Gipuma | | | 99.22 29 | 98.86 42 | 99.64 16 | 99.70 63 | 99.24 58 | 99.17 96 | 99.63 47 | 99.52 3 | 99.89 1 | 96.54 180 | 99.14 93 | 99.93 1 | 99.42 29 | 99.15 39 | 99.52 45 | 99.04 46 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
v52 | | | 99.67 6 | 99.59 7 | 99.76 9 | 99.91 9 | 99.69 11 | 99.85 4 | 99.79 16 | 99.12 9 | 99.68 11 | 99.95 2 | 99.72 14 | 99.77 2 | 99.58 17 | 99.61 11 | 99.54 39 | 99.50 13 |
|
V4 | | | 99.67 6 | 99.60 6 | 99.76 9 | 99.91 9 | 99.69 11 | 99.85 4 | 99.79 16 | 99.13 8 | 99.68 11 | 99.95 2 | 99.72 14 | 99.77 2 | 99.58 17 | 99.61 11 | 99.54 39 | 99.50 13 |
|
DTE-MVSNet | | | 99.52 13 | 99.27 19 | 99.82 2 | 99.93 3 | 99.77 4 | 99.79 10 | 99.87 7 | 97.89 45 | 99.70 10 | 99.55 62 | 99.21 79 | 99.77 2 | 99.65 10 | 99.43 23 | 99.90 3 | 99.36 21 |
|
v7n | | | 99.68 5 | 99.61 4 | 99.76 9 | 99.89 14 | 99.74 8 | 99.87 2 | 99.82 14 | 99.20 6 | 99.71 5 | 99.96 1 | 99.73 12 | 99.76 5 | 99.58 17 | 99.59 15 | 99.52 45 | 99.46 17 |
|
PEN-MVS | | | 99.54 11 | 99.30 18 | 99.83 1 | 99.92 5 | 99.76 5 | 99.80 8 | 99.88 4 | 97.60 66 | 99.71 5 | 99.59 55 | 99.52 43 | 99.75 6 | 99.64 12 | 99.51 19 | 99.90 3 | 99.46 17 |
|
SixPastTwentyTwo | | | 99.70 4 | 99.59 7 | 99.82 2 | 99.93 3 | 99.80 2 | 99.86 3 | 99.87 7 | 98.87 14 | 99.79 4 | 99.85 27 | 99.33 63 | 99.74 7 | 99.85 2 | 99.82 1 | 99.74 22 | 99.63 4 |
|
v748 | | | 99.67 6 | 99.61 4 | 99.75 13 | 99.87 17 | 99.68 13 | 99.84 6 | 99.79 16 | 99.14 7 | 99.64 16 | 99.89 12 | 99.88 5 | 99.72 8 | 99.58 17 | 99.57 17 | 99.62 30 | 99.50 13 |
|
PS-CasMVS | | | 99.50 14 | 99.23 21 | 99.82 2 | 99.92 5 | 99.75 7 | 99.78 11 | 99.89 2 | 97.30 85 | 99.71 5 | 99.60 53 | 99.23 75 | 99.71 9 | 99.65 10 | 99.55 18 | 99.90 3 | 99.56 8 |
|
CP-MVSNet | | | 99.39 20 | 99.04 29 | 99.80 6 | 99.91 9 | 99.70 10 | 99.75 15 | 99.88 4 | 96.82 108 | 99.68 11 | 99.32 76 | 98.86 121 | 99.68 10 | 99.57 21 | 99.47 21 | 99.89 6 | 99.52 10 |
|
WR-MVS | | | 99.61 10 | 99.44 11 | 99.82 2 | 99.92 5 | 99.80 2 | 99.80 8 | 99.89 2 | 98.54 19 | 99.66 14 | 99.78 40 | 99.16 87 | 99.68 10 | 99.70 6 | 99.63 6 | 99.94 1 | 99.49 16 |
|
Anonymous20231211 | | | 99.79 1 | 99.80 1 | 99.77 7 | 99.97 1 | 99.87 1 | 99.90 1 | 99.92 1 | 99.76 1 | 99.25 60 | 99.79 37 | 99.98 1 | 99.63 12 | 99.84 3 | 99.78 3 | 99.94 1 | 99.61 6 |
|
anonymousdsp | | | 99.64 9 | 99.55 9 | 99.74 14 | 99.87 17 | 99.56 22 | 99.82 7 | 99.73 28 | 98.54 19 | 99.71 5 | 99.92 6 | 99.84 7 | 99.61 13 | 99.70 6 | 99.63 6 | 99.69 26 | 99.64 2 |
|
ACMH | | 97.81 6 | 99.44 19 | 99.33 14 | 99.56 23 | 99.81 28 | 99.42 38 | 99.73 19 | 99.58 55 | 99.02 11 | 99.10 81 | 99.41 73 | 99.69 19 | 99.60 14 | 99.45 27 | 99.26 36 | 99.55 38 | 99.05 45 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
COLMAP_ROB | | 98.29 2 | 99.37 21 | 99.25 20 | 99.51 30 | 99.74 51 | 99.12 82 | 99.56 40 | 99.39 94 | 98.96 12 | 99.17 68 | 99.44 70 | 99.63 33 | 99.58 15 | 99.48 25 | 99.27 34 | 99.60 35 | 98.81 76 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
no-one | | | 99.01 45 | 98.94 36 | 99.09 90 | 98.97 194 | 98.55 153 | 99.37 69 | 99.04 164 | 97.59 67 | 99.36 37 | 99.66 45 | 99.75 9 | 99.57 16 | 98.47 85 | 99.27 34 | 98.21 184 | 99.30 25 |
|
ACMH+ | | 97.53 7 | 99.29 25 | 99.20 24 | 99.40 45 | 99.81 28 | 99.22 63 | 99.59 36 | 99.50 77 | 98.64 18 | 98.29 156 | 99.21 85 | 99.69 19 | 99.57 16 | 99.53 22 | 99.33 30 | 99.66 28 | 98.81 76 |
|
WR-MVS_H | | | 99.48 15 | 99.23 21 | 99.76 9 | 99.91 9 | 99.76 5 | 99.75 15 | 99.88 4 | 97.27 88 | 99.58 19 | 99.56 59 | 99.24 73 | 99.56 18 | 99.60 15 | 99.60 14 | 99.88 8 | 99.58 7 |
|
LTVRE_ROB | | 98.82 1 | 99.76 2 | 99.75 2 | 99.77 7 | 99.87 17 | 99.71 9 | 99.77 12 | 99.76 22 | 99.52 3 | 99.80 2 | 99.79 37 | 99.91 2 | 99.56 18 | 99.83 4 | 99.75 4 | 99.86 9 | 99.75 1 |
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 |
v11 | | | 99.19 31 | 98.95 32 | 99.47 33 | 99.66 75 | 99.54 28 | 99.65 23 | 99.73 28 | 98.06 31 | 99.38 36 | 99.92 6 | 99.40 54 | 99.55 20 | 98.29 104 | 98.50 92 | 98.88 132 | 98.92 64 |
|
TDRefinement | | | 99.54 11 | 99.50 10 | 99.60 19 | 99.70 63 | 99.35 45 | 99.77 12 | 99.58 55 | 99.40 5 | 99.28 56 | 99.66 45 | 99.41 51 | 99.55 20 | 99.74 5 | 99.65 5 | 99.70 23 | 99.25 26 |
|
v13 | | | 99.22 29 | 98.99 31 | 99.49 31 | 99.68 67 | 99.58 20 | 99.67 20 | 99.77 21 | 98.10 29 | 99.36 37 | 99.88 13 | 99.37 57 | 99.54 22 | 98.50 84 | 98.51 91 | 98.92 124 | 99.03 48 |
|
v12 | | | 99.19 31 | 98.95 32 | 99.48 32 | 99.67 70 | 99.56 22 | 99.66 22 | 99.76 22 | 98.06 31 | 99.33 42 | 99.88 13 | 99.34 62 | 99.53 23 | 98.42 91 | 98.43 96 | 98.91 127 | 98.97 55 |
|
FC-MVSNet-test | | | 99.32 23 | 99.33 14 | 99.31 65 | 99.87 17 | 99.65 17 | 99.63 29 | 99.75 25 | 97.76 50 | 97.29 204 | 99.87 18 | 99.63 33 | 99.52 24 | 99.66 9 | 99.63 6 | 99.77 19 | 99.12 37 |
|
v1144 | | | 98.94 53 | 98.53 67 | 99.42 41 | 99.62 96 | 99.03 100 | 99.58 37 | 99.36 112 | 97.99 35 | 99.49 29 | 99.91 11 | 99.20 81 | 99.51 25 | 97.61 161 | 97.85 129 | 98.95 119 | 98.10 141 |
|
V9 | | | 99.16 35 | 98.90 39 | 99.46 34 | 99.66 75 | 99.54 28 | 99.65 23 | 99.75 25 | 98.01 34 | 99.31 46 | 99.87 18 | 99.31 67 | 99.51 25 | 98.34 98 | 98.34 99 | 98.90 129 | 98.91 65 |
|
v7 | | | 98.91 58 | 98.53 67 | 99.36 55 | 99.53 119 | 98.99 106 | 99.57 38 | 99.36 112 | 97.58 69 | 99.32 44 | 99.88 13 | 99.23 75 | 99.50 27 | 97.77 149 | 97.98 117 | 98.91 127 | 98.26 126 |
|
v10 | | | 99.01 45 | 98.66 57 | 99.41 42 | 99.52 124 | 99.39 41 | 99.57 38 | 99.66 41 | 97.59 67 | 99.32 44 | 99.88 13 | 99.23 75 | 99.50 27 | 97.77 149 | 97.98 117 | 98.92 124 | 98.78 81 |
|
V14 | | | 99.13 37 | 98.85 44 | 99.45 35 | 99.65 81 | 99.52 30 | 99.63 29 | 99.74 27 | 97.97 36 | 99.30 49 | 99.87 18 | 99.27 71 | 99.49 29 | 98.23 110 | 98.24 102 | 98.88 132 | 98.83 71 |
|
DeepC-MVS | | 97.88 4 | 99.33 22 | 99.15 25 | 99.53 29 | 99.73 56 | 99.05 90 | 99.49 56 | 99.40 92 | 98.42 22 | 99.55 23 | 99.71 43 | 99.89 4 | 99.49 29 | 99.14 39 | 98.81 65 | 99.54 39 | 99.02 51 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
v15 | | | 99.09 40 | 98.79 46 | 99.43 39 | 99.64 89 | 99.50 31 | 99.61 33 | 99.73 28 | 97.92 40 | 99.28 56 | 99.86 22 | 99.24 73 | 99.47 31 | 98.12 121 | 98.14 107 | 98.87 134 | 98.76 83 |
|
NR-MVSNet | | | 99.10 39 | 98.68 56 | 99.58 21 | 99.89 14 | 99.23 60 | 99.35 72 | 99.63 47 | 96.58 123 | 99.36 37 | 99.05 95 | 98.67 133 | 99.46 32 | 99.63 13 | 98.73 75 | 99.80 15 | 98.88 69 |
|
SteuartSystems-ACMMP | | | 98.94 53 | 98.52 69 | 99.43 39 | 99.79 33 | 99.13 80 | 99.33 76 | 99.55 60 | 96.17 143 | 99.04 93 | 97.53 152 | 99.65 30 | 99.46 32 | 99.04 53 | 98.76 71 | 99.44 58 | 99.35 22 |
Skip Steuart: Steuart Systems R&D Blog. |
v1192 | | | 98.91 58 | 98.48 72 | 99.41 42 | 99.61 99 | 99.03 100 | 99.64 26 | 99.25 136 | 97.91 42 | 99.58 19 | 99.92 6 | 99.07 110 | 99.45 34 | 97.55 165 | 97.68 146 | 98.93 121 | 98.23 128 |
|
v1240 | | | 98.86 70 | 98.41 87 | 99.38 51 | 99.59 100 | 99.05 90 | 99.65 23 | 99.14 152 | 97.68 61 | 99.66 14 | 99.93 5 | 98.72 128 | 99.45 34 | 97.38 176 | 97.72 144 | 98.79 150 | 98.35 117 |
|
TranMVSNet+NR-MVSNet | | | 99.23 27 | 98.91 38 | 99.61 17 | 99.81 28 | 99.45 36 | 99.47 58 | 99.68 37 | 97.28 87 | 99.39 35 | 99.54 63 | 99.08 108 | 99.45 34 | 99.09 45 | 98.84 62 | 99.83 11 | 99.04 46 |
|
v1921920 | | | 98.89 62 | 98.46 73 | 99.39 46 | 99.58 102 | 99.04 95 | 99.64 26 | 99.17 147 | 97.91 42 | 99.64 16 | 99.92 6 | 98.99 117 | 99.44 37 | 97.44 172 | 97.57 156 | 98.84 141 | 98.35 117 |
|
LGP-MVS_train | | | 98.84 73 | 98.33 95 | 99.44 36 | 99.78 36 | 98.98 107 | 99.39 67 | 99.55 60 | 95.41 158 | 98.90 109 | 97.51 153 | 99.68 22 | 99.44 37 | 99.03 54 | 98.81 65 | 99.57 37 | 98.91 65 |
|
pmmvs6 | | | 99.74 3 | 99.75 2 | 99.73 15 | 99.92 5 | 99.67 15 | 99.76 14 | 99.84 11 | 99.59 2 | 99.52 26 | 99.87 18 | 99.91 2 | 99.43 39 | 99.87 1 | 99.81 2 | 99.89 6 | 99.52 10 |
|
v144192 | | | 98.88 64 | 98.46 73 | 99.37 53 | 99.56 107 | 99.03 100 | 99.61 33 | 99.26 133 | 97.79 49 | 99.58 19 | 99.88 13 | 99.11 101 | 99.43 39 | 97.38 176 | 97.61 152 | 98.80 148 | 98.43 112 |
|
ACMP | | 96.54 13 | 98.87 65 | 98.40 89 | 99.41 42 | 99.74 51 | 98.88 128 | 99.29 79 | 99.50 77 | 96.85 104 | 98.96 100 | 97.05 165 | 99.66 27 | 99.43 39 | 98.98 58 | 98.60 85 | 99.52 45 | 98.81 76 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
MIMVSNet1 | | | 99.46 17 | 99.34 13 | 99.60 19 | 99.83 23 | 99.68 13 | 99.74 18 | 99.71 33 | 98.20 27 | 99.41 34 | 99.86 22 | 99.66 27 | 99.41 42 | 99.50 23 | 99.39 25 | 99.50 51 | 99.10 41 |
|
tfpnnormal | | | 99.19 31 | 98.90 39 | 99.54 26 | 99.81 28 | 99.55 26 | 99.60 35 | 99.54 66 | 98.53 21 | 99.23 61 | 98.40 120 | 98.23 144 | 99.40 43 | 99.29 34 | 99.36 28 | 99.63 29 | 98.95 61 |
|
v1141 | | | 98.87 65 | 98.45 77 | 99.36 55 | 99.65 81 | 99.04 95 | 99.56 40 | 99.38 101 | 97.83 46 | 99.29 51 | 99.86 22 | 99.16 87 | 99.40 43 | 97.68 155 | 97.78 132 | 98.86 137 | 97.82 153 |
|
v1neww | | | 98.84 73 | 98.45 77 | 99.29 69 | 99.54 112 | 98.98 107 | 99.54 47 | 99.37 109 | 97.48 73 | 99.10 81 | 99.80 35 | 99.12 97 | 99.40 43 | 97.85 141 | 97.89 123 | 98.81 143 | 98.04 144 |
|
v7new | | | 98.84 73 | 98.45 77 | 99.29 69 | 99.54 112 | 98.98 107 | 99.54 47 | 99.37 109 | 97.48 73 | 99.10 81 | 99.80 35 | 99.12 97 | 99.40 43 | 97.85 141 | 97.89 123 | 98.81 143 | 98.04 144 |
|
v17 | | | 98.96 51 | 98.63 58 | 99.35 60 | 99.54 112 | 99.41 39 | 99.55 43 | 99.70 34 | 97.40 80 | 99.10 81 | 99.79 37 | 99.10 102 | 99.40 43 | 97.96 128 | 97.99 115 | 98.80 148 | 98.77 82 |
|
v16 | | | 98.95 52 | 98.62 59 | 99.34 62 | 99.53 119 | 99.41 39 | 99.54 47 | 99.70 34 | 97.34 84 | 99.07 87 | 99.76 41 | 99.10 102 | 99.40 43 | 97.96 128 | 98.00 114 | 98.79 150 | 98.76 83 |
|
divwei89l23v2f112 | | | 98.87 65 | 98.45 77 | 99.36 55 | 99.65 81 | 99.04 95 | 99.56 40 | 99.38 101 | 97.83 46 | 99.29 51 | 99.86 22 | 99.15 91 | 99.40 43 | 97.68 155 | 97.78 132 | 98.86 137 | 97.82 153 |
|
v6 | | | 98.84 73 | 98.46 73 | 99.30 66 | 99.54 112 | 98.98 107 | 99.54 47 | 99.37 109 | 97.49 72 | 99.11 80 | 99.81 32 | 99.13 96 | 99.40 43 | 97.86 138 | 97.89 123 | 98.81 143 | 98.04 144 |
|
v1 | | | 98.87 65 | 98.45 77 | 99.36 55 | 99.65 81 | 99.04 95 | 99.55 43 | 99.38 101 | 97.83 46 | 99.30 49 | 99.86 22 | 99.17 84 | 99.40 43 | 97.68 155 | 97.77 139 | 98.86 137 | 97.82 153 |
|
Baseline_NR-MVSNet | | | 99.18 34 | 98.87 41 | 99.54 26 | 99.74 51 | 99.56 22 | 99.36 71 | 99.62 51 | 96.53 129 | 99.29 51 | 99.85 27 | 98.64 135 | 99.40 43 | 99.03 54 | 99.63 6 | 99.83 11 | 98.86 70 |
|
v8 | | | 98.94 53 | 98.60 60 | 99.35 60 | 99.54 112 | 99.39 41 | 99.55 43 | 99.67 40 | 97.48 73 | 99.13 76 | 99.81 32 | 99.10 102 | 99.39 53 | 97.86 138 | 97.89 123 | 98.81 143 | 98.66 94 |
|
v2v482 | | | 98.85 72 | 98.40 89 | 99.38 51 | 99.65 81 | 98.98 107 | 99.55 43 | 99.39 94 | 97.92 40 | 99.35 40 | 99.85 27 | 99.14 93 | 99.39 53 | 97.50 167 | 97.78 132 | 98.98 116 | 97.60 160 |
|
v18 | | | 98.89 62 | 98.54 65 | 99.30 66 | 99.50 127 | 99.37 44 | 99.51 52 | 99.68 37 | 97.25 92 | 99.00 96 | 99.76 41 | 99.04 111 | 99.36 55 | 97.81 145 | 97.86 128 | 98.77 153 | 98.68 93 |
|
UniMVSNet_NR-MVSNet | | | 98.97 49 | 98.46 73 | 99.56 23 | 99.76 44 | 99.34 46 | 99.29 79 | 99.61 52 | 96.55 127 | 99.55 23 | 99.05 95 | 97.96 155 | 99.36 55 | 98.84 68 | 98.50 92 | 99.81 14 | 98.97 55 |
|
DU-MVS | | | 99.04 43 | 98.59 61 | 99.56 23 | 99.74 51 | 99.23 60 | 99.29 79 | 99.63 47 | 96.58 123 | 99.55 23 | 99.05 95 | 98.68 131 | 99.36 55 | 99.03 54 | 98.60 85 | 99.77 19 | 98.97 55 |
|
ACMM | | 96.66 11 | 98.90 60 | 98.44 83 | 99.44 36 | 99.74 51 | 98.95 116 | 99.47 58 | 99.55 60 | 97.66 62 | 99.09 85 | 96.43 181 | 99.41 51 | 99.35 58 | 98.95 59 | 98.67 80 | 99.45 56 | 99.03 48 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
V42 | | | 98.81 81 | 98.49 71 | 99.18 78 | 99.52 124 | 98.92 122 | 99.50 55 | 99.29 129 | 97.43 78 | 98.97 98 | 99.81 32 | 99.00 116 | 99.30 59 | 97.93 131 | 98.01 113 | 98.51 173 | 98.34 121 |
|
ACMMPR | | | 99.05 42 | 98.72 51 | 99.44 36 | 99.79 33 | 99.12 82 | 99.35 72 | 99.56 58 | 97.74 55 | 99.21 62 | 97.72 146 | 99.55 41 | 99.29 60 | 98.90 66 | 98.81 65 | 99.41 66 | 99.19 33 |
|
ACMMP | | | 98.82 80 | 98.33 95 | 99.39 46 | 99.77 38 | 99.14 79 | 99.37 69 | 99.54 66 | 96.47 133 | 99.03 95 | 96.26 185 | 99.52 43 | 99.28 61 | 98.92 64 | 98.80 68 | 99.37 73 | 99.16 36 |
Qingshan Xu, Weihang Kong, Wenbing Tao, Marc Pollefeys: Multi-Scale Geometric Consistency Guided and Planar Prior Assisted Multi-View Stereo. IEEE Transactions on Pattern Analysis and Machine Intelligence |
TransMVSNet (Re) | | | 99.45 18 | 99.32 16 | 99.61 17 | 99.88 16 | 99.60 18 | 99.75 15 | 99.63 47 | 99.11 10 | 99.28 56 | 99.83 31 | 98.35 141 | 99.27 62 | 99.70 6 | 99.62 10 | 99.84 10 | 99.03 48 |
|
UniMVSNet (Re) | | | 99.08 41 | 98.69 55 | 99.54 26 | 99.75 47 | 99.33 48 | 99.29 79 | 99.64 46 | 96.75 115 | 99.48 30 | 99.30 78 | 98.69 129 | 99.26 63 | 98.94 60 | 98.76 71 | 99.78 18 | 99.02 51 |
|
CSCG | | | 99.23 27 | 99.15 25 | 99.32 64 | 99.83 23 | 99.45 36 | 98.97 116 | 99.21 141 | 98.83 15 | 99.04 93 | 99.43 71 | 99.64 31 | 99.26 63 | 98.85 67 | 98.20 105 | 99.62 30 | 99.62 5 |
|
pm-mvs1 | | | 99.47 16 | 99.38 12 | 99.57 22 | 99.82 25 | 99.49 32 | 99.63 29 | 99.65 43 | 98.88 13 | 99.31 46 | 99.85 27 | 99.02 113 | 99.23 65 | 99.60 15 | 99.58 16 | 99.80 15 | 99.22 31 |
|
PGM-MVS | | | 98.69 86 | 98.09 111 | 99.39 46 | 99.76 44 | 99.07 86 | 99.30 78 | 99.51 74 | 94.76 175 | 99.18 67 | 96.70 174 | 99.51 46 | 99.20 66 | 98.79 73 | 98.71 78 | 99.39 71 | 99.11 38 |
|
CPTT-MVS | | | 98.28 120 | 97.51 139 | 99.16 80 | 99.54 112 | 98.78 133 | 98.96 117 | 99.36 112 | 96.30 139 | 98.89 112 | 93.10 214 | 99.30 68 | 99.20 66 | 98.35 97 | 97.96 120 | 99.03 112 | 98.82 73 |
|
v148 | | | 98.77 84 | 98.45 77 | 99.15 81 | 99.68 67 | 98.94 120 | 99.49 56 | 99.31 128 | 97.95 38 | 98.91 108 | 99.65 49 | 99.62 35 | 99.18 68 | 97.99 127 | 97.64 150 | 98.33 178 | 97.38 169 |
|
MCST-MVS | | | 98.25 123 | 97.57 137 | 99.06 91 | 99.53 119 | 98.24 172 | 98.63 154 | 99.17 147 | 95.88 151 | 98.58 131 | 96.11 187 | 99.09 106 | 99.18 68 | 97.58 164 | 97.31 167 | 99.25 90 | 98.75 85 |
|
EPP-MVSNet | | | 98.61 95 | 98.19 105 | 99.11 87 | 99.86 22 | 99.60 18 | 99.44 63 | 99.53 71 | 97.37 83 | 96.85 212 | 98.69 111 | 93.75 189 | 99.18 68 | 99.22 37 | 99.35 29 | 99.82 13 | 99.32 23 |
|
UA-Net | | | 99.30 24 | 99.22 23 | 99.39 46 | 99.94 2 | 99.66 16 | 98.91 124 | 99.86 9 | 97.74 55 | 98.74 123 | 99.00 101 | 99.60 38 | 99.17 71 | 99.50 23 | 99.39 25 | 99.70 23 | 99.64 2 |
|
EG-PatchMatch MVS | | | 99.01 45 | 98.77 48 | 99.28 73 | 99.64 89 | 98.90 126 | 98.81 136 | 99.27 132 | 96.55 127 | 99.71 5 | 99.31 77 | 99.66 27 | 99.17 71 | 99.28 36 | 99.11 43 | 99.10 99 | 98.57 101 |
|
TSAR-MVS + MP. | | | 99.02 44 | 98.95 32 | 99.11 87 | 99.23 171 | 98.79 132 | 99.51 52 | 98.73 182 | 97.50 71 | 98.56 132 | 99.03 98 | 99.59 39 | 99.16 73 | 99.29 34 | 99.17 38 | 99.50 51 | 99.24 29 |
|
pmmvs-eth3d | | | 98.68 87 | 98.14 107 | 99.29 69 | 99.49 130 | 98.45 161 | 99.45 62 | 99.38 101 | 97.21 94 | 99.50 28 | 99.65 49 | 99.21 79 | 99.16 73 | 97.11 184 | 97.56 157 | 98.79 150 | 97.82 153 |
|
zzz-MVS | | | 98.94 53 | 98.57 64 | 99.37 53 | 99.77 38 | 99.15 78 | 99.24 87 | 99.55 60 | 97.38 82 | 99.16 71 | 96.64 176 | 99.69 19 | 99.15 75 | 99.09 45 | 98.92 56 | 99.37 73 | 99.11 38 |
|
CP-MVS | | | 98.86 70 | 98.43 86 | 99.36 55 | 99.68 67 | 98.97 114 | 99.19 95 | 99.46 86 | 96.60 121 | 99.20 63 | 97.11 164 | 99.51 46 | 99.15 75 | 98.92 64 | 98.82 63 | 99.45 56 | 99.08 43 |
|
HFP-MVS | | | 98.97 49 | 98.70 53 | 99.29 69 | 99.67 70 | 98.98 107 | 99.13 100 | 99.53 71 | 97.76 50 | 98.90 109 | 98.07 134 | 99.50 48 | 99.14 77 | 98.64 79 | 98.78 69 | 99.37 73 | 99.18 34 |
|
X-MVS | | | 98.59 98 | 97.99 120 | 99.30 66 | 99.75 47 | 99.07 86 | 99.17 96 | 99.50 77 | 96.62 119 | 98.95 102 | 93.95 209 | 99.37 57 | 99.11 78 | 98.94 60 | 98.86 58 | 99.35 77 | 99.09 42 |
|
EU-MVSNet | | | 98.68 87 | 98.94 36 | 98.37 160 | 99.14 180 | 98.74 138 | 99.64 26 | 98.20 207 | 98.21 26 | 99.17 68 | 99.66 45 | 99.18 83 | 99.08 79 | 99.11 42 | 98.86 58 | 95.00 216 | 98.83 71 |
|
MDA-MVSNet-bldmvs | | | 97.75 143 | 97.26 145 | 98.33 161 | 99.35 150 | 98.45 161 | 99.32 77 | 97.21 223 | 97.90 44 | 99.05 90 | 99.01 100 | 96.86 174 | 99.08 79 | 99.36 30 | 92.97 217 | 95.97 213 | 96.25 192 |
|
MP-MVS | | | 98.78 83 | 98.30 97 | 99.34 62 | 99.75 47 | 98.95 116 | 99.26 84 | 99.46 86 | 95.78 154 | 99.17 68 | 96.98 169 | 99.72 14 | 99.06 81 | 98.84 68 | 98.74 74 | 99.33 79 | 99.11 38 |
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo. |
APDe-MVS | | | 99.15 36 | 98.95 32 | 99.39 46 | 99.77 38 | 99.28 55 | 99.52 51 | 99.54 66 | 97.22 93 | 99.06 88 | 99.20 86 | 99.64 31 | 99.05 82 | 99.14 39 | 99.02 53 | 99.39 71 | 99.17 35 |
|
CLD-MVS | | | 98.48 108 | 98.15 106 | 98.86 117 | 99.53 119 | 98.35 165 | 98.55 165 | 97.83 217 | 96.02 148 | 98.97 98 | 99.08 92 | 99.75 9 | 99.03 83 | 98.10 123 | 97.33 166 | 99.28 87 | 98.44 111 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
USDC | | | 98.26 122 | 97.57 137 | 99.06 91 | 99.42 139 | 97.98 187 | 98.83 132 | 98.85 175 | 97.57 70 | 99.59 18 | 99.15 88 | 98.59 136 | 98.99 84 | 97.42 173 | 96.08 197 | 98.69 158 | 96.23 193 |
|
RPSCF | | | 98.84 73 | 98.81 45 | 98.89 112 | 99.37 142 | 98.95 116 | 98.51 167 | 98.85 175 | 97.73 57 | 98.33 153 | 98.97 103 | 99.14 93 | 98.95 85 | 99.18 38 | 98.68 79 | 99.31 83 | 98.99 53 |
|
new-patchmatchnet | | | 97.26 165 | 96.12 179 | 98.58 147 | 99.55 109 | 98.63 146 | 99.14 99 | 97.04 225 | 98.80 16 | 99.19 65 | 99.92 6 | 99.19 82 | 98.92 86 | 95.51 209 | 87.04 225 | 97.66 194 | 93.73 214 |
|
OPM-MVS | | | 98.84 73 | 98.59 61 | 99.12 85 | 99.52 124 | 98.50 158 | 99.13 100 | 99.22 139 | 97.76 50 | 98.76 120 | 98.70 110 | 99.61 36 | 98.90 87 | 98.67 77 | 98.37 98 | 99.19 95 | 98.57 101 |
|
TinyColmap | | | 98.27 121 | 97.62 136 | 99.03 97 | 99.29 160 | 97.79 193 | 98.92 122 | 98.95 172 | 97.48 73 | 99.52 26 | 98.65 113 | 97.86 157 | 98.90 87 | 98.34 98 | 97.27 168 | 98.64 162 | 95.97 196 |
|
MVS_111021_HR | | | 98.58 99 | 98.26 100 | 98.96 106 | 99.32 154 | 98.81 130 | 98.48 168 | 98.99 169 | 96.81 110 | 99.16 71 | 98.07 134 | 99.23 75 | 98.89 89 | 98.43 90 | 98.27 101 | 98.90 129 | 98.24 127 |
|
TSAR-MVS + GP. | | | 98.54 104 | 98.29 99 | 98.82 124 | 99.28 163 | 98.59 149 | 97.73 206 | 99.24 138 | 95.93 150 | 98.59 130 | 99.07 93 | 99.17 84 | 98.86 90 | 98.44 87 | 98.10 109 | 99.26 89 | 98.72 87 |
|
SD-MVS | | | 98.73 85 | 98.54 65 | 98.95 107 | 99.14 180 | 98.76 134 | 98.46 170 | 99.14 152 | 97.71 59 | 98.56 132 | 98.06 136 | 99.61 36 | 98.85 91 | 98.56 81 | 97.74 141 | 99.54 39 | 99.32 23 |
|
ACMMP_Plus | | | 98.94 53 | 98.72 51 | 99.21 74 | 99.67 70 | 99.08 85 | 99.26 84 | 99.39 94 | 96.84 105 | 98.88 113 | 98.22 127 | 99.68 22 | 98.82 92 | 99.06 48 | 98.90 57 | 99.25 90 | 99.25 26 |
|
train_agg | | | 97.99 133 | 97.26 145 | 98.83 121 | 99.43 138 | 98.22 174 | 98.91 124 | 99.07 161 | 94.43 184 | 97.96 174 | 96.42 182 | 99.30 68 | 98.81 93 | 97.39 174 | 96.62 185 | 98.82 142 | 98.47 107 |
|
pmmvs5 | | | 98.37 116 | 97.81 126 | 99.03 97 | 99.46 132 | 98.97 114 | 99.03 108 | 98.96 171 | 95.85 152 | 99.05 90 | 99.45 69 | 98.66 134 | 98.79 94 | 96.02 202 | 97.52 158 | 98.87 134 | 98.21 131 |
|
HPM-MVS++ | | | 98.56 103 | 98.08 112 | 99.11 87 | 99.53 119 | 98.61 148 | 99.02 112 | 99.32 126 | 96.29 140 | 99.06 88 | 97.23 159 | 99.50 48 | 98.77 95 | 98.15 117 | 97.90 121 | 98.96 117 | 98.90 67 |
|
MSDG | | | 98.20 127 | 97.88 125 | 98.56 149 | 99.33 151 | 97.74 196 | 98.27 184 | 98.10 208 | 97.20 96 | 98.06 167 | 98.59 115 | 99.16 87 | 98.76 96 | 98.39 93 | 97.71 145 | 98.86 137 | 96.38 190 |
|
PM-MVS | | | 98.57 100 | 98.24 102 | 98.95 107 | 99.26 165 | 98.59 149 | 99.03 108 | 98.74 181 | 96.84 105 | 99.44 33 | 99.13 89 | 98.31 143 | 98.75 97 | 98.03 125 | 98.21 103 | 98.48 174 | 98.58 99 |
|
HyFIR lowres test | | | 98.08 132 | 97.16 152 | 99.14 84 | 99.72 58 | 98.91 123 | 99.41 64 | 99.58 55 | 97.93 39 | 98.82 116 | 99.24 80 | 95.81 183 | 98.73 98 | 95.16 214 | 95.13 206 | 98.60 165 | 97.94 150 |
|
TSAR-MVS + ACMM | | | 98.64 92 | 98.58 63 | 98.72 132 | 99.17 177 | 98.63 146 | 98.69 143 | 99.10 159 | 97.69 60 | 98.30 155 | 99.12 91 | 99.38 56 | 98.70 99 | 98.45 86 | 97.51 159 | 98.35 177 | 99.25 26 |
|
conf0.05thres1000 | | | 97.44 162 | 95.93 184 | 99.20 77 | 99.82 25 | 99.56 22 | 99.41 64 | 99.61 52 | 97.42 79 | 98.01 172 | 94.34 208 | 82.73 223 | 98.68 100 | 99.33 33 | 99.42 24 | 99.67 27 | 98.74 86 |
|
SMA-MVS | | | 98.87 65 | 98.73 50 | 99.04 96 | 99.72 58 | 99.05 90 | 98.64 153 | 99.17 147 | 96.31 138 | 98.80 118 | 99.07 93 | 99.70 18 | 98.67 101 | 98.93 63 | 98.82 63 | 99.23 93 | 99.23 30 |
|
PLC | | 95.63 15 | 97.73 146 | 97.01 157 | 98.57 148 | 99.10 184 | 97.80 192 | 97.72 207 | 98.77 180 | 96.34 136 | 98.38 149 | 93.46 213 | 98.06 150 | 98.66 102 | 97.90 134 | 97.65 149 | 98.77 153 | 97.90 151 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
MVS_111021_LR | | | 98.39 115 | 98.11 109 | 98.71 134 | 99.08 187 | 98.54 156 | 98.23 187 | 98.56 193 | 96.57 125 | 99.13 76 | 98.41 119 | 98.86 121 | 98.65 103 | 98.23 110 | 97.87 127 | 98.65 161 | 98.28 123 |
|
AdaColmap | | | 97.57 157 | 96.57 166 | 98.74 130 | 99.25 168 | 98.01 182 | 98.36 179 | 98.98 170 | 94.44 183 | 98.47 146 | 92.44 218 | 97.91 156 | 98.62 104 | 98.19 112 | 97.74 141 | 98.73 155 | 97.28 172 |
|
Anonymous20231206 | | | 98.50 106 | 98.03 117 | 99.05 94 | 99.50 127 | 99.01 104 | 99.15 98 | 99.26 133 | 96.38 135 | 99.12 78 | 99.50 66 | 99.12 97 | 98.60 105 | 97.68 155 | 97.24 170 | 98.66 159 | 97.30 171 |
|
HQP-MVS | | | 97.58 156 | 96.65 165 | 98.66 141 | 99.30 157 | 97.99 185 | 97.88 201 | 98.65 187 | 94.58 177 | 98.66 126 | 94.65 202 | 99.15 91 | 98.59 106 | 96.10 200 | 95.59 199 | 98.90 129 | 98.50 106 |
|
DeepPCF-MVS | | 96.68 10 | 98.20 127 | 98.26 100 | 98.12 174 | 97.03 238 | 98.11 178 | 98.44 172 | 97.70 218 | 96.77 112 | 98.52 137 | 98.91 104 | 99.17 84 | 98.58 107 | 98.41 92 | 98.02 112 | 98.46 175 | 98.46 108 |
|
NCCC | | | 97.84 141 | 96.96 158 | 98.87 114 | 99.39 141 | 98.27 169 | 98.46 170 | 99.02 166 | 96.78 111 | 98.73 124 | 91.12 220 | 98.91 118 | 98.57 108 | 97.83 144 | 97.49 160 | 99.04 111 | 98.33 122 |
|
TAPA-MVS | | 96.65 12 | 98.23 124 | 97.96 122 | 98.55 150 | 98.81 200 | 98.16 176 | 98.40 174 | 97.94 214 | 96.68 117 | 98.49 142 | 98.61 114 | 98.89 119 | 98.57 108 | 97.45 170 | 97.59 154 | 99.09 103 | 98.35 117 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
ambc | | | | 97.89 124 | | 99.45 133 | 97.88 189 | 97.78 203 | | 97.27 88 | 99.80 2 | 98.99 102 | 98.48 139 | 98.55 110 | 97.80 146 | 96.68 183 | 98.54 169 | 98.10 141 |
|
3Dnovator+ | | 97.85 5 | 98.61 95 | 98.14 107 | 99.15 81 | 99.62 96 | 98.37 164 | 99.10 104 | 99.51 74 | 98.04 33 | 98.98 97 | 96.07 189 | 98.75 127 | 98.55 110 | 98.51 83 | 98.40 97 | 99.17 96 | 98.82 73 |
|
Vis-MVSNet (Re-imp) | | | 98.46 111 | 98.23 103 | 98.73 131 | 99.81 28 | 99.29 54 | 98.79 137 | 99.50 77 | 96.20 142 | 96.03 217 | 98.29 125 | 96.98 172 | 98.54 112 | 99.11 42 | 99.08 44 | 99.70 23 | 98.62 96 |
|
DeepC-MVS_fast | | 97.38 8 | 98.65 90 | 98.34 94 | 99.02 100 | 99.33 151 | 98.29 166 | 98.99 113 | 98.71 184 | 97.40 80 | 99.31 46 | 98.20 128 | 99.40 54 | 98.54 112 | 98.33 101 | 98.18 106 | 99.23 93 | 98.58 99 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
MSLP-MVS++ | | | 97.99 133 | 97.64 135 | 98.40 157 | 98.91 196 | 98.47 160 | 97.12 225 | 98.78 179 | 96.49 130 | 98.48 144 | 93.57 212 | 99.12 97 | 98.51 114 | 98.31 102 | 98.58 87 | 98.58 167 | 98.95 61 |
|
Fast-Effi-MVS+ | | | 98.42 113 | 97.79 127 | 99.15 81 | 99.69 66 | 98.66 144 | 98.94 119 | 99.68 37 | 94.49 179 | 99.05 90 | 98.06 136 | 98.86 121 | 98.48 115 | 98.18 113 | 97.78 132 | 99.05 110 | 98.54 105 |
|
Effi-MVS+ | | | 98.11 131 | 97.29 144 | 99.06 91 | 99.62 96 | 98.55 153 | 98.16 190 | 99.80 15 | 94.64 176 | 99.15 74 | 96.59 177 | 97.43 165 | 98.44 116 | 97.46 169 | 97.90 121 | 99.17 96 | 98.45 110 |
|
OMC-MVS | | | 98.35 117 | 98.10 110 | 98.64 143 | 98.85 198 | 97.99 185 | 98.56 164 | 98.21 205 | 97.26 90 | 98.87 115 | 98.54 116 | 99.27 71 | 98.43 117 | 98.34 98 | 97.66 147 | 98.92 124 | 97.65 159 |
|
pmmvs4 | | | 97.87 140 | 97.02 156 | 98.86 117 | 99.20 172 | 97.68 199 | 98.89 128 | 99.03 165 | 96.57 125 | 99.12 78 | 99.03 98 | 97.26 169 | 98.42 118 | 95.16 214 | 96.34 189 | 98.53 170 | 97.10 181 |
|
MDTV_nov1_ep13_2view | | | 97.12 168 | 96.19 178 | 98.22 170 | 99.13 182 | 98.05 180 | 99.24 87 | 99.47 83 | 97.61 65 | 99.15 74 | 99.59 55 | 99.01 114 | 98.40 119 | 94.87 216 | 90.14 220 | 93.91 221 | 94.04 213 |
|
tfpn | | | 94.97 206 | 91.60 219 | 98.90 110 | 99.73 56 | 99.33 48 | 99.11 103 | 99.51 74 | 95.05 165 | 97.19 209 | 89.03 224 | 62.62 241 | 98.37 120 | 98.53 82 | 98.97 55 | 99.48 54 | 97.70 157 |
|
canonicalmvs | | | 98.34 118 | 97.92 123 | 98.83 121 | 99.45 133 | 99.21 64 | 98.37 177 | 99.53 71 | 97.06 102 | 97.74 183 | 96.95 171 | 95.05 186 | 98.36 121 | 98.77 74 | 98.85 60 | 99.51 50 | 99.53 9 |
|
CNVR-MVS | | | 98.22 126 | 97.76 128 | 98.76 129 | 99.33 151 | 98.26 170 | 98.48 168 | 98.88 174 | 96.22 141 | 98.47 146 | 95.79 191 | 99.33 63 | 98.35 122 | 98.37 94 | 97.99 115 | 99.03 112 | 98.38 115 |
|
CNLPA | | | 97.75 143 | 97.26 145 | 98.32 163 | 98.58 212 | 97.86 190 | 97.80 202 | 98.09 209 | 96.49 130 | 98.49 142 | 96.15 186 | 98.08 149 | 98.35 122 | 98.00 126 | 97.03 177 | 98.61 164 | 97.21 178 |
|
CHOSEN 1792x2688 | | | 98.31 119 | 98.02 118 | 98.66 141 | 99.55 109 | 98.57 152 | 99.38 68 | 99.25 136 | 98.42 22 | 98.48 144 | 99.58 57 | 99.85 6 | 98.31 124 | 95.75 205 | 95.71 198 | 96.96 205 | 98.27 125 |
|
HSP-MVS | | | 98.50 106 | 98.05 115 | 99.03 97 | 99.67 70 | 99.33 48 | 99.51 52 | 99.26 133 | 95.28 160 | 98.51 138 | 98.19 129 | 99.74 11 | 98.29 125 | 97.69 154 | 96.70 182 | 98.96 117 | 99.41 20 |
|
view800 | | | 96.48 182 | 94.42 195 | 98.87 114 | 99.70 63 | 99.26 56 | 99.05 106 | 99.45 90 | 94.77 174 | 97.32 200 | 88.21 225 | 83.40 221 | 98.28 126 | 98.37 94 | 99.33 30 | 99.44 58 | 97.58 162 |
|
tfpn_n400 | | | 97.59 154 | 96.36 172 | 99.01 101 | 99.66 75 | 99.19 69 | 99.21 92 | 99.55 60 | 97.62 63 | 97.77 179 | 94.60 203 | 87.78 202 | 98.27 127 | 98.44 87 | 98.72 76 | 99.62 30 | 98.21 131 |
|
tfpnconf | | | 97.59 154 | 96.36 172 | 99.01 101 | 99.66 75 | 99.19 69 | 99.21 92 | 99.55 60 | 97.62 63 | 97.77 179 | 94.60 203 | 87.78 202 | 98.27 127 | 98.44 87 | 98.72 76 | 99.62 30 | 98.21 131 |
|
IS_MVSNet | | | 98.20 127 | 98.00 119 | 98.44 154 | 99.82 25 | 99.48 33 | 99.25 86 | 99.56 58 | 95.58 156 | 93.93 234 | 97.56 151 | 96.52 176 | 98.27 127 | 99.08 47 | 99.20 37 | 99.80 15 | 98.56 104 |
|
tfpnview11 | | | 97.49 159 | 96.22 176 | 98.97 105 | 99.63 94 | 99.24 58 | 99.12 102 | 99.54 66 | 96.76 113 | 97.77 179 | 94.60 203 | 87.78 202 | 98.25 130 | 97.93 131 | 99.14 40 | 99.52 45 | 98.08 143 |
|
CDPH-MVS | | | 97.99 133 | 97.23 148 | 98.87 114 | 99.58 102 | 98.29 166 | 98.83 132 | 99.20 145 | 93.76 198 | 98.11 165 | 96.11 187 | 99.16 87 | 98.23 131 | 97.80 146 | 97.22 171 | 99.29 86 | 98.28 123 |
|
APD-MVS | | | 98.47 109 | 97.97 121 | 99.05 94 | 99.64 89 | 98.91 123 | 98.94 119 | 99.45 90 | 94.40 186 | 98.77 119 | 97.26 158 | 99.41 51 | 98.21 132 | 98.67 77 | 98.57 89 | 99.31 83 | 98.57 101 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
PCF-MVS | | 95.58 16 | 97.60 152 | 96.67 162 | 98.69 137 | 99.44 136 | 98.23 173 | 98.37 177 | 98.81 178 | 93.01 208 | 98.22 159 | 97.97 140 | 99.59 39 | 98.20 133 | 95.72 207 | 95.08 207 | 99.08 104 | 97.09 183 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
view600 | | | 96.39 186 | 94.30 196 | 98.82 124 | 99.65 81 | 99.16 76 | 98.98 114 | 99.36 112 | 94.46 182 | 97.39 196 | 87.28 226 | 84.16 219 | 98.16 134 | 98.16 114 | 99.48 20 | 99.40 68 | 97.42 167 |
|
FC-MVSNet-train | | | 99.13 37 | 99.05 28 | 99.21 74 | 99.87 17 | 99.57 21 | 99.67 20 | 99.60 54 | 96.75 115 | 98.28 157 | 99.48 67 | 99.52 43 | 98.10 135 | 99.47 26 | 99.37 27 | 99.76 21 | 99.21 32 |
|
thres600view7 | | | 96.35 187 | 94.27 197 | 98.79 127 | 99.66 75 | 99.18 71 | 98.94 119 | 99.38 101 | 94.37 188 | 97.21 206 | 87.19 228 | 84.10 220 | 98.10 135 | 98.16 114 | 99.47 21 | 99.42 63 | 97.43 166 |
|
QAPM | | | 98.62 94 | 98.40 89 | 98.89 112 | 99.57 106 | 98.80 131 | 98.63 154 | 99.35 117 | 96.82 108 | 98.60 129 | 98.85 108 | 99.08 108 | 98.09 137 | 98.31 102 | 98.21 103 | 99.08 104 | 98.72 87 |
|
PVSNet_Blended_VisFu | | | 98.98 48 | 98.79 46 | 99.21 74 | 99.76 44 | 99.34 46 | 99.35 72 | 99.35 117 | 97.12 99 | 99.46 31 | 99.56 59 | 98.89 119 | 98.08 138 | 99.05 49 | 98.58 87 | 99.27 88 | 98.98 54 |
|
PHI-MVS | | | 98.57 100 | 98.20 104 | 99.00 103 | 99.48 131 | 98.91 123 | 98.68 144 | 99.17 147 | 94.97 170 | 99.27 59 | 98.33 122 | 99.33 63 | 98.05 139 | 98.82 70 | 98.62 84 | 99.34 78 | 98.38 115 |
|
DI_MVS_plusplus_trai | | | 97.57 157 | 96.55 167 | 98.77 128 | 99.55 109 | 98.76 134 | 99.22 90 | 99.00 168 | 97.08 100 | 97.95 175 | 97.78 145 | 91.35 196 | 98.02 140 | 96.20 198 | 96.81 181 | 98.87 134 | 97.87 152 |
|
LS3D | | | 98.79 82 | 98.52 69 | 99.12 85 | 99.64 89 | 99.09 84 | 99.24 87 | 99.46 86 | 97.75 53 | 98.93 106 | 97.47 154 | 98.23 144 | 97.98 141 | 99.36 30 | 99.30 32 | 99.46 55 | 98.42 113 |
|
3Dnovator | | 98.16 3 | 98.65 90 | 98.35 93 | 99.00 103 | 99.59 100 | 98.70 140 | 98.90 127 | 99.36 112 | 97.97 36 | 99.09 85 | 96.55 179 | 99.09 106 | 97.97 142 | 98.70 76 | 98.65 83 | 99.12 98 | 98.81 76 |
|
thres400 | | | 96.22 192 | 94.08 200 | 98.72 132 | 99.58 102 | 99.05 90 | 98.83 132 | 99.22 139 | 94.01 195 | 97.40 194 | 86.34 234 | 84.91 218 | 97.93 143 | 97.85 141 | 99.08 44 | 99.37 73 | 97.28 172 |
|
thres200 | | | 96.23 191 | 94.13 198 | 98.69 137 | 99.44 136 | 99.18 71 | 98.58 163 | 99.38 101 | 93.52 201 | 97.35 198 | 86.33 235 | 85.83 215 | 97.93 143 | 98.16 114 | 98.78 69 | 99.42 63 | 97.10 181 |
|
IterMVS-LS | | | 98.23 124 | 97.66 132 | 98.90 110 | 99.63 94 | 99.38 43 | 99.07 105 | 99.48 82 | 97.75 53 | 98.81 117 | 99.37 75 | 94.57 188 | 97.88 145 | 96.54 195 | 97.04 176 | 98.53 170 | 98.97 55 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
PatchMatch-RL | | | 97.24 166 | 96.45 170 | 98.17 171 | 98.70 206 | 97.57 201 | 97.31 221 | 98.48 197 | 94.42 185 | 98.39 148 | 95.74 192 | 96.35 179 | 97.88 145 | 97.75 151 | 97.48 161 | 98.24 182 | 95.87 197 |
|
thresconf0.02 | | | 95.49 201 | 92.74 213 | 98.70 135 | 99.32 154 | 98.70 140 | 98.87 130 | 99.21 141 | 95.95 149 | 97.57 188 | 90.63 221 | 73.55 235 | 97.86 147 | 96.09 201 | 97.03 177 | 99.40 68 | 97.22 177 |
|
ESAPD | | | 98.60 97 | 98.41 87 | 98.83 121 | 99.56 107 | 99.21 64 | 98.66 151 | 99.47 83 | 95.22 161 | 98.35 151 | 98.48 118 | 99.67 26 | 97.84 148 | 98.80 72 | 98.57 89 | 99.10 99 | 98.93 63 |
|
casdiffmvs | | | 98.43 112 | 98.08 112 | 98.85 120 | 99.37 142 | 98.89 127 | 98.66 151 | 99.54 66 | 97.07 101 | 98.68 125 | 98.53 117 | 99.33 63 | 97.83 149 | 96.89 188 | 97.11 173 | 99.01 114 | 98.70 89 |
|
MS-PatchMatch | | | 97.60 152 | 97.22 149 | 98.04 178 | 98.67 208 | 97.18 205 | 97.91 198 | 98.28 202 | 95.82 153 | 98.34 152 | 97.66 147 | 98.38 140 | 97.77 150 | 97.10 185 | 97.25 169 | 97.27 200 | 97.18 179 |
|
testmv | | | 97.48 161 | 96.83 161 | 98.24 168 | 99.37 142 | 97.79 193 | 98.59 161 | 99.07 161 | 92.40 211 | 97.59 186 | 99.24 80 | 98.11 148 | 97.66 151 | 97.64 159 | 97.11 173 | 97.17 201 | 95.54 201 |
|
test1235678 | | | 97.49 159 | 96.84 160 | 98.24 168 | 99.37 142 | 97.79 193 | 98.59 161 | 99.07 161 | 92.41 210 | 97.59 186 | 99.24 80 | 98.15 147 | 97.66 151 | 97.64 159 | 97.12 172 | 97.17 201 | 95.55 200 |
|
IterMVS | | | 97.40 163 | 96.67 162 | 98.25 165 | 99.45 133 | 98.66 144 | 98.87 130 | 98.73 182 | 96.40 134 | 98.94 105 | 99.56 59 | 95.26 185 | 97.58 153 | 95.38 210 | 94.70 211 | 95.90 214 | 96.72 186 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
Vis-MVSNet | | | 99.25 26 | 99.32 16 | 99.17 79 | 99.65 81 | 99.55 26 | 99.63 29 | 99.33 121 | 98.16 28 | 99.29 51 | 99.65 49 | 99.77 8 | 97.56 154 | 99.44 28 | 99.14 40 | 99.58 36 | 99.51 12 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
MVE | | 82.47 18 | 93.12 222 | 94.09 199 | 91.99 233 | 90.79 240 | 82.50 242 | 93.93 239 | 96.30 227 | 96.06 147 | 88.81 240 | 98.19 129 | 96.38 178 | 97.56 154 | 97.24 182 | 95.18 204 | 84.58 239 | 93.07 216 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
tfpn111 | | | 96.48 182 | 94.67 194 | 98.59 145 | 99.37 142 | 99.18 71 | 98.68 144 | 99.39 94 | 92.02 217 | 97.21 206 | 90.63 221 | 86.34 210 | 97.45 156 | 98.15 117 | 99.08 44 | 99.43 60 | 97.28 172 |
|
conf0.01 | | | 94.53 213 | 91.09 222 | 98.53 152 | 99.29 160 | 99.05 90 | 98.68 144 | 99.35 117 | 92.02 217 | 97.04 210 | 84.45 237 | 68.52 237 | 97.45 156 | 97.79 148 | 99.08 44 | 99.41 66 | 96.70 187 |
|
conf0.002 | | | 93.97 218 | 90.06 226 | 98.52 153 | 99.26 165 | 99.02 103 | 98.68 144 | 99.33 121 | 92.02 217 | 97.01 211 | 83.82 238 | 63.41 240 | 97.45 156 | 97.73 152 | 97.98 117 | 99.40 68 | 96.47 189 |
|
conf200view11 | | | 96.16 195 | 94.08 200 | 98.59 145 | 99.37 142 | 99.18 71 | 98.68 144 | 99.39 94 | 92.02 217 | 97.21 206 | 86.53 231 | 86.34 210 | 97.45 156 | 98.15 117 | 99.08 44 | 99.43 60 | 97.28 172 |
|
tfpn200view9 | | | 96.17 193 | 94.08 200 | 98.60 144 | 99.37 142 | 99.18 71 | 98.68 144 | 99.39 94 | 92.02 217 | 97.30 202 | 86.53 231 | 86.34 210 | 97.45 156 | 98.15 117 | 99.08 44 | 99.43 60 | 97.28 172 |
|
N_pmnet | | | 96.68 180 | 95.70 189 | 97.84 185 | 99.42 139 | 98.00 184 | 99.35 72 | 98.21 205 | 98.40 24 | 98.13 164 | 99.42 72 | 99.30 68 | 97.44 161 | 94.00 224 | 88.79 222 | 94.47 220 | 91.96 222 |
|
Anonymous20240521 | | | 98.42 113 | 98.05 115 | 98.86 117 | 99.67 70 | 99.16 76 | 98.79 137 | 99.21 141 | 95.11 164 | 98.54 135 | 97.87 142 | 97.47 164 | 97.39 162 | 99.14 39 | 99.01 54 | 99.54 39 | 98.60 97 |
|
CVMVSNet | | | 97.38 164 | 97.39 141 | 97.37 194 | 98.58 212 | 97.72 197 | 98.70 142 | 97.42 220 | 97.21 94 | 95.95 220 | 99.46 68 | 93.31 192 | 97.38 163 | 97.60 162 | 97.78 132 | 96.18 210 | 98.66 94 |
|
OpenMVS | | 97.26 9 | 97.88 139 | 97.17 151 | 98.70 135 | 99.50 127 | 98.55 153 | 98.34 180 | 99.11 157 | 93.92 196 | 98.90 109 | 95.04 199 | 98.23 144 | 97.38 163 | 98.11 122 | 98.12 108 | 98.95 119 | 98.23 128 |
|
pmmvs3 | | | 96.30 189 | 95.87 185 | 96.80 211 | 97.66 233 | 96.48 211 | 97.93 197 | 93.80 234 | 93.40 203 | 98.54 135 | 98.27 126 | 97.50 163 | 97.37 165 | 97.49 168 | 93.11 216 | 95.52 215 | 94.85 207 |
|
abl_6 | | | | | 98.38 159 | 99.03 191 | 98.04 181 | 98.08 193 | 98.65 187 | 93.23 204 | 98.56 132 | 94.58 206 | 98.57 137 | 97.17 166 | | | 98.81 143 | 97.42 167 |
|
Anonymous202405211 | | | | 98.44 83 | | 99.79 33 | 99.32 52 | 99.05 106 | 99.34 120 | 96.59 122 | | 97.95 141 | 97.68 161 | 97.16 167 | 99.36 30 | 99.28 33 | 99.61 34 | 98.90 67 |
|
MVS_Test | | | 97.69 147 | 97.15 153 | 98.33 161 | 99.27 164 | 98.43 163 | 98.25 185 | 99.29 129 | 95.00 169 | 97.39 196 | 98.86 106 | 98.00 153 | 97.14 168 | 95.38 210 | 96.22 191 | 98.62 163 | 98.15 139 |
|
TSAR-MVS + COLMAP | | | 97.62 151 | 97.31 143 | 97.98 180 | 98.47 218 | 97.39 203 | 98.29 183 | 98.25 203 | 96.68 117 | 97.54 190 | 98.87 105 | 98.04 152 | 97.08 169 | 96.78 190 | 96.26 190 | 98.26 181 | 97.12 180 |
|
test20.03 | | | 98.84 73 | 98.74 49 | 98.95 107 | 99.77 38 | 99.33 48 | 99.21 92 | 99.46 86 | 97.29 86 | 98.88 113 | 99.65 49 | 99.10 102 | 97.07 170 | 99.11 42 | 98.76 71 | 99.32 82 | 97.98 149 |
|
DELS-MVS | | | 98.63 93 | 98.70 53 | 98.55 150 | 99.24 170 | 99.04 95 | 98.96 117 | 98.52 194 | 96.83 107 | 98.38 149 | 99.58 57 | 99.68 22 | 97.06 171 | 98.74 75 | 98.44 95 | 99.10 99 | 98.59 98 |
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 |
tfpn1000 | | | 97.10 170 | 95.97 182 | 98.41 156 | 99.64 89 | 99.30 53 | 98.89 128 | 99.49 81 | 96.49 130 | 95.97 219 | 95.31 195 | 85.62 216 | 96.92 172 | 97.86 138 | 99.13 42 | 99.53 44 | 98.11 140 |
|
MVS_0304 | | | 98.57 100 | 98.36 92 | 98.82 124 | 99.72 58 | 98.94 120 | 98.92 122 | 99.14 152 | 96.76 113 | 99.33 42 | 98.30 124 | 99.73 12 | 96.74 173 | 98.05 124 | 97.79 131 | 99.08 104 | 98.97 55 |
|
thres100view900 | | | 95.74 199 | 93.66 208 | 98.17 171 | 99.37 142 | 98.59 149 | 98.10 191 | 98.33 201 | 92.02 217 | 97.30 202 | 86.53 231 | 86.34 210 | 96.69 174 | 96.77 191 | 98.47 94 | 99.24 92 | 96.89 184 |
|
new_pmnet | | | 96.59 181 | 96.40 171 | 96.81 210 | 98.24 227 | 95.46 229 | 97.71 209 | 94.75 233 | 96.92 103 | 96.80 214 | 99.23 84 | 97.81 159 | 96.69 174 | 96.58 194 | 95.16 205 | 96.69 206 | 93.64 215 |
|
FMVSNet1 | | | 98.90 60 | 99.10 27 | 98.67 139 | 99.54 112 | 99.48 33 | 99.22 90 | 99.66 41 | 98.39 25 | 97.50 191 | 99.66 45 | 99.04 111 | 96.58 176 | 99.05 49 | 99.03 50 | 99.52 45 | 99.08 43 |
|
CANet | | | 98.47 109 | 98.30 97 | 98.67 139 | 99.65 81 | 98.87 129 | 98.82 135 | 99.01 167 | 96.14 144 | 99.29 51 | 98.86 106 | 99.01 114 | 96.54 177 | 98.36 96 | 98.08 110 | 98.72 156 | 98.80 80 |
|
diffmvs | | | 97.05 171 | 96.20 177 | 98.04 178 | 99.08 187 | 98.01 182 | 98.20 188 | 99.10 159 | 94.48 181 | 97.31 201 | 95.15 197 | 97.82 158 | 96.53 178 | 94.32 221 | 94.76 210 | 98.05 188 | 98.82 73 |
|
GA-MVS | | | 96.84 176 | 95.86 186 | 97.98 180 | 99.16 179 | 98.29 166 | 97.91 198 | 98.64 189 | 95.14 163 | 97.71 184 | 98.04 138 | 88.90 199 | 96.50 179 | 96.41 196 | 96.61 186 | 97.97 191 | 97.60 160 |
|
MAR-MVS | | | 97.12 168 | 96.28 175 | 98.11 175 | 98.94 195 | 97.22 204 | 97.65 211 | 99.38 101 | 90.93 232 | 98.15 163 | 95.17 196 | 97.13 170 | 96.48 180 | 97.71 153 | 97.40 162 | 98.06 187 | 98.40 114 |
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 |
PMMVS2 | | | 96.29 190 | 97.05 155 | 95.40 227 | 98.32 224 | 96.16 216 | 98.18 189 | 97.46 219 | 97.20 96 | 84.51 241 | 99.60 53 | 98.68 131 | 96.37 181 | 98.59 80 | 97.38 163 | 97.58 196 | 91.76 224 |
|
CR-MVSNet | | | 95.38 203 | 93.01 211 | 98.16 173 | 98.63 210 | 95.85 225 | 97.64 212 | 99.78 19 | 91.27 228 | 98.50 139 | 96.84 172 | 82.16 224 | 96.34 182 | 94.40 219 | 95.50 200 | 98.05 188 | 95.04 205 |
|
PatchT | | | 95.49 201 | 93.29 210 | 98.06 177 | 98.65 209 | 96.20 215 | 98.91 124 | 99.73 28 | 92.00 223 | 98.50 139 | 96.67 175 | 83.25 222 | 96.34 182 | 94.40 219 | 95.50 200 | 96.21 209 | 95.04 205 |
|
PVSNet_BlendedMVS | | | 97.93 137 | 97.66 132 | 98.25 165 | 99.30 157 | 98.67 142 | 98.31 181 | 97.95 212 | 94.30 189 | 98.75 121 | 97.63 148 | 98.76 125 | 96.30 184 | 98.29 104 | 97.78 132 | 98.93 121 | 98.18 135 |
|
PVSNet_Blended | | | 97.93 137 | 97.66 132 | 98.25 165 | 99.30 157 | 98.67 142 | 98.31 181 | 97.95 212 | 94.30 189 | 98.75 121 | 97.63 148 | 98.76 125 | 96.30 184 | 98.29 104 | 97.78 132 | 98.93 121 | 98.18 135 |
|
CHOSEN 280x420 | | | 96.80 177 | 96.30 174 | 97.39 193 | 99.09 185 | 96.52 210 | 98.76 140 | 99.29 129 | 93.88 197 | 97.65 185 | 98.34 121 | 93.66 190 | 96.29 186 | 98.28 107 | 97.73 143 | 93.27 225 | 95.70 198 |
|
tfpn_ndepth | | | 96.69 179 | 95.49 191 | 98.09 176 | 99.17 177 | 99.13 80 | 98.61 159 | 99.38 101 | 94.90 173 | 95.85 221 | 92.85 216 | 88.19 201 | 96.07 187 | 97.28 181 | 98.67 80 | 99.49 53 | 97.44 165 |
|
Effi-MVS+-dtu | | | 97.78 142 | 97.37 142 | 98.26 164 | 99.25 168 | 98.50 158 | 97.89 200 | 99.19 146 | 94.51 178 | 98.16 162 | 95.93 190 | 98.80 124 | 95.97 188 | 98.27 109 | 97.38 163 | 99.10 99 | 98.23 128 |
|
LP | | | 95.33 205 | 93.45 209 | 97.54 192 | 98.68 207 | 97.40 202 | 98.73 141 | 98.41 199 | 96.33 137 | 98.92 107 | 97.84 144 | 88.30 200 | 95.92 189 | 92.98 225 | 89.38 221 | 94.56 219 | 91.90 223 |
|
ADS-MVSNet | | | 94.41 216 | 92.13 217 | 97.07 200 | 98.86 197 | 96.60 209 | 98.38 176 | 98.47 198 | 96.13 146 | 98.02 169 | 96.98 169 | 87.50 206 | 95.87 190 | 89.89 229 | 87.58 224 | 92.79 229 | 90.27 228 |
|
PMMVS | | | 96.47 184 | 95.81 187 | 97.23 197 | 97.38 236 | 95.96 223 | 97.31 221 | 96.91 226 | 93.21 205 | 97.93 176 | 97.14 162 | 97.64 162 | 95.70 191 | 95.24 212 | 96.18 194 | 98.17 185 | 95.33 203 |
|
MVS-HIRNet | | | 94.86 207 | 93.83 205 | 96.07 221 | 97.07 237 | 94.00 236 | 94.31 238 | 99.17 147 | 91.23 231 | 98.17 161 | 98.69 111 | 97.43 165 | 95.66 192 | 94.05 223 | 91.92 218 | 92.04 232 | 89.46 232 |
|
MDTV_nov1_ep13 | | | 94.47 214 | 92.15 216 | 97.17 198 | 98.54 216 | 96.42 213 | 98.10 191 | 98.89 173 | 94.49 179 | 98.02 169 | 97.41 155 | 86.49 207 | 95.56 193 | 90.85 228 | 87.95 223 | 93.91 221 | 91.45 226 |
|
PatchmatchNet | | | 93.88 220 | 91.08 223 | 97.14 199 | 98.75 202 | 96.01 222 | 98.25 185 | 99.39 94 | 94.95 171 | 98.96 100 | 96.32 183 | 85.35 217 | 95.50 194 | 88.89 231 | 85.89 229 | 91.99 233 | 90.15 229 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
testus | | | 96.13 196 | 95.13 192 | 97.28 196 | 99.13 182 | 97.00 207 | 96.84 229 | 97.89 216 | 90.48 233 | 97.40 194 | 93.60 211 | 96.47 177 | 95.39 195 | 96.21 197 | 96.19 193 | 97.05 203 | 95.99 195 |
|
DWT-MVSNet_training | | | 91.07 231 | 86.55 234 | 96.35 219 | 98.28 225 | 95.82 228 | 98.00 194 | 95.03 232 | 91.24 230 | 97.99 173 | 90.35 223 | 63.43 239 | 95.25 196 | 86.06 235 | 86.62 227 | 93.55 223 | 92.30 221 |
|
E-PMN | | | 92.28 228 | 90.12 225 | 94.79 230 | 98.56 214 | 90.90 238 | 95.16 236 | 93.68 235 | 95.36 159 | 95.10 230 | 96.56 178 | 89.05 198 | 95.24 197 | 95.21 213 | 81.84 235 | 90.98 235 | 81.94 236 |
|
PMVS | | 92.51 17 | 98.66 89 | 98.86 42 | 98.43 155 | 99.26 165 | 98.98 107 | 98.60 160 | 98.59 191 | 97.73 57 | 99.45 32 | 99.38 74 | 98.54 138 | 95.24 197 | 99.62 14 | 99.61 11 | 99.42 63 | 98.17 137 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
test2356 | | | 92.46 224 | 88.72 232 | 96.82 209 | 98.48 217 | 95.34 231 | 96.22 234 | 98.09 209 | 87.46 239 | 96.01 218 | 92.82 217 | 64.42 238 | 95.10 199 | 94.08 222 | 94.05 214 | 97.02 204 | 92.87 217 |
|
CMPMVS | | 74.71 19 | 96.17 193 | 96.06 181 | 96.30 220 | 97.41 235 | 94.52 235 | 94.83 237 | 95.46 230 | 91.57 226 | 97.26 205 | 94.45 207 | 98.33 142 | 94.98 200 | 98.28 107 | 97.59 154 | 97.86 192 | 97.68 158 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
EPMVS | | | 93.67 221 | 90.82 224 | 96.99 206 | 98.62 211 | 96.39 214 | 98.40 174 | 99.11 157 | 95.54 157 | 97.87 177 | 97.14 162 | 81.27 228 | 94.97 201 | 88.54 233 | 86.80 226 | 92.95 227 | 90.06 230 |
|
RPMNet | | | 94.72 209 | 92.01 218 | 97.88 184 | 98.56 214 | 95.85 225 | 97.78 203 | 99.70 34 | 91.27 228 | 98.33 153 | 93.69 210 | 81.88 225 | 94.91 202 | 92.60 227 | 94.34 213 | 98.01 190 | 94.46 209 |
|
DeepMVS_CX | | | | | | | 87.86 241 | 92.27 241 | 61.98 237 | 93.64 200 | 93.62 235 | 91.17 219 | 91.67 195 | 94.90 203 | 95.99 203 | | 92.48 231 | 94.18 212 |
|
EMVS | | | 91.84 229 | 89.39 229 | 94.70 231 | 98.44 220 | 90.84 239 | 95.27 235 | 93.53 236 | 95.18 162 | 95.26 228 | 95.62 194 | 87.59 205 | 94.77 204 | 94.87 216 | 80.72 236 | 90.95 236 | 80.88 237 |
|
dps | | | 92.35 227 | 88.78 231 | 96.52 217 | 98.21 228 | 95.94 224 | 97.78 203 | 98.38 200 | 89.88 236 | 96.81 213 | 95.07 198 | 75.31 232 | 94.70 205 | 88.62 232 | 86.21 228 | 93.21 226 | 90.41 227 |
|
tpm | | | 93.89 219 | 91.21 221 | 97.03 203 | 98.36 222 | 96.07 220 | 97.53 219 | 99.65 43 | 92.24 212 | 98.64 127 | 97.23 159 | 74.67 234 | 94.64 206 | 92.68 226 | 90.73 219 | 93.37 224 | 94.82 208 |
|
CostFormer | | | 92.75 223 | 89.49 227 | 96.55 216 | 98.78 201 | 95.83 227 | 97.55 215 | 98.59 191 | 91.83 225 | 97.34 199 | 96.31 184 | 78.53 229 | 94.50 207 | 86.14 234 | 84.92 230 | 92.54 230 | 92.84 218 |
|
GBi-Net | | | 97.69 147 | 97.75 129 | 97.62 189 | 98.71 203 | 99.21 64 | 98.62 156 | 99.33 121 | 94.09 192 | 95.60 223 | 98.17 131 | 95.97 180 | 94.39 208 | 99.05 49 | 99.03 50 | 99.08 104 | 98.70 89 |
|
test1 | | | 97.69 147 | 97.75 129 | 97.62 189 | 98.71 203 | 99.21 64 | 98.62 156 | 99.33 121 | 94.09 192 | 95.60 223 | 98.17 131 | 95.97 180 | 94.39 208 | 99.05 49 | 99.03 50 | 99.08 104 | 98.70 89 |
|
FMVSNet2 | | | 97.94 136 | 98.08 112 | 97.77 188 | 98.71 203 | 99.21 64 | 98.62 156 | 99.47 83 | 96.62 119 | 96.37 216 | 99.20 86 | 97.70 160 | 94.39 208 | 97.39 174 | 97.75 140 | 99.08 104 | 98.70 89 |
|
Fast-Effi-MVS+-dtu | | | 96.99 172 | 96.46 169 | 97.61 191 | 98.98 193 | 97.89 188 | 97.54 216 | 99.76 22 | 93.43 202 | 96.55 215 | 94.93 200 | 98.06 150 | 94.32 211 | 96.93 187 | 96.50 188 | 98.53 170 | 97.47 164 |
|
gm-plane-assit | | | 94.62 210 | 91.39 220 | 98.39 158 | 99.90 13 | 99.47 35 | 99.40 66 | 99.65 43 | 97.44 77 | 99.56 22 | 99.68 44 | 59.40 244 | 94.23 212 | 96.17 199 | 94.77 209 | 97.61 195 | 92.79 219 |
|
CDS-MVSNet | | | 97.75 143 | 97.68 131 | 97.83 186 | 99.08 187 | 98.20 175 | 98.68 144 | 98.61 190 | 95.63 155 | 97.80 178 | 99.24 80 | 96.93 173 | 94.09 213 | 97.96 128 | 97.82 130 | 98.71 157 | 97.99 147 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
TAMVS | | | 96.95 174 | 96.94 159 | 96.97 207 | 99.07 190 | 97.67 200 | 97.98 196 | 97.12 224 | 95.04 166 | 95.41 226 | 99.27 79 | 95.57 184 | 94.09 213 | 97.32 178 | 97.11 173 | 98.16 186 | 96.59 188 |
|
CANet_DTU | | | 97.65 150 | 97.50 140 | 97.82 187 | 99.19 175 | 98.08 179 | 98.41 173 | 98.67 186 | 94.40 186 | 99.16 71 | 98.32 123 | 98.69 129 | 93.96 215 | 97.87 137 | 97.61 152 | 97.51 197 | 97.56 163 |
|
tpmp4_e23 | | | 92.43 226 | 88.82 230 | 96.64 215 | 98.46 219 | 95.17 232 | 97.61 214 | 98.85 175 | 92.42 209 | 98.18 160 | 93.03 215 | 74.92 233 | 93.80 216 | 88.91 230 | 84.60 231 | 92.95 227 | 92.66 220 |
|
MIMVSNet | | | 97.24 166 | 97.15 153 | 97.36 195 | 99.03 191 | 98.52 157 | 98.55 165 | 99.73 28 | 94.94 172 | 94.94 231 | 97.98 139 | 97.37 167 | 93.66 217 | 97.60 162 | 97.34 165 | 98.23 183 | 96.29 191 |
|
tpmrst | | | 92.45 225 | 89.48 228 | 95.92 224 | 98.43 221 | 95.03 233 | 97.14 224 | 97.92 215 | 94.16 191 | 97.56 189 | 97.86 143 | 81.63 227 | 93.56 218 | 85.89 236 | 82.86 232 | 90.91 237 | 88.95 235 |
|
FMVSNet5 | | | 94.57 212 | 92.77 212 | 96.67 214 | 97.88 229 | 98.72 139 | 97.54 216 | 98.70 185 | 88.64 238 | 95.11 229 | 86.90 229 | 81.77 226 | 93.27 219 | 97.92 133 | 98.07 111 | 97.50 198 | 97.34 170 |
|
FMVSNet3 | | | 96.85 175 | 96.67 162 | 97.06 201 | 97.56 234 | 99.01 104 | 97.99 195 | 99.33 121 | 94.09 192 | 95.60 223 | 98.17 131 | 95.97 180 | 93.26 220 | 94.76 218 | 96.22 191 | 98.59 166 | 98.46 108 |
|
FPMVS | | | 96.97 173 | 97.20 150 | 96.70 213 | 97.75 231 | 96.11 219 | 97.72 207 | 95.47 229 | 97.13 98 | 98.02 169 | 97.57 150 | 96.67 175 | 92.97 221 | 99.00 57 | 98.34 99 | 98.28 180 | 95.58 199 |
|
testgi | | | 98.18 130 | 98.44 83 | 97.89 183 | 99.78 36 | 99.23 60 | 98.78 139 | 99.21 141 | 97.26 90 | 97.41 193 | 97.39 156 | 99.36 61 | 92.85 222 | 98.82 70 | 98.66 82 | 99.31 83 | 98.35 117 |
|
tpm cat1 | | | 91.52 230 | 87.70 233 | 95.97 223 | 98.33 223 | 94.98 234 | 97.06 226 | 98.03 211 | 92.11 216 | 98.03 168 | 94.77 201 | 77.19 231 | 92.71 223 | 83.56 237 | 82.24 234 | 91.67 234 | 89.04 234 |
|
test-mter | | | 94.62 210 | 94.02 203 | 95.32 228 | 97.72 232 | 96.75 208 | 96.23 233 | 95.67 228 | 89.83 237 | 93.23 238 | 96.99 168 | 85.94 214 | 92.66 224 | 97.32 178 | 96.11 196 | 96.44 207 | 95.22 204 |
|
test12356 | | | 95.71 200 | 95.55 190 | 95.89 225 | 98.27 226 | 96.48 211 | 96.90 228 | 97.35 222 | 92.13 215 | 95.64 222 | 99.13 89 | 97.97 154 | 92.34 225 | 96.94 186 | 96.55 187 | 94.87 218 | 89.61 231 |
|
UGNet | | | 98.52 105 | 99.00 30 | 97.96 182 | 99.58 102 | 99.26 56 | 99.27 83 | 99.40 92 | 98.07 30 | 98.28 157 | 98.76 109 | 99.71 17 | 92.24 226 | 98.94 60 | 98.85 60 | 99.00 115 | 99.43 19 |
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 |
test-LLR | | | 94.79 208 | 93.71 206 | 96.06 222 | 99.20 172 | 96.16 216 | 96.31 231 | 98.50 195 | 89.98 234 | 94.08 232 | 97.01 166 | 86.43 208 | 92.20 227 | 96.76 192 | 95.31 202 | 96.05 211 | 94.31 210 |
|
TESTMET0.1,1 | | | 94.44 215 | 93.71 206 | 95.30 229 | 97.84 230 | 96.16 216 | 96.31 231 | 95.32 231 | 89.98 234 | 94.08 232 | 97.01 166 | 86.43 208 | 92.20 227 | 96.76 192 | 95.31 202 | 96.05 211 | 94.31 210 |
|
IB-MVS | | 95.85 14 | 95.87 197 | 94.88 193 | 97.02 204 | 99.09 185 | 98.25 171 | 97.16 223 | 97.38 221 | 91.97 224 | 97.77 179 | 83.61 239 | 97.29 168 | 92.03 229 | 97.16 183 | 97.66 147 | 98.66 159 | 98.20 134 |
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 |
MVSTER | | | 95.38 203 | 93.99 204 | 97.01 205 | 98.83 199 | 98.95 116 | 96.62 230 | 99.14 152 | 92.17 214 | 97.44 192 | 97.29 157 | 77.88 230 | 91.63 230 | 97.45 170 | 96.18 194 | 98.41 176 | 97.99 147 |
|
EPNet_dtu | | | 96.31 188 | 95.96 183 | 96.72 212 | 99.18 176 | 95.39 230 | 97.03 227 | 99.13 156 | 93.02 207 | 99.35 40 | 97.23 159 | 97.07 171 | 90.70 231 | 95.74 206 | 95.08 207 | 94.94 217 | 98.16 138 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
1111 | | | 94.22 217 | 92.26 215 | 96.51 218 | 99.71 61 | 98.75 136 | 99.03 108 | 99.83 12 | 95.01 167 | 93.39 236 | 99.54 63 | 60.23 242 | 89.58 232 | 97.90 134 | 97.62 151 | 97.50 198 | 96.75 185 |
|
.test1245 | | | 74.10 233 | 68.09 236 | 81.11 234 | 99.71 61 | 98.75 136 | 99.03 108 | 99.83 12 | 95.01 167 | 93.39 236 | 99.54 63 | 60.23 242 | 89.58 232 | 97.90 134 | 10.38 238 | 5.14 242 | 14.81 238 |
|
EPNet | | | 96.44 185 | 96.08 180 | 96.86 208 | 99.32 154 | 97.15 206 | 97.69 210 | 99.32 126 | 93.67 199 | 98.11 165 | 95.64 193 | 93.44 191 | 89.07 234 | 96.86 189 | 96.83 180 | 97.67 193 | 98.97 55 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
test0.0.03 1 | | | 95.81 198 | 95.77 188 | 95.85 226 | 99.20 172 | 98.15 177 | 97.49 220 | 98.50 195 | 92.24 212 | 92.74 239 | 96.82 173 | 92.70 193 | 88.60 235 | 97.31 180 | 97.01 179 | 98.57 168 | 96.19 194 |
|
gg-mvs-nofinetune | | | 96.77 178 | 96.52 168 | 97.06 201 | 99.66 75 | 97.82 191 | 97.54 216 | 99.86 9 | 98.69 17 | 98.61 128 | 99.94 4 | 89.62 197 | 88.37 236 | 97.55 165 | 96.67 184 | 98.30 179 | 95.35 202 |
|
testpf | | | 87.81 232 | 83.90 235 | 92.37 232 | 96.76 239 | 88.65 240 | 93.04 240 | 98.24 204 | 85.20 240 | 95.28 227 | 86.82 230 | 72.43 236 | 82.35 237 | 82.62 238 | 82.30 233 | 88.55 238 | 89.29 233 |
|
tmp_tt | | | | | 65.28 235 | 82.24 241 | 71.50 243 | 70.81 243 | 23.21 238 | 96.14 144 | 81.70 242 | 85.98 236 | 92.44 194 | 49.84 238 | 95.81 204 | 94.36 212 | 83.86 240 | |
|
testmvs | | | 9.73 235 | 13.38 237 | 5.48 238 | 3.62 242 | 4.12 244 | 6.40 245 | 3.19 240 | 14.92 241 | 7.68 245 | 22.10 240 | 13.89 246 | 6.83 239 | 13.47 239 | 10.38 238 | 5.14 242 | 14.81 238 |
|
test123 | | | 9.37 236 | 12.26 238 | 6.00 237 | 3.32 243 | 4.06 245 | 6.39 246 | 3.41 239 | 13.20 242 | 10.48 244 | 16.43 241 | 16.22 245 | 6.76 240 | 11.37 240 | 10.40 237 | 5.62 241 | 14.10 240 |
|
GG-mvs-BLEND | | | 65.66 234 | 92.62 214 | 34.20 236 | 1.45 244 | 93.75 237 | 85.40 242 | 1.64 241 | 91.37 227 | 17.21 243 | 87.25 227 | 94.78 187 | 3.25 241 | 95.64 208 | 93.80 215 | 96.27 208 | 91.74 225 |
|
sosnet-low-res | | | 0.00 237 | 0.00 239 | 0.00 239 | 0.00 245 | 0.00 246 | 0.00 247 | 0.00 242 | 0.00 243 | 0.00 246 | 0.00 242 | 0.00 247 | 0.00 242 | 0.00 241 | 0.00 240 | 0.00 244 | 0.00 241 |
|
sosnet | | | 0.00 237 | 0.00 239 | 0.00 239 | 0.00 245 | 0.00 246 | 0.00 247 | 0.00 242 | 0.00 243 | 0.00 246 | 0.00 242 | 0.00 247 | 0.00 242 | 0.00 241 | 0.00 240 | 0.00 244 | 0.00 241 |
|
our_test_3 | | | | | | 99.29 160 | 97.72 197 | 98.98 114 | | | | | | | | | | |
|
MTAPA | | | | | | | | | | | 99.19 65 | | 99.68 22 | | | | | |
|
MTMP | | | | | | | | | | | 99.20 63 | | 99.54 42 | | | | | |
|
Patchmatch-RL test | | | | | | | | 32.47 244 | | | | | | | | | | |
|
XVS | | | | | | 99.77 38 | 99.07 86 | 99.46 60 | | | 98.95 102 | | 99.37 57 | | | | 99.33 79 | |
|
X-MVStestdata | | | | | | 99.77 38 | 99.07 86 | 99.46 60 | | | 98.95 102 | | 99.37 57 | | | | 99.33 79 | |
|
mPP-MVS | | | | | | 99.75 47 | | | | | | | 99.49 50 | | | | | |
|
NP-MVS | | | | | | | | | | 93.07 206 | | | | | | | | |
|
Patchmtry | | | | | | | 96.05 221 | 97.64 212 | 99.78 19 | | 98.50 139 | | | | | | | |
|