LCM-MVSNet | | | 95.70 1 | 96.40 1 | 93.61 2 | 98.67 1 | 85.39 22 | 95.54 3 | 97.36 1 | 96.97 1 | 99.04 1 | 99.05 1 | 96.61 1 | 95.92 6 | 85.07 28 | 99.27 3 | 99.54 1 |
|
TDRefinement | | | 93.52 2 | 93.39 3 | 93.88 1 | 95.94 10 | 90.26 3 | 95.70 2 | 96.46 2 | 90.58 7 | 92.86 37 | 96.29 16 | 88.16 22 | 94.17 56 | 86.07 24 | 98.48 19 | 97.22 25 |
|
LTVRE_ROB | | 86.10 1 | 93.04 3 | 93.44 2 | 91.82 15 | 93.73 38 | 85.72 21 | 96.79 1 | 95.51 4 | 88.86 11 | 95.63 10 | 96.99 6 | 84.81 44 | 93.16 107 | 91.10 1 | 97.53 49 | 96.58 36 |
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 |
HPM-MVS_fast | | | 92.50 4 | 92.54 4 | 92.37 3 | 95.93 11 | 85.81 20 | 92.99 10 | 94.23 15 | 85.21 22 | 92.51 44 | 95.13 40 | 90.65 9 | 95.34 27 | 88.06 5 | 98.15 30 | 95.95 48 |
|
HPM-MVS | | | 92.13 5 | 92.20 6 | 91.91 12 | 95.58 17 | 84.67 31 | 93.51 6 | 94.85 9 | 82.88 36 | 91.77 53 | 93.94 78 | 90.55 11 | 95.73 14 | 88.50 4 | 98.23 27 | 95.33 66 |
|
APD-MVS_3200maxsize | | | 92.05 6 | 92.24 5 | 91.48 16 | 93.02 53 | 85.17 24 | 92.47 18 | 95.05 8 | 87.65 17 | 93.21 33 | 94.39 61 | 90.09 12 | 95.08 34 | 86.67 16 | 97.60 48 | 94.18 88 |
|
COLMAP_ROB |  | 83.01 3 | 91.97 7 | 91.95 7 | 92.04 7 | 93.68 39 | 86.15 12 | 93.37 8 | 95.10 7 | 90.28 8 | 92.11 48 | 95.03 42 | 89.75 13 | 94.93 37 | 79.95 92 | 98.27 25 | 95.04 72 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
ACMMP |  | | 91.91 8 | 91.87 12 | 92.03 8 | 95.53 18 | 85.91 15 | 93.35 9 | 94.16 18 | 82.52 40 | 92.39 47 | 94.14 69 | 89.15 15 | 95.62 16 | 87.35 11 | 98.24 26 | 94.56 77 |
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 |
mPP-MVS | | | 91.69 9 | 91.47 17 | 92.37 3 | 96.04 9 | 88.48 5 | 92.72 12 | 92.60 63 | 83.09 33 | 91.54 56 | 94.25 65 | 87.67 27 | 95.51 24 | 87.21 15 | 98.11 31 | 93.12 116 |
|
CP-MVS | | | 91.67 10 | 91.58 14 | 91.96 9 | 95.29 21 | 87.62 6 | 93.38 7 | 93.36 32 | 83.16 32 | 91.06 62 | 94.00 72 | 88.26 19 | 95.71 15 | 87.28 14 | 98.39 21 | 92.55 126 |
|
XVS | | | 91.54 11 | 91.36 19 | 92.08 5 | 95.64 15 | 86.25 10 | 92.64 13 | 93.33 34 | 85.07 23 | 89.99 76 | 94.03 71 | 86.57 33 | 95.80 11 | 87.35 11 | 97.62 46 | 94.20 86 |
|
UA-Net | | | 91.49 12 | 91.53 15 | 91.39 18 | 94.98 25 | 82.95 43 | 93.52 5 | 92.79 57 | 88.22 14 | 88.53 110 | 97.64 2 | 83.45 53 | 94.55 48 | 86.02 25 | 98.60 14 | 96.67 34 |
|
ACMMPR | | | 91.49 12 | 91.35 21 | 91.92 11 | 95.74 13 | 85.88 17 | 92.58 16 | 93.25 40 | 81.99 46 | 91.40 59 | 94.17 68 | 87.51 28 | 95.87 8 | 87.74 6 | 97.76 41 | 93.99 91 |
|
LPG-MVS_test | | | 91.47 14 | 91.68 13 | 90.82 27 | 94.75 28 | 81.69 44 | 90.00 33 | 94.27 12 | 82.35 41 | 93.67 27 | 94.82 46 | 91.18 4 | 95.52 22 | 85.36 26 | 98.73 8 | 95.23 69 |
|
region2R | | | 91.44 15 | 91.30 23 | 91.87 13 | 95.75 12 | 85.90 16 | 92.63 15 | 93.30 37 | 81.91 48 | 90.88 67 | 94.21 66 | 87.75 24 | 95.87 8 | 87.60 9 | 97.71 44 | 93.83 95 |
|
HFP-MVS | | | 91.30 16 | 91.39 18 | 91.02 23 | 95.43 19 | 84.66 32 | 92.58 16 | 93.29 38 | 81.99 46 | 91.47 57 | 93.96 75 | 88.35 17 | 95.56 19 | 87.74 6 | 97.74 42 | 92.85 119 |
|
APDe-MVS | | | 91.22 17 | 91.92 8 | 89.14 46 | 92.97 55 | 78.04 66 | 92.84 11 | 94.14 19 | 83.33 30 | 93.90 23 | 95.73 26 | 88.77 16 | 96.41 1 | 87.60 9 | 97.98 37 | 92.98 118 |
|
PGM-MVS | | | 91.20 18 | 90.95 27 | 91.93 10 | 95.67 14 | 85.85 18 | 90.00 33 | 93.90 24 | 80.32 62 | 91.74 54 | 94.41 60 | 88.17 21 | 95.98 4 | 86.37 17 | 97.99 36 | 93.96 93 |
|
SteuartSystems-ACMMP | | | 91.16 19 | 91.36 19 | 90.55 30 | 93.91 37 | 80.97 51 | 91.49 25 | 93.48 31 | 82.82 37 | 92.60 43 | 93.97 73 | 88.19 20 | 96.29 2 | 87.61 8 | 98.20 29 | 94.39 84 |
Skip Steuart: Steuart Systems R&D Blog. |
MP-MVS |  | | 91.14 20 | 90.91 28 | 91.83 14 | 96.18 8 | 86.88 8 | 92.20 19 | 93.03 49 | 82.59 39 | 88.52 111 | 94.37 62 | 86.74 32 | 95.41 25 | 86.32 18 | 98.21 28 | 93.19 115 |
|
ACMH+ | | 77.89 11 | 90.73 21 | 91.50 16 | 88.44 51 | 93.00 54 | 76.26 84 | 89.65 42 | 95.55 3 | 87.72 16 | 93.89 24 | 94.94 44 | 91.62 3 | 93.44 94 | 78.35 105 | 98.76 5 | 95.61 61 |
|
ACMM | | 79.39 9 | 90.65 22 | 90.99 25 | 89.63 41 | 95.03 24 | 83.53 37 | 89.62 43 | 93.35 33 | 79.20 75 | 93.83 25 | 93.60 82 | 90.81 7 | 92.96 113 | 85.02 30 | 98.45 20 | 92.41 129 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
LS3D | | | 90.60 23 | 90.34 34 | 91.38 19 | 89.03 131 | 84.23 35 | 93.58 4 | 94.68 10 | 90.65 6 | 90.33 71 | 93.95 77 | 84.50 47 | 95.37 26 | 80.87 77 | 95.50 106 | 94.53 80 |
|
ACMP | | 79.16 10 | 90.54 24 | 90.60 31 | 90.35 34 | 94.36 31 | 80.98 50 | 89.16 52 | 94.05 21 | 79.03 79 | 92.87 36 | 93.74 81 | 90.60 10 | 95.21 32 | 82.87 56 | 98.76 5 | 94.87 73 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
#test# | | | 90.49 25 | 90.31 35 | 91.02 23 | 95.43 19 | 84.66 32 | 90.65 30 | 93.29 38 | 77.00 101 | 91.47 57 | 93.96 75 | 88.35 17 | 95.56 19 | 84.88 31 | 97.74 42 | 92.85 119 |
|
v7n | | | 90.13 26 | 90.96 26 | 87.65 63 | 91.95 80 | 71.06 117 | 89.99 35 | 93.05 46 | 86.53 19 | 94.29 19 | 96.27 17 | 82.69 60 | 94.08 59 | 86.25 21 | 97.63 45 | 97.82 10 |
|
PMVS |  | 80.48 6 | 90.08 27 | 90.66 30 | 88.34 53 | 96.71 2 | 92.97 2 | 90.31 31 | 89.57 142 | 88.51 13 | 90.11 72 | 95.12 41 | 90.98 6 | 88.92 187 | 77.55 112 | 97.07 57 | 83.13 234 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
PS-CasMVS | | | 90.06 28 | 91.92 8 | 84.47 115 | 96.56 4 | 58.83 217 | 89.04 53 | 92.74 58 | 91.40 4 | 96.12 4 | 96.06 21 | 87.23 29 | 95.57 18 | 79.42 100 | 98.74 7 | 99.00 2 |
|
PEN-MVS | | | 90.03 29 | 91.88 11 | 84.48 114 | 96.57 3 | 58.88 216 | 88.95 54 | 93.19 41 | 91.62 3 | 96.01 6 | 96.16 20 | 87.02 30 | 95.60 17 | 78.69 103 | 98.72 10 | 98.97 3 |
|
OurMVSNet-221017-0 | | | 90.01 30 | 89.74 39 | 90.83 26 | 93.16 50 | 80.37 52 | 91.91 23 | 93.11 43 | 81.10 55 | 95.32 12 | 97.24 4 | 72.94 165 | 94.85 39 | 85.07 28 | 97.78 40 | 97.26 22 |
|
DTE-MVSNet | | | 89.98 31 | 91.91 10 | 84.21 122 | 96.51 5 | 57.84 220 | 88.93 55 | 92.84 56 | 91.92 2 | 96.16 3 | 96.23 18 | 86.95 31 | 95.99 3 | 79.05 101 | 98.57 16 | 98.80 6 |
|
XVG-ACMP-BASELINE | | | 89.98 31 | 89.84 37 | 90.41 32 | 94.91 27 | 84.50 34 | 89.49 48 | 93.98 22 | 79.68 68 | 92.09 49 | 93.89 79 | 83.80 50 | 93.10 109 | 82.67 60 | 98.04 32 | 93.64 104 |
|
v52 | | | 89.97 33 | 90.60 31 | 88.07 57 | 88.69 136 | 72.01 109 | 91.35 26 | 92.64 61 | 82.22 43 | 95.97 8 | 96.31 14 | 84.82 43 | 93.98 63 | 88.59 2 | 94.83 127 | 98.23 7 |
|
V4 | | | 89.97 33 | 90.60 31 | 88.07 57 | 88.69 136 | 72.01 109 | 91.35 26 | 92.64 61 | 82.22 43 | 95.98 7 | 96.31 14 | 84.80 45 | 93.98 63 | 88.59 2 | 94.83 127 | 98.23 7 |
|
3Dnovator+ | | 83.92 2 | 89.97 33 | 89.66 40 | 90.92 25 | 91.27 98 | 81.66 47 | 91.25 28 | 94.13 20 | 88.89 10 | 88.83 105 | 94.26 64 | 77.55 105 | 95.86 10 | 84.88 31 | 95.87 97 | 95.24 68 |
|
WR-MVS_H | | | 89.91 36 | 91.31 22 | 85.71 93 | 96.32 7 | 62.39 182 | 89.54 46 | 93.31 36 | 90.21 9 | 95.57 11 | 95.66 28 | 81.42 79 | 95.90 7 | 80.94 76 | 98.80 4 | 98.84 5 |
|
mvs_tets | | | 89.78 37 | 89.27 44 | 91.30 20 | 93.51 41 | 84.79 29 | 89.89 37 | 90.63 112 | 70.00 168 | 94.55 16 | 96.67 9 | 87.94 23 | 93.59 78 | 84.27 39 | 95.97 92 | 95.52 62 |
|
test_djsdf | | | 89.62 38 | 89.01 46 | 91.45 17 | 92.36 70 | 82.98 42 | 91.98 21 | 90.08 132 | 71.54 156 | 94.28 20 | 96.54 11 | 81.57 77 | 94.27 50 | 86.26 19 | 96.49 74 | 97.09 29 |
|
XVG-OURS-SEG-HR | | | 89.59 39 | 89.37 43 | 90.28 35 | 94.47 30 | 85.95 14 | 86.84 82 | 93.91 23 | 80.07 65 | 86.75 136 | 93.26 84 | 93.64 2 | 90.93 156 | 84.60 35 | 90.75 193 | 93.97 92 |
|
APD-MVS |  | | 89.54 40 | 89.63 41 | 89.26 45 | 92.57 63 | 81.34 49 | 90.19 32 | 93.08 45 | 80.87 57 | 91.13 61 | 93.19 85 | 86.22 38 | 95.97 5 | 82.23 64 | 97.18 55 | 90.45 164 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
jajsoiax | | | 89.41 41 | 88.81 50 | 91.19 22 | 93.38 45 | 84.72 30 | 89.70 39 | 90.29 127 | 69.27 171 | 94.39 17 | 96.38 13 | 86.02 40 | 93.52 88 | 83.96 42 | 95.92 95 | 95.34 65 |
|
CPTT-MVS | | | 89.39 42 | 88.98 48 | 90.63 29 | 95.09 23 | 86.95 7 | 92.09 20 | 92.30 68 | 79.74 67 | 87.50 124 | 92.38 105 | 81.42 79 | 93.28 102 | 83.07 53 | 97.24 53 | 91.67 142 |
|
ACMH | | 76.49 14 | 89.34 43 | 91.14 24 | 83.96 128 | 92.50 66 | 70.36 121 | 89.55 44 | 93.84 25 | 81.89 49 | 94.70 14 | 95.44 36 | 90.69 8 | 88.31 194 | 83.33 49 | 98.30 24 | 93.20 114 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
CP-MVSNet | | | 89.27 44 | 90.91 28 | 84.37 118 | 96.34 6 | 58.61 219 | 88.66 60 | 92.06 73 | 90.78 5 | 95.67 9 | 95.17 39 | 81.80 75 | 95.54 21 | 79.00 102 | 98.69 11 | 98.95 4 |
|
XVG-OURS | | | 89.18 45 | 88.83 49 | 90.23 36 | 94.28 32 | 86.11 13 | 85.91 96 | 93.60 29 | 80.16 64 | 89.13 101 | 93.44 83 | 83.82 49 | 90.98 154 | 83.86 45 | 95.30 113 | 93.60 106 |
|
DeepC-MVS | | 82.31 4 | 89.15 46 | 89.08 45 | 89.37 44 | 93.64 40 | 79.07 59 | 88.54 61 | 94.20 16 | 73.53 128 | 89.71 86 | 94.82 46 | 85.09 42 | 95.77 13 | 84.17 41 | 98.03 34 | 93.26 112 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
SD-MVS | | | 88.96 47 | 89.88 36 | 86.22 81 | 91.63 86 | 77.07 76 | 89.82 38 | 93.77 26 | 78.90 80 | 92.88 35 | 92.29 109 | 86.11 39 | 90.22 174 | 86.24 22 | 97.24 53 | 91.36 148 |
|
HPM-MVS++ | | | 88.93 48 | 88.45 54 | 90.38 33 | 94.92 26 | 85.85 18 | 89.70 39 | 91.27 102 | 78.20 87 | 86.69 137 | 92.28 110 | 80.36 86 | 95.06 35 | 86.17 23 | 96.49 74 | 90.22 168 |
|
v748 | | | 88.91 49 | 89.82 38 | 86.19 85 | 90.06 121 | 68.53 132 | 88.81 57 | 91.48 87 | 84.36 26 | 94.19 21 | 95.98 22 | 82.52 63 | 92.67 121 | 84.30 38 | 96.67 68 | 97.37 19 |
|
test_0402 | | | 88.65 50 | 89.58 42 | 85.88 90 | 92.55 64 | 72.22 108 | 84.01 120 | 89.44 144 | 88.63 12 | 94.38 18 | 95.77 25 | 86.38 37 | 93.59 78 | 79.84 93 | 95.21 114 | 91.82 139 |
|
DP-MVS | | | 88.60 51 | 89.01 46 | 87.36 67 | 91.30 96 | 77.50 71 | 87.55 70 | 92.97 51 | 87.95 15 | 89.62 92 | 92.87 94 | 84.56 46 | 93.89 66 | 77.65 111 | 96.62 69 | 90.70 157 |
|
wuykxyi23d | | | 88.46 52 | 88.80 51 | 87.44 66 | 90.96 106 | 93.03 1 | 85.85 98 | 81.96 205 | 74.58 120 | 98.58 2 | 97.29 3 | 87.73 25 | 87.31 200 | 82.84 58 | 99.41 1 | 81.99 247 |
|
PS-MVSNAJss | | | 88.31 53 | 87.90 57 | 89.56 43 | 93.31 46 | 77.96 67 | 87.94 65 | 91.97 76 | 70.73 162 | 94.19 21 | 96.67 9 | 76.94 112 | 94.57 46 | 83.07 53 | 96.28 79 | 96.15 39 |
|
OMC-MVS | | | 88.19 54 | 87.52 61 | 90.19 37 | 91.94 82 | 81.68 46 | 87.49 72 | 93.17 42 | 76.02 109 | 88.64 108 | 91.22 132 | 84.24 48 | 93.37 97 | 77.97 110 | 97.03 58 | 95.52 62 |
|
RPSCF | | | 88.00 55 | 86.93 73 | 91.22 21 | 90.08 119 | 89.30 4 | 89.68 41 | 91.11 105 | 79.26 74 | 89.68 87 | 94.81 49 | 82.44 64 | 87.74 197 | 76.54 120 | 88.74 210 | 96.61 35 |
|
AllTest | | | 87.97 56 | 87.40 65 | 89.68 39 | 91.59 87 | 83.40 38 | 89.50 47 | 95.44 5 | 79.47 70 | 88.00 118 | 93.03 88 | 82.66 61 | 91.47 143 | 70.81 152 | 96.14 86 | 94.16 89 |
|
TranMVSNet+NR-MVSNet | | | 87.86 57 | 88.76 52 | 85.18 99 | 94.02 34 | 64.13 153 | 84.38 116 | 91.29 101 | 84.88 25 | 92.06 50 | 93.84 80 | 86.45 35 | 93.73 69 | 73.22 142 | 98.66 12 | 97.69 11 |
|
nrg030 | | | 87.85 58 | 88.49 53 | 85.91 89 | 90.07 120 | 69.73 123 | 87.86 66 | 94.20 16 | 74.04 123 | 92.70 41 | 94.66 50 | 85.88 41 | 91.50 142 | 79.72 94 | 97.32 52 | 96.50 37 |
|
CNVR-MVS | | | 87.81 59 | 87.68 60 | 88.21 54 | 92.87 57 | 77.30 75 | 85.25 105 | 91.23 103 | 77.31 97 | 87.07 131 | 91.47 128 | 82.94 58 | 94.71 42 | 84.67 34 | 96.27 81 | 92.62 125 |
|
HQP_MVS | | | 87.75 60 | 87.43 64 | 88.70 49 | 93.45 42 | 76.42 82 | 89.45 49 | 93.61 27 | 79.44 72 | 86.55 138 | 92.95 92 | 74.84 129 | 95.22 30 | 80.78 79 | 95.83 99 | 94.46 81 |
|
NCCC | | | 87.36 61 | 86.87 74 | 88.83 47 | 92.32 72 | 78.84 62 | 86.58 92 | 91.09 106 | 78.77 82 | 84.85 161 | 90.89 149 | 80.85 82 | 95.29 28 | 81.14 73 | 95.32 110 | 92.34 132 |
|
v13 | | | 87.31 62 | 88.10 55 | 84.94 101 | 88.84 133 | 63.75 157 | 87.85 67 | 91.47 90 | 79.12 76 | 93.72 26 | 95.82 24 | 75.20 123 | 93.58 81 | 84.76 33 | 96.16 84 | 97.48 16 |
|
DeepPCF-MVS | | 81.24 5 | 87.28 63 | 86.21 85 | 90.49 31 | 91.48 94 | 84.90 27 | 83.41 141 | 92.38 67 | 70.25 167 | 89.35 99 | 90.68 156 | 82.85 59 | 94.57 46 | 79.55 96 | 95.95 93 | 92.00 137 |
|
SixPastTwentyTwo | | | 87.20 64 | 87.45 63 | 86.45 75 | 92.52 65 | 69.19 130 | 87.84 68 | 88.05 156 | 81.66 51 | 94.64 15 | 96.53 12 | 65.94 202 | 94.75 41 | 83.02 55 | 96.83 64 | 95.41 64 |
|
v12 | | | 87.15 65 | 87.91 56 | 84.84 103 | 88.69 136 | 63.52 160 | 87.58 69 | 91.46 91 | 78.74 83 | 93.57 29 | 95.66 28 | 74.94 127 | 93.57 82 | 84.50 36 | 96.08 89 | 97.43 17 |
|
v11 | | | 86.96 66 | 87.78 58 | 84.51 112 | 88.50 142 | 62.60 178 | 87.21 75 | 91.63 82 | 78.08 90 | 93.40 31 | 95.56 33 | 75.07 124 | 93.57 82 | 84.46 37 | 96.08 89 | 97.36 20 |
|
V9 | | | 86.96 66 | 87.70 59 | 84.74 107 | 88.52 141 | 63.27 166 | 87.31 74 | 91.45 93 | 78.28 86 | 93.43 30 | 95.45 35 | 74.59 135 | 93.57 82 | 84.23 40 | 96.01 91 | 97.38 18 |
|
UniMVSNet (Re) | | | 86.87 68 | 86.98 71 | 86.55 73 | 93.11 52 | 68.48 133 | 83.80 128 | 92.87 53 | 80.37 60 | 89.61 94 | 91.81 119 | 77.72 102 | 94.18 54 | 75.00 129 | 98.53 17 | 96.99 32 |
|
Vis-MVSNet |  | | 86.86 69 | 86.58 78 | 87.72 61 | 92.09 76 | 77.43 72 | 87.35 73 | 92.09 72 | 78.87 81 | 84.27 171 | 94.05 70 | 78.35 97 | 93.65 72 | 80.54 83 | 91.58 181 | 92.08 136 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
UniMVSNet_NR-MVSNet | | | 86.84 70 | 87.06 68 | 86.17 86 | 92.86 59 | 67.02 141 | 82.55 162 | 91.56 83 | 83.08 34 | 90.92 64 | 91.82 118 | 78.25 98 | 93.99 61 | 74.16 131 | 98.35 22 | 97.49 15 |
|
DU-MVS | | | 86.80 71 | 86.99 70 | 86.21 83 | 93.24 48 | 67.02 141 | 83.16 148 | 92.21 69 | 81.73 50 | 90.92 64 | 91.97 112 | 77.20 107 | 93.99 61 | 74.16 131 | 98.35 22 | 97.61 12 |
|
V14 | | | 86.75 72 | 87.46 62 | 84.62 110 | 88.35 145 | 63.00 169 | 87.02 80 | 91.42 95 | 77.78 92 | 93.27 32 | 95.23 38 | 74.22 136 | 93.56 85 | 83.95 43 | 95.93 94 | 97.31 21 |
|
Regformer-2 | | | 86.74 73 | 86.08 87 | 88.73 48 | 84.18 211 | 79.20 58 | 83.52 136 | 89.33 145 | 83.33 30 | 89.92 82 | 85.07 228 | 83.23 56 | 93.16 107 | 83.39 48 | 92.72 169 | 93.83 95 |
|
IS-MVSNet | | | 86.66 74 | 86.82 77 | 86.17 86 | 92.05 78 | 66.87 143 | 91.21 29 | 88.64 150 | 86.30 21 | 89.60 95 | 92.59 100 | 69.22 189 | 94.91 38 | 73.89 135 | 97.89 39 | 96.72 33 |
|
v15 | | | 86.56 75 | 87.25 66 | 84.51 112 | 88.15 149 | 62.72 174 | 86.72 89 | 91.40 97 | 77.38 95 | 93.11 34 | 95.00 43 | 73.93 142 | 93.55 86 | 83.67 47 | 95.86 98 | 97.26 22 |
|
v10 | | | 86.54 76 | 87.10 67 | 84.84 103 | 88.16 148 | 63.28 165 | 86.64 91 | 92.20 70 | 75.42 116 | 92.81 38 | 94.50 56 | 74.05 140 | 94.06 60 | 83.88 44 | 96.28 79 | 97.17 27 |
|
Regformer-4 | | | 86.41 77 | 85.71 92 | 88.52 50 | 84.27 207 | 77.57 70 | 84.07 118 | 88.00 158 | 82.82 37 | 89.84 83 | 85.48 220 | 82.06 68 | 92.77 118 | 83.83 46 | 91.04 186 | 95.22 71 |
|
PHI-MVS | | | 86.38 78 | 85.81 90 | 88.08 56 | 88.44 144 | 77.34 73 | 89.35 51 | 93.05 46 | 73.15 137 | 84.76 162 | 87.70 201 | 78.87 95 | 94.18 54 | 80.67 81 | 96.29 78 | 92.73 123 |
|
v17 | | | 86.32 79 | 86.95 72 | 84.44 116 | 88.00 151 | 62.62 177 | 86.74 87 | 91.48 87 | 77.17 98 | 92.74 39 | 94.56 52 | 73.74 146 | 93.53 87 | 83.27 50 | 94.87 126 | 97.18 26 |
|
test_prior3 | | | 86.31 80 | 86.31 82 | 86.32 77 | 90.59 113 | 71.99 111 | 83.37 142 | 92.85 54 | 75.43 114 | 84.58 163 | 91.57 123 | 81.92 73 | 94.17 56 | 79.54 97 | 96.97 59 | 92.80 121 |
|
CSCG | | | 86.26 81 | 86.47 80 | 85.60 95 | 90.87 108 | 74.26 92 | 87.98 64 | 91.85 79 | 80.35 61 | 89.54 98 | 88.01 196 | 79.09 93 | 92.13 129 | 75.51 124 | 95.06 119 | 90.41 165 |
|
v16 | | | 86.24 82 | 86.85 75 | 84.43 117 | 87.96 153 | 62.59 179 | 86.73 88 | 91.48 87 | 77.17 98 | 92.67 42 | 94.55 53 | 73.63 147 | 93.52 88 | 83.26 51 | 94.16 139 | 97.17 27 |
|
DeepC-MVS_fast | | 80.27 8 | 86.23 83 | 85.65 94 | 87.96 60 | 91.30 96 | 76.92 77 | 87.19 76 | 91.99 75 | 70.56 163 | 84.96 157 | 90.69 155 | 80.01 89 | 95.14 33 | 78.37 104 | 95.78 101 | 91.82 139 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
v8 | | | 86.22 84 | 86.83 76 | 84.36 119 | 87.82 155 | 62.35 183 | 86.42 93 | 91.33 100 | 76.78 102 | 92.73 40 | 94.48 57 | 73.41 154 | 93.72 70 | 83.10 52 | 95.41 107 | 97.01 31 |
|
CDPH-MVS | | | 86.17 85 | 85.54 95 | 88.05 59 | 92.25 73 | 75.45 87 | 83.85 125 | 92.01 74 | 65.91 194 | 86.19 144 | 91.75 121 | 83.77 51 | 94.98 36 | 77.43 114 | 96.71 67 | 93.73 101 |
|
Regformer-1 | | | 86.00 86 | 85.50 96 | 87.49 64 | 84.18 211 | 76.90 78 | 83.52 136 | 87.94 160 | 82.18 45 | 89.19 100 | 85.07 228 | 82.28 66 | 91.89 134 | 82.40 62 | 92.72 169 | 93.69 103 |
|
NR-MVSNet | | | 86.00 86 | 86.22 84 | 85.34 97 | 93.24 48 | 64.56 152 | 82.21 172 | 90.46 116 | 80.99 56 | 88.42 113 | 91.97 112 | 77.56 104 | 93.85 67 | 72.46 147 | 98.65 13 | 97.61 12 |
|
v18 | | | 85.99 88 | 86.55 79 | 84.30 120 | 87.73 161 | 62.29 187 | 86.40 94 | 91.49 86 | 76.64 103 | 92.40 46 | 94.20 67 | 73.28 158 | 93.52 88 | 82.87 56 | 93.99 143 | 97.09 29 |
|
FC-MVSNet-test | | | 85.93 89 | 87.05 69 | 82.58 154 | 92.25 73 | 56.44 231 | 85.75 99 | 93.09 44 | 77.33 96 | 91.94 51 | 94.65 51 | 74.78 131 | 93.41 96 | 75.11 127 | 98.58 15 | 97.88 9 |
|
agg_prior3 | | | 85.76 90 | 84.95 104 | 88.16 55 | 92.43 68 | 79.92 55 | 83.98 121 | 90.03 134 | 65.11 200 | 83.66 176 | 90.64 160 | 81.00 81 | 93.67 71 | 81.21 71 | 96.54 71 | 90.88 153 |
|
agg_prior1 | | | 85.72 91 | 85.20 99 | 87.28 68 | 91.58 90 | 77.69 68 | 83.69 131 | 90.30 124 | 66.29 190 | 84.32 168 | 91.07 143 | 82.13 67 | 93.18 105 | 81.02 74 | 96.36 77 | 90.98 149 |
|
TAPA-MVS | | 77.73 12 | 85.71 92 | 84.83 105 | 88.37 52 | 88.78 135 | 79.72 56 | 87.15 78 | 93.50 30 | 69.17 172 | 85.80 149 | 89.56 177 | 80.76 83 | 92.13 129 | 73.21 143 | 95.51 105 | 93.25 113 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
canonicalmvs | | | 85.50 93 | 86.14 86 | 83.58 140 | 87.97 152 | 67.13 140 | 87.55 70 | 94.32 11 | 73.44 130 | 88.47 112 | 87.54 204 | 86.45 35 | 91.06 153 | 75.76 123 | 93.76 150 | 92.54 127 |
|
EPP-MVSNet | | | 85.47 94 | 85.04 101 | 86.77 71 | 91.52 93 | 69.37 125 | 91.63 24 | 87.98 159 | 81.51 53 | 87.05 132 | 91.83 117 | 66.18 201 | 95.29 28 | 70.75 154 | 96.89 61 | 95.64 56 |
|
FIs | | | 85.35 95 | 86.27 83 | 82.60 153 | 91.86 83 | 57.31 224 | 85.10 107 | 93.05 46 | 75.83 112 | 91.02 63 | 93.97 73 | 73.57 151 | 92.91 116 | 73.97 134 | 98.02 35 | 97.58 14 |
|
K. test v3 | | | 85.14 96 | 84.73 106 | 86.37 76 | 91.13 103 | 69.63 124 | 85.45 103 | 76.68 230 | 84.06 28 | 92.44 45 | 96.99 6 | 62.03 214 | 94.65 43 | 80.58 82 | 93.24 162 | 94.83 76 |
|
EI-MVSNet-Vis-set | | | 85.12 97 | 84.53 118 | 86.88 69 | 84.01 213 | 72.76 100 | 83.91 124 | 85.18 188 | 80.44 59 | 88.75 106 | 85.49 219 | 80.08 88 | 91.92 132 | 82.02 65 | 90.85 191 | 95.97 46 |
|
Regformer-3 | | | 85.06 98 | 84.67 111 | 86.22 81 | 84.27 207 | 73.43 96 | 84.07 118 | 85.26 186 | 80.77 58 | 88.62 109 | 85.48 220 | 80.56 85 | 90.39 171 | 81.99 66 | 91.04 186 | 94.85 75 |
|
EI-MVSNet-UG-set | | | 85.04 99 | 84.44 120 | 86.85 70 | 83.87 215 | 72.52 103 | 83.82 126 | 85.15 189 | 80.27 63 | 88.75 106 | 85.45 222 | 79.95 90 | 91.90 133 | 81.92 67 | 90.80 192 | 96.13 40 |
|
X-MVStestdata | | | 85.04 99 | 82.70 141 | 92.08 5 | 95.64 15 | 86.25 10 | 92.64 13 | 93.33 34 | 85.07 23 | 89.99 76 | 16.05 295 | 86.57 33 | 95.80 11 | 87.35 11 | 97.62 46 | 94.20 86 |
|
MSLP-MVS | | | 85.00 101 | 86.03 88 | 81.90 160 | 91.84 84 | 71.56 115 | 86.75 86 | 93.02 50 | 75.95 110 | 87.12 128 | 89.39 179 | 77.98 99 | 89.40 184 | 77.46 113 | 94.78 129 | 84.75 214 |
|
F-COLMAP | | | 84.97 102 | 83.42 135 | 89.63 41 | 92.39 69 | 83.40 38 | 88.83 56 | 91.92 78 | 73.19 136 | 80.18 208 | 89.15 182 | 77.04 110 | 93.28 102 | 65.82 189 | 92.28 175 | 92.21 135 |
|
v7 | | | 84.81 103 | 85.00 102 | 84.23 121 | 88.15 149 | 63.27 166 | 83.79 129 | 91.39 98 | 71.10 160 | 90.07 73 | 91.28 130 | 74.04 141 | 93.63 74 | 81.48 70 | 93.67 153 | 95.79 49 |
|
3Dnovator | | 80.37 7 | 84.80 104 | 84.71 109 | 85.06 100 | 86.36 184 | 74.71 90 | 88.77 58 | 90.00 135 | 75.65 113 | 84.96 157 | 93.17 86 | 74.06 139 | 91.19 149 | 78.28 107 | 91.09 184 | 89.29 176 |
|
IterMVS-LS | | | 84.73 105 | 84.98 103 | 83.96 128 | 87.35 167 | 63.66 158 | 83.25 145 | 89.88 137 | 76.06 107 | 89.62 92 | 92.37 108 | 73.40 156 | 92.52 123 | 78.16 108 | 94.77 131 | 95.69 54 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
MVS_111021_HR | | | 84.63 106 | 84.34 127 | 85.49 96 | 90.18 118 | 75.86 86 | 79.23 207 | 87.13 167 | 73.35 131 | 85.56 153 | 89.34 180 | 83.60 52 | 90.50 169 | 76.64 119 | 94.05 142 | 90.09 171 |
|
HQP-MVS | | | 84.61 107 | 84.06 130 | 86.27 79 | 91.19 99 | 70.66 119 | 84.77 108 | 92.68 59 | 73.30 132 | 80.55 204 | 90.17 168 | 72.10 177 | 94.61 44 | 77.30 115 | 94.47 136 | 93.56 108 |
|
v1192 | | | 84.57 108 | 84.69 110 | 84.21 122 | 87.75 160 | 62.88 171 | 83.02 149 | 91.43 94 | 69.08 173 | 89.98 78 | 90.89 149 | 72.70 170 | 93.62 77 | 82.41 61 | 94.97 121 | 96.13 40 |
|
FMVSNet1 | | | 84.55 109 | 85.45 97 | 81.85 162 | 90.27 117 | 61.05 202 | 86.83 83 | 88.27 153 | 78.57 84 | 89.66 88 | 95.64 30 | 75.43 121 | 90.68 164 | 69.09 167 | 95.33 109 | 93.82 97 |
|
v1144 | | | 84.54 110 | 84.72 108 | 84.00 126 | 87.67 163 | 62.55 180 | 82.97 150 | 90.93 108 | 70.32 166 | 89.80 84 | 90.99 145 | 73.50 152 | 93.48 92 | 81.69 69 | 94.65 134 | 95.97 46 |
|
Gipuma |  | | 84.44 111 | 86.33 81 | 78.78 193 | 84.20 210 | 73.57 95 | 89.55 44 | 90.44 117 | 84.24 27 | 84.38 166 | 94.89 45 | 76.35 118 | 80.40 241 | 76.14 121 | 96.80 66 | 82.36 242 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
v1neww | | | 84.43 112 | 84.66 112 | 83.75 133 | 87.81 156 | 62.34 184 | 83.59 132 | 90.27 128 | 72.33 146 | 89.93 80 | 91.22 132 | 73.28 158 | 93.29 99 | 80.25 88 | 93.25 160 | 95.62 57 |
|
v7new | | | 84.43 112 | 84.66 112 | 83.75 133 | 87.81 156 | 62.34 184 | 83.59 132 | 90.27 128 | 72.33 146 | 89.93 80 | 91.22 132 | 73.28 158 | 93.29 99 | 80.25 88 | 93.25 160 | 95.62 57 |
|
v6 | | | 84.43 112 | 84.66 112 | 83.75 133 | 87.81 156 | 62.34 184 | 83.59 132 | 90.26 130 | 72.33 146 | 89.94 79 | 91.19 136 | 73.30 157 | 93.29 99 | 80.26 87 | 93.26 159 | 95.62 57 |
|
testing_2 | | | 84.36 115 | 84.64 115 | 83.50 145 | 86.74 178 | 63.97 156 | 84.56 113 | 90.31 122 | 66.22 191 | 91.62 55 | 94.55 53 | 75.88 119 | 91.95 131 | 77.02 118 | 94.89 123 | 94.56 77 |
|
MCST-MVS | | | 84.36 115 | 83.93 132 | 85.63 94 | 91.59 87 | 71.58 114 | 83.52 136 | 92.13 71 | 61.82 219 | 83.96 172 | 89.75 174 | 79.93 91 | 93.46 93 | 78.33 106 | 94.34 138 | 91.87 138 |
|
VDDNet | | | 84.35 117 | 85.39 98 | 81.25 171 | 95.13 22 | 59.32 213 | 85.42 104 | 81.11 211 | 86.41 20 | 87.41 125 | 96.21 19 | 73.61 150 | 90.61 167 | 66.33 183 | 96.85 62 | 93.81 100 |
|
v1240 | | | 84.30 118 | 84.51 119 | 83.65 138 | 87.65 164 | 61.26 198 | 82.85 153 | 91.54 84 | 67.94 181 | 90.68 69 | 90.65 158 | 71.71 182 | 93.64 73 | 82.84 58 | 94.78 129 | 96.07 42 |
|
MVS_111021_LR | | | 84.28 119 | 83.76 133 | 85.83 92 | 89.23 128 | 83.07 41 | 80.99 192 | 83.56 198 | 72.71 141 | 86.07 145 | 89.07 183 | 81.75 76 | 86.19 211 | 77.11 117 | 93.36 155 | 88.24 184 |
|
v144192 | | | 84.24 120 | 84.41 121 | 83.71 137 | 87.59 166 | 61.57 195 | 82.95 151 | 91.03 107 | 67.82 183 | 89.80 84 | 90.49 161 | 73.28 158 | 93.51 91 | 81.88 68 | 94.89 123 | 96.04 44 |
|
v1921920 | | | 84.23 121 | 84.37 126 | 83.79 131 | 87.64 165 | 61.71 190 | 82.91 152 | 91.20 104 | 67.94 181 | 90.06 74 | 90.34 164 | 72.04 180 | 93.59 78 | 82.32 63 | 94.91 122 | 96.07 42 |
|
VDD-MVS | | | 84.23 121 | 84.58 117 | 83.20 148 | 91.17 102 | 65.16 150 | 83.25 145 | 84.97 194 | 79.79 66 | 87.18 127 | 94.27 63 | 74.77 132 | 90.89 158 | 69.24 165 | 96.54 71 | 93.55 110 |
|
v1141 | | | 84.16 123 | 84.38 123 | 83.52 142 | 87.32 169 | 61.70 192 | 82.79 155 | 89.74 138 | 71.90 153 | 89.64 89 | 91.12 139 | 72.68 171 | 93.10 109 | 80.39 86 | 93.80 148 | 95.75 51 |
|
divwei89l23v2f112 | | | 84.16 123 | 84.38 123 | 83.52 142 | 87.32 169 | 61.70 192 | 82.79 155 | 89.74 138 | 71.90 153 | 89.64 89 | 91.12 139 | 72.68 171 | 93.10 109 | 80.40 84 | 93.81 147 | 95.75 51 |
|
v1 | | | 84.16 123 | 84.38 123 | 83.52 142 | 87.33 168 | 61.71 190 | 82.79 155 | 89.73 140 | 71.89 155 | 89.64 89 | 91.11 141 | 72.72 168 | 93.10 109 | 80.40 84 | 93.79 149 | 95.75 51 |
|
v2v482 | | | 84.09 126 | 84.24 128 | 83.62 139 | 87.13 173 | 61.40 196 | 82.71 159 | 89.71 141 | 72.19 149 | 89.55 96 | 91.41 129 | 70.70 186 | 93.20 104 | 81.02 74 | 93.76 150 | 96.25 38 |
|
EG-PatchMatch MVS | | | 84.08 127 | 84.11 129 | 83.98 127 | 92.22 75 | 72.61 102 | 82.20 174 | 87.02 170 | 72.63 142 | 88.86 103 | 91.02 144 | 78.52 96 | 91.11 151 | 73.41 141 | 91.09 184 | 88.21 185 |
|
DP-MVS Recon | | | 84.05 128 | 83.22 137 | 86.52 74 | 91.73 85 | 75.27 88 | 83.23 147 | 92.40 66 | 72.04 150 | 82.04 189 | 88.33 192 | 77.91 101 | 93.95 65 | 66.17 184 | 95.12 117 | 90.34 167 |
|
TransMVSNet (Re) | | | 84.02 129 | 85.74 91 | 78.85 192 | 91.00 105 | 55.20 239 | 82.29 168 | 87.26 165 | 79.65 69 | 88.38 115 | 95.52 34 | 83.00 57 | 86.88 204 | 67.97 175 | 96.60 70 | 94.45 83 |
|
Baseline_NR-MVSNet | | | 84.00 130 | 85.90 89 | 78.29 199 | 91.47 95 | 53.44 247 | 82.29 168 | 87.00 171 | 79.06 78 | 89.55 96 | 95.72 27 | 77.20 107 | 86.14 212 | 72.30 148 | 98.51 18 | 95.28 67 |
|
TSAR-MVS | | | 83.95 131 | 82.69 142 | 87.72 61 | 89.27 127 | 81.45 48 | 83.72 130 | 81.58 210 | 74.73 119 | 85.66 150 | 86.06 216 | 72.56 174 | 92.69 120 | 75.44 125 | 95.21 114 | 89.01 181 |
|
alignmvs | | | 83.94 132 | 83.98 131 | 83.80 130 | 87.80 159 | 67.88 137 | 84.54 114 | 91.42 95 | 73.27 135 | 88.41 114 | 87.96 197 | 72.33 176 | 90.83 159 | 76.02 122 | 94.11 140 | 92.69 124 |
|
AdaColmap |  | | 83.66 133 | 83.69 134 | 83.57 141 | 90.05 122 | 72.26 107 | 86.29 95 | 90.00 135 | 78.19 88 | 81.65 193 | 87.16 206 | 83.40 54 | 94.24 53 | 61.69 207 | 94.76 132 | 84.21 220 |
|
MIMVSNet1 | | | 83.63 134 | 84.59 116 | 80.74 176 | 94.06 33 | 62.77 173 | 82.72 158 | 84.53 196 | 77.57 94 | 90.34 70 | 95.92 23 | 76.88 115 | 85.83 216 | 61.88 205 | 97.42 50 | 93.62 105 |
|
WR-MVS | | | 83.56 135 | 84.40 122 | 81.06 174 | 93.43 44 | 54.88 240 | 78.67 211 | 85.02 192 | 81.24 54 | 90.74 68 | 91.56 125 | 72.85 166 | 91.08 152 | 68.00 174 | 98.04 32 | 97.23 24 |
|
CNLPA | | | 83.55 136 | 83.10 140 | 84.90 102 | 89.34 126 | 83.87 36 | 84.54 114 | 88.77 147 | 79.09 77 | 83.54 178 | 88.66 188 | 74.87 128 | 81.73 237 | 66.84 181 | 92.29 174 | 89.11 177 |
|
LCM-MVSNet-Re | | | 83.48 137 | 85.06 100 | 78.75 194 | 85.94 189 | 55.75 235 | 80.05 197 | 94.27 12 | 76.47 104 | 96.09 5 | 94.54 55 | 83.31 55 | 89.75 180 | 59.95 219 | 94.89 123 | 90.75 156 |
|
V42 | | | 83.47 138 | 83.37 136 | 83.75 133 | 83.16 220 | 63.33 164 | 81.31 187 | 90.23 131 | 69.51 170 | 90.91 66 | 90.81 152 | 74.16 138 | 92.29 127 | 80.06 90 | 90.22 200 | 95.62 57 |
|
VPA-MVSNet | | | 83.47 138 | 84.73 106 | 79.69 184 | 90.29 116 | 57.52 223 | 81.30 189 | 88.69 149 | 76.29 105 | 87.58 122 | 94.44 58 | 80.60 84 | 87.20 201 | 66.60 182 | 96.82 65 | 94.34 85 |
|
PAPM_NR | | | 83.23 140 | 83.19 139 | 83.33 146 | 90.90 107 | 65.98 147 | 88.19 63 | 90.78 109 | 78.13 89 | 80.87 200 | 87.92 199 | 73.49 153 | 92.42 124 | 70.07 159 | 88.40 212 | 91.60 144 |
|
CLD-MVS | | | 83.18 141 | 82.64 143 | 84.79 105 | 89.05 130 | 67.82 138 | 77.93 215 | 92.52 64 | 68.33 177 | 85.07 156 | 81.54 254 | 82.06 68 | 92.96 113 | 69.35 164 | 97.91 38 | 93.57 107 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
ANet_high | | | 83.17 142 | 85.68 93 | 75.65 220 | 81.24 230 | 45.26 278 | 79.94 199 | 92.91 52 | 83.83 29 | 91.33 60 | 96.88 8 | 80.25 87 | 85.92 214 | 68.89 169 | 95.89 96 | 95.76 50 |
|
114514_t | | | 83.10 143 | 82.54 146 | 84.77 106 | 92.90 56 | 69.10 131 | 86.65 90 | 90.62 113 | 54.66 247 | 81.46 195 | 90.81 152 | 76.98 111 | 94.38 49 | 72.62 146 | 96.18 83 | 90.82 155 |
|
UGNet | | | 82.78 144 | 81.64 155 | 86.21 83 | 86.20 187 | 76.24 85 | 86.86 81 | 85.68 182 | 77.07 100 | 73.76 239 | 92.82 95 | 69.64 187 | 91.82 137 | 69.04 168 | 93.69 152 | 90.56 162 |
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 |
LF4IMVS | | | 82.75 145 | 81.93 153 | 85.19 98 | 82.08 225 | 80.15 54 | 85.53 102 | 88.76 148 | 68.01 179 | 85.58 152 | 87.75 200 | 71.80 181 | 86.85 205 | 74.02 133 | 93.87 146 | 88.58 183 |
|
EI-MVSNet | | | 82.61 146 | 82.42 148 | 83.20 148 | 83.25 218 | 63.66 158 | 83.50 139 | 85.07 190 | 76.06 107 | 86.55 138 | 85.10 226 | 73.41 154 | 90.25 172 | 78.15 109 | 90.67 195 | 95.68 55 |
|
QAPM | | | 82.59 147 | 82.59 145 | 82.58 154 | 86.44 179 | 66.69 144 | 89.94 36 | 90.36 120 | 67.97 180 | 84.94 159 | 92.58 102 | 72.71 169 | 92.18 128 | 70.63 157 | 87.73 218 | 88.85 182 |
|
MVS_Test | | | 82.47 148 | 83.22 137 | 80.22 180 | 82.62 224 | 57.75 222 | 82.54 163 | 91.96 77 | 71.16 159 | 82.89 182 | 92.52 104 | 77.41 106 | 90.50 169 | 80.04 91 | 87.84 217 | 92.40 130 |
|
v148 | | | 82.31 149 | 82.48 147 | 81.81 165 | 85.59 190 | 59.66 211 | 81.47 185 | 86.02 179 | 72.85 139 | 88.05 117 | 90.65 158 | 70.73 185 | 90.91 157 | 75.15 126 | 91.79 179 | 94.87 73 |
|
API-MVS | | | 82.28 150 | 82.61 144 | 81.30 169 | 86.29 185 | 69.79 122 | 88.71 59 | 87.67 162 | 78.42 85 | 82.15 188 | 84.15 237 | 77.98 99 | 91.59 141 | 65.39 190 | 92.75 168 | 82.51 241 |
|
MVSFormer | | | 82.23 151 | 81.57 157 | 84.19 124 | 85.54 191 | 69.26 127 | 91.98 21 | 90.08 132 | 71.54 156 | 76.23 223 | 85.07 228 | 58.69 228 | 94.27 50 | 86.26 19 | 88.77 208 | 89.03 179 |
|
PCF-MVS | | 74.62 15 | 82.15 152 | 80.92 164 | 85.84 91 | 89.43 124 | 72.30 106 | 80.53 194 | 91.82 80 | 57.36 236 | 87.81 120 | 89.92 171 | 77.67 103 | 93.63 74 | 58.69 224 | 95.08 118 | 91.58 145 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
PLC |  | 73.85 16 | 82.09 153 | 80.31 168 | 87.45 65 | 90.86 109 | 80.29 53 | 85.88 97 | 90.65 111 | 68.17 178 | 76.32 222 | 86.33 213 | 73.12 163 | 92.61 122 | 61.40 211 | 90.02 202 | 89.44 174 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
GBi-Net | | | 82.02 154 | 82.07 150 | 81.85 162 | 86.38 181 | 61.05 202 | 86.83 83 | 88.27 153 | 72.43 143 | 86.00 146 | 95.64 30 | 63.78 210 | 90.68 164 | 65.95 185 | 93.34 156 | 93.82 97 |
|
test1 | | | 82.02 154 | 82.07 150 | 81.85 162 | 86.38 181 | 61.05 202 | 86.83 83 | 88.27 153 | 72.43 143 | 86.00 146 | 95.64 30 | 63.78 210 | 90.68 164 | 65.95 185 | 93.34 156 | 93.82 97 |
|
OpenMVS |  | 76.72 13 | 81.98 156 | 82.00 152 | 81.93 159 | 84.42 205 | 68.22 135 | 88.50 62 | 89.48 143 | 66.92 186 | 81.80 192 | 91.86 114 | 72.59 173 | 90.16 176 | 71.19 151 | 91.25 182 | 87.40 195 |
|
PVSNet_Blended_VisFu | | | 81.55 157 | 80.49 167 | 84.70 109 | 91.58 90 | 73.24 98 | 84.21 117 | 91.67 81 | 62.86 212 | 80.94 198 | 87.16 206 | 67.27 196 | 92.87 117 | 69.82 161 | 88.94 207 | 87.99 189 |
|
DELS-MVS | | | 81.44 158 | 81.25 159 | 82.03 158 | 84.27 207 | 62.87 172 | 76.47 229 | 92.49 65 | 70.97 161 | 81.64 194 | 83.83 238 | 75.03 125 | 92.70 119 | 74.29 130 | 92.22 177 | 90.51 163 |
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 |
Test4 | | | 81.31 159 | 81.13 161 | 81.88 161 | 84.89 197 | 63.05 168 | 82.37 165 | 90.50 115 | 62.75 213 | 89.00 102 | 88.29 193 | 67.55 195 | 91.68 139 | 73.55 139 | 91.24 183 | 90.89 152 |
|
FMVSNet2 | | | 81.31 159 | 81.61 156 | 80.41 178 | 86.38 181 | 58.75 218 | 83.93 123 | 86.58 174 | 72.43 143 | 87.65 121 | 92.98 90 | 63.78 210 | 90.22 174 | 66.86 179 | 93.92 145 | 92.27 133 |
|
DI_MVS_test_dynamic | | | 81.27 161 | 81.26 158 | 81.29 170 | 84.98 196 | 61.65 194 | 81.98 177 | 87.25 166 | 63.56 206 | 87.56 123 | 89.60 176 | 73.62 148 | 91.83 136 | 72.20 149 | 90.59 199 | 90.38 166 |
|
TinyColmap | | | 81.25 162 | 82.34 149 | 77.99 203 | 85.33 194 | 60.68 206 | 82.32 167 | 88.33 152 | 71.26 158 | 86.97 133 | 92.22 111 | 77.10 109 | 86.98 203 | 62.37 203 | 95.17 116 | 86.31 202 |
|
DI_MVS_test_normal | | | 81.23 163 | 81.16 160 | 81.43 168 | 84.77 199 | 61.99 189 | 81.46 186 | 86.95 172 | 63.16 211 | 87.22 126 | 89.63 175 | 73.62 148 | 91.65 140 | 72.92 144 | 90.70 194 | 90.65 160 |
|
BH-untuned | | | 80.96 164 | 80.99 162 | 80.84 175 | 88.55 140 | 68.23 134 | 80.33 195 | 88.46 151 | 72.79 140 | 86.55 138 | 86.76 210 | 74.72 133 | 91.77 138 | 61.79 206 | 88.99 206 | 82.52 240 |
|
liao | | | 80.86 165 | 79.81 172 | 84.02 125 | 93.93 36 | 78.70 63 | 81.64 182 | 80.18 215 | 55.43 244 | 83.67 175 | 91.15 137 | 71.29 183 | 91.41 147 | 67.95 176 | 93.06 164 | 81.96 248 |
|
BH-RMVSNet | | | 80.53 166 | 80.22 170 | 81.49 167 | 87.19 172 | 66.21 146 | 77.79 217 | 86.23 176 | 74.21 122 | 83.69 174 | 88.50 190 | 73.25 162 | 90.75 161 | 63.18 202 | 87.90 216 | 87.52 193 |
|
EPNet | | | 80.37 167 | 78.41 179 | 86.23 80 | 76.75 262 | 73.28 97 | 87.18 77 | 77.45 223 | 76.24 106 | 68.14 263 | 88.93 185 | 65.41 204 | 93.85 67 | 69.47 163 | 96.12 88 | 91.55 146 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
MG-MVS | | | 80.32 168 | 80.94 163 | 78.47 198 | 88.18 146 | 52.62 253 | 82.29 168 | 85.01 193 | 72.01 151 | 79.24 211 | 92.54 103 | 69.36 188 | 93.36 98 | 70.65 156 | 89.19 205 | 89.45 173 |
|
VPNet | | | 80.25 169 | 81.68 154 | 75.94 218 | 92.46 67 | 47.98 273 | 76.70 225 | 81.67 209 | 73.45 129 | 84.87 160 | 92.82 95 | 74.66 134 | 86.51 208 | 61.66 208 | 96.85 62 | 93.33 111 |
|
MAR-MVS | | | 80.24 170 | 78.74 177 | 84.73 108 | 86.87 177 | 78.18 65 | 85.75 99 | 87.81 161 | 65.67 197 | 77.84 214 | 78.50 265 | 73.79 145 | 90.53 168 | 61.59 210 | 90.87 190 | 85.49 209 |
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 |
PM-MVS | | | 80.20 171 | 79.00 175 | 83.78 132 | 88.17 147 | 86.66 9 | 81.31 187 | 66.81 276 | 69.64 169 | 88.33 116 | 90.19 167 | 64.58 206 | 83.63 230 | 71.99 150 | 90.03 201 | 81.06 263 |
|
LFMVS | | | 80.15 172 | 80.56 165 | 78.89 191 | 89.19 129 | 55.93 233 | 85.22 106 | 73.78 241 | 82.96 35 | 84.28 170 | 92.72 99 | 57.38 234 | 90.07 178 | 63.80 197 | 95.75 102 | 90.68 158 |
|
MSDG | | | 80.06 173 | 79.99 171 | 80.25 179 | 83.91 214 | 68.04 136 | 77.51 220 | 89.19 146 | 77.65 93 | 81.94 190 | 83.45 241 | 76.37 117 | 86.31 210 | 63.31 201 | 86.59 226 | 86.41 200 |
|
ab-mvs | | | 79.67 174 | 80.56 165 | 76.99 209 | 88.48 143 | 56.93 226 | 84.70 111 | 86.06 178 | 68.95 175 | 80.78 201 | 93.08 87 | 75.30 122 | 84.62 223 | 56.78 231 | 90.90 189 | 89.43 175 |
|
VNet | | | 79.31 175 | 80.27 169 | 76.44 213 | 87.92 154 | 53.95 243 | 75.58 235 | 84.35 197 | 74.39 121 | 82.23 186 | 90.72 154 | 72.84 167 | 84.39 225 | 60.38 218 | 93.98 144 | 90.97 150 |
|
diffmvs | | | 79.20 176 | 79.04 174 | 79.69 184 | 78.64 251 | 58.90 215 | 81.79 178 | 87.61 163 | 65.07 201 | 73.65 241 | 89.80 172 | 73.10 164 | 87.79 196 | 75.02 128 | 86.63 225 | 92.38 131 |
|
PAPR | | | 78.84 177 | 78.10 180 | 81.07 173 | 85.17 195 | 60.22 209 | 82.21 172 | 90.57 114 | 62.51 215 | 75.32 232 | 84.61 235 | 74.99 126 | 92.30 126 | 59.48 222 | 88.04 215 | 90.68 158 |
|
PVSNet_BlendedMVS | | | 78.80 178 | 77.84 181 | 81.65 166 | 84.43 203 | 63.41 161 | 79.49 203 | 90.44 117 | 61.70 221 | 75.43 230 | 87.07 208 | 69.11 190 | 91.44 145 | 60.68 216 | 92.24 176 | 90.11 170 |
|
FMVSNet3 | | | 78.80 178 | 78.55 178 | 79.57 187 | 82.89 222 | 56.89 228 | 81.76 179 | 85.77 181 | 69.04 174 | 86.00 146 | 90.44 163 | 51.75 249 | 90.09 177 | 65.95 185 | 93.34 156 | 91.72 141 |
|
mvs_anonymous | | | 78.13 180 | 78.76 176 | 76.23 217 | 79.24 245 | 50.31 266 | 78.69 210 | 84.82 195 | 61.60 222 | 83.09 181 | 92.82 95 | 73.89 144 | 87.01 202 | 68.33 173 | 86.41 227 | 91.37 147 |
|
TAMVS | | | 78.08 181 | 76.36 189 | 83.23 147 | 90.62 112 | 72.87 99 | 79.08 208 | 80.01 217 | 61.72 220 | 81.35 197 | 86.92 209 | 63.96 209 | 88.78 188 | 50.61 251 | 93.01 166 | 88.04 188 |
|
Vis-MVSNet (Re-imp) | | | 77.82 182 | 77.79 182 | 77.92 204 | 88.82 134 | 51.29 258 | 83.28 144 | 71.97 253 | 74.04 123 | 82.23 186 | 89.78 173 | 57.38 234 | 89.41 183 | 57.22 229 | 95.41 107 | 93.05 117 |
|
OpenMVS_ROB |  | 70.19 17 | 77.77 183 | 77.46 183 | 78.71 195 | 84.39 206 | 61.15 200 | 81.18 191 | 82.52 201 | 62.45 216 | 83.34 179 | 87.37 205 | 66.20 200 | 88.66 191 | 64.69 193 | 85.02 239 | 86.32 201 |
|
MDA-MVSNet-bldmvs | | | 77.47 184 | 76.90 186 | 79.16 190 | 79.03 247 | 64.59 151 | 66.58 268 | 75.67 234 | 73.15 137 | 88.86 103 | 88.99 184 | 66.94 197 | 81.23 238 | 64.71 192 | 88.22 214 | 91.64 143 |
|
jason | | | 77.42 185 | 75.75 195 | 82.43 156 | 87.10 174 | 69.27 126 | 77.99 214 | 81.94 207 | 51.47 264 | 77.84 214 | 85.07 228 | 60.32 218 | 89.00 185 | 70.74 155 | 89.27 204 | 89.03 179 |
jason: jason. |
CDS-MVSNet | | | 77.32 186 | 75.40 197 | 83.06 150 | 89.00 132 | 72.48 104 | 77.90 216 | 82.17 204 | 60.81 224 | 78.94 212 | 83.49 240 | 59.30 225 | 88.76 189 | 54.64 244 | 92.37 173 | 87.93 191 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
MVSTER | | | 77.09 187 | 75.70 196 | 81.25 171 | 75.27 273 | 61.08 201 | 77.49 221 | 85.07 190 | 60.78 225 | 86.55 138 | 88.68 187 | 43.14 273 | 90.25 172 | 73.69 137 | 90.67 195 | 92.42 128 |
|
Patchmatch-RL test | | | 77.08 188 | 77.10 185 | 77.01 208 | 84.83 198 | 66.54 145 | 72.29 251 | 69.16 267 | 57.70 234 | 86.76 135 | 90.46 162 | 72.42 175 | 82.59 234 | 69.63 162 | 90.65 197 | 81.90 250 |
|
PS-MVSNAJ | | | 77.04 189 | 76.53 188 | 78.56 197 | 87.09 175 | 61.40 196 | 75.26 236 | 87.13 167 | 61.25 223 | 74.38 237 | 77.22 270 | 76.94 112 | 90.94 155 | 64.63 194 | 84.83 242 | 83.35 231 |
|
IterMVS | | | 76.91 190 | 76.34 190 | 78.64 196 | 80.91 233 | 64.03 154 | 76.30 230 | 79.03 218 | 64.88 203 | 83.11 180 | 89.16 181 | 59.90 221 | 84.46 224 | 68.61 171 | 85.15 238 | 87.42 194 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
TR-MVS | | | 76.77 191 | 75.79 193 | 79.72 183 | 86.10 188 | 65.79 149 | 77.14 222 | 83.02 199 | 65.20 199 | 81.40 196 | 82.10 250 | 66.30 199 | 90.73 163 | 55.57 238 | 85.27 235 | 82.65 236 |
|
USDC | | | 76.63 192 | 76.73 187 | 76.34 215 | 83.46 216 | 57.20 225 | 80.02 198 | 88.04 157 | 52.14 259 | 83.65 177 | 91.25 131 | 63.24 213 | 86.65 207 | 54.66 243 | 94.11 140 | 85.17 210 |
|
BH-w/o | | | 76.57 193 | 76.07 192 | 78.10 201 | 86.88 176 | 65.92 148 | 77.63 218 | 86.33 175 | 65.69 196 | 80.89 199 | 79.95 261 | 68.97 192 | 90.74 162 | 53.01 248 | 85.25 236 | 77.62 268 |
|
Patchmtry | | | 76.56 194 | 77.46 183 | 73.83 228 | 79.37 244 | 46.60 276 | 82.41 164 | 76.90 226 | 73.81 126 | 85.56 153 | 92.38 105 | 48.07 258 | 83.98 228 | 63.36 200 | 95.31 112 | 90.92 151 |
|
PVSNet_Blended | | | 76.49 195 | 75.40 197 | 79.76 182 | 84.43 203 | 63.41 161 | 75.14 238 | 90.44 117 | 57.36 236 | 75.43 230 | 78.30 266 | 69.11 190 | 91.44 145 | 60.68 216 | 87.70 219 | 84.42 218 |
|
lupinMVS | | | 76.37 196 | 74.46 203 | 82.09 157 | 85.54 191 | 69.26 127 | 76.79 223 | 80.77 213 | 50.68 271 | 76.23 223 | 82.82 247 | 58.69 228 | 88.94 186 | 69.85 160 | 88.77 208 | 88.07 186 |
|
cascas | | | 76.29 197 | 74.81 199 | 80.72 177 | 84.47 202 | 62.94 170 | 73.89 245 | 87.34 164 | 55.94 242 | 75.16 234 | 76.53 273 | 63.97 208 | 91.16 150 | 65.00 191 | 90.97 188 | 88.06 187 |
|
RPMNet | | | 76.06 198 | 75.79 193 | 76.85 211 | 79.58 240 | 62.64 175 | 82.58 160 | 71.75 257 | 74.80 118 | 75.72 228 | 92.59 100 | 48.69 256 | 84.07 226 | 73.48 140 | 82.91 253 | 83.85 222 |
|
GA-MVS | | | 75.83 199 | 74.61 200 | 79.48 189 | 81.87 227 | 59.25 214 | 73.42 249 | 82.88 200 | 68.68 176 | 79.75 209 | 81.80 252 | 50.62 251 | 89.46 181 | 66.85 180 | 85.64 232 | 89.72 172 |
|
MV-PatchMatch | | | 75.81 200 | 73.51 207 | 82.71 152 | 89.35 125 | 73.62 94 | 80.06 196 | 85.20 187 | 60.30 227 | 73.96 238 | 87.94 198 | 57.89 232 | 89.45 182 | 52.02 250 | 74.87 276 | 85.06 212 |
|
wuyk23d | | | 75.13 201 | 79.30 173 | 62.63 264 | 75.56 269 | 75.18 89 | 80.89 193 | 73.10 246 | 75.06 117 | 94.76 13 | 95.32 37 | 87.73 25 | 52.85 289 | 34.16 286 | 97.11 56 | 59.85 287 |
|
EU-MVSNet | | | 75.12 202 | 74.43 204 | 77.18 207 | 83.11 221 | 59.48 212 | 85.71 101 | 82.43 202 | 39.76 290 | 85.64 151 | 88.76 186 | 44.71 269 | 87.88 195 | 73.86 136 | 85.88 230 | 84.16 221 |
|
CMPMVS |  | 59.41 20 | 75.12 202 | 73.57 206 | 79.77 181 | 75.84 267 | 67.22 139 | 81.21 190 | 82.18 203 | 50.78 269 | 76.50 219 | 87.66 202 | 55.20 241 | 82.99 232 | 62.17 204 | 90.64 198 | 89.09 178 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
1112_ss | | | 74.82 204 | 73.74 205 | 78.04 202 | 89.57 123 | 60.04 210 | 76.49 228 | 87.09 169 | 54.31 248 | 73.66 240 | 79.80 262 | 60.25 219 | 86.76 206 | 58.37 225 | 84.15 245 | 87.32 196 |
|
PatchMatch-RL | | | 74.48 205 | 73.22 208 | 78.27 200 | 87.70 162 | 85.26 23 | 75.92 231 | 70.09 262 | 64.34 205 | 76.09 226 | 81.25 256 | 65.87 203 | 78.07 246 | 53.86 245 | 83.82 247 | 71.48 279 |
|
XXY-MVS | | | 74.44 206 | 76.19 191 | 69.21 246 | 84.61 201 | 52.43 254 | 71.70 253 | 77.18 224 | 60.73 226 | 80.60 202 | 90.96 147 | 75.44 120 | 69.35 264 | 56.13 234 | 88.33 213 | 85.86 206 |
|
CR-MVSNet | | | 74.00 207 | 73.04 210 | 76.85 211 | 79.58 240 | 62.64 175 | 82.58 160 | 76.90 226 | 50.50 272 | 75.72 228 | 92.38 105 | 48.07 258 | 84.07 226 | 68.72 170 | 82.91 253 | 83.85 222 |
|
Test_1112_low_res | | | 73.90 208 | 73.08 209 | 76.35 214 | 90.35 115 | 55.95 232 | 73.40 250 | 86.17 177 | 50.70 270 | 73.14 243 | 85.94 217 | 58.31 230 | 85.90 215 | 56.51 232 | 83.22 250 | 87.20 197 |
|
test20.03 | | | 73.75 209 | 74.59 202 | 71.22 240 | 81.11 231 | 51.12 260 | 70.15 257 | 72.10 252 | 70.42 164 | 80.28 207 | 91.50 127 | 64.21 207 | 74.72 256 | 46.96 267 | 94.58 135 | 87.82 192 |
|
liao1 | | | 73.22 210 | 72.56 213 | 75.20 221 | 80.41 239 | 57.84 220 | 81.64 182 | 85.36 185 | 51.68 262 | 73.10 244 | 76.65 272 | 61.45 216 | 85.19 219 | 63.54 198 | 79.21 269 | 82.59 237 |
|
HC-MVS | | | 73.21 211 | 72.59 212 | 75.06 222 | 80.97 232 | 60.81 205 | 81.64 182 | 85.92 180 | 46.03 283 | 71.68 249 | 77.54 267 | 68.47 193 | 89.77 179 | 55.70 237 | 85.39 233 | 74.60 274 |
|
HY-MVS | | 64.64 18 | 73.03 212 | 72.47 214 | 74.71 224 | 83.36 217 | 54.19 241 | 82.14 175 | 81.96 205 | 56.76 241 | 69.57 259 | 86.21 215 | 60.03 220 | 84.83 222 | 49.58 256 | 82.65 255 | 85.11 211 |
|
EPNet_dtu | | | 72.87 213 | 71.33 221 | 77.49 206 | 77.72 257 | 60.55 207 | 82.35 166 | 75.79 232 | 66.49 189 | 58.39 291 | 81.06 257 | 53.68 245 | 85.98 213 | 53.55 246 | 92.97 167 | 85.95 204 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
CVMVSNet | | | 72.62 214 | 71.41 220 | 76.28 216 | 83.25 218 | 60.34 208 | 83.50 139 | 79.02 219 | 37.77 291 | 76.33 221 | 85.10 226 | 49.60 254 | 87.41 199 | 70.54 158 | 77.54 274 | 81.08 261 |
|
testgi | | | 72.36 215 | 74.61 200 | 65.59 257 | 80.56 237 | 42.82 284 | 68.29 260 | 73.35 245 | 66.87 187 | 81.84 191 | 89.93 170 | 72.08 179 | 66.92 271 | 46.05 269 | 92.54 171 | 87.01 199 |
|
FPMVS | | | 72.29 216 | 72.00 216 | 73.14 231 | 88.63 139 | 85.00 25 | 74.65 241 | 67.39 270 | 71.94 152 | 77.80 216 | 87.66 202 | 50.48 252 | 75.83 252 | 49.95 253 | 79.51 265 | 58.58 289 |
|
FMVSNet5 | | | 72.10 217 | 71.69 218 | 73.32 229 | 81.57 229 | 53.02 250 | 76.77 224 | 78.37 220 | 63.31 209 | 76.37 220 | 91.85 115 | 36.68 284 | 78.98 245 | 47.87 263 | 92.45 172 | 87.95 190 |
|
PAPM | | | 71.77 218 | 70.06 227 | 76.92 210 | 86.39 180 | 53.97 242 | 76.62 226 | 86.62 173 | 53.44 253 | 63.97 279 | 84.73 234 | 57.79 233 | 92.34 125 | 39.65 277 | 81.33 260 | 84.45 217 |
|
IB-MVS | | 62.13 19 | 71.64 219 | 68.97 232 | 79.66 186 | 80.80 236 | 62.26 188 | 73.94 244 | 76.90 226 | 63.27 210 | 68.63 262 | 76.79 271 | 33.83 286 | 91.84 135 | 59.28 223 | 87.26 221 | 84.88 213 |
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 |
UnsupCasMVSNet_eth | | | 71.63 220 | 72.30 215 | 69.62 244 | 76.47 263 | 52.70 252 | 70.03 258 | 80.97 212 | 59.18 230 | 79.36 210 | 88.21 194 | 60.50 217 | 69.12 265 | 58.33 227 | 77.62 273 | 87.04 198 |
|
no-one | | | 71.52 221 | 70.43 225 | 74.81 223 | 78.45 253 | 63.41 161 | 57.73 285 | 77.03 225 | 51.46 265 | 77.17 218 | 90.33 165 | 54.96 243 | 80.35 242 | 47.41 264 | 99.29 2 | 80.68 265 |
|
HyFIR | | | 71.49 222 | 71.95 217 | 70.08 241 | 84.74 200 | 46.83 275 | 63.41 273 | 76.88 229 | 47.99 279 | 76.15 225 | 88.34 191 | 65.15 205 | 79.77 244 | 60.78 215 | 84.14 246 | 83.64 225 |
|
MIMVSNet | | | 71.09 223 | 71.59 219 | 69.57 245 | 87.23 171 | 50.07 267 | 78.91 209 | 71.83 255 | 60.20 228 | 71.26 251 | 91.76 120 | 55.08 242 | 76.09 250 | 41.06 275 | 87.02 224 | 82.54 239 |
|
MS-PatchMatch | | | 70.93 224 | 70.22 226 | 73.06 232 | 81.85 228 | 62.50 181 | 73.82 246 | 77.90 221 | 52.44 257 | 75.92 227 | 81.27 255 | 55.67 239 | 81.75 236 | 55.37 240 | 77.70 272 | 74.94 273 |
|
pm-mvs1 | | | 70.57 225 | 69.48 230 | 73.85 227 | 80.42 238 | 56.56 230 | 73.77 247 | 71.49 259 | 48.39 278 | 73.32 242 | 88.60 189 | 52.30 248 | 80.42 240 | 48.53 260 | 88.51 211 | 84.55 215 |
|
PatchT | | | 70.52 226 | 72.76 211 | 63.79 263 | 79.38 243 | 33.53 292 | 77.63 218 | 65.37 278 | 73.61 127 | 71.77 248 | 92.79 98 | 44.38 270 | 75.65 253 | 64.53 195 | 85.37 234 | 82.18 245 |
|
testmv | | | 70.47 227 | 70.70 222 | 69.77 243 | 86.22 186 | 53.89 244 | 67.32 265 | 71.91 254 | 63.32 208 | 78.16 213 | 89.47 178 | 56.12 237 | 73.10 257 | 36.43 283 | 87.33 220 | 82.33 243 |
|
N_pmnet | | | 70.20 228 | 68.80 234 | 74.38 225 | 80.91 233 | 84.81 28 | 59.12 282 | 76.45 231 | 55.06 245 | 75.31 233 | 82.36 249 | 55.74 238 | 54.82 288 | 47.02 266 | 87.24 222 | 83.52 227 |
|
tpmvs | | | 70.16 229 | 69.56 229 | 71.96 238 | 74.71 277 | 48.13 271 | 79.63 201 | 75.45 235 | 65.02 202 | 70.26 256 | 81.88 251 | 45.34 266 | 85.68 217 | 58.34 226 | 75.39 275 | 82.08 246 |
|
YYNet1 | | | 70.06 230 | 70.44 223 | 68.90 247 | 73.76 279 | 53.42 248 | 58.99 283 | 67.20 272 | 58.42 232 | 87.10 129 | 85.39 224 | 59.82 222 | 67.32 268 | 59.79 220 | 83.50 249 | 85.96 203 |
|
MDA-MVSNet_test_wron | | | 70.05 231 | 70.44 223 | 68.88 248 | 73.84 278 | 53.47 246 | 58.93 284 | 67.28 271 | 58.43 231 | 87.09 130 | 85.40 223 | 59.80 223 | 67.25 269 | 59.66 221 | 83.54 248 | 85.92 205 |
|
CostFormer | | | 69.98 232 | 68.68 235 | 73.87 226 | 77.14 260 | 50.72 264 | 79.26 206 | 74.51 239 | 51.94 261 | 70.97 254 | 84.75 233 | 45.16 268 | 87.49 198 | 55.16 241 | 79.23 268 | 83.40 230 |
|
PatchmatchNet |  | | 69.71 233 | 68.83 233 | 72.33 236 | 77.66 258 | 53.60 245 | 79.29 205 | 69.99 263 | 57.66 235 | 72.53 245 | 82.93 246 | 46.45 262 | 80.08 243 | 60.91 214 | 72.09 281 | 83.31 232 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
tpmp4_e23 | | | 69.43 234 | 67.33 240 | 75.72 219 | 78.53 252 | 52.75 251 | 82.13 176 | 74.91 236 | 49.23 276 | 66.37 268 | 84.17 236 | 41.28 277 | 88.67 190 | 49.73 255 | 79.63 264 | 85.75 207 |
|
LP | | | 69.42 235 | 68.30 237 | 72.77 233 | 71.48 289 | 56.84 229 | 73.66 248 | 74.84 237 | 63.52 207 | 70.95 255 | 83.35 242 | 49.55 255 | 77.15 248 | 57.13 230 | 70.21 284 | 84.33 219 |
|
JIA-IIPM | | | 69.41 236 | 66.64 245 | 77.70 205 | 73.19 281 | 71.24 116 | 75.67 233 | 65.56 277 | 70.42 164 | 65.18 274 | 92.97 91 | 33.64 287 | 83.06 231 | 53.52 247 | 69.61 288 | 78.79 267 |
|
UnsupCasMVSNet_bld | | | 69.21 237 | 69.68 228 | 67.82 253 | 79.42 242 | 51.15 259 | 67.82 264 | 75.79 232 | 54.15 249 | 77.47 217 | 85.36 225 | 59.26 226 | 70.64 260 | 48.46 261 | 79.35 267 | 81.66 253 |
|
gg-mvs-nofinetune | | | 68.96 238 | 69.11 231 | 68.52 252 | 76.12 266 | 45.32 277 | 83.59 132 | 55.88 291 | 86.68 18 | 64.62 278 | 97.01 5 | 30.36 290 | 83.97 229 | 44.78 271 | 82.94 252 | 76.26 271 |
|
tpm2 | | | 68.45 239 | 66.83 242 | 73.30 230 | 78.93 248 | 48.50 270 | 79.76 200 | 71.76 256 | 47.50 280 | 69.92 258 | 83.60 239 | 42.07 276 | 88.40 192 | 48.44 262 | 79.51 265 | 83.01 235 |
|
tpm | | | 67.95 240 | 68.08 239 | 67.55 254 | 78.74 250 | 43.53 283 | 75.60 234 | 67.10 275 | 54.92 246 | 72.23 247 | 88.10 195 | 42.87 274 | 75.97 251 | 52.21 249 | 80.95 263 | 83.15 233 |
|
PatchFormer-LS_test | | | 67.91 241 | 66.49 246 | 72.17 237 | 75.29 272 | 51.85 256 | 75.68 232 | 73.62 243 | 57.23 238 | 68.64 260 | 68.13 287 | 42.19 275 | 82.76 233 | 64.06 196 | 73.51 278 | 81.89 251 |
|
WTY-MVS | | | 67.91 241 | 68.35 236 | 66.58 255 | 80.82 235 | 48.12 272 | 65.96 269 | 72.60 248 | 53.67 252 | 71.20 252 | 81.68 253 | 58.97 227 | 69.06 266 | 48.57 259 | 81.67 258 | 82.55 238 |
|
test-LLR | | | 67.21 243 | 66.74 243 | 68.63 250 | 76.45 264 | 55.21 237 | 67.89 261 | 67.14 273 | 62.43 217 | 65.08 275 | 72.39 281 | 43.41 271 | 69.37 262 | 61.00 212 | 84.89 240 | 81.31 256 |
|
sss | | | 66.92 244 | 67.26 241 | 65.90 256 | 77.23 259 | 51.10 261 | 64.79 270 | 71.72 258 | 52.12 260 | 70.13 257 | 80.18 259 | 57.96 231 | 65.36 278 | 50.21 252 | 81.01 262 | 81.25 258 |
|
tpm cat1 | | | 66.76 245 | 65.21 249 | 71.42 239 | 77.09 261 | 50.62 265 | 78.01 213 | 73.68 242 | 44.89 285 | 68.64 260 | 79.00 264 | 45.51 264 | 82.42 235 | 49.91 254 | 70.15 285 | 81.23 260 |
|
DWT-MVSNet_test | | | 66.43 246 | 64.37 250 | 72.63 234 | 74.86 276 | 50.86 263 | 76.52 227 | 72.74 247 | 54.06 250 | 65.50 272 | 68.30 286 | 32.13 288 | 84.84 221 | 61.63 209 | 73.59 277 | 82.19 244 |
|
PVSNet | | 58.17 21 | 66.41 247 | 65.63 248 | 68.75 249 | 81.96 226 | 49.88 268 | 62.19 276 | 72.51 250 | 51.03 267 | 68.04 264 | 75.34 277 | 50.84 250 | 74.77 254 | 45.82 270 | 82.96 251 | 81.60 254 |
|
tpmrst | | | 66.28 248 | 66.69 244 | 65.05 261 | 72.82 285 | 39.33 287 | 78.20 212 | 70.69 261 | 53.16 255 | 67.88 265 | 80.36 258 | 48.18 257 | 74.75 255 | 58.13 228 | 70.79 283 | 81.08 261 |
|
ADS-MVSNet2 | | | 65.87 249 | 63.64 254 | 72.55 235 | 73.16 282 | 56.92 227 | 67.10 266 | 74.81 238 | 49.74 273 | 66.04 270 | 82.97 244 | 46.71 260 | 77.26 247 | 42.29 272 | 69.96 286 | 83.46 228 |
|
test1235678 | | | 65.57 250 | 65.73 247 | 65.06 260 | 82.84 223 | 50.90 262 | 62.90 274 | 69.26 265 | 57.17 239 | 72.36 246 | 83.04 243 | 46.02 263 | 70.10 261 | 32.79 288 | 85.24 237 | 74.19 275 |
|
test-mter | | | 65.00 251 | 63.79 252 | 68.63 250 | 76.45 264 | 55.21 237 | 67.89 261 | 67.14 273 | 50.98 268 | 65.08 275 | 72.39 281 | 28.27 292 | 69.37 262 | 61.00 212 | 84.89 240 | 81.31 256 |
|
test0.0.03 1 | | | 64.66 252 | 64.36 251 | 65.57 258 | 75.03 275 | 46.89 274 | 64.69 271 | 61.58 285 | 62.43 217 | 71.18 253 | 77.54 267 | 43.41 271 | 68.47 267 | 40.75 276 | 82.65 255 | 81.35 255 |
|
pmmvs3 | | | 62.47 253 | 60.02 266 | 69.80 242 | 71.58 288 | 64.00 155 | 70.52 256 | 58.44 288 | 39.77 289 | 66.05 269 | 75.84 274 | 27.10 294 | 72.28 258 | 46.15 268 | 84.77 243 | 73.11 277 |
|
EPMVS | | | 62.47 253 | 62.63 257 | 62.01 265 | 70.63 290 | 38.74 288 | 74.76 239 | 52.86 292 | 53.91 251 | 67.71 266 | 80.01 260 | 39.40 281 | 66.60 273 | 55.54 239 | 68.81 290 | 80.68 265 |
|
testus | | | 62.33 255 | 63.03 255 | 60.20 271 | 78.78 249 | 40.74 285 | 59.14 280 | 69.80 264 | 49.26 275 | 71.41 250 | 74.72 279 | 52.33 247 | 63.52 281 | 29.84 290 | 82.01 257 | 76.36 270 |
|
ADS-MVSNet | | | 61.90 256 | 62.19 258 | 61.03 270 | 73.16 282 | 36.42 290 | 67.10 266 | 61.75 283 | 49.74 273 | 66.04 270 | 82.97 244 | 46.71 260 | 63.21 283 | 42.29 272 | 69.96 286 | 83.46 228 |
|
1111 | | | 61.71 257 | 63.77 253 | 55.55 276 | 78.05 254 | 25.74 296 | 60.62 277 | 67.52 268 | 66.09 192 | 74.68 235 | 86.50 211 | 16.00 297 | 59.22 286 | 38.79 278 | 85.65 231 | 81.70 252 |
|
PMMVS | | | 61.65 258 | 60.38 263 | 65.47 259 | 65.40 295 | 69.26 127 | 63.97 272 | 61.73 284 | 36.80 292 | 60.11 285 | 68.43 284 | 59.42 224 | 66.35 274 | 48.97 258 | 78.57 270 | 60.81 286 |
|
E-PMN | | | 61.59 259 | 61.62 259 | 61.49 268 | 66.81 292 | 55.40 236 | 53.77 289 | 60.34 286 | 66.80 188 | 58.90 290 | 65.50 290 | 40.48 280 | 66.12 275 | 55.72 236 | 86.25 228 | 62.95 285 |
|
TESTMET0.1,1 | | | 61.29 260 | 60.32 264 | 64.19 262 | 72.06 286 | 51.30 257 | 67.89 261 | 62.09 281 | 45.27 284 | 60.65 284 | 69.01 283 | 27.93 293 | 64.74 280 | 56.31 233 | 81.65 259 | 76.53 269 |
|
MVS-HIRNet | | | 61.16 261 | 62.92 256 | 55.87 274 | 79.09 246 | 35.34 291 | 71.83 252 | 57.98 290 | 46.56 281 | 59.05 289 | 91.14 138 | 49.95 253 | 76.43 249 | 38.74 280 | 71.92 282 | 55.84 290 |
|
EMVS | | | 61.10 262 | 60.81 262 | 61.99 266 | 65.96 294 | 55.86 234 | 53.10 290 | 58.97 287 | 67.06 184 | 56.89 293 | 63.33 291 | 40.98 278 | 67.03 270 | 54.79 242 | 86.18 229 | 63.08 284 |
|
DSMNet-mixed | | | 60.98 263 | 61.61 260 | 59.09 273 | 72.88 284 | 45.05 280 | 74.70 240 | 46.61 297 | 26.20 294 | 65.34 273 | 90.32 166 | 55.46 240 | 63.12 284 | 41.72 274 | 81.30 261 | 69.09 282 |
|
dp | | | 60.70 264 | 60.29 265 | 61.92 267 | 72.04 287 | 38.67 289 | 70.83 254 | 64.08 279 | 51.28 266 | 60.75 283 | 77.28 269 | 36.59 285 | 71.58 259 | 47.41 264 | 62.34 293 | 75.52 272 |
|
testpf | | | 58.55 265 | 61.58 261 | 49.48 280 | 66.03 293 | 40.05 286 | 74.40 242 | 58.07 289 | 64.72 204 | 59.36 287 | 72.67 280 | 22.76 295 | 66.92 271 | 67.07 178 | 69.15 289 | 41.46 292 |
|
test2356 | | | 56.69 266 | 55.15 270 | 61.32 269 | 73.20 280 | 44.11 281 | 54.95 287 | 62.52 280 | 48.75 277 | 62.45 281 | 68.42 285 | 21.10 296 | 65.67 277 | 26.86 292 | 78.08 271 | 74.19 275 |
|
PVSNet_0 | | 51.08 22 | 56.10 267 | 54.97 271 | 59.48 272 | 75.12 274 | 53.28 249 | 55.16 286 | 61.89 282 | 44.30 286 | 59.16 288 | 62.48 292 | 54.22 244 | 65.91 276 | 35.40 285 | 47.01 294 | 59.25 288 |
|
new_pmnet | | | 55.69 268 | 57.66 268 | 49.76 279 | 75.47 271 | 30.59 293 | 59.56 279 | 51.45 294 | 43.62 287 | 62.49 280 | 75.48 275 | 40.96 279 | 49.15 291 | 37.39 281 | 72.52 279 | 69.55 281 |
|
PMMVS2 | | | 55.64 269 | 59.27 267 | 44.74 282 | 64.30 296 | 12.32 300 | 40.60 292 | 49.79 295 | 53.19 254 | 65.06 277 | 84.81 232 | 53.60 246 | 49.76 290 | 32.68 289 | 89.41 203 | 72.15 278 |
|
test12356 | | | 54.91 270 | 57.14 269 | 48.22 281 | 75.83 268 | 17.47 299 | 52.31 291 | 69.20 266 | 51.66 263 | 60.11 285 | 75.40 276 | 29.77 291 | 62.62 285 | 27.64 291 | 72.37 280 | 64.59 283 |
|
PNet_i23d | | | 52.13 271 | 51.24 274 | 54.79 277 | 75.56 269 | 45.26 278 | 54.54 288 | 52.55 293 | 66.95 185 | 57.19 292 | 65.82 289 | 13.15 299 | 63.40 282 | 36.39 284 | 39.04 296 | 55.71 291 |
|
MVE |  | 40.22 23 | 51.82 272 | 50.47 275 | 55.87 274 | 62.66 298 | 51.91 255 | 31.61 294 | 39.28 298 | 40.65 288 | 50.76 295 | 74.98 278 | 56.24 236 | 44.67 292 | 33.94 287 | 64.11 292 | 71.04 280 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
HyFIR lowres test | | | 51.64 273 | 51.77 273 | 51.24 278 | 64.21 297 | 49.39 269 | 68.80 259 | 46.62 296 | 28.12 293 | 52.64 294 | 65.93 288 | 38.34 283 | 64.88 279 | 37.16 282 | 64.13 291 | 39.44 293 |
|
.test1245 | | | 48.02 274 | 54.41 272 | 28.84 284 | 78.05 254 | 25.74 296 | 60.62 277 | 67.52 268 | 66.09 192 | 74.68 235 | 86.50 211 | 16.00 297 | 59.22 286 | 38.79 278 | 1.47 298 | 1.55 297 |
|
pcd1.5k->3k | | | 38.83 275 | 41.11 276 | 32.01 283 | 93.13 51 | 0.00 304 | 0.00 295 | 91.38 99 | 0.00 299 | 0.00 300 | 0.00 298 | 89.24 14 | 0.00 297 | 0.00 297 | 96.24 82 | 96.02 45 |
|
cdsmvs_eth3d_5k | | | 20.81 276 | 27.75 277 | 0.00 289 | 0.00 303 | 0.00 304 | 0.00 295 | 85.44 184 | 0.00 299 | 0.00 300 | 82.82 247 | 81.46 78 | 0.00 297 | 0.00 297 | 0.00 301 | 0.00 299 |
|
DUST3R | | | 20.25 277 | 24.50 278 | 7.49 286 | 4.47 300 | 8.70 301 | 34.17 293 | 25.16 299 | 1.00 296 | 32.43 297 | 18.49 294 | 39.37 282 | 9.21 294 | 21.64 293 | 43.75 295 | 4.57 295 |
|
ab-mvs-re | | | 6.65 278 | 8.87 279 | 0.00 289 | 0.00 303 | 0.00 304 | 0.00 295 | 0.00 303 | 0.00 299 | 0.00 300 | 79.80 262 | 0.00 302 | 0.00 297 | 0.00 297 | 0.00 301 | 0.00 299 |
|
pcd_1.5k_mvsjas | | | 6.41 279 | 8.55 280 | 0.00 289 | 0.00 303 | 0.00 304 | 0.00 295 | 0.00 303 | 0.00 299 | 0.00 300 | 0.00 298 | 76.94 112 | 0.00 297 | 0.00 297 | 0.00 301 | 0.00 299 |
|
test123 | | | 6.27 280 | 8.08 281 | 0.84 287 | 1.11 302 | 0.57 302 | 62.90 274 | 0.82 301 | 0.54 297 | 1.07 299 | 2.75 297 | 1.26 300 | 0.30 295 | 1.04 295 | 1.26 300 | 1.66 296 |
|
testmvs | | | 5.91 281 | 7.65 282 | 0.72 288 | 1.20 301 | 0.37 303 | 59.14 280 | 0.67 302 | 0.49 298 | 1.11 298 | 2.76 296 | 0.94 301 | 0.24 296 | 1.02 296 | 1.47 298 | 1.55 297 |
|
sosnet-low-res | | | 0.00 282 | 0.00 283 | 0.00 289 | 0.00 303 | 0.00 304 | 0.00 295 | 0.00 303 | 0.00 299 | 0.00 300 | 0.00 298 | 0.00 302 | 0.00 297 | 0.00 297 | 0.00 301 | 0.00 299 |
|
sosnet | | | 0.00 282 | 0.00 283 | 0.00 289 | 0.00 303 | 0.00 304 | 0.00 295 | 0.00 303 | 0.00 299 | 0.00 300 | 0.00 298 | 0.00 302 | 0.00 297 | 0.00 297 | 0.00 301 | 0.00 299 |
|
uncertanet | | | 0.00 282 | 0.00 283 | 0.00 289 | 0.00 303 | 0.00 304 | 0.00 295 | 0.00 303 | 0.00 299 | 0.00 300 | 0.00 298 | 0.00 302 | 0.00 297 | 0.00 297 | 0.00 301 | 0.00 299 |
|
Regformer | | | 0.00 282 | 0.00 283 | 0.00 289 | 0.00 303 | 0.00 304 | 0.00 295 | 0.00 303 | 0.00 299 | 0.00 300 | 0.00 298 | 0.00 302 | 0.00 297 | 0.00 297 | 0.00 301 | 0.00 299 |
|
uanet | | | 0.00 282 | 0.00 283 | 0.00 289 | 0.00 303 | 0.00 304 | 0.00 295 | 0.00 303 | 0.00 299 | 0.00 300 | 0.00 298 | 0.00 302 | 0.00 297 | 0.00 297 | 0.00 301 | 0.00 299 |
|
test9_res | | | | | | | | | | | | | | | 80.83 78 | 96.45 76 | 90.57 161 |
|
TEST9 | | | | | | 92.34 71 | 79.70 57 | 83.94 122 | 90.32 121 | 65.41 198 | 84.49 165 | 90.97 146 | 82.03 70 | 93.63 74 | | | |
|
train_agg | | | | | | | | | | | | | | | 81.21 71 | 96.54 71 | 90.88 153 |
|
Patchmatch-test1 | | | | | | 85.44 193 | 61.17 199 | 75.24 237 | 73.42 244 | | 86.97 133 | 91.56 125 | 74.17 137 | | | 87.04 223 | |
|
Patchmatch-test | | | | | | 67.85 291 | 25.43 298 | | | | | 86.31 214 | | | | | |
|
test_8 | | | | | | 92.09 76 | 78.87 61 | 83.82 126 | 90.31 122 | 65.79 195 | 84.36 167 | 90.96 147 | 81.93 72 | 93.44 94 | | | |
|
agg_prior2 | | | | | | | | | | | | | | | 79.68 95 | 96.16 84 | 90.22 168 |
|
agg_prior | | | | | | 91.58 90 | 77.69 68 | | 90.30 124 | | 84.32 168 | | | 93.18 105 | | | |
|
TestCases | | | | | 89.68 39 | 91.59 87 | 83.40 38 | | 95.44 5 | 79.47 70 | 88.00 118 | 93.03 88 | 82.66 61 | 91.47 143 | 70.81 152 | 96.14 86 | 94.16 89 |
|
test_prior4 | | | | | | | 78.97 60 | 84.59 112 | | | | | | | | | |
|
test_prior2 | | | | | | | | 83.37 142 | | 75.43 114 | 84.58 163 | 91.57 123 | 81.92 73 | | 79.54 97 | 96.97 59 | |
|
test_prior | | | | | 86.32 77 | 90.59 113 | 71.99 111 | | 92.85 54 | | | | | 94.17 56 | | | 92.80 121 |
|
旧先验2 | | | | | | | | 81.73 180 | | 56.88 240 | 86.54 143 | | | 84.90 220 | 72.81 145 | | |
|
新几何2 | | | | | | | | 81.72 181 | | | | | | | | | |
|
新几何1 | | | | | 82.95 151 | 93.96 35 | 78.56 64 | | 80.24 214 | 55.45 243 | 83.93 173 | 91.08 142 | 71.19 184 | 88.33 193 | 65.84 188 | 93.07 163 | 81.95 249 |
|
旧先验1 | | | | | | 91.97 79 | 71.77 113 | | 81.78 208 | | | 91.84 116 | 73.92 143 | | | 93.65 154 | 83.61 226 |
|
无先验 | | | | | | | | 82.81 154 | 85.62 183 | 58.09 233 | | | | 91.41 147 | 67.95 176 | | 84.48 216 |
|
原ACMM2 | | | | | | | | 82.26 171 | | | | | | | | | |
|
原ACMM1 | | | | | 84.60 111 | 92.81 61 | 74.01 93 | | 91.50 85 | 62.59 214 | 82.73 184 | 90.67 157 | 76.53 116 | 94.25 52 | 69.24 165 | 95.69 104 | 85.55 208 |
|
test222 | | | | | | 93.31 46 | 76.54 80 | 79.38 204 | 77.79 222 | 52.59 256 | 82.36 185 | 90.84 151 | 66.83 198 | | | 91.69 180 | 81.25 258 |
|
testdata2 | | | | | | | | | | | | | | 86.43 209 | 63.52 199 | | |
|
segment_acmp | | | | | | | | | | | | | 81.94 71 | | | | |
|
testdata | | | | | 79.54 188 | 92.87 57 | 72.34 105 | | 80.14 216 | 59.91 229 | 85.47 155 | 91.75 121 | 67.96 194 | 85.24 218 | 68.57 172 | 92.18 178 | 81.06 263 |
|
testdata1 | | | | | | | | 79.62 202 | | 73.95 125 | | | | | | | |
|
test12 | | | | | 86.57 72 | 90.74 110 | 72.63 101 | | 90.69 110 | | 82.76 183 | | 79.20 92 | 94.80 40 | | 95.32 110 | 92.27 133 |
|
plane_prior7 | | | | | | 93.45 42 | 77.31 74 | | | | | | | | | | |
|
plane_prior6 | | | | | | 92.61 62 | 76.54 80 | | | | | | 74.84 129 | | | | |
|
plane_prior5 | | | | | | | | | 93.61 27 | | | | | 95.22 30 | 80.78 79 | 95.83 99 | 94.46 81 |
|
plane_prior4 | | | | | | | | | | | | 92.95 92 | | | | | |
|
plane_prior3 | | | | | | | 76.85 79 | | | 77.79 91 | 86.55 138 | | | | | | |
|
plane_prior2 | | | | | | | | 89.45 49 | | 79.44 72 | | | | | | | |
|
plane_prior1 | | | | | | 92.83 60 | | | | | | | | | | | |
|
plane_prior | | | | | | | 76.42 82 | 87.15 78 | | 75.94 111 | | | | | | 95.03 120 | |
|
abl_6 | | | | | | | | | | | | | | | | | 93.71 102 |
|
n2 | | | | | | | | | 0.00 303 | | | | | | | | |
|
nn | | | | | | | | | 0.00 303 | | | | | | | | |
|
door-mid | | | | | | | | | 74.45 240 | | | | | | | | |
|
lessismore_v0 | | | | | 85.95 88 | 91.10 104 | 70.99 118 | | 70.91 260 | | 91.79 52 | 94.42 59 | 61.76 215 | 92.93 115 | 79.52 99 | 93.03 165 | 93.93 94 |
|
LGP-MVS_train | | | | | 90.82 27 | 94.75 28 | 81.69 44 | | 94.27 12 | 82.35 41 | 93.67 27 | 94.82 46 | 91.18 4 | 95.52 22 | 85.36 26 | 98.73 8 | 95.23 69 |
|
test11 | | | | | | | | | 91.46 91 | | | | | | | | |
|
door | | | | | | | | | 72.57 249 | | | | | | | | |
|
HQP5-MVS | | | | | | | 70.66 119 | | | | | | | | | | |
|
HQP-NCC | | | | | | 91.19 99 | | 84.77 108 | | 73.30 132 | 80.55 204 | | | | | | |
|
ACMP_Plane | | | | | | 91.19 99 | | 84.77 108 | | 73.30 132 | 80.55 204 | | | | | | |
|
BP-MVS | | | | | | | | | | | | | | | 77.30 115 | | |
|
HQP4-MVS | | | | | | | | | | | 80.56 203 | | | 94.61 44 | | | 93.56 108 |
|
HQP3-MVS | | | | | | | | | 92.68 59 | | | | | | | 94.47 136 | |
|
HQP2-MVS | | | | | | | | | | | | | 72.10 177 | | | | |
|
NP-MVS | | | | | | 91.95 80 | 74.55 91 | | | | | 90.17 168 | | | | | |
|
MDTV_nov1_ep13_2view | | | | | | | 27.60 295 | 70.76 255 | |