SED-MVS | | | 90.08 2 | 90.85 2 | 87.77 26 | 95.30 2 | 70.98 70 | 93.57 7 | 94.06 12 | 77.24 52 | 93.10 1 | 95.72 8 | 82.99 1 | 97.44 5 | 89.07 9 | 96.63 4 | 94.88 12 |
|
test_241102_ONE | | | | | | 95.30 2 | 70.98 70 | | 94.06 12 | 77.17 56 | 93.10 1 | 95.39 11 | 82.99 1 | 97.27 10 | | | |
|
test0726 | | | | | | 95.27 5 | 71.25 63 | 93.60 6 | 94.11 8 | 77.33 50 | 92.81 3 | 95.79 3 | 80.98 9 | | | | |
|
DVP-MVS++ | | | 90.23 1 | 91.01 1 | 87.89 24 | 94.34 29 | 71.25 63 | 95.06 1 | 94.23 5 | 78.38 35 | 92.78 4 | 95.74 6 | 82.45 3 | 97.49 3 | 89.42 4 | 96.68 2 | 94.95 8 |
|
test_241102_TWO | | | | | | | | | 94.06 12 | 77.24 52 | 92.78 4 | 95.72 8 | 81.26 8 | 97.44 5 | 89.07 9 | 96.58 6 | 94.26 41 |
|
IU-MVS | | | | | | 95.30 2 | 71.25 63 | | 92.95 56 | 66.81 244 | 92.39 6 | | | | 88.94 11 | 96.63 4 | 94.85 17 |
|
SMA-MVS |  | | 89.08 7 | 89.23 7 | 88.61 5 | 94.25 33 | 73.73 10 | 92.40 23 | 93.63 23 | 74.77 112 | 92.29 7 | 95.97 2 | 74.28 36 | 97.24 11 | 88.58 13 | 96.91 1 | 94.87 14 |
Yufeng Yin; Xiaoyan Liu; Zichao Zhang: SMA-MVS: Segmentation-Guided Multi-Scale Anchor Deformation Patch Multi-View Stereo. IEEE Transactions on Circuits and Systems for Video Technology |
DPE-MVS |  | | 89.48 5 | 89.98 4 | 88.01 14 | 94.80 11 | 72.69 32 | 91.59 43 | 94.10 10 | 75.90 88 | 92.29 7 | 95.66 10 | 81.67 6 | 97.38 9 | 87.44 20 | 96.34 15 | 93.95 54 |
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025 |
DVP-MVS |  | | 89.60 3 | 90.35 3 | 87.33 45 | 95.27 5 | 71.25 63 | 93.49 9 | 92.73 65 | 77.33 50 | 92.12 9 | 95.78 4 | 80.98 9 | 97.40 7 | 89.08 7 | 96.41 12 | 93.33 86 |
Zhenlong Yuan, Jinguo Luo, Fei Shen, Zhaoxin Li, Cong Liu, Tianlu Mao, Zhaoqi Wang: DVP-MVS: Synergize Depth-Edge and Visibility Prior for Multi-View Stereo. AAAI2025 |
test_0728_THIRD | | | | | | | | | | 78.38 35 | 92.12 9 | 95.78 4 | 81.46 7 | 97.40 7 | 89.42 4 | 96.57 7 | 94.67 24 |
|
test_one_0601 | | | | | | 95.07 7 | 71.46 61 | | 94.14 7 | 78.27 37 | 92.05 11 | 95.74 6 | 80.83 11 | | | | |
|
PC_three_1452 | | | | | | | | | | 68.21 236 | 92.02 12 | 94.00 48 | 82.09 5 | 95.98 55 | 84.58 40 | 96.68 2 | 94.95 8 |
|
test_part2 | | | | | | 95.06 8 | 72.65 33 | | | | 91.80 13 | | | | | | |
|
MSP-MVS | | | 89.51 4 | 89.91 5 | 88.30 9 | 94.28 32 | 73.46 18 | 92.90 16 | 94.11 8 | 80.27 12 | 91.35 14 | 94.16 41 | 78.35 13 | 96.77 23 | 89.59 3 | 94.22 64 | 94.67 24 |
Zhenlong Yuan, Cong Liu, Fei Shen, Zhaoxin Li, Jingguo luo, Tianlu Mao and Zhaoqi Wang: MSP-MVS: Multi-granularity Segmentation Prior Guided Multi-View Stereo. AAAI2025 |
FOURS1 | | | | | | 95.00 10 | 72.39 42 | 95.06 1 | 93.84 18 | 74.49 118 | 91.30 15 | | | | | | |
|
APDe-MVS | | | 89.15 6 | 89.63 6 | 87.73 30 | 94.49 20 | 71.69 58 | 93.83 4 | 93.96 16 | 75.70 92 | 91.06 16 | 96.03 1 | 76.84 15 | 97.03 15 | 89.09 6 | 95.65 32 | 94.47 31 |
|
SD-MVS | | | 88.06 14 | 88.50 13 | 86.71 57 | 92.60 76 | 72.71 30 | 91.81 41 | 93.19 40 | 77.87 38 | 90.32 17 | 94.00 48 | 74.83 28 | 93.78 145 | 87.63 17 | 94.27 63 | 93.65 73 |
Zhenlong Yuan, Jiakai Cao, Zhaoxin Li, Hao Jiang and Zhaoqi Wang: SD-MVS: Segmentation-driven Deformation Multi-View Stereo with Spherical Refinement and EM optimization. AAAI2024 |
DeepPCF-MVS | | 80.84 1 | 88.10 12 | 88.56 12 | 86.73 56 | 92.24 78 | 69.03 110 | 89.57 90 | 93.39 34 | 77.53 47 | 89.79 18 | 94.12 43 | 78.98 12 | 96.58 36 | 85.66 27 | 95.72 29 | 94.58 27 |
|
xxxxxxxxxxxxxcwj | | | 87.88 19 | 87.92 19 | 87.77 26 | 93.80 44 | 72.35 45 | 90.47 67 | 89.69 169 | 74.31 122 | 89.16 19 | 95.10 13 | 75.65 22 | 96.19 45 | 87.07 21 | 96.01 17 | 94.79 19 |
|
SF-MVS | | | 88.46 11 | 88.74 11 | 87.64 38 | 92.78 69 | 71.95 53 | 92.40 23 | 94.74 2 | 75.71 90 | 89.16 19 | 95.10 13 | 75.65 22 | 96.19 45 | 87.07 21 | 96.01 17 | 94.79 19 |
|
TSAR-MVS + MP. | | | 88.02 17 | 88.11 16 | 87.72 32 | 93.68 49 | 72.13 50 | 91.41 48 | 92.35 80 | 74.62 116 | 88.90 21 | 93.85 52 | 75.75 21 | 96.00 53 | 87.80 15 | 94.63 53 | 95.04 6 |
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition |
ETH3D-3000-0.1 | | | 88.09 13 | 88.29 14 | 87.50 41 | 92.76 70 | 71.89 56 | 91.43 47 | 94.70 3 | 74.47 119 | 88.86 22 | 94.61 21 | 75.23 25 | 95.84 58 | 86.62 26 | 95.92 21 | 94.78 21 |
|
APD-MVS |  | | 87.44 26 | 87.52 24 | 87.19 47 | 94.24 34 | 72.39 42 | 91.86 40 | 92.83 61 | 73.01 151 | 88.58 23 | 94.52 23 | 73.36 42 | 96.49 37 | 84.26 47 | 95.01 42 | 92.70 108 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
9.14 | | | | 88.26 15 | | 92.84 68 | | 91.52 46 | 94.75 1 | 73.93 132 | 88.57 24 | 94.67 19 | 75.57 24 | 95.79 59 | 86.77 23 | 95.76 28 | |
|
testtj | | | 87.78 20 | 87.78 21 | 87.77 26 | 94.55 18 | 72.47 39 | 92.23 32 | 93.49 29 | 74.75 113 | 88.33 25 | 94.43 32 | 73.27 44 | 97.02 16 | 84.18 51 | 94.84 48 | 93.82 62 |
|
ACMMP_NAP | | | 88.05 16 | 88.08 17 | 87.94 17 | 93.70 47 | 73.05 23 | 90.86 57 | 93.59 25 | 76.27 82 | 88.14 26 | 95.09 15 | 71.06 62 | 96.67 28 | 87.67 16 | 96.37 14 | 94.09 46 |
|
SteuartSystems-ACMMP | | | 88.72 10 | 88.86 10 | 88.32 8 | 92.14 80 | 72.96 26 | 93.73 5 | 93.67 22 | 80.19 14 | 88.10 27 | 94.80 16 | 73.76 41 | 97.11 13 | 87.51 18 | 95.82 24 | 94.90 11 |
Skip Steuart: Steuart Systems R&D Blog. |
CNVR-MVS | | | 88.93 9 | 89.13 9 | 88.33 7 | 94.77 12 | 73.82 9 | 90.51 64 | 93.00 47 | 80.90 9 | 88.06 28 | 94.06 46 | 76.43 17 | 96.84 20 | 88.48 14 | 95.99 19 | 94.34 37 |
|
canonicalmvs | | | 85.91 55 | 85.87 57 | 86.04 72 | 89.84 124 | 69.44 108 | 90.45 70 | 93.00 47 | 76.70 72 | 88.01 29 | 91.23 107 | 73.28 43 | 93.91 140 | 81.50 80 | 88.80 124 | 94.77 22 |
|
HPM-MVS++ |  | | 89.02 8 | 89.15 8 | 88.63 4 | 95.01 9 | 76.03 1 | 92.38 26 | 92.85 60 | 80.26 13 | 87.78 30 | 94.27 36 | 75.89 20 | 96.81 22 | 87.45 19 | 96.44 9 | 93.05 97 |
|
ZD-MVS | | | | | | 94.38 27 | 72.22 48 | | 92.67 67 | 70.98 181 | 87.75 31 | 94.07 45 | 74.01 40 | 96.70 26 | 84.66 39 | 94.84 48 | |
|
alignmvs | | | 85.48 62 | 85.32 64 | 85.96 74 | 89.51 131 | 69.47 105 | 89.74 86 | 92.47 74 | 76.17 83 | 87.73 32 | 91.46 103 | 70.32 70 | 93.78 145 | 81.51 79 | 88.95 121 | 94.63 26 |
|
ETH3 D test6400 | | | 87.50 25 | 87.44 26 | 87.70 35 | 93.71 46 | 71.75 57 | 90.62 62 | 94.05 15 | 70.80 183 | 87.59 33 | 93.51 56 | 77.57 14 | 96.63 31 | 83.31 58 | 95.77 26 | 94.72 23 |
|
ETH3D cwj APD-0.16 | | | 87.31 32 | 87.27 28 | 87.44 43 | 91.60 88 | 72.45 41 | 90.02 78 | 94.37 4 | 71.76 165 | 87.28 34 | 94.27 36 | 75.18 26 | 96.08 49 | 85.16 30 | 95.77 26 | 93.80 65 |
|
旧先验2 | | | | | | | | 86.56 186 | | 58.10 331 | 87.04 35 | | | 88.98 280 | 74.07 142 | | |
|
Regformer-2 | | | 86.63 43 | 86.53 43 | 86.95 51 | 89.33 138 | 71.24 67 | 88.43 123 | 92.05 93 | 82.50 1 | 86.88 36 | 90.09 132 | 74.45 31 | 95.61 63 | 84.38 43 | 90.63 103 | 94.01 51 |
|
SR-MVS | | | 86.73 39 | 86.67 41 | 86.91 52 | 94.11 40 | 72.11 51 | 92.37 27 | 92.56 73 | 74.50 117 | 86.84 37 | 94.65 20 | 67.31 97 | 95.77 60 | 84.80 37 | 92.85 75 | 92.84 106 |
|
Regformer-1 | | | 86.41 48 | 86.33 46 | 86.64 58 | 89.33 138 | 70.93 75 | 88.43 123 | 91.39 123 | 82.14 3 | 86.65 38 | 90.09 132 | 74.39 34 | 95.01 96 | 83.97 53 | 90.63 103 | 93.97 53 |
|
dcpmvs_2 | | | 85.63 61 | 86.15 53 | 84.06 126 | 91.71 86 | 64.94 196 | 86.47 189 | 91.87 105 | 73.63 137 | 86.60 39 | 93.02 70 | 76.57 16 | 91.87 224 | 83.36 57 | 92.15 84 | 95.35 1 |
|
test1172 | | | 86.20 52 | 86.22 49 | 86.12 70 | 93.95 42 | 69.89 96 | 91.79 42 | 92.28 82 | 75.07 104 | 86.40 40 | 94.58 22 | 65.00 122 | 95.56 65 | 84.34 45 | 92.60 78 | 92.90 104 |
|
MP-MVS-pluss | | | 87.67 22 | 87.72 22 | 87.54 39 | 93.64 50 | 72.04 52 | 89.80 84 | 93.50 28 | 75.17 103 | 86.34 41 | 95.29 12 | 70.86 63 | 96.00 53 | 88.78 12 | 96.04 16 | 94.58 27 |
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
APD-MVS_3200maxsize | | | 85.97 54 | 85.88 56 | 86.22 67 | 92.69 72 | 69.53 103 | 91.93 37 | 92.99 49 | 73.54 141 | 85.94 42 | 94.51 26 | 65.80 114 | 95.61 63 | 83.04 65 | 92.51 80 | 93.53 81 |
|
zzz-MVS | | | 87.53 24 | 87.41 27 | 87.90 21 | 94.18 37 | 74.25 5 | 90.23 74 | 92.02 94 | 79.45 21 | 85.88 43 | 94.80 16 | 68.07 88 | 96.21 43 | 86.69 24 | 95.34 36 | 93.23 89 |
|
MTAPA | | | 87.23 33 | 87.00 34 | 87.90 21 | 94.18 37 | 74.25 5 | 86.58 185 | 92.02 94 | 79.45 21 | 85.88 43 | 94.80 16 | 68.07 88 | 96.21 43 | 86.69 24 | 95.34 36 | 93.23 89 |
|
TSAR-MVS + GP. | | | 85.71 59 | 85.33 63 | 86.84 53 | 91.34 90 | 72.50 37 | 89.07 102 | 87.28 234 | 76.41 75 | 85.80 45 | 90.22 130 | 74.15 39 | 95.37 82 | 81.82 78 | 91.88 87 | 92.65 112 |
|
NCCC | | | 88.06 14 | 88.01 18 | 88.24 10 | 94.41 24 | 73.62 11 | 91.22 52 | 92.83 61 | 81.50 6 | 85.79 46 | 93.47 59 | 73.02 47 | 97.00 17 | 84.90 33 | 94.94 44 | 94.10 45 |
|
SR-MVS-dyc-post | | | 85.77 57 | 85.61 59 | 86.23 66 | 93.06 62 | 70.63 82 | 91.88 38 | 92.27 83 | 73.53 142 | 85.69 47 | 94.45 28 | 65.00 122 | 95.56 65 | 82.75 68 | 91.87 88 | 92.50 115 |
|
RE-MVS-def | | | | 85.48 60 | | 93.06 62 | 70.63 82 | 91.88 38 | 92.27 83 | 73.53 142 | 85.69 47 | 94.45 28 | 63.87 129 | | 82.75 68 | 91.87 88 | 92.50 115 |
|
testdata | | | | | 79.97 239 | 90.90 97 | 64.21 210 | | 84.71 264 | 59.27 323 | 85.40 49 | 92.91 71 | 62.02 160 | 89.08 278 | 68.95 190 | 91.37 95 | 86.63 292 |
|
Regformer-4 | | | 85.68 60 | 85.45 61 | 86.35 62 | 88.95 156 | 69.67 100 | 88.29 133 | 91.29 125 | 81.73 5 | 85.36 50 | 90.01 135 | 72.62 49 | 95.35 83 | 83.28 61 | 87.57 136 | 94.03 49 |
|
abl_6 | | | 85.23 67 | 84.95 71 | 86.07 71 | 92.23 79 | 70.48 86 | 90.80 59 | 92.08 92 | 73.51 144 | 85.26 51 | 94.16 41 | 62.75 146 | 95.92 57 | 82.46 75 | 91.30 97 | 91.81 138 |
|
ZNCC-MVS | | | 87.94 18 | 87.85 20 | 88.20 11 | 94.39 26 | 73.33 20 | 93.03 14 | 93.81 20 | 76.81 66 | 85.24 52 | 94.32 35 | 71.76 56 | 96.93 18 | 85.53 29 | 95.79 25 | 94.32 38 |
|
PHI-MVS | | | 86.43 46 | 86.17 52 | 87.24 46 | 90.88 98 | 70.96 72 | 92.27 31 | 94.07 11 | 72.45 154 | 85.22 53 | 91.90 90 | 69.47 78 | 96.42 38 | 83.28 61 | 95.94 20 | 94.35 36 |
|
patch_mono-2 | | | 83.65 80 | 84.54 75 | 80.99 219 | 90.06 119 | 65.83 178 | 84.21 246 | 88.74 205 | 71.60 171 | 85.01 54 | 92.44 81 | 74.51 30 | 83.50 325 | 82.15 77 | 92.15 84 | 93.64 75 |
|
Regformer-3 | | | 85.23 67 | 85.07 68 | 85.70 76 | 88.95 156 | 69.01 112 | 88.29 133 | 89.91 163 | 80.95 8 | 85.01 54 | 90.01 135 | 72.45 50 | 94.19 126 | 82.50 74 | 87.57 136 | 93.90 57 |
|
TEST9 | | | | | | 93.26 56 | 72.96 26 | 88.75 113 | 91.89 103 | 68.44 234 | 85.00 56 | 93.10 65 | 74.36 35 | 95.41 76 | | | |
|
train_agg | | | 86.43 46 | 86.20 50 | 87.13 49 | 93.26 56 | 72.96 26 | 88.75 113 | 91.89 103 | 68.69 230 | 85.00 56 | 93.10 65 | 74.43 32 | 95.41 76 | 84.97 32 | 95.71 30 | 93.02 99 |
|
HFP-MVS | | | 87.58 23 | 87.47 25 | 87.94 17 | 94.58 16 | 73.54 15 | 93.04 12 | 93.24 37 | 76.78 68 | 84.91 58 | 94.44 30 | 70.78 64 | 96.61 32 | 84.53 41 | 94.89 46 | 93.66 68 |
|
#test# | | | 87.33 31 | 87.13 33 | 87.94 17 | 94.58 16 | 73.54 15 | 92.34 28 | 93.24 37 | 75.23 100 | 84.91 58 | 94.44 30 | 70.78 64 | 96.61 32 | 83.75 56 | 94.89 46 | 93.66 68 |
|
test_prior3 | | | 86.73 39 | 86.86 40 | 86.33 63 | 92.61 74 | 69.59 101 | 88.85 109 | 92.97 54 | 75.41 96 | 84.91 58 | 93.54 54 | 74.28 36 | 95.48 70 | 83.31 58 | 95.86 22 | 93.91 55 |
|
test_prior2 | | | | | | | | 88.85 109 | | 75.41 96 | 84.91 58 | 93.54 54 | 74.28 36 | | 83.31 58 | 95.86 22 | |
|
test_8 | | | | | | 93.13 58 | 72.57 36 | 88.68 118 | 91.84 107 | 68.69 230 | 84.87 62 | 93.10 65 | 74.43 32 | 95.16 87 | | | |
|
MCST-MVS | | | 87.37 30 | 87.25 30 | 87.73 30 | 94.53 19 | 72.46 40 | 89.82 82 | 93.82 19 | 73.07 149 | 84.86 63 | 92.89 72 | 76.22 18 | 96.33 39 | 84.89 35 | 95.13 41 | 94.40 34 |
|
GST-MVS | | | 87.42 28 | 87.26 29 | 87.89 24 | 94.12 39 | 72.97 25 | 92.39 25 | 93.43 32 | 76.89 64 | 84.68 64 | 93.99 50 | 70.67 67 | 96.82 21 | 84.18 51 | 95.01 42 | 93.90 57 |
|
h-mvs33 | | | 83.15 89 | 82.19 97 | 86.02 73 | 90.56 105 | 70.85 78 | 88.15 140 | 89.16 185 | 76.02 86 | 84.67 65 | 91.39 105 | 61.54 165 | 95.50 69 | 82.71 70 | 75.48 281 | 91.72 140 |
|
hse-mvs2 | | | 81.72 111 | 80.94 117 | 84.07 125 | 88.72 167 | 67.68 144 | 85.87 205 | 87.26 235 | 76.02 86 | 84.67 65 | 88.22 185 | 61.54 165 | 93.48 161 | 82.71 70 | 73.44 308 | 91.06 157 |
|
ACMMPR | | | 87.44 26 | 87.23 31 | 88.08 13 | 94.64 13 | 73.59 12 | 93.04 12 | 93.20 39 | 76.78 68 | 84.66 67 | 94.52 23 | 68.81 86 | 96.65 29 | 84.53 41 | 94.90 45 | 94.00 52 |
|
CDPH-MVS | | | 85.76 58 | 85.29 66 | 87.17 48 | 93.49 53 | 71.08 68 | 88.58 121 | 92.42 78 | 68.32 235 | 84.61 68 | 93.48 57 | 72.32 51 | 96.15 48 | 79.00 96 | 95.43 34 | 94.28 40 |
|
UA-Net | | | 85.08 71 | 84.96 70 | 85.45 80 | 92.07 81 | 68.07 137 | 89.78 85 | 90.86 138 | 82.48 2 | 84.60 69 | 93.20 63 | 69.35 79 | 95.22 85 | 71.39 166 | 90.88 101 | 93.07 96 |
|
CS-MVS-test | | | 86.26 50 | 86.48 44 | 85.60 77 | 90.84 99 | 66.60 163 | 91.16 53 | 93.56 26 | 79.82 18 | 84.57 70 | 89.89 137 | 70.67 67 | 95.04 94 | 84.30 46 | 93.48 69 | 95.16 4 |
|
CS-MVS | | | 86.61 44 | 86.96 36 | 85.56 79 | 90.78 102 | 66.54 165 | 92.84 17 | 93.30 36 | 79.67 20 | 84.55 71 | 92.25 84 | 71.46 59 | 95.00 97 | 84.25 49 | 93.48 69 | 95.15 5 |
|
region2R | | | 87.42 28 | 87.20 32 | 88.09 12 | 94.63 14 | 73.55 13 | 93.03 14 | 93.12 42 | 76.73 71 | 84.45 72 | 94.52 23 | 69.09 82 | 96.70 26 | 84.37 44 | 94.83 50 | 94.03 49 |
|
agg_prior1 | | | 86.22 51 | 86.09 55 | 86.62 59 | 92.85 66 | 71.94 54 | 88.59 120 | 91.78 110 | 68.96 225 | 84.41 73 | 93.18 64 | 74.94 27 | 94.93 98 | 84.75 38 | 95.33 38 | 93.01 100 |
|
agg_prior | | | | | | 92.85 66 | 71.94 54 | | 91.78 110 | | 84.41 73 | | | 94.93 98 | | | |
|
VDD-MVS | | | 83.01 94 | 82.36 95 | 84.96 93 | 91.02 95 | 66.40 166 | 88.91 106 | 88.11 214 | 77.57 43 | 84.39 75 | 93.29 62 | 52.19 245 | 93.91 140 | 77.05 118 | 88.70 126 | 94.57 29 |
|
casdiffmvs | | | 85.11 70 | 85.14 67 | 85.01 91 | 87.20 214 | 65.77 181 | 87.75 151 | 92.83 61 | 77.84 39 | 84.36 76 | 92.38 82 | 72.15 53 | 93.93 139 | 81.27 82 | 90.48 105 | 95.33 2 |
|
MSLP-MVS++ | | | 85.43 64 | 85.76 58 | 84.45 110 | 91.93 83 | 70.24 87 | 90.71 60 | 92.86 59 | 77.46 49 | 84.22 77 | 92.81 76 | 67.16 99 | 92.94 186 | 80.36 90 | 94.35 61 | 90.16 189 |
|
DeepC-MVS_fast | | 79.65 3 | 86.91 38 | 86.62 42 | 87.76 29 | 93.52 52 | 72.37 44 | 91.26 49 | 93.04 43 | 76.62 73 | 84.22 77 | 93.36 61 | 71.44 60 | 96.76 24 | 80.82 86 | 95.33 38 | 94.16 43 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
DROMVSNet | | | 86.01 53 | 86.38 45 | 84.91 97 | 89.31 143 | 66.27 169 | 92.32 29 | 93.63 23 | 79.37 23 | 84.17 79 | 91.88 91 | 69.04 85 | 95.43 74 | 83.93 54 | 93.77 67 | 93.01 100 |
|
ETV-MVS | | | 84.90 74 | 84.67 74 | 85.59 78 | 89.39 136 | 68.66 126 | 88.74 115 | 92.64 71 | 79.97 17 | 84.10 80 | 85.71 250 | 69.32 80 | 95.38 79 | 80.82 86 | 91.37 95 | 92.72 107 |
|
VNet | | | 82.21 102 | 82.41 93 | 81.62 200 | 90.82 100 | 60.93 260 | 84.47 237 | 89.78 165 | 76.36 80 | 84.07 81 | 91.88 91 | 64.71 124 | 90.26 258 | 70.68 171 | 88.89 122 | 93.66 68 |
|
baseline | | | 84.93 72 | 84.98 69 | 84.80 102 | 87.30 212 | 65.39 188 | 87.30 163 | 92.88 58 | 77.62 41 | 84.04 82 | 92.26 83 | 71.81 55 | 93.96 133 | 81.31 81 | 90.30 107 | 95.03 7 |
|
PGM-MVS | | | 86.68 41 | 86.27 48 | 87.90 21 | 94.22 35 | 73.38 19 | 90.22 75 | 93.04 43 | 75.53 94 | 83.86 83 | 94.42 33 | 67.87 92 | 96.64 30 | 82.70 72 | 94.57 55 | 93.66 68 |
|
MP-MVS |  | | 87.71 21 | 87.64 23 | 87.93 20 | 94.36 28 | 73.88 7 | 92.71 22 | 92.65 70 | 77.57 43 | 83.84 84 | 94.40 34 | 72.24 52 | 96.28 41 | 85.65 28 | 95.30 40 | 93.62 76 |
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo. |
HPM-MVS |  | | 87.11 35 | 86.98 35 | 87.50 41 | 93.88 43 | 72.16 49 | 92.19 33 | 93.33 35 | 76.07 85 | 83.81 85 | 93.95 51 | 69.77 76 | 96.01 52 | 85.15 31 | 94.66 52 | 94.32 38 |
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023 |
CP-MVS | | | 87.11 35 | 86.92 37 | 87.68 37 | 94.20 36 | 73.86 8 | 93.98 3 | 92.82 64 | 76.62 73 | 83.68 86 | 94.46 27 | 67.93 90 | 95.95 56 | 84.20 50 | 94.39 59 | 93.23 89 |
|
XVS | | | 87.18 34 | 86.91 38 | 88.00 15 | 94.42 22 | 73.33 20 | 92.78 18 | 92.99 49 | 79.14 24 | 83.67 87 | 94.17 40 | 67.45 95 | 96.60 34 | 83.06 63 | 94.50 56 | 94.07 47 |
|
X-MVStestdata | | | 80.37 145 | 77.83 181 | 88.00 15 | 94.42 22 | 73.33 20 | 92.78 18 | 92.99 49 | 79.14 24 | 83.67 87 | 12.47 373 | 67.45 95 | 96.60 34 | 83.06 63 | 94.50 56 | 94.07 47 |
|
DELS-MVS | | | 85.41 65 | 85.30 65 | 85.77 75 | 88.49 174 | 67.93 139 | 85.52 218 | 93.44 31 | 78.70 31 | 83.63 89 | 89.03 163 | 74.57 29 | 95.71 62 | 80.26 92 | 94.04 65 | 93.66 68 |
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 |
LFMVS | | | 81.82 110 | 81.23 111 | 83.57 143 | 91.89 84 | 63.43 228 | 89.84 81 | 81.85 305 | 77.04 61 | 83.21 90 | 93.10 65 | 52.26 244 | 93.43 165 | 71.98 161 | 89.95 114 | 93.85 59 |
|
VDDNet | | | 81.52 117 | 80.67 120 | 84.05 128 | 90.44 108 | 64.13 212 | 89.73 87 | 85.91 254 | 71.11 178 | 83.18 91 | 93.48 57 | 50.54 268 | 93.49 160 | 73.40 150 | 88.25 132 | 94.54 30 |
|
CSCG | | | 86.41 48 | 86.19 51 | 87.07 50 | 92.91 65 | 72.48 38 | 90.81 58 | 93.56 26 | 73.95 130 | 83.16 92 | 91.07 113 | 75.94 19 | 95.19 86 | 79.94 94 | 94.38 60 | 93.55 79 |
|
nrg030 | | | 83.88 76 | 83.53 79 | 84.96 93 | 86.77 222 | 69.28 109 | 90.46 69 | 92.67 67 | 74.79 111 | 82.95 93 | 91.33 106 | 72.70 48 | 93.09 180 | 80.79 88 | 79.28 238 | 92.50 115 |
|
EI-MVSNet-Vis-set | | | 84.19 75 | 83.81 78 | 85.31 82 | 88.18 183 | 67.85 140 | 87.66 153 | 89.73 168 | 80.05 16 | 82.95 93 | 89.59 147 | 70.74 66 | 94.82 106 | 80.66 89 | 84.72 172 | 93.28 88 |
|
MVS_Test | | | 83.15 89 | 83.06 85 | 83.41 148 | 86.86 218 | 63.21 232 | 86.11 199 | 92.00 97 | 74.31 122 | 82.87 95 | 89.44 155 | 70.03 72 | 93.21 170 | 77.39 115 | 88.50 130 | 93.81 63 |
|
DPM-MVS | | | 84.93 72 | 84.29 77 | 86.84 53 | 90.20 112 | 73.04 24 | 87.12 167 | 93.04 43 | 69.80 203 | 82.85 96 | 91.22 108 | 73.06 46 | 96.02 51 | 76.72 123 | 94.63 53 | 91.46 148 |
|
DeepC-MVS | | 79.81 2 | 87.08 37 | 86.88 39 | 87.69 36 | 91.16 92 | 72.32 47 | 90.31 72 | 93.94 17 | 77.12 58 | 82.82 97 | 94.23 39 | 72.13 54 | 97.09 14 | 84.83 36 | 95.37 35 | 93.65 73 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
mPP-MVS | | | 86.67 42 | 86.32 47 | 87.72 32 | 94.41 24 | 73.55 13 | 92.74 20 | 92.22 87 | 76.87 65 | 82.81 98 | 94.25 38 | 66.44 104 | 96.24 42 | 82.88 67 | 94.28 62 | 93.38 83 |
|
test12 | | | | | 86.80 55 | 92.63 73 | 70.70 81 | | 91.79 109 | | 82.71 99 | | 71.67 57 | 96.16 47 | | 94.50 56 | 93.54 80 |
|
HPM-MVS_fast | | | 85.35 66 | 84.95 71 | 86.57 61 | 93.69 48 | 70.58 85 | 92.15 35 | 91.62 114 | 73.89 133 | 82.67 100 | 94.09 44 | 62.60 147 | 95.54 68 | 80.93 84 | 92.93 73 | 93.57 78 |
|
Effi-MVS+ | | | 83.62 82 | 83.08 84 | 85.24 85 | 88.38 179 | 67.45 147 | 88.89 107 | 89.15 186 | 75.50 95 | 82.27 101 | 88.28 182 | 69.61 77 | 94.45 116 | 77.81 110 | 87.84 134 | 93.84 61 |
|
EI-MVSNet-UG-set | | | 83.81 77 | 83.38 81 | 85.09 89 | 87.87 192 | 67.53 146 | 87.44 159 | 89.66 170 | 79.74 19 | 82.23 102 | 89.41 156 | 70.24 71 | 94.74 109 | 79.95 93 | 83.92 180 | 92.99 102 |
|
MVS_111021_HR | | | 85.14 69 | 84.75 73 | 86.32 65 | 91.65 87 | 72.70 31 | 85.98 201 | 90.33 151 | 76.11 84 | 82.08 103 | 91.61 98 | 71.36 61 | 94.17 128 | 81.02 83 | 92.58 79 | 92.08 131 |
|
diffmvs | | | 82.10 103 | 81.88 105 | 82.76 181 | 83.00 284 | 63.78 218 | 83.68 254 | 89.76 166 | 72.94 152 | 82.02 104 | 89.85 139 | 65.96 113 | 90.79 252 | 82.38 76 | 87.30 143 | 93.71 67 |
|
xiu_mvs_v1_base_debu | | | 80.80 133 | 79.72 137 | 84.03 131 | 87.35 207 | 70.19 90 | 85.56 211 | 88.77 200 | 69.06 221 | 81.83 105 | 88.16 186 | 50.91 262 | 92.85 188 | 78.29 107 | 87.56 138 | 89.06 227 |
|
xiu_mvs_v1_base | | | 80.80 133 | 79.72 137 | 84.03 131 | 87.35 207 | 70.19 90 | 85.56 211 | 88.77 200 | 69.06 221 | 81.83 105 | 88.16 186 | 50.91 262 | 92.85 188 | 78.29 107 | 87.56 138 | 89.06 227 |
|
xiu_mvs_v1_base_debi | | | 80.80 133 | 79.72 137 | 84.03 131 | 87.35 207 | 70.19 90 | 85.56 211 | 88.77 200 | 69.06 221 | 81.83 105 | 88.16 186 | 50.91 262 | 92.85 188 | 78.29 107 | 87.56 138 | 89.06 227 |
|
新几何1 | | | | | 83.42 146 | 93.13 58 | 70.71 80 | | 85.48 257 | 57.43 336 | 81.80 108 | 91.98 88 | 63.28 135 | 92.27 207 | 64.60 229 | 92.99 72 | 87.27 275 |
|
test_yl | | | 81.17 122 | 80.47 124 | 83.24 154 | 89.13 151 | 63.62 219 | 86.21 196 | 89.95 161 | 72.43 157 | 81.78 109 | 89.61 145 | 57.50 206 | 93.58 154 | 70.75 169 | 86.90 148 | 92.52 113 |
|
DCV-MVSNet | | | 81.17 122 | 80.47 124 | 83.24 154 | 89.13 151 | 63.62 219 | 86.21 196 | 89.95 161 | 72.43 157 | 81.78 109 | 89.61 145 | 57.50 206 | 93.58 154 | 70.75 169 | 86.90 148 | 92.52 113 |
|
1121 | | | 80.84 128 | 79.77 135 | 84.05 128 | 93.11 60 | 70.78 79 | 84.66 231 | 85.42 258 | 57.37 337 | 81.76 111 | 92.02 87 | 63.41 133 | 94.12 129 | 67.28 205 | 92.93 73 | 87.26 276 |
|
MG-MVS | | | 83.41 85 | 83.45 80 | 83.28 151 | 92.74 71 | 62.28 246 | 88.17 138 | 89.50 173 | 75.22 101 | 81.49 112 | 92.74 80 | 66.75 100 | 95.11 89 | 72.85 156 | 91.58 92 | 92.45 118 |
|
CANet | | | 86.45 45 | 86.10 54 | 87.51 40 | 90.09 114 | 70.94 74 | 89.70 88 | 92.59 72 | 81.78 4 | 81.32 113 | 91.43 104 | 70.34 69 | 97.23 12 | 84.26 47 | 93.36 71 | 94.37 35 |
|
MVSFormer | | | 82.85 95 | 82.05 101 | 85.24 85 | 87.35 207 | 70.21 88 | 90.50 65 | 90.38 147 | 68.55 232 | 81.32 113 | 89.47 150 | 61.68 162 | 93.46 163 | 78.98 97 | 90.26 108 | 92.05 132 |
|
lupinMVS | | | 81.39 120 | 80.27 129 | 84.76 103 | 87.35 207 | 70.21 88 | 85.55 214 | 86.41 246 | 62.85 294 | 81.32 113 | 88.61 172 | 61.68 162 | 92.24 210 | 78.41 105 | 90.26 108 | 91.83 136 |
|
xiu_mvs_v2_base | | | 81.69 113 | 81.05 114 | 83.60 141 | 89.15 150 | 68.03 138 | 84.46 239 | 90.02 159 | 70.67 187 | 81.30 116 | 86.53 236 | 63.17 139 | 94.19 126 | 75.60 132 | 88.54 128 | 88.57 249 |
|
PS-MVSNAJ | | | 81.69 113 | 81.02 115 | 83.70 140 | 89.51 131 | 68.21 135 | 84.28 245 | 90.09 158 | 70.79 184 | 81.26 117 | 85.62 254 | 63.15 140 | 94.29 118 | 75.62 131 | 88.87 123 | 88.59 248 |
|
原ACMM1 | | | | | 84.35 115 | 93.01 64 | 68.79 116 | | 92.44 75 | 63.96 285 | 81.09 118 | 91.57 99 | 66.06 110 | 95.45 72 | 67.19 208 | 94.82 51 | 88.81 242 |
|
jason | | | 81.39 120 | 80.29 128 | 84.70 104 | 86.63 224 | 69.90 95 | 85.95 202 | 86.77 242 | 63.24 287 | 81.07 119 | 89.47 150 | 61.08 178 | 92.15 213 | 78.33 106 | 90.07 113 | 92.05 132 |
jason: jason. |
OPM-MVS | | | 83.50 83 | 82.95 87 | 85.14 87 | 88.79 164 | 70.95 73 | 89.13 101 | 91.52 117 | 77.55 46 | 80.96 120 | 91.75 93 | 60.71 182 | 94.50 115 | 79.67 95 | 86.51 155 | 89.97 205 |
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS). |
Vis-MVSNet |  | | 83.46 84 | 82.80 90 | 85.43 81 | 90.25 111 | 68.74 120 | 90.30 73 | 90.13 157 | 76.33 81 | 80.87 121 | 92.89 72 | 61.00 179 | 94.20 125 | 72.45 160 | 90.97 99 | 93.35 85 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
ACMMP |  | | 85.89 56 | 85.39 62 | 87.38 44 | 93.59 51 | 72.63 34 | 92.74 20 | 93.18 41 | 76.78 68 | 80.73 122 | 93.82 53 | 64.33 125 | 96.29 40 | 82.67 73 | 90.69 102 | 93.23 89 |
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 |
Anonymous20240529 | | | 80.19 149 | 78.89 157 | 84.10 123 | 90.60 104 | 64.75 199 | 88.95 105 | 90.90 136 | 65.97 259 | 80.59 123 | 91.17 110 | 49.97 273 | 93.73 151 | 69.16 188 | 82.70 200 | 93.81 63 |
|
test_part1 | | | 82.78 96 | 82.08 100 | 84.89 98 | 90.66 103 | 66.97 158 | 90.96 56 | 92.93 57 | 77.19 55 | 80.53 124 | 90.04 134 | 63.44 132 | 95.39 78 | 76.04 127 | 76.90 258 | 92.31 122 |
|
MVS_111021_LR | | | 82.61 99 | 82.11 98 | 84.11 122 | 88.82 161 | 71.58 59 | 85.15 221 | 86.16 251 | 74.69 114 | 80.47 125 | 91.04 114 | 62.29 154 | 90.55 256 | 80.33 91 | 90.08 112 | 90.20 188 |
|
ECVR-MVS |  | | 79.61 157 | 79.26 149 | 80.67 226 | 90.08 115 | 54.69 327 | 87.89 148 | 77.44 337 | 74.88 109 | 80.27 126 | 92.79 77 | 48.96 287 | 92.45 198 | 68.55 194 | 92.50 81 | 94.86 15 |
|
VPA-MVSNet | | | 80.60 139 | 80.55 122 | 80.76 224 | 88.07 187 | 60.80 263 | 86.86 175 | 91.58 116 | 75.67 93 | 80.24 127 | 89.45 154 | 63.34 134 | 90.25 259 | 70.51 173 | 79.22 239 | 91.23 153 |
|
test1111 | | | 79.43 164 | 79.18 152 | 80.15 236 | 89.99 120 | 53.31 340 | 87.33 162 | 77.05 340 | 75.04 105 | 80.23 128 | 92.77 79 | 48.97 286 | 92.33 206 | 68.87 191 | 92.40 83 | 94.81 18 |
|
test2506 | | | 77.30 217 | 76.49 214 | 79.74 244 | 90.08 115 | 52.02 343 | 87.86 150 | 63.10 370 | 74.88 109 | 80.16 129 | 92.79 77 | 38.29 343 | 92.35 204 | 68.74 193 | 92.50 81 | 94.86 15 |
|
Anonymous202405211 | | | 78.25 192 | 77.01 200 | 81.99 194 | 91.03 94 | 60.67 265 | 84.77 229 | 83.90 277 | 70.65 189 | 80.00 130 | 91.20 109 | 41.08 333 | 91.43 235 | 65.21 223 | 85.26 167 | 93.85 59 |
|
test222 | | | | | | 91.50 89 | 68.26 133 | 84.16 247 | 83.20 291 | 54.63 348 | 79.74 131 | 91.63 97 | 58.97 195 | | | 91.42 94 | 86.77 288 |
|
OMC-MVS | | | 82.69 97 | 81.97 104 | 84.85 99 | 88.75 166 | 67.42 148 | 87.98 142 | 90.87 137 | 74.92 108 | 79.72 132 | 91.65 95 | 62.19 157 | 93.96 133 | 75.26 135 | 86.42 156 | 93.16 94 |
|
CPTT-MVS | | | 83.73 78 | 83.33 82 | 84.92 96 | 93.28 55 | 70.86 77 | 92.09 36 | 90.38 147 | 68.75 229 | 79.57 133 | 92.83 74 | 60.60 186 | 93.04 184 | 80.92 85 | 91.56 93 | 90.86 165 |
|
IS-MVSNet | | | 83.15 89 | 82.81 89 | 84.18 121 | 89.94 122 | 63.30 230 | 91.59 43 | 88.46 211 | 79.04 28 | 79.49 134 | 92.16 85 | 65.10 119 | 94.28 119 | 67.71 200 | 91.86 90 | 94.95 8 |
|
PS-MVSNAJss | | | 82.07 105 | 81.31 109 | 84.34 116 | 86.51 225 | 67.27 152 | 89.27 94 | 91.51 118 | 71.75 166 | 79.37 135 | 90.22 130 | 63.15 140 | 94.27 120 | 77.69 111 | 82.36 203 | 91.49 146 |
|
EPP-MVSNet | | | 83.40 86 | 83.02 86 | 84.57 106 | 90.13 113 | 64.47 205 | 92.32 29 | 90.73 139 | 74.45 121 | 79.35 136 | 91.10 111 | 69.05 84 | 95.12 88 | 72.78 157 | 87.22 144 | 94.13 44 |
|
DP-MVS Recon | | | 83.11 92 | 82.09 99 | 86.15 68 | 94.44 21 | 70.92 76 | 88.79 111 | 92.20 88 | 70.53 190 | 79.17 137 | 91.03 116 | 64.12 127 | 96.03 50 | 68.39 197 | 90.14 110 | 91.50 145 |
|
ab-mvs | | | 79.51 160 | 78.97 156 | 81.14 215 | 88.46 176 | 60.91 261 | 83.84 252 | 89.24 182 | 70.36 192 | 79.03 138 | 88.87 166 | 63.23 138 | 90.21 260 | 65.12 224 | 82.57 201 | 92.28 124 |
|
EIA-MVS | | | 83.31 88 | 82.80 90 | 84.82 100 | 89.59 127 | 65.59 183 | 88.21 136 | 92.68 66 | 74.66 115 | 78.96 139 | 86.42 238 | 69.06 83 | 95.26 84 | 75.54 133 | 90.09 111 | 93.62 76 |
|
PVSNet_Blended_VisFu | | | 82.62 98 | 81.83 106 | 84.96 93 | 90.80 101 | 69.76 98 | 88.74 115 | 91.70 113 | 69.39 210 | 78.96 139 | 88.46 177 | 65.47 116 | 94.87 105 | 74.42 138 | 88.57 127 | 90.24 187 |
|
HQP_MVS | | | 83.64 81 | 83.14 83 | 85.14 87 | 90.08 115 | 68.71 122 | 91.25 50 | 92.44 75 | 79.12 26 | 78.92 141 | 91.00 117 | 60.42 188 | 95.38 79 | 78.71 99 | 86.32 157 | 91.33 150 |
|
plane_prior3 | | | | | | | 68.60 127 | | | 78.44 33 | 78.92 141 | | | | | | |
|
RRT_MVS | | | 79.88 154 | 78.38 167 | 84.38 112 | 85.42 239 | 70.60 84 | 88.71 117 | 88.75 204 | 72.30 159 | 78.83 143 | 89.14 158 | 44.44 314 | 92.18 212 | 78.50 102 | 79.33 237 | 90.35 183 |
|
EI-MVSNet | | | 80.52 142 | 79.98 131 | 82.12 189 | 84.28 255 | 63.19 234 | 86.41 190 | 88.95 196 | 74.18 127 | 78.69 144 | 87.54 201 | 66.62 101 | 92.43 199 | 72.57 159 | 80.57 222 | 90.74 169 |
|
MVSTER | | | 79.01 176 | 77.88 180 | 82.38 187 | 83.07 281 | 64.80 198 | 84.08 251 | 88.95 196 | 69.01 224 | 78.69 144 | 87.17 213 | 54.70 225 | 92.43 199 | 74.69 137 | 80.57 222 | 89.89 208 |
|
API-MVS | | | 81.99 107 | 81.23 111 | 84.26 119 | 90.94 96 | 70.18 93 | 91.10 54 | 89.32 177 | 71.51 173 | 78.66 146 | 88.28 182 | 65.26 117 | 95.10 92 | 64.74 228 | 91.23 98 | 87.51 269 |
|
GeoE | | | 81.71 112 | 81.01 116 | 83.80 139 | 89.51 131 | 64.45 206 | 88.97 104 | 88.73 206 | 71.27 176 | 78.63 147 | 89.76 141 | 66.32 106 | 93.20 172 | 69.89 180 | 86.02 162 | 93.74 66 |
|
UniMVSNet (Re) | | | 81.60 116 | 81.11 113 | 83.09 161 | 88.38 179 | 64.41 207 | 87.60 154 | 93.02 46 | 78.42 34 | 78.56 148 | 88.16 186 | 69.78 75 | 93.26 169 | 69.58 184 | 76.49 265 | 91.60 141 |
|
MAR-MVS | | | 81.84 109 | 80.70 119 | 85.27 84 | 91.32 91 | 71.53 60 | 89.82 82 | 90.92 135 | 69.77 204 | 78.50 149 | 86.21 242 | 62.36 153 | 94.52 114 | 65.36 222 | 92.05 86 | 89.77 213 |
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 |
Fast-Effi-MVS+ | | | 80.81 131 | 79.92 132 | 83.47 144 | 88.85 158 | 64.51 202 | 85.53 216 | 89.39 175 | 70.79 184 | 78.49 150 | 85.06 266 | 67.54 94 | 93.58 154 | 67.03 211 | 86.58 153 | 92.32 121 |
|
FIs | | | 82.07 105 | 82.42 92 | 81.04 218 | 88.80 163 | 58.34 285 | 88.26 135 | 93.49 29 | 76.93 63 | 78.47 151 | 91.04 114 | 69.92 74 | 92.34 205 | 69.87 181 | 84.97 169 | 92.44 119 |
|
UniMVSNet_NR-MVSNet | | | 81.88 108 | 81.54 108 | 82.92 170 | 88.46 176 | 63.46 226 | 87.13 166 | 92.37 79 | 80.19 14 | 78.38 152 | 89.14 158 | 71.66 58 | 93.05 182 | 70.05 177 | 76.46 266 | 92.25 125 |
|
DU-MVS | | | 81.12 124 | 80.52 123 | 82.90 171 | 87.80 195 | 63.46 226 | 87.02 170 | 91.87 105 | 79.01 29 | 78.38 152 | 89.07 161 | 65.02 120 | 93.05 182 | 70.05 177 | 76.46 266 | 92.20 127 |
|
CLD-MVS | | | 82.31 101 | 81.65 107 | 84.29 118 | 88.47 175 | 67.73 143 | 85.81 209 | 92.35 80 | 75.78 89 | 78.33 154 | 86.58 233 | 64.01 128 | 94.35 117 | 76.05 126 | 87.48 141 | 90.79 166 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
VPNet | | | 78.69 183 | 78.66 160 | 78.76 260 | 88.31 181 | 55.72 323 | 84.45 240 | 86.63 244 | 76.79 67 | 78.26 155 | 90.55 124 | 59.30 193 | 89.70 268 | 66.63 212 | 77.05 256 | 90.88 164 |
|
V42 | | | 79.38 168 | 78.24 172 | 82.83 173 | 81.10 319 | 65.50 185 | 85.55 214 | 89.82 164 | 71.57 172 | 78.21 156 | 86.12 244 | 60.66 184 | 93.18 175 | 75.64 130 | 75.46 283 | 89.81 212 |
|
BH-RMVSNet | | | 79.61 157 | 78.44 165 | 83.14 159 | 89.38 137 | 65.93 175 | 84.95 226 | 87.15 237 | 73.56 140 | 78.19 157 | 89.79 140 | 56.67 214 | 93.36 166 | 59.53 268 | 86.74 151 | 90.13 191 |
|
v2v482 | | | 80.23 147 | 79.29 148 | 83.05 164 | 83.62 267 | 64.14 211 | 87.04 169 | 89.97 160 | 73.61 138 | 78.18 158 | 87.22 210 | 61.10 177 | 93.82 143 | 76.11 125 | 76.78 263 | 91.18 154 |
|
PVSNet_BlendedMVS | | | 80.60 139 | 80.02 130 | 82.36 188 | 88.85 158 | 65.40 186 | 86.16 198 | 92.00 97 | 69.34 212 | 78.11 159 | 86.09 245 | 66.02 111 | 94.27 120 | 71.52 163 | 82.06 205 | 87.39 271 |
|
PVSNet_Blended | | | 80.98 125 | 80.34 126 | 82.90 171 | 88.85 158 | 65.40 186 | 84.43 241 | 92.00 97 | 67.62 239 | 78.11 159 | 85.05 267 | 66.02 111 | 94.27 120 | 71.52 163 | 89.50 117 | 89.01 232 |
|
v1144 | | | 80.03 151 | 79.03 154 | 83.01 166 | 83.78 265 | 64.51 202 | 87.11 168 | 90.57 143 | 71.96 164 | 78.08 161 | 86.20 243 | 61.41 169 | 93.94 136 | 74.93 136 | 77.23 253 | 90.60 174 |
|
TranMVSNet+NR-MVSNet | | | 80.84 128 | 80.31 127 | 82.42 186 | 87.85 193 | 62.33 244 | 87.74 152 | 91.33 124 | 80.55 11 | 77.99 162 | 89.86 138 | 65.23 118 | 92.62 192 | 67.05 210 | 75.24 291 | 92.30 123 |
|
Baseline_NR-MVSNet | | | 78.15 197 | 78.33 170 | 77.61 278 | 85.79 232 | 56.21 319 | 86.78 179 | 85.76 255 | 73.60 139 | 77.93 163 | 87.57 199 | 65.02 120 | 88.99 279 | 67.14 209 | 75.33 287 | 87.63 265 |
|
TR-MVS | | | 77.44 213 | 76.18 219 | 81.20 213 | 88.24 182 | 63.24 231 | 84.61 235 | 86.40 247 | 67.55 240 | 77.81 164 | 86.48 237 | 54.10 230 | 93.15 176 | 57.75 286 | 82.72 199 | 87.20 277 |
|
v1192 | | | 79.59 159 | 78.43 166 | 83.07 163 | 83.55 269 | 64.52 201 | 86.93 173 | 90.58 142 | 70.83 182 | 77.78 165 | 85.90 246 | 59.15 194 | 93.94 136 | 73.96 143 | 77.19 255 | 90.76 167 |
|
PCF-MVS | | 73.52 7 | 80.38 144 | 78.84 158 | 85.01 91 | 87.71 199 | 68.99 113 | 83.65 255 | 91.46 122 | 63.00 291 | 77.77 166 | 90.28 127 | 66.10 108 | 95.09 93 | 61.40 254 | 88.22 133 | 90.94 163 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
WR-MVS | | | 79.49 161 | 79.22 151 | 80.27 234 | 88.79 164 | 58.35 284 | 85.06 223 | 88.61 209 | 78.56 32 | 77.65 167 | 88.34 180 | 63.81 131 | 90.66 255 | 64.98 226 | 77.22 254 | 91.80 139 |
|
XVG-OURS | | | 80.41 143 | 79.23 150 | 83.97 135 | 85.64 235 | 69.02 111 | 83.03 268 | 90.39 146 | 71.09 179 | 77.63 168 | 91.49 102 | 54.62 227 | 91.35 237 | 75.71 129 | 83.47 188 | 91.54 143 |
|
v144192 | | | 79.47 162 | 78.37 168 | 82.78 179 | 83.35 272 | 63.96 214 | 86.96 171 | 90.36 150 | 69.99 198 | 77.50 169 | 85.67 252 | 60.66 184 | 93.77 147 | 74.27 140 | 76.58 264 | 90.62 172 |
|
v1921920 | | | 79.22 170 | 78.03 175 | 82.80 176 | 83.30 274 | 63.94 215 | 86.80 177 | 90.33 151 | 69.91 201 | 77.48 170 | 85.53 255 | 58.44 198 | 93.75 149 | 73.60 145 | 76.85 261 | 90.71 170 |
|
thisisatest0530 | | | 79.40 166 | 77.76 185 | 84.31 117 | 87.69 201 | 65.10 194 | 87.36 160 | 84.26 273 | 70.04 197 | 77.42 171 | 88.26 184 | 49.94 274 | 94.79 108 | 70.20 175 | 84.70 173 | 93.03 98 |
|
FC-MVSNet-test | | | 81.52 117 | 82.02 102 | 80.03 238 | 88.42 178 | 55.97 321 | 87.95 144 | 93.42 33 | 77.10 59 | 77.38 172 | 90.98 119 | 69.96 73 | 91.79 225 | 68.46 196 | 84.50 174 | 92.33 120 |
|
v1240 | | | 78.99 177 | 77.78 183 | 82.64 182 | 83.21 276 | 63.54 223 | 86.62 184 | 90.30 153 | 69.74 207 | 77.33 173 | 85.68 251 | 57.04 212 | 93.76 148 | 73.13 154 | 76.92 257 | 90.62 172 |
|
PAPM_NR | | | 83.02 93 | 82.41 93 | 84.82 100 | 92.47 77 | 66.37 167 | 87.93 146 | 91.80 108 | 73.82 134 | 77.32 174 | 90.66 122 | 67.90 91 | 94.90 102 | 70.37 174 | 89.48 118 | 93.19 93 |
|
ACMM | | 73.20 8 | 80.78 136 | 79.84 134 | 83.58 142 | 89.31 143 | 68.37 130 | 89.99 79 | 91.60 115 | 70.28 194 | 77.25 175 | 89.66 143 | 53.37 236 | 93.53 159 | 74.24 141 | 82.85 196 | 88.85 240 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
HQP4-MVS | | | | | | | | | | | 77.24 176 | | | 95.11 89 | | | 91.03 159 |
|
AUN-MVS | | | 79.21 171 | 77.60 190 | 84.05 128 | 88.71 168 | 67.61 145 | 85.84 207 | 87.26 235 | 69.08 220 | 77.23 177 | 88.14 190 | 53.20 238 | 93.47 162 | 75.50 134 | 73.45 307 | 91.06 157 |
|
HQP-NCC | | | | | | 89.33 138 | | 89.17 96 | | 76.41 75 | 77.23 177 | | | | | | |
|
ACMP_Plane | | | | | | 89.33 138 | | 89.17 96 | | 76.41 75 | 77.23 177 | | | | | | |
|
HQP-MVS | | | 82.61 99 | 82.02 102 | 84.37 113 | 89.33 138 | 66.98 156 | 89.17 96 | 92.19 89 | 76.41 75 | 77.23 177 | 90.23 129 | 60.17 191 | 95.11 89 | 77.47 113 | 85.99 163 | 91.03 159 |
|
TAPA-MVS | | 73.13 9 | 79.15 172 | 77.94 177 | 82.79 178 | 89.59 127 | 62.99 239 | 88.16 139 | 91.51 118 | 65.77 260 | 77.14 181 | 91.09 112 | 60.91 180 | 93.21 170 | 50.26 323 | 87.05 146 | 92.17 129 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
PAPR | | | 81.66 115 | 80.89 118 | 83.99 134 | 90.27 110 | 64.00 213 | 86.76 181 | 91.77 112 | 68.84 228 | 77.13 182 | 89.50 148 | 67.63 93 | 94.88 104 | 67.55 202 | 88.52 129 | 93.09 95 |
|
UniMVSNet_ETH3D | | | 79.10 174 | 78.24 172 | 81.70 199 | 86.85 219 | 60.24 271 | 87.28 164 | 88.79 199 | 74.25 125 | 76.84 183 | 90.53 125 | 49.48 279 | 91.56 231 | 67.98 198 | 82.15 204 | 93.29 87 |
|
EPNet | | | 83.72 79 | 82.92 88 | 86.14 69 | 84.22 257 | 69.48 104 | 91.05 55 | 85.27 259 | 81.30 7 | 76.83 184 | 91.65 95 | 66.09 109 | 95.56 65 | 76.00 128 | 93.85 66 | 93.38 83 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
baseline1 | | | 76.98 222 | 76.75 210 | 77.66 276 | 88.13 184 | 55.66 324 | 85.12 222 | 81.89 303 | 73.04 150 | 76.79 185 | 88.90 164 | 62.43 152 | 87.78 296 | 63.30 236 | 71.18 323 | 89.55 219 |
|
tttt0517 | | | 79.40 166 | 77.91 178 | 83.90 138 | 88.10 186 | 63.84 216 | 88.37 130 | 84.05 275 | 71.45 174 | 76.78 186 | 89.12 160 | 49.93 276 | 94.89 103 | 70.18 176 | 83.18 192 | 92.96 103 |
|
TAMVS | | | 78.89 180 | 77.51 192 | 83.03 165 | 87.80 195 | 67.79 142 | 84.72 230 | 85.05 262 | 67.63 238 | 76.75 187 | 87.70 195 | 62.25 155 | 90.82 251 | 58.53 279 | 87.13 145 | 90.49 178 |
|
XVG-OURS-SEG-HR | | | 80.81 131 | 79.76 136 | 83.96 136 | 85.60 236 | 68.78 117 | 83.54 260 | 90.50 144 | 70.66 188 | 76.71 188 | 91.66 94 | 60.69 183 | 91.26 239 | 76.94 120 | 81.58 210 | 91.83 136 |
|
3Dnovator+ | | 77.84 4 | 85.48 62 | 84.47 76 | 88.51 6 | 91.08 93 | 73.49 17 | 93.18 11 | 93.78 21 | 80.79 10 | 76.66 189 | 93.37 60 | 60.40 190 | 96.75 25 | 77.20 116 | 93.73 68 | 95.29 3 |
|
LPG-MVS_test | | | 82.08 104 | 81.27 110 | 84.50 108 | 89.23 147 | 68.76 118 | 90.22 75 | 91.94 101 | 75.37 98 | 76.64 190 | 91.51 100 | 54.29 228 | 94.91 100 | 78.44 103 | 83.78 181 | 89.83 210 |
|
LGP-MVS_train | | | | | 84.50 108 | 89.23 147 | 68.76 118 | | 91.94 101 | 75.37 98 | 76.64 190 | 91.51 100 | 54.29 228 | 94.91 100 | 78.44 103 | 83.78 181 | 89.83 210 |
|
tfpn200view9 | | | 76.42 231 | 75.37 230 | 79.55 251 | 89.13 151 | 57.65 297 | 85.17 219 | 83.60 280 | 73.41 145 | 76.45 192 | 86.39 239 | 52.12 246 | 91.95 219 | 48.33 331 | 83.75 183 | 89.07 225 |
|
thres400 | | | 76.50 228 | 75.37 230 | 79.86 241 | 89.13 151 | 57.65 297 | 85.17 219 | 83.60 280 | 73.41 145 | 76.45 192 | 86.39 239 | 52.12 246 | 91.95 219 | 48.33 331 | 83.75 183 | 90.00 201 |
|
HyFIR lowres test | | | 77.53 212 | 75.40 228 | 83.94 137 | 89.59 127 | 66.62 161 | 80.36 292 | 88.64 208 | 56.29 343 | 76.45 192 | 85.17 263 | 57.64 204 | 93.28 168 | 61.34 256 | 83.10 194 | 91.91 134 |
|
mvs-test1 | | | 80.88 126 | 79.40 144 | 85.29 83 | 85.13 245 | 69.75 99 | 89.28 93 | 88.10 215 | 74.99 106 | 76.44 195 | 86.72 222 | 57.27 209 | 94.26 124 | 73.53 146 | 83.18 192 | 91.87 135 |
|
CDS-MVSNet | | | 79.07 175 | 77.70 187 | 83.17 158 | 87.60 202 | 68.23 134 | 84.40 243 | 86.20 250 | 67.49 241 | 76.36 196 | 86.54 235 | 61.54 165 | 90.79 252 | 61.86 250 | 87.33 142 | 90.49 178 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
thres100view900 | | | 76.50 228 | 75.55 224 | 79.33 252 | 89.52 130 | 56.99 305 | 85.83 208 | 83.23 289 | 73.94 131 | 76.32 197 | 87.12 214 | 51.89 253 | 91.95 219 | 48.33 331 | 83.75 183 | 89.07 225 |
|
thres600view7 | | | 76.50 228 | 75.44 226 | 79.68 246 | 89.40 135 | 57.16 302 | 85.53 216 | 83.23 289 | 73.79 135 | 76.26 198 | 87.09 215 | 51.89 253 | 91.89 222 | 48.05 336 | 83.72 186 | 90.00 201 |
|
UGNet | | | 80.83 130 | 79.59 140 | 84.54 107 | 88.04 188 | 68.09 136 | 89.42 91 | 88.16 213 | 76.95 62 | 76.22 199 | 89.46 152 | 49.30 282 | 93.94 136 | 68.48 195 | 90.31 106 | 91.60 141 |
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_djsdf | | | 80.30 146 | 79.32 147 | 83.27 152 | 83.98 262 | 65.37 189 | 90.50 65 | 90.38 147 | 68.55 232 | 76.19 200 | 88.70 168 | 56.44 215 | 93.46 163 | 78.98 97 | 80.14 228 | 90.97 162 |
|
v148 | | | 78.72 182 | 77.80 182 | 81.47 204 | 82.73 291 | 61.96 250 | 86.30 194 | 88.08 217 | 73.26 147 | 76.18 201 | 85.47 257 | 62.46 151 | 92.36 203 | 71.92 162 | 73.82 304 | 90.09 195 |
|
WTY-MVS | | | 75.65 241 | 75.68 222 | 75.57 297 | 86.40 226 | 56.82 307 | 77.92 318 | 82.40 299 | 65.10 267 | 76.18 201 | 87.72 194 | 63.13 143 | 80.90 337 | 60.31 262 | 81.96 206 | 89.00 234 |
|
mvs_anonymous | | | 79.42 165 | 79.11 153 | 80.34 232 | 84.45 254 | 57.97 291 | 82.59 270 | 87.62 227 | 67.40 242 | 76.17 203 | 88.56 175 | 68.47 87 | 89.59 269 | 70.65 172 | 86.05 161 | 93.47 82 |
|
Anonymous20231211 | | | 78.97 178 | 77.69 188 | 82.81 175 | 90.54 106 | 64.29 209 | 90.11 77 | 91.51 118 | 65.01 270 | 76.16 204 | 88.13 191 | 50.56 267 | 93.03 185 | 69.68 183 | 77.56 251 | 91.11 156 |
|
bset_n11_16_dypcd | | | 77.12 219 | 75.47 225 | 82.06 191 | 81.12 318 | 65.99 173 | 81.37 284 | 83.20 291 | 69.94 200 | 76.09 205 | 83.38 288 | 47.75 292 | 92.26 208 | 78.51 101 | 77.91 247 | 87.95 257 |
|
thisisatest0515 | | | 77.33 216 | 75.38 229 | 83.18 157 | 85.27 241 | 63.80 217 | 82.11 275 | 83.27 288 | 65.06 268 | 75.91 206 | 83.84 280 | 49.54 278 | 94.27 120 | 67.24 207 | 86.19 159 | 91.48 147 |
|
RRT_test8_iter05 | | | 78.38 190 | 77.40 193 | 81.34 209 | 86.00 230 | 58.86 280 | 86.55 187 | 91.26 126 | 72.13 163 | 75.91 206 | 87.42 204 | 44.97 311 | 93.73 151 | 77.02 119 | 75.30 288 | 91.45 149 |
|
CANet_DTU | | | 80.61 138 | 79.87 133 | 82.83 173 | 85.60 236 | 63.17 235 | 87.36 160 | 88.65 207 | 76.37 79 | 75.88 208 | 88.44 178 | 53.51 235 | 93.07 181 | 73.30 151 | 89.74 116 | 92.25 125 |
|
thres200 | | | 75.55 242 | 74.47 240 | 78.82 259 | 87.78 198 | 57.85 294 | 83.07 267 | 83.51 283 | 72.44 156 | 75.84 209 | 84.42 272 | 52.08 248 | 91.75 226 | 47.41 338 | 83.64 187 | 86.86 286 |
|
CHOSEN 1792x2688 | | | 77.63 211 | 75.69 221 | 83.44 145 | 89.98 121 | 68.58 128 | 78.70 310 | 87.50 230 | 56.38 342 | 75.80 210 | 86.84 218 | 58.67 196 | 91.40 236 | 61.58 253 | 85.75 166 | 90.34 184 |
|
AdaColmap |  | | 80.58 141 | 79.42 143 | 84.06 126 | 93.09 61 | 68.91 115 | 89.36 92 | 88.97 195 | 69.27 213 | 75.70 211 | 89.69 142 | 57.20 211 | 95.77 60 | 63.06 238 | 88.41 131 | 87.50 270 |
|
c3_l | | | 78.75 181 | 77.91 178 | 81.26 211 | 82.89 288 | 61.56 255 | 84.09 250 | 89.13 188 | 69.97 199 | 75.56 212 | 84.29 274 | 66.36 105 | 92.09 215 | 73.47 149 | 75.48 281 | 90.12 192 |
|
miper_ehance_all_eth | | | 78.59 186 | 77.76 185 | 81.08 217 | 82.66 293 | 61.56 255 | 83.65 255 | 89.15 186 | 68.87 227 | 75.55 213 | 83.79 282 | 66.49 103 | 92.03 216 | 73.25 152 | 76.39 268 | 89.64 216 |
|
miper_enhance_ethall | | | 77.87 206 | 76.86 204 | 80.92 221 | 81.65 307 | 61.38 257 | 82.68 269 | 88.98 193 | 65.52 264 | 75.47 214 | 82.30 300 | 65.76 115 | 92.00 218 | 72.95 155 | 76.39 268 | 89.39 221 |
|
3Dnovator | | 76.31 5 | 83.38 87 | 82.31 96 | 86.59 60 | 87.94 191 | 72.94 29 | 90.64 61 | 92.14 91 | 77.21 54 | 75.47 214 | 92.83 74 | 58.56 197 | 94.72 110 | 73.24 153 | 92.71 77 | 92.13 130 |
|
jajsoiax | | | 79.29 169 | 77.96 176 | 83.27 152 | 84.68 251 | 66.57 164 | 89.25 95 | 90.16 156 | 69.20 217 | 75.46 216 | 89.49 149 | 45.75 308 | 93.13 178 | 76.84 121 | 80.80 218 | 90.11 193 |
|
IterMVS-LS | | | 80.06 150 | 79.38 145 | 82.11 190 | 85.89 231 | 63.20 233 | 86.79 178 | 89.34 176 | 74.19 126 | 75.45 217 | 86.72 222 | 66.62 101 | 92.39 201 | 72.58 158 | 76.86 260 | 90.75 168 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
BH-untuned | | | 79.47 162 | 78.60 161 | 82.05 192 | 89.19 149 | 65.91 176 | 86.07 200 | 88.52 210 | 72.18 160 | 75.42 218 | 87.69 196 | 61.15 176 | 93.54 158 | 60.38 261 | 86.83 150 | 86.70 290 |
|
mvs_tets | | | 79.13 173 | 77.77 184 | 83.22 156 | 84.70 250 | 66.37 167 | 89.17 96 | 90.19 155 | 69.38 211 | 75.40 219 | 89.46 152 | 44.17 316 | 93.15 176 | 76.78 122 | 80.70 220 | 90.14 190 |
|
HY-MVS | | 69.67 12 | 77.95 203 | 77.15 198 | 80.36 231 | 87.57 206 | 60.21 272 | 83.37 262 | 87.78 225 | 66.11 255 | 75.37 220 | 87.06 217 | 63.27 136 | 90.48 257 | 61.38 255 | 82.43 202 | 90.40 182 |
|
GBi-Net | | | 78.40 188 | 77.40 193 | 81.40 206 | 87.60 202 | 63.01 236 | 88.39 127 | 89.28 178 | 71.63 168 | 75.34 221 | 87.28 206 | 54.80 221 | 91.11 242 | 62.72 239 | 79.57 231 | 90.09 195 |
|
test1 | | | 78.40 188 | 77.40 193 | 81.40 206 | 87.60 202 | 63.01 236 | 88.39 127 | 89.28 178 | 71.63 168 | 75.34 221 | 87.28 206 | 54.80 221 | 91.11 242 | 62.72 239 | 79.57 231 | 90.09 195 |
|
FMVSNet3 | | | 77.88 205 | 76.85 205 | 80.97 220 | 86.84 220 | 62.36 243 | 86.52 188 | 88.77 200 | 71.13 177 | 75.34 221 | 86.66 229 | 54.07 231 | 91.10 245 | 62.72 239 | 79.57 231 | 89.45 220 |
|
CostFormer | | | 75.24 247 | 73.90 246 | 79.27 253 | 82.65 294 | 58.27 286 | 80.80 285 | 82.73 297 | 61.57 305 | 75.33 224 | 83.13 290 | 55.52 217 | 91.07 248 | 64.98 226 | 78.34 245 | 88.45 251 |
|
FMVSNet2 | | | 78.20 195 | 77.21 197 | 81.20 213 | 87.60 202 | 62.89 240 | 87.47 158 | 89.02 191 | 71.63 168 | 75.29 225 | 87.28 206 | 54.80 221 | 91.10 245 | 62.38 243 | 79.38 235 | 89.61 217 |
|
v8 | | | 79.97 153 | 79.02 155 | 82.80 176 | 84.09 259 | 64.50 204 | 87.96 143 | 90.29 154 | 74.13 129 | 75.24 226 | 86.81 219 | 62.88 145 | 93.89 142 | 74.39 139 | 75.40 285 | 90.00 201 |
|
anonymousdsp | | | 78.60 185 | 77.15 198 | 82.98 168 | 80.51 325 | 67.08 154 | 87.24 165 | 89.53 172 | 65.66 262 | 75.16 227 | 87.19 212 | 52.52 239 | 92.25 209 | 77.17 117 | 79.34 236 | 89.61 217 |
|
QAPM | | | 80.88 126 | 79.50 142 | 85.03 90 | 88.01 190 | 68.97 114 | 91.59 43 | 92.00 97 | 66.63 251 | 75.15 228 | 92.16 85 | 57.70 203 | 95.45 72 | 63.52 232 | 88.76 125 | 90.66 171 |
|
v10 | | | 79.74 156 | 78.67 159 | 82.97 169 | 84.06 260 | 64.95 195 | 87.88 149 | 90.62 141 | 73.11 148 | 75.11 229 | 86.56 234 | 61.46 168 | 94.05 132 | 73.68 144 | 75.55 279 | 89.90 207 |
|
Vis-MVSNet (Re-imp) | | | 78.36 191 | 78.45 164 | 78.07 271 | 88.64 170 | 51.78 346 | 86.70 182 | 79.63 326 | 74.14 128 | 75.11 229 | 90.83 120 | 61.29 173 | 89.75 266 | 58.10 283 | 91.60 91 | 92.69 110 |
|
cl22 | | | 78.07 199 | 77.01 200 | 81.23 212 | 82.37 300 | 61.83 252 | 83.55 259 | 87.98 219 | 68.96 225 | 75.06 231 | 83.87 278 | 61.40 170 | 91.88 223 | 73.53 146 | 76.39 268 | 89.98 204 |
|
ACMP | | 74.13 6 | 81.51 119 | 80.57 121 | 84.36 114 | 89.42 134 | 68.69 125 | 89.97 80 | 91.50 121 | 74.46 120 | 75.04 232 | 90.41 126 | 53.82 233 | 94.54 112 | 77.56 112 | 82.91 195 | 89.86 209 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
Effi-MVS+-dtu | | | 80.03 151 | 78.57 162 | 84.42 111 | 85.13 245 | 68.74 120 | 88.77 112 | 88.10 215 | 74.99 106 | 74.97 233 | 83.49 286 | 57.27 209 | 93.36 166 | 73.53 146 | 80.88 216 | 91.18 154 |
|
XXY-MVS | | | 75.41 245 | 75.56 223 | 74.96 303 | 83.59 268 | 57.82 295 | 80.59 290 | 83.87 278 | 66.54 252 | 74.93 234 | 88.31 181 | 63.24 137 | 80.09 340 | 62.16 246 | 76.85 261 | 86.97 284 |
|
eth_miper_zixun_eth | | | 77.92 204 | 76.69 211 | 81.61 202 | 83.00 284 | 61.98 249 | 83.15 264 | 89.20 184 | 69.52 209 | 74.86 235 | 84.35 273 | 61.76 161 | 92.56 195 | 71.50 165 | 72.89 312 | 90.28 186 |
|
GA-MVS | | | 76.87 224 | 75.17 233 | 81.97 195 | 82.75 290 | 62.58 241 | 81.44 283 | 86.35 249 | 72.16 162 | 74.74 236 | 82.89 292 | 46.20 303 | 92.02 217 | 68.85 192 | 81.09 214 | 91.30 152 |
|
sss | | | 73.60 259 | 73.64 249 | 73.51 314 | 82.80 289 | 55.01 326 | 76.12 324 | 81.69 306 | 62.47 299 | 74.68 237 | 85.85 249 | 57.32 208 | 78.11 347 | 60.86 259 | 80.93 215 | 87.39 271 |
|
BH-w/o | | | 78.21 194 | 77.33 196 | 80.84 222 | 88.81 162 | 65.13 193 | 84.87 227 | 87.85 224 | 69.75 205 | 74.52 238 | 84.74 270 | 61.34 171 | 93.11 179 | 58.24 282 | 85.84 165 | 84.27 320 |
|
FMVSNet1 | | | 77.44 213 | 76.12 220 | 81.40 206 | 86.81 221 | 63.01 236 | 88.39 127 | 89.28 178 | 70.49 191 | 74.39 239 | 87.28 206 | 49.06 285 | 91.11 242 | 60.91 258 | 78.52 241 | 90.09 195 |
|
cl____ | | | 77.72 208 | 76.76 208 | 80.58 227 | 82.49 297 | 60.48 268 | 83.09 265 | 87.87 222 | 69.22 215 | 74.38 240 | 85.22 262 | 62.10 158 | 91.53 232 | 71.09 167 | 75.41 284 | 89.73 215 |
|
DIV-MVS_self_test | | | 77.72 208 | 76.76 208 | 80.58 227 | 82.48 298 | 60.48 268 | 83.09 265 | 87.86 223 | 69.22 215 | 74.38 240 | 85.24 261 | 62.10 158 | 91.53 232 | 71.09 167 | 75.40 285 | 89.74 214 |
|
114514_t | | | 80.68 137 | 79.51 141 | 84.20 120 | 94.09 41 | 67.27 152 | 89.64 89 | 91.11 132 | 58.75 328 | 74.08 242 | 90.72 121 | 58.10 199 | 95.04 94 | 69.70 182 | 89.42 119 | 90.30 185 |
|
WR-MVS_H | | | 78.51 187 | 78.49 163 | 78.56 263 | 88.02 189 | 56.38 316 | 88.43 123 | 92.67 67 | 77.14 57 | 73.89 243 | 87.55 200 | 66.25 107 | 89.24 275 | 58.92 274 | 73.55 306 | 90.06 199 |
|
tpm2 | | | 73.26 264 | 71.46 266 | 78.63 261 | 83.34 273 | 56.71 310 | 80.65 289 | 80.40 319 | 56.63 341 | 73.55 244 | 82.02 305 | 51.80 255 | 91.24 240 | 56.35 297 | 78.42 244 | 87.95 257 |
|
CP-MVSNet | | | 78.22 193 | 78.34 169 | 77.84 273 | 87.83 194 | 54.54 329 | 87.94 145 | 91.17 130 | 77.65 40 | 73.48 245 | 88.49 176 | 62.24 156 | 88.43 288 | 62.19 245 | 74.07 299 | 90.55 176 |
|
pm-mvs1 | | | 77.25 218 | 76.68 212 | 78.93 258 | 84.22 257 | 58.62 283 | 86.41 190 | 88.36 212 | 71.37 175 | 73.31 246 | 88.01 192 | 61.22 175 | 89.15 277 | 64.24 230 | 73.01 311 | 89.03 231 |
|
PS-CasMVS | | | 78.01 202 | 78.09 174 | 77.77 275 | 87.71 199 | 54.39 331 | 88.02 141 | 91.22 127 | 77.50 48 | 73.26 247 | 88.64 171 | 60.73 181 | 88.41 289 | 61.88 249 | 73.88 303 | 90.53 177 |
|
CVMVSNet | | | 72.99 268 | 72.58 257 | 74.25 310 | 84.28 255 | 50.85 352 | 86.41 190 | 83.45 286 | 44.56 358 | 73.23 248 | 87.54 201 | 49.38 280 | 85.70 309 | 65.90 218 | 78.44 243 | 86.19 297 |
|
PEN-MVS | | | 77.73 207 | 77.69 188 | 77.84 273 | 87.07 217 | 53.91 334 | 87.91 147 | 91.18 129 | 77.56 45 | 73.14 249 | 88.82 167 | 61.23 174 | 89.17 276 | 59.95 264 | 72.37 314 | 90.43 180 |
|
1112_ss | | | 77.40 215 | 76.43 216 | 80.32 233 | 89.11 155 | 60.41 270 | 83.65 255 | 87.72 226 | 62.13 302 | 73.05 250 | 86.72 222 | 62.58 149 | 89.97 263 | 62.11 248 | 80.80 218 | 90.59 175 |
|
tpm | | | 72.37 274 | 71.71 265 | 74.35 309 | 82.19 302 | 52.00 344 | 79.22 304 | 77.29 338 | 64.56 274 | 72.95 251 | 83.68 285 | 51.35 258 | 83.26 328 | 58.33 281 | 75.80 275 | 87.81 262 |
|
cascas | | | 76.72 226 | 74.64 236 | 82.99 167 | 85.78 233 | 65.88 177 | 82.33 273 | 89.21 183 | 60.85 310 | 72.74 252 | 81.02 311 | 47.28 295 | 93.75 149 | 67.48 203 | 85.02 168 | 89.34 222 |
|
CR-MVSNet | | | 73.37 261 | 71.27 270 | 79.67 247 | 81.32 316 | 65.19 191 | 75.92 326 | 80.30 320 | 59.92 317 | 72.73 253 | 81.19 308 | 52.50 240 | 86.69 302 | 59.84 265 | 77.71 248 | 87.11 282 |
|
RPMNet | | | 73.51 260 | 70.49 276 | 82.58 184 | 81.32 316 | 65.19 191 | 75.92 326 | 92.27 83 | 57.60 335 | 72.73 253 | 76.45 345 | 52.30 243 | 95.43 74 | 48.14 335 | 77.71 248 | 87.11 282 |
|
DTE-MVSNet | | | 76.99 221 | 76.80 206 | 77.54 280 | 86.24 227 | 53.06 342 | 87.52 156 | 90.66 140 | 77.08 60 | 72.50 255 | 88.67 170 | 60.48 187 | 89.52 270 | 57.33 290 | 70.74 325 | 90.05 200 |
|
Test_1112_low_res | | | 76.40 232 | 75.44 226 | 79.27 253 | 89.28 145 | 58.09 287 | 81.69 279 | 87.07 238 | 59.53 321 | 72.48 256 | 86.67 228 | 61.30 172 | 89.33 273 | 60.81 260 | 80.15 227 | 90.41 181 |
|
v7n | | | 78.97 178 | 77.58 191 | 83.14 159 | 83.45 271 | 65.51 184 | 88.32 131 | 91.21 128 | 73.69 136 | 72.41 257 | 86.32 241 | 57.93 200 | 93.81 144 | 69.18 187 | 75.65 277 | 90.11 193 |
|
SCA | | | 74.22 253 | 72.33 260 | 79.91 240 | 84.05 261 | 62.17 247 | 79.96 297 | 79.29 328 | 66.30 254 | 72.38 258 | 80.13 320 | 51.95 251 | 88.60 286 | 59.25 270 | 77.67 250 | 88.96 236 |
|
CNLPA | | | 78.08 198 | 76.79 207 | 81.97 195 | 90.40 109 | 71.07 69 | 87.59 155 | 84.55 267 | 66.03 258 | 72.38 258 | 89.64 144 | 57.56 205 | 86.04 307 | 59.61 267 | 83.35 189 | 88.79 243 |
|
NR-MVSNet | | | 80.23 147 | 79.38 145 | 82.78 179 | 87.80 195 | 63.34 229 | 86.31 193 | 91.09 133 | 79.01 29 | 72.17 260 | 89.07 161 | 67.20 98 | 92.81 191 | 66.08 217 | 75.65 277 | 92.20 127 |
|
OpenMVS |  | 72.83 10 | 79.77 155 | 78.33 170 | 84.09 124 | 85.17 242 | 69.91 94 | 90.57 63 | 90.97 134 | 66.70 247 | 72.17 260 | 91.91 89 | 54.70 225 | 93.96 133 | 61.81 251 | 90.95 100 | 88.41 253 |
|
MVS | | | 78.19 196 | 76.99 202 | 81.78 197 | 85.66 234 | 66.99 155 | 84.66 231 | 90.47 145 | 55.08 347 | 72.02 262 | 85.27 260 | 63.83 130 | 94.11 131 | 66.10 216 | 89.80 115 | 84.24 321 |
|
XVG-ACMP-BASELINE | | | 76.11 236 | 74.27 243 | 81.62 200 | 83.20 277 | 64.67 200 | 83.60 258 | 89.75 167 | 69.75 205 | 71.85 263 | 87.09 215 | 32.78 356 | 92.11 214 | 69.99 179 | 80.43 224 | 88.09 256 |
|
PatchmatchNet |  | | 73.12 266 | 71.33 269 | 78.49 266 | 83.18 278 | 60.85 262 | 79.63 299 | 78.57 330 | 64.13 279 | 71.73 264 | 79.81 325 | 51.20 260 | 85.97 308 | 57.40 289 | 76.36 271 | 88.66 246 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
tpmrst | | | 72.39 272 | 72.13 261 | 73.18 318 | 80.54 324 | 49.91 355 | 79.91 298 | 79.08 329 | 63.11 289 | 71.69 265 | 79.95 322 | 55.32 218 | 82.77 330 | 65.66 221 | 73.89 302 | 86.87 285 |
|
TransMVSNet (Re) | | | 75.39 246 | 74.56 238 | 77.86 272 | 85.50 238 | 57.10 304 | 86.78 179 | 86.09 253 | 72.17 161 | 71.53 266 | 87.34 205 | 63.01 144 | 89.31 274 | 56.84 294 | 61.83 348 | 87.17 278 |
|
Fast-Effi-MVS+-dtu | | | 78.02 201 | 76.49 214 | 82.62 183 | 83.16 280 | 66.96 159 | 86.94 172 | 87.45 232 | 72.45 154 | 71.49 267 | 84.17 275 | 54.79 224 | 91.58 230 | 67.61 201 | 80.31 225 | 89.30 223 |
|
PAPM | | | 77.68 210 | 76.40 217 | 81.51 203 | 87.29 213 | 61.85 251 | 83.78 253 | 89.59 171 | 64.74 272 | 71.23 268 | 88.70 168 | 62.59 148 | 93.66 153 | 52.66 310 | 87.03 147 | 89.01 232 |
|
tfpnnormal | | | 74.39 250 | 73.16 253 | 78.08 270 | 86.10 229 | 58.05 288 | 84.65 234 | 87.53 229 | 70.32 193 | 71.22 269 | 85.63 253 | 54.97 220 | 89.86 264 | 43.03 352 | 75.02 292 | 86.32 294 |
|
RPSCF | | | 73.23 265 | 71.46 266 | 78.54 264 | 82.50 296 | 59.85 273 | 82.18 274 | 82.84 296 | 58.96 325 | 71.15 270 | 89.41 156 | 45.48 310 | 84.77 317 | 58.82 276 | 71.83 319 | 91.02 161 |
|
DWT-MVSNet_test | | | 73.70 258 | 71.86 263 | 79.21 255 | 82.91 287 | 58.94 279 | 82.34 272 | 82.17 300 | 65.21 265 | 71.05 271 | 78.31 334 | 44.21 315 | 90.17 261 | 63.29 237 | 77.28 252 | 88.53 250 |
|
PatchT | | | 68.46 302 | 67.85 296 | 70.29 330 | 80.70 322 | 43.93 365 | 72.47 339 | 74.88 346 | 60.15 315 | 70.55 272 | 76.57 344 | 49.94 274 | 81.59 333 | 50.58 317 | 74.83 294 | 85.34 308 |
|
CL-MVSNet_self_test | | | 72.37 274 | 71.46 266 | 75.09 302 | 79.49 338 | 53.53 336 | 80.76 287 | 85.01 263 | 69.12 219 | 70.51 273 | 82.05 304 | 57.92 201 | 84.13 320 | 52.27 311 | 66.00 340 | 87.60 266 |
|
IterMVS-SCA-FT | | | 75.43 244 | 73.87 247 | 80.11 237 | 82.69 292 | 64.85 197 | 81.57 281 | 83.47 285 | 69.16 218 | 70.49 274 | 84.15 276 | 51.95 251 | 88.15 291 | 69.23 186 | 72.14 317 | 87.34 273 |
|
miper_lstm_enhance | | | 74.11 254 | 73.11 254 | 77.13 286 | 80.11 328 | 59.62 275 | 72.23 340 | 86.92 241 | 66.76 246 | 70.40 275 | 82.92 291 | 56.93 213 | 82.92 329 | 69.06 189 | 72.63 313 | 88.87 239 |
|
gg-mvs-nofinetune | | | 69.95 291 | 67.96 294 | 75.94 293 | 83.07 281 | 54.51 330 | 77.23 321 | 70.29 356 | 63.11 289 | 70.32 276 | 62.33 359 | 43.62 318 | 88.69 285 | 53.88 305 | 87.76 135 | 84.62 319 |
|
DP-MVS | | | 76.78 225 | 74.57 237 | 83.42 146 | 93.29 54 | 69.46 107 | 88.55 122 | 83.70 279 | 63.98 284 | 70.20 277 | 88.89 165 | 54.01 232 | 94.80 107 | 46.66 340 | 81.88 208 | 86.01 302 |
|
pmmvs6 | | | 74.69 249 | 73.39 250 | 78.61 262 | 81.38 313 | 57.48 300 | 86.64 183 | 87.95 220 | 64.99 271 | 70.18 278 | 86.61 230 | 50.43 269 | 89.52 270 | 62.12 247 | 70.18 327 | 88.83 241 |
|
PVSNet | | 64.34 18 | 72.08 276 | 70.87 275 | 75.69 295 | 86.21 228 | 56.44 314 | 74.37 336 | 80.73 313 | 62.06 303 | 70.17 279 | 82.23 302 | 42.86 322 | 83.31 327 | 54.77 302 | 84.45 176 | 87.32 274 |
|
1314 | | | 76.53 227 | 75.30 232 | 80.21 235 | 83.93 263 | 62.32 245 | 84.66 231 | 88.81 198 | 60.23 314 | 70.16 280 | 84.07 277 | 55.30 219 | 90.73 254 | 67.37 204 | 83.21 191 | 87.59 268 |
|
Patchmtry | | | 70.74 282 | 69.16 284 | 75.49 299 | 80.72 321 | 54.07 333 | 74.94 335 | 80.30 320 | 58.34 329 | 70.01 281 | 81.19 308 | 52.50 240 | 86.54 303 | 53.37 307 | 71.09 324 | 85.87 305 |
|
EPMVS | | | 69.02 296 | 68.16 291 | 71.59 322 | 79.61 336 | 49.80 357 | 77.40 320 | 66.93 364 | 62.82 295 | 70.01 281 | 79.05 327 | 45.79 306 | 77.86 349 | 56.58 295 | 75.26 290 | 87.13 281 |
|
IterMVS | | | 74.29 251 | 72.94 255 | 78.35 267 | 81.53 310 | 63.49 225 | 81.58 280 | 82.49 298 | 68.06 237 | 69.99 283 | 83.69 284 | 51.66 257 | 85.54 310 | 65.85 219 | 71.64 320 | 86.01 302 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
test-LLR | | | 72.94 269 | 72.43 258 | 74.48 307 | 81.35 314 | 58.04 289 | 78.38 311 | 77.46 335 | 66.66 248 | 69.95 284 | 79.00 329 | 48.06 290 | 79.24 341 | 66.13 214 | 84.83 170 | 86.15 298 |
|
test-mter | | | 71.41 278 | 70.39 279 | 74.48 307 | 81.35 314 | 58.04 289 | 78.38 311 | 77.46 335 | 60.32 313 | 69.95 284 | 79.00 329 | 36.08 350 | 79.24 341 | 66.13 214 | 84.83 170 | 86.15 298 |
|
pmmvs4 | | | 74.03 256 | 71.91 262 | 80.39 230 | 81.96 304 | 68.32 131 | 81.45 282 | 82.14 301 | 59.32 322 | 69.87 286 | 85.13 264 | 52.40 242 | 88.13 292 | 60.21 263 | 74.74 295 | 84.73 317 |
|
PLC |  | 70.83 11 | 78.05 200 | 76.37 218 | 83.08 162 | 91.88 85 | 67.80 141 | 88.19 137 | 89.46 174 | 64.33 278 | 69.87 286 | 88.38 179 | 53.66 234 | 93.58 154 | 58.86 275 | 82.73 198 | 87.86 261 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
LTVRE_ROB | | 69.57 13 | 76.25 234 | 74.54 239 | 81.41 205 | 88.60 171 | 64.38 208 | 79.24 303 | 89.12 189 | 70.76 186 | 69.79 288 | 87.86 193 | 49.09 284 | 93.20 172 | 56.21 298 | 80.16 226 | 86.65 291 |
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 |
LS3D | | | 76.95 223 | 74.82 235 | 83.37 149 | 90.45 107 | 67.36 151 | 89.15 100 | 86.94 240 | 61.87 304 | 69.52 289 | 90.61 123 | 51.71 256 | 94.53 113 | 46.38 343 | 86.71 152 | 88.21 255 |
|
IB-MVS | | 68.01 15 | 75.85 239 | 73.36 251 | 83.31 150 | 84.76 249 | 66.03 171 | 83.38 261 | 85.06 261 | 70.21 196 | 69.40 290 | 81.05 310 | 45.76 307 | 94.66 111 | 65.10 225 | 75.49 280 | 89.25 224 |
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 |
PatchMatch-RL | | | 72.38 273 | 70.90 273 | 76.80 289 | 88.60 171 | 67.38 150 | 79.53 300 | 76.17 343 | 62.75 296 | 69.36 291 | 82.00 306 | 45.51 309 | 84.89 316 | 53.62 306 | 80.58 221 | 78.12 353 |
|
MDTV_nov1_ep13 | | | | 69.97 281 | | 83.18 278 | 53.48 337 | 77.10 322 | 80.18 323 | 60.45 311 | 69.33 292 | 80.44 317 | 48.89 288 | 86.90 301 | 51.60 314 | 78.51 242 | |
|
D2MVS | | | 74.82 248 | 73.21 252 | 79.64 248 | 79.81 332 | 62.56 242 | 80.34 293 | 87.35 233 | 64.37 277 | 68.86 293 | 82.66 296 | 46.37 300 | 90.10 262 | 67.91 199 | 81.24 213 | 86.25 295 |
|
PMMVS | | | 69.34 294 | 68.67 286 | 71.35 326 | 75.67 352 | 62.03 248 | 75.17 330 | 73.46 351 | 50.00 356 | 68.68 294 | 79.05 327 | 52.07 249 | 78.13 346 | 61.16 257 | 82.77 197 | 73.90 357 |
|
Patchmatch-RL test | | | 70.24 288 | 67.78 299 | 77.61 278 | 77.43 346 | 59.57 277 | 71.16 342 | 70.33 355 | 62.94 293 | 68.65 295 | 72.77 353 | 50.62 266 | 85.49 311 | 69.58 184 | 66.58 338 | 87.77 263 |
|
MS-PatchMatch | | | 73.83 257 | 72.67 256 | 77.30 283 | 83.87 264 | 66.02 172 | 81.82 276 | 84.66 265 | 61.37 308 | 68.61 296 | 82.82 294 | 47.29 294 | 88.21 290 | 59.27 269 | 84.32 177 | 77.68 354 |
|
tpm cat1 | | | 70.57 284 | 68.31 289 | 77.35 282 | 82.41 299 | 57.95 292 | 78.08 315 | 80.22 322 | 52.04 353 | 68.54 297 | 77.66 340 | 52.00 250 | 87.84 295 | 51.77 312 | 72.07 318 | 86.25 295 |
|
TESTMET0.1,1 | | | 69.89 292 | 69.00 285 | 72.55 319 | 79.27 341 | 56.85 306 | 78.38 311 | 74.71 349 | 57.64 334 | 68.09 298 | 77.19 342 | 37.75 345 | 76.70 352 | 63.92 231 | 84.09 179 | 84.10 324 |
|
MIMVSNet | | | 70.69 283 | 69.30 282 | 74.88 304 | 84.52 252 | 56.35 317 | 75.87 328 | 79.42 327 | 64.59 273 | 67.76 299 | 82.41 298 | 41.10 332 | 81.54 334 | 46.64 342 | 81.34 211 | 86.75 289 |
|
ACMH+ | | 68.96 14 | 76.01 237 | 74.01 244 | 82.03 193 | 88.60 171 | 65.31 190 | 88.86 108 | 87.55 228 | 70.25 195 | 67.75 300 | 87.47 203 | 41.27 331 | 93.19 174 | 58.37 280 | 75.94 274 | 87.60 266 |
|
LCM-MVSNet-Re | | | 77.05 220 | 76.94 203 | 77.36 281 | 87.20 214 | 51.60 347 | 80.06 295 | 80.46 318 | 75.20 102 | 67.69 301 | 86.72 222 | 62.48 150 | 88.98 280 | 63.44 234 | 89.25 120 | 91.51 144 |
|
ITE_SJBPF | | | | | 78.22 268 | 81.77 306 | 60.57 266 | | 83.30 287 | 69.25 214 | 67.54 302 | 87.20 211 | 36.33 349 | 87.28 300 | 54.34 303 | 74.62 296 | 86.80 287 |
|
pmmvs5 | | | 71.55 277 | 70.20 280 | 75.61 296 | 77.83 344 | 56.39 315 | 81.74 278 | 80.89 310 | 57.76 333 | 67.46 303 | 84.49 271 | 49.26 283 | 85.32 313 | 57.08 292 | 75.29 289 | 85.11 313 |
|
MVP-Stereo | | | 76.12 235 | 74.46 241 | 81.13 216 | 85.37 240 | 69.79 97 | 84.42 242 | 87.95 220 | 65.03 269 | 67.46 303 | 85.33 259 | 53.28 237 | 91.73 228 | 58.01 284 | 83.27 190 | 81.85 340 |
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
test_0402 | | | 72.79 270 | 70.44 277 | 79.84 242 | 88.13 184 | 65.99 173 | 85.93 203 | 84.29 271 | 65.57 263 | 67.40 305 | 85.49 256 | 46.92 297 | 92.61 193 | 35.88 361 | 74.38 298 | 80.94 345 |
|
GG-mvs-BLEND | | | | | 75.38 300 | 81.59 309 | 55.80 322 | 79.32 302 | 69.63 358 | | 67.19 306 | 73.67 352 | 43.24 319 | 88.90 284 | 50.41 318 | 84.50 174 | 81.45 342 |
|
tpmvs | | | 71.09 280 | 69.29 283 | 76.49 290 | 82.04 303 | 56.04 320 | 78.92 308 | 81.37 309 | 64.05 282 | 67.18 307 | 78.28 335 | 49.74 277 | 89.77 265 | 49.67 326 | 72.37 314 | 83.67 326 |
|
OurMVSNet-221017-0 | | | 74.26 252 | 72.42 259 | 79.80 243 | 83.76 266 | 59.59 276 | 85.92 204 | 86.64 243 | 66.39 253 | 66.96 308 | 87.58 198 | 39.46 337 | 91.60 229 | 65.76 220 | 69.27 329 | 88.22 254 |
|
baseline2 | | | 75.70 240 | 73.83 248 | 81.30 210 | 83.26 275 | 61.79 253 | 82.57 271 | 80.65 314 | 66.81 244 | 66.88 309 | 83.42 287 | 57.86 202 | 92.19 211 | 63.47 233 | 79.57 231 | 89.91 206 |
|
MVS_0304 | | | 72.48 271 | 70.89 274 | 77.24 284 | 82.20 301 | 59.68 274 | 84.11 249 | 83.49 284 | 67.10 243 | 66.87 310 | 80.59 316 | 35.00 353 | 87.40 298 | 59.07 273 | 79.58 230 | 84.63 318 |
|
F-COLMAP | | | 76.38 233 | 74.33 242 | 82.50 185 | 89.28 145 | 66.95 160 | 88.41 126 | 89.03 190 | 64.05 282 | 66.83 311 | 88.61 172 | 46.78 298 | 92.89 187 | 57.48 287 | 78.55 240 | 87.67 264 |
|
ACMH | | 67.68 16 | 75.89 238 | 73.93 245 | 81.77 198 | 88.71 168 | 66.61 162 | 88.62 119 | 89.01 192 | 69.81 202 | 66.78 312 | 86.70 227 | 41.95 330 | 91.51 234 | 55.64 299 | 78.14 246 | 87.17 278 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
test0.0.03 1 | | | 68.00 303 | 67.69 300 | 68.90 335 | 77.55 345 | 47.43 359 | 75.70 329 | 72.95 353 | 66.66 248 | 66.56 313 | 82.29 301 | 48.06 290 | 75.87 356 | 44.97 349 | 74.51 297 | 83.41 328 |
|
MDTV_nov1_ep13_2view | | | | | | | 37.79 370 | 75.16 331 | | 55.10 346 | 66.53 314 | | 49.34 281 | | 53.98 304 | | 87.94 259 |
|
KD-MVS_2432*1600 | | | 66.22 314 | 63.89 315 | 73.21 315 | 75.47 355 | 53.42 338 | 70.76 345 | 84.35 269 | 64.10 280 | 66.52 315 | 78.52 332 | 34.55 354 | 84.98 314 | 50.40 319 | 50.33 363 | 81.23 343 |
|
miper_refine_blended | | | 66.22 314 | 63.89 315 | 73.21 315 | 75.47 355 | 53.42 338 | 70.76 345 | 84.35 269 | 64.10 280 | 66.52 315 | 78.52 332 | 34.55 354 | 84.98 314 | 50.40 319 | 50.33 363 | 81.23 343 |
|
ET-MVSNet_ETH3D | | | 78.63 184 | 76.63 213 | 84.64 105 | 86.73 223 | 69.47 105 | 85.01 224 | 84.61 266 | 69.54 208 | 66.51 317 | 86.59 231 | 50.16 271 | 91.75 226 | 76.26 124 | 84.24 178 | 92.69 110 |
|
EU-MVSNet | | | 68.53 301 | 67.61 301 | 71.31 327 | 78.51 343 | 47.01 361 | 84.47 237 | 84.27 272 | 42.27 359 | 66.44 318 | 84.79 269 | 40.44 335 | 83.76 322 | 58.76 277 | 68.54 334 | 83.17 330 |
|
EPNet_dtu | | | 75.46 243 | 74.86 234 | 77.23 285 | 82.57 295 | 54.60 328 | 86.89 174 | 83.09 293 | 71.64 167 | 66.25 319 | 85.86 248 | 55.99 216 | 88.04 293 | 54.92 301 | 86.55 154 | 89.05 230 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
Anonymous20231206 | | | 68.60 299 | 67.80 298 | 71.02 328 | 80.23 327 | 50.75 353 | 78.30 314 | 80.47 317 | 56.79 340 | 66.11 320 | 82.63 297 | 46.35 301 | 78.95 343 | 43.62 351 | 75.70 276 | 83.36 329 |
|
SixPastTwentyTwo | | | 73.37 261 | 71.26 271 | 79.70 245 | 85.08 247 | 57.89 293 | 85.57 210 | 83.56 282 | 71.03 180 | 65.66 321 | 85.88 247 | 42.10 328 | 92.57 194 | 59.11 272 | 63.34 346 | 88.65 247 |
|
MSDG | | | 73.36 263 | 70.99 272 | 80.49 229 | 84.51 253 | 65.80 179 | 80.71 288 | 86.13 252 | 65.70 261 | 65.46 322 | 83.74 283 | 44.60 312 | 90.91 250 | 51.13 316 | 76.89 259 | 84.74 316 |
|
OpenMVS_ROB |  | 64.09 19 | 70.56 285 | 68.19 290 | 77.65 277 | 80.26 326 | 59.41 278 | 85.01 224 | 82.96 295 | 58.76 327 | 65.43 323 | 82.33 299 | 37.63 346 | 91.23 241 | 45.34 348 | 76.03 273 | 82.32 337 |
|
ppachtmachnet_test | | | 70.04 290 | 67.34 303 | 78.14 269 | 79.80 333 | 61.13 258 | 79.19 305 | 80.59 315 | 59.16 324 | 65.27 324 | 79.29 326 | 46.75 299 | 87.29 299 | 49.33 327 | 66.72 336 | 86.00 304 |
|
ADS-MVSNet2 | | | 66.20 316 | 63.33 318 | 74.82 305 | 79.92 330 | 58.75 282 | 67.55 355 | 75.19 345 | 53.37 350 | 65.25 325 | 75.86 346 | 42.32 325 | 80.53 339 | 41.57 355 | 68.91 331 | 85.18 310 |
|
ADS-MVSNet | | | 64.36 320 | 62.88 322 | 68.78 337 | 79.92 330 | 47.17 360 | 67.55 355 | 71.18 354 | 53.37 350 | 65.25 325 | 75.86 346 | 42.32 325 | 73.99 363 | 41.57 355 | 68.91 331 | 85.18 310 |
|
testgi | | | 66.67 310 | 66.53 308 | 67.08 341 | 75.62 353 | 41.69 368 | 75.93 325 | 76.50 342 | 66.11 255 | 65.20 327 | 86.59 231 | 35.72 351 | 74.71 360 | 43.71 350 | 73.38 309 | 84.84 315 |
|
PM-MVS | | | 66.41 312 | 64.14 314 | 73.20 317 | 73.92 359 | 56.45 313 | 78.97 307 | 64.96 368 | 63.88 286 | 64.72 328 | 80.24 319 | 19.84 368 | 83.44 326 | 66.24 213 | 64.52 344 | 79.71 350 |
|
JIA-IIPM | | | 66.32 313 | 62.82 323 | 76.82 288 | 77.09 348 | 61.72 254 | 65.34 358 | 75.38 344 | 58.04 332 | 64.51 329 | 62.32 360 | 42.05 329 | 86.51 304 | 51.45 315 | 69.22 330 | 82.21 338 |
|
ambc | | | | | 75.24 301 | 73.16 363 | 50.51 354 | 63.05 362 | 87.47 231 | | 64.28 330 | 77.81 339 | 17.80 369 | 89.73 267 | 57.88 285 | 60.64 351 | 85.49 306 |
|
EG-PatchMatch MVS | | | 74.04 255 | 71.82 264 | 80.71 225 | 84.92 248 | 67.42 148 | 85.86 206 | 88.08 217 | 66.04 257 | 64.22 331 | 83.85 279 | 35.10 352 | 92.56 195 | 57.44 288 | 80.83 217 | 82.16 339 |
|
dp | | | 66.80 308 | 65.43 310 | 70.90 329 | 79.74 335 | 48.82 358 | 75.12 333 | 74.77 347 | 59.61 319 | 64.08 332 | 77.23 341 | 42.89 321 | 80.72 338 | 48.86 329 | 66.58 338 | 83.16 331 |
|
KD-MVS_self_test | | | 68.81 297 | 67.59 302 | 72.46 320 | 74.29 358 | 45.45 362 | 77.93 317 | 87.00 239 | 63.12 288 | 63.99 333 | 78.99 331 | 42.32 325 | 84.77 317 | 56.55 296 | 64.09 345 | 87.16 280 |
|
pmmvs-eth3d | | | 70.50 286 | 67.83 297 | 78.52 265 | 77.37 347 | 66.18 170 | 81.82 276 | 81.51 307 | 58.90 326 | 63.90 334 | 80.42 318 | 42.69 323 | 86.28 306 | 58.56 278 | 65.30 342 | 83.11 332 |
|
COLMAP_ROB |  | 66.92 17 | 73.01 267 | 70.41 278 | 80.81 223 | 87.13 216 | 65.63 182 | 88.30 132 | 84.19 274 | 62.96 292 | 63.80 335 | 87.69 196 | 38.04 344 | 92.56 195 | 46.66 340 | 74.91 293 | 84.24 321 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
FMVSNet5 | | | 69.50 293 | 67.96 294 | 74.15 311 | 82.97 286 | 55.35 325 | 80.01 296 | 82.12 302 | 62.56 298 | 63.02 336 | 81.53 307 | 36.92 347 | 81.92 332 | 48.42 330 | 74.06 300 | 85.17 312 |
|
test20.03 | | | 67.45 305 | 66.95 306 | 68.94 334 | 75.48 354 | 44.84 364 | 77.50 319 | 77.67 334 | 66.66 248 | 63.01 337 | 83.80 281 | 47.02 296 | 78.40 345 | 42.53 354 | 68.86 333 | 83.58 327 |
|
K. test v3 | | | 71.19 279 | 68.51 287 | 79.21 255 | 83.04 283 | 57.78 296 | 84.35 244 | 76.91 341 | 72.90 153 | 62.99 338 | 82.86 293 | 39.27 338 | 91.09 247 | 61.65 252 | 52.66 360 | 88.75 244 |
|
our_test_3 | | | 69.14 295 | 67.00 305 | 75.57 297 | 79.80 333 | 58.80 281 | 77.96 316 | 77.81 333 | 59.55 320 | 62.90 339 | 78.25 336 | 47.43 293 | 83.97 321 | 51.71 313 | 67.58 335 | 83.93 325 |
|
CHOSEN 280x420 | | | 66.51 311 | 64.71 312 | 71.90 321 | 81.45 311 | 63.52 224 | 57.98 363 | 68.95 362 | 53.57 349 | 62.59 340 | 76.70 343 | 46.22 302 | 75.29 359 | 55.25 300 | 79.68 229 | 76.88 356 |
|
Anonymous20240521 | | | 68.80 298 | 67.22 304 | 73.55 313 | 74.33 357 | 54.11 332 | 83.18 263 | 85.61 256 | 58.15 330 | 61.68 341 | 80.94 313 | 30.71 360 | 81.27 336 | 57.00 293 | 73.34 310 | 85.28 309 |
|
USDC | | | 70.33 287 | 68.37 288 | 76.21 292 | 80.60 323 | 56.23 318 | 79.19 305 | 86.49 245 | 60.89 309 | 61.29 342 | 85.47 257 | 31.78 359 | 89.47 272 | 53.37 307 | 76.21 272 | 82.94 336 |
|
lessismore_v0 | | | | | 78.97 257 | 81.01 320 | 57.15 303 | | 65.99 365 | | 61.16 343 | 82.82 294 | 39.12 339 | 91.34 238 | 59.67 266 | 46.92 365 | 88.43 252 |
|
UnsupCasMVSNet_eth | | | 67.33 306 | 65.99 309 | 71.37 324 | 73.48 361 | 51.47 349 | 75.16 331 | 85.19 260 | 65.20 266 | 60.78 344 | 80.93 315 | 42.35 324 | 77.20 351 | 57.12 291 | 53.69 359 | 85.44 307 |
|
AllTest | | | 70.96 281 | 68.09 293 | 79.58 249 | 85.15 243 | 63.62 219 | 84.58 236 | 79.83 324 | 62.31 300 | 60.32 345 | 86.73 220 | 32.02 357 | 88.96 282 | 50.28 321 | 71.57 321 | 86.15 298 |
|
TestCases | | | | | 79.58 249 | 85.15 243 | 63.62 219 | | 79.83 324 | 62.31 300 | 60.32 345 | 86.73 220 | 32.02 357 | 88.96 282 | 50.28 321 | 71.57 321 | 86.15 298 |
|
Patchmatch-test | | | 64.82 319 | 63.24 319 | 69.57 332 | 79.42 339 | 49.82 356 | 63.49 361 | 69.05 361 | 51.98 354 | 59.95 347 | 80.13 320 | 50.91 262 | 70.98 365 | 40.66 357 | 73.57 305 | 87.90 260 |
|
MIMVSNet1 | | | 68.58 300 | 66.78 307 | 73.98 312 | 80.07 329 | 51.82 345 | 80.77 286 | 84.37 268 | 64.40 276 | 59.75 348 | 82.16 303 | 36.47 348 | 83.63 324 | 42.73 353 | 70.33 326 | 86.48 293 |
|
LF4IMVS | | | 64.02 321 | 62.19 324 | 69.50 333 | 70.90 366 | 53.29 341 | 76.13 323 | 77.18 339 | 52.65 352 | 58.59 349 | 80.98 312 | 23.55 365 | 76.52 353 | 53.06 309 | 66.66 337 | 78.68 352 |
|
PVSNet_0 | | 57.27 20 | 61.67 324 | 59.27 327 | 68.85 336 | 79.61 336 | 57.44 301 | 68.01 354 | 73.44 352 | 55.93 344 | 58.54 350 | 70.41 356 | 44.58 313 | 77.55 350 | 47.01 339 | 35.91 366 | 71.55 359 |
|
TDRefinement | | | 67.49 304 | 64.34 313 | 76.92 287 | 73.47 362 | 61.07 259 | 84.86 228 | 82.98 294 | 59.77 318 | 58.30 351 | 85.13 264 | 26.06 362 | 87.89 294 | 47.92 337 | 60.59 352 | 81.81 341 |
|
UnsupCasMVSNet_bld | | | 63.70 322 | 61.53 326 | 70.21 331 | 73.69 360 | 51.39 350 | 72.82 338 | 81.89 303 | 55.63 345 | 57.81 352 | 71.80 355 | 38.67 340 | 78.61 344 | 49.26 328 | 52.21 361 | 80.63 346 |
|
DSMNet-mixed | | | 57.77 327 | 56.90 329 | 60.38 345 | 67.70 368 | 35.61 371 | 69.18 350 | 53.97 373 | 32.30 368 | 57.49 353 | 79.88 323 | 40.39 336 | 68.57 367 | 38.78 359 | 72.37 314 | 76.97 355 |
|
N_pmnet | | | 52.79 330 | 53.26 331 | 51.40 350 | 78.99 342 | 7.68 381 | 69.52 348 | 3.89 381 | 51.63 355 | 57.01 354 | 74.98 350 | 40.83 334 | 65.96 368 | 37.78 360 | 64.67 343 | 80.56 348 |
|
new-patchmatchnet | | | 61.73 323 | 61.73 325 | 61.70 344 | 72.74 365 | 24.50 378 | 69.16 351 | 78.03 332 | 61.40 306 | 56.72 355 | 75.53 349 | 38.42 341 | 76.48 354 | 45.95 345 | 57.67 354 | 84.13 323 |
|
CMPMVS |  | 51.72 21 | 70.19 289 | 68.16 291 | 76.28 291 | 73.15 364 | 57.55 299 | 79.47 301 | 83.92 276 | 48.02 357 | 56.48 356 | 84.81 268 | 43.13 320 | 86.42 305 | 62.67 242 | 81.81 209 | 84.89 314 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
TinyColmap | | | 67.30 307 | 64.81 311 | 74.76 306 | 81.92 305 | 56.68 311 | 80.29 294 | 81.49 308 | 60.33 312 | 56.27 357 | 83.22 289 | 24.77 363 | 87.66 297 | 45.52 346 | 69.47 328 | 79.95 349 |
|
YYNet1 | | | 65.03 317 | 62.91 321 | 71.38 323 | 75.85 351 | 56.60 312 | 69.12 352 | 74.66 350 | 57.28 338 | 54.12 358 | 77.87 338 | 45.85 305 | 74.48 361 | 49.95 324 | 61.52 350 | 83.05 333 |
|
MDA-MVSNet_test_wron | | | 65.03 317 | 62.92 320 | 71.37 324 | 75.93 350 | 56.73 308 | 69.09 353 | 74.73 348 | 57.28 338 | 54.03 359 | 77.89 337 | 45.88 304 | 74.39 362 | 49.89 325 | 61.55 349 | 82.99 335 |
|
pmmvs3 | | | 57.79 326 | 54.26 330 | 68.37 338 | 64.02 370 | 56.72 309 | 75.12 333 | 65.17 366 | 40.20 361 | 52.93 360 | 69.86 357 | 20.36 367 | 75.48 358 | 45.45 347 | 55.25 358 | 72.90 358 |
|
MVS-HIRNet | | | 59.14 325 | 57.67 328 | 63.57 343 | 81.65 307 | 43.50 366 | 71.73 341 | 65.06 367 | 39.59 363 | 51.43 361 | 57.73 363 | 38.34 342 | 82.58 331 | 39.53 358 | 73.95 301 | 64.62 362 |
|
MDA-MVSNet-bldmvs | | | 66.68 309 | 63.66 317 | 75.75 294 | 79.28 340 | 60.56 267 | 73.92 337 | 78.35 331 | 64.43 275 | 50.13 362 | 79.87 324 | 44.02 317 | 83.67 323 | 46.10 344 | 56.86 355 | 83.03 334 |
|
new_pmnet | | | 50.91 332 | 50.29 333 | 52.78 349 | 68.58 367 | 34.94 373 | 63.71 360 | 56.63 372 | 39.73 362 | 44.95 363 | 65.47 358 | 21.93 366 | 58.48 369 | 34.98 362 | 56.62 356 | 64.92 361 |
|
FPMVS | | | 53.68 329 | 51.64 332 | 59.81 346 | 65.08 369 | 51.03 351 | 69.48 349 | 69.58 359 | 41.46 360 | 40.67 364 | 72.32 354 | 16.46 371 | 70.00 366 | 24.24 368 | 65.42 341 | 58.40 365 |
|
LCM-MVSNet | | | 54.25 328 | 49.68 334 | 67.97 339 | 53.73 373 | 45.28 363 | 66.85 357 | 80.78 312 | 35.96 365 | 39.45 365 | 62.23 361 | 8.70 377 | 78.06 348 | 48.24 334 | 51.20 362 | 80.57 347 |
|
PMMVS2 | | | 40.82 336 | 38.86 339 | 46.69 351 | 53.84 372 | 16.45 379 | 48.61 366 | 49.92 374 | 37.49 364 | 31.67 366 | 60.97 362 | 8.14 378 | 56.42 370 | 28.42 365 | 30.72 368 | 67.19 360 |
|
ANet_high | | | 50.57 333 | 46.10 336 | 63.99 342 | 48.67 376 | 39.13 369 | 70.99 344 | 80.85 311 | 61.39 307 | 31.18 367 | 57.70 364 | 17.02 370 | 73.65 364 | 31.22 363 | 15.89 373 | 79.18 351 |
|
Gipuma |  | | 45.18 334 | 41.86 337 | 55.16 348 | 77.03 349 | 51.52 348 | 32.50 369 | 80.52 316 | 32.46 367 | 27.12 368 | 35.02 369 | 9.52 376 | 75.50 357 | 22.31 369 | 60.21 353 | 38.45 368 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
PMVS |  | 37.38 22 | 44.16 335 | 40.28 338 | 55.82 347 | 40.82 378 | 42.54 367 | 65.12 359 | 63.99 369 | 34.43 366 | 24.48 369 | 57.12 365 | 3.92 379 | 76.17 355 | 17.10 371 | 55.52 357 | 48.75 366 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
DeepMVS_CX |  | | | | 27.40 356 | 40.17 379 | 26.90 376 | | 24.59 380 | 17.44 372 | 23.95 370 | 48.61 367 | 9.77 375 | 26.48 375 | 18.06 370 | 24.47 369 | 28.83 369 |
|
tmp_tt | | | 18.61 342 | 21.40 345 | 10.23 358 | 4.82 381 | 10.11 380 | 34.70 368 | 30.74 379 | 1.48 375 | 23.91 371 | 26.07 372 | 28.42 361 | 13.41 377 | 27.12 366 | 15.35 374 | 7.17 372 |
|
test_method | | | 31.52 338 | 29.28 342 | 38.23 353 | 27.03 380 | 6.50 382 | 20.94 371 | 62.21 371 | 4.05 374 | 22.35 372 | 52.50 366 | 13.33 372 | 47.58 373 | 27.04 367 | 34.04 367 | 60.62 363 |
|
MVE |  | 26.22 23 | 30.37 340 | 25.89 344 | 43.81 352 | 44.55 377 | 35.46 372 | 28.87 370 | 39.07 377 | 18.20 371 | 18.58 373 | 40.18 368 | 2.68 380 | 47.37 374 | 17.07 372 | 23.78 370 | 48.60 367 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
E-PMN | | | 31.77 337 | 30.64 340 | 35.15 354 | 52.87 374 | 27.67 375 | 57.09 364 | 47.86 375 | 24.64 369 | 16.40 374 | 33.05 370 | 11.23 374 | 54.90 371 | 14.46 373 | 18.15 371 | 22.87 370 |
|
EMVS | | | 30.81 339 | 29.65 341 | 34.27 355 | 50.96 375 | 25.95 377 | 56.58 365 | 46.80 376 | 24.01 370 | 15.53 375 | 30.68 371 | 12.47 373 | 54.43 372 | 12.81 374 | 17.05 372 | 22.43 371 |
|
wuyk23d | | | 16.82 343 | 15.94 346 | 19.46 357 | 58.74 371 | 31.45 374 | 39.22 367 | 3.74 382 | 6.84 373 | 6.04 376 | 2.70 376 | 1.27 381 | 24.29 376 | 10.54 375 | 14.40 375 | 2.63 373 |
|
EGC-MVSNET | | | 52.07 331 | 47.05 335 | 67.14 340 | 83.51 270 | 60.71 264 | 80.50 291 | 67.75 363 | 0.07 376 | 0.43 377 | 75.85 348 | 24.26 364 | 81.54 334 | 28.82 364 | 62.25 347 | 59.16 364 |
|
testmvs | | | 6.04 346 | 8.02 349 | 0.10 360 | 0.08 382 | 0.03 384 | 69.74 347 | 0.04 383 | 0.05 377 | 0.31 378 | 1.68 377 | 0.02 383 | 0.04 378 | 0.24 376 | 0.02 376 | 0.25 375 |
|
test123 | | | 6.12 345 | 8.11 348 | 0.14 359 | 0.06 383 | 0.09 383 | 71.05 343 | 0.03 384 | 0.04 378 | 0.25 379 | 1.30 378 | 0.05 382 | 0.03 379 | 0.21 377 | 0.01 377 | 0.29 374 |
|
test_blank | | | 0.00 348 | 0.00 351 | 0.00 361 | 0.00 384 | 0.00 385 | 0.00 372 | 0.00 385 | 0.00 379 | 0.00 380 | 0.00 379 | 0.00 384 | 0.00 380 | 0.00 378 | 0.00 378 | 0.00 376 |
|
uanet_test | | | 0.00 348 | 0.00 351 | 0.00 361 | 0.00 384 | 0.00 385 | 0.00 372 | 0.00 385 | 0.00 379 | 0.00 380 | 0.00 379 | 0.00 384 | 0.00 380 | 0.00 378 | 0.00 378 | 0.00 376 |
|
DCPMVS | | | 0.00 348 | 0.00 351 | 0.00 361 | 0.00 384 | 0.00 385 | 0.00 372 | 0.00 385 | 0.00 379 | 0.00 380 | 0.00 379 | 0.00 384 | 0.00 380 | 0.00 378 | 0.00 378 | 0.00 376 |
|
cdsmvs_eth3d_5k | | | 19.96 341 | 26.61 343 | 0.00 361 | 0.00 384 | 0.00 385 | 0.00 372 | 89.26 181 | 0.00 379 | 0.00 380 | 88.61 172 | 61.62 164 | 0.00 380 | 0.00 378 | 0.00 378 | 0.00 376 |
|
pcd_1.5k_mvsjas | | | 5.26 347 | 7.02 350 | 0.00 361 | 0.00 384 | 0.00 385 | 0.00 372 | 0.00 385 | 0.00 379 | 0.00 380 | 0.00 379 | 63.15 140 | 0.00 380 | 0.00 378 | 0.00 378 | 0.00 376 |
|
sosnet-low-res | | | 0.00 348 | 0.00 351 | 0.00 361 | 0.00 384 | 0.00 385 | 0.00 372 | 0.00 385 | 0.00 379 | 0.00 380 | 0.00 379 | 0.00 384 | 0.00 380 | 0.00 378 | 0.00 378 | 0.00 376 |
|
sosnet | | | 0.00 348 | 0.00 351 | 0.00 361 | 0.00 384 | 0.00 385 | 0.00 372 | 0.00 385 | 0.00 379 | 0.00 380 | 0.00 379 | 0.00 384 | 0.00 380 | 0.00 378 | 0.00 378 | 0.00 376 |
|
uncertanet | | | 0.00 348 | 0.00 351 | 0.00 361 | 0.00 384 | 0.00 385 | 0.00 372 | 0.00 385 | 0.00 379 | 0.00 380 | 0.00 379 | 0.00 384 | 0.00 380 | 0.00 378 | 0.00 378 | 0.00 376 |
|
Regformer | | | 0.00 348 | 0.00 351 | 0.00 361 | 0.00 384 | 0.00 385 | 0.00 372 | 0.00 385 | 0.00 379 | 0.00 380 | 0.00 379 | 0.00 384 | 0.00 380 | 0.00 378 | 0.00 378 | 0.00 376 |
|
ab-mvs-re | | | 7.23 344 | 9.64 347 | 0.00 361 | 0.00 384 | 0.00 385 | 0.00 372 | 0.00 385 | 0.00 379 | 0.00 380 | 86.72 222 | 0.00 384 | 0.00 380 | 0.00 378 | 0.00 378 | 0.00 376 |
|
uanet | | | 0.00 348 | 0.00 351 | 0.00 361 | 0.00 384 | 0.00 385 | 0.00 372 | 0.00 385 | 0.00 379 | 0.00 380 | 0.00 379 | 0.00 384 | 0.00 380 | 0.00 378 | 0.00 378 | 0.00 376 |
|
MSC_two_6792asdad | | | | | 89.16 1 | 94.34 29 | 75.53 2 | | 92.99 49 | | | | | 97.53 1 | 89.67 1 | 96.44 9 | 94.41 32 |
|
No_MVS | | | | | 89.16 1 | 94.34 29 | 75.53 2 | | 92.99 49 | | | | | 97.53 1 | 89.67 1 | 96.44 9 | 94.41 32 |
|
eth-test2 | | | | | | 0.00 384 | | | | | | | | | | | |
|
eth-test | | | | | | 0.00 384 | | | | | | | | | | | |
|
OPU-MVS | | | | | 89.06 3 | 94.62 15 | 75.42 4 | 93.57 7 | | | | 94.02 47 | 82.45 3 | 96.87 19 | 83.77 55 | 96.48 8 | 94.88 12 |
|
save fliter | | | | | | 93.80 44 | 72.35 45 | 90.47 67 | 91.17 130 | 74.31 122 | | | | | | | |
|
test_0728_SECOND | | | | | 87.71 34 | 95.34 1 | 71.43 62 | 93.49 9 | 94.23 5 | | | | | 97.49 3 | 89.08 7 | 96.41 12 | 94.21 42 |
|
GSMVS | | | | | | | | | | | | | | | | | 88.96 236 |
|
sam_mvs1 | | | | | | | | | | | | | 51.32 259 | | | | 88.96 236 |
|
sam_mvs | | | | | | | | | | | | | 50.01 272 | | | | |
|
MTGPA |  | | | | | | | | 92.02 94 | | | | | | | | |
|
test_post1 | | | | | | | | 78.90 309 | | | | 5.43 375 | 48.81 289 | 85.44 312 | 59.25 270 | | |
|
test_post | | | | | | | | | | | | 5.46 374 | 50.36 270 | 84.24 319 | | | |
|
patchmatchnet-post | | | | | | | | | | | | 74.00 351 | 51.12 261 | 88.60 286 | | | |
|
MTMP | | | | | | | | 92.18 34 | 32.83 378 | | | | | | | | |
|
gm-plane-assit | | | | | | 81.40 312 | 53.83 335 | | | 62.72 297 | | 80.94 313 | | 92.39 201 | 63.40 235 | | |
|
test9_res | | | | | | | | | | | | | | | 84.90 33 | 95.70 31 | 92.87 105 |
|
agg_prior2 | | | | | | | | | | | | | | | 82.91 66 | 95.45 33 | 92.70 108 |
|
test_prior4 | | | | | | | 72.60 35 | 89.01 103 | | | | | | | | | |
|
test_prior | | | | | 86.33 63 | 92.61 74 | 69.59 101 | | 92.97 54 | | | | | 95.48 70 | | | 93.91 55 |
|
新几何2 | | | | | | | | 86.29 195 | | | | | | | | | |
|
旧先验1 | | | | | | 91.96 82 | 65.79 180 | | 86.37 248 | | | 93.08 69 | 69.31 81 | | | 92.74 76 | 88.74 245 |
|
无先验 | | | | | | | | 87.48 157 | 88.98 193 | 60.00 316 | | | | 94.12 129 | 67.28 205 | | 88.97 235 |
|
原ACMM2 | | | | | | | | 86.86 175 | | | | | | | | | |
|
testdata2 | | | | | | | | | | | | | | 91.01 249 | 62.37 244 | | |
|
segment_acmp | | | | | | | | | | | | | 73.08 45 | | | | |
|
testdata1 | | | | | | | | 84.14 248 | | 75.71 90 | | | | | | | |
|
plane_prior7 | | | | | | 90.08 115 | 68.51 129 | | | | | | | | | | |
|
plane_prior6 | | | | | | 89.84 124 | 68.70 124 | | | | | | 60.42 188 | | | | |
|
plane_prior5 | | | | | | | | | 92.44 75 | | | | | 95.38 79 | 78.71 99 | 86.32 157 | 91.33 150 |
|
plane_prior4 | | | | | | | | | | | | 91.00 117 | | | | | |
|
plane_prior2 | | | | | | | | 91.25 50 | | 79.12 26 | | | | | | | |
|
plane_prior1 | | | | | | 89.90 123 | | | | | | | | | | | |
|
plane_prior | | | | | | | 68.71 122 | 90.38 71 | | 77.62 41 | | | | | | 86.16 160 | |
|
n2 | | | | | | | | | 0.00 385 | | | | | | | | |
|
nn | | | | | | | | | 0.00 385 | | | | | | | | |
|
door-mid | | | | | | | | | 69.98 357 | | | | | | | | |
|
test11 | | | | | | | | | 92.23 86 | | | | | | | | |
|
door | | | | | | | | | 69.44 360 | | | | | | | | |
|
HQP5-MVS | | | | | | | 66.98 156 | | | | | | | | | | |
|
BP-MVS | | | | | | | | | | | | | | | 77.47 113 | | |
|
HQP3-MVS | | | | | | | | | 92.19 89 | | | | | | | 85.99 163 | |
|
HQP2-MVS | | | | | | | | | | | | | 60.17 191 | | | | |
|
NP-MVS | | | | | | 89.62 126 | 68.32 131 | | | | | 90.24 128 | | | | | |
|
ACMMP++_ref | | | | | | | | | | | | | | | | 81.95 207 | |
|
ACMMP++ | | | | | | | | | | | | | | | | 81.25 212 | |
|
Test By Simon | | | | | | | | | | | | | 64.33 125 | | | | |
|