LTVRE_ROB | | 99.39 1 | 99.90 1 | 99.87 1 | 99.93 1 | 99.97 1 | 99.82 6 | 99.91 5 | 99.92 43 | 99.75 7 | 99.93 4 | 99.89 42 | 100.00 1 | 99.87 2 | 99.93 4 | 99.82 6 | 99.96 3 | 99.90 2 |
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 |
v748 | | | 99.89 2 | 99.87 1 | 99.92 4 | 99.96 8 | 99.80 11 | 99.91 5 | 99.95 28 | 99.77 5 | 99.92 8 | 99.96 5 | 99.93 39 | 99.81 9 | 99.92 7 | 99.82 6 | 99.96 3 | 99.90 2 |
|
v7n | | | 99.89 2 | 99.86 4 | 99.93 1 | 99.97 1 | 99.83 2 | 99.93 1 | 99.96 14 | 99.77 5 | 99.89 18 | 99.99 1 | 99.86 70 | 99.84 5 | 99.89 9 | 99.81 10 | 99.97 1 | 99.88 9 |
|
v52 | | | 99.89 2 | 99.85 6 | 99.92 4 | 99.97 1 | 99.80 11 | 99.92 2 | 99.97 1 | 99.78 3 | 99.90 14 | 99.96 5 | 99.85 76 | 99.82 7 | 99.88 12 | 99.82 6 | 99.96 3 | 99.89 5 |
|
V4 | | | 99.89 2 | 99.85 6 | 99.92 4 | 99.97 1 | 99.80 11 | 99.92 2 | 99.97 1 | 99.78 3 | 99.90 14 | 99.96 5 | 99.84 78 | 99.82 7 | 99.88 12 | 99.82 6 | 99.96 3 | 99.89 5 |
|
SixPastTwentyTwo | | | 99.89 2 | 99.85 6 | 99.93 1 | 99.97 1 | 99.88 1 | 99.92 2 | 99.97 1 | 99.66 14 | 99.94 3 | 99.94 15 | 99.74 96 | 99.81 9 | 99.97 2 | 99.89 1 | 99.96 3 | 99.89 5 |
|
pmmvs6 | | | 99.88 7 | 99.87 1 | 99.89 12 | 99.97 1 | 99.76 18 | 99.89 8 | 99.96 14 | 99.82 2 | 99.90 14 | 99.92 26 | 99.95 22 | 99.68 39 | 99.93 4 | 99.88 2 | 99.95 9 | 99.86 12 |
|
anonymousdsp | | | 99.87 8 | 99.86 4 | 99.88 15 | 99.95 11 | 99.75 23 | 99.90 7 | 99.96 14 | 99.69 10 | 99.83 54 | 99.96 5 | 99.99 3 | 99.74 26 | 99.95 3 | 99.83 3 | 99.91 24 | 99.88 9 |
|
FC-MVSNet-test | | | 99.84 9 | 99.80 9 | 99.89 12 | 99.96 8 | 99.83 2 | 99.84 17 | 99.95 28 | 99.37 58 | 99.77 76 | 99.95 10 | 99.96 13 | 99.85 3 | 99.93 4 | 99.83 3 | 99.95 9 | 99.72 48 |
|
TDRefinement | | | 99.81 10 | 99.76 11 | 99.86 18 | 99.83 101 | 99.53 69 | 99.89 8 | 99.91 48 | 99.73 8 | 99.88 23 | 99.83 62 | 99.96 13 | 99.76 19 | 99.91 8 | 99.81 10 | 99.86 54 | 99.59 78 |
|
WR-MVS | | | 99.79 11 | 99.68 16 | 99.91 8 | 99.95 11 | 99.83 2 | 99.87 12 | 99.96 14 | 99.39 57 | 99.93 4 | 99.87 50 | 99.29 156 | 99.77 17 | 99.83 20 | 99.72 20 | 99.97 1 | 99.82 16 |
|
MIMVSNet1 | | | 99.79 11 | 99.75 12 | 99.84 24 | 99.89 40 | 99.83 2 | 99.84 17 | 99.89 57 | 99.31 64 | 99.93 4 | 99.92 26 | 99.97 9 | 99.68 39 | 99.89 9 | 99.64 27 | 99.82 77 | 99.66 61 |
|
pm-mvs1 | | | 99.77 13 | 99.69 15 | 99.86 18 | 99.94 21 | 99.68 37 | 99.84 17 | 99.93 35 | 99.59 28 | 99.87 29 | 99.92 26 | 99.21 159 | 99.65 54 | 99.88 12 | 99.77 13 | 99.93 18 | 99.78 28 |
|
PEN-MVS | | | 99.77 13 | 99.65 19 | 99.91 8 | 99.95 11 | 99.80 11 | 99.86 13 | 99.97 1 | 99.08 94 | 99.89 18 | 99.69 81 | 99.68 104 | 99.84 5 | 99.81 24 | 99.64 27 | 99.95 9 | 99.81 19 |
|
EU-MVSNet | | | 99.76 15 | 99.74 13 | 99.78 49 | 99.82 106 | 99.81 9 | 99.88 10 | 99.87 63 | 99.31 64 | 99.75 86 | 99.91 35 | 99.76 95 | 99.78 15 | 99.84 19 | 99.74 17 | 99.56 157 | 99.81 19 |
|
Vis-MVSNet | ![Method available under a permissive open source license. permissive](img/icon_permissive.png) | | 99.76 15 | 99.78 10 | 99.75 63 | 99.92 27 | 99.77 17 | 99.83 20 | 99.85 82 | 99.43 50 | 99.85 41 | 99.84 60 | 100.00 1 | 99.13 137 | 99.83 20 | 99.66 25 | 99.90 27 | 99.90 2 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
DTE-MVSNet | | | 99.75 17 | 99.61 27 | 99.92 4 | 99.95 11 | 99.81 9 | 99.86 13 | 99.96 14 | 99.18 81 | 99.92 8 | 99.66 84 | 99.45 138 | 99.85 3 | 99.80 25 | 99.56 33 | 99.96 3 | 99.79 25 |
|
tfpnnormal | | | 99.74 18 | 99.63 22 | 99.86 18 | 99.93 24 | 99.75 23 | 99.80 29 | 99.89 57 | 99.31 64 | 99.88 23 | 99.43 120 | 99.66 107 | 99.77 17 | 99.80 25 | 99.71 21 | 99.92 22 | 99.76 34 |
|
DeepC-MVS | | 99.05 5 | 99.74 18 | 99.64 20 | 99.84 24 | 99.90 35 | 99.39 105 | 99.79 31 | 99.81 122 | 99.69 10 | 99.90 14 | 99.87 50 | 99.98 4 | 99.81 9 | 99.62 51 | 99.32 65 | 99.83 73 | 99.65 65 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
thisisatest0515 | | | 99.73 20 | 99.67 17 | 99.81 34 | 99.93 24 | 99.74 25 | 99.68 71 | 99.91 48 | 99.59 28 | 99.88 23 | 99.73 72 | 99.81 84 | 99.55 71 | 99.59 52 | 99.53 43 | 99.89 32 | 99.70 53 |
|
v13 | | | 99.73 20 | 99.63 22 | 99.85 21 | 99.87 52 | 99.71 29 | 99.80 29 | 99.96 14 | 99.62 22 | 99.83 54 | 99.93 19 | 99.66 107 | 99.75 21 | 99.41 73 | 99.26 70 | 99.89 32 | 99.80 24 |
|
PS-CasMVS | | | 99.73 20 | 99.59 33 | 99.90 11 | 99.95 11 | 99.80 11 | 99.85 16 | 99.97 1 | 98.95 112 | 99.86 34 | 99.73 72 | 99.36 147 | 99.81 9 | 99.83 20 | 99.67 24 | 99.95 9 | 99.83 15 |
|
WR-MVS_H | | | 99.73 20 | 99.61 27 | 99.88 15 | 99.95 11 | 99.82 6 | 99.83 20 | 99.96 14 | 99.01 105 | 99.84 45 | 99.71 79 | 99.41 144 | 99.74 26 | 99.77 30 | 99.70 22 | 99.95 9 | 99.82 16 |
|
no-one | | | 99.73 20 | 99.70 14 | 99.76 57 | 99.77 132 | 99.58 55 | 99.76 39 | 99.90 56 | 99.08 94 | 99.86 34 | 99.90 39 | 99.98 4 | 99.66 51 | 99.98 1 | 99.73 18 | 99.59 150 | 99.67 59 |
|
v12 | | | 99.72 25 | 99.61 27 | 99.85 21 | 99.86 69 | 99.70 34 | 99.79 31 | 99.96 14 | 99.61 23 | 99.83 54 | 99.93 19 | 99.61 111 | 99.74 26 | 99.38 75 | 99.22 72 | 99.89 32 | 99.79 25 |
|
v11 | | | 99.72 25 | 99.62 25 | 99.85 21 | 99.87 52 | 99.71 29 | 99.81 26 | 99.96 14 | 99.63 19 | 99.83 54 | 99.97 4 | 99.58 118 | 99.75 21 | 99.33 87 | 99.33 63 | 99.87 48 | 99.79 25 |
|
TransMVSNet (Re) | | | 99.72 25 | 99.59 33 | 99.88 15 | 99.95 11 | 99.76 18 | 99.88 10 | 99.94 31 | 99.58 31 | 99.92 8 | 99.90 39 | 98.55 177 | 99.65 54 | 99.89 9 | 99.76 14 | 99.95 9 | 99.70 53 |
|
ACMH | | 99.11 4 | 99.72 25 | 99.63 22 | 99.84 24 | 99.87 52 | 99.59 53 | 99.83 20 | 99.88 61 | 99.46 47 | 99.87 29 | 99.66 84 | 99.95 22 | 99.76 19 | 99.73 35 | 99.47 51 | 99.84 62 | 99.52 109 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
V9 | | | 99.71 29 | 99.59 33 | 99.84 24 | 99.86 69 | 99.69 36 | 99.78 34 | 99.96 14 | 99.61 23 | 99.84 45 | 99.93 19 | 99.61 111 | 99.73 30 | 99.34 85 | 99.17 78 | 99.88 37 | 99.78 28 |
|
FC-MVSNet-train | | | 99.70 30 | 99.67 17 | 99.74 69 | 99.94 21 | 99.71 29 | 99.82 24 | 99.91 48 | 99.14 90 | 99.53 145 | 99.70 80 | 99.88 64 | 99.33 108 | 99.88 12 | 99.61 32 | 99.94 16 | 99.77 30 |
|
COLMAP_ROB | ![Method available under an open source license with copyleft or other restrictive terms. copyleft](img/icon_copyleft.png) | 99.18 2 | 99.70 30 | 99.60 31 | 99.81 34 | 99.84 90 | 99.37 116 | 99.76 39 | 99.84 95 | 99.54 40 | 99.82 61 | 99.64 87 | 99.95 22 | 99.75 21 | 99.79 27 | 99.56 33 | 99.83 73 | 99.37 149 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
V14 | | | 99.69 32 | 99.56 38 | 99.84 24 | 99.86 69 | 99.68 37 | 99.78 34 | 99.96 14 | 99.60 27 | 99.83 54 | 99.93 19 | 99.58 118 | 99.72 34 | 99.28 102 | 99.11 93 | 99.88 37 | 99.77 30 |
|
ACMH+ | | 98.94 6 | 99.69 32 | 99.59 33 | 99.81 34 | 99.88 45 | 99.41 102 | 99.75 45 | 99.86 67 | 99.43 50 | 99.80 66 | 99.54 102 | 99.97 9 | 99.73 30 | 99.82 23 | 99.52 45 | 99.85 58 | 99.43 130 |
|
test20.03 | | | 99.68 34 | 99.60 31 | 99.76 57 | 99.91 32 | 99.70 34 | 99.68 71 | 99.87 63 | 99.05 101 | 99.88 23 | 99.92 26 | 99.88 64 | 99.50 85 | 99.77 30 | 99.42 58 | 99.75 97 | 99.49 115 |
|
CP-MVSNet | | | 99.68 34 | 99.51 45 | 99.89 12 | 99.95 11 | 99.76 18 | 99.83 20 | 99.96 14 | 98.83 129 | 99.84 45 | 99.65 86 | 99.09 163 | 99.80 13 | 99.78 28 | 99.62 31 | 99.95 9 | 99.82 16 |
|
v15 | | | 99.67 36 | 99.54 41 | 99.83 29 | 99.86 69 | 99.67 40 | 99.76 39 | 99.95 28 | 99.59 28 | 99.83 54 | 99.93 19 | 99.55 122 | 99.71 38 | 99.23 111 | 99.05 101 | 99.87 48 | 99.75 37 |
|
PVSNet_Blended_VisFu | | | 99.66 37 | 99.64 20 | 99.67 83 | 99.91 32 | 99.71 29 | 99.61 86 | 99.79 131 | 99.41 53 | 99.91 12 | 99.85 57 | 99.61 111 | 99.00 147 | 99.67 42 | 99.42 58 | 99.81 81 | 99.81 19 |
|
v10 | | | 99.65 38 | 99.51 45 | 99.81 34 | 99.83 101 | 99.61 47 | 99.75 45 | 99.94 31 | 99.56 36 | 99.76 79 | 99.94 15 | 99.60 115 | 99.73 30 | 99.11 140 | 99.01 108 | 99.85 58 | 99.74 41 |
|
CHOSEN 1792x2688 | | | 99.65 38 | 99.55 39 | 99.77 53 | 99.93 24 | 99.60 49 | 99.79 31 | 99.92 43 | 99.73 8 | 99.74 92 | 99.93 19 | 99.98 4 | 99.80 13 | 98.83 188 | 99.01 108 | 99.45 171 | 99.76 34 |
|
UA-Net | | | 99.64 40 | 99.62 25 | 99.66 85 | 99.97 1 | 99.82 6 | 99.14 179 | 99.96 14 | 98.95 112 | 99.52 151 | 99.38 128 | 99.86 70 | 99.55 71 | 99.72 36 | 99.66 25 | 99.80 84 | 99.94 1 |
|
v17 | | | 99.62 41 | 99.48 48 | 99.79 46 | 99.80 111 | 99.60 49 | 99.73 57 | 99.94 31 | 99.46 47 | 99.73 98 | 99.88 48 | 99.52 127 | 99.67 43 | 99.16 133 | 98.96 118 | 99.84 62 | 99.75 37 |
|
Baseline_NR-MVSNet | | | 99.62 41 | 99.48 48 | 99.78 49 | 99.85 82 | 99.76 18 | 99.59 91 | 99.82 111 | 98.84 127 | 99.88 23 | 99.91 35 | 99.04 165 | 99.61 62 | 99.46 64 | 99.78 12 | 99.94 16 | 99.60 76 |
|
pmmvs-eth3d | | | 99.61 43 | 99.48 48 | 99.75 63 | 99.87 52 | 99.30 137 | 99.75 45 | 99.89 57 | 99.23 71 | 99.85 41 | 99.88 48 | 99.97 9 | 99.49 89 | 99.46 64 | 99.01 108 | 99.68 116 | 99.52 109 |
|
v1144 | | | 99.61 43 | 99.43 59 | 99.82 30 | 99.88 45 | 99.41 102 | 99.76 39 | 99.86 67 | 99.64 17 | 99.84 45 | 99.95 10 | 99.49 134 | 99.74 26 | 99.00 156 | 98.93 123 | 99.84 62 | 99.58 88 |
|
v16 | | | 99.61 43 | 99.47 52 | 99.78 49 | 99.79 119 | 99.60 49 | 99.72 62 | 99.94 31 | 99.45 49 | 99.70 109 | 99.85 57 | 99.54 125 | 99.67 43 | 99.15 134 | 98.96 118 | 99.83 73 | 99.76 34 |
|
v8 | | | 99.61 43 | 99.45 56 | 99.79 46 | 99.80 111 | 99.59 53 | 99.73 57 | 99.93 35 | 99.48 45 | 99.77 76 | 99.90 39 | 99.48 136 | 99.67 43 | 99.11 140 | 98.89 127 | 99.84 62 | 99.73 44 |
|
v7 | | | 99.61 43 | 99.46 55 | 99.79 46 | 99.83 101 | 99.37 116 | 99.75 45 | 99.84 95 | 99.56 36 | 99.76 79 | 99.94 15 | 99.60 115 | 99.73 30 | 99.11 140 | 99.01 108 | 99.85 58 | 99.63 69 |
|
CSCG | | | 99.61 43 | 99.52 44 | 99.71 73 | 99.89 40 | 99.62 44 | 99.52 107 | 99.76 151 | 99.61 23 | 99.69 111 | 99.73 72 | 99.96 13 | 99.57 69 | 99.27 105 | 98.62 166 | 99.81 81 | 99.85 14 |
|
v1192 | | | 99.60 49 | 99.41 63 | 99.82 30 | 99.89 40 | 99.43 97 | 99.81 26 | 99.84 95 | 99.63 19 | 99.85 41 | 99.95 10 | 99.35 150 | 99.72 34 | 99.01 154 | 98.90 126 | 99.82 77 | 99.58 88 |
|
APDe-MVS | | | 99.60 49 | 99.48 48 | 99.73 71 | 99.85 82 | 99.51 82 | 99.75 45 | 99.85 82 | 99.17 82 | 99.81 64 | 99.56 99 | 99.94 33 | 99.44 97 | 99.42 72 | 99.22 72 | 99.67 118 | 99.54 99 |
|
v1921920 | | | 99.59 51 | 99.40 66 | 99.82 30 | 99.88 45 | 99.45 91 | 99.81 26 | 99.83 103 | 99.65 15 | 99.86 34 | 99.95 10 | 99.29 156 | 99.75 21 | 98.98 160 | 98.86 135 | 99.78 88 | 99.59 78 |
|
v18 | | | 99.59 51 | 99.44 58 | 99.76 57 | 99.78 125 | 99.57 57 | 99.70 69 | 99.93 35 | 99.43 50 | 99.69 111 | 99.85 57 | 99.51 129 | 99.65 54 | 99.08 151 | 98.87 132 | 99.82 77 | 99.74 41 |
|
TranMVSNet+NR-MVSNet | | | 99.59 51 | 99.42 62 | 99.80 39 | 99.87 52 | 99.55 64 | 99.64 77 | 99.86 67 | 99.05 101 | 99.88 23 | 99.72 76 | 99.33 153 | 99.64 57 | 99.47 62 | 99.14 83 | 99.91 24 | 99.67 59 |
|
EG-PatchMatch MVS | | | 99.59 51 | 99.49 47 | 99.70 76 | 99.82 106 | 99.26 145 | 99.39 137 | 99.83 103 | 98.99 107 | 99.93 4 | 99.54 102 | 99.92 48 | 99.51 81 | 99.78 28 | 99.50 46 | 99.73 105 | 99.41 135 |
|
pmmvs5 | | | 99.58 55 | 99.47 52 | 99.70 76 | 99.84 90 | 99.50 83 | 99.58 95 | 99.80 128 | 98.98 110 | 99.73 98 | 99.92 26 | 99.81 84 | 99.49 89 | 99.28 102 | 99.05 101 | 99.77 92 | 99.73 44 |
|
v144192 | | | 99.58 55 | 99.39 70 | 99.80 39 | 99.87 52 | 99.44 93 | 99.77 36 | 99.84 95 | 99.64 17 | 99.86 34 | 99.93 19 | 99.35 150 | 99.72 34 | 98.92 168 | 98.82 141 | 99.74 101 | 99.66 61 |
|
v148 | | | 99.58 55 | 99.43 59 | 99.76 57 | 99.87 52 | 99.40 104 | 99.76 39 | 99.85 82 | 99.48 45 | 99.83 54 | 99.82 64 | 99.83 81 | 99.51 81 | 99.20 121 | 98.82 141 | 99.75 97 | 99.45 123 |
|
v1141 | | | 99.58 55 | 99.39 70 | 99.80 39 | 99.87 52 | 99.39 105 | 99.74 53 | 99.85 82 | 99.58 31 | 99.84 45 | 99.92 26 | 99.49 134 | 99.68 39 | 98.98 160 | 98.83 138 | 99.84 62 | 99.52 109 |
|
v1240 | | | 99.58 55 | 99.38 76 | 99.82 30 | 99.89 40 | 99.49 85 | 99.82 24 | 99.83 103 | 99.63 19 | 99.86 34 | 99.96 5 | 98.92 171 | 99.75 21 | 99.15 134 | 98.96 118 | 99.76 94 | 99.56 93 |
|
divwei89l23v2f112 | | | 99.58 55 | 99.39 70 | 99.80 39 | 99.87 52 | 99.39 105 | 99.74 53 | 99.85 82 | 99.57 34 | 99.84 45 | 99.92 26 | 99.48 136 | 99.67 43 | 98.98 160 | 98.83 138 | 99.84 62 | 99.52 109 |
|
v1 | | | 99.58 55 | 99.39 70 | 99.80 39 | 99.87 52 | 99.39 105 | 99.74 53 | 99.85 82 | 99.58 31 | 99.84 45 | 99.92 26 | 99.51 129 | 99.67 43 | 98.98 160 | 98.82 141 | 99.84 62 | 99.52 109 |
|
v1neww | | | 99.57 62 | 99.40 66 | 99.77 53 | 99.80 111 | 99.34 126 | 99.72 62 | 99.82 111 | 99.49 42 | 99.76 79 | 99.89 42 | 99.50 131 | 99.67 43 | 99.10 148 | 98.89 127 | 99.84 62 | 99.59 78 |
|
v7new | | | 99.57 62 | 99.40 66 | 99.77 53 | 99.80 111 | 99.34 126 | 99.72 62 | 99.82 111 | 99.49 42 | 99.76 79 | 99.89 42 | 99.50 131 | 99.67 43 | 99.10 148 | 98.89 127 | 99.84 62 | 99.59 78 |
|
v6 | | | 99.57 62 | 99.40 66 | 99.77 53 | 99.80 111 | 99.34 126 | 99.72 62 | 99.82 111 | 99.49 42 | 99.76 79 | 99.89 42 | 99.52 127 | 99.67 43 | 99.10 148 | 98.89 127 | 99.84 62 | 99.59 78 |
|
V42 | | | 99.57 62 | 99.41 63 | 99.75 63 | 99.84 90 | 99.37 116 | 99.73 57 | 99.83 103 | 99.41 53 | 99.75 86 | 99.89 42 | 99.42 142 | 99.60 64 | 99.15 134 | 98.96 118 | 99.76 94 | 99.65 65 |
|
TSAR-MVS + MP. | | | 99.56 66 | 99.54 41 | 99.58 103 | 99.69 165 | 99.14 167 | 99.73 57 | 99.45 211 | 99.50 41 | 99.35 187 | 99.60 95 | 99.93 39 | 99.50 85 | 99.56 54 | 99.37 62 | 99.77 92 | 99.64 68 |
|
v2v482 | | | 99.56 66 | 99.35 79 | 99.81 34 | 99.87 52 | 99.35 123 | 99.75 45 | 99.85 82 | 99.56 36 | 99.87 29 | 99.95 10 | 99.44 140 | 99.66 51 | 98.91 171 | 98.76 150 | 99.86 54 | 99.45 123 |
|
Gipuma | ![Method available under an open source license with copyleft or other restrictive terms. copyleft](img/icon_copyleft.png) | | 99.55 68 | 99.23 94 | 99.91 8 | 99.87 52 | 99.52 75 | 99.86 13 | 99.93 35 | 99.87 1 | 99.96 2 | 96.72 226 | 99.55 122 | 99.97 1 | 99.77 30 | 99.46 53 | 99.87 48 | 99.74 41 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
NR-MVSNet | | | 99.52 69 | 99.29 85 | 99.80 39 | 99.96 8 | 99.38 110 | 99.55 100 | 99.81 122 | 98.86 123 | 99.87 29 | 99.51 113 | 98.81 173 | 99.72 34 | 99.86 17 | 99.04 104 | 99.89 32 | 99.54 99 |
|
zzz-MVS | | | 99.51 70 | 99.36 77 | 99.68 81 | 99.88 45 | 99.38 110 | 99.53 104 | 99.84 95 | 99.11 93 | 99.59 136 | 98.93 169 | 99.95 22 | 99.58 68 | 99.44 70 | 99.21 74 | 99.65 122 | 99.52 109 |
|
ACMMPR | | | 99.51 70 | 99.32 82 | 99.72 72 | 99.87 52 | 99.33 130 | 99.61 86 | 99.85 82 | 99.19 79 | 99.73 98 | 98.73 178 | 99.95 22 | 99.61 62 | 99.35 82 | 99.14 83 | 99.66 120 | 99.58 88 |
|
UniMVSNet (Re) | | | 99.50 72 | 99.29 85 | 99.75 63 | 99.86 69 | 99.47 88 | 99.51 110 | 99.82 111 | 98.90 119 | 99.89 18 | 99.64 87 | 99.00 166 | 99.55 71 | 99.32 89 | 99.08 96 | 99.90 27 | 99.59 78 |
|
FMVSNet1 | | | 99.50 72 | 99.57 37 | 99.42 136 | 99.67 173 | 99.65 42 | 99.60 90 | 99.91 48 | 99.40 55 | 99.39 177 | 99.83 62 | 99.27 158 | 98.14 188 | 99.68 39 | 99.50 46 | 99.81 81 | 99.68 56 |
|
HyFIR lowres test | | | 99.50 72 | 99.26 89 | 99.80 39 | 99.95 11 | 99.62 44 | 99.76 39 | 99.97 1 | 99.67 12 | 99.56 142 | 99.94 15 | 98.40 181 | 99.78 15 | 98.84 187 | 98.59 169 | 99.76 94 | 99.72 48 |
|
PM-MVS | | | 99.49 75 | 99.43 59 | 99.57 107 | 99.76 137 | 99.34 126 | 99.53 104 | 99.77 143 | 98.93 116 | 99.75 86 | 99.46 117 | 99.83 81 | 99.11 139 | 99.72 36 | 99.29 67 | 99.49 167 | 99.46 122 |
|
Anonymous20231206 | | | 99.48 76 | 99.31 83 | 99.69 80 | 99.79 119 | 99.57 57 | 99.63 80 | 99.79 131 | 98.88 121 | 99.91 12 | 99.72 76 | 99.93 39 | 99.59 65 | 99.24 108 | 98.63 165 | 99.43 176 | 99.18 168 |
|
DU-MVS | | | 99.48 76 | 99.26 89 | 99.75 63 | 99.85 82 | 99.38 110 | 99.50 114 | 99.81 122 | 98.86 123 | 99.89 18 | 99.51 113 | 98.98 167 | 99.59 65 | 99.46 64 | 98.97 116 | 99.87 48 | 99.63 69 |
|
RPSCF | | | 99.48 76 | 99.45 56 | 99.52 118 | 99.73 154 | 99.33 130 | 99.13 180 | 99.77 143 | 99.33 62 | 99.47 162 | 99.39 127 | 99.92 48 | 99.36 102 | 99.63 48 | 99.13 89 | 99.63 134 | 99.41 135 |
|
ACMMP_Plus | | | 99.47 79 | 99.33 81 | 99.63 93 | 99.85 82 | 99.28 142 | 99.56 98 | 99.83 103 | 98.75 135 | 99.48 159 | 99.03 163 | 99.95 22 | 99.47 96 | 99.48 59 | 99.19 75 | 99.57 154 | 99.59 78 |
|
Anonymous20231211 | | | 99.47 79 | 99.39 70 | 99.57 107 | 99.89 40 | 99.60 49 | 99.50 114 | 99.69 171 | 98.91 118 | 99.62 128 | 99.17 148 | 99.35 150 | 98.86 163 | 99.63 48 | 99.46 53 | 99.84 62 | 99.62 73 |
|
SteuartSystems-ACMMP | | | 99.47 79 | 99.22 97 | 99.76 57 | 99.88 45 | 99.36 119 | 99.65 76 | 99.84 95 | 98.47 167 | 99.80 66 | 98.68 181 | 99.96 13 | 99.68 39 | 99.37 77 | 99.06 98 | 99.72 109 | 99.66 61 |
Skip Steuart: Steuart Systems R&D Blog. |
ACMM | | 98.37 12 | 99.47 79 | 99.23 94 | 99.74 69 | 99.86 69 | 99.19 161 | 99.68 71 | 99.86 67 | 99.16 86 | 99.71 107 | 98.52 189 | 99.95 22 | 99.62 61 | 99.35 82 | 99.02 106 | 99.74 101 | 99.42 134 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
HFP-MVS | | | 99.46 83 | 99.30 84 | 99.65 87 | 99.82 106 | 99.25 148 | 99.50 114 | 99.82 111 | 99.23 71 | 99.58 140 | 98.86 171 | 99.94 33 | 99.56 70 | 99.14 137 | 99.12 92 | 99.63 134 | 99.56 93 |
|
LGP-MVS_train | | | 99.46 83 | 99.18 109 | 99.78 49 | 99.87 52 | 99.25 148 | 99.71 68 | 99.87 63 | 98.02 198 | 99.79 69 | 98.90 170 | 99.96 13 | 99.66 51 | 99.49 58 | 99.17 78 | 99.79 87 | 99.49 115 |
|
ACMP | | 98.32 13 | 99.44 85 | 99.18 109 | 99.75 63 | 99.83 101 | 99.18 162 | 99.64 77 | 99.83 103 | 98.81 131 | 99.79 69 | 98.42 195 | 99.96 13 | 99.64 57 | 99.46 64 | 98.98 115 | 99.74 101 | 99.44 126 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
Anonymous20240521 | | | 99.43 86 | 99.23 94 | 99.67 83 | 99.92 27 | 99.76 18 | 99.64 77 | 99.93 35 | 99.06 99 | 99.68 118 | 97.77 211 | 98.97 168 | 98.97 154 | 99.72 36 | 99.54 41 | 99.88 37 | 99.81 19 |
|
SMA-MVS | | | 99.43 86 | 99.41 63 | 99.45 131 | 99.82 106 | 99.31 135 | 99.02 193 | 99.59 192 | 99.06 99 | 99.34 190 | 99.53 109 | 99.96 13 | 99.38 101 | 99.29 97 | 99.13 89 | 99.53 163 | 99.59 78 |
|
testgi | | | 99.43 86 | 99.47 52 | 99.38 145 | 99.90 35 | 99.67 40 | 99.30 158 | 99.73 161 | 98.64 152 | 99.53 145 | 99.52 111 | 99.90 56 | 98.08 191 | 99.65 46 | 99.40 61 | 99.75 97 | 99.55 98 |
|
DELS-MVS | | | 99.42 89 | 99.53 43 | 99.29 161 | 99.52 202 | 99.43 97 | 99.42 132 | 99.28 225 | 99.16 86 | 99.72 102 | 99.82 64 | 99.97 9 | 98.17 185 | 99.56 54 | 99.16 80 | 99.65 122 | 99.59 78 |
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 |
3Dnovator | | 99.16 3 | 99.42 89 | 99.22 97 | 99.65 87 | 99.78 125 | 99.13 170 | 99.50 114 | 99.85 82 | 99.40 55 | 99.80 66 | 98.59 185 | 99.79 92 | 99.30 115 | 99.20 121 | 99.06 98 | 99.71 112 | 99.35 152 |
|
ESAPD | | | 99.41 91 | 99.36 77 | 99.47 128 | 99.66 174 | 99.48 86 | 99.46 127 | 99.75 159 | 98.65 146 | 99.41 173 | 99.67 82 | 99.95 22 | 98.82 164 | 99.21 117 | 99.14 83 | 99.72 109 | 99.40 142 |
|
UniMVSNet_NR-MVSNet | | | 99.41 91 | 99.12 121 | 99.76 57 | 99.86 69 | 99.48 86 | 99.50 114 | 99.81 122 | 98.84 127 | 99.89 18 | 99.45 118 | 98.32 185 | 99.59 65 | 99.22 114 | 98.89 127 | 99.90 27 | 99.63 69 |
|
CP-MVS | | | 99.41 91 | 99.20 102 | 99.65 87 | 99.80 111 | 99.23 155 | 99.44 130 | 99.75 159 | 98.60 157 | 99.74 92 | 98.66 182 | 99.93 39 | 99.48 93 | 99.33 87 | 99.16 80 | 99.73 105 | 99.48 118 |
|
QAPM | | | 99.41 91 | 99.21 101 | 99.64 92 | 99.78 125 | 99.16 164 | 99.51 110 | 99.85 82 | 99.20 76 | 99.72 102 | 99.43 120 | 99.81 84 | 99.25 120 | 98.87 177 | 98.71 155 | 99.71 112 | 99.30 157 |
|
UGNet | | | 99.40 95 | 99.61 27 | 99.16 183 | 99.88 45 | 99.64 43 | 99.61 86 | 99.77 143 | 99.31 64 | 99.63 127 | 99.33 131 | 99.93 39 | 96.46 224 | 99.63 48 | 99.53 43 | 99.63 134 | 99.89 5 |
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 |
Vis-MVSNet (Re-imp) | | | 99.40 95 | 99.28 87 | 99.55 112 | 99.92 27 | 99.68 37 | 99.31 153 | 99.87 63 | 98.69 142 | 99.16 198 | 99.08 158 | 98.64 176 | 99.20 124 | 99.65 46 | 99.46 53 | 99.83 73 | 99.72 48 |
|
OPM-MVS | | | 99.39 97 | 99.22 97 | 99.59 101 | 99.76 137 | 98.82 194 | 99.51 110 | 99.79 131 | 99.17 82 | 99.53 145 | 99.31 135 | 99.95 22 | 99.35 103 | 99.22 114 | 98.79 149 | 99.60 144 | 99.27 161 |
|
Fast-Effi-MVS+ | | | 99.39 97 | 99.18 109 | 99.63 93 | 99.86 69 | 99.28 142 | 99.45 129 | 99.91 48 | 98.47 167 | 99.61 130 | 99.50 115 | 99.57 120 | 99.17 125 | 99.24 108 | 98.66 161 | 99.78 88 | 99.59 78 |
|
testmv | | | 99.39 97 | 99.19 106 | 99.62 98 | 99.84 90 | 99.38 110 | 99.37 143 | 99.86 67 | 98.47 167 | 99.79 69 | 99.82 64 | 99.39 146 | 99.63 59 | 99.30 92 | 98.70 157 | 99.21 199 | 99.28 159 |
|
test1235678 | | | 99.39 97 | 99.20 102 | 99.62 98 | 99.84 90 | 99.38 110 | 99.38 141 | 99.86 67 | 98.47 167 | 99.79 69 | 99.82 64 | 99.41 144 | 99.63 59 | 99.30 92 | 98.71 155 | 99.21 199 | 99.28 159 |
|
LS3D | | | 99.39 97 | 99.28 87 | 99.52 118 | 99.77 132 | 99.39 105 | 99.55 100 | 99.82 111 | 98.93 116 | 99.64 125 | 98.52 189 | 99.67 106 | 98.58 175 | 99.74 34 | 99.63 29 | 99.75 97 | 99.06 183 |
|
CANet | | | 99.36 102 | 99.39 70 | 99.34 157 | 99.80 111 | 99.35 123 | 99.41 135 | 99.47 209 | 99.20 76 | 99.74 92 | 99.54 102 | 99.68 104 | 98.05 194 | 99.23 111 | 98.97 116 | 99.57 154 | 99.73 44 |
|
MVS_0304 | | | 99.36 102 | 99.35 79 | 99.37 149 | 99.85 82 | 99.36 119 | 99.39 137 | 99.56 195 | 99.36 60 | 99.75 86 | 99.23 141 | 99.90 56 | 97.97 197 | 99.00 156 | 98.83 138 | 99.69 115 | 99.77 30 |
|
ACMMP | ![Method available under an open source license with copyleft or other restrictive terms. copyleft](img/icon_copyleft.png) | | 99.36 102 | 99.06 129 | 99.71 73 | 99.86 69 | 99.36 119 | 99.63 80 | 99.85 82 | 98.33 182 | 99.72 102 | 97.73 213 | 99.94 33 | 99.53 77 | 99.37 77 | 99.13 89 | 99.65 122 | 99.56 93 |
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 |
SD-MVS | | | 99.35 105 | 99.26 89 | 99.46 129 | 99.66 174 | 99.15 166 | 98.92 206 | 99.67 178 | 99.55 39 | 99.35 187 | 98.83 173 | 99.91 54 | 99.35 103 | 99.19 126 | 98.53 171 | 99.78 88 | 99.68 56 |
|
MP-MVS | ![Method available under an open source license with copyleft or other restrictive terms. copyleft](img/icon_copyleft.png) | | 99.35 105 | 99.09 126 | 99.65 87 | 99.84 90 | 99.22 156 | 99.59 91 | 99.78 137 | 98.13 191 | 99.67 120 | 98.44 193 | 99.93 39 | 99.43 99 | 99.31 91 | 99.09 95 | 99.60 144 | 99.49 115 |
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo. |
pmmvs4 | | | 99.34 107 | 99.15 116 | 99.57 107 | 99.77 132 | 98.90 188 | 99.51 110 | 99.77 143 | 99.07 97 | 99.73 98 | 99.72 76 | 99.84 78 | 99.07 141 | 98.85 183 | 98.39 180 | 99.55 161 | 99.27 161 |
|
EPP-MVSNet | | | 99.34 107 | 99.10 124 | 99.62 98 | 99.94 21 | 99.74 25 | 99.66 74 | 99.80 128 | 99.07 97 | 98.93 210 | 99.61 92 | 96.13 198 | 99.49 89 | 99.67 42 | 99.63 29 | 99.92 22 | 99.86 12 |
|
casdiffmvs1 | | | 99.33 109 | 99.20 102 | 99.48 126 | 99.75 141 | 99.35 123 | 99.18 170 | 99.86 67 | 99.16 86 | 99.67 120 | 99.64 87 | 99.07 164 | 98.78 166 | 98.71 198 | 98.64 163 | 99.65 122 | 99.81 19 |
|
TSAR-MVS + GP. | | | 99.33 109 | 99.17 113 | 99.51 120 | 99.71 158 | 99.00 182 | 98.84 214 | 99.71 166 | 98.23 187 | 99.74 92 | 99.53 109 | 99.90 56 | 99.35 103 | 99.38 75 | 98.85 136 | 99.72 109 | 99.31 155 |
|
PHI-MVS | | | 99.33 109 | 99.19 106 | 99.49 125 | 99.69 165 | 99.25 148 | 99.27 162 | 99.59 192 | 98.44 173 | 99.78 75 | 99.15 149 | 99.92 48 | 98.95 157 | 99.39 74 | 99.04 104 | 99.64 132 | 99.18 168 |
|
PGM-MVS | | | 99.32 112 | 98.99 139 | 99.71 73 | 99.86 69 | 99.31 135 | 99.59 91 | 99.86 67 | 97.51 213 | 99.75 86 | 98.23 199 | 99.94 33 | 99.53 77 | 99.29 97 | 99.08 96 | 99.65 122 | 99.54 99 |
|
DeepC-MVS_fast | | 98.69 9 | 99.32 112 | 99.13 119 | 99.53 114 | 99.63 181 | 98.78 197 | 99.53 104 | 99.33 223 | 99.08 94 | 99.77 76 | 99.18 147 | 99.89 59 | 99.29 116 | 99.00 156 | 98.70 157 | 99.65 122 | 99.30 157 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
MSDG | | | 99.32 112 | 99.09 126 | 99.58 103 | 99.75 141 | 98.74 201 | 99.36 145 | 99.54 198 | 99.14 90 | 99.72 102 | 99.24 139 | 99.89 59 | 99.51 81 | 99.30 92 | 98.76 150 | 99.62 140 | 98.54 202 |
|
TSAR-MVS + ACMM | | | 99.31 115 | 99.26 89 | 99.37 149 | 99.66 174 | 98.97 185 | 99.20 168 | 99.56 195 | 99.33 62 | 99.19 197 | 99.54 102 | 99.91 54 | 99.32 111 | 99.12 139 | 98.34 183 | 99.29 191 | 99.65 65 |
|
3Dnovator+ | | 98.92 7 | 99.31 115 | 99.03 134 | 99.63 93 | 99.77 132 | 98.90 188 | 99.52 107 | 99.81 122 | 99.37 58 | 99.72 102 | 98.03 207 | 99.73 99 | 99.32 111 | 98.99 159 | 98.81 146 | 99.67 118 | 99.36 150 |
|
X-MVS | | | 99.30 117 | 98.99 139 | 99.66 85 | 99.85 82 | 99.30 137 | 99.49 121 | 99.82 111 | 98.32 183 | 99.69 111 | 97.31 222 | 99.93 39 | 99.50 85 | 99.37 77 | 99.16 80 | 99.60 144 | 99.53 104 |
|
MVS_111021_HR | | | 99.30 117 | 99.14 117 | 99.48 126 | 99.58 198 | 99.25 148 | 99.27 162 | 99.61 186 | 98.74 136 | 99.66 123 | 99.02 164 | 99.84 78 | 99.33 108 | 99.20 121 | 98.76 150 | 99.44 173 | 99.18 168 |
|
TAPA-MVS | | 98.54 10 | 99.30 117 | 99.24 93 | 99.36 155 | 99.44 216 | 98.77 199 | 99.00 196 | 99.41 215 | 99.23 71 | 99.60 134 | 99.50 115 | 99.86 70 | 99.15 133 | 99.29 97 | 98.95 122 | 99.56 157 | 99.08 180 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
CLD-MVS | | | 99.30 117 | 99.01 138 | 99.63 93 | 99.75 141 | 98.89 191 | 99.35 148 | 99.60 188 | 98.53 164 | 99.86 34 | 99.57 98 | 99.94 33 | 99.52 80 | 98.96 164 | 98.10 197 | 99.70 114 | 99.08 180 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
USDC | | | 99.29 121 | 98.98 141 | 99.65 87 | 99.72 155 | 98.87 192 | 99.47 125 | 99.66 182 | 99.35 61 | 99.87 29 | 99.58 97 | 99.87 69 | 99.51 81 | 98.85 183 | 97.93 204 | 99.65 122 | 98.38 206 |
|
HSP-MVS | | | 99.27 122 | 99.07 128 | 99.50 122 | 99.76 137 | 99.54 67 | 99.73 57 | 99.72 163 | 98.94 114 | 99.23 194 | 98.96 165 | 99.96 13 | 98.91 158 | 98.72 197 | 97.71 210 | 99.63 134 | 99.66 61 |
|
PMVS | ![Method available under an open source license with copyleft or other restrictive terms. copyleft](img/icon_copyleft.png) | 94.32 17 | 99.27 122 | 99.55 39 | 98.94 201 | 99.60 191 | 99.43 97 | 99.39 137 | 99.54 198 | 98.99 107 | 99.69 111 | 99.60 95 | 99.81 84 | 95.68 232 | 99.88 12 | 99.83 3 | 99.73 105 | 99.31 155 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
MVS_111021_LR | | | 99.25 124 | 99.13 119 | 99.39 141 | 99.50 209 | 99.14 167 | 99.23 166 | 99.50 206 | 98.67 144 | 99.61 130 | 99.12 153 | 99.81 84 | 99.16 129 | 99.28 102 | 98.67 160 | 99.35 186 | 99.21 166 |
|
HPM-MVS++ | ![Method available under an open source license with copyleft or other restrictive terms. copyleft](img/icon_copyleft.png) | | 99.23 125 | 98.98 141 | 99.53 114 | 99.75 141 | 99.02 181 | 99.44 130 | 99.77 143 | 98.65 146 | 99.52 151 | 98.72 179 | 99.92 48 | 99.33 108 | 98.77 195 | 98.40 179 | 99.40 180 | 99.36 150 |
|
PMMVS2 | | | 99.23 125 | 99.22 97 | 99.24 170 | 99.80 111 | 99.14 167 | 99.50 114 | 99.82 111 | 99.12 92 | 98.41 234 | 99.91 35 | 99.98 4 | 98.51 176 | 99.48 59 | 98.76 150 | 99.38 182 | 98.14 214 |
|
CPTT-MVS | | | 99.21 127 | 98.89 149 | 99.58 103 | 99.72 155 | 99.12 173 | 99.30 158 | 99.76 151 | 98.62 153 | 99.66 123 | 97.51 216 | 99.89 59 | 99.48 93 | 99.01 154 | 98.64 163 | 99.58 152 | 99.40 142 |
|
TinyColmap | | | 99.21 127 | 98.89 149 | 99.59 101 | 99.61 187 | 98.61 210 | 99.47 125 | 99.67 178 | 99.02 104 | 99.82 61 | 99.15 149 | 99.74 96 | 99.35 103 | 99.17 131 | 98.33 184 | 99.63 134 | 98.22 212 |
|
Effi-MVS+ | | | 99.20 129 | 98.93 144 | 99.50 122 | 99.79 119 | 99.26 145 | 98.82 217 | 99.96 14 | 98.37 181 | 99.60 134 | 99.12 153 | 98.36 183 | 99.05 144 | 98.93 166 | 98.82 141 | 99.78 88 | 99.68 56 |
|
PVSNet_BlendedMVS | | | 99.20 129 | 99.17 113 | 99.23 171 | 99.69 165 | 99.33 130 | 99.04 188 | 99.13 228 | 98.41 177 | 99.79 69 | 99.33 131 | 99.36 147 | 98.10 189 | 99.29 97 | 98.87 132 | 99.65 122 | 99.56 93 |
|
PVSNet_Blended | | | 99.20 129 | 99.17 113 | 99.23 171 | 99.69 165 | 99.33 130 | 99.04 188 | 99.13 228 | 98.41 177 | 99.79 69 | 99.33 131 | 99.36 147 | 98.10 189 | 99.29 97 | 98.87 132 | 99.65 122 | 99.56 93 |
|
MCST-MVS | | | 99.17 132 | 98.82 159 | 99.57 107 | 99.75 141 | 98.70 205 | 99.25 165 | 99.69 171 | 98.62 153 | 99.59 136 | 98.54 187 | 99.79 92 | 99.53 77 | 98.48 205 | 98.15 192 | 99.64 132 | 99.43 130 |
|
APD-MVS | ![Method available under an open source license with copyleft or other restrictive terms. copyleft](img/icon_copyleft.png) | | 99.17 132 | 98.92 145 | 99.46 129 | 99.78 125 | 99.24 153 | 99.34 149 | 99.78 137 | 97.79 206 | 99.48 159 | 98.25 198 | 99.88 64 | 98.77 167 | 99.18 129 | 98.92 124 | 99.63 134 | 99.18 168 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
OpenMVS | ![Method available under an open source license with copyleft or other restrictive terms. copyleft](img/icon_copyleft.png) | 98.82 8 | 99.17 132 | 98.85 155 | 99.53 114 | 99.75 141 | 99.06 178 | 99.36 145 | 99.82 111 | 98.28 185 | 99.76 79 | 98.47 191 | 99.61 111 | 98.91 158 | 98.80 191 | 98.70 157 | 99.60 144 | 99.04 188 |
|
IterMVS-LS | | | 99.16 135 | 98.82 159 | 99.57 107 | 99.87 52 | 99.71 29 | 99.58 95 | 99.92 43 | 99.24 70 | 99.71 107 | 99.73 72 | 95.79 199 | 98.91 158 | 98.82 189 | 98.66 161 | 99.43 176 | 99.77 30 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
DeepPCF-MVS | | 98.38 11 | 99.16 135 | 99.20 102 | 99.12 187 | 99.20 234 | 98.71 204 | 98.85 213 | 99.06 230 | 99.17 82 | 98.96 209 | 99.61 92 | 99.86 70 | 99.29 116 | 99.17 131 | 98.72 154 | 99.36 184 | 99.15 176 |
|
diffmvs1 | | | 99.15 137 | 99.04 133 | 99.27 168 | 99.66 174 | 99.17 163 | 98.97 198 | 99.86 67 | 99.03 103 | 99.41 173 | 99.54 102 | 99.33 153 | 98.40 181 | 98.36 207 | 98.12 194 | 99.33 188 | 99.75 37 |
|
CDS-MVSNet | | | 99.15 137 | 99.10 124 | 99.21 178 | 99.59 195 | 99.22 156 | 99.48 123 | 99.47 209 | 98.89 120 | 99.41 173 | 99.84 60 | 98.11 188 | 97.76 200 | 99.26 107 | 99.01 108 | 99.57 154 | 99.38 145 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
IS_MVSNet | | | 99.15 137 | 99.12 121 | 99.19 181 | 99.92 27 | 99.73 28 | 99.55 100 | 99.86 67 | 98.45 172 | 96.91 245 | 98.74 177 | 98.33 184 | 99.02 146 | 99.54 56 | 99.47 51 | 99.88 37 | 99.61 75 |
|
test12356 | | | 99.12 140 | 99.03 134 | 99.23 171 | 99.78 125 | 98.95 186 | 99.10 183 | 99.72 163 | 98.26 186 | 99.81 64 | 99.87 50 | 99.20 160 | 98.06 192 | 99.47 62 | 98.80 147 | 98.91 211 | 98.67 199 |
|
MDA-MVSNet-bldmvs | | | 99.11 141 | 99.11 123 | 99.12 187 | 99.91 32 | 99.38 110 | 99.77 36 | 98.72 233 | 99.31 64 | 99.85 41 | 99.43 120 | 98.26 186 | 99.48 93 | 99.85 18 | 98.47 174 | 96.99 228 | 99.08 180 |
|
OMC-MVS | | | 99.11 141 | 98.95 143 | 99.29 161 | 99.37 223 | 98.57 212 | 99.19 169 | 99.20 227 | 98.87 122 | 99.58 140 | 99.13 151 | 99.88 64 | 99.00 147 | 99.19 126 | 98.46 175 | 99.43 176 | 98.57 200 |
|
MVS_Test | | | 99.09 143 | 98.92 145 | 99.29 161 | 99.61 187 | 99.07 177 | 99.04 188 | 99.81 122 | 98.58 159 | 99.37 181 | 99.74 70 | 98.87 172 | 98.41 180 | 98.61 201 | 98.01 202 | 99.50 166 | 99.57 92 |
|
casdiffmvs | | | 99.09 143 | 98.86 154 | 99.36 155 | 99.71 158 | 99.21 159 | 98.95 203 | 99.85 82 | 98.65 146 | 99.68 118 | 99.56 99 | 98.38 182 | 98.36 182 | 98.25 214 | 98.24 186 | 99.58 152 | 99.73 44 |
|
tfpn_n400 | | | 99.08 145 | 98.56 170 | 99.70 76 | 99.85 82 | 99.56 62 | 99.63 80 | 99.86 67 | 99.21 74 | 99.37 181 | 98.95 166 | 94.24 204 | 99.55 71 | 99.20 121 | 99.29 67 | 99.93 18 | 99.44 126 |
|
tfpnconf | | | 99.08 145 | 98.56 170 | 99.70 76 | 99.85 82 | 99.56 62 | 99.63 80 | 99.86 67 | 99.21 74 | 99.37 181 | 98.95 166 | 94.24 204 | 99.55 71 | 99.20 121 | 99.29 67 | 99.93 18 | 99.44 126 |
|
CNVR-MVS | | | 99.08 145 | 98.83 156 | 99.37 149 | 99.61 187 | 98.74 201 | 99.15 177 | 99.54 198 | 98.59 158 | 99.37 181 | 98.15 203 | 99.88 64 | 99.08 140 | 98.91 171 | 98.46 175 | 99.48 168 | 99.06 183 |
|
IterMVS | | | 99.08 145 | 98.90 148 | 99.29 161 | 99.87 52 | 99.53 69 | 99.52 107 | 99.77 143 | 98.94 114 | 99.75 86 | 99.91 35 | 97.52 194 | 98.72 170 | 98.86 181 | 98.14 193 | 98.09 221 | 99.43 130 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
FMVSNet2 | | | 99.07 149 | 99.19 106 | 98.93 203 | 99.02 239 | 99.53 69 | 99.31 153 | 99.84 95 | 98.86 123 | 98.88 213 | 99.64 87 | 98.44 180 | 96.92 218 | 99.35 82 | 99.00 113 | 99.61 141 | 99.53 104 |
|
CVMVSNet | | | 99.06 150 | 98.88 152 | 99.28 166 | 99.52 202 | 99.53 69 | 99.42 132 | 99.69 171 | 98.74 136 | 98.27 237 | 99.89 42 | 95.48 203 | 99.44 97 | 99.46 64 | 99.33 63 | 99.32 190 | 99.75 37 |
|
CDPH-MVS | | | 99.05 151 | 98.63 166 | 99.54 113 | 99.75 141 | 98.78 197 | 99.59 91 | 99.68 176 | 97.79 206 | 99.37 181 | 98.20 202 | 99.86 70 | 99.14 135 | 98.58 202 | 98.01 202 | 99.68 116 | 99.16 174 |
|
TAMVS | | | 99.05 151 | 99.02 137 | 99.08 193 | 99.69 165 | 99.22 156 | 99.33 150 | 99.32 224 | 99.16 86 | 98.97 208 | 99.87 50 | 97.36 195 | 97.76 200 | 99.21 117 | 99.00 113 | 99.44 173 | 99.33 153 |
|
tfpnview11 | | | 99.04 153 | 98.49 178 | 99.68 81 | 99.84 90 | 99.58 55 | 99.56 98 | 99.86 67 | 98.86 123 | 99.37 181 | 98.95 166 | 94.24 204 | 99.54 76 | 98.87 177 | 99.54 41 | 99.91 24 | 99.39 144 |
|
CANet_DTU | | | 99.03 154 | 99.18 109 | 98.87 206 | 99.58 198 | 99.03 179 | 99.18 170 | 99.41 215 | 98.65 146 | 99.74 92 | 99.55 101 | 99.71 101 | 96.13 230 | 99.19 126 | 98.92 124 | 99.17 203 | 99.18 168 |
|
Effi-MVS+-dtu | | | 99.01 155 | 99.05 130 | 98.98 197 | 99.60 191 | 99.13 170 | 99.03 192 | 99.61 186 | 98.52 166 | 99.01 205 | 98.53 188 | 99.83 81 | 96.95 217 | 99.48 59 | 98.59 169 | 99.66 120 | 99.25 165 |
|
canonicalmvs | | | 99.00 156 | 98.68 165 | 99.37 149 | 99.68 172 | 99.42 101 | 98.94 205 | 99.89 57 | 99.00 106 | 98.99 206 | 98.43 194 | 95.69 200 | 98.96 156 | 99.18 129 | 99.18 76 | 99.74 101 | 99.88 9 |
|
MIMVSNet | | | 99.00 156 | 99.03 134 | 98.97 199 | 99.32 228 | 99.32 134 | 99.39 137 | 99.91 48 | 98.41 177 | 98.76 217 | 99.24 139 | 99.17 161 | 97.13 211 | 99.30 92 | 98.80 147 | 99.29 191 | 99.01 189 |
|
CHOSEN 280x420 | | | 98.99 158 | 98.91 147 | 99.07 194 | 99.77 132 | 99.26 145 | 99.55 100 | 99.92 43 | 98.62 153 | 98.67 222 | 99.62 91 | 97.20 196 | 98.44 179 | 99.50 57 | 99.18 76 | 98.08 222 | 98.99 192 |
|
diffmvs | | | 98.99 158 | 98.88 152 | 99.11 190 | 99.62 182 | 99.12 173 | 98.70 224 | 99.86 67 | 98.72 140 | 99.43 167 | 99.44 119 | 99.14 162 | 97.87 198 | 98.31 209 | 97.73 209 | 99.18 202 | 99.72 48 |
|
GBi-Net | | | 98.96 160 | 99.05 130 | 98.85 207 | 99.02 239 | 99.53 69 | 99.31 153 | 99.78 137 | 98.13 191 | 98.48 230 | 99.43 120 | 97.58 191 | 96.92 218 | 99.68 39 | 99.50 46 | 99.61 141 | 99.53 104 |
|
test1 | | | 98.96 160 | 99.05 130 | 98.85 207 | 99.02 239 | 99.53 69 | 99.31 153 | 99.78 137 | 98.13 191 | 98.48 230 | 99.43 120 | 97.58 191 | 96.92 218 | 99.68 39 | 99.50 46 | 99.61 141 | 99.53 104 |
|
PCF-MVS | | 97.86 15 | 98.95 162 | 98.53 173 | 99.44 134 | 99.70 163 | 98.80 196 | 98.96 200 | 99.69 171 | 98.65 146 | 99.59 136 | 99.33 131 | 99.94 33 | 99.12 138 | 98.01 220 | 97.11 216 | 99.59 150 | 97.83 218 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
MS-PatchMatch | | | 98.94 163 | 98.71 164 | 99.21 178 | 99.52 202 | 98.22 230 | 98.97 198 | 99.53 203 | 98.76 133 | 99.50 157 | 98.59 185 | 99.56 121 | 98.68 171 | 98.63 200 | 98.45 177 | 99.05 208 | 98.73 196 |
|
AdaColmap | ![Method available as binary. binary](img/icon_binary.png) | | 98.93 164 | 98.53 173 | 99.39 141 | 99.52 202 | 98.65 208 | 99.11 182 | 99.59 192 | 98.08 195 | 99.44 165 | 97.46 219 | 99.45 138 | 99.24 121 | 98.92 168 | 98.44 178 | 99.44 173 | 98.73 196 |
|
MSLP-MVS++ | | | 98.92 165 | 98.73 163 | 99.14 184 | 99.44 216 | 99.00 182 | 98.36 233 | 99.35 220 | 98.82 130 | 99.38 179 | 96.06 228 | 99.79 92 | 99.07 141 | 98.88 176 | 99.05 101 | 99.27 193 | 99.53 104 |
|
new_pmnet | | | 98.91 166 | 98.89 149 | 98.94 201 | 99.51 207 | 98.27 226 | 99.15 177 | 98.66 234 | 99.17 82 | 99.48 159 | 99.79 68 | 99.80 90 | 98.49 178 | 99.23 111 | 98.20 189 | 98.34 219 | 97.74 222 |
|
train_agg | | | 98.89 167 | 98.48 179 | 99.38 145 | 99.69 165 | 98.76 200 | 99.31 153 | 99.60 188 | 97.71 208 | 98.98 207 | 97.89 209 | 99.89 59 | 99.29 116 | 98.32 208 | 97.59 213 | 99.42 179 | 99.16 174 |
|
NCCC | | | 98.88 168 | 98.42 180 | 99.42 136 | 99.62 182 | 98.81 195 | 99.10 183 | 99.54 198 | 98.76 133 | 99.53 145 | 95.97 229 | 99.80 90 | 99.16 129 | 98.49 204 | 98.06 200 | 99.55 161 | 99.05 185 |
|
PLC | ![Method available under an open source license with copyleft or other restrictive terms. copyleft](img/icon_copyleft.png) | 97.83 16 | 98.88 168 | 98.52 175 | 99.30 160 | 99.45 214 | 98.60 211 | 98.65 225 | 99.49 207 | 98.66 145 | 99.59 136 | 96.33 227 | 99.59 117 | 99.17 125 | 98.87 177 | 98.53 171 | 99.46 169 | 99.05 185 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
pmmvs3 | | | 98.85 170 | 98.60 167 | 99.13 185 | 99.66 174 | 98.72 203 | 99.37 143 | 99.06 230 | 98.44 173 | 99.76 79 | 99.74 70 | 99.55 122 | 99.15 133 | 99.04 152 | 96.00 224 | 97.80 223 | 98.72 198 |
|
Fast-Effi-MVS+-dtu | | | 98.82 171 | 98.80 161 | 98.84 209 | 99.51 207 | 98.90 188 | 98.96 200 | 99.91 48 | 98.29 184 | 99.11 203 | 98.47 191 | 99.63 110 | 96.03 231 | 99.21 117 | 98.12 194 | 99.52 164 | 99.01 189 |
|
CNLPA | | | 98.82 171 | 98.52 175 | 99.18 182 | 99.21 233 | 98.50 216 | 98.73 222 | 99.34 222 | 98.73 138 | 99.56 142 | 97.55 215 | 99.42 142 | 99.06 143 | 98.93 166 | 98.10 197 | 99.21 199 | 98.38 206 |
|
PatchMatch-RL | | | 98.80 173 | 98.52 175 | 99.12 187 | 99.38 222 | 98.70 205 | 98.56 228 | 99.55 197 | 97.81 205 | 99.34 190 | 97.57 214 | 99.31 155 | 98.67 172 | 99.27 105 | 98.62 166 | 99.22 198 | 98.35 208 |
|
thisisatest0530 | | | 98.78 174 | 98.26 184 | 99.39 141 | 99.78 125 | 99.43 97 | 99.07 185 | 99.64 184 | 98.44 173 | 99.42 171 | 99.22 142 | 92.68 217 | 98.63 173 | 99.30 92 | 99.14 83 | 99.80 84 | 99.60 76 |
|
tttt0517 | | | 98.77 175 | 98.25 186 | 99.38 145 | 99.79 119 | 99.46 89 | 99.07 185 | 99.64 184 | 98.40 180 | 99.38 179 | 99.21 145 | 92.54 218 | 98.63 173 | 99.34 85 | 99.14 83 | 99.80 84 | 99.62 73 |
|
DI_MVS_plusplus_trai | | | 98.74 176 | 98.08 194 | 99.51 120 | 99.79 119 | 99.29 141 | 99.61 86 | 99.60 188 | 99.20 76 | 99.46 163 | 99.09 157 | 92.93 211 | 98.97 154 | 98.27 213 | 98.35 182 | 99.65 122 | 99.45 123 |
|
TSAR-MVS + COLMAP | | | 98.74 176 | 98.58 169 | 98.93 203 | 99.29 230 | 98.23 227 | 99.04 188 | 99.24 226 | 98.79 132 | 98.80 216 | 99.37 129 | 99.71 101 | 98.06 192 | 98.02 219 | 97.46 215 | 99.16 204 | 98.48 204 |
|
testus | | | 98.74 176 | 98.33 182 | 99.23 171 | 99.71 158 | 99.03 179 | 98.17 239 | 99.60 188 | 97.18 220 | 99.52 151 | 98.07 205 | 98.45 179 | 99.21 123 | 98.30 210 | 98.06 200 | 99.14 206 | 99.21 166 |
|
tfpn1000 | | | 98.73 179 | 98.07 195 | 99.50 122 | 99.84 90 | 99.61 47 | 99.48 123 | 99.84 95 | 98.71 141 | 98.74 218 | 98.71 180 | 91.70 220 | 99.17 125 | 98.81 190 | 99.55 39 | 99.90 27 | 99.43 130 |
|
MDTV_nov1_ep13_2view | | | 98.73 179 | 98.31 183 | 99.22 176 | 99.75 141 | 99.24 153 | 99.75 45 | 99.93 35 | 99.31 64 | 99.84 45 | 99.86 56 | 99.81 84 | 99.31 113 | 97.40 227 | 94.77 225 | 96.73 230 | 97.81 219 |
|
PMMVS | | | 98.71 181 | 98.55 172 | 98.90 205 | 99.28 231 | 98.45 218 | 98.53 231 | 99.45 211 | 97.67 210 | 99.15 201 | 98.76 176 | 99.54 125 | 97.79 199 | 98.77 195 | 98.23 187 | 99.16 204 | 98.46 205 |
|
HQP-MVS | | | 98.70 182 | 98.19 190 | 99.28 166 | 99.61 187 | 98.52 214 | 98.71 223 | 99.35 220 | 97.97 200 | 99.53 145 | 97.38 220 | 99.85 76 | 99.14 135 | 97.53 224 | 96.85 221 | 99.36 184 | 99.26 164 |
|
tfpn_ndepth | | | 98.67 183 | 98.03 196 | 99.42 136 | 99.65 179 | 99.50 83 | 99.29 160 | 99.78 137 | 98.17 190 | 99.04 204 | 98.36 196 | 93.29 209 | 98.88 161 | 98.46 206 | 99.26 70 | 99.88 37 | 99.14 177 |
|
N_pmnet | | | 98.64 184 | 98.23 189 | 99.11 190 | 99.78 125 | 99.25 148 | 99.75 45 | 99.39 219 | 99.65 15 | 99.70 109 | 99.78 69 | 99.89 59 | 98.81 165 | 97.60 223 | 94.28 226 | 97.24 227 | 97.15 226 |
|
CMPMVS | ![Method available as binary. binary](img/icon_binary.png) | 76.62 19 | 98.64 184 | 98.60 167 | 98.68 214 | 99.33 226 | 97.07 242 | 98.11 243 | 98.50 236 | 97.69 209 | 99.26 193 | 98.35 197 | 99.66 107 | 97.62 203 | 99.43 71 | 99.02 106 | 99.24 196 | 99.01 189 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
FMVSNet3 | | | 98.63 186 | 98.75 162 | 98.49 218 | 98.10 246 | 99.44 93 | 99.02 193 | 99.78 137 | 98.13 191 | 98.48 230 | 99.43 120 | 97.58 191 | 96.16 229 | 98.85 183 | 98.39 180 | 99.40 180 | 99.41 135 |
|
GA-MVS | | | 98.59 187 | 98.15 191 | 99.09 192 | 99.59 195 | 99.13 170 | 98.84 214 | 99.52 204 | 98.61 156 | 99.35 187 | 99.67 82 | 93.03 210 | 97.73 202 | 98.90 175 | 98.26 185 | 99.51 165 | 99.48 118 |
|
MAR-MVS | | | 98.54 188 | 98.15 191 | 98.98 197 | 99.37 223 | 98.09 233 | 98.56 228 | 99.65 183 | 96.11 239 | 99.27 192 | 97.16 225 | 99.50 131 | 98.03 196 | 98.87 177 | 98.23 187 | 99.01 209 | 99.13 178 |
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 |
new-patchmatchnet | | | 98.49 189 | 97.60 198 | 99.53 114 | 99.90 35 | 99.55 64 | 99.77 36 | 99.48 208 | 99.67 12 | 99.86 34 | 99.98 3 | 99.98 4 | 99.50 85 | 96.90 230 | 91.52 231 | 98.67 216 | 95.62 231 |
|
FPMVS | | | 98.48 190 | 98.83 156 | 98.07 230 | 99.09 237 | 97.98 236 | 99.07 185 | 98.04 242 | 98.99 107 | 99.22 196 | 98.85 172 | 99.43 141 | 93.79 239 | 99.66 44 | 99.11 93 | 99.24 196 | 97.76 220 |
|
MVS-HIRNet | | | 98.45 191 | 98.25 186 | 98.69 213 | 99.12 235 | 97.81 240 | 98.55 230 | 99.85 82 | 98.58 159 | 99.67 120 | 99.61 92 | 99.86 70 | 97.46 206 | 97.95 221 | 96.37 223 | 97.49 225 | 97.56 223 |
|
test0.0.03 1 | | | 98.41 192 | 98.41 181 | 98.40 222 | 99.62 182 | 99.16 164 | 98.87 211 | 99.41 215 | 97.15 221 | 96.60 247 | 99.31 135 | 97.00 197 | 96.55 223 | 98.91 171 | 98.51 173 | 99.37 183 | 98.82 195 |
|
gg-mvs-nofinetune | | | 98.40 193 | 98.26 184 | 98.57 216 | 99.83 101 | 98.86 193 | 98.77 220 | 99.97 1 | 99.57 34 | 99.99 1 | 99.99 1 | 93.81 207 | 93.50 240 | 98.91 171 | 98.20 189 | 99.33 188 | 98.52 203 |
|
conf0.05thres1000 | | | 98.36 194 | 97.28 204 | 99.63 93 | 99.92 27 | 99.74 25 | 99.66 74 | 99.88 61 | 98.68 143 | 98.92 211 | 97.30 223 | 86.02 238 | 99.49 89 | 99.77 30 | 99.73 18 | 99.93 18 | 99.69 55 |
|
tfpn111 | | | 98.25 195 | 97.29 203 | 99.37 149 | 99.74 150 | 99.52 75 | 99.17 172 | 99.76 151 | 96.10 240 | 98.65 224 | 98.23 199 | 89.10 226 | 99.00 147 | 99.11 140 | 99.56 33 | 99.88 37 | 99.41 135 |
|
PatchT | | | 98.11 196 | 97.12 205 | 99.26 169 | 99.65 179 | 98.34 223 | 99.57 97 | 99.97 1 | 97.48 215 | 99.43 167 | 99.04 162 | 90.84 222 | 98.15 186 | 98.04 217 | 97.78 205 | 98.82 213 | 98.30 209 |
|
thresconf0.02 | | | 98.10 197 | 96.83 208 | 99.58 103 | 99.71 158 | 99.28 142 | 99.40 136 | 99.72 163 | 98.65 146 | 99.39 177 | 98.23 199 | 86.73 236 | 99.43 99 | 97.73 222 | 98.17 191 | 99.86 54 | 99.05 185 |
|
EPNet_dtu | | | 98.09 198 | 98.25 186 | 97.91 232 | 99.58 198 | 98.02 235 | 98.19 238 | 99.67 178 | 97.94 202 | 99.74 92 | 99.07 160 | 98.71 175 | 93.40 241 | 97.50 225 | 97.09 217 | 96.89 229 | 99.44 126 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
EPNet | | | 98.06 199 | 98.11 193 | 98.00 231 | 99.60 191 | 98.99 184 | 98.38 232 | 99.68 176 | 98.18 189 | 98.85 215 | 97.89 209 | 95.60 202 | 92.72 242 | 98.30 210 | 98.10 197 | 98.76 214 | 99.72 48 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
CR-MVSNet | | | 97.91 200 | 96.80 209 | 99.22 176 | 99.60 191 | 98.23 227 | 98.91 207 | 99.97 1 | 96.89 230 | 99.43 167 | 99.10 156 | 89.24 225 | 98.15 186 | 98.04 217 | 97.78 205 | 99.26 194 | 98.30 209 |
|
view800 | | | 97.89 201 | 96.56 211 | 99.45 131 | 99.86 69 | 99.57 57 | 99.42 132 | 99.80 128 | 97.50 214 | 98.40 235 | 93.78 235 | 86.63 237 | 99.31 113 | 99.24 108 | 99.68 23 | 99.89 32 | 99.54 99 |
|
view600 | | | 97.88 202 | 96.55 213 | 99.44 134 | 99.84 90 | 99.52 75 | 99.38 141 | 99.76 151 | 97.36 217 | 98.50 229 | 93.29 236 | 87.31 233 | 99.26 119 | 99.13 138 | 99.76 14 | 99.88 37 | 99.48 118 |
|
thres200 | | | 97.87 203 | 96.56 211 | 99.39 141 | 99.76 137 | 99.52 75 | 99.13 180 | 99.76 151 | 96.88 232 | 98.66 223 | 92.87 241 | 88.77 230 | 99.16 129 | 99.11 140 | 99.42 58 | 99.88 37 | 99.33 153 |
|
thres600view7 | | | 97.86 204 | 96.53 217 | 99.41 139 | 99.84 90 | 99.52 75 | 99.36 145 | 99.76 151 | 97.32 218 | 98.38 236 | 93.24 237 | 87.25 234 | 99.23 122 | 99.11 140 | 99.75 16 | 99.88 37 | 99.48 118 |
|
conf200view11 | | | 97.85 205 | 96.54 214 | 99.37 149 | 99.74 150 | 99.52 75 | 99.17 172 | 99.76 151 | 96.10 240 | 98.65 224 | 92.99 238 | 89.10 226 | 99.00 147 | 99.11 140 | 99.56 33 | 99.88 37 | 99.41 135 |
|
tfpn200view9 | | | 97.85 205 | 96.54 214 | 99.38 145 | 99.74 150 | 99.52 75 | 99.17 172 | 99.76 151 | 96.10 240 | 98.70 220 | 92.99 238 | 89.10 226 | 99.00 147 | 99.11 140 | 99.56 33 | 99.88 37 | 99.41 135 |
|
thres400 | | | 97.82 207 | 96.47 218 | 99.40 140 | 99.81 110 | 99.44 93 | 99.29 160 | 99.69 171 | 97.15 221 | 98.57 226 | 92.82 242 | 87.96 231 | 99.16 129 | 98.96 164 | 99.55 39 | 99.86 54 | 99.41 135 |
|
IB-MVS | | 98.10 14 | 97.76 208 | 97.40 202 | 98.18 225 | 99.62 182 | 99.11 175 | 98.24 236 | 98.35 238 | 96.56 235 | 99.44 165 | 91.28 245 | 98.96 170 | 93.84 238 | 98.09 216 | 98.62 166 | 99.56 157 | 99.18 168 |
Christian Sormann, Mattia Rossi, Andreas Kuhn and Friedrich Fraundorfer: IB-MVS: An Iterative Algorithm for Deep Multi-View Stereo based on Binary Decisions. BMVC 2021 |
test-LLR | | | 97.74 209 | 97.46 200 | 98.08 228 | 99.62 182 | 98.37 221 | 98.26 234 | 99.41 215 | 97.03 225 | 97.38 243 | 99.54 102 | 92.89 212 | 95.12 235 | 98.78 193 | 97.68 211 | 98.65 217 | 97.90 216 |
|
RPMNet | | | 97.70 210 | 96.54 214 | 99.06 195 | 99.57 201 | 98.23 227 | 98.95 203 | 99.97 1 | 96.89 230 | 99.49 158 | 99.13 151 | 89.63 224 | 97.09 213 | 96.68 231 | 97.02 218 | 99.26 194 | 98.19 213 |
|
thres100view900 | | | 97.69 211 | 96.37 219 | 99.23 171 | 99.74 150 | 99.21 159 | 98.81 218 | 99.43 214 | 96.10 240 | 98.70 220 | 92.99 238 | 89.10 226 | 98.88 161 | 98.58 202 | 99.31 66 | 99.82 77 | 99.27 161 |
|
FMVSNet5 | | | 97.69 211 | 96.98 206 | 98.53 217 | 98.53 244 | 99.36 119 | 98.90 209 | 99.54 198 | 96.38 236 | 98.44 233 | 95.38 231 | 90.08 223 | 97.05 216 | 99.46 64 | 99.06 98 | 98.73 215 | 99.12 179 |
|
MVE | ![Method available under a permissive open source license. permissive](img/icon_permissive.png) | 91.08 18 | 97.68 213 | 97.65 197 | 97.71 238 | 98.46 245 | 91.62 249 | 97.92 245 | 98.86 232 | 98.73 138 | 97.99 241 | 98.64 183 | 99.96 13 | 99.17 125 | 99.59 52 | 97.75 207 | 93.87 245 | 97.27 224 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
test-mter | | | 97.65 214 | 97.57 199 | 97.75 236 | 98.90 242 | 98.56 213 | 98.15 240 | 98.45 237 | 96.92 229 | 96.84 246 | 99.52 111 | 92.53 219 | 95.24 234 | 99.04 152 | 98.12 194 | 98.90 212 | 98.29 211 |
|
TESTMET0.1,1 | | | 97.62 215 | 97.46 200 | 97.81 234 | 99.07 238 | 98.37 221 | 98.26 234 | 98.35 238 | 97.03 225 | 97.38 243 | 99.54 102 | 92.89 212 | 95.12 235 | 98.78 193 | 97.68 211 | 98.65 217 | 97.90 216 |
|
MVSTER | | | 97.55 216 | 96.75 210 | 98.48 219 | 99.46 213 | 99.54 67 | 98.24 236 | 99.77 143 | 97.56 212 | 99.41 173 | 99.31 135 | 84.86 239 | 94.66 237 | 98.86 181 | 97.75 207 | 99.34 187 | 99.38 145 |
|
LP | | | 97.43 217 | 96.28 220 | 98.77 210 | 99.69 165 | 98.92 187 | 99.49 121 | 99.70 168 | 98.53 164 | 99.82 61 | 99.12 153 | 95.67 201 | 97.30 209 | 94.65 234 | 91.76 229 | 96.65 232 | 95.34 233 |
|
MDTV_nov1_ep13 | | | 97.41 218 | 96.26 221 | 98.76 211 | 99.47 212 | 98.43 219 | 99.26 164 | 99.82 111 | 98.06 197 | 99.23 194 | 99.22 142 | 92.86 214 | 98.05 194 | 95.33 233 | 93.66 228 | 96.73 230 | 96.26 228 |
|
ADS-MVSNet | | | 97.29 219 | 96.17 222 | 98.59 215 | 99.59 195 | 98.70 205 | 99.32 151 | 99.86 67 | 98.47 167 | 99.56 142 | 99.08 158 | 98.16 187 | 97.34 208 | 92.92 235 | 91.17 232 | 95.91 234 | 94.72 235 |
|
1111 | | | 96.83 220 | 95.02 227 | 98.95 200 | 99.90 35 | 99.57 57 | 99.62 84 | 99.97 1 | 98.58 159 | 98.06 239 | 99.87 50 | 69.04 249 | 96.43 226 | 99.36 80 | 99.14 83 | 99.73 105 | 99.54 99 |
|
gm-plane-assit | | | 96.82 221 | 94.84 228 | 99.13 185 | 99.95 11 | 99.78 16 | 99.69 70 | 99.92 43 | 99.19 79 | 99.84 45 | 99.92 26 | 72.93 246 | 96.44 225 | 98.21 215 | 97.01 219 | 98.92 210 | 96.87 227 |
|
PatchmatchNet | ![Method available under a permissive open source license. permissive](img/icon_permissive.png) | | 96.81 222 | 95.41 224 | 98.43 221 | 99.43 218 | 98.30 224 | 99.23 166 | 99.93 35 | 98.19 188 | 99.64 125 | 98.81 175 | 93.50 208 | 97.43 207 | 92.89 237 | 90.78 234 | 94.94 240 | 95.41 232 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
tfpn | | | 96.77 223 | 94.47 230 | 99.45 131 | 99.88 45 | 99.62 44 | 99.46 127 | 99.83 103 | 97.61 211 | 98.27 237 | 94.22 234 | 71.45 248 | 99.34 107 | 99.32 89 | 99.46 53 | 99.90 27 | 99.58 88 |
|
EPMVS | | | 96.76 224 | 95.30 226 | 98.46 220 | 99.42 219 | 98.47 217 | 99.32 151 | 99.91 48 | 98.42 176 | 99.51 155 | 99.07 160 | 92.81 215 | 97.12 212 | 92.39 238 | 91.71 230 | 95.51 236 | 94.20 237 |
|
E-PMN | | | 96.72 225 | 95.78 223 | 97.81 234 | 99.45 214 | 95.46 245 | 98.14 242 | 98.33 240 | 97.99 199 | 98.73 219 | 98.09 204 | 98.97 168 | 97.54 205 | 97.45 226 | 91.09 233 | 94.70 242 | 91.40 241 |
|
conf0.01 | | | 96.70 226 | 94.44 232 | 99.34 157 | 99.71 158 | 99.46 89 | 99.17 172 | 99.73 161 | 96.10 240 | 98.53 227 | 91.96 243 | 75.75 244 | 99.00 147 | 98.85 183 | 99.56 33 | 99.87 48 | 99.38 145 |
|
tpm | | | 96.56 227 | 94.68 229 | 98.74 212 | 99.12 235 | 97.90 237 | 98.79 219 | 99.93 35 | 96.79 233 | 99.69 111 | 99.19 146 | 81.48 241 | 97.56 204 | 95.46 232 | 93.97 227 | 97.37 226 | 97.99 215 |
|
EMVS | | | 96.47 228 | 95.38 225 | 97.74 237 | 99.42 219 | 95.37 246 | 98.07 244 | 98.27 241 | 97.85 204 | 98.90 212 | 97.48 217 | 98.73 174 | 97.20 210 | 97.21 228 | 90.39 235 | 94.59 244 | 90.65 242 |
|
conf0.002 | | | 96.39 229 | 93.87 234 | 99.33 159 | 99.70 163 | 99.45 91 | 99.17 172 | 99.71 166 | 96.10 240 | 98.51 228 | 91.88 244 | 72.65 247 | 99.00 147 | 98.80 191 | 98.82 141 | 99.87 48 | 99.38 145 |
|
test2356 | | | 96.34 230 | 94.05 233 | 99.00 196 | 99.39 221 | 98.28 225 | 98.15 240 | 99.51 205 | 96.23 237 | 99.16 198 | 97.95 208 | 73.39 245 | 98.75 169 | 97.07 229 | 96.86 220 | 99.06 207 | 98.57 200 |
|
tpmrst | | | 96.18 231 | 94.47 230 | 98.18 225 | 99.52 202 | 97.89 238 | 98.96 200 | 99.79 131 | 98.07 196 | 99.16 198 | 99.30 138 | 92.69 216 | 96.69 221 | 90.76 240 | 88.85 239 | 94.96 239 | 93.69 239 |
|
CostFormer | | | 95.61 232 | 93.35 237 | 98.24 224 | 99.48 211 | 98.03 234 | 98.65 225 | 99.83 103 | 96.93 228 | 99.42 171 | 98.83 173 | 83.65 240 | 97.08 214 | 90.39 241 | 89.54 238 | 94.94 240 | 96.11 230 |
|
dps | | | 95.59 233 | 93.46 236 | 98.08 228 | 99.33 226 | 98.22 230 | 98.87 211 | 99.70 168 | 96.17 238 | 98.87 214 | 97.75 212 | 86.85 235 | 96.60 222 | 91.24 239 | 89.62 237 | 95.10 238 | 94.34 236 |
|
tpm cat1 | | | 95.52 234 | 93.49 235 | 97.88 233 | 99.28 231 | 97.87 239 | 98.65 225 | 99.77 143 | 97.27 219 | 99.46 163 | 98.04 206 | 90.99 221 | 95.46 233 | 88.57 244 | 88.14 242 | 94.64 243 | 93.54 240 |
|
tpmp4_e23 | | | 95.42 235 | 92.99 238 | 98.27 223 | 99.32 228 | 97.77 241 | 98.74 221 | 99.79 131 | 97.11 223 | 99.61 130 | 97.47 218 | 80.64 242 | 96.36 228 | 92.92 235 | 88.79 240 | 95.80 235 | 96.19 229 |
|
DWT-MVSNet_training | | | 94.92 236 | 92.14 239 | 98.15 227 | 99.37 223 | 98.43 219 | 98.99 197 | 98.51 235 | 96.76 234 | 99.52 151 | 97.35 221 | 77.20 243 | 97.08 214 | 89.76 242 | 90.38 236 | 95.43 237 | 95.13 234 |
|
testpf | | | 93.65 237 | 91.79 240 | 95.82 239 | 98.71 243 | 93.25 247 | 96.38 247 | 99.67 178 | 95.38 246 | 97.83 242 | 94.48 233 | 87.69 232 | 89.61 244 | 88.96 243 | 88.79 240 | 92.71 246 | 93.97 238 |
|
v1.0 | | | 91.57 238 | 84.95 241 | 99.29 161 | 99.79 119 | 99.44 93 | 99.02 193 | 99.79 131 | 97.96 201 | 99.12 202 | 99.22 142 | 99.95 22 | 98.50 177 | 99.21 117 | 98.84 137 | 99.56 157 | 0.00 246 |
|
.test1245 | | | 79.44 239 | 75.07 242 | 84.53 241 | 99.90 35 | 99.57 57 | 99.62 84 | 99.97 1 | 98.58 159 | 98.06 239 | 99.87 50 | 69.04 249 | 96.43 226 | 99.36 80 | 24.74 243 | 13.21 247 | 34.30 243 |
|
GG-mvs-BLEND | | | 70.44 240 | 96.91 207 | 39.57 242 | 3.32 250 | 96.51 243 | 91.01 249 | 4.05 247 | 97.03 225 | 33.20 249 | 94.67 232 | 97.75 190 | 7.59 247 | 98.28 212 | 96.85 221 | 98.24 220 | 97.26 225 |
|
testmvs | | | 22.33 241 | 29.66 243 | 13.79 243 | 8.97 248 | 10.35 250 | 15.53 252 | 8.09 246 | 32.51 247 | 19.87 250 | 45.18 246 | 30.56 252 | 17.05 246 | 29.96 245 | 24.74 243 | 13.21 247 | 34.30 243 |
|
test123 | | | 21.52 242 | 28.47 244 | 13.42 244 | 7.29 249 | 10.12 251 | 15.70 251 | 8.31 245 | 31.54 248 | 19.34 251 | 36.33 247 | 37.40 251 | 17.14 245 | 27.45 246 | 23.17 245 | 12.73 249 | 33.30 245 |
|
sosnet-low-res | | | 0.00 243 | 0.00 245 | 0.00 245 | 0.00 251 | 0.00 252 | 0.00 253 | 0.00 248 | 0.00 249 | 0.00 252 | 0.00 248 | 0.00 253 | 0.00 248 | 0.00 247 | 0.00 246 | 0.00 250 | 0.00 246 |
|
sosnet | | | 0.00 243 | 0.00 245 | 0.00 245 | 0.00 251 | 0.00 252 | 0.00 253 | 0.00 248 | 0.00 249 | 0.00 252 | 0.00 248 | 0.00 253 | 0.00 248 | 0.00 247 | 0.00 246 | 0.00 250 | 0.00 246 |
|
Anonymous202405211 | | | | 99.14 117 | | 99.87 52 | 99.55 64 | 99.50 114 | 99.70 168 | 98.55 163 | | 98.61 184 | 98.46 178 | 98.76 168 | 99.66 44 | 99.50 46 | 99.85 58 | 99.63 69 |
|
our_test_3 | | | | | | 99.75 141 | 99.11 175 | 99.74 53 | | | | | | | | | | |
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ambc | | | | 98.83 156 | | 99.72 155 | 98.52 214 | 98.84 214 | | 98.96 111 | 99.92 8 | 99.34 130 | 99.74 96 | 99.04 145 | 98.68 199 | 97.57 214 | 99.46 169 | 98.99 192 |
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MTAPA | | | | | | | | | | | 99.62 128 | | 99.95 22 | | | | | |
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MTMP | | | | | | | | | | | 99.53 145 | | 99.92 48 | | | | | |
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Patchmatch-RL test | | | | | | | | 65.75 250 | | | | | | | | | | |
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tmp_tt | | | | | 88.14 240 | 96.68 247 | 91.91 248 | 93.70 248 | 61.38 244 | 99.61 23 | 90.51 248 | 99.40 126 | 99.71 101 | 90.32 243 | 99.22 114 | 99.44 57 | 96.25 233 | |
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XVS | | | | | | 99.86 69 | 99.30 137 | 99.72 62 | | | 99.69 111 | | 99.93 39 | | | | 99.60 144 | |
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X-MVStestdata | | | | | | 99.86 69 | 99.30 137 | 99.72 62 | | | 99.69 111 | | 99.93 39 | | | | 99.60 144 | |
|
abl_6 | | | | | 99.21 178 | 99.49 210 | 98.62 209 | 98.90 209 | 99.44 213 | 97.08 224 | 99.61 130 | 97.19 224 | 99.73 99 | 98.35 183 | | | 99.45 171 | 98.84 194 |
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mPP-MVS | | | | | | 99.84 90 | | | | | | | 99.92 48 | | | | | |
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NP-MVS | | | | | | | | | | 97.37 216 | | | | | | | | |
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Patchmtry | | | | | | | 98.19 232 | 98.91 207 | 99.97 1 | | 99.43 167 | | | | | | | |
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DeepMVS_CX | ![Method available under an open source license with copyleft or other restrictive terms. copyleft](img/icon_copyleft.png) | | | | | | 96.39 244 | 97.15 246 | 88.89 243 | 97.94 202 | 99.51 155 | 95.71 230 | 97.88 189 | 98.19 184 | 98.92 168 | | 97.73 224 | 97.75 221 |
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