.63 340 | 52.69 334 | 60.22 332 | 77.28 333 | 41.06 336 | 80.12 338 | 46.15 336 | 41.14 333 | 61.57 335 |
|
EMVS | | | 64.07 312 | 63.26 313 | 66.53 326 | 81.73 331 | 58.81 341 | 91.85 326 | 84.75 341 | 51.93 336 | 59.09 333 | 75.13 334 | 43.32 335 | 79.09 339 | 42.03 337 | 39.47 334 | 61.69 334 |
|
no-one | | | 74.41 305 | 70.76 307 | 85.35 313 | 79.88 332 | 76.83 321 | 94.68 317 | 94.22 327 | 80.33 320 | 63.81 330 | 79.73 331 | 35.45 339 | 93.36 324 | 71.78 323 | 36.99 336 | 85.86 327 |
|
FPMVS | | | 77.62 304 | 77.14 302 | 79.05 319 | 79.25 333 | 60.97 337 | 95.79 305 | 95.94 311 | 65.96 328 | 67.93 329 | 94.40 294 | 37.73 337 | 88.88 333 | 68.83 326 | 88.46 272 | 87.29 324 |
|
PNet_i23d | | | 67.70 309 | 65.07 310 | 75.60 321 | 78.61 334 | 59.61 339 | 89.14 329 | 88.24 338 | 61.83 330 | 52.37 334 | 80.89 329 | 18.91 342 | 84.91 335 | 62.70 332 | 52.93 331 | 82.28 329 |
|
wuyk23d | | | 30.17 316 | 30.18 318 | 30.16 329 | 78.61 334 | 43.29 343 | 66.79 336 | 14.21 345 | 17.31 338 | 14.82 341 | 11.93 342 | 11.55 345 | 41.43 341 | 37.08 338 | 19.30 338 | 5.76 339 |
|
testmv | | | 78.74 300 | 77.35 301 | 82.89 317 | 78.16 336 | 69.30 333 | 95.87 303 | 94.65 323 | 81.11 318 | 70.98 328 | 87.11 325 | 46.31 332 | 90.42 331 | 65.28 330 | 76.72 323 | 88.95 323 |
|
LCM-MVSNet | | | 78.70 301 | 76.24 305 | 86.08 311 | 77.26 337 | 71.99 330 | 94.34 320 | 96.72 297 | 61.62 331 | 76.53 322 | 89.33 322 | 33.91 340 | 92.78 326 | 81.85 305 | 74.60 326 | 93.46 317 |
|
MVE | | 62.14 22 | 63.28 314 | 59.38 314 | 74.99 322 | 74.33 338 | 65.47 335 | 85.55 332 | 80.50 343 | 52.02 335 | 51.10 335 | 75.00 335 | 10.91 347 | 80.50 337 | 51.60 335 | 53.40 330 | 78.99 331 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
wuykxyi23d | | | 63.73 313 | 58.86 315 | 78.35 320 | 67.62 339 | 67.90 334 | 86.56 331 | 87.81 339 | 58.26 332 | 42.49 338 | 70.28 336 | 11.55 345 | 85.05 334 | 63.66 331 | 41.50 332 | 82.11 330 |
|
ANet_high | | | 69.08 307 | 65.37 309 | 80.22 318 | 65.99 340 | 71.96 331 | 90.91 328 | 90.09 335 | 82.62 313 | 49.93 336 | 78.39 332 | 29.36 341 | 81.75 336 | 62.49 333 | 38.52 335 | 86.95 326 |
|
PMVS | | 61.03 23 | 65.95 310 | 63.57 312 | 73.09 324 | 57.90 341 | 51.22 342 | 85.05 333 | 93.93 330 | 54.45 333 | 44.32 337 | 83.57 326 | 13.22 343 | 89.15 332 | 58.68 334 | 81.00 310 | 78.91 332 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
tmp_tt | | | 68.90 308 | 66.97 308 | 74.68 323 | 50.78 342 | 59.95 338 | 87.13 330 | 83.47 342 | 38.80 337 | 62.21 331 | 96.23 267 | 64.70 326 | 76.91 340 | 88.91 270 | 30.49 337 | 87.19 325 |
|
testmvs | | | 21.48 318 | 24.95 319 | 11.09 331 | 14.89 343 | 6.47 345 | 96.56 292 | 9.87 346 | 7.55 339 | 17.93 339 | 39.02 338 | 9.43 348 | 5.90 343 | 16.56 340 | 12.72 339 | 20.91 337 |
|
test123 | | | 20.95 319 | 23.72 320 | 12.64 330 | 13.54 344 | 8.19 344 | 96.55 294 | 6.13 347 | 7.48 340 | 16.74 340 | 37.98 339 | 12.97 344 | 6.05 342 | 16.69 339 | 5.43 341 | 23.68 336 |
|
cdsmvs_eth3d_5k | | | 23.98 317 | 31.98 317 | 0.00 332 | 0.00 345 | 0.00 346 | 0.00 337 | 98.59 113 | 0.00 341 | 0.00 342 | 98.61 100 | 90.60 123 | 0.00 344 | 0.00 341 | 0.00 342 | 0.00 340 |
|
pcd_1.5k_mvsjas | | | 7.88 321 | 10.50 322 | 0.00 332 | 0.00 345 | 0.00 346 | 0.00 337 | 0.00 348 | 0.00 341 | 0.00 342 | 0.00 343 | 94.51 60 | 0.00 344 | 0.00 341 | 0.00 342 | 0.00 340 |
|
sosnet-low-res | | | 0.00 322 | 0.00 323 | 0.00 332 | 0.00 345 | 0.00 346 | 0.00 337 | 0.00 348 | 0.00 341 | 0.00 342 | 0.00 343 | 0.00 349 | 0.00 344 | 0.00 341 | 0.00 342 | 0.00 340 |
|
sosnet | | | 0.00 322 | 0.00 323 | 0.00 332 | 0.00 345 | 0.00 346 | 0.00 337 | 0.00 348 | 0.00 341 | 0.00 342 | 0.00 343 | 0.00 349 | 0.00 344 | 0.00 341 | 0.00 342 | 0.00 340 |
|
uncertanet | | | 0.00 322 | 0.00 323 | 0.00 332 | 0.00 345 | 0.00 346 | 0.00 337 | 0.00 348 | 0.00 341 | 0.00 342 | 0.00 343 | 0.00 349 | 0.00 344 | 0.00 341 | 0.00 342 | 0.00 340 |
|
Regformer | | | 0.00 322 | 0.00 323 | 0.00 332 | 0.00 345 | 0.00 346 | 0.00 337 | 0.00 348 | 0.00 341 | 0.00 342 | 0.00 343 | 0.00 349 | 0.00 344 | 0.00 341 | 0.00 342 | 0.00 340 |
|
ab-mvs-re | | | 8.20 320 | 10.94 321 | 0.00 332 | 0.00 345 | 0.00 346 | 0.00 337 | 0.00 348 | 0.00 341 | 0.00 342 | 98.43 115 | 0.00 349 | 0.00 344 | 0.00 341 | 0.00 342 | 0.00 340 |
|
uanet | | | 0.00 322 | 0.00 323 | 0.00 332 | 0.00 345 | 0.00 346 | 0.00 337 | 0.00 348 | 0.00 341 | 0.00 342 | 0.00 343 | 0.00 349 | 0.00 344 | 0.00 341 | 0.00 342 | 0.00 340 |
|
ESAPD | | | | | | | | | 98.84 53 | | | | | | | | |
|
sam_mvs1 | | | | | | | | | | | | | 89.45 134 | | | | |
|
sam_mvs | | | | | | | | | | | | | 88.99 145 | | | | |
|
MTGPA | | | | | | | | | 98.74 77 | | | | | | | | |
|
test_post1 | | | | | | | | 96.68 288 | | | | 30.43 341 | 87.85 192 | 98.69 196 | 92.59 197 | | |
|
test_post | | | | | | | | | | | | 31.83 340 | 88.83 157 | 98.91 178 | | | |
|
patchmatchnet-post | | | | | | | | | | | | 95.10 289 | 89.42 135 | 98.89 182 | | | |
|
MTMP | | | | | | | | | 94.14 328 | | | | | | | | |
|
test9_res | | | | | | | | | | | | | | | 96.39 94 | 99.57 55 | 99.69 35 |
|
agg_prior2 | | | | | | | | | | | | | | | 95.87 106 | 99.57 55 | 99.68 41 |
|
test_prior4 | | | | | | | 98.01 41 | 97.86 222 | | | | | | | | | |
|
test_prior2 | | | | | | | | 97.80 227 | | 96.12 63 | 97.89 75 | 98.69 92 | 95.96 25 | | 96.89 71 | 99.60 49 | |
|
旧先验2 | | | | | | | | 97.57 244 | | 91.30 245 | 98.67 36 | | | 99.80 57 | 95.70 115 | | |
|
新几何2 | | | | | | | | 97.64 239 | | | | | | | | | |
|
无先验 | | | | | | | | 97.58 243 | 98.72 84 | 91.38 239 | | | | 99.87 35 | 93.36 172 | | 99.60 59 |
|
原ACMM2 | | | | | | | | 97.67 237 | | | | | | | | | |
|
testdata2 | | | | | | | | | | | | | | 99.89 27 | 91.65 221 | | |
|
segment_acmp | | | | | | | | | | | | | 96.85 3 | | | | |
|
testdata1 | | | | | | | | 97.32 261 | | 96.34 57 | | | | | | | |
|
plane_prior5 | | | | | | | | | 98.56 120 | | | | | 99.03 164 | 96.07 97 | 94.27 193 | 96.92 204 |
|
plane_prior4 | | | | | | | | | | | | 98.28 131 | | | | | |
|
plane_prior3 | | | | | | | 94.61 194 | | | 97.02 39 | 95.34 153 | | | | | | |
|
plane_prior2 | | | | | | | | 98.80 90 | | 97.28 21 | | | | | | | |
|
plane_prior | | | | | | | 94.60 196 | 98.44 153 | | 96.74 46 | | | | | | 94.22 195 | |
|
n2 | | | | | | | | | 0.00 348 | | | | | | | | |
|
nn | | | | | | | | | 0.00 348 | | | | | | | | |
|
door-mid | | | | | | | | | 94.37 325 | | | | | | | | |
|
test11 | | | | | | | | | 98.66 105 | | | | | | | | |
|
door | | | | | | | | | 94.64 324 | | | | | | | | |
|
HQP5-MVS | | | | | | | 94.25 209 | | | | | | | | | | |
|
BP-MVS | | | | | | | | | | | | | | | 95.30 125 | | |
|
HQP4-MVS | | | | | | | | | | | 94.45 174 | | | 98.96 171 | | | 96.87 214 |
|
HQP3-MVS | | | | | | | | | 98.46 140 | | | | | | | 94.18 197 | |
|
HQP2-MVS | | | | | | | | | | | | | 86.75 213 | | | | |
|
MDTV_nov1_ep13_2view | | | | | | | 84.26 310 | 96.89 281 | | 90.97 252 | 97.90 74 | | 89.89 132 | | 93.91 159 | | 99.18 108 |
|
ACMMP++_ref | | | | | | | | | | | | | | | | 92.97 224 | |
|
ACMMP++ | | | | | | | | | | | | | | | | 93.61 212 | |
|
Test By Simon | | | | | | | | | | | | | 94.64 57 | | | | |
|