LCM-MVSNet | | | 99.86 1 | 99.86 1 | 99.87 1 | 99.99 1 | 99.77 1 | 99.77 1 | 99.80 1 | 99.97 1 | 99.97 1 | 99.95 1 | 99.74 1 | 99.98 1 | 99.56 1 | 100.00 1 | 99.85 4 |
|
Anonymous20231211 | | | 99.29 2 | 99.41 2 | 98.91 22 | 99.94 2 | 97.08 37 | 99.47 3 | 99.51 5 | 99.56 2 | 99.83 3 | 99.80 2 | 99.13 3 | 99.90 13 | 97.55 49 | 99.93 21 | 99.75 13 |
|
LTVRE_ROB | | 96.88 1 | 99.18 3 | 99.34 3 | 98.72 35 | 99.71 7 | 96.99 40 | 99.69 2 | 99.57 3 | 99.02 14 | 99.62 10 | 99.36 16 | 98.53 8 | 99.52 155 | 98.58 24 | 99.95 13 | 99.66 23 |
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 |
pmmvs6 | | | 99.07 4 | 99.24 4 | 98.56 44 | 99.81 3 | 96.38 56 | 98.87 9 | 99.30 9 | 99.01 15 | 99.63 9 | 99.66 4 | 99.27 2 | 99.68 99 | 97.75 41 | 99.89 33 | 99.62 31 |
|
mvs_tets | | | 98.90 5 | 98.94 8 | 98.75 30 | 99.69 8 | 96.48 54 | 98.54 20 | 99.22 10 | 96.23 99 | 99.71 5 | 99.48 7 | 98.77 7 | 99.93 2 | 98.89 10 | 99.95 13 | 99.84 6 |
|
TDRefinement | | | 98.90 5 | 98.86 11 | 99.02 8 | 99.54 23 | 98.06 6 | 99.34 5 | 99.44 7 | 98.85 19 | 99.00 39 | 99.20 31 | 97.42 31 | 99.59 136 | 97.21 62 | 99.76 49 | 99.40 90 |
|
UA-Net | | | 98.88 7 | 98.76 16 | 99.22 2 | 99.11 76 | 97.89 10 | 99.47 3 | 99.32 8 | 99.08 9 | 97.87 133 | 99.67 3 | 96.47 70 | 99.92 4 | 97.88 34 | 99.98 3 | 99.85 4 |
|
v52 | | | 98.85 8 | 99.01 5 | 98.37 54 | 99.61 15 | 95.53 80 | 99.01 7 | 99.04 45 | 98.48 26 | 99.31 22 | 99.41 11 | 96.82 56 | 99.87 21 | 99.44 2 | 99.95 13 | 99.70 19 |
|
V4 | | | 98.85 8 | 99.01 5 | 98.37 54 | 99.61 15 | 95.53 80 | 99.01 7 | 99.04 45 | 98.48 26 | 99.31 22 | 99.41 11 | 96.81 57 | 99.87 21 | 99.44 2 | 99.95 13 | 99.70 19 |
|
DTE-MVSNet | | | 98.79 10 | 98.86 11 | 98.59 42 | 99.55 21 | 96.12 63 | 98.48 24 | 99.10 25 | 99.36 3 | 99.29 25 | 99.06 47 | 97.27 37 | 99.93 2 | 97.71 43 | 99.91 27 | 99.70 19 |
|
jajsoiax | | | 98.77 11 | 98.79 15 | 98.74 32 | 99.66 10 | 96.48 54 | 98.45 25 | 99.12 22 | 95.83 114 | 99.67 7 | 99.37 14 | 98.25 11 | 99.92 4 | 98.77 14 | 99.94 19 | 99.82 7 |
|
PEN-MVS | | | 98.75 12 | 98.85 13 | 98.44 49 | 99.58 18 | 95.67 74 | 98.45 25 | 99.15 19 | 99.33 4 | 99.30 24 | 99.00 48 | 97.27 37 | 99.92 4 | 97.64 44 | 99.92 24 | 99.75 13 |
|
v7n | | | 98.73 13 | 98.99 7 | 97.95 80 | 99.64 12 | 94.20 123 | 98.67 12 | 99.14 20 | 99.08 9 | 99.42 16 | 99.23 29 | 96.53 65 | 99.91 12 | 99.27 4 | 99.93 21 | 99.73 16 |
|
PS-CasMVS | | | 98.73 13 | 98.85 13 | 98.39 53 | 99.55 21 | 95.47 82 | 98.49 22 | 99.13 21 | 99.22 7 | 99.22 28 | 98.96 52 | 97.35 33 | 99.92 4 | 97.79 39 | 99.93 21 | 99.79 8 |
|
test_djsdf | | | 98.73 13 | 98.74 18 | 98.69 37 | 99.63 13 | 96.30 59 | 98.67 12 | 99.02 50 | 96.50 90 | 99.32 21 | 99.44 10 | 97.43 30 | 99.92 4 | 98.73 17 | 99.95 13 | 99.86 3 |
|
anonymousdsp | | | 98.72 16 | 98.63 21 | 98.99 10 | 99.62 14 | 97.29 34 | 98.65 15 | 99.19 14 | 95.62 120 | 99.35 20 | 99.37 14 | 97.38 32 | 99.90 13 | 98.59 23 | 99.91 27 | 99.77 9 |
|
wuykxyi23d | | | 98.68 17 | 98.53 26 | 99.13 3 | 99.44 34 | 97.97 7 | 96.85 105 | 99.02 50 | 95.81 115 | 99.88 2 | 99.38 13 | 98.14 14 | 99.69 94 | 98.32 28 | 99.95 13 | 99.73 16 |
|
WR-MVS_H | | | 98.65 18 | 98.62 23 | 98.75 30 | 99.51 26 | 96.61 50 | 98.55 19 | 99.17 15 | 99.05 12 | 99.17 31 | 98.79 60 | 95.47 101 | 99.89 17 | 97.95 32 | 99.91 27 | 99.75 13 |
|
OurMVSNet-221017-0 | | | 98.61 19 | 98.61 25 | 98.63 41 | 99.77 4 | 96.35 57 | 99.17 6 | 99.05 38 | 98.05 40 | 99.61 11 | 99.52 5 | 93.72 160 | 99.88 19 | 98.72 20 | 99.88 34 | 99.65 24 |
|
v748 | | | 98.58 20 | 98.89 10 | 97.67 97 | 99.61 15 | 93.53 146 | 98.59 16 | 98.90 74 | 98.97 17 | 99.43 15 | 99.15 40 | 96.53 65 | 99.85 24 | 98.88 11 | 99.91 27 | 99.64 27 |
|
nrg030 | | | 98.54 21 | 98.62 23 | 98.32 59 | 99.22 55 | 95.66 75 | 97.90 56 | 99.08 30 | 98.31 32 | 99.02 36 | 98.74 65 | 97.68 24 | 99.61 129 | 97.77 40 | 99.85 39 | 99.70 19 |
|
PS-MVSNAJss | | | 98.53 22 | 98.63 21 | 98.21 67 | 99.68 9 | 94.82 102 | 98.10 44 | 99.21 11 | 96.91 82 | 99.75 4 | 99.45 9 | 95.82 87 | 99.92 4 | 98.80 13 | 99.96 11 | 99.89 1 |
|
MIMVSNet1 | | | 98.51 23 | 98.45 31 | 98.67 38 | 99.72 6 | 96.71 46 | 98.76 10 | 98.89 76 | 98.49 25 | 99.38 18 | 99.14 41 | 95.44 103 | 99.84 28 | 96.47 81 | 99.80 45 | 99.47 64 |
|
pm-mvs1 | | | 98.47 24 | 98.67 19 | 97.86 84 | 99.52 25 | 94.58 110 | 98.28 31 | 99.00 61 | 97.57 62 | 99.27 26 | 99.22 30 | 98.32 10 | 99.50 160 | 97.09 68 | 99.75 53 | 99.50 50 |
|
ACMH | | 93.61 9 | 98.44 25 | 98.76 16 | 97.51 107 | 99.43 37 | 93.54 145 | 98.23 34 | 99.05 38 | 97.40 74 | 99.37 19 | 99.08 46 | 98.79 6 | 99.47 166 | 97.74 42 | 99.71 62 | 99.50 50 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
CP-MVSNet | | | 98.42 26 | 98.46 29 | 98.30 62 | 99.46 32 | 95.22 90 | 98.27 33 | 98.84 86 | 99.05 12 | 99.01 37 | 98.65 72 | 95.37 104 | 99.90 13 | 97.57 48 | 99.91 27 | 99.77 9 |
|
abl_6 | | | 98.42 26 | 98.19 41 | 99.09 4 | 99.16 63 | 98.10 5 | 97.73 68 | 99.11 23 | 97.76 49 | 98.62 55 | 98.27 102 | 97.88 21 | 99.80 37 | 95.67 104 | 99.50 109 | 99.38 95 |
|
TransMVSNet (Re) | | | 98.38 28 | 98.67 19 | 97.51 107 | 99.51 26 | 93.39 150 | 98.20 39 | 98.87 80 | 98.23 34 | 99.48 12 | 99.27 25 | 98.47 9 | 99.55 147 | 96.52 78 | 99.53 102 | 99.60 34 |
|
TranMVSNet+NR-MVSNet | | | 98.33 29 | 98.30 39 | 98.43 50 | 99.07 80 | 95.87 67 | 96.73 109 | 99.05 38 | 98.67 21 | 98.84 44 | 98.45 85 | 97.58 27 | 99.88 19 | 96.45 82 | 99.86 38 | 99.54 45 |
|
HPM-MVS_fast | | | 98.32 30 | 98.13 44 | 98.88 23 | 99.54 23 | 97.48 27 | 98.35 28 | 99.03 49 | 95.88 111 | 97.88 128 | 98.22 107 | 98.15 13 | 99.74 57 | 96.50 80 | 99.62 79 | 99.42 85 |
|
ANet_high | | | 98.31 31 | 98.94 8 | 96.41 172 | 99.33 47 | 89.64 208 | 97.92 55 | 99.56 4 | 99.27 5 | 99.66 8 | 99.50 6 | 97.67 25 | 99.83 30 | 97.55 49 | 99.98 3 | 99.77 9 |
|
VPA-MVSNet | | | 98.27 32 | 98.46 29 | 97.70 93 | 99.06 81 | 93.80 135 | 97.76 63 | 99.00 61 | 98.40 29 | 99.07 34 | 98.98 50 | 96.89 50 | 99.75 52 | 97.19 65 | 99.79 46 | 99.55 44 |
|
Vis-MVSNet | | | 98.27 32 | 98.34 35 | 98.07 72 | 99.33 47 | 95.21 92 | 98.04 48 | 99.46 6 | 97.32 77 | 97.82 137 | 99.11 43 | 96.75 59 | 99.86 23 | 97.84 36 | 99.36 149 | 99.15 131 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
COLMAP_ROB | | 94.48 6 | 98.25 34 | 98.11 45 | 98.64 40 | 99.21 58 | 97.35 32 | 97.96 52 | 99.16 16 | 98.34 31 | 98.78 47 | 98.52 80 | 97.32 34 | 99.45 174 | 94.08 168 | 99.67 72 | 99.13 134 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
ACMH+ | | 93.58 10 | 98.23 35 | 98.31 37 | 97.98 79 | 99.39 42 | 95.22 90 | 97.55 80 | 99.20 13 | 98.21 35 | 99.25 27 | 98.51 81 | 98.21 12 | 99.40 188 | 94.79 142 | 99.72 58 | 99.32 104 |
|
FC-MVSNet-test | | | 98.16 36 | 98.37 33 | 97.56 102 | 99.49 30 | 93.10 154 | 98.35 28 | 99.21 11 | 98.43 28 | 98.89 43 | 98.83 59 | 94.30 139 | 99.81 33 | 97.87 35 | 99.91 27 | 99.77 9 |
|
MTAPA | | | 98.14 37 | 97.84 56 | 99.06 5 | 99.44 34 | 97.90 8 | 97.25 91 | 98.73 109 | 97.69 56 | 97.90 124 | 97.96 136 | 95.81 91 | 99.82 31 | 96.13 88 | 99.61 83 | 99.45 71 |
|
APDe-MVS | | | 98.14 37 | 98.03 50 | 98.47 48 | 98.72 107 | 96.04 64 | 98.07 46 | 99.10 25 | 95.96 108 | 98.59 59 | 98.69 69 | 96.94 48 | 99.81 33 | 96.64 74 | 99.58 89 | 99.57 40 |
|
APD-MVS_3200maxsize | | | 98.13 39 | 97.90 53 | 98.79 28 | 98.79 100 | 97.31 33 | 97.55 80 | 98.92 72 | 97.72 54 | 98.25 87 | 98.13 119 | 97.10 43 | 99.75 52 | 95.44 116 | 99.24 170 | 99.32 104 |
|
HPM-MVS | | | 98.11 40 | 97.83 57 | 98.92 19 | 99.42 39 | 97.46 28 | 98.57 17 | 99.05 38 | 95.43 129 | 97.41 152 | 97.50 175 | 97.98 17 | 99.79 38 | 95.58 113 | 99.57 92 | 99.50 50 |
|
Gipuma | | | 98.07 41 | 98.31 37 | 97.36 124 | 99.76 5 | 96.28 60 | 98.51 21 | 99.10 25 | 98.76 20 | 96.79 175 | 99.34 20 | 96.61 62 | 98.82 266 | 96.38 83 | 99.50 109 | 96.98 276 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
ACMMP | | | 98.05 42 | 97.75 62 | 98.93 18 | 99.23 54 | 97.60 19 | 98.09 45 | 98.96 69 | 95.75 117 | 97.91 123 | 98.06 128 | 96.89 50 | 99.76 48 | 95.32 121 | 99.57 92 | 99.43 83 |
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 |
ACMM | | 93.33 11 | 98.05 42 | 97.79 58 | 98.85 24 | 99.15 66 | 97.55 23 | 96.68 111 | 98.83 92 | 95.21 137 | 98.36 75 | 98.13 119 | 98.13 16 | 99.62 123 | 96.04 92 | 99.54 100 | 99.39 93 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
v13 | | | 98.02 44 | 98.52 27 | 96.51 166 | 99.02 85 | 90.14 200 | 98.07 46 | 99.09 29 | 98.10 39 | 99.13 32 | 99.35 18 | 94.84 118 | 99.74 57 | 99.12 5 | 99.98 3 | 99.65 24 |
|
SteuartSystems-ACMMP | | | 98.02 44 | 97.76 61 | 98.79 28 | 99.43 37 | 97.21 36 | 97.15 95 | 98.90 74 | 96.58 89 | 98.08 105 | 97.87 147 | 97.02 47 | 99.76 48 | 95.25 123 | 99.59 87 | 99.40 90 |
Skip Steuart: Steuart Systems R&D Blog. |
MPTG | | | 98.01 46 | 97.66 68 | 99.06 5 | 99.44 34 | 97.90 8 | 95.66 157 | 98.73 109 | 97.69 56 | 97.90 124 | 97.96 136 | 95.81 91 | 99.82 31 | 96.13 88 | 99.61 83 | 99.45 71 |
|
v12 | | | 97.97 47 | 98.47 28 | 96.46 169 | 98.98 89 | 90.01 204 | 97.97 51 | 99.08 30 | 98.00 42 | 99.11 33 | 99.34 20 | 94.70 121 | 99.73 62 | 99.07 6 | 99.98 3 | 99.64 27 |
|
XVS | | | 97.96 48 | 97.63 73 | 98.94 15 | 99.15 66 | 97.66 16 | 97.77 61 | 98.83 92 | 97.42 70 | 96.32 192 | 97.64 165 | 96.49 68 | 99.72 67 | 95.66 106 | 99.37 146 | 99.45 71 |
|
NR-MVSNet | | | 97.96 48 | 97.86 55 | 98.26 64 | 98.73 105 | 95.54 78 | 98.14 42 | 98.73 109 | 97.79 47 | 99.42 16 | 97.83 148 | 94.40 136 | 99.78 39 | 95.91 100 | 99.76 49 | 99.46 66 |
|
ACMMPR | | | 97.95 50 | 97.62 75 | 98.94 15 | 99.20 59 | 97.56 22 | 97.59 77 | 98.83 92 | 96.05 102 | 97.46 150 | 97.63 166 | 96.77 58 | 99.76 48 | 95.61 110 | 99.46 122 | 99.49 58 |
|
FMVSNet1 | | | 97.95 50 | 98.08 46 | 97.56 102 | 99.14 74 | 93.67 139 | 98.23 34 | 98.66 126 | 97.41 73 | 99.00 39 | 99.19 32 | 95.47 101 | 99.73 62 | 95.83 101 | 99.76 49 | 99.30 108 |
|
HFP-MVS | | | 97.94 52 | 97.64 71 | 98.83 25 | 99.15 66 | 97.50 25 | 97.59 77 | 98.84 86 | 96.05 102 | 97.49 145 | 97.54 170 | 97.07 45 | 99.70 84 | 95.61 110 | 99.46 122 | 99.30 108 |
|
LPG-MVS_test | | | 97.94 52 | 97.67 67 | 98.74 32 | 99.15 66 | 97.02 38 | 97.09 99 | 99.02 50 | 95.15 141 | 98.34 77 | 98.23 104 | 97.91 19 | 99.70 84 | 94.41 154 | 99.73 55 | 99.50 50 |
|
FIs | | | 97.93 54 | 98.07 47 | 97.48 114 | 99.38 43 | 92.95 156 | 98.03 50 | 99.11 23 | 98.04 41 | 98.62 55 | 98.66 71 | 93.75 159 | 99.78 39 | 97.23 61 | 99.84 40 | 99.73 16 |
|
region2R | | | 97.92 55 | 97.59 77 | 98.92 19 | 99.22 55 | 97.55 23 | 97.60 76 | 98.84 86 | 96.00 106 | 97.22 157 | 97.62 167 | 96.87 53 | 99.76 48 | 95.48 114 | 99.43 134 | 99.46 66 |
|
CP-MVS | | | 97.92 55 | 97.56 80 | 98.99 10 | 98.99 87 | 97.82 12 | 97.93 54 | 98.96 69 | 96.11 101 | 96.89 173 | 97.45 178 | 96.85 54 | 99.78 39 | 95.19 126 | 99.63 78 | 99.38 95 |
|
mPP-MVS | | | 97.91 57 | 97.53 81 | 99.04 7 | 99.22 55 | 97.87 11 | 97.74 66 | 98.78 101 | 96.04 104 | 97.10 163 | 97.73 160 | 96.53 65 | 99.78 39 | 95.16 129 | 99.50 109 | 99.46 66 |
|
V9 | | | 97.90 58 | 98.40 32 | 96.40 173 | 98.93 91 | 89.86 206 | 97.86 58 | 99.07 34 | 97.88 46 | 99.05 35 | 99.30 23 | 94.53 132 | 99.72 67 | 99.01 8 | 99.98 3 | 99.63 29 |
|
ACMMP_Plus | | | 97.89 59 | 97.63 73 | 98.67 38 | 99.35 46 | 96.84 43 | 96.36 118 | 98.79 98 | 95.07 147 | 97.88 128 | 98.35 91 | 97.24 40 | 99.72 67 | 96.05 91 | 99.58 89 | 99.45 71 |
|
PGM-MVS | | | 97.88 60 | 97.52 82 | 98.96 13 | 99.20 59 | 97.62 18 | 97.09 99 | 99.06 36 | 95.45 127 | 97.55 141 | 97.94 140 | 97.11 42 | 99.78 39 | 94.77 144 | 99.46 122 | 99.48 61 |
|
DP-MVS | | | 97.87 61 | 97.89 54 | 97.81 87 | 98.62 123 | 94.82 102 | 97.13 98 | 98.79 98 | 98.98 16 | 98.74 50 | 98.49 82 | 95.80 93 | 99.49 162 | 95.04 135 | 99.44 127 | 99.11 142 |
|
RPSCF | | | 97.87 61 | 97.51 83 | 98.95 14 | 99.15 66 | 98.43 3 | 97.56 79 | 99.06 36 | 96.19 100 | 98.48 67 | 98.70 68 | 94.72 120 | 99.24 220 | 94.37 157 | 99.33 159 | 99.17 127 |
|
test_0402 | | | 97.84 63 | 97.97 51 | 97.47 115 | 99.19 61 | 94.07 126 | 96.71 110 | 98.73 109 | 98.66 22 | 98.56 61 | 98.41 87 | 96.84 55 | 99.69 94 | 94.82 139 | 99.81 43 | 98.64 194 |
|
V14 | | | 97.83 64 | 98.33 36 | 96.35 174 | 98.88 97 | 89.72 207 | 97.75 64 | 99.05 38 | 97.74 50 | 99.01 37 | 99.27 25 | 94.35 137 | 99.71 77 | 98.95 9 | 99.97 8 | 99.62 31 |
|
UniMVSNet_NR-MVSNet | | | 97.83 64 | 97.65 69 | 98.37 54 | 98.72 107 | 95.78 69 | 95.66 157 | 99.02 50 | 98.11 38 | 98.31 82 | 97.69 164 | 94.65 126 | 99.85 24 | 97.02 70 | 99.71 62 | 99.48 61 |
|
UniMVSNet (Re) | | | 97.83 64 | 97.65 69 | 98.35 58 | 98.80 99 | 95.86 68 | 95.92 147 | 99.04 45 | 97.51 67 | 98.22 89 | 97.81 152 | 94.68 124 | 99.78 39 | 97.14 67 | 99.75 53 | 99.41 87 |
|
v11 | | | 97.82 67 | 98.36 34 | 96.17 191 | 98.93 91 | 89.16 226 | 97.79 60 | 99.08 30 | 97.64 59 | 99.19 29 | 99.32 22 | 94.28 140 | 99.72 67 | 99.07 6 | 99.97 8 | 99.63 29 |
|
DeepC-MVS | | 95.41 4 | 97.82 67 | 97.70 64 | 98.16 68 | 98.78 101 | 95.72 71 | 96.23 126 | 99.02 50 | 93.92 181 | 98.62 55 | 98.99 49 | 97.69 23 | 99.62 123 | 96.18 87 | 99.87 36 | 99.15 131 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
DU-MVS | | | 97.79 69 | 97.60 76 | 98.36 57 | 98.73 105 | 95.78 69 | 95.65 159 | 98.87 80 | 97.57 62 | 98.31 82 | 97.83 148 | 94.69 122 | 99.85 24 | 97.02 70 | 99.71 62 | 99.46 66 |
|
v15 | | | 97.77 70 | 98.26 40 | 96.30 180 | 98.81 98 | 89.59 213 | 97.62 73 | 99.04 45 | 97.59 61 | 98.97 41 | 99.24 27 | 94.19 144 | 99.70 84 | 98.88 11 | 99.97 8 | 99.61 33 |
|
LS3D | | | 97.77 70 | 97.50 84 | 98.57 43 | 96.24 275 | 97.58 21 | 98.45 25 | 98.85 83 | 98.58 24 | 97.51 143 | 97.94 140 | 95.74 94 | 99.63 117 | 95.19 126 | 98.97 196 | 98.51 205 |
|
3Dnovator+ | | 96.13 3 | 97.73 72 | 97.59 77 | 98.15 69 | 98.11 178 | 95.60 76 | 98.04 48 | 98.70 118 | 98.13 37 | 96.93 171 | 98.45 85 | 95.30 108 | 99.62 123 | 95.64 108 | 98.96 197 | 99.24 120 |
|
Baseline_NR-MVSNet | | | 97.72 73 | 97.79 58 | 97.50 110 | 99.56 19 | 93.29 151 | 95.44 166 | 98.86 82 | 98.20 36 | 98.37 74 | 99.24 27 | 94.69 122 | 99.55 147 | 95.98 97 | 99.79 46 | 99.65 24 |
|
v17 | | | 97.70 74 | 98.17 42 | 96.28 183 | 98.77 102 | 89.59 213 | 97.62 73 | 99.01 59 | 97.54 64 | 98.72 52 | 99.18 35 | 94.06 148 | 99.68 99 | 98.74 16 | 99.92 24 | 99.58 36 |
|
MP-MVS-pluss | | | 97.69 75 | 97.36 89 | 98.70 36 | 99.50 29 | 96.84 43 | 95.38 175 | 98.99 64 | 92.45 214 | 98.11 99 | 98.31 95 | 97.25 39 | 99.77 47 | 96.60 75 | 99.62 79 | 99.48 61 |
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
v16 | | | 97.69 75 | 98.16 43 | 96.29 182 | 98.75 103 | 89.60 211 | 97.62 73 | 99.01 59 | 97.53 66 | 98.69 54 | 99.18 35 | 94.05 149 | 99.68 99 | 98.73 17 | 99.88 34 | 99.58 36 |
|
EG-PatchMatch MVS | | | 97.69 75 | 97.79 58 | 97.40 122 | 99.06 81 | 93.52 147 | 95.96 143 | 98.97 68 | 94.55 162 | 98.82 45 | 98.76 63 | 97.31 35 | 99.29 214 | 97.20 64 | 99.44 127 | 99.38 95 |
|
MP-MVS | | | 97.64 78 | 97.18 104 | 99.00 9 | 99.32 49 | 97.77 14 | 97.49 83 | 98.73 109 | 96.27 98 | 95.59 218 | 97.75 157 | 96.30 75 | 99.78 39 | 93.70 178 | 99.48 119 | 99.45 71 |
|
#test# | | | 97.62 79 | 97.22 102 | 98.83 25 | 99.15 66 | 97.50 25 | 96.81 107 | 98.84 86 | 94.25 172 | 97.49 145 | 97.54 170 | 97.07 45 | 99.70 84 | 94.37 157 | 99.46 122 | 99.30 108 |
|
3Dnovator | | 96.53 2 | 97.61 80 | 97.64 71 | 97.50 110 | 97.74 217 | 93.65 143 | 98.49 22 | 98.88 78 | 96.86 83 | 97.11 162 | 98.55 78 | 95.82 87 | 99.73 62 | 95.94 98 | 99.42 137 | 99.13 134 |
|
v18 | | | 97.60 81 | 98.06 48 | 96.23 184 | 98.68 117 | 89.46 216 | 97.48 84 | 98.98 66 | 97.33 76 | 98.60 58 | 99.13 42 | 93.86 152 | 99.67 105 | 98.62 21 | 99.87 36 | 99.56 41 |
|
v8 | | | 97.60 81 | 98.06 48 | 96.23 184 | 98.71 110 | 89.44 217 | 97.43 86 | 98.82 96 | 97.29 78 | 98.74 50 | 99.10 44 | 93.86 152 | 99.68 99 | 98.61 22 | 99.94 19 | 99.56 41 |
|
XVG-ACMP-BASELINE | | | 97.58 83 | 97.28 94 | 98.49 46 | 99.16 63 | 96.90 42 | 96.39 116 | 98.98 66 | 95.05 148 | 98.06 106 | 98.02 131 | 95.86 83 | 99.56 143 | 94.37 157 | 99.64 77 | 99.00 155 |
|
v10 | | | 97.55 84 | 97.97 51 | 96.31 178 | 98.60 125 | 89.64 208 | 97.44 85 | 99.02 50 | 96.60 87 | 98.72 52 | 99.16 39 | 93.48 164 | 99.72 67 | 98.76 15 | 99.92 24 | 99.58 36 |
|
OPM-MVS | | | 97.54 85 | 97.25 95 | 98.41 51 | 99.11 76 | 96.61 50 | 95.24 187 | 98.46 148 | 94.58 161 | 98.10 102 | 98.07 125 | 97.09 44 | 99.39 194 | 95.16 129 | 99.44 127 | 99.21 122 |
|
XXY-MVS | | | 97.54 85 | 97.70 64 | 97.07 138 | 99.46 32 | 92.21 166 | 97.22 94 | 99.00 61 | 94.93 151 | 98.58 60 | 98.92 56 | 97.31 35 | 99.41 185 | 94.44 152 | 99.43 134 | 99.59 35 |
|
Regformer-4 | | | 97.53 87 | 97.47 86 | 97.71 92 | 97.35 243 | 93.91 131 | 95.26 185 | 98.14 193 | 97.97 43 | 98.34 77 | 97.89 145 | 95.49 99 | 99.71 77 | 97.41 57 | 99.42 137 | 99.51 49 |
|
SixPastTwentyTwo | | | 97.49 88 | 97.57 79 | 97.26 130 | 99.56 19 | 92.33 163 | 98.28 31 | 96.97 252 | 98.30 33 | 99.45 14 | 99.35 18 | 88.43 248 | 99.89 17 | 98.01 31 | 99.76 49 | 99.54 45 |
|
ACMP | | 92.54 13 | 97.47 89 | 97.10 111 | 98.55 45 | 99.04 84 | 96.70 47 | 96.24 125 | 98.89 76 | 93.71 185 | 97.97 115 | 97.75 157 | 97.44 29 | 99.63 117 | 93.22 185 | 99.70 65 | 99.32 104 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
testing_2 | | | 97.43 90 | 97.71 63 | 96.60 159 | 98.91 94 | 90.85 190 | 96.01 136 | 98.54 140 | 94.78 154 | 98.78 47 | 98.96 52 | 96.35 74 | 99.54 149 | 97.25 60 | 99.82 42 | 99.40 90 |
|
TSAR-MVS + MP. | | | 97.42 91 | 97.23 101 | 98.00 78 | 99.38 43 | 95.00 96 | 97.63 72 | 98.20 184 | 93.00 200 | 98.16 94 | 98.06 128 | 95.89 82 | 99.72 67 | 95.67 104 | 99.10 183 | 99.28 115 |
|
Regformer-2 | | | 97.41 92 | 97.24 97 | 97.93 81 | 97.21 252 | 94.72 105 | 94.85 208 | 98.27 176 | 97.74 50 | 98.11 99 | 97.50 175 | 95.58 97 | 99.69 94 | 96.57 77 | 99.31 161 | 99.37 100 |
|
CSCG | | | 97.40 93 | 97.30 91 | 97.69 95 | 98.95 90 | 94.83 101 | 97.28 90 | 98.99 64 | 96.35 97 | 98.13 98 | 95.95 259 | 95.99 80 | 99.66 110 | 94.36 160 | 99.73 55 | 98.59 199 |
|
XVG-OURS-SEG-HR | | | 97.38 94 | 97.07 114 | 98.30 62 | 99.01 86 | 97.41 31 | 94.66 213 | 99.02 50 | 95.20 138 | 98.15 96 | 97.52 173 | 98.83 5 | 98.43 294 | 94.87 137 | 96.41 288 | 99.07 149 |
|
HSP-MVS | | | 97.37 95 | 96.85 124 | 98.92 19 | 99.26 51 | 97.70 15 | 97.66 69 | 98.23 180 | 95.65 118 | 98.51 64 | 96.46 235 | 92.15 199 | 99.81 33 | 95.14 131 | 98.58 232 | 99.26 119 |
|
VDD-MVS | | | 97.37 95 | 97.25 95 | 97.74 91 | 98.69 116 | 94.50 113 | 97.04 101 | 95.61 279 | 98.59 23 | 98.51 64 | 98.72 66 | 92.54 191 | 99.58 138 | 96.02 94 | 99.49 116 | 99.12 139 |
|
SD-MVS | | | 97.37 95 | 97.70 64 | 96.35 174 | 98.14 174 | 95.13 93 | 96.54 112 | 98.92 72 | 95.94 109 | 99.19 29 | 98.08 124 | 97.74 22 | 95.06 326 | 95.24 124 | 99.54 100 | 98.87 176 |
|
PM-MVS | | | 97.36 98 | 97.10 111 | 98.14 70 | 98.91 94 | 96.77 45 | 96.20 127 | 98.63 133 | 93.82 182 | 98.54 62 | 98.33 93 | 93.98 150 | 99.05 238 | 95.99 96 | 99.45 126 | 98.61 197 |
|
LCM-MVSNet-Re | | | 97.33 99 | 97.33 90 | 97.32 126 | 98.13 177 | 93.79 136 | 96.99 103 | 99.65 2 | 96.74 85 | 99.47 13 | 98.93 55 | 96.91 49 | 99.84 28 | 90.11 243 | 99.06 189 | 98.32 222 |
|
EI-MVSNet-UG-set | | | 97.32 100 | 97.40 87 | 97.09 137 | 97.34 246 | 92.01 174 | 95.33 179 | 97.65 225 | 97.74 50 | 98.30 84 | 98.14 118 | 95.04 114 | 99.69 94 | 97.55 49 | 99.52 106 | 99.58 36 |
|
EI-MVSNet-Vis-set | | | 97.32 100 | 97.39 88 | 97.11 135 | 97.36 242 | 92.08 172 | 95.34 178 | 97.65 225 | 97.74 50 | 98.29 85 | 98.11 122 | 95.05 112 | 99.68 99 | 97.50 53 | 99.50 109 | 99.56 41 |
|
Regformer-1 | | | 97.27 102 | 97.16 106 | 97.61 100 | 97.21 252 | 93.86 133 | 94.85 208 | 98.04 204 | 97.62 60 | 98.03 109 | 97.50 175 | 95.34 105 | 99.63 117 | 96.52 78 | 99.31 161 | 99.35 102 |
|
VPNet | | | 97.26 103 | 97.49 85 | 96.59 161 | 99.47 31 | 90.58 195 | 96.27 122 | 98.53 141 | 97.77 48 | 98.46 69 | 98.41 87 | 94.59 128 | 99.68 99 | 94.61 148 | 99.29 165 | 99.52 48 |
|
Regformer-3 | | | 97.25 104 | 97.29 92 | 97.11 135 | 97.35 243 | 92.32 164 | 95.26 185 | 97.62 230 | 97.67 58 | 98.17 93 | 97.89 145 | 95.05 112 | 99.56 143 | 97.16 66 | 99.42 137 | 99.46 66 |
|
canonicalmvs | | | 97.23 105 | 97.21 103 | 97.30 127 | 97.65 225 | 94.39 115 | 97.84 59 | 99.05 38 | 97.42 70 | 96.68 178 | 93.85 296 | 97.63 26 | 99.33 208 | 96.29 85 | 98.47 237 | 98.18 238 |
|
AllTest | | | 97.20 106 | 96.92 122 | 98.06 73 | 99.08 78 | 96.16 61 | 97.14 97 | 99.16 16 | 94.35 169 | 97.78 138 | 98.07 125 | 95.84 84 | 99.12 229 | 91.41 211 | 99.42 137 | 98.91 168 |
|
XVG-OURS | | | 97.12 107 | 96.74 131 | 98.26 64 | 98.99 87 | 97.45 29 | 93.82 247 | 99.05 38 | 95.19 139 | 98.32 80 | 97.70 163 | 95.22 110 | 98.41 295 | 94.27 162 | 98.13 244 | 98.93 165 |
|
V42 | | | 97.04 108 | 97.16 106 | 96.68 157 | 98.59 127 | 91.05 187 | 96.33 120 | 98.36 161 | 94.60 158 | 97.99 111 | 98.30 98 | 93.32 170 | 99.62 123 | 97.40 58 | 99.53 102 | 99.38 95 |
|
APD-MVS | | | 97.00 109 | 96.53 143 | 98.41 51 | 98.55 132 | 96.31 58 | 96.32 121 | 98.77 102 | 92.96 206 | 97.44 151 | 97.58 169 | 95.84 84 | 99.74 57 | 91.96 199 | 99.35 152 | 99.19 124 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
HPM-MVS++ | | | 96.99 110 | 96.38 148 | 98.81 27 | 98.64 118 | 97.59 20 | 95.97 139 | 98.20 184 | 95.51 125 | 95.06 225 | 96.53 231 | 94.10 147 | 99.70 84 | 94.29 161 | 99.15 176 | 99.13 134 |
|
GBi-Net | | | 96.99 110 | 96.80 128 | 97.56 102 | 97.96 189 | 93.67 139 | 98.23 34 | 98.66 126 | 95.59 122 | 97.99 111 | 99.19 32 | 89.51 240 | 99.73 62 | 94.60 149 | 99.44 127 | 99.30 108 |
|
test1 | | | 96.99 110 | 96.80 128 | 97.56 102 | 97.96 189 | 93.67 139 | 98.23 34 | 98.66 126 | 95.59 122 | 97.99 111 | 99.19 32 | 89.51 240 | 99.73 62 | 94.60 149 | 99.44 127 | 99.30 108 |
|
VDDNet | | | 96.98 113 | 96.84 125 | 97.41 121 | 99.40 41 | 93.26 152 | 97.94 53 | 95.31 281 | 99.26 6 | 98.39 73 | 99.18 35 | 87.85 255 | 99.62 123 | 95.13 132 | 99.09 184 | 99.35 102 |
|
v1neww | | | 96.97 114 | 97.24 97 | 96.15 192 | 98.70 112 | 89.44 217 | 95.97 139 | 98.33 166 | 95.25 134 | 97.88 128 | 98.15 115 | 93.83 155 | 99.61 129 | 97.50 53 | 99.50 109 | 99.41 87 |
|
v7new | | | 96.97 114 | 97.24 97 | 96.15 192 | 98.70 112 | 89.44 217 | 95.97 139 | 98.33 166 | 95.25 134 | 97.88 128 | 98.15 115 | 93.83 155 | 99.61 129 | 97.50 53 | 99.50 109 | 99.41 87 |
|
v6 | | | 96.97 114 | 97.24 97 | 96.15 192 | 98.71 110 | 89.44 217 | 95.97 139 | 98.33 166 | 95.25 134 | 97.89 126 | 98.15 115 | 93.86 152 | 99.61 129 | 97.51 52 | 99.50 109 | 99.42 85 |
|
PHI-MVS | | | 96.96 117 | 96.53 143 | 98.25 66 | 97.48 234 | 96.50 53 | 96.76 108 | 98.85 83 | 93.52 188 | 96.19 201 | 96.85 210 | 95.94 81 | 99.42 179 | 93.79 176 | 99.43 134 | 98.83 179 |
|
v7 | | | 96.93 118 | 97.17 105 | 96.23 184 | 98.59 127 | 89.64 208 | 95.96 143 | 98.66 126 | 94.41 166 | 97.87 133 | 98.38 90 | 93.47 165 | 99.64 114 | 97.93 33 | 99.24 170 | 99.43 83 |
|
IS-MVSNet | | | 96.93 118 | 96.68 133 | 97.70 93 | 99.25 53 | 94.00 129 | 98.57 17 | 96.74 260 | 98.36 30 | 98.14 97 | 97.98 135 | 88.23 249 | 99.71 77 | 93.10 188 | 99.72 58 | 99.38 95 |
|
CNVR-MVS | | | 96.92 120 | 96.55 140 | 98.03 77 | 98.00 186 | 95.54 78 | 94.87 206 | 98.17 189 | 94.60 158 | 96.38 190 | 97.05 199 | 95.67 95 | 99.36 203 | 95.12 133 | 99.08 185 | 99.19 124 |
|
IterMVS-LS | | | 96.92 120 | 97.29 92 | 95.79 214 | 98.51 139 | 88.13 250 | 95.10 191 | 98.66 126 | 96.99 79 | 98.46 69 | 98.68 70 | 92.55 189 | 99.74 57 | 96.91 72 | 99.79 46 | 99.50 50 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
WR-MVS | | | 96.90 122 | 96.81 127 | 97.16 132 | 98.56 131 | 92.20 168 | 94.33 220 | 98.12 195 | 97.34 75 | 98.20 91 | 97.33 188 | 92.81 181 | 99.75 52 | 94.79 142 | 99.81 43 | 99.54 45 |
|
DeepPCF-MVS | | 94.58 5 | 96.90 122 | 96.43 147 | 98.31 61 | 97.48 234 | 97.23 35 | 92.56 281 | 98.60 136 | 92.84 208 | 98.54 62 | 97.40 181 | 96.64 61 | 98.78 270 | 94.40 156 | 99.41 143 | 98.93 165 |
|
v1141 | | | 96.86 124 | 97.14 108 | 96.04 199 | 98.55 132 | 89.06 229 | 95.44 166 | 98.33 166 | 95.14 143 | 97.93 121 | 98.19 109 | 93.36 168 | 99.62 123 | 97.61 45 | 99.69 66 | 99.44 79 |
|
divwei89l23v2f112 | | | 96.86 124 | 97.14 108 | 96.04 199 | 98.54 135 | 89.06 229 | 95.44 166 | 98.33 166 | 95.14 143 | 97.93 121 | 98.19 109 | 93.36 168 | 99.61 129 | 97.61 45 | 99.68 70 | 99.44 79 |
|
v1 | | | 96.86 124 | 97.14 108 | 96.04 199 | 98.55 132 | 89.06 229 | 95.44 166 | 98.33 166 | 95.14 143 | 97.94 118 | 98.18 113 | 93.39 167 | 99.61 129 | 97.61 45 | 99.69 66 | 99.44 79 |
|
v1144 | | | 96.84 127 | 97.08 113 | 96.13 196 | 98.42 145 | 89.28 224 | 95.41 173 | 98.67 124 | 94.21 174 | 97.97 115 | 98.31 95 | 93.06 175 | 99.65 111 | 98.06 30 | 99.62 79 | 99.45 71 |
|
VNet | | | 96.84 127 | 96.83 126 | 96.88 147 | 98.06 180 | 92.02 173 | 96.35 119 | 97.57 232 | 97.70 55 | 97.88 128 | 97.80 153 | 92.40 196 | 99.54 149 | 94.73 147 | 98.96 197 | 99.08 147 |
|
EPP-MVSNet | | | 96.84 127 | 96.58 137 | 97.65 98 | 99.18 62 | 93.78 137 | 98.68 11 | 96.34 263 | 97.91 45 | 97.30 155 | 98.06 128 | 88.46 247 | 99.85 24 | 93.85 174 | 99.40 144 | 99.32 104 |
|
v1192 | | | 96.83 130 | 97.06 115 | 96.15 192 | 98.28 155 | 89.29 223 | 95.36 176 | 98.77 102 | 93.73 184 | 98.11 99 | 98.34 92 | 93.02 179 | 99.67 105 | 98.35 26 | 99.58 89 | 99.50 50 |
|
MVS_111021_LR | | | 96.82 131 | 96.55 140 | 97.62 99 | 98.27 157 | 95.34 85 | 93.81 248 | 98.33 166 | 94.59 160 | 96.56 182 | 96.63 226 | 96.61 62 | 98.73 274 | 94.80 141 | 99.34 154 | 98.78 185 |
|
Effi-MVS+-dtu | | | 96.81 132 | 96.09 157 | 98.99 10 | 96.90 263 | 98.69 2 | 96.42 115 | 98.09 197 | 95.86 112 | 95.15 224 | 95.54 269 | 94.26 141 | 99.81 33 | 94.06 169 | 98.51 235 | 98.47 207 |
|
UGNet | | | 96.81 132 | 96.56 139 | 97.58 101 | 96.64 266 | 93.84 134 | 97.75 64 | 97.12 247 | 96.47 93 | 93.62 264 | 98.88 58 | 93.22 173 | 99.53 151 | 95.61 110 | 99.69 66 | 99.36 101 |
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 |
v2v482 | | | 96.78 134 | 97.06 115 | 95.95 206 | 98.57 130 | 88.77 239 | 95.36 176 | 98.26 178 | 95.18 140 | 97.85 135 | 98.23 104 | 92.58 188 | 99.63 117 | 97.80 38 | 99.69 66 | 99.45 71 |
|
v1240 | | | 96.74 135 | 97.02 117 | 95.91 209 | 98.18 167 | 88.52 241 | 95.39 174 | 98.88 78 | 93.15 197 | 98.46 69 | 98.40 89 | 92.80 182 | 99.71 77 | 98.45 25 | 99.49 116 | 99.49 58 |
|
DeepC-MVS_fast | | 94.34 7 | 96.74 135 | 96.51 145 | 97.44 119 | 97.69 220 | 94.15 124 | 96.02 135 | 98.43 152 | 93.17 196 | 97.30 155 | 97.38 186 | 95.48 100 | 99.28 215 | 93.74 177 | 99.34 154 | 98.88 174 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
MVS_111021_HR | | | 96.73 137 | 96.54 142 | 97.27 128 | 98.35 149 | 93.66 142 | 93.42 262 | 98.36 161 | 94.74 155 | 96.58 180 | 96.76 219 | 96.54 64 | 98.99 246 | 94.87 137 | 99.27 168 | 99.15 131 |
|
v1921920 | | | 96.72 138 | 96.96 120 | 95.99 203 | 98.21 164 | 88.79 238 | 95.42 171 | 98.79 98 | 93.22 192 | 98.19 92 | 98.26 103 | 92.68 185 | 99.70 84 | 98.34 27 | 99.55 98 | 99.49 58 |
|
FMVSNet2 | | | 96.72 138 | 96.67 134 | 96.87 148 | 97.96 189 | 91.88 176 | 97.15 95 | 98.06 202 | 95.59 122 | 98.50 66 | 98.62 73 | 89.51 240 | 99.65 111 | 94.99 136 | 99.60 86 | 99.07 149 |
|
PMVS | | 89.60 17 | 96.71 140 | 96.97 118 | 95.95 206 | 99.51 26 | 97.81 13 | 97.42 87 | 97.49 233 | 97.93 44 | 95.95 207 | 98.58 74 | 96.88 52 | 96.91 320 | 89.59 250 | 99.36 149 | 93.12 318 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
v144192 | | | 96.69 141 | 96.90 123 | 96.03 202 | 98.25 160 | 88.92 232 | 95.49 164 | 98.77 102 | 93.05 199 | 98.09 103 | 98.29 99 | 92.51 193 | 99.70 84 | 98.11 29 | 99.56 94 | 99.47 64 |
|
CPTT-MVS | | | 96.69 141 | 96.08 158 | 98.49 46 | 98.89 96 | 96.64 49 | 97.25 91 | 98.77 102 | 92.89 207 | 96.01 206 | 97.13 195 | 92.23 198 | 99.67 105 | 92.24 197 | 99.34 154 | 99.17 127 |
|
HQP_MVS | | | 96.66 143 | 96.33 151 | 97.68 96 | 98.70 112 | 94.29 118 | 96.50 113 | 98.75 106 | 96.36 95 | 96.16 202 | 96.77 217 | 91.91 211 | 99.46 170 | 92.59 193 | 99.20 173 | 99.28 115 |
|
EI-MVSNet | | | 96.63 144 | 96.93 121 | 95.74 215 | 97.26 250 | 88.13 250 | 95.29 183 | 97.65 225 | 96.99 79 | 97.94 118 | 98.19 109 | 92.55 189 | 99.58 138 | 96.91 72 | 99.56 94 | 99.50 50 |
|
ab-mvs | | | 96.59 145 | 96.59 136 | 96.60 159 | 98.64 118 | 92.21 166 | 98.35 28 | 97.67 221 | 94.45 163 | 96.99 167 | 98.79 60 | 94.96 116 | 99.49 162 | 90.39 240 | 99.07 187 | 98.08 241 |
|
v148 | | | 96.58 146 | 96.97 118 | 95.42 225 | 98.63 122 | 87.57 259 | 95.09 193 | 97.90 207 | 95.91 110 | 98.24 88 | 97.96 136 | 93.42 166 | 99.39 194 | 96.04 92 | 99.52 106 | 99.29 114 |
|
test20.03 | | | 96.58 146 | 96.61 135 | 96.48 168 | 98.49 141 | 91.72 180 | 95.68 156 | 97.69 220 | 96.81 84 | 98.27 86 | 97.92 143 | 94.18 145 | 98.71 276 | 90.78 227 | 99.66 74 | 99.00 155 |
|
NCCC | | | 96.52 148 | 95.99 162 | 98.10 71 | 97.81 202 | 95.68 73 | 95.00 202 | 98.20 184 | 95.39 130 | 95.40 220 | 96.36 242 | 93.81 157 | 99.45 174 | 93.55 181 | 98.42 238 | 99.17 127 |
|
pmmvs-eth3d | | | 96.49 149 | 96.18 154 | 97.42 120 | 98.25 160 | 94.29 118 | 94.77 212 | 98.07 201 | 89.81 243 | 97.97 115 | 98.33 93 | 93.11 174 | 99.08 235 | 95.46 115 | 99.84 40 | 98.89 170 |
|
OMC-MVS | | | 96.48 150 | 96.00 161 | 97.91 82 | 98.30 151 | 96.01 66 | 94.86 207 | 98.60 136 | 91.88 225 | 97.18 159 | 97.21 192 | 96.11 78 | 99.04 239 | 90.49 238 | 99.34 154 | 98.69 192 |
|
TSAR-MVS + GP. | | | 96.47 151 | 96.12 155 | 97.49 113 | 97.74 217 | 95.23 87 | 94.15 233 | 96.90 254 | 93.26 191 | 98.04 108 | 96.70 221 | 94.41 135 | 98.89 258 | 94.77 144 | 99.14 177 | 98.37 215 |
|
Fast-Effi-MVS+-dtu | | | 96.44 152 | 96.12 155 | 97.39 123 | 97.18 254 | 94.39 115 | 95.46 165 | 98.73 109 | 96.03 105 | 94.72 232 | 94.92 282 | 96.28 77 | 99.69 94 | 93.81 175 | 97.98 248 | 98.09 240 |
|
K. test v3 | | | 96.44 152 | 96.28 152 | 96.95 143 | 99.41 40 | 91.53 182 | 97.65 70 | 90.31 321 | 98.89 18 | 98.93 42 | 99.36 16 | 84.57 275 | 99.92 4 | 97.81 37 | 99.56 94 | 99.39 93 |
|
MSLP-MVS++ | | | 96.42 154 | 96.71 132 | 95.57 220 | 97.82 201 | 90.56 197 | 95.71 154 | 98.84 86 | 94.72 156 | 96.71 177 | 97.39 184 | 94.91 117 | 98.10 310 | 95.28 122 | 99.02 191 | 98.05 244 |
|
MVS_Test | | | 96.27 155 | 96.79 130 | 94.73 249 | 96.94 261 | 86.63 273 | 96.18 128 | 98.33 166 | 94.94 150 | 96.07 204 | 98.28 100 | 95.25 109 | 99.26 218 | 97.21 62 | 97.90 252 | 98.30 225 |
|
MCST-MVS | | | 96.24 156 | 95.80 167 | 97.56 102 | 98.75 103 | 94.13 125 | 94.66 213 | 98.17 189 | 90.17 240 | 96.21 200 | 96.10 253 | 95.14 111 | 99.43 178 | 94.13 166 | 98.85 212 | 99.13 134 |
|
mvs-test1 | | | 96.20 157 | 95.50 174 | 98.32 59 | 96.90 263 | 98.16 4 | 95.07 196 | 98.09 197 | 95.86 112 | 93.63 263 | 94.32 292 | 94.26 141 | 99.71 77 | 94.06 169 | 97.27 275 | 97.07 273 |
|
Effi-MVS+ | | | 96.19 158 | 96.01 160 | 96.71 154 | 97.43 239 | 92.19 169 | 96.12 131 | 99.10 25 | 95.45 127 | 93.33 277 | 94.71 284 | 97.23 41 | 99.56 143 | 93.21 186 | 97.54 264 | 98.37 215 |
|
DELS-MVS | | | 96.17 159 | 96.23 153 | 95.99 203 | 97.55 232 | 90.04 202 | 92.38 285 | 98.52 142 | 94.13 177 | 96.55 185 | 97.06 198 | 94.99 115 | 99.58 138 | 95.62 109 | 99.28 166 | 98.37 215 |
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 |
MVSFormer | | | 96.14 160 | 96.36 149 | 95.49 224 | 97.68 221 | 87.81 256 | 98.67 12 | 99.02 50 | 96.50 90 | 94.48 240 | 96.15 250 | 86.90 260 | 99.92 4 | 98.73 17 | 99.13 179 | 98.74 188 |
|
testgi | | | 96.07 161 | 96.50 146 | 94.80 246 | 99.26 51 | 87.69 258 | 95.96 143 | 98.58 139 | 95.08 146 | 98.02 110 | 96.25 246 | 97.92 18 | 97.60 316 | 88.68 264 | 98.74 218 | 99.11 142 |
|
LF4IMVS | | | 96.07 161 | 95.63 171 | 97.36 124 | 98.19 165 | 95.55 77 | 95.44 166 | 98.82 96 | 92.29 217 | 95.70 216 | 96.55 229 | 92.63 187 | 98.69 278 | 91.75 208 | 99.33 159 | 97.85 254 |
|
alignmvs | | | 96.01 163 | 95.52 173 | 97.50 110 | 97.77 216 | 94.71 106 | 96.07 132 | 96.84 255 | 97.48 68 | 96.78 176 | 94.28 293 | 85.50 266 | 99.40 188 | 96.22 86 | 98.73 221 | 98.40 212 |
|
TinyColmap | | | 96.00 164 | 96.34 150 | 94.96 240 | 97.90 193 | 87.91 253 | 94.13 235 | 98.49 146 | 94.41 166 | 98.16 94 | 97.76 154 | 96.29 76 | 98.68 281 | 90.52 235 | 99.42 137 | 98.30 225 |
|
PVSNet_Blended_VisFu | | | 95.95 165 | 95.80 167 | 96.42 171 | 99.28 50 | 90.62 194 | 95.31 181 | 99.08 30 | 88.40 254 | 96.97 169 | 98.17 114 | 92.11 201 | 99.78 39 | 93.64 179 | 99.21 172 | 98.86 177 |
|
test_prior3 | | | 95.91 166 | 95.39 178 | 97.46 116 | 97.79 211 | 94.26 121 | 93.33 266 | 98.42 155 | 94.21 174 | 94.02 252 | 96.25 246 | 93.64 161 | 99.34 205 | 91.90 200 | 98.96 197 | 98.79 183 |
|
UnsupCasMVSNet_eth | | | 95.91 166 | 95.73 169 | 96.44 170 | 98.48 143 | 91.52 183 | 95.31 181 | 98.45 149 | 95.76 116 | 97.48 148 | 97.54 170 | 89.53 239 | 98.69 278 | 94.43 153 | 94.61 305 | 99.13 134 |
|
QAPM | | | 95.88 168 | 95.57 172 | 96.80 149 | 97.90 193 | 91.84 178 | 98.18 41 | 98.73 109 | 88.41 253 | 96.42 188 | 98.13 119 | 94.73 119 | 99.75 52 | 88.72 262 | 98.94 201 | 98.81 180 |
|
MVP-Stereo | | | 95.69 169 | 95.28 180 | 96.92 144 | 98.15 173 | 93.03 155 | 95.64 161 | 98.20 184 | 90.39 237 | 96.63 179 | 97.73 160 | 91.63 214 | 99.10 233 | 91.84 204 | 97.31 273 | 98.63 196 |
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
MDA-MVSNet-bldmvs | | | 95.69 169 | 95.67 170 | 95.74 215 | 98.48 143 | 88.76 240 | 92.84 273 | 97.25 240 | 96.00 106 | 97.59 140 | 97.95 139 | 91.38 219 | 99.46 170 | 93.16 187 | 96.35 289 | 98.99 158 |
|
new-patchmatchnet | | | 95.67 171 | 96.58 137 | 92.94 279 | 97.48 234 | 80.21 304 | 92.96 272 | 98.19 188 | 94.83 152 | 98.82 45 | 98.79 60 | 93.31 171 | 99.51 159 | 95.83 101 | 99.04 190 | 99.12 139 |
|
MVS_0305 | | | 95.66 172 | 95.44 176 | 96.31 178 | 96.60 268 | 90.43 199 | 94.23 226 | 98.52 142 | 95.01 149 | 91.76 298 | 96.65 225 | 91.75 213 | 99.70 84 | 94.75 146 | 99.65 75 | 98.81 180 |
|
xiu_mvs_v1_base_debu | | | 95.62 173 | 95.96 163 | 94.60 252 | 98.01 183 | 88.42 242 | 93.99 239 | 98.21 181 | 92.98 201 | 95.91 208 | 94.53 286 | 96.39 71 | 99.72 67 | 95.43 118 | 98.19 241 | 95.64 303 |
|
xiu_mvs_v1_base | | | 95.62 173 | 95.96 163 | 94.60 252 | 98.01 183 | 88.42 242 | 93.99 239 | 98.21 181 | 92.98 201 | 95.91 208 | 94.53 286 | 96.39 71 | 99.72 67 | 95.43 118 | 98.19 241 | 95.64 303 |
|
xiu_mvs_v1_base_debi | | | 95.62 173 | 95.96 163 | 94.60 252 | 98.01 183 | 88.42 242 | 93.99 239 | 98.21 181 | 92.98 201 | 95.91 208 | 94.53 286 | 96.39 71 | 99.72 67 | 95.43 118 | 98.19 241 | 95.64 303 |
|
DP-MVS Recon | | | 95.55 176 | 95.13 184 | 96.80 149 | 98.51 139 | 93.99 130 | 94.60 215 | 98.69 119 | 90.20 239 | 95.78 212 | 96.21 249 | 92.73 184 | 98.98 248 | 90.58 234 | 98.86 210 | 97.42 269 |
|
test_normal | | | 95.51 177 | 95.46 175 | 95.68 219 | 97.97 188 | 89.12 228 | 93.73 250 | 95.86 273 | 91.98 221 | 97.17 160 | 96.94 205 | 91.55 215 | 99.42 179 | 95.21 125 | 98.73 221 | 98.51 205 |
|
testmv | | | 95.51 177 | 95.33 179 | 96.05 198 | 98.23 162 | 89.51 215 | 93.50 259 | 98.63 133 | 94.25 172 | 98.22 89 | 97.73 160 | 92.51 193 | 99.47 166 | 85.22 296 | 99.72 58 | 99.17 127 |
|
Fast-Effi-MVS+ | | | 95.49 179 | 95.07 186 | 96.75 152 | 97.67 224 | 92.82 157 | 94.22 228 | 98.60 136 | 91.61 227 | 93.42 274 | 92.90 303 | 96.73 60 | 99.70 84 | 92.60 192 | 97.89 253 | 97.74 259 |
|
TAMVS | | | 95.49 179 | 94.94 191 | 97.16 132 | 98.31 150 | 93.41 149 | 95.07 196 | 96.82 256 | 91.09 232 | 97.51 143 | 97.82 151 | 89.96 234 | 99.42 179 | 88.42 267 | 99.44 127 | 98.64 194 |
|
OpenMVS | | 94.22 8 | 95.48 181 | 95.20 182 | 96.32 177 | 97.16 255 | 91.96 175 | 97.74 66 | 98.84 86 | 87.26 265 | 94.36 242 | 98.01 132 | 93.95 151 | 99.67 105 | 90.70 231 | 98.75 217 | 97.35 270 |
|
CLD-MVS | | | 95.47 182 | 95.07 186 | 96.69 156 | 98.27 157 | 92.53 160 | 91.36 299 | 98.67 124 | 91.22 231 | 95.78 212 | 94.12 294 | 95.65 96 | 98.98 248 | 90.81 225 | 99.72 58 | 98.57 200 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
train_agg | | | 95.46 183 | 94.66 201 | 97.88 83 | 97.84 199 | 95.23 87 | 93.62 254 | 98.39 157 | 87.04 269 | 93.78 258 | 95.99 254 | 94.58 129 | 99.52 155 | 91.76 206 | 98.90 203 | 98.89 170 |
|
DI_MVS_plusplus_test | | | 95.46 183 | 95.43 177 | 95.55 221 | 98.05 181 | 88.84 236 | 94.18 230 | 95.75 275 | 91.92 224 | 97.32 154 | 96.94 205 | 91.44 217 | 99.39 194 | 94.81 140 | 98.48 236 | 98.43 211 |
|
CDPH-MVS | | | 95.45 185 | 94.65 202 | 97.84 86 | 98.28 155 | 94.96 98 | 93.73 250 | 98.33 166 | 85.03 290 | 95.44 219 | 96.60 227 | 95.31 107 | 99.44 177 | 90.01 245 | 99.13 179 | 99.11 142 |
|
IterMVS | | | 95.42 186 | 95.83 166 | 94.20 264 | 97.52 233 | 83.78 294 | 92.41 284 | 97.47 237 | 95.49 126 | 98.06 106 | 98.49 82 | 87.94 251 | 99.58 138 | 96.02 94 | 99.02 191 | 99.23 121 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
agg_prior1 | | | 95.39 187 | 94.60 205 | 97.75 90 | 97.80 206 | 94.96 98 | 93.39 263 | 98.36 161 | 87.20 267 | 93.49 269 | 95.97 257 | 94.65 126 | 99.53 151 | 91.69 209 | 98.86 210 | 98.77 186 |
|
Test4 | | | 95.39 187 | 95.24 181 | 95.82 213 | 98.07 179 | 89.60 211 | 94.40 219 | 98.49 146 | 91.39 230 | 97.40 153 | 96.32 244 | 87.32 259 | 99.41 185 | 95.09 134 | 98.71 223 | 98.44 210 |
|
mvs_anonymous | | | 95.36 189 | 96.07 159 | 93.21 274 | 96.29 274 | 81.56 299 | 94.60 215 | 97.66 223 | 93.30 190 | 96.95 170 | 98.91 57 | 93.03 178 | 99.38 199 | 96.60 75 | 97.30 274 | 98.69 192 |
|
MSDG | | | 95.33 190 | 95.13 184 | 95.94 208 | 97.40 241 | 91.85 177 | 91.02 302 | 98.37 160 | 95.30 132 | 96.31 194 | 95.99 254 | 94.51 133 | 98.38 299 | 89.59 250 | 97.65 261 | 97.60 264 |
|
LFMVS | | | 95.32 191 | 94.88 195 | 96.62 158 | 98.03 182 | 91.47 184 | 97.65 70 | 90.72 320 | 99.11 8 | 97.89 126 | 98.31 95 | 79.20 288 | 99.48 164 | 93.91 173 | 99.12 182 | 98.93 165 |
|
agg_prior3 | | | 95.30 192 | 94.46 213 | 97.80 88 | 97.80 206 | 95.00 96 | 93.63 253 | 98.34 165 | 86.33 275 | 93.40 276 | 95.84 261 | 94.15 146 | 99.50 160 | 91.76 206 | 98.90 203 | 98.89 170 |
|
F-COLMAP | | | 95.30 192 | 94.38 215 | 98.05 76 | 98.64 118 | 96.04 64 | 95.61 163 | 98.66 126 | 89.00 248 | 93.22 278 | 96.40 241 | 92.90 180 | 99.35 204 | 87.45 280 | 97.53 265 | 98.77 186 |
|
Anonymous20231206 | | | 95.27 194 | 95.06 188 | 95.88 210 | 98.72 107 | 89.37 222 | 95.70 155 | 97.85 210 | 88.00 261 | 96.98 168 | 97.62 167 | 91.95 207 | 99.34 205 | 89.21 254 | 99.53 102 | 98.94 163 |
|
FMVSNet3 | | | 95.26 195 | 94.94 191 | 96.22 188 | 96.53 270 | 90.06 201 | 95.99 137 | 97.66 223 | 94.11 178 | 97.99 111 | 97.91 144 | 80.22 286 | 99.63 117 | 94.60 149 | 99.44 127 | 98.96 160 |
|
N_pmnet | | | 95.18 196 | 94.23 218 | 98.06 73 | 97.85 195 | 96.55 52 | 92.49 282 | 91.63 315 | 89.34 245 | 98.09 103 | 97.41 180 | 90.33 228 | 99.06 237 | 91.58 210 | 99.31 161 | 98.56 201 |
|
HQP-MVS | | | 95.17 197 | 94.58 207 | 96.92 144 | 97.85 195 | 92.47 161 | 94.26 221 | 98.43 152 | 93.18 193 | 92.86 282 | 95.08 276 | 90.33 228 | 99.23 222 | 90.51 236 | 98.74 218 | 99.05 152 |
|
Vis-MVSNet (Re-imp) | | | 95.11 198 | 94.85 196 | 95.87 211 | 99.12 75 | 89.17 225 | 97.54 82 | 94.92 283 | 96.50 90 | 96.58 180 | 97.27 190 | 83.64 276 | 99.48 164 | 88.42 267 | 99.67 72 | 98.97 159 |
|
AdaColmap | | | 95.11 198 | 94.62 204 | 96.58 162 | 97.33 247 | 94.45 114 | 94.92 204 | 98.08 199 | 93.15 197 | 93.98 255 | 95.53 270 | 94.34 138 | 99.10 233 | 85.69 291 | 98.61 229 | 96.20 298 |
|
API-MVS | | | 95.09 200 | 95.01 189 | 95.31 229 | 96.61 267 | 94.02 128 | 96.83 106 | 97.18 244 | 95.60 121 | 95.79 211 | 94.33 291 | 94.54 131 | 98.37 301 | 85.70 290 | 98.52 233 | 93.52 315 |
|
CNLPA | | | 95.04 201 | 94.47 210 | 96.75 152 | 97.81 202 | 95.25 86 | 94.12 236 | 97.89 208 | 94.41 166 | 94.57 235 | 95.69 263 | 90.30 231 | 98.35 302 | 86.72 285 | 98.76 216 | 96.64 290 |
|
Patchmtry | | | 95.03 202 | 94.59 206 | 96.33 176 | 94.83 299 | 90.82 192 | 96.38 117 | 97.20 242 | 96.59 88 | 97.49 145 | 98.57 75 | 77.67 294 | 99.38 199 | 92.95 191 | 99.62 79 | 98.80 182 |
|
PVSNet_BlendedMVS | | | 95.02 203 | 94.93 193 | 95.27 230 | 97.79 211 | 87.40 264 | 94.14 234 | 98.68 121 | 88.94 249 | 94.51 238 | 98.01 132 | 93.04 176 | 99.30 211 | 89.77 248 | 99.49 116 | 99.11 142 |
|
diffmvs | | | 95.00 204 | 95.00 190 | 95.01 239 | 96.53 270 | 87.96 252 | 95.73 152 | 98.32 175 | 90.67 236 | 91.89 295 | 97.43 179 | 92.07 204 | 98.90 255 | 95.44 116 | 96.88 278 | 98.16 239 |
|
TAPA-MVS | | 93.32 12 | 94.93 205 | 94.23 218 | 97.04 140 | 98.18 167 | 94.51 111 | 95.22 188 | 98.73 109 | 81.22 307 | 96.25 198 | 95.95 259 | 93.80 158 | 98.98 248 | 89.89 246 | 98.87 208 | 97.62 262 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
CDS-MVSNet | | | 94.88 206 | 94.12 222 | 97.14 134 | 97.64 226 | 93.57 144 | 93.96 242 | 97.06 249 | 90.05 241 | 96.30 195 | 96.55 229 | 86.10 263 | 99.47 166 | 90.10 244 | 99.31 161 | 98.40 212 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
no-one | | | 94.84 207 | 94.76 199 | 95.09 236 | 98.29 152 | 87.49 261 | 91.82 293 | 97.49 233 | 88.21 257 | 97.84 136 | 98.75 64 | 91.51 216 | 99.27 216 | 88.96 259 | 99.99 2 | 98.52 204 |
|
MS-PatchMatch | | | 94.83 208 | 94.91 194 | 94.57 255 | 96.81 265 | 87.10 268 | 94.23 226 | 97.34 238 | 88.74 251 | 97.14 161 | 97.11 196 | 91.94 208 | 98.23 306 | 92.99 190 | 97.92 250 | 98.37 215 |
|
pmmvs4 | | | 94.82 209 | 94.19 220 | 96.70 155 | 97.42 240 | 92.75 159 | 92.09 290 | 96.76 258 | 86.80 272 | 95.73 215 | 97.22 191 | 89.28 243 | 98.89 258 | 93.28 184 | 99.14 177 | 98.46 209 |
|
YYNet1 | | | 94.73 210 | 94.84 197 | 94.41 259 | 97.47 238 | 85.09 287 | 90.29 307 | 95.85 274 | 92.52 211 | 97.53 142 | 97.76 154 | 91.97 206 | 99.18 225 | 93.31 183 | 96.86 279 | 98.95 161 |
|
MDA-MVSNet_test_wron | | | 94.73 210 | 94.83 198 | 94.42 258 | 97.48 234 | 85.15 285 | 90.28 308 | 95.87 272 | 92.52 211 | 97.48 148 | 97.76 154 | 91.92 210 | 99.17 227 | 93.32 182 | 96.80 282 | 98.94 163 |
|
UnsupCasMVSNet_bld | | | 94.72 212 | 94.26 217 | 96.08 197 | 98.62 123 | 90.54 198 | 93.38 264 | 98.05 203 | 90.30 238 | 97.02 166 | 96.80 215 | 89.54 237 | 99.16 228 | 88.44 266 | 96.18 291 | 98.56 201 |
|
BH-untuned | | | 94.69 213 | 94.75 200 | 94.52 257 | 97.95 192 | 87.53 260 | 94.07 237 | 97.01 250 | 93.99 179 | 97.10 163 | 95.65 266 | 92.65 186 | 98.95 253 | 87.60 277 | 96.74 283 | 97.09 272 |
|
Patchmatch-RL test | | | 94.66 214 | 94.49 209 | 95.19 232 | 98.54 135 | 88.91 233 | 92.57 280 | 98.74 108 | 91.46 229 | 98.32 80 | 97.75 157 | 77.31 299 | 98.81 268 | 96.06 90 | 99.61 83 | 97.85 254 |
|
pmmvs5 | | | 94.63 215 | 94.34 216 | 95.50 223 | 97.63 227 | 88.34 245 | 94.02 238 | 97.13 246 | 87.15 268 | 95.22 223 | 97.15 194 | 87.50 256 | 99.27 216 | 93.99 172 | 99.26 169 | 98.88 174 |
|
PAPM_NR | | | 94.61 216 | 94.17 221 | 95.96 205 | 98.36 148 | 91.23 185 | 95.93 146 | 97.95 205 | 92.98 201 | 93.42 274 | 94.43 290 | 90.53 226 | 98.38 299 | 87.60 277 | 96.29 290 | 98.27 228 |
|
PatchMatch-RL | | | 94.61 216 | 93.81 228 | 97.02 142 | 98.19 165 | 95.72 71 | 93.66 252 | 97.23 241 | 88.17 258 | 94.94 229 | 95.62 267 | 91.43 218 | 98.57 286 | 87.36 281 | 97.68 258 | 96.76 286 |
|
BH-RMVSNet | | | 94.56 218 | 94.44 214 | 94.91 241 | 97.57 229 | 87.44 263 | 93.78 249 | 96.26 264 | 93.69 186 | 96.41 189 | 96.50 234 | 92.10 202 | 99.00 245 | 85.96 288 | 97.71 255 | 98.31 223 |
|
USDC | | | 94.56 218 | 94.57 208 | 94.55 256 | 97.78 215 | 86.43 275 | 92.75 276 | 98.65 132 | 85.96 278 | 96.91 172 | 97.93 142 | 90.82 224 | 98.74 273 | 90.71 230 | 99.59 87 | 98.47 207 |
|
jason | | | 94.39 220 | 94.04 224 | 95.41 227 | 98.29 152 | 87.85 255 | 92.74 278 | 96.75 259 | 85.38 288 | 95.29 221 | 96.15 250 | 88.21 250 | 99.65 111 | 94.24 164 | 99.34 154 | 98.74 188 |
jason: jason. |
1121 | | | 94.26 221 | 93.26 237 | 97.27 128 | 98.26 159 | 94.73 104 | 95.86 148 | 97.71 219 | 77.96 320 | 94.53 237 | 96.71 220 | 91.93 209 | 99.40 188 | 87.71 273 | 98.64 227 | 97.69 260 |
|
EU-MVSNet | | | 94.25 222 | 94.47 210 | 93.60 268 | 98.14 174 | 82.60 297 | 97.24 93 | 92.72 307 | 85.08 289 | 98.48 67 | 98.94 54 | 82.59 279 | 98.76 272 | 97.47 56 | 99.53 102 | 99.44 79 |
|
xiu_mvs_v2_base | | | 94.22 223 | 94.63 203 | 92.99 278 | 97.32 248 | 84.84 290 | 92.12 288 | 97.84 211 | 91.96 222 | 94.17 245 | 93.43 297 | 96.07 79 | 99.71 77 | 91.27 214 | 97.48 267 | 94.42 311 |
|
RPMNet | | | 94.22 223 | 94.03 225 | 94.78 247 | 95.44 292 | 88.15 248 | 96.18 128 | 93.73 291 | 97.43 69 | 94.10 248 | 98.49 82 | 79.40 287 | 99.39 194 | 95.69 103 | 95.81 293 | 96.81 284 |
|
sss | | | 94.22 223 | 93.72 229 | 95.74 215 | 97.71 219 | 89.95 205 | 93.84 246 | 96.98 251 | 88.38 256 | 93.75 260 | 95.74 262 | 87.94 251 | 98.89 258 | 91.02 218 | 98.10 245 | 98.37 215 |
|
MVSTER | | | 94.21 226 | 93.93 227 | 95.05 238 | 95.83 285 | 86.46 274 | 95.18 189 | 97.65 225 | 92.41 216 | 97.94 118 | 98.00 134 | 72.39 314 | 99.58 138 | 96.36 84 | 99.56 94 | 99.12 139 |
|
MAR-MVS | | | 94.21 226 | 93.03 241 | 97.76 89 | 96.94 261 | 97.44 30 | 96.97 104 | 97.15 245 | 87.89 263 | 92.00 293 | 92.73 307 | 92.14 200 | 99.12 229 | 83.92 304 | 97.51 266 | 96.73 287 |
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 |
1112_ss | | | 94.12 228 | 93.42 233 | 96.23 184 | 98.59 127 | 90.85 190 | 94.24 225 | 98.85 83 | 85.49 283 | 92.97 280 | 94.94 280 | 86.01 264 | 99.64 114 | 91.78 205 | 97.92 250 | 98.20 235 |
|
PS-MVSNAJ | | | 94.10 229 | 94.47 210 | 93.00 277 | 97.35 243 | 84.88 289 | 91.86 292 | 97.84 211 | 91.96 222 | 94.17 245 | 92.50 309 | 95.82 87 | 99.71 77 | 91.27 214 | 97.48 267 | 94.40 312 |
|
CHOSEN 1792x2688 | | | 94.10 229 | 93.41 234 | 96.18 190 | 99.16 63 | 90.04 202 | 92.15 287 | 98.68 121 | 79.90 312 | 96.22 199 | 97.83 148 | 87.92 254 | 99.42 179 | 89.18 255 | 99.65 75 | 99.08 147 |
|
MG-MVS | | | 94.08 231 | 94.00 226 | 94.32 261 | 97.09 257 | 85.89 276 | 93.19 270 | 95.96 270 | 92.52 211 | 94.93 230 | 97.51 174 | 89.54 237 | 98.77 271 | 87.52 279 | 97.71 255 | 98.31 223 |
|
PLC | | 91.02 16 | 94.05 232 | 92.90 244 | 97.51 107 | 98.00 186 | 95.12 94 | 94.25 224 | 98.25 179 | 86.17 276 | 91.48 299 | 95.25 274 | 91.01 222 | 99.19 224 | 85.02 298 | 96.69 284 | 98.22 233 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
114514_t | | | 93.96 233 | 93.22 239 | 96.19 189 | 99.06 81 | 90.97 189 | 95.99 137 | 98.94 71 | 73.88 326 | 93.43 273 | 96.93 207 | 92.38 197 | 99.37 202 | 89.09 256 | 99.28 166 | 98.25 230 |
|
PVSNet_Blended | | | 93.96 233 | 93.65 230 | 94.91 241 | 97.79 211 | 87.40 264 | 91.43 298 | 98.68 121 | 84.50 294 | 94.51 238 | 94.48 289 | 93.04 176 | 99.30 211 | 89.77 248 | 98.61 229 | 98.02 249 |
|
MVS_dtu | | | 93.94 235 | 93.30 235 | 95.86 212 | 94.60 302 | 89.39 221 | 93.96 242 | 96.81 257 | 92.57 210 | 87.83 319 | 95.66 265 | 84.98 272 | 99.60 135 | 94.25 163 | 99.02 191 | 98.60 198 |
|
lupinMVS | | | 93.77 236 | 93.28 236 | 95.24 231 | 97.68 221 | 87.81 256 | 92.12 288 | 96.05 266 | 84.52 293 | 94.48 240 | 95.06 278 | 86.90 260 | 99.63 117 | 93.62 180 | 99.13 179 | 98.27 228 |
|
PatchT | | | 93.75 237 | 93.57 232 | 94.29 263 | 95.05 297 | 87.32 266 | 96.05 133 | 92.98 302 | 97.54 64 | 94.25 243 | 98.72 66 | 75.79 307 | 99.24 220 | 95.92 99 | 95.81 293 | 96.32 296 |
|
EPNet | | | 93.72 238 | 92.62 251 | 97.03 141 | 87.61 333 | 92.25 165 | 96.27 122 | 91.28 317 | 96.74 85 | 87.65 320 | 97.39 184 | 85.00 271 | 99.64 114 | 92.14 198 | 99.48 119 | 99.20 123 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
HyFIR lowres test | | | 93.72 238 | 92.65 250 | 96.91 146 | 98.93 91 | 91.81 179 | 91.23 301 | 98.52 142 | 82.69 300 | 96.46 187 | 96.52 233 | 80.38 285 | 99.90 13 | 90.36 241 | 98.79 213 | 99.03 153 |
|
PMMVS2 | | | 93.66 240 | 94.07 223 | 92.45 285 | 97.57 229 | 80.67 303 | 86.46 320 | 96.00 267 | 93.99 179 | 97.10 163 | 97.38 186 | 89.90 235 | 97.82 313 | 88.76 261 | 99.47 121 | 98.86 177 |
|
OpenMVS_ROB | | 91.80 14 | 93.64 241 | 93.05 240 | 95.42 225 | 97.31 249 | 91.21 186 | 95.08 195 | 96.68 262 | 81.56 304 | 96.88 174 | 96.41 239 | 90.44 227 | 99.25 219 | 85.39 295 | 97.67 259 | 95.80 301 |
|
Patchmatch-test | | | 93.60 242 | 93.25 238 | 94.63 250 | 96.14 280 | 87.47 262 | 96.04 134 | 94.50 287 | 93.57 187 | 96.47 186 | 96.97 203 | 76.50 302 | 98.61 284 | 90.67 232 | 98.41 239 | 97.81 257 |
|
WTY-MVS | | | 93.55 243 | 93.00 242 | 95.19 232 | 97.81 202 | 87.86 254 | 93.89 244 | 96.00 267 | 89.02 247 | 94.07 250 | 95.44 271 | 86.27 262 | 99.33 208 | 87.69 275 | 96.82 280 | 98.39 214 |
|
MVS_test0326 | | | 93.54 244 | 92.94 243 | 95.35 228 | 94.17 312 | 88.28 246 | 93.48 260 | 95.99 269 | 92.45 214 | 86.60 323 | 95.26 273 | 85.37 267 | 99.53 151 | 94.11 167 | 98.99 195 | 98.23 231 |
|
Test_1112_low_res | | | 93.53 245 | 92.86 245 | 95.54 222 | 98.60 125 | 88.86 235 | 92.75 276 | 98.69 119 | 82.66 301 | 92.65 287 | 96.92 208 | 84.75 273 | 99.56 143 | 90.94 221 | 97.76 254 | 98.19 236 |
|
MIMVSNet | | | 93.42 246 | 92.86 245 | 95.10 235 | 98.17 169 | 88.19 247 | 98.13 43 | 93.69 292 | 92.07 218 | 95.04 227 | 98.21 108 | 80.95 283 | 99.03 242 | 81.42 312 | 98.06 246 | 98.07 243 |
|
FMVSNet5 | | | 93.39 247 | 92.35 253 | 96.50 167 | 95.83 285 | 90.81 193 | 97.31 88 | 98.27 176 | 92.74 209 | 96.27 196 | 98.28 100 | 62.23 327 | 99.67 105 | 90.86 223 | 99.36 149 | 99.03 153 |
|
Patchmatch-test1 | | | 93.38 248 | 93.59 231 | 92.73 281 | 96.24 275 | 81.40 300 | 93.24 268 | 94.00 290 | 91.58 228 | 94.57 235 | 96.67 223 | 87.94 251 | 99.03 242 | 90.42 239 | 97.66 260 | 97.77 258 |
|
CR-MVSNet | | | 93.29 249 | 92.79 247 | 94.78 247 | 95.44 292 | 88.15 248 | 96.18 128 | 97.20 242 | 84.94 291 | 94.10 248 | 98.57 75 | 77.67 294 | 99.39 194 | 95.17 128 | 95.81 293 | 96.81 284 |
|
wuyk23d | | | 93.25 250 | 95.20 182 | 87.40 312 | 96.07 281 | 95.38 83 | 97.04 101 | 94.97 282 | 95.33 131 | 99.70 6 | 98.11 122 | 98.14 14 | 91.94 328 | 77.76 318 | 99.68 70 | 74.89 326 |
|
LP | | | 93.12 251 | 92.78 249 | 94.14 265 | 94.50 305 | 85.48 280 | 95.73 152 | 95.68 277 | 92.97 205 | 95.05 226 | 97.17 193 | 81.93 280 | 99.40 188 | 93.06 189 | 88.96 320 | 97.55 265 |
|
test1235678 | | | 92.95 252 | 92.40 252 | 94.61 251 | 96.95 260 | 86.87 270 | 90.75 304 | 97.75 215 | 91.00 234 | 96.33 191 | 95.38 272 | 85.21 269 | 98.92 254 | 79.00 316 | 99.20 173 | 98.03 247 |
|
X-MVStestdata | | | 92.86 253 | 90.83 270 | 98.94 15 | 99.15 66 | 97.66 16 | 97.77 61 | 98.83 92 | 97.42 70 | 96.32 192 | 36.50 330 | 96.49 68 | 99.72 67 | 95.66 106 | 99.37 146 | 99.45 71 |
|
GA-MVS | | | 92.83 254 | 92.15 256 | 94.87 244 | 96.97 259 | 87.27 267 | 90.03 309 | 96.12 265 | 91.83 226 | 94.05 251 | 94.57 285 | 76.01 306 | 98.97 252 | 92.46 195 | 97.34 272 | 98.36 220 |
|
CMPMVS | | 73.10 23 | 92.74 255 | 91.39 262 | 96.77 151 | 93.57 318 | 94.67 108 | 94.21 229 | 97.67 221 | 80.36 311 | 93.61 265 | 96.60 227 | 82.85 278 | 97.35 317 | 84.86 299 | 98.78 214 | 98.29 227 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
HY-MVS | | 91.43 15 | 92.58 256 | 91.81 260 | 94.90 243 | 96.49 272 | 88.87 234 | 97.31 88 | 94.62 285 | 85.92 279 | 90.50 307 | 96.84 211 | 85.05 270 | 99.40 188 | 83.77 307 | 95.78 296 | 96.43 295 |
|
TR-MVS | | | 92.54 257 | 92.20 255 | 93.57 269 | 96.49 272 | 86.66 272 | 93.51 258 | 94.73 284 | 89.96 242 | 94.95 228 | 93.87 295 | 90.24 233 | 98.61 284 | 81.18 313 | 94.88 302 | 95.45 307 |
|
PMMVS | | | 92.39 258 | 91.08 266 | 96.30 180 | 93.12 321 | 92.81 158 | 90.58 306 | 95.96 270 | 79.17 315 | 91.85 296 | 92.27 310 | 90.29 232 | 98.66 283 | 89.85 247 | 96.68 285 | 97.43 268 |
|
1314 | | | 92.38 259 | 92.30 254 | 92.64 283 | 95.42 294 | 85.15 285 | 95.86 148 | 96.97 252 | 85.40 287 | 90.62 303 | 93.06 301 | 91.12 221 | 97.80 314 | 86.74 284 | 95.49 301 | 94.97 309 |
|
new_pmnet | | | 92.34 260 | 91.69 261 | 94.32 261 | 96.23 277 | 89.16 226 | 92.27 286 | 92.88 304 | 84.39 296 | 95.29 221 | 96.35 243 | 85.66 265 | 96.74 323 | 84.53 301 | 97.56 263 | 97.05 274 |
|
CVMVSNet | | | 92.33 261 | 92.79 247 | 90.95 298 | 97.26 250 | 75.84 319 | 95.29 183 | 92.33 310 | 81.86 302 | 96.27 196 | 98.19 109 | 81.44 281 | 98.46 293 | 94.23 165 | 98.29 240 | 98.55 203 |
|
PAPR | | | 92.22 262 | 91.27 265 | 95.07 237 | 95.73 288 | 88.81 237 | 91.97 291 | 97.87 209 | 85.80 281 | 90.91 301 | 92.73 307 | 91.16 220 | 98.33 303 | 79.48 314 | 95.76 297 | 98.08 241 |
|
DSMNet-mixed | | | 92.19 263 | 91.83 259 | 93.25 273 | 96.18 279 | 83.68 295 | 96.27 122 | 93.68 294 | 76.97 323 | 92.54 289 | 99.18 35 | 89.20 245 | 98.55 289 | 83.88 305 | 98.60 231 | 97.51 267 |
|
BH-w/o | | | 92.14 264 | 91.94 257 | 92.73 281 | 97.13 256 | 85.30 282 | 92.46 283 | 95.64 278 | 89.33 246 | 94.21 244 | 92.74 306 | 89.60 236 | 98.24 305 | 81.68 311 | 94.66 304 | 94.66 310 |
|
PCF-MVS | | 89.43 18 | 92.12 265 | 90.64 273 | 96.57 164 | 97.80 206 | 93.48 148 | 89.88 313 | 98.45 149 | 74.46 325 | 96.04 205 | 95.68 264 | 90.71 225 | 99.31 210 | 73.73 321 | 99.01 194 | 96.91 280 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
PatchmatchNet | | | 91.98 266 | 91.87 258 | 92.30 287 | 94.60 302 | 79.71 305 | 95.12 190 | 93.59 297 | 89.52 244 | 93.61 265 | 97.02 201 | 77.94 292 | 99.18 225 | 90.84 224 | 94.57 306 | 98.01 250 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
cascas | | | 91.89 267 | 91.35 263 | 93.51 270 | 94.27 308 | 85.60 278 | 88.86 316 | 98.61 135 | 79.32 314 | 92.16 292 | 91.44 314 | 89.22 244 | 98.12 309 | 90.80 226 | 97.47 269 | 96.82 283 |
|
JIA-IIPM | | | 91.79 268 | 90.69 272 | 95.11 234 | 93.80 315 | 90.98 188 | 94.16 232 | 91.78 314 | 96.38 94 | 90.30 309 | 99.30 23 | 72.02 316 | 98.90 255 | 88.28 269 | 90.17 317 | 95.45 307 |
|
ADS-MVSNet2 | | | 91.47 269 | 90.51 275 | 94.36 260 | 95.51 290 | 85.63 277 | 95.05 199 | 95.70 276 | 83.46 298 | 92.69 285 | 96.84 211 | 79.15 289 | 99.41 185 | 85.66 292 | 90.52 315 | 98.04 245 |
|
EPNet_dtu | | | 91.39 270 | 90.75 271 | 93.31 272 | 90.48 331 | 82.61 296 | 94.80 210 | 92.88 304 | 93.39 189 | 81.74 329 | 94.90 283 | 81.36 282 | 99.11 232 | 88.28 269 | 98.87 208 | 98.21 234 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
PVSNet | | 86.72 19 | 91.10 271 | 90.97 267 | 91.49 292 | 97.56 231 | 78.04 312 | 87.17 318 | 94.60 286 | 84.65 292 | 92.34 290 | 92.20 311 | 87.37 258 | 98.47 292 | 85.17 297 | 97.69 257 | 97.96 251 |
|
tpm | | | 91.08 272 | 90.85 269 | 91.75 291 | 95.33 295 | 78.09 310 | 95.03 201 | 91.27 318 | 88.75 250 | 93.53 268 | 97.40 181 | 71.24 317 | 99.30 211 | 91.25 216 | 93.87 307 | 97.87 253 |
|
ADS-MVSNet | | | 90.95 273 | 90.26 277 | 93.04 275 | 95.51 290 | 82.37 298 | 95.05 199 | 93.41 298 | 83.46 298 | 92.69 285 | 96.84 211 | 79.15 289 | 98.70 277 | 85.66 292 | 90.52 315 | 98.04 245 |
|
testus | | | 90.90 274 | 90.51 275 | 92.06 289 | 96.07 281 | 79.45 306 | 88.99 314 | 98.44 151 | 85.46 285 | 94.15 247 | 90.77 317 | 89.12 246 | 98.01 312 | 73.66 322 | 97.95 249 | 98.71 191 |
|
tpmvs | | | 90.79 275 | 90.87 268 | 90.57 301 | 92.75 325 | 76.30 317 | 95.79 151 | 93.64 295 | 91.04 233 | 91.91 294 | 96.26 245 | 77.19 300 | 98.86 264 | 89.38 253 | 89.85 318 | 96.56 293 |
|
tpmrst | | | 90.31 276 | 90.61 274 | 89.41 305 | 94.06 313 | 72.37 326 | 95.06 198 | 93.69 292 | 88.01 260 | 92.32 291 | 96.86 209 | 77.45 296 | 98.82 266 | 91.04 217 | 87.01 323 | 97.04 275 |
|
test0.0.03 1 | | | 90.11 277 | 89.21 284 | 92.83 280 | 93.89 314 | 86.87 270 | 91.74 294 | 88.74 325 | 92.02 219 | 94.71 233 | 91.14 316 | 73.92 311 | 94.48 327 | 83.75 308 | 92.94 309 | 97.16 271 |
|
MVS | | | 90.02 278 | 89.20 285 | 92.47 284 | 94.71 300 | 86.90 269 | 95.86 148 | 96.74 260 | 64.72 328 | 90.62 303 | 92.77 305 | 92.54 191 | 98.39 297 | 79.30 315 | 95.56 300 | 92.12 319 |
|
pmmvs3 | | | 90.00 279 | 88.90 288 | 93.32 271 | 94.20 311 | 85.34 281 | 91.25 300 | 92.56 309 | 78.59 317 | 93.82 257 | 95.17 275 | 67.36 325 | 98.69 278 | 89.08 257 | 98.03 247 | 95.92 299 |
|
CHOSEN 280x420 | | | 89.98 280 | 89.19 286 | 92.37 286 | 95.60 289 | 81.13 301 | 86.22 321 | 97.09 248 | 81.44 306 | 87.44 321 | 93.15 299 | 73.99 310 | 99.47 166 | 88.69 263 | 99.07 187 | 96.52 294 |
|
test-LLR | | | 89.97 281 | 89.90 279 | 90.16 302 | 94.24 309 | 74.98 320 | 89.89 310 | 89.06 323 | 92.02 219 | 89.97 310 | 90.77 317 | 73.92 311 | 98.57 286 | 91.88 202 | 97.36 270 | 96.92 278 |
|
FPMVS | | | 89.92 282 | 88.63 289 | 93.82 266 | 98.37 147 | 96.94 41 | 91.58 295 | 93.34 299 | 88.00 261 | 90.32 308 | 97.10 197 | 70.87 319 | 91.13 329 | 71.91 325 | 96.16 292 | 93.39 317 |
|
CostFormer | | | 89.75 283 | 89.25 282 | 91.26 295 | 94.69 301 | 78.00 313 | 95.32 180 | 91.98 312 | 81.50 305 | 90.55 305 | 96.96 204 | 71.06 318 | 98.89 258 | 88.59 265 | 92.63 312 | 96.87 281 |
|
PatchFormer-LS_test | | | 89.62 284 | 89.12 287 | 91.11 297 | 93.62 316 | 78.42 309 | 94.57 217 | 93.62 296 | 88.39 255 | 90.54 306 | 88.40 324 | 72.33 315 | 99.03 242 | 92.41 196 | 88.20 321 | 95.89 300 |
|
E-PMN | | | 89.52 285 | 89.78 280 | 88.73 307 | 93.14 320 | 77.61 314 | 83.26 325 | 92.02 311 | 94.82 153 | 93.71 261 | 93.11 300 | 75.31 308 | 96.81 321 | 85.81 289 | 96.81 281 | 91.77 321 |
|
EPMVS | | | 89.26 286 | 88.55 290 | 91.39 293 | 92.36 326 | 79.11 307 | 95.65 159 | 79.86 330 | 88.60 252 | 93.12 279 | 96.53 231 | 70.73 320 | 98.10 310 | 90.75 228 | 89.32 319 | 96.98 276 |
|
EMVS | | | 89.06 287 | 89.22 283 | 88.61 308 | 93.00 322 | 77.34 315 | 82.91 326 | 90.92 319 | 94.64 157 | 92.63 288 | 91.81 313 | 76.30 304 | 97.02 319 | 83.83 306 | 96.90 277 | 91.48 322 |
|
1111 | | | 88.78 288 | 89.39 281 | 86.96 313 | 98.53 137 | 62.84 331 | 91.49 296 | 97.48 235 | 94.45 163 | 96.56 182 | 96.45 236 | 43.83 337 | 98.87 262 | 86.33 286 | 99.40 144 | 99.18 126 |
|
IB-MVS | | 85.98 20 | 88.63 289 | 86.95 298 | 93.68 267 | 95.12 296 | 84.82 291 | 90.85 303 | 90.17 322 | 87.55 264 | 88.48 316 | 91.34 315 | 58.01 329 | 99.59 136 | 87.24 282 | 93.80 308 | 96.63 292 |
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 |
tpm2 | | | 88.47 290 | 87.69 293 | 90.79 299 | 94.98 298 | 77.34 315 | 95.09 193 | 91.83 313 | 77.51 322 | 89.40 312 | 96.41 239 | 67.83 324 | 98.73 274 | 83.58 309 | 92.60 313 | 96.29 297 |
|
tpmp4_e23 | | | 88.46 291 | 87.54 294 | 91.22 296 | 94.56 304 | 78.08 311 | 95.63 162 | 93.17 300 | 79.08 316 | 85.85 324 | 96.80 215 | 65.86 326 | 98.85 265 | 84.10 303 | 92.85 310 | 96.72 288 |
|
MVS-HIRNet | | | 88.40 292 | 90.20 278 | 82.99 316 | 97.01 258 | 60.04 333 | 93.11 271 | 85.61 327 | 84.45 295 | 88.72 315 | 99.09 45 | 84.72 274 | 98.23 306 | 82.52 310 | 96.59 286 | 90.69 324 |
|
gg-mvs-nofinetune | | | 88.28 293 | 86.96 297 | 92.23 288 | 92.84 324 | 84.44 292 | 98.19 40 | 74.60 332 | 99.08 9 | 87.01 322 | 99.47 8 | 56.93 330 | 98.23 306 | 78.91 317 | 95.61 299 | 94.01 313 |
|
dp | | | 88.08 294 | 88.05 292 | 88.16 311 | 92.85 323 | 68.81 328 | 94.17 231 | 92.88 304 | 85.47 284 | 91.38 300 | 96.14 252 | 68.87 323 | 98.81 268 | 86.88 283 | 83.80 327 | 96.87 281 |
|
tpm cat1 | | | 88.01 295 | 87.33 295 | 90.05 304 | 94.48 306 | 76.28 318 | 94.47 218 | 94.35 289 | 73.84 327 | 89.26 313 | 95.61 268 | 73.64 313 | 98.30 304 | 84.13 302 | 86.20 324 | 95.57 306 |
|
test12356 | | | 87.98 296 | 88.41 291 | 86.69 314 | 95.84 284 | 63.49 330 | 87.15 319 | 97.32 239 | 87.21 266 | 91.78 297 | 93.36 298 | 70.66 321 | 98.39 297 | 74.70 320 | 97.64 262 | 98.19 236 |
|
test-mter | | | 87.92 297 | 87.17 296 | 90.16 302 | 94.24 309 | 74.98 320 | 89.89 310 | 89.06 323 | 86.44 274 | 89.97 310 | 90.77 317 | 54.96 333 | 98.57 286 | 91.88 202 | 97.36 270 | 96.92 278 |
|
DWT-MVSNet_test | | | 87.92 297 | 86.77 299 | 91.39 293 | 93.18 319 | 78.62 308 | 95.10 191 | 91.42 316 | 85.58 282 | 88.00 317 | 88.73 323 | 60.60 328 | 98.90 255 | 90.60 233 | 87.70 322 | 96.65 289 |
|
PAPM | | | 87.64 299 | 85.84 302 | 93.04 275 | 96.54 269 | 84.99 288 | 88.42 317 | 95.57 280 | 79.52 313 | 83.82 326 | 93.05 302 | 80.57 284 | 98.41 295 | 62.29 329 | 92.79 311 | 95.71 302 |
|
TESTMET0.1,1 | | | 87.20 300 | 86.57 300 | 89.07 306 | 93.62 316 | 72.84 325 | 89.89 310 | 87.01 326 | 85.46 285 | 89.12 314 | 90.20 321 | 56.00 332 | 97.72 315 | 90.91 222 | 96.92 276 | 96.64 290 |
|
MVE | | 73.61 22 | 86.48 301 | 85.92 301 | 88.18 310 | 96.23 277 | 85.28 283 | 81.78 328 | 75.79 331 | 86.01 277 | 82.53 328 | 91.88 312 | 92.74 183 | 87.47 331 | 71.42 326 | 94.86 303 | 91.78 320 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
test2356 | | | 85.45 302 | 83.26 305 | 92.01 290 | 91.12 328 | 80.76 302 | 85.16 322 | 92.90 303 | 83.90 297 | 90.63 302 | 87.71 326 | 53.10 334 | 97.24 318 | 69.20 327 | 95.65 298 | 98.03 247 |
|
PVSNet_0 | | 81.89 21 | 84.49 303 | 83.21 306 | 88.34 309 | 95.76 287 | 74.97 322 | 83.49 324 | 92.70 308 | 78.47 318 | 87.94 318 | 86.90 327 | 83.38 277 | 96.63 324 | 73.44 323 | 66.86 330 | 93.40 316 |
|
PNet_i23d | | | 83.82 304 | 83.39 304 | 85.10 315 | 96.07 281 | 65.16 329 | 81.87 327 | 94.37 288 | 90.87 235 | 93.92 256 | 92.89 304 | 52.80 335 | 96.44 325 | 77.52 319 | 70.22 329 | 93.70 314 |
|
testpf | | | 82.70 305 | 84.35 303 | 77.74 317 | 88.97 332 | 73.23 324 | 93.85 245 | 84.33 328 | 88.10 259 | 85.06 325 | 90.42 320 | 52.62 336 | 91.05 330 | 91.00 219 | 84.82 326 | 68.93 327 |
|
.test1245 | | | 73.49 306 | 79.27 307 | 56.15 319 | 98.53 137 | 62.84 331 | 91.49 296 | 97.48 235 | 94.45 163 | 96.56 182 | 96.45 236 | 43.83 337 | 98.87 262 | 86.33 286 | 8.32 332 | 6.75 330 |
|
tmp_tt | | | 57.23 307 | 62.50 308 | 41.44 320 | 34.77 334 | 49.21 335 | 83.93 323 | 60.22 336 | 15.31 330 | 71.11 331 | 79.37 329 | 70.09 322 | 44.86 333 | 64.76 328 | 82.93 328 | 30.25 328 |
|
pcd1.5k->3k | | | 41.47 308 | 44.19 309 | 33.29 321 | 99.65 11 | 0.00 338 | 0.00 329 | 99.07 34 | 0.00 333 | 0.00 334 | 0.00 335 | 99.04 4 | 0.00 336 | 0.00 333 | 99.96 11 | 99.87 2 |
|
cdsmvs_eth3d_5k | | | 24.22 309 | 32.30 310 | 0.00 324 | 0.00 337 | 0.00 338 | 0.00 329 | 98.10 196 | 0.00 333 | 0.00 334 | 95.06 278 | 97.54 28 | 0.00 336 | 0.00 333 | 0.00 334 | 0.00 332 |
|
test123 | | | 12.59 310 | 15.49 311 | 3.87 322 | 6.07 335 | 2.55 336 | 90.75 304 | 2.59 338 | 2.52 331 | 5.20 333 | 13.02 332 | 4.96 339 | 1.85 335 | 5.20 331 | 9.09 331 | 7.23 329 |
|
testmvs | | | 12.33 311 | 15.23 312 | 3.64 323 | 5.77 336 | 2.23 337 | 88.99 314 | 3.62 337 | 2.30 332 | 5.29 332 | 13.09 331 | 4.52 340 | 1.95 334 | 5.16 332 | 8.32 332 | 6.75 330 |
|
pcd_1.5k_mvsjas | | | 7.98 312 | 10.65 313 | 0.00 324 | 0.00 337 | 0.00 338 | 0.00 329 | 0.00 339 | 0.00 333 | 0.00 334 | 0.00 335 | 95.82 87 | 0.00 336 | 0.00 333 | 0.00 334 | 0.00 332 |
|
ab-mvs-re | | | 7.91 313 | 10.55 314 | 0.00 324 | 0.00 337 | 0.00 338 | 0.00 329 | 0.00 339 | 0.00 333 | 0.00 334 | 94.94 280 | 0.00 341 | 0.00 336 | 0.00 333 | 0.00 334 | 0.00 332 |
|
sosnet-low-res | | | 0.00 314 | 0.00 315 | 0.00 324 | 0.00 337 | 0.00 338 | 0.00 329 | 0.00 339 | 0.00 333 | 0.00 334 | 0.00 335 | 0.00 341 | 0.00 336 | 0.00 333 | 0.00 334 | 0.00 332 |
|
sosnet | | | 0.00 314 | 0.00 315 | 0.00 324 | 0.00 337 | 0.00 338 | 0.00 329 | 0.00 339 | 0.00 333 | 0.00 334 | 0.00 335 | 0.00 341 | 0.00 336 | 0.00 333 | 0.00 334 | 0.00 332 |
|
uncertanet | | | 0.00 314 | 0.00 315 | 0.00 324 | 0.00 337 | 0.00 338 | 0.00 329 | 0.00 339 | 0.00 333 | 0.00 334 | 0.00 335 | 0.00 341 | 0.00 336 | 0.00 333 | 0.00 334 | 0.00 332 |
|
Regformer | | | 0.00 314 | 0.00 315 | 0.00 324 | 0.00 337 | 0.00 338 | 0.00 329 | 0.00 339 | 0.00 333 | 0.00 334 | 0.00 335 | 0.00 341 | 0.00 336 | 0.00 333 | 0.00 334 | 0.00 332 |
|
uanet | | | 0.00 314 | 0.00 315 | 0.00 324 | 0.00 337 | 0.00 338 | 0.00 329 | 0.00 339 | 0.00 333 | 0.00 334 | 0.00 335 | 0.00 341 | 0.00 336 | 0.00 333 | 0.00 334 | 0.00 332 |
|
sam_mvs1 | | | | | | | | | | | | | 77.80 293 | | | | |
|
sam_mvs | | | | | | | | | | | | | 77.38 297 | | | | |
|
semantic-postprocess | | | | | 94.85 245 | 97.68 221 | 85.53 279 | | 97.63 229 | 96.99 79 | 98.36 75 | 98.54 79 | 87.44 257 | 99.75 52 | 97.07 69 | 99.08 185 | 99.27 118 |
|
ambc | | | | | 96.56 165 | 98.23 162 | 91.68 181 | 97.88 57 | 98.13 194 | | 98.42 72 | 98.56 77 | 94.22 143 | 99.04 239 | 94.05 171 | 99.35 152 | 98.95 161 |
|
MTGPA | | | | | | | | | 98.73 109 | | | | | | | | |
|
test_post1 | | | | | | | | 94.98 203 | | | | 10.37 334 | 76.21 305 | 99.04 239 | 89.47 252 | | |
|
test_post | | | | | | | | | | | | 10.87 333 | 76.83 301 | 99.07 236 | | | |
|
patchmatchnet-post | | | | | | | | | | | | 96.84 211 | 77.36 298 | 99.42 179 | | | |
|
GG-mvs-BLEND | | | | | 90.60 300 | 91.00 329 | 84.21 293 | 98.23 34 | 72.63 335 | | 82.76 327 | 84.11 328 | 56.14 331 | 96.79 322 | 72.20 324 | 92.09 314 | 90.78 323 |
|
MTMP | | | | | | | | | 74.60 332 | | | | | | | | |
|
gm-plane-assit | | | | | | 91.79 327 | 71.40 327 | | | 81.67 303 | | 90.11 322 | | 98.99 246 | 84.86 299 | | |
|
test9_res | | | | | | | | | | | | | | | 91.29 213 | 98.89 207 | 99.00 155 |
|
TEST9 | | | | | | 97.84 199 | 95.23 87 | 93.62 254 | 98.39 157 | 86.81 271 | 93.78 258 | 95.99 254 | 94.68 124 | 99.52 155 | | | |
|
test_8 | | | | | | 97.81 202 | 95.07 95 | 93.54 257 | 98.38 159 | 87.04 269 | 93.71 261 | 95.96 258 | 94.58 129 | 99.52 155 | | | |
|
agg_prior2 | | | | | | | | | | | | | | | 90.34 242 | 98.90 203 | 99.10 146 |
|
agg_prior | | | | | | 97.80 206 | 94.96 98 | | 98.36 161 | | 93.49 269 | | | 99.53 151 | | | |
|
TestCases | | | | | 98.06 73 | 99.08 78 | 96.16 61 | | 99.16 16 | 94.35 169 | 97.78 138 | 98.07 125 | 95.84 84 | 99.12 229 | 91.41 211 | 99.42 137 | 98.91 168 |
|
test_prior4 | | | | | | | 95.38 83 | 93.61 256 | | | | | | | | | |
|
test_prior2 | | | | | | | | 93.33 266 | | 94.21 174 | 94.02 252 | 96.25 246 | 93.64 161 | | 91.90 200 | 98.96 197 | |
|
test_prior | | | | | 97.46 116 | 97.79 211 | 94.26 121 | | 98.42 155 | | | | | 99.34 205 | | | 98.79 183 |
|
旧先验2 | | | | | | | | 93.35 265 | | 77.95 321 | 95.77 214 | | | 98.67 282 | 90.74 229 | | |
|
新几何2 | | | | | | | | 93.43 261 | | | | | | | | | |
|
新几何1 | | | | | 97.25 131 | 98.29 152 | 94.70 107 | | 97.73 217 | 77.98 319 | 94.83 231 | 96.67 223 | 92.08 203 | 99.45 174 | 88.17 271 | 98.65 226 | 97.61 263 |
|
旧先验1 | | | | | | 97.80 206 | 93.87 132 | | 97.75 215 | | | 97.04 200 | 93.57 163 | | | 98.68 224 | 98.72 190 |
|
无先验 | | | | | | | | 93.20 269 | 97.91 206 | 80.78 308 | | | | 99.40 188 | 87.71 273 | | 97.94 252 |
|
原ACMM2 | | | | | | | | 92.82 274 | | | | | | | | | |
|
原ACMM1 | | | | | 96.58 162 | 98.16 171 | 92.12 170 | | 98.15 192 | 85.90 280 | 93.49 269 | 96.43 238 | 92.47 195 | 99.38 199 | 87.66 276 | 98.62 228 | 98.23 231 |
|
test222 | | | | | | 98.17 169 | 93.24 153 | 92.74 278 | 97.61 231 | 75.17 324 | 94.65 234 | 96.69 222 | 90.96 223 | | | 98.66 225 | 97.66 261 |
|
testdata2 | | | | | | | | | | | | | | 99.46 170 | 87.84 272 | | |
|
segment_acmp | | | | | | | | | | | | | 95.34 105 | | | | |
|
testdata | | | | | 95.70 218 | 98.16 171 | 90.58 195 | | 97.72 218 | 80.38 310 | 95.62 217 | 97.02 201 | 92.06 205 | 98.98 248 | 89.06 258 | 98.52 233 | 97.54 266 |
|
testdata1 | | | | | | | | 92.77 275 | | 93.78 183 | | | | | | | |
|
test12 | | | | | 97.46 116 | 97.61 228 | 94.07 126 | | 97.78 214 | | 93.57 267 | | 93.31 171 | 99.42 179 | | 98.78 214 | 98.89 170 |
|
plane_prior7 | | | | | | 98.70 112 | 94.67 108 | | | | | | | | | | |
|
plane_prior6 | | | | | | 98.38 146 | 94.37 117 | | | | | | 91.91 211 | | | | |
|
plane_prior5 | | | | | | | | | 98.75 106 | | | | | 99.46 170 | 92.59 193 | 99.20 173 | 99.28 115 |
|
plane_prior4 | | | | | | | | | | | | 96.77 217 | | | | | |
|
plane_prior3 | | | | | | | 94.51 111 | | | 95.29 133 | 96.16 202 | | | | | | |
|
plane_prior2 | | | | | | | | 96.50 113 | | 96.36 95 | | | | | | | |
|
plane_prior1 | | | | | | 98.49 141 | | | | | | | | | | | |
|
plane_prior | | | | | | | 94.29 118 | 95.42 171 | | 94.31 171 | | | | | | 98.93 202 | |
|
n2 | | | | | | | | | 0.00 339 | | | | | | | | |
|
nn | | | | | | | | | 0.00 339 | | | | | | | | |
|
door-mid | | | | | | | | | 98.17 189 | | | | | | | | |
|
lessismore_v0 | | | | | 97.05 139 | 99.36 45 | 92.12 170 | | 84.07 329 | | 98.77 49 | 98.98 50 | 85.36 268 | 99.74 57 | 97.34 59 | 99.37 146 | 99.30 108 |
|
LGP-MVS_train | | | | | 98.74 32 | 99.15 66 | 97.02 38 | | 99.02 50 | 95.15 141 | 98.34 77 | 98.23 104 | 97.91 19 | 99.70 84 | 94.41 154 | 99.73 55 | 99.50 50 |
|
test11 | | | | | | | | | 98.08 199 | | | | | | | | |
|
door | | | | | | | | | 97.81 213 | | | | | | | | |
|
HQP5-MVS | | | | | | | 92.47 161 | | | | | | | | | | |
|
HQP-NCC | | | | | | 97.85 195 | | 94.26 221 | | 93.18 193 | 92.86 282 | | | | | | |
|
ACMP_Plane | | | | | | 97.85 195 | | 94.26 221 | | 93.18 193 | 92.86 282 | | | | | | |
|
BP-MVS | | | | | | | | | | | | | | | 90.51 236 | | |
|
HQP4-MVS | | | | | | | | | | | 92.87 281 | | | 99.23 222 | | | 99.06 151 |
|
HQP3-MVS | | | | | | | | | 98.43 152 | | | | | | | 98.74 218 | |
|
HQP2-MVS | | | | | | | | | | | | | 90.33 228 | | | | |
|
NP-MVS | | | | | | 98.14 174 | 93.72 138 | | | | | 95.08 276 | | | | | |
|
MDTV_nov1_ep13_2view | | | | | | | 57.28 334 | 94.89 205 | | 80.59 309 | 94.02 252 | | 78.66 291 | | 85.50 294 | | 97.82 256 |
|
MDTV_nov1_ep13 | | | | 91.28 264 | | 94.31 307 | 73.51 323 | 94.80 210 | 93.16 301 | 86.75 273 | 93.45 272 | 97.40 181 | 76.37 303 | 98.55 289 | 88.85 260 | 96.43 287 | |
|
ACMMP++_ref | | | | | | | | | | | | | | | | 99.52 106 | |
|
ACMMP++ | | | | | | | | | | | | | | | | 99.55 98 | |
|
Test By Simon | | | | | | | | | | | | | 94.51 133 | | | | |
|
ITE_SJBPF | | | | | 97.85 85 | 98.64 118 | 96.66 48 | | 98.51 145 | 95.63 119 | 97.22 157 | 97.30 189 | 95.52 98 | 98.55 289 | 90.97 220 | 98.90 203 | 98.34 221 |
|
DeepMVS_CX | | | | | 77.17 318 | 90.94 330 | 85.28 283 | | 74.08 334 | 52.51 329 | 80.87 330 | 88.03 325 | 75.25 309 | 70.63 332 | 59.23 330 | 84.94 325 | 75.62 325 |
|