patch_mono-2 | | | 98.36 48 | 98.87 3 | 96.82 206 | 99.53 39 | 90.68 311 | 98.64 147 | 99.29 8 | 97.88 5 | 99.19 29 | 99.52 3 | 96.80 15 | 99.97 1 | 99.11 1 | 99.86 1 | 99.82 10 |
|
dcpmvs_2 | | | 98.08 61 | 98.59 10 | 96.56 230 | 99.57 35 | 90.34 317 | 99.15 41 | 98.38 196 | 96.82 64 | 99.29 20 | 99.49 7 | 95.78 49 | 99.57 139 | 98.94 2 | 99.86 1 | 99.77 23 |
|
test_0728_THIRD | | | | | | | | | | 97.32 33 | 99.45 11 | 99.46 13 | 97.88 1 | 99.94 4 | 98.47 22 | 99.86 1 | 99.85 4 |
|
CP-MVS | | | 98.57 27 | 98.36 27 | 99.19 46 | 99.66 28 | 97.86 73 | 99.34 16 | 98.87 58 | 95.96 97 | 98.60 75 | 99.13 73 | 96.05 36 | 99.94 4 | 97.77 59 | 99.86 1 | 99.77 23 |
|
CHOSEN 280x420 | | | 97.18 111 | 97.18 94 | 97.20 180 | 98.81 138 | 93.27 266 | 95.78 344 | 99.15 19 | 95.25 132 | 96.79 167 | 98.11 191 | 92.29 122 | 99.07 198 | 98.56 13 | 99.85 5 | 99.25 136 |
|
SD-MVS | | | 98.64 15 | 98.68 7 | 98.53 94 | 99.33 69 | 98.36 47 | 98.90 88 | 98.85 68 | 97.28 36 | 99.72 3 | 99.39 18 | 96.63 19 | 97.60 332 | 98.17 36 | 99.85 5 | 99.64 76 |
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 |
APDe-MVS | | | 99.02 4 | 98.84 4 | 99.55 9 | 99.57 35 | 98.96 16 | 99.39 10 | 98.93 39 | 97.38 30 | 99.41 13 | 99.54 1 | 96.66 17 | 99.84 57 | 98.86 4 | 99.85 5 | 99.87 1 |
|
HPM-MVS_fast | | | 98.38 46 | 98.13 51 | 99.12 60 | 99.75 4 | 97.86 73 | 99.44 9 | 98.82 74 | 94.46 171 | 98.94 45 | 99.20 59 | 95.16 76 | 99.74 111 | 97.58 74 | 99.85 5 | 99.77 23 |
|
SteuartSystems-ACMMP | | | 98.90 6 | 98.75 6 | 99.36 24 | 99.22 98 | 98.43 38 | 99.10 52 | 98.87 58 | 97.38 30 | 99.35 17 | 99.40 17 | 97.78 5 | 99.87 48 | 97.77 59 | 99.85 5 | 99.78 16 |
Skip Steuart: Steuart Systems R&D Blog. |
DPE-MVS |  | | 98.92 5 | 98.67 8 | 99.65 2 | 99.58 34 | 99.20 9 | 98.42 181 | 98.91 45 | 97.58 15 | 99.54 8 | 99.46 13 | 97.10 12 | 99.94 4 | 97.64 70 | 99.84 10 | 99.83 7 |
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025 |
HPM-MVS |  | | 98.36 48 | 98.10 54 | 99.13 57 | 99.74 8 | 97.82 77 | 99.53 6 | 98.80 91 | 94.63 164 | 98.61 74 | 98.97 97 | 95.13 77 | 99.77 105 | 97.65 69 | 99.83 11 | 99.79 13 |
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023 |
SED-MVS | | | 99.09 1 | 98.91 1 | 99.63 4 | 99.71 21 | 99.24 5 | 99.02 67 | 98.87 58 | 97.65 10 | 99.73 1 | 99.48 8 | 97.53 7 | 99.94 4 | 98.43 26 | 99.81 12 | 99.70 54 |
|
IU-MVS | | | | | | 99.71 21 | 99.23 7 | | 98.64 141 | 95.28 130 | 99.63 4 | | | | 98.35 32 | 99.81 12 | 99.83 7 |
|
ZNCC-MVS | | | 98.49 37 | 98.20 49 | 99.35 25 | 99.73 12 | 98.39 39 | 99.19 37 | 98.86 64 | 95.77 103 | 98.31 92 | 99.10 78 | 95.46 57 | 99.93 19 | 97.57 77 | 99.81 12 | 99.74 37 |
|
DVP-MVS |  | | 99.03 3 | 98.83 5 | 99.63 4 | 99.72 13 | 99.25 2 | 98.97 77 | 98.58 153 | 97.62 12 | 99.45 11 | 99.46 13 | 97.42 9 | 99.94 4 | 98.47 22 | 99.81 12 | 99.69 57 |
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_SECOND | | | | | 99.71 1 | 99.72 13 | 99.35 1 | 98.97 77 | 98.88 51 | | | | | 99.94 4 | 98.47 22 | 99.81 12 | 99.84 6 |
|
SMA-MVS |  | | 98.58 24 | 98.25 43 | 99.56 8 | 99.51 43 | 99.04 15 | 98.95 81 | 98.80 91 | 93.67 209 | 99.37 16 | 99.52 3 | 96.52 21 | 99.89 39 | 98.06 41 | 99.81 12 | 99.76 30 |
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 |
mPP-MVS | | | 98.51 36 | 98.26 42 | 99.25 42 | 99.75 4 | 98.04 65 | 99.28 22 | 98.81 80 | 96.24 86 | 98.35 89 | 99.23 52 | 95.46 57 | 99.94 4 | 97.42 84 | 99.81 12 | 99.77 23 |
|
MSC_two_6792asdad | | | | | 99.62 6 | 99.17 103 | 99.08 11 | | 98.63 143 | | | | | 99.94 4 | 98.53 14 | 99.80 19 | 99.86 2 |
|
No_MVS | | | | | 99.62 6 | 99.17 103 | 99.08 11 | | 98.63 143 | | | | | 99.94 4 | 98.53 14 | 99.80 19 | 99.86 2 |
|
test_241102_TWO | | | | | | | | | 98.87 58 | 97.65 10 | 99.53 9 | 99.48 8 | 97.34 11 | 99.94 4 | 98.43 26 | 99.80 19 | 99.83 7 |
|
MP-MVS-pluss | | | 98.31 56 | 97.92 63 | 99.49 12 | 99.72 13 | 98.88 18 | 98.43 179 | 98.78 99 | 94.10 179 | 97.69 129 | 99.42 16 | 95.25 72 | 99.92 25 | 98.09 40 | 99.80 19 | 99.67 67 |
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
zzz-MVS | | | 98.55 31 | 98.25 43 | 99.46 15 | 99.76 2 | 98.64 27 | 98.55 163 | 98.74 108 | 97.27 40 | 98.02 104 | 99.39 18 | 94.81 84 | 99.96 2 | 97.91 48 | 99.79 23 | 99.77 23 |
|
MTAPA | | | 98.58 24 | 98.29 40 | 99.46 15 | 99.76 2 | 98.64 27 | 98.90 88 | 98.74 108 | 97.27 40 | 98.02 104 | 99.39 18 | 94.81 84 | 99.96 2 | 97.91 48 | 99.79 23 | 99.77 23 |
|
region2R | | | 98.61 18 | 98.38 25 | 99.29 34 | 99.74 8 | 98.16 60 | 99.23 27 | 98.93 39 | 96.15 89 | 98.94 45 | 99.17 63 | 95.91 43 | 99.94 4 | 97.55 78 | 99.79 23 | 99.78 16 |
|
ACMMPR | | | 98.59 21 | 98.36 27 | 99.29 34 | 99.74 8 | 98.15 61 | 99.23 27 | 98.95 35 | 96.10 94 | 98.93 49 | 99.19 62 | 95.70 50 | 99.94 4 | 97.62 71 | 99.79 23 | 99.78 16 |
|
HFP-MVS | | | 98.63 17 | 98.40 23 | 99.32 31 | 99.72 13 | 98.29 51 | 99.23 27 | 98.96 33 | 96.10 94 | 98.94 45 | 99.17 63 | 96.06 34 | 99.92 25 | 97.62 71 | 99.78 27 | 99.75 32 |
|
#test# | | | 98.54 33 | 98.27 41 | 99.32 31 | 99.72 13 | 98.29 51 | 98.98 76 | 98.96 33 | 95.65 110 | 98.94 45 | 99.17 63 | 96.06 34 | 99.92 25 | 97.21 91 | 99.78 27 | 99.75 32 |
|
MP-MVS |  | | 98.33 54 | 98.01 58 | 99.28 38 | 99.75 4 | 98.18 58 | 99.22 31 | 98.79 96 | 96.13 91 | 97.92 117 | 99.23 52 | 94.54 90 | 99.94 4 | 96.74 122 | 99.78 27 | 99.73 42 |
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo. |
PGM-MVS | | | 98.49 37 | 98.23 47 | 99.27 41 | 99.72 13 | 98.08 64 | 98.99 73 | 99.49 5 | 95.43 120 | 99.03 39 | 99.32 37 | 95.56 53 | 99.94 4 | 96.80 117 | 99.77 30 | 99.78 16 |
|
APD-MVS |  | | 98.35 50 | 98.00 59 | 99.42 18 | 99.51 43 | 98.72 21 | 98.80 114 | 98.82 74 | 94.52 168 | 99.23 24 | 99.25 50 | 95.54 55 | 99.80 84 | 96.52 128 | 99.77 30 | 99.74 37 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
114514_t | | | 96.93 120 | 96.27 133 | 98.92 72 | 99.50 45 | 97.63 83 | 98.85 100 | 98.90 46 | 84.80 353 | 97.77 122 | 99.11 76 | 92.84 114 | 99.66 127 | 94.85 180 | 99.77 30 | 99.47 107 |
|
CPTT-MVS | | | 97.72 77 | 97.32 89 | 98.92 72 | 99.64 30 | 97.10 105 | 99.12 48 | 98.81 80 | 92.34 258 | 98.09 97 | 99.08 86 | 93.01 113 | 99.92 25 | 96.06 143 | 99.77 30 | 99.75 32 |
|
DeepPCF-MVS | | 96.37 2 | 97.93 69 | 98.48 22 | 96.30 254 | 99.00 121 | 89.54 327 | 97.43 278 | 98.87 58 | 98.16 2 | 99.26 22 | 99.38 25 | 96.12 32 | 99.64 130 | 98.30 34 | 99.77 30 | 99.72 46 |
|
DeepC-MVS_fast | | 96.70 1 | 98.55 31 | 98.34 33 | 99.18 50 | 99.25 90 | 98.04 65 | 98.50 170 | 98.78 99 | 97.72 7 | 98.92 51 | 99.28 44 | 95.27 70 | 99.82 68 | 97.55 78 | 99.77 30 | 99.69 57 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
Regformer-3 | | | 98.59 21 | 98.50 17 | 98.86 76 | 99.43 61 | 97.05 106 | 98.40 183 | 98.68 125 | 97.43 26 | 99.06 37 | 99.31 39 | 95.80 47 | 99.77 105 | 98.62 10 | 99.76 36 | 99.78 16 |
|
Regformer-4 | | | 98.64 15 | 98.53 14 | 98.99 66 | 99.43 61 | 97.37 92 | 98.40 183 | 98.79 96 | 97.46 23 | 99.09 36 | 99.31 39 | 95.86 46 | 99.80 84 | 98.64 8 | 99.76 36 | 99.79 13 |
|
DELS-MVS | | | 98.40 45 | 98.20 49 | 98.99 66 | 99.00 121 | 97.66 81 | 97.75 260 | 98.89 48 | 97.71 9 | 98.33 90 | 98.97 97 | 94.97 81 | 99.88 47 | 98.42 28 | 99.76 36 | 99.42 117 |
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 |
MVS_111021_HR | | | 98.47 40 | 98.34 33 | 98.88 75 | 99.22 98 | 97.32 93 | 97.91 244 | 99.58 3 | 97.20 44 | 98.33 90 | 99.00 95 | 95.99 39 | 99.64 130 | 98.05 43 | 99.76 36 | 99.69 57 |
|
PHI-MVS | | | 98.34 52 | 98.06 55 | 99.18 50 | 99.15 109 | 98.12 63 | 99.04 60 | 99.09 21 | 93.32 222 | 98.83 57 | 99.10 78 | 96.54 20 | 99.83 60 | 97.70 67 | 99.76 36 | 99.59 87 |
|
DeepC-MVS | | 95.98 3 | 97.88 70 | 97.58 72 | 98.77 78 | 99.25 90 | 96.93 111 | 98.83 104 | 98.75 106 | 96.96 58 | 96.89 161 | 99.50 5 | 90.46 166 | 99.87 48 | 97.84 56 | 99.76 36 | 99.52 94 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
ACMMP_NAP | | | 98.61 18 | 98.30 39 | 99.55 9 | 99.62 32 | 98.95 17 | 98.82 107 | 98.81 80 | 95.80 102 | 99.16 32 | 99.47 10 | 95.37 63 | 99.92 25 | 97.89 51 | 99.75 42 | 99.79 13 |
|
MVS_111021_LR | | | 98.34 52 | 98.23 47 | 98.67 83 | 99.27 87 | 96.90 113 | 97.95 240 | 99.58 3 | 97.14 49 | 98.44 83 | 99.01 94 | 95.03 80 | 99.62 135 | 97.91 48 | 99.75 42 | 99.50 100 |
|
3Dnovator | | 94.51 5 | 97.46 92 | 96.93 105 | 99.07 63 | 97.78 214 | 97.64 82 | 99.35 15 | 99.06 23 | 97.02 55 | 93.75 260 | 99.16 68 | 89.25 187 | 99.92 25 | 97.22 90 | 99.75 42 | 99.64 76 |
|
XVS | | | 98.70 10 | 98.49 20 | 99.34 26 | 99.70 24 | 98.35 48 | 99.29 20 | 98.88 51 | 97.40 27 | 98.46 79 | 99.20 59 | 95.90 44 | 99.89 39 | 97.85 54 | 99.74 45 | 99.78 16 |
|
X-MVStestdata | | | 94.06 273 | 92.30 293 | 99.34 26 | 99.70 24 | 98.35 48 | 99.29 20 | 98.88 51 | 97.40 27 | 98.46 79 | 43.50 373 | 95.90 44 | 99.89 39 | 97.85 54 | 99.74 45 | 99.78 16 |
|
OPU-MVS | | | | | 99.37 23 | 99.24 96 | 99.05 14 | 99.02 67 | | | | 99.16 68 | 97.81 3 | 99.37 165 | 97.24 89 | 99.73 47 | 99.70 54 |
|
xxxxxxxxxxxxxcwj | | | 98.70 10 | 98.50 17 | 99.30 33 | 99.46 55 | 98.38 40 | 98.21 208 | 98.52 164 | 97.95 3 | 99.32 18 | 99.39 18 | 96.22 24 | 99.84 57 | 97.72 62 | 99.73 47 | 99.67 67 |
|
SF-MVS | | | 98.59 21 | 98.32 38 | 99.41 19 | 99.54 38 | 98.71 22 | 99.04 60 | 98.81 80 | 95.12 139 | 99.32 18 | 99.39 18 | 96.22 24 | 99.84 57 | 97.72 62 | 99.73 47 | 99.67 67 |
|
ETH3D-3000-0.1 | | | 98.35 50 | 98.00 59 | 99.38 20 | 99.47 52 | 98.68 25 | 98.67 142 | 98.84 69 | 94.66 163 | 99.11 34 | 99.25 50 | 95.46 57 | 99.81 75 | 96.80 117 | 99.73 47 | 99.63 79 |
|
TSAR-MVS + MP. | | | 98.78 7 | 98.62 9 | 99.24 43 | 99.69 26 | 98.28 53 | 99.14 43 | 98.66 136 | 96.84 62 | 99.56 6 | 99.31 39 | 96.34 23 | 99.70 119 | 98.32 33 | 99.73 47 | 99.73 42 |
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition |
Regformer-1 | | | 98.66 13 | 98.51 16 | 99.12 60 | 99.35 64 | 97.81 79 | 98.37 185 | 98.76 103 | 97.49 19 | 99.20 26 | 99.21 55 | 96.08 33 | 99.79 96 | 98.42 28 | 99.73 47 | 99.75 32 |
|
Regformer-2 | | | 98.69 12 | 98.52 15 | 99.19 46 | 99.35 64 | 98.01 67 | 98.37 185 | 98.81 80 | 97.48 20 | 99.21 25 | 99.21 55 | 96.13 31 | 99.80 84 | 98.40 30 | 99.73 47 | 99.75 32 |
|
DVP-MVS++ | | | 99.08 2 | 98.89 2 | 99.64 3 | 99.17 103 | 99.23 7 | 99.69 1 | 98.88 51 | 97.32 33 | 99.53 9 | 99.47 10 | 97.81 3 | 99.94 4 | 98.47 22 | 99.72 54 | 99.74 37 |
|
PC_three_1452 | | | | | | | | | | 95.08 144 | 99.60 5 | 99.16 68 | 97.86 2 | 98.47 265 | 97.52 81 | 99.72 54 | 99.74 37 |
|
9.14 | | | | 98.06 55 | | 99.47 52 | | 98.71 132 | 98.82 74 | 94.36 173 | 99.16 32 | 99.29 43 | 96.05 36 | 99.81 75 | 97.00 96 | 99.71 56 | |
|
MSLP-MVS++ | | | 98.56 29 | 98.57 11 | 98.55 90 | 99.26 89 | 96.80 116 | 98.71 132 | 99.05 25 | 97.28 36 | 98.84 55 | 99.28 44 | 96.47 22 | 99.40 163 | 98.52 20 | 99.70 57 | 99.47 107 |
|
ETH3 D test6400 | | | 97.59 86 | 97.01 101 | 99.34 26 | 99.40 63 | 98.56 30 | 98.20 211 | 98.81 80 | 91.63 281 | 98.44 83 | 98.85 115 | 93.98 104 | 99.82 68 | 94.11 208 | 99.69 58 | 99.64 76 |
|
CDPH-MVS | | | 97.94 68 | 97.49 80 | 99.28 38 | 99.47 52 | 98.44 36 | 97.91 244 | 98.67 133 | 92.57 250 | 98.77 60 | 98.85 115 | 95.93 42 | 99.72 113 | 95.56 163 | 99.69 58 | 99.68 63 |
|
HPM-MVS++ |  | | 98.58 24 | 98.25 43 | 99.55 9 | 99.50 45 | 99.08 11 | 98.72 131 | 98.66 136 | 97.51 18 | 98.15 93 | 98.83 119 | 95.70 50 | 99.92 25 | 97.53 80 | 99.67 60 | 99.66 71 |
|
APD-MVS_3200maxsize | | | 98.53 35 | 98.33 37 | 99.15 56 | 99.50 45 | 97.92 72 | 99.15 41 | 98.81 80 | 96.24 86 | 99.20 26 | 99.37 26 | 95.30 68 | 99.80 84 | 97.73 61 | 99.67 60 | 99.72 46 |
|
abl_6 | | | 98.30 57 | 98.03 57 | 99.13 57 | 99.56 37 | 97.76 80 | 99.13 46 | 98.82 74 | 96.14 90 | 99.26 22 | 99.37 26 | 93.33 109 | 99.93 19 | 96.96 100 | 99.67 60 | 99.69 57 |
|
CNVR-MVS | | | 98.78 7 | 98.56 12 | 99.45 17 | 99.32 72 | 98.87 19 | 98.47 173 | 98.81 80 | 97.72 7 | 98.76 61 | 99.16 68 | 97.05 13 | 99.78 100 | 98.06 41 | 99.66 63 | 99.69 57 |
|
SR-MVS-dyc-post | | | 98.54 33 | 98.35 29 | 99.13 57 | 99.49 49 | 97.86 73 | 99.11 49 | 98.80 91 | 96.49 78 | 99.17 30 | 99.35 32 | 95.34 65 | 99.82 68 | 97.72 62 | 99.65 64 | 99.71 50 |
|
RE-MVS-def | | | | 98.34 33 | | 99.49 49 | 97.86 73 | 99.11 49 | 98.80 91 | 96.49 78 | 99.17 30 | 99.35 32 | 95.29 69 | | 97.72 62 | 99.65 64 | 99.71 50 |
|
CANet | | | 98.05 62 | 97.76 67 | 98.90 74 | 98.73 142 | 97.27 96 | 98.35 188 | 98.78 99 | 97.37 32 | 97.72 127 | 98.96 103 | 91.53 145 | 99.92 25 | 98.79 6 | 99.65 64 | 99.51 98 |
|
EI-MVSNet-Vis-set | | | 98.47 40 | 98.39 24 | 98.69 81 | 99.46 55 | 96.49 131 | 98.30 199 | 98.69 122 | 97.21 43 | 98.84 55 | 99.36 30 | 95.41 60 | 99.78 100 | 98.62 10 | 99.65 64 | 99.80 12 |
|
test1172 | | | 98.56 29 | 98.35 29 | 99.16 53 | 99.53 39 | 97.94 71 | 99.09 53 | 98.83 72 | 96.52 77 | 99.05 38 | 99.34 35 | 95.34 65 | 99.82 68 | 97.86 53 | 99.64 68 | 99.73 42 |
|
CSCG | | | 97.85 72 | 97.74 68 | 98.20 119 | 99.67 27 | 95.16 189 | 99.22 31 | 99.32 7 | 93.04 233 | 97.02 154 | 98.92 109 | 95.36 64 | 99.91 34 | 97.43 83 | 99.64 68 | 99.52 94 |
|
SR-MVS | | | 98.57 27 | 98.35 29 | 99.24 43 | 99.53 39 | 98.18 58 | 99.09 53 | 98.82 74 | 96.58 74 | 99.10 35 | 99.32 37 | 95.39 61 | 99.82 68 | 97.70 67 | 99.63 70 | 99.72 46 |
|
GST-MVS | | | 98.43 42 | 98.12 52 | 99.34 26 | 99.72 13 | 98.38 40 | 99.09 53 | 98.82 74 | 95.71 106 | 98.73 64 | 99.06 88 | 95.27 70 | 99.93 19 | 97.07 95 | 99.63 70 | 99.72 46 |
|
QAPM | | | 96.29 143 | 95.40 163 | 98.96 70 | 97.85 211 | 97.60 85 | 99.23 27 | 98.93 39 | 89.76 323 | 93.11 283 | 99.02 90 | 89.11 192 | 99.93 19 | 91.99 269 | 99.62 72 | 99.34 121 |
|
MCST-MVS | | | 98.65 14 | 98.37 26 | 99.48 13 | 99.60 33 | 98.87 19 | 98.41 182 | 98.68 125 | 97.04 54 | 98.52 78 | 98.80 122 | 96.78 16 | 99.83 60 | 97.93 47 | 99.61 73 | 99.74 37 |
|
test_prior3 | | | 98.22 59 | 97.90 64 | 99.19 46 | 99.31 74 | 98.22 55 | 97.80 256 | 98.84 69 | 96.12 92 | 97.89 119 | 98.69 132 | 95.96 40 | 99.70 119 | 96.89 106 | 99.60 74 | 99.65 73 |
|
test_prior2 | | | | | | | | 97.80 256 | | 96.12 92 | 97.89 119 | 98.69 132 | 95.96 40 | | 96.89 106 | 99.60 74 | |
|
jason | | | 97.32 104 | 97.08 98 | 98.06 131 | 97.45 243 | 95.59 172 | 97.87 250 | 97.91 270 | 94.79 155 | 98.55 77 | 98.83 119 | 91.12 153 | 99.23 175 | 97.58 74 | 99.60 74 | 99.34 121 |
jason: jason. |
MSP-MVS | | | 98.74 9 | 98.55 13 | 99.29 34 | 99.75 4 | 98.23 54 | 99.26 24 | 98.88 51 | 97.52 17 | 99.41 13 | 98.78 124 | 96.00 38 | 99.79 96 | 97.79 58 | 99.59 77 | 99.85 4 |
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 |
MVSFormer | | | 97.57 88 | 97.49 80 | 97.84 141 | 98.07 197 | 95.76 169 | 99.47 7 | 98.40 191 | 94.98 147 | 98.79 58 | 98.83 119 | 92.34 120 | 98.41 278 | 96.91 102 | 99.59 77 | 99.34 121 |
|
lupinMVS | | | 97.44 96 | 97.22 93 | 98.12 127 | 98.07 197 | 95.76 169 | 97.68 264 | 97.76 275 | 94.50 169 | 98.79 58 | 98.61 140 | 92.34 120 | 99.30 169 | 97.58 74 | 99.59 77 | 99.31 127 |
|
ZD-MVS | | | | | | 99.46 55 | 98.70 23 | | 98.79 96 | 93.21 226 | 98.67 67 | 98.97 97 | 95.70 50 | 99.83 60 | 96.07 140 | 99.58 80 | |
|
test9_res | | | | | | | | | | | | | | | 96.39 134 | 99.57 81 | 99.69 57 |
|
train_agg | | | 97.97 63 | 97.52 77 | 99.33 30 | 99.31 74 | 98.50 34 | 97.92 242 | 98.73 112 | 92.98 235 | 97.74 125 | 98.68 134 | 96.20 27 | 99.80 84 | 96.59 124 | 99.57 81 | 99.68 63 |
|
agg_prior2 | | | | | | | | | | | | | | | 95.87 150 | 99.57 81 | 99.68 63 |
|
3Dnovator+ | | 94.38 6 | 97.43 97 | 96.78 112 | 99.38 20 | 97.83 212 | 98.52 32 | 99.37 12 | 98.71 118 | 97.09 53 | 92.99 286 | 99.13 73 | 89.36 184 | 99.89 39 | 96.97 98 | 99.57 81 | 99.71 50 |
|
LS3D | | | 97.16 112 | 96.66 121 | 98.68 82 | 98.53 161 | 97.19 103 | 98.93 85 | 98.90 46 | 92.83 243 | 95.99 195 | 99.37 26 | 92.12 129 | 99.87 48 | 93.67 221 | 99.57 81 | 98.97 170 |
|
CS-MVS-test | | | 98.49 37 | 98.50 17 | 98.46 101 | 99.20 101 | 97.05 106 | 99.64 4 | 98.50 172 | 97.45 25 | 98.88 53 | 99.14 72 | 95.25 72 | 99.15 184 | 98.83 5 | 99.56 86 | 99.20 139 |
|
agg_prior1 | | | 97.95 67 | 97.51 79 | 99.28 38 | 99.30 79 | 98.38 40 | 97.81 255 | 98.72 114 | 93.16 229 | 97.57 138 | 98.66 137 | 96.14 30 | 99.81 75 | 96.63 123 | 99.56 86 | 99.66 71 |
|
test12 | | | | | 99.18 50 | 99.16 107 | 98.19 57 | | 98.53 162 | | 98.07 98 | | 95.13 77 | 99.72 113 | | 99.56 86 | 99.63 79 |
|
CHOSEN 1792x2688 | | | 97.12 114 | 96.80 109 | 98.08 129 | 99.30 79 | 94.56 222 | 98.05 231 | 99.71 1 | 93.57 213 | 97.09 148 | 98.91 110 | 88.17 216 | 99.89 39 | 96.87 112 | 99.56 86 | 99.81 11 |
|
ETH3D cwj APD-0.16 | | | 97.96 64 | 97.52 77 | 99.29 34 | 99.05 114 | 98.52 32 | 98.33 191 | 98.68 125 | 93.18 227 | 98.68 66 | 99.13 73 | 94.62 88 | 99.83 60 | 96.45 130 | 99.55 90 | 99.52 94 |
|
EI-MVSNet-UG-set | | | 98.41 43 | 98.34 33 | 98.61 86 | 99.45 59 | 96.32 140 | 98.28 202 | 98.68 125 | 97.17 46 | 98.74 62 | 99.37 26 | 95.25 72 | 99.79 96 | 98.57 12 | 99.54 91 | 99.73 42 |
|
testtj | | | 98.33 54 | 97.95 61 | 99.47 14 | 99.49 49 | 98.70 23 | 98.83 104 | 98.86 64 | 95.48 117 | 98.91 52 | 99.17 63 | 95.48 56 | 99.93 19 | 95.80 153 | 99.53 92 | 99.76 30 |
|
test222 | | | | | | 99.23 97 | 97.17 104 | 97.40 279 | 98.66 136 | 88.68 334 | 98.05 99 | 98.96 103 | 94.14 100 | | | 99.53 92 | 99.61 82 |
|
MG-MVS | | | 97.81 73 | 97.60 71 | 98.44 103 | 99.12 111 | 95.97 155 | 97.75 260 | 98.78 99 | 96.89 61 | 98.46 79 | 99.22 54 | 93.90 105 | 99.68 125 | 94.81 183 | 99.52 94 | 99.67 67 |
|
DROMVSNet | | | 98.21 60 | 98.11 53 | 98.49 98 | 98.34 175 | 97.26 100 | 99.61 5 | 98.43 186 | 96.78 65 | 98.87 54 | 98.84 117 | 93.72 106 | 99.01 208 | 98.91 3 | 99.50 95 | 99.19 143 |
|
UGNet | | | 96.78 126 | 96.30 132 | 98.19 121 | 98.24 182 | 95.89 165 | 98.88 95 | 98.93 39 | 97.39 29 | 96.81 165 | 97.84 216 | 82.60 304 | 99.90 37 | 96.53 127 | 99.49 96 | 98.79 181 |
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 |
API-MVS | | | 97.41 99 | 97.25 91 | 97.91 138 | 98.70 147 | 96.80 116 | 98.82 107 | 98.69 122 | 94.53 166 | 98.11 95 | 98.28 177 | 94.50 94 | 99.57 139 | 94.12 207 | 99.49 96 | 97.37 233 |
|
CS-MVS | | | 98.41 43 | 98.49 20 | 98.18 122 | 99.08 113 | 96.33 139 | 99.67 3 | 98.49 177 | 97.17 46 | 98.93 49 | 99.10 78 | 95.79 48 | 99.12 188 | 98.67 7 | 99.48 98 | 99.10 157 |
|
新几何1 | | | | | 99.16 53 | 99.34 66 | 98.01 67 | | 98.69 122 | 90.06 318 | 98.13 94 | 98.95 105 | 94.60 89 | 99.89 39 | 91.97 270 | 99.47 99 | 99.59 87 |
|
旧先验1 | | | | | | 99.29 82 | 97.48 88 | | 98.70 121 | | | 99.09 84 | 95.56 53 | | | 99.47 99 | 99.61 82 |
|
OpenMVS |  | 93.04 13 | 95.83 164 | 95.00 186 | 98.32 111 | 97.18 262 | 97.32 93 | 99.21 34 | 98.97 31 | 89.96 319 | 91.14 320 | 99.05 89 | 86.64 248 | 99.92 25 | 93.38 227 | 99.47 99 | 97.73 223 |
|
原ACMM1 | | | | | 98.65 84 | 99.32 72 | 96.62 122 | | 98.67 133 | 93.27 225 | 97.81 121 | 98.97 97 | 95.18 75 | 99.83 60 | 93.84 215 | 99.46 102 | 99.50 100 |
|
1121 | | | 97.37 102 | 96.77 116 | 99.16 53 | 99.34 66 | 97.99 70 | 98.19 215 | 98.68 125 | 90.14 317 | 98.01 108 | 98.97 97 | 94.80 86 | 99.87 48 | 93.36 229 | 99.46 102 | 99.61 82 |
|
testdata | | | | | 98.26 115 | 99.20 101 | 95.36 182 | | 98.68 125 | 91.89 273 | 98.60 75 | 99.10 78 | 94.44 96 | 99.82 68 | 94.27 202 | 99.44 104 | 99.58 91 |
|
DP-MVS Recon | | | 97.86 71 | 97.46 82 | 99.06 64 | 99.53 39 | 98.35 48 | 98.33 191 | 98.89 48 | 92.62 247 | 98.05 99 | 98.94 106 | 95.34 65 | 99.65 128 | 96.04 144 | 99.42 105 | 99.19 143 |
|
NCCC | | | 98.61 18 | 98.35 29 | 99.38 20 | 99.28 86 | 98.61 29 | 98.45 174 | 98.76 103 | 97.82 6 | 98.45 82 | 98.93 107 | 96.65 18 | 99.83 60 | 97.38 86 | 99.41 106 | 99.71 50 |
|
TAPA-MVS | | 93.98 7 | 95.35 190 | 94.56 205 | 97.74 151 | 99.13 110 | 94.83 208 | 98.33 191 | 98.64 141 | 86.62 342 | 96.29 187 | 98.61 140 | 94.00 103 | 99.29 170 | 80.00 357 | 99.41 106 | 99.09 158 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
PVSNet_Blended | | | 97.38 101 | 97.12 95 | 98.14 123 | 99.25 90 | 95.35 184 | 97.28 292 | 99.26 9 | 93.13 230 | 97.94 114 | 98.21 184 | 92.74 116 | 99.81 75 | 96.88 109 | 99.40 108 | 99.27 134 |
|
MS-PatchMatch | | | 93.84 277 | 93.63 265 | 94.46 318 | 96.18 311 | 89.45 328 | 97.76 259 | 98.27 215 | 92.23 264 | 92.13 310 | 97.49 245 | 79.50 325 | 98.69 242 | 89.75 304 | 99.38 109 | 95.25 341 |
|
CANet_DTU | | | 96.96 119 | 96.55 124 | 98.21 118 | 98.17 192 | 96.07 149 | 97.98 238 | 98.21 222 | 97.24 42 | 97.13 147 | 98.93 107 | 86.88 245 | 99.91 34 | 95.00 178 | 99.37 110 | 98.66 191 |
|
DPM-MVS | | | 97.55 90 | 96.99 103 | 99.23 45 | 99.04 116 | 98.55 31 | 97.17 300 | 98.35 200 | 94.85 154 | 97.93 116 | 98.58 145 | 95.07 79 | 99.71 118 | 92.60 250 | 99.34 111 | 99.43 115 |
|
MVP-Stereo | | | 94.28 258 | 93.92 243 | 95.35 289 | 94.95 342 | 92.60 277 | 97.97 239 | 97.65 280 | 91.61 282 | 90.68 325 | 97.09 272 | 86.32 255 | 98.42 271 | 89.70 306 | 99.34 111 | 95.02 348 |
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
CNLPA | | | 97.45 95 | 97.03 100 | 98.73 79 | 99.05 114 | 97.44 91 | 98.07 229 | 98.53 162 | 95.32 128 | 96.80 166 | 98.53 149 | 93.32 110 | 99.72 113 | 94.31 201 | 99.31 113 | 99.02 165 |
|
AdaColmap |  | | 97.15 113 | 96.70 117 | 98.48 99 | 99.16 107 | 96.69 121 | 98.01 235 | 98.89 48 | 94.44 172 | 96.83 162 | 98.68 134 | 90.69 163 | 99.76 107 | 94.36 197 | 99.29 114 | 98.98 169 |
|
Vis-MVSNet |  | | 97.42 98 | 97.11 96 | 98.34 110 | 98.66 151 | 96.23 143 | 99.22 31 | 99.00 28 | 96.63 73 | 98.04 101 | 99.21 55 | 88.05 221 | 99.35 166 | 96.01 146 | 99.21 115 | 99.45 113 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
EIA-MVS | | | 97.75 75 | 97.58 72 | 98.27 113 | 98.38 168 | 96.44 133 | 99.01 69 | 98.60 146 | 95.88 99 | 97.26 143 | 97.53 243 | 94.97 81 | 99.33 168 | 97.38 86 | 99.20 116 | 99.05 163 |
|
EPNet | | | 97.28 105 | 96.87 108 | 98.51 95 | 94.98 341 | 96.14 147 | 98.90 88 | 97.02 321 | 98.28 1 | 95.99 195 | 99.11 76 | 91.36 147 | 99.89 39 | 96.98 97 | 99.19 117 | 99.50 100 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
PS-MVSNAJ | | | 97.73 76 | 97.77 66 | 97.62 162 | 98.68 150 | 95.58 173 | 97.34 287 | 98.51 167 | 97.29 35 | 98.66 71 | 97.88 211 | 94.51 91 | 99.90 37 | 97.87 52 | 99.17 118 | 97.39 231 |
|
PVSNet_Blended_VisFu | | | 97.70 78 | 97.46 82 | 98.44 103 | 99.27 87 | 95.91 163 | 98.63 149 | 99.16 18 | 94.48 170 | 97.67 130 | 98.88 112 | 92.80 115 | 99.91 34 | 97.11 93 | 99.12 119 | 99.50 100 |
|
BH-RMVSNet | | | 95.92 160 | 95.32 172 | 97.69 156 | 98.32 179 | 94.64 214 | 98.19 215 | 97.45 300 | 94.56 165 | 96.03 193 | 98.61 140 | 85.02 274 | 99.12 188 | 90.68 290 | 99.06 120 | 99.30 130 |
|
test2506 | | | 94.44 248 | 93.91 245 | 96.04 263 | 99.02 118 | 88.99 337 | 99.06 57 | 79.47 380 | 96.96 58 | 98.36 87 | 99.26 47 | 77.21 343 | 99.52 151 | 96.78 119 | 99.04 121 | 99.59 87 |
|
test1111 | | | 95.94 158 | 95.78 148 | 96.41 246 | 98.99 124 | 90.12 319 | 99.04 60 | 92.45 369 | 96.99 57 | 98.03 102 | 99.27 46 | 81.40 311 | 99.48 157 | 96.87 112 | 99.04 121 | 99.63 79 |
|
ECVR-MVS |  | | 95.95 156 | 95.71 153 | 96.65 217 | 99.02 118 | 90.86 305 | 99.03 63 | 91.80 370 | 96.96 58 | 98.10 96 | 99.26 47 | 81.31 312 | 99.51 152 | 96.90 105 | 99.04 121 | 99.59 87 |
|
PVSNet | | 91.96 18 | 96.35 141 | 96.15 137 | 96.96 196 | 99.17 103 | 92.05 283 | 96.08 337 | 98.68 125 | 93.69 205 | 97.75 124 | 97.80 222 | 88.86 201 | 99.69 124 | 94.26 203 | 99.01 124 | 99.15 150 |
|
PatchMatch-RL | | | 96.59 132 | 96.03 142 | 98.27 113 | 99.31 74 | 96.51 130 | 97.91 244 | 99.06 23 | 93.72 201 | 96.92 159 | 98.06 194 | 88.50 210 | 99.65 128 | 91.77 274 | 99.00 125 | 98.66 191 |
|
PCF-MVS | | 93.45 11 | 94.68 228 | 93.43 273 | 98.42 106 | 98.62 155 | 96.77 118 | 95.48 349 | 98.20 224 | 84.63 354 | 93.34 274 | 98.32 174 | 88.55 208 | 99.81 75 | 84.80 344 | 98.96 126 | 98.68 188 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
MAR-MVS | | | 96.91 121 | 96.40 129 | 98.45 102 | 98.69 149 | 96.90 113 | 98.66 145 | 98.68 125 | 92.40 257 | 97.07 151 | 97.96 203 | 91.54 144 | 99.75 109 | 93.68 219 | 98.92 127 | 98.69 187 |
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 |
F-COLMAP | | | 97.09 116 | 96.80 109 | 97.97 135 | 99.45 59 | 94.95 203 | 98.55 163 | 98.62 145 | 93.02 234 | 96.17 190 | 98.58 145 | 94.01 102 | 99.81 75 | 93.95 212 | 98.90 128 | 99.14 152 |
|
ETV-MVS | | | 97.96 64 | 97.81 65 | 98.40 107 | 98.42 166 | 97.27 96 | 98.73 127 | 98.55 158 | 96.84 62 | 98.38 86 | 97.44 250 | 95.39 61 | 99.35 166 | 97.62 71 | 98.89 129 | 98.58 197 |
|
DP-MVS | | | 96.59 132 | 95.93 144 | 98.57 88 | 99.34 66 | 96.19 146 | 98.70 136 | 98.39 193 | 89.45 328 | 94.52 220 | 99.35 32 | 91.85 135 | 99.85 54 | 92.89 246 | 98.88 130 | 99.68 63 |
|
OMC-MVS | | | 97.55 90 | 97.34 88 | 98.20 119 | 99.33 69 | 95.92 162 | 98.28 202 | 98.59 148 | 95.52 116 | 97.97 111 | 99.10 78 | 93.28 111 | 99.49 153 | 95.09 176 | 98.88 130 | 99.19 143 |
|
PAPM_NR | | | 97.46 92 | 97.11 96 | 98.50 96 | 99.50 45 | 96.41 135 | 98.63 149 | 98.60 146 | 95.18 135 | 97.06 152 | 98.06 194 | 94.26 99 | 99.57 139 | 93.80 217 | 98.87 132 | 99.52 94 |
|
ACMMP |  | | 98.23 58 | 97.95 61 | 99.09 62 | 99.74 8 | 97.62 84 | 99.03 63 | 99.41 6 | 95.98 96 | 97.60 137 | 99.36 30 | 94.45 95 | 99.93 19 | 97.14 92 | 98.85 133 | 99.70 54 |
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 |
UA-Net | | | 97.96 64 | 97.62 70 | 98.98 68 | 98.86 133 | 97.47 89 | 98.89 92 | 99.08 22 | 96.67 71 | 98.72 65 | 99.54 1 | 93.15 112 | 99.81 75 | 94.87 179 | 98.83 134 | 99.65 73 |
|
MSDG | | | 95.93 159 | 95.30 174 | 97.83 142 | 98.90 129 | 95.36 182 | 96.83 324 | 98.37 197 | 91.32 292 | 94.43 227 | 98.73 130 | 90.27 170 | 99.60 136 | 90.05 299 | 98.82 135 | 98.52 198 |
|
EPNet_dtu | | | 95.21 198 | 94.95 190 | 95.99 265 | 96.17 312 | 90.45 315 | 98.16 221 | 97.27 310 | 96.77 66 | 93.14 282 | 98.33 173 | 90.34 168 | 98.42 271 | 85.57 337 | 98.81 136 | 99.09 158 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
PLC |  | 95.07 4 | 97.20 110 | 96.78 112 | 98.44 103 | 99.29 82 | 96.31 142 | 98.14 222 | 98.76 103 | 92.41 256 | 96.39 185 | 98.31 175 | 94.92 83 | 99.78 100 | 94.06 210 | 98.77 137 | 99.23 137 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
xiu_mvs_v1_base_debu | | | 97.60 83 | 97.56 74 | 97.72 152 | 98.35 170 | 95.98 150 | 97.86 251 | 98.51 167 | 97.13 50 | 99.01 41 | 98.40 162 | 91.56 141 | 99.80 84 | 98.53 14 | 98.68 138 | 97.37 233 |
|
xiu_mvs_v1_base | | | 97.60 83 | 97.56 74 | 97.72 152 | 98.35 170 | 95.98 150 | 97.86 251 | 98.51 167 | 97.13 50 | 99.01 41 | 98.40 162 | 91.56 141 | 99.80 84 | 98.53 14 | 98.68 138 | 97.37 233 |
|
xiu_mvs_v1_base_debi | | | 97.60 83 | 97.56 74 | 97.72 152 | 98.35 170 | 95.98 150 | 97.86 251 | 98.51 167 | 97.13 50 | 99.01 41 | 98.40 162 | 91.56 141 | 99.80 84 | 98.53 14 | 98.68 138 | 97.37 233 |
|
MVS-HIRNet | | | 89.46 323 | 88.40 322 | 92.64 335 | 97.58 228 | 82.15 365 | 94.16 360 | 93.05 368 | 75.73 364 | 90.90 322 | 82.52 366 | 79.42 326 | 98.33 286 | 83.53 349 | 98.68 138 | 97.43 228 |
|
xiu_mvs_v2_base | | | 97.66 80 | 97.70 69 | 97.56 166 | 98.61 156 | 95.46 179 | 97.44 276 | 98.46 179 | 97.15 48 | 98.65 72 | 98.15 188 | 94.33 97 | 99.80 84 | 97.84 56 | 98.66 142 | 97.41 229 |
|
Vis-MVSNet (Re-imp) | | | 96.87 123 | 96.55 124 | 97.83 142 | 98.73 142 | 95.46 179 | 99.20 35 | 98.30 212 | 94.96 149 | 96.60 173 | 98.87 113 | 90.05 172 | 98.59 254 | 93.67 221 | 98.60 143 | 99.46 111 |
|
IS-MVSNet | | | 97.22 107 | 96.88 107 | 98.25 116 | 98.85 135 | 96.36 137 | 99.19 37 | 97.97 264 | 95.39 122 | 97.23 144 | 98.99 96 | 91.11 154 | 98.93 219 | 94.60 189 | 98.59 144 | 99.47 107 |
|
PAPR | | | 96.84 124 | 96.24 135 | 98.65 84 | 98.72 146 | 96.92 112 | 97.36 285 | 98.57 154 | 93.33 221 | 96.67 169 | 97.57 240 | 94.30 98 | 99.56 142 | 91.05 285 | 98.59 144 | 99.47 107 |
|
TSAR-MVS + GP. | | | 98.38 46 | 98.24 46 | 98.81 77 | 99.22 98 | 97.25 101 | 98.11 227 | 98.29 214 | 97.19 45 | 98.99 44 | 99.02 90 | 96.22 24 | 99.67 126 | 98.52 20 | 98.56 146 | 99.51 98 |
|
diffmvs | | | 97.58 87 | 97.40 86 | 98.13 125 | 98.32 179 | 95.81 168 | 98.06 230 | 98.37 197 | 96.20 88 | 98.74 62 | 98.89 111 | 91.31 150 | 99.25 172 | 98.16 37 | 98.52 147 | 99.34 121 |
|
BH-untuned | | | 95.95 156 | 95.72 150 | 96.65 217 | 98.55 160 | 92.26 279 | 98.23 206 | 97.79 274 | 93.73 200 | 94.62 217 | 98.01 198 | 88.97 199 | 99.00 209 | 93.04 239 | 98.51 148 | 98.68 188 |
|
test-LLR | | | 95.10 204 | 94.87 193 | 95.80 275 | 96.77 284 | 89.70 323 | 96.91 314 | 95.21 351 | 95.11 140 | 94.83 212 | 95.72 335 | 87.71 228 | 98.97 210 | 93.06 237 | 98.50 149 | 98.72 184 |
|
TESTMET0.1,1 | | | 94.18 264 | 93.69 263 | 95.63 281 | 96.92 276 | 89.12 333 | 96.91 314 | 94.78 356 | 93.17 228 | 94.88 209 | 96.45 315 | 78.52 331 | 98.92 220 | 93.09 236 | 98.50 149 | 98.85 177 |
|
test-mter | | | 94.08 271 | 93.51 270 | 95.80 275 | 96.77 284 | 89.70 323 | 96.91 314 | 95.21 351 | 92.89 240 | 94.83 212 | 95.72 335 | 77.69 338 | 98.97 210 | 93.06 237 | 98.50 149 | 98.72 184 |
|
1314 | | | 96.25 147 | 95.73 149 | 97.79 146 | 97.13 265 | 95.55 176 | 98.19 215 | 98.59 148 | 93.47 216 | 92.03 312 | 97.82 220 | 91.33 149 | 99.49 153 | 94.62 188 | 98.44 152 | 98.32 207 |
|
LCM-MVSNet-Re | | | 95.22 197 | 95.32 172 | 94.91 301 | 98.18 190 | 87.85 352 | 98.75 120 | 95.66 348 | 95.11 140 | 88.96 338 | 96.85 299 | 90.26 171 | 97.65 330 | 95.65 161 | 98.44 152 | 99.22 138 |
|
EPP-MVSNet | | | 97.46 92 | 97.28 90 | 97.99 134 | 98.64 153 | 95.38 181 | 99.33 19 | 98.31 206 | 93.61 212 | 97.19 145 | 99.07 87 | 94.05 101 | 99.23 175 | 96.89 106 | 98.43 154 | 99.37 120 |
|
casdiffmvs | | | 97.63 82 | 97.41 85 | 98.28 112 | 98.33 177 | 96.14 147 | 98.82 107 | 98.32 204 | 96.38 83 | 97.95 112 | 99.21 55 | 91.23 152 | 99.23 175 | 98.12 38 | 98.37 155 | 99.48 105 |
|
PatchmatchNet |  | | 95.71 169 | 95.52 161 | 96.29 255 | 97.58 228 | 90.72 310 | 96.84 323 | 97.52 293 | 94.06 180 | 97.08 149 | 96.96 290 | 89.24 188 | 98.90 224 | 92.03 268 | 98.37 155 | 99.26 135 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
MVS | | | 94.67 231 | 93.54 269 | 98.08 129 | 96.88 280 | 96.56 128 | 98.19 215 | 98.50 172 | 78.05 362 | 92.69 294 | 98.02 196 | 91.07 156 | 99.63 133 | 90.09 296 | 98.36 157 | 98.04 214 |
|
gg-mvs-nofinetune | | | 92.21 300 | 90.58 307 | 97.13 185 | 96.75 287 | 95.09 194 | 95.85 342 | 89.40 374 | 85.43 352 | 94.50 221 | 81.98 367 | 80.80 319 | 98.40 284 | 92.16 262 | 98.33 158 | 97.88 217 |
|
SCA | | | 95.46 179 | 95.13 180 | 96.46 243 | 97.67 221 | 91.29 300 | 97.33 288 | 97.60 284 | 94.68 160 | 96.92 159 | 97.10 268 | 83.97 295 | 98.89 225 | 92.59 252 | 98.32 159 | 99.20 139 |
|
baseline | | | 97.64 81 | 97.44 84 | 98.25 116 | 98.35 170 | 96.20 144 | 99.00 71 | 98.32 204 | 96.33 85 | 98.03 102 | 99.17 63 | 91.35 148 | 99.16 181 | 98.10 39 | 98.29 160 | 99.39 118 |
|
MVS_Test | | | 97.28 105 | 97.00 102 | 98.13 125 | 98.33 177 | 95.97 155 | 98.74 123 | 98.07 254 | 94.27 175 | 98.44 83 | 98.07 193 | 92.48 118 | 99.26 171 | 96.43 132 | 98.19 161 | 99.16 149 |
|
sss | | | 97.39 100 | 96.98 104 | 98.61 86 | 98.60 157 | 96.61 124 | 98.22 207 | 98.93 39 | 93.97 187 | 98.01 108 | 98.48 154 | 91.98 133 | 99.85 54 | 96.45 130 | 98.15 162 | 99.39 118 |
|
Patchmatch-test | | | 94.42 249 | 93.68 264 | 96.63 221 | 97.60 226 | 91.76 288 | 94.83 355 | 97.49 297 | 89.45 328 | 94.14 242 | 97.10 268 | 88.99 195 | 98.83 233 | 85.37 340 | 98.13 163 | 99.29 132 |
|
COLMAP_ROB |  | 93.27 12 | 95.33 192 | 94.87 193 | 96.71 212 | 99.29 82 | 93.24 268 | 98.58 155 | 98.11 243 | 89.92 320 | 93.57 264 | 99.10 78 | 86.37 254 | 99.79 96 | 90.78 288 | 98.10 164 | 97.09 238 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
GeoE | | | 96.58 134 | 96.07 139 | 98.10 128 | 98.35 170 | 95.89 165 | 99.34 16 | 98.12 240 | 93.12 231 | 96.09 191 | 98.87 113 | 89.71 178 | 98.97 210 | 92.95 242 | 98.08 165 | 99.43 115 |
|
mvs-test1 | | | 96.60 130 | 96.68 120 | 96.37 249 | 97.89 209 | 91.81 286 | 98.56 161 | 98.10 245 | 96.57 75 | 96.52 180 | 97.94 205 | 90.81 158 | 99.45 161 | 95.72 156 | 98.01 166 | 97.86 219 |
|
Effi-MVS+-dtu | | | 96.29 143 | 96.56 123 | 95.51 283 | 97.89 209 | 90.22 318 | 98.80 114 | 98.10 245 | 96.57 75 | 96.45 184 | 96.66 306 | 90.81 158 | 98.91 221 | 95.72 156 | 97.99 167 | 97.40 230 |
|
Fast-Effi-MVS+ | | | 96.28 145 | 95.70 155 | 98.03 132 | 98.29 181 | 95.97 155 | 98.58 155 | 98.25 220 | 91.74 276 | 95.29 203 | 97.23 262 | 91.03 157 | 99.15 184 | 92.90 244 | 97.96 168 | 98.97 170 |
|
mvs_anonymous | | | 96.70 128 | 96.53 126 | 97.18 182 | 98.19 188 | 93.78 244 | 98.31 197 | 98.19 225 | 94.01 184 | 94.47 222 | 98.27 180 | 92.08 131 | 98.46 266 | 97.39 85 | 97.91 169 | 99.31 127 |
|
PMMVS | | | 96.60 130 | 96.33 131 | 97.41 172 | 97.90 208 | 93.93 240 | 97.35 286 | 98.41 189 | 92.84 242 | 97.76 123 | 97.45 249 | 91.10 155 | 99.20 178 | 96.26 136 | 97.91 169 | 99.11 155 |
|
AllTest | | | 95.24 196 | 94.65 201 | 96.99 192 | 99.25 90 | 93.21 269 | 98.59 153 | 98.18 228 | 91.36 288 | 93.52 266 | 98.77 126 | 84.67 281 | 99.72 113 | 89.70 306 | 97.87 171 | 98.02 215 |
|
TestCases | | | | | 96.99 192 | 99.25 90 | 93.21 269 | | 98.18 228 | 91.36 288 | 93.52 266 | 98.77 126 | 84.67 281 | 99.72 113 | 89.70 306 | 97.87 171 | 98.02 215 |
|
TAMVS | | | 97.02 117 | 96.79 111 | 97.70 155 | 98.06 199 | 95.31 186 | 98.52 165 | 98.31 206 | 93.95 188 | 97.05 153 | 98.61 140 | 93.49 108 | 98.52 260 | 95.33 168 | 97.81 173 | 99.29 132 |
|
Effi-MVS+ | | | 97.12 114 | 96.69 118 | 98.39 108 | 98.19 188 | 96.72 120 | 97.37 283 | 98.43 186 | 93.71 202 | 97.65 133 | 98.02 196 | 92.20 127 | 99.25 172 | 96.87 112 | 97.79 174 | 99.19 143 |
|
Fast-Effi-MVS+-dtu | | | 95.87 161 | 95.85 146 | 95.91 270 | 97.74 218 | 91.74 290 | 98.69 138 | 98.15 236 | 95.56 113 | 94.92 208 | 97.68 231 | 88.98 198 | 98.79 237 | 93.19 234 | 97.78 175 | 97.20 237 |
|
DSMNet-mixed | | | 92.52 298 | 92.58 289 | 92.33 337 | 94.15 351 | 82.65 364 | 98.30 199 | 94.26 362 | 89.08 332 | 92.65 295 | 95.73 333 | 85.01 275 | 95.76 358 | 86.24 332 | 97.76 176 | 98.59 195 |
|
CDS-MVSNet | | | 96.99 118 | 96.69 118 | 97.90 139 | 98.05 200 | 95.98 150 | 98.20 211 | 98.33 203 | 93.67 209 | 96.95 155 | 98.49 153 | 93.54 107 | 98.42 271 | 95.24 174 | 97.74 177 | 99.31 127 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
thisisatest0515 | | | 95.61 177 | 94.89 192 | 97.76 149 | 98.15 193 | 95.15 191 | 96.77 325 | 94.41 359 | 92.95 237 | 97.18 146 | 97.43 251 | 84.78 279 | 99.45 161 | 94.63 186 | 97.73 178 | 98.68 188 |
|
thisisatest0530 | | | 96.01 153 | 95.36 168 | 97.97 135 | 98.38 168 | 95.52 177 | 98.88 95 | 94.19 363 | 94.04 181 | 97.64 134 | 98.31 175 | 83.82 300 | 99.46 160 | 95.29 171 | 97.70 179 | 98.93 174 |
|
BH-w/o | | | 95.38 186 | 95.08 183 | 96.26 256 | 98.34 175 | 91.79 287 | 97.70 263 | 97.43 302 | 92.87 241 | 94.24 237 | 97.22 263 | 88.66 204 | 98.84 231 | 91.55 278 | 97.70 179 | 98.16 212 |
|
PAPM | | | 94.95 214 | 94.00 238 | 97.78 147 | 97.04 270 | 95.65 171 | 96.03 340 | 98.25 220 | 91.23 297 | 94.19 240 | 97.80 222 | 91.27 151 | 98.86 230 | 82.61 351 | 97.61 181 | 98.84 179 |
|
tttt0517 | | | 96.07 150 | 95.51 162 | 97.78 147 | 98.41 167 | 94.84 206 | 99.28 22 | 94.33 361 | 94.26 176 | 97.64 134 | 98.64 139 | 84.05 293 | 99.47 159 | 95.34 167 | 97.60 182 | 99.03 164 |
|
HyFIR lowres test | | | 96.90 122 | 96.49 127 | 98.14 123 | 99.33 69 | 95.56 174 | 97.38 281 | 99.65 2 | 92.34 258 | 97.61 136 | 98.20 185 | 89.29 186 | 99.10 195 | 96.97 98 | 97.60 182 | 99.77 23 |
|
CVMVSNet | | | 95.43 182 | 96.04 141 | 93.57 326 | 97.93 206 | 83.62 361 | 98.12 225 | 98.59 148 | 95.68 107 | 96.56 174 | 99.02 90 | 87.51 232 | 97.51 336 | 93.56 225 | 97.44 184 | 99.60 85 |
|
MDTV_nov1_ep13 | | | | 95.40 163 | | 97.48 237 | 88.34 346 | 96.85 322 | 97.29 308 | 93.74 199 | 97.48 141 | 97.26 259 | 89.18 189 | 99.05 199 | 91.92 271 | 97.43 185 | |
|
baseline2 | | | 95.11 203 | 94.52 207 | 96.87 203 | 96.65 293 | 93.56 253 | 98.27 204 | 94.10 365 | 93.45 217 | 92.02 313 | 97.43 251 | 87.45 236 | 99.19 179 | 93.88 214 | 97.41 186 | 97.87 218 |
|
EPMVS | | | 94.99 210 | 94.48 209 | 96.52 236 | 97.22 256 | 91.75 289 | 97.23 294 | 91.66 371 | 94.11 178 | 97.28 142 | 96.81 301 | 85.70 264 | 98.84 231 | 93.04 239 | 97.28 187 | 98.97 170 |
|
LFMVS | | | 95.86 162 | 94.98 188 | 98.47 100 | 98.87 132 | 96.32 140 | 98.84 103 | 96.02 342 | 93.40 219 | 98.62 73 | 99.20 59 | 74.99 352 | 99.63 133 | 97.72 62 | 97.20 188 | 99.46 111 |
|
ADS-MVSNet2 | | | 94.58 237 | 94.40 217 | 95.11 296 | 98.00 201 | 88.74 340 | 96.04 338 | 97.30 307 | 90.15 315 | 96.47 182 | 96.64 309 | 87.89 224 | 97.56 334 | 90.08 297 | 97.06 189 | 99.02 165 |
|
ADS-MVSNet | | | 95.00 209 | 94.45 213 | 96.63 221 | 98.00 201 | 91.91 285 | 96.04 338 | 97.74 277 | 90.15 315 | 96.47 182 | 96.64 309 | 87.89 224 | 98.96 214 | 90.08 297 | 97.06 189 | 99.02 165 |
|
GG-mvs-BLEND | | | | | 96.59 226 | 96.34 306 | 94.98 200 | 96.51 334 | 88.58 375 | | 93.10 284 | 94.34 351 | 80.34 322 | 98.05 312 | 89.53 309 | 96.99 191 | 96.74 273 |
|
cascas | | | 94.63 233 | 93.86 249 | 96.93 198 | 96.91 278 | 94.27 232 | 96.00 341 | 98.51 167 | 85.55 351 | 94.54 219 | 96.23 322 | 84.20 291 | 98.87 228 | 95.80 153 | 96.98 192 | 97.66 226 |
|
WTY-MVS | | | 97.37 102 | 96.92 106 | 98.72 80 | 98.86 133 | 96.89 115 | 98.31 197 | 98.71 118 | 95.26 131 | 97.67 130 | 98.56 148 | 92.21 126 | 99.78 100 | 95.89 148 | 96.85 193 | 99.48 105 |
|
VDD-MVS | | | 95.82 165 | 95.23 176 | 97.61 163 | 98.84 136 | 93.98 239 | 98.68 139 | 97.40 304 | 95.02 146 | 97.95 112 | 99.34 35 | 74.37 356 | 99.78 100 | 98.64 8 | 96.80 194 | 99.08 161 |
|
test_yl | | | 97.22 107 | 96.78 112 | 98.54 92 | 98.73 142 | 96.60 125 | 98.45 174 | 98.31 206 | 94.70 157 | 98.02 104 | 98.42 160 | 90.80 160 | 99.70 119 | 96.81 115 | 96.79 195 | 99.34 121 |
|
DCV-MVSNet | | | 97.22 107 | 96.78 112 | 98.54 92 | 98.73 142 | 96.60 125 | 98.45 174 | 98.31 206 | 94.70 157 | 98.02 104 | 98.42 160 | 90.80 160 | 99.70 119 | 96.81 115 | 96.79 195 | 99.34 121 |
|
PatchT | | | 93.06 292 | 91.97 297 | 96.35 251 | 96.69 290 | 92.67 276 | 94.48 357 | 97.08 315 | 86.62 342 | 97.08 149 | 92.23 359 | 87.94 223 | 97.90 322 | 78.89 361 | 96.69 197 | 98.49 199 |
|
VNet | | | 97.79 74 | 97.40 86 | 98.96 70 | 98.88 131 | 97.55 86 | 98.63 149 | 98.93 39 | 96.74 68 | 99.02 40 | 98.84 117 | 90.33 169 | 99.83 60 | 98.53 14 | 96.66 198 | 99.50 100 |
|
CR-MVSNet | | | 94.76 225 | 94.15 229 | 96.59 226 | 97.00 271 | 93.43 259 | 94.96 351 | 97.56 286 | 92.46 251 | 96.93 157 | 96.24 320 | 88.15 217 | 97.88 326 | 87.38 326 | 96.65 199 | 98.46 200 |
|
RPMNet | | | 92.81 294 | 91.34 302 | 97.24 178 | 97.00 271 | 93.43 259 | 94.96 351 | 98.80 91 | 82.27 357 | 96.93 157 | 92.12 360 | 86.98 243 | 99.82 68 | 76.32 365 | 96.65 199 | 98.46 200 |
|
VDDNet | | | 95.36 189 | 94.53 206 | 97.86 140 | 98.10 196 | 95.13 193 | 98.85 100 | 97.75 276 | 90.46 309 | 98.36 87 | 99.39 18 | 73.27 358 | 99.64 130 | 97.98 44 | 96.58 201 | 98.81 180 |
|
alignmvs | | | 97.56 89 | 97.07 99 | 99.01 65 | 98.66 151 | 98.37 46 | 98.83 104 | 98.06 259 | 96.74 68 | 98.00 110 | 97.65 232 | 90.80 160 | 99.48 157 | 98.37 31 | 96.56 202 | 99.19 143 |
|
HY-MVS | | 93.96 8 | 96.82 125 | 96.23 136 | 98.57 88 | 98.46 165 | 97.00 108 | 98.14 222 | 98.21 222 | 93.95 188 | 96.72 168 | 97.99 200 | 91.58 140 | 99.76 107 | 94.51 194 | 96.54 203 | 98.95 173 |
|
1112_ss | | | 96.63 129 | 96.00 143 | 98.50 96 | 98.56 158 | 96.37 136 | 98.18 219 | 98.10 245 | 92.92 238 | 94.84 210 | 98.43 158 | 92.14 128 | 99.58 138 | 94.35 198 | 96.51 204 | 99.56 93 |
|
thres200 | | | 95.25 195 | 94.57 204 | 97.28 177 | 98.81 138 | 94.92 204 | 98.20 211 | 97.11 314 | 95.24 134 | 96.54 178 | 96.22 324 | 84.58 283 | 99.53 148 | 87.93 324 | 96.50 205 | 97.39 231 |
|
Test_1112_low_res | | | 96.34 142 | 95.66 158 | 98.36 109 | 98.56 158 | 95.94 158 | 97.71 262 | 98.07 254 | 92.10 268 | 94.79 214 | 97.29 258 | 91.75 137 | 99.56 142 | 94.17 205 | 96.50 205 | 99.58 91 |
|
tpmrst | | | 95.63 174 | 95.69 156 | 95.44 287 | 97.54 233 | 88.54 343 | 96.97 309 | 97.56 286 | 93.50 215 | 97.52 140 | 96.93 294 | 89.49 180 | 99.16 181 | 95.25 173 | 96.42 207 | 98.64 193 |
|
ab-mvs | | | 96.42 139 | 95.71 153 | 98.55 90 | 98.63 154 | 96.75 119 | 97.88 249 | 98.74 108 | 93.84 193 | 96.54 178 | 98.18 187 | 85.34 271 | 99.75 109 | 95.93 147 | 96.35 208 | 99.15 150 |
|
thres600view7 | | | 95.49 178 | 94.77 195 | 97.67 158 | 98.98 125 | 95.02 196 | 98.85 100 | 96.90 327 | 95.38 123 | 96.63 171 | 96.90 295 | 84.29 286 | 99.59 137 | 88.65 319 | 96.33 209 | 98.40 202 |
|
RPSCF | | | 94.87 219 | 95.40 163 | 93.26 332 | 98.89 130 | 82.06 366 | 98.33 191 | 98.06 259 | 90.30 314 | 96.56 174 | 99.26 47 | 87.09 240 | 99.49 153 | 93.82 216 | 96.32 210 | 98.24 208 |
|
thres100view900 | | | 95.38 186 | 94.70 199 | 97.41 172 | 98.98 125 | 94.92 204 | 98.87 97 | 96.90 327 | 95.38 123 | 96.61 172 | 96.88 296 | 84.29 286 | 99.56 142 | 88.11 320 | 96.29 211 | 97.76 220 |
|
tfpn200view9 | | | 95.32 193 | 94.62 202 | 97.43 171 | 98.94 127 | 94.98 200 | 98.68 139 | 96.93 325 | 95.33 126 | 96.55 176 | 96.53 312 | 84.23 289 | 99.56 142 | 88.11 320 | 96.29 211 | 97.76 220 |
|
thres400 | | | 95.38 186 | 94.62 202 | 97.65 161 | 98.94 127 | 94.98 200 | 98.68 139 | 96.93 325 | 95.33 126 | 96.55 176 | 96.53 312 | 84.23 289 | 99.56 142 | 88.11 320 | 96.29 211 | 98.40 202 |
|
canonicalmvs | | | 97.67 79 | 97.23 92 | 98.98 68 | 98.70 147 | 98.38 40 | 99.34 16 | 98.39 193 | 96.76 67 | 97.67 130 | 97.40 253 | 92.26 123 | 99.49 153 | 98.28 35 | 96.28 214 | 99.08 161 |
|
XVG-OURS | | | 96.55 135 | 96.41 128 | 96.99 192 | 98.75 141 | 93.76 245 | 97.50 275 | 98.52 164 | 95.67 108 | 96.83 162 | 99.30 42 | 88.95 200 | 99.53 148 | 95.88 149 | 96.26 215 | 97.69 225 |
|
GA-MVS | | | 94.81 222 | 94.03 234 | 97.14 184 | 97.15 264 | 93.86 242 | 96.76 326 | 97.58 285 | 94.00 185 | 94.76 215 | 97.04 281 | 80.91 316 | 98.48 262 | 91.79 273 | 96.25 216 | 99.09 158 |
|
tpm2 | | | 94.19 262 | 93.76 258 | 95.46 286 | 97.23 255 | 89.04 335 | 97.31 290 | 96.85 333 | 87.08 341 | 96.21 189 | 96.79 302 | 83.75 301 | 98.74 240 | 92.43 260 | 96.23 217 | 98.59 195 |
|
MIMVSNet | | | 93.26 287 | 92.21 294 | 96.41 246 | 97.73 219 | 93.13 271 | 95.65 346 | 97.03 319 | 91.27 296 | 94.04 247 | 96.06 327 | 75.33 350 | 97.19 340 | 86.56 330 | 96.23 217 | 98.92 175 |
|
TR-MVS | | | 94.94 216 | 94.20 224 | 97.17 183 | 97.75 215 | 94.14 236 | 97.59 271 | 97.02 321 | 92.28 263 | 95.75 198 | 97.64 234 | 83.88 297 | 98.96 214 | 89.77 303 | 96.15 219 | 98.40 202 |
|
MVS_0304 | | | 92.81 294 | 92.01 296 | 95.23 291 | 97.46 239 | 91.33 298 | 98.17 220 | 98.81 80 | 91.13 301 | 93.80 258 | 95.68 338 | 66.08 366 | 98.06 311 | 90.79 287 | 96.13 220 | 96.32 321 |
|
CostFormer | | | 94.95 214 | 94.73 198 | 95.60 282 | 97.28 252 | 89.06 334 | 97.53 274 | 96.89 329 | 89.66 325 | 96.82 164 | 96.72 304 | 86.05 259 | 98.95 218 | 95.53 164 | 96.13 220 | 98.79 181 |
|
tpmvs | | | 94.60 234 | 94.36 218 | 95.33 290 | 97.46 239 | 88.60 342 | 96.88 320 | 97.68 278 | 91.29 294 | 93.80 258 | 96.42 317 | 88.58 205 | 99.24 174 | 91.06 283 | 96.04 222 | 98.17 211 |
|
tpm cat1 | | | 93.36 282 | 92.80 284 | 95.07 298 | 97.58 228 | 87.97 350 | 96.76 326 | 97.86 272 | 82.17 358 | 93.53 265 | 96.04 328 | 86.13 257 | 99.13 187 | 89.24 314 | 95.87 223 | 98.10 213 |
|
XVG-OURS-SEG-HR | | | 96.51 136 | 96.34 130 | 97.02 191 | 98.77 140 | 93.76 245 | 97.79 258 | 98.50 172 | 95.45 119 | 96.94 156 | 99.09 84 | 87.87 226 | 99.55 147 | 96.76 121 | 95.83 224 | 97.74 222 |
|
DWT-MVSNet_test | | | 94.82 220 | 94.36 218 | 96.20 258 | 97.35 249 | 90.79 308 | 98.34 189 | 96.57 340 | 92.91 239 | 95.33 202 | 96.44 316 | 82.00 306 | 99.12 188 | 94.52 193 | 95.78 225 | 98.70 186 |
|
JIA-IIPM | | | 93.35 283 | 92.49 290 | 95.92 269 | 96.48 301 | 90.65 312 | 95.01 350 | 96.96 323 | 85.93 348 | 96.08 192 | 87.33 364 | 87.70 230 | 98.78 238 | 91.35 280 | 95.58 226 | 98.34 205 |
|
Anonymous202405211 | | | 95.28 194 | 94.49 208 | 97.67 158 | 99.00 121 | 93.75 247 | 98.70 136 | 97.04 318 | 90.66 305 | 96.49 181 | 98.80 122 | 78.13 335 | 99.83 60 | 96.21 138 | 95.36 227 | 99.44 114 |
|
Anonymous20240529 | | | 95.10 204 | 94.22 223 | 97.75 150 | 99.01 120 | 94.26 233 | 98.87 97 | 98.83 72 | 85.79 350 | 96.64 170 | 98.97 97 | 78.73 330 | 99.85 54 | 96.27 135 | 94.89 228 | 99.12 154 |
|
CLD-MVS | | | 95.62 175 | 95.34 169 | 96.46 243 | 97.52 236 | 93.75 247 | 97.27 293 | 98.46 179 | 95.53 114 | 94.42 228 | 98.00 199 | 86.21 256 | 98.97 210 | 96.25 137 | 94.37 229 | 96.66 286 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
dp | | | 94.15 265 | 93.90 246 | 94.90 302 | 97.31 251 | 86.82 357 | 96.97 309 | 97.19 313 | 91.22 298 | 96.02 194 | 96.61 311 | 85.51 267 | 99.02 206 | 90.00 301 | 94.30 230 | 98.85 177 |
|
HQP_MVS | | | 96.14 149 | 95.90 145 | 96.85 204 | 97.42 244 | 94.60 220 | 98.80 114 | 98.56 156 | 97.28 36 | 95.34 200 | 98.28 177 | 87.09 240 | 99.03 203 | 96.07 140 | 94.27 231 | 96.92 249 |
|
plane_prior5 | | | | | | | | | 98.56 156 | | | | | 99.03 203 | 96.07 140 | 94.27 231 | 96.92 249 |
|
plane_prior | | | | | | | 94.60 220 | 98.44 177 | | 96.74 68 | | | | | | 94.22 233 | |
|
OPM-MVS | | | 95.69 172 | 95.33 171 | 96.76 209 | 96.16 314 | 94.63 215 | 98.43 179 | 98.39 193 | 96.64 72 | 95.02 206 | 98.78 124 | 85.15 273 | 99.05 199 | 95.21 175 | 94.20 234 | 96.60 291 |
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS). |
HQP3-MVS | | | | | | | | | 98.46 179 | | | | | | | 94.18 235 | |
|
HQP-MVS | | | 95.72 168 | 95.40 163 | 96.69 215 | 97.20 258 | 94.25 234 | 98.05 231 | 98.46 179 | 96.43 80 | 94.45 223 | 97.73 225 | 86.75 246 | 98.96 214 | 95.30 169 | 94.18 235 | 96.86 262 |
|
LPG-MVS_test | | | 95.62 175 | 95.34 169 | 96.47 240 | 97.46 239 | 93.54 254 | 98.99 73 | 98.54 160 | 94.67 161 | 94.36 230 | 98.77 126 | 85.39 268 | 99.11 192 | 95.71 158 | 94.15 237 | 96.76 271 |
|
LGP-MVS_train | | | | | 96.47 240 | 97.46 239 | 93.54 254 | | 98.54 160 | 94.67 161 | 94.36 230 | 98.77 126 | 85.39 268 | 99.11 192 | 95.71 158 | 94.15 237 | 96.76 271 |
|
test_djsdf | | | 96.00 154 | 95.69 156 | 96.93 198 | 95.72 327 | 95.49 178 | 99.47 7 | 98.40 191 | 94.98 147 | 94.58 218 | 97.86 213 | 89.16 190 | 98.41 278 | 96.91 102 | 94.12 239 | 96.88 258 |
|
jajsoiax | | | 95.45 181 | 95.03 185 | 96.73 211 | 95.42 338 | 94.63 215 | 99.14 43 | 98.52 164 | 95.74 104 | 93.22 277 | 98.36 167 | 83.87 298 | 98.65 248 | 96.95 101 | 94.04 240 | 96.91 254 |
|
anonymousdsp | | | 95.42 183 | 94.91 191 | 96.94 197 | 95.10 340 | 95.90 164 | 99.14 43 | 98.41 189 | 93.75 197 | 93.16 279 | 97.46 247 | 87.50 234 | 98.41 278 | 95.63 162 | 94.03 241 | 96.50 310 |
|
mvs_tets | | | 95.41 185 | 95.00 186 | 96.65 217 | 95.58 331 | 94.42 226 | 99.00 71 | 98.55 158 | 95.73 105 | 93.21 278 | 98.38 165 | 83.45 302 | 98.63 249 | 97.09 94 | 94.00 242 | 96.91 254 |
|
ACMP | | 93.49 10 | 95.34 191 | 94.98 188 | 96.43 245 | 97.67 221 | 93.48 258 | 98.73 127 | 98.44 183 | 94.94 152 | 92.53 299 | 98.53 149 | 84.50 285 | 99.14 186 | 95.48 166 | 94.00 242 | 96.66 286 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
ACMM | | 93.85 9 | 95.69 172 | 95.38 167 | 96.61 223 | 97.61 225 | 93.84 243 | 98.91 87 | 98.44 183 | 95.25 132 | 94.28 234 | 98.47 155 | 86.04 261 | 99.12 188 | 95.50 165 | 93.95 244 | 96.87 260 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
UniMVSNet_ETH3D | | | 94.24 259 | 93.33 275 | 96.97 195 | 97.19 261 | 93.38 263 | 98.74 123 | 98.57 154 | 91.21 299 | 93.81 257 | 98.58 145 | 72.85 359 | 98.77 239 | 95.05 177 | 93.93 245 | 98.77 183 |
|
XVG-ACMP-BASELINE | | | 94.54 240 | 94.14 230 | 95.75 278 | 96.55 296 | 91.65 292 | 98.11 227 | 98.44 183 | 94.96 149 | 94.22 238 | 97.90 208 | 79.18 328 | 99.11 192 | 94.05 211 | 93.85 246 | 96.48 312 |
|
EG-PatchMatch MVS | | | 91.13 308 | 90.12 311 | 94.17 323 | 94.73 347 | 89.00 336 | 98.13 224 | 97.81 273 | 89.22 331 | 85.32 355 | 96.46 314 | 67.71 363 | 98.42 271 | 87.89 325 | 93.82 247 | 95.08 346 |
|
testgi | | | 93.06 292 | 92.45 291 | 94.88 303 | 96.43 303 | 89.90 320 | 98.75 120 | 97.54 292 | 95.60 111 | 91.63 317 | 97.91 207 | 74.46 355 | 97.02 342 | 86.10 333 | 93.67 248 | 97.72 224 |
|
test0.0.03 1 | | | 94.08 271 | 93.51 270 | 95.80 275 | 95.53 333 | 92.89 275 | 97.38 281 | 95.97 344 | 95.11 140 | 92.51 301 | 96.66 306 | 87.71 228 | 96.94 344 | 87.03 328 | 93.67 248 | 97.57 227 |
|
CMPMVS |  | 66.06 21 | 89.70 319 | 89.67 315 | 89.78 343 | 93.19 358 | 76.56 368 | 97.00 308 | 98.35 200 | 80.97 359 | 81.57 360 | 97.75 224 | 74.75 353 | 98.61 250 | 89.85 302 | 93.63 250 | 94.17 354 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
ACMMP++ | | | | | | | | | | | | | | | | 93.61 251 | |
|
D2MVS | | | 95.18 200 | 95.08 183 | 95.48 284 | 97.10 267 | 92.07 282 | 98.30 199 | 99.13 20 | 94.02 183 | 92.90 287 | 96.73 303 | 89.48 181 | 98.73 241 | 94.48 195 | 93.60 252 | 95.65 337 |
|
EI-MVSNet | | | 95.96 155 | 95.83 147 | 96.36 250 | 97.93 206 | 93.70 251 | 98.12 225 | 98.27 215 | 93.70 204 | 95.07 204 | 99.02 90 | 92.23 125 | 98.54 258 | 94.68 185 | 93.46 253 | 96.84 263 |
|
MVSTER | | | 96.06 151 | 95.72 150 | 97.08 189 | 98.23 183 | 95.93 161 | 98.73 127 | 98.27 215 | 94.86 153 | 95.07 204 | 98.09 192 | 88.21 214 | 98.54 258 | 96.59 124 | 93.46 253 | 96.79 267 |
|
PS-MVSNAJss | | | 96.43 138 | 96.26 134 | 96.92 201 | 95.84 325 | 95.08 195 | 99.16 40 | 98.50 172 | 95.87 100 | 93.84 256 | 98.34 172 | 94.51 91 | 98.61 250 | 96.88 109 | 93.45 255 | 97.06 240 |
|
LTVRE_ROB | | 92.95 15 | 94.60 234 | 93.90 246 | 96.68 216 | 97.41 247 | 94.42 226 | 98.52 165 | 98.59 148 | 91.69 279 | 91.21 319 | 98.35 168 | 84.87 277 | 99.04 202 | 91.06 283 | 93.44 256 | 96.60 291 |
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 |
ITE_SJBPF | | | | | 95.44 287 | 97.42 244 | 91.32 299 | | 97.50 295 | 95.09 143 | 93.59 262 | 98.35 168 | 81.70 309 | 98.88 227 | 89.71 305 | 93.39 257 | 96.12 326 |
|
PVSNet_BlendedMVS | | | 96.73 127 | 96.60 122 | 97.12 186 | 99.25 90 | 95.35 184 | 98.26 205 | 99.26 9 | 94.28 174 | 97.94 114 | 97.46 247 | 92.74 116 | 99.81 75 | 96.88 109 | 93.32 258 | 96.20 324 |
|
ACMH | | 92.88 16 | 94.55 239 | 93.95 242 | 96.34 252 | 97.63 224 | 93.26 267 | 98.81 113 | 98.49 177 | 93.43 218 | 89.74 332 | 98.53 149 | 81.91 308 | 99.08 197 | 93.69 218 | 93.30 259 | 96.70 280 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
OpenMVS_ROB |  | 86.42 20 | 89.00 324 | 87.43 329 | 93.69 325 | 93.08 359 | 89.42 329 | 97.91 244 | 96.89 329 | 78.58 361 | 85.86 352 | 94.69 346 | 69.48 361 | 98.29 294 | 77.13 364 | 93.29 260 | 93.36 361 |
|
USDC | | | 93.33 285 | 92.71 286 | 95.21 292 | 96.83 283 | 90.83 307 | 96.91 314 | 97.50 295 | 93.84 193 | 90.72 324 | 98.14 189 | 77.69 338 | 98.82 234 | 89.51 310 | 93.21 261 | 95.97 330 |
|
RRT_MVS | | | 96.04 152 | 95.53 160 | 97.56 166 | 97.07 269 | 97.32 93 | 98.57 160 | 98.09 250 | 95.15 137 | 95.02 206 | 98.44 157 | 88.20 215 | 98.58 256 | 96.17 139 | 93.09 262 | 96.79 267 |
|
ACMMP++_ref | | | | | | | | | | | | | | | | 92.97 263 | |
|
test_0402 | | | 91.32 305 | 90.27 310 | 94.48 316 | 96.60 294 | 91.12 302 | 98.50 170 | 97.22 312 | 86.10 347 | 88.30 343 | 96.98 287 | 77.65 340 | 97.99 317 | 78.13 363 | 92.94 264 | 94.34 352 |
|
FIs | | | 96.51 136 | 96.12 138 | 97.67 158 | 97.13 265 | 97.54 87 | 99.36 13 | 99.22 15 | 95.89 98 | 94.03 248 | 98.35 168 | 91.98 133 | 98.44 269 | 96.40 133 | 92.76 265 | 97.01 242 |
|
FC-MVSNet-test | | | 96.42 139 | 96.05 140 | 97.53 168 | 96.95 274 | 97.27 96 | 99.36 13 | 99.23 13 | 95.83 101 | 93.93 250 | 98.37 166 | 92.00 132 | 98.32 287 | 96.02 145 | 92.72 266 | 97.00 243 |
|
TinyColmap | | | 92.31 299 | 91.53 300 | 94.65 311 | 96.92 276 | 89.75 322 | 96.92 312 | 96.68 337 | 90.45 310 | 89.62 333 | 97.85 215 | 76.06 348 | 98.81 235 | 86.74 329 | 92.51 267 | 95.41 339 |
|
ACMH+ | | 92.99 14 | 94.30 255 | 93.77 256 | 95.88 273 | 97.81 213 | 92.04 284 | 98.71 132 | 98.37 197 | 93.99 186 | 90.60 326 | 98.47 155 | 80.86 318 | 99.05 199 | 92.75 248 | 92.40 268 | 96.55 299 |
|
GBi-Net | | | 94.49 244 | 93.80 253 | 96.56 230 | 98.21 185 | 95.00 197 | 98.82 107 | 98.18 228 | 92.46 251 | 94.09 244 | 97.07 275 | 81.16 313 | 97.95 318 | 92.08 264 | 92.14 269 | 96.72 276 |
|
test1 | | | 94.49 244 | 93.80 253 | 96.56 230 | 98.21 185 | 95.00 197 | 98.82 107 | 98.18 228 | 92.46 251 | 94.09 244 | 97.07 275 | 81.16 313 | 97.95 318 | 92.08 264 | 92.14 269 | 96.72 276 |
|
FMVSNet3 | | | 94.97 213 | 94.26 222 | 97.11 187 | 98.18 190 | 96.62 122 | 98.56 161 | 98.26 219 | 93.67 209 | 94.09 244 | 97.10 268 | 84.25 288 | 98.01 314 | 92.08 264 | 92.14 269 | 96.70 280 |
|
FMVSNet2 | | | 94.47 246 | 93.61 266 | 97.04 190 | 98.21 185 | 96.43 134 | 98.79 118 | 98.27 215 | 92.46 251 | 93.50 269 | 97.09 272 | 81.16 313 | 98.00 316 | 91.09 281 | 91.93 272 | 96.70 280 |
|
LF4IMVS | | | 93.14 291 | 92.79 285 | 94.20 321 | 95.88 323 | 88.67 341 | 97.66 266 | 97.07 316 | 93.81 196 | 91.71 315 | 97.65 232 | 77.96 337 | 98.81 235 | 91.47 279 | 91.92 273 | 95.12 344 |
|
OurMVSNet-221017-0 | | | 94.21 260 | 94.00 238 | 94.85 304 | 95.60 330 | 89.22 332 | 98.89 92 | 97.43 302 | 95.29 129 | 92.18 309 | 98.52 152 | 82.86 303 | 98.59 254 | 93.46 226 | 91.76 274 | 96.74 273 |
|
EGC-MVSNET | | | 75.22 335 | 69.54 338 | 92.28 338 | 94.81 345 | 89.58 326 | 97.64 267 | 96.50 341 | 1.82 378 | 5.57 379 | 95.74 331 | 68.21 362 | 96.26 356 | 73.80 367 | 91.71 275 | 90.99 363 |
|
pmmvs4 | | | 94.69 226 | 93.99 240 | 96.81 207 | 95.74 326 | 95.94 158 | 97.40 279 | 97.67 279 | 90.42 311 | 93.37 273 | 97.59 238 | 89.08 193 | 98.20 299 | 92.97 241 | 91.67 276 | 96.30 322 |
|
tpm | | | 94.13 266 | 93.80 253 | 95.12 295 | 96.50 299 | 87.91 351 | 97.44 276 | 95.89 347 | 92.62 247 | 96.37 186 | 96.30 319 | 84.13 292 | 98.30 291 | 93.24 232 | 91.66 277 | 99.14 152 |
|
our_test_3 | | | 93.65 280 | 93.30 276 | 94.69 309 | 95.45 336 | 89.68 325 | 96.91 314 | 97.65 280 | 91.97 271 | 91.66 316 | 96.88 296 | 89.67 179 | 97.93 321 | 88.02 323 | 91.49 278 | 96.48 312 |
|
bset_n11_16_dypcd | | | 94.89 218 | 94.27 221 | 96.76 209 | 94.41 349 | 95.15 191 | 95.67 345 | 95.64 349 | 95.53 114 | 94.65 216 | 97.52 244 | 87.10 239 | 98.29 294 | 96.58 126 | 91.35 279 | 96.83 265 |
|
IterMVS | | | 94.09 270 | 93.85 250 | 94.80 307 | 97.99 203 | 90.35 316 | 97.18 298 | 98.12 240 | 93.68 207 | 92.46 304 | 97.34 254 | 84.05 293 | 97.41 337 | 92.51 257 | 91.33 280 | 96.62 289 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
IterMVS-SCA-FT | | | 94.11 268 | 93.87 248 | 94.85 304 | 97.98 205 | 90.56 314 | 97.18 298 | 98.11 243 | 93.75 197 | 92.58 297 | 97.48 246 | 83.97 295 | 97.41 337 | 92.48 259 | 91.30 281 | 96.58 293 |
|
FMVSNet1 | | | 93.19 290 | 92.07 295 | 96.56 230 | 97.54 233 | 95.00 197 | 98.82 107 | 98.18 228 | 90.38 312 | 92.27 307 | 97.07 275 | 73.68 357 | 97.95 318 | 89.36 313 | 91.30 281 | 96.72 276 |
|
XXY-MVS | | | 95.20 199 | 94.45 213 | 97.46 169 | 96.75 287 | 96.56 128 | 98.86 99 | 98.65 140 | 93.30 224 | 93.27 276 | 98.27 180 | 84.85 278 | 98.87 228 | 94.82 182 | 91.26 283 | 96.96 246 |
|
cl22 | | | 94.68 228 | 94.19 225 | 96.13 261 | 98.11 195 | 93.60 252 | 96.94 311 | 98.31 206 | 92.43 255 | 93.32 275 | 96.87 298 | 86.51 249 | 98.28 296 | 94.10 209 | 91.16 284 | 96.51 308 |
|
miper_ehance_all_eth | | | 95.01 208 | 94.69 200 | 95.97 267 | 97.70 220 | 93.31 265 | 97.02 307 | 98.07 254 | 92.23 264 | 93.51 268 | 96.96 290 | 91.85 135 | 98.15 302 | 93.68 219 | 91.16 284 | 96.44 315 |
|
miper_enhance_ethall | | | 95.10 204 | 94.75 197 | 96.12 262 | 97.53 235 | 93.73 249 | 96.61 331 | 98.08 252 | 92.20 267 | 93.89 252 | 96.65 308 | 92.44 119 | 98.30 291 | 94.21 204 | 91.16 284 | 96.34 318 |
|
RRT_test8_iter05 | | | 94.56 238 | 94.19 225 | 95.67 280 | 97.60 226 | 91.34 296 | 98.93 85 | 98.42 188 | 94.75 156 | 93.39 272 | 97.87 212 | 79.00 329 | 98.61 250 | 96.78 119 | 90.99 287 | 97.07 239 |
|
pmmvs5 | | | 93.65 280 | 92.97 282 | 95.68 279 | 95.49 334 | 92.37 278 | 98.20 211 | 97.28 309 | 89.66 325 | 92.58 297 | 97.26 259 | 82.14 305 | 98.09 308 | 93.18 235 | 90.95 288 | 96.58 293 |
|
ET-MVSNet_ETH3D | | | 94.13 266 | 92.98 281 | 97.58 164 | 98.22 184 | 96.20 144 | 97.31 290 | 95.37 350 | 94.53 166 | 79.56 362 | 97.63 236 | 86.51 249 | 97.53 335 | 96.91 102 | 90.74 289 | 99.02 165 |
|
SixPastTwentyTwo | | | 93.34 284 | 92.86 283 | 94.75 308 | 95.67 328 | 89.41 330 | 98.75 120 | 96.67 338 | 93.89 190 | 90.15 330 | 98.25 182 | 80.87 317 | 98.27 297 | 90.90 286 | 90.64 290 | 96.57 295 |
|
N_pmnet | | | 87.12 328 | 87.77 327 | 85.17 348 | 95.46 335 | 61.92 375 | 97.37 283 | 70.66 381 | 85.83 349 | 88.73 342 | 96.04 328 | 85.33 272 | 97.76 329 | 80.02 356 | 90.48 291 | 95.84 332 |
|
ppachtmachnet_test | | | 93.22 288 | 92.63 288 | 94.97 300 | 95.45 336 | 90.84 306 | 96.88 320 | 97.88 271 | 90.60 306 | 92.08 311 | 97.26 259 | 88.08 220 | 97.86 327 | 85.12 341 | 90.33 292 | 96.22 323 |
|
DIV-MVS_self_test | | | 94.52 242 | 94.03 234 | 95.99 265 | 97.57 232 | 93.38 263 | 97.05 305 | 97.94 267 | 91.74 276 | 92.81 289 | 97.10 268 | 89.12 191 | 98.07 310 | 92.60 250 | 90.30 293 | 96.53 302 |
|
cl____ | | | 94.51 243 | 94.01 237 | 96.02 264 | 97.58 228 | 93.40 262 | 97.05 305 | 97.96 266 | 91.73 278 | 92.76 291 | 97.08 274 | 89.06 194 | 98.13 304 | 92.61 249 | 90.29 294 | 96.52 305 |
|
IterMVS-LS | | | 95.46 179 | 95.21 177 | 96.22 257 | 98.12 194 | 93.72 250 | 98.32 196 | 98.13 239 | 93.71 202 | 94.26 235 | 97.31 257 | 92.24 124 | 98.10 306 | 94.63 186 | 90.12 295 | 96.84 263 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
Patchmtry | | | 93.22 288 | 92.35 292 | 95.84 274 | 96.77 284 | 93.09 273 | 94.66 356 | 97.56 286 | 87.37 340 | 92.90 287 | 96.24 320 | 88.15 217 | 97.90 322 | 87.37 327 | 90.10 296 | 96.53 302 |
|
EU-MVSNet | | | 93.66 278 | 94.14 230 | 92.25 339 | 95.96 321 | 83.38 362 | 98.52 165 | 98.12 240 | 94.69 159 | 92.61 296 | 98.13 190 | 87.36 237 | 96.39 355 | 91.82 272 | 90.00 297 | 96.98 244 |
|
Anonymous20231206 | | | 91.66 303 | 91.10 303 | 93.33 330 | 94.02 355 | 87.35 354 | 98.58 155 | 97.26 311 | 90.48 308 | 90.16 329 | 96.31 318 | 83.83 299 | 96.53 353 | 79.36 359 | 89.90 298 | 96.12 326 |
|
eth_miper_zixun_eth | | | 94.68 228 | 94.41 216 | 95.47 285 | 97.64 223 | 91.71 291 | 96.73 328 | 98.07 254 | 92.71 245 | 93.64 261 | 97.21 264 | 90.54 165 | 98.17 301 | 93.38 227 | 89.76 299 | 96.54 300 |
|
FMVSNet5 | | | 91.81 301 | 90.92 304 | 94.49 315 | 97.21 257 | 92.09 281 | 98.00 237 | 97.55 291 | 89.31 330 | 90.86 323 | 95.61 339 | 74.48 354 | 95.32 361 | 85.57 337 | 89.70 300 | 96.07 328 |
|
miper_lstm_enhance | | | 94.33 253 | 94.07 233 | 95.11 296 | 97.75 215 | 90.97 304 | 97.22 295 | 98.03 261 | 91.67 280 | 92.76 291 | 96.97 288 | 90.03 173 | 97.78 328 | 92.51 257 | 89.64 301 | 96.56 297 |
|
v1192 | | | 94.32 254 | 93.58 267 | 96.53 235 | 96.10 315 | 94.45 224 | 98.50 170 | 98.17 233 | 91.54 283 | 94.19 240 | 97.06 278 | 86.95 244 | 98.43 270 | 90.14 295 | 89.57 302 | 96.70 280 |
|
v1144 | | | 94.59 236 | 93.92 243 | 96.60 225 | 96.21 309 | 94.78 212 | 98.59 153 | 98.14 238 | 91.86 275 | 94.21 239 | 97.02 283 | 87.97 222 | 98.41 278 | 91.72 275 | 89.57 302 | 96.61 290 |
|
Anonymous20240521 | | | 91.18 307 | 90.44 308 | 93.42 327 | 93.70 356 | 88.47 344 | 98.94 83 | 97.56 286 | 88.46 335 | 89.56 335 | 95.08 344 | 77.15 345 | 96.97 343 | 83.92 347 | 89.55 304 | 94.82 350 |
|
VPA-MVSNet | | | 95.75 167 | 95.11 182 | 97.69 156 | 97.24 254 | 97.27 96 | 98.94 83 | 99.23 13 | 95.13 138 | 95.51 199 | 97.32 256 | 85.73 263 | 98.91 221 | 97.33 88 | 89.55 304 | 96.89 257 |
|
v1240 | | | 94.06 273 | 93.29 277 | 96.34 252 | 96.03 319 | 93.90 241 | 98.44 177 | 98.17 233 | 91.18 300 | 94.13 243 | 97.01 285 | 86.05 259 | 98.42 271 | 89.13 316 | 89.50 306 | 96.70 280 |
|
K. test v3 | | | 92.55 297 | 91.91 299 | 94.48 316 | 95.64 329 | 89.24 331 | 99.07 56 | 94.88 355 | 94.04 181 | 86.78 348 | 97.59 238 | 77.64 341 | 97.64 331 | 92.08 264 | 89.43 307 | 96.57 295 |
|
v1921920 | | | 94.20 261 | 93.47 272 | 96.40 248 | 95.98 320 | 94.08 237 | 98.52 165 | 98.15 236 | 91.33 291 | 94.25 236 | 97.20 265 | 86.41 253 | 98.42 271 | 90.04 300 | 89.39 308 | 96.69 285 |
|
new_pmnet | | | 90.06 317 | 89.00 321 | 93.22 333 | 94.18 350 | 88.32 347 | 96.42 336 | 96.89 329 | 86.19 345 | 85.67 354 | 93.62 353 | 77.18 344 | 97.10 341 | 81.61 353 | 89.29 309 | 94.23 353 |
|
c3_l | | | 94.79 223 | 94.43 215 | 95.89 272 | 97.75 215 | 93.12 272 | 97.16 301 | 98.03 261 | 92.23 264 | 93.46 271 | 97.05 280 | 91.39 146 | 98.01 314 | 93.58 224 | 89.21 310 | 96.53 302 |
|
v144192 | | | 94.39 251 | 93.70 262 | 96.48 239 | 96.06 317 | 94.35 230 | 98.58 155 | 98.16 235 | 91.45 285 | 94.33 232 | 97.02 283 | 87.50 234 | 98.45 267 | 91.08 282 | 89.11 311 | 96.63 288 |
|
nrg030 | | | 96.28 145 | 95.72 150 | 97.96 137 | 96.90 279 | 98.15 61 | 99.39 10 | 98.31 206 | 95.47 118 | 94.42 228 | 98.35 168 | 92.09 130 | 98.69 242 | 97.50 82 | 89.05 312 | 97.04 241 |
|
DeepMVS_CX |  | | | | 86.78 345 | 97.09 268 | 72.30 371 | | 95.17 354 | 75.92 363 | 84.34 357 | 95.19 341 | 70.58 360 | 95.35 359 | 79.98 358 | 89.04 313 | 92.68 362 |
|
tfpnnormal | | | 93.66 278 | 92.70 287 | 96.55 234 | 96.94 275 | 95.94 158 | 98.97 77 | 99.19 16 | 91.04 302 | 91.38 318 | 97.34 254 | 84.94 276 | 98.61 250 | 85.45 339 | 89.02 314 | 95.11 345 |
|
Anonymous20231211 | | | 94.10 269 | 93.26 278 | 96.61 223 | 99.11 112 | 94.28 231 | 99.01 69 | 98.88 51 | 86.43 344 | 92.81 289 | 97.57 240 | 81.66 310 | 98.68 245 | 94.83 181 | 89.02 314 | 96.88 258 |
|
v2v482 | | | 94.69 226 | 94.03 234 | 96.65 217 | 96.17 312 | 94.79 211 | 98.67 142 | 98.08 252 | 92.72 244 | 94.00 249 | 97.16 266 | 87.69 231 | 98.45 267 | 92.91 243 | 88.87 316 | 96.72 276 |
|
V42 | | | 94.78 224 | 94.14 230 | 96.70 214 | 96.33 307 | 95.22 188 | 98.97 77 | 98.09 250 | 92.32 260 | 94.31 233 | 97.06 278 | 88.39 211 | 98.55 257 | 92.90 244 | 88.87 316 | 96.34 318 |
|
WR-MVS | | | 95.15 201 | 94.46 211 | 97.22 179 | 96.67 292 | 96.45 132 | 98.21 208 | 98.81 80 | 94.15 177 | 93.16 279 | 97.69 228 | 87.51 232 | 98.30 291 | 95.29 171 | 88.62 318 | 96.90 256 |
|
FPMVS | | | 77.62 334 | 77.14 334 | 79.05 352 | 79.25 375 | 60.97 376 | 95.79 343 | 95.94 345 | 65.96 366 | 67.93 369 | 94.40 348 | 37.73 375 | 88.88 371 | 68.83 368 | 88.46 319 | 87.29 365 |
|
v10 | | | 94.29 256 | 93.55 268 | 96.51 237 | 96.39 304 | 94.80 210 | 98.99 73 | 98.19 225 | 91.35 290 | 93.02 285 | 96.99 286 | 88.09 219 | 98.41 278 | 90.50 292 | 88.41 320 | 96.33 320 |
|
test_part1 | | | 94.82 220 | 93.82 251 | 97.82 144 | 98.84 136 | 97.82 77 | 99.03 63 | 98.81 80 | 92.31 262 | 92.51 301 | 97.89 210 | 81.96 307 | 98.67 246 | 94.80 184 | 88.24 321 | 96.98 244 |
|
CP-MVSNet | | | 94.94 216 | 94.30 220 | 96.83 205 | 96.72 289 | 95.56 174 | 99.11 49 | 98.95 35 | 93.89 190 | 92.42 305 | 97.90 208 | 87.19 238 | 98.12 305 | 94.32 200 | 88.21 322 | 96.82 266 |
|
MIMVSNet1 | | | 89.67 320 | 88.28 324 | 93.82 324 | 92.81 361 | 91.08 303 | 98.01 235 | 97.45 300 | 87.95 337 | 87.90 345 | 95.87 330 | 67.63 364 | 94.56 365 | 78.73 362 | 88.18 323 | 95.83 333 |
|
PS-CasMVS | | | 94.67 231 | 93.99 240 | 96.71 212 | 96.68 291 | 95.26 187 | 99.13 46 | 99.03 26 | 93.68 207 | 92.33 306 | 97.95 204 | 85.35 270 | 98.10 306 | 93.59 223 | 88.16 324 | 96.79 267 |
|
WR-MVS_H | | | 95.05 207 | 94.46 211 | 96.81 207 | 96.86 281 | 95.82 167 | 99.24 26 | 99.24 11 | 93.87 192 | 92.53 299 | 96.84 300 | 90.37 167 | 98.24 298 | 93.24 232 | 87.93 325 | 96.38 317 |
|
v8 | | | 94.47 246 | 93.77 256 | 96.57 229 | 96.36 305 | 94.83 208 | 99.05 59 | 98.19 225 | 91.92 272 | 93.16 279 | 96.97 288 | 88.82 203 | 98.48 262 | 91.69 276 | 87.79 326 | 96.39 316 |
|
v7n | | | 94.19 262 | 93.43 273 | 96.47 240 | 95.90 322 | 94.38 229 | 99.26 24 | 98.34 202 | 91.99 270 | 92.76 291 | 97.13 267 | 88.31 212 | 98.52 260 | 89.48 311 | 87.70 327 | 96.52 305 |
|
UniMVSNet (Re) | | | 95.78 166 | 95.19 178 | 97.58 164 | 96.99 273 | 97.47 89 | 98.79 118 | 99.18 17 | 95.60 111 | 93.92 251 | 97.04 281 | 91.68 138 | 98.48 262 | 95.80 153 | 87.66 328 | 96.79 267 |
|
baseline1 | | | 95.84 163 | 95.12 181 | 98.01 133 | 98.49 164 | 95.98 150 | 98.73 127 | 97.03 319 | 95.37 125 | 96.22 188 | 98.19 186 | 89.96 174 | 99.16 181 | 94.60 189 | 87.48 329 | 98.90 176 |
|
Gipuma |  | | 78.40 332 | 76.75 335 | 83.38 349 | 95.54 332 | 80.43 367 | 79.42 370 | 97.40 304 | 64.67 367 | 73.46 365 | 80.82 368 | 45.65 372 | 93.14 367 | 66.32 369 | 87.43 330 | 76.56 370 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
NR-MVSNet | | | 94.98 212 | 94.16 228 | 97.44 170 | 96.53 297 | 97.22 102 | 98.74 123 | 98.95 35 | 94.96 149 | 89.25 337 | 97.69 228 | 89.32 185 | 98.18 300 | 94.59 191 | 87.40 331 | 96.92 249 |
|
VPNet | | | 94.99 210 | 94.19 225 | 97.40 174 | 97.16 263 | 96.57 127 | 98.71 132 | 98.97 31 | 95.67 108 | 94.84 210 | 98.24 183 | 80.36 321 | 98.67 246 | 96.46 129 | 87.32 332 | 96.96 246 |
|
UniMVSNet_NR-MVSNet | | | 95.71 169 | 95.15 179 | 97.40 174 | 96.84 282 | 96.97 109 | 98.74 123 | 99.24 11 | 95.16 136 | 93.88 253 | 97.72 227 | 91.68 138 | 98.31 289 | 95.81 151 | 87.25 333 | 96.92 249 |
|
DU-MVS | | | 95.42 183 | 94.76 196 | 97.40 174 | 96.53 297 | 96.97 109 | 98.66 145 | 98.99 30 | 95.43 120 | 93.88 253 | 97.69 228 | 88.57 206 | 98.31 289 | 95.81 151 | 87.25 333 | 96.92 249 |
|
v148 | | | 94.29 256 | 93.76 258 | 95.91 270 | 96.10 315 | 92.93 274 | 98.58 155 | 97.97 264 | 92.59 249 | 93.47 270 | 96.95 292 | 88.53 209 | 98.32 287 | 92.56 254 | 87.06 335 | 96.49 311 |
|
Baseline_NR-MVSNet | | | 94.35 252 | 93.81 252 | 95.96 268 | 96.20 310 | 94.05 238 | 98.61 152 | 96.67 338 | 91.44 286 | 93.85 255 | 97.60 237 | 88.57 206 | 98.14 303 | 94.39 196 | 86.93 336 | 95.68 336 |
|
PEN-MVS | | | 94.42 249 | 93.73 260 | 96.49 238 | 96.28 308 | 94.84 206 | 99.17 39 | 99.00 28 | 93.51 214 | 92.23 308 | 97.83 219 | 86.10 258 | 97.90 322 | 92.55 255 | 86.92 337 | 96.74 273 |
|
TranMVSNet+NR-MVSNet | | | 95.14 202 | 94.48 209 | 97.11 187 | 96.45 302 | 96.36 137 | 99.03 63 | 99.03 26 | 95.04 145 | 93.58 263 | 97.93 206 | 88.27 213 | 98.03 313 | 94.13 206 | 86.90 338 | 96.95 248 |
|
MDA-MVSNet_test_wron | | | 90.71 312 | 89.38 317 | 94.68 310 | 94.83 344 | 90.78 309 | 97.19 297 | 97.46 298 | 87.60 338 | 72.41 367 | 95.72 335 | 86.51 249 | 96.71 350 | 85.92 335 | 86.80 339 | 96.56 297 |
|
YYNet1 | | | 90.70 313 | 89.39 316 | 94.62 312 | 94.79 346 | 90.65 312 | 97.20 296 | 97.46 298 | 87.54 339 | 72.54 366 | 95.74 331 | 86.51 249 | 96.66 351 | 86.00 334 | 86.76 340 | 96.54 300 |
|
MDA-MVSNet-bldmvs | | | 89.97 318 | 88.35 323 | 94.83 306 | 95.21 339 | 91.34 296 | 97.64 267 | 97.51 294 | 88.36 336 | 71.17 368 | 96.13 326 | 79.22 327 | 96.63 352 | 83.65 348 | 86.27 341 | 96.52 305 |
|
test20.03 | | | 90.89 311 | 90.38 309 | 92.43 336 | 93.48 357 | 88.14 349 | 98.33 191 | 97.56 286 | 93.40 219 | 87.96 344 | 96.71 305 | 80.69 320 | 94.13 366 | 79.15 360 | 86.17 342 | 95.01 349 |
|
DTE-MVSNet | | | 93.98 275 | 93.26 278 | 96.14 260 | 96.06 317 | 94.39 228 | 99.20 35 | 98.86 64 | 93.06 232 | 91.78 314 | 97.81 221 | 85.87 262 | 97.58 333 | 90.53 291 | 86.17 342 | 96.46 314 |
|
pm-mvs1 | | | 93.94 276 | 93.06 280 | 96.59 226 | 96.49 300 | 95.16 189 | 98.95 81 | 98.03 261 | 92.32 260 | 91.08 321 | 97.84 216 | 84.54 284 | 98.41 278 | 92.16 262 | 86.13 344 | 96.19 325 |
|
lessismore_v0 | | | | | 94.45 319 | 94.93 343 | 88.44 345 | | 91.03 372 | | 86.77 349 | 97.64 234 | 76.23 347 | 98.42 271 | 90.31 294 | 85.64 345 | 96.51 308 |
|
pmmvs6 | | | 91.77 302 | 90.63 306 | 95.17 294 | 94.69 348 | 91.24 301 | 98.67 142 | 97.92 269 | 86.14 346 | 89.62 333 | 97.56 242 | 75.79 349 | 98.34 285 | 90.75 289 | 84.56 346 | 95.94 331 |
|
IB-MVS | | 91.98 17 | 93.27 286 | 91.97 297 | 97.19 181 | 97.47 238 | 93.41 261 | 97.09 304 | 95.99 343 | 93.32 222 | 92.47 303 | 95.73 333 | 78.06 336 | 99.53 148 | 94.59 191 | 82.98 347 | 98.62 194 |
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 |
ambc | | | | | 89.49 344 | 86.66 369 | 75.78 369 | 92.66 362 | 96.72 335 | | 86.55 350 | 92.50 358 | 46.01 371 | 97.90 322 | 90.32 293 | 82.09 348 | 94.80 351 |
|
Patchmatch-RL test | | | 91.49 304 | 90.85 305 | 93.41 328 | 91.37 364 | 84.40 359 | 92.81 361 | 95.93 346 | 91.87 274 | 87.25 346 | 94.87 345 | 88.99 195 | 96.53 353 | 92.54 256 | 82.00 349 | 99.30 130 |
|
PM-MVS | | | 87.77 326 | 86.55 330 | 91.40 342 | 91.03 366 | 83.36 363 | 96.92 312 | 95.18 353 | 91.28 295 | 86.48 351 | 93.42 354 | 53.27 370 | 96.74 347 | 89.43 312 | 81.97 350 | 94.11 355 |
|
pmmvs-eth3d | | | 90.36 315 | 89.05 320 | 94.32 320 | 91.10 365 | 92.12 280 | 97.63 270 | 96.95 324 | 88.86 333 | 84.91 356 | 93.13 355 | 78.32 332 | 96.74 347 | 88.70 318 | 81.81 351 | 94.09 356 |
|
h-mvs33 | | | 96.17 148 | 95.62 159 | 97.81 145 | 99.03 117 | 94.45 224 | 98.64 147 | 98.75 106 | 97.48 20 | 98.67 67 | 98.72 131 | 89.76 176 | 99.86 53 | 97.95 45 | 81.59 352 | 99.11 155 |
|
TransMVSNet (Re) | | | 92.67 296 | 91.51 301 | 96.15 259 | 96.58 295 | 94.65 213 | 98.90 88 | 96.73 334 | 90.86 304 | 89.46 336 | 97.86 213 | 85.62 265 | 98.09 308 | 86.45 331 | 81.12 353 | 95.71 335 |
|
PMVS |  | 61.03 23 | 65.95 338 | 63.57 342 | 73.09 355 | 57.90 380 | 51.22 381 | 85.05 368 | 93.93 366 | 54.45 369 | 44.32 375 | 83.57 365 | 13.22 379 | 89.15 370 | 58.68 371 | 81.00 354 | 78.91 369 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
AUN-MVS | | | 94.53 241 | 93.73 260 | 96.92 201 | 98.50 162 | 93.52 257 | 98.34 189 | 98.10 245 | 93.83 195 | 95.94 197 | 97.98 202 | 85.59 266 | 99.03 203 | 94.35 198 | 80.94 355 | 98.22 209 |
|
hse-mvs2 | | | 95.71 169 | 95.30 174 | 96.93 198 | 98.50 162 | 93.53 256 | 98.36 187 | 98.10 245 | 97.48 20 | 98.67 67 | 97.99 200 | 89.76 176 | 99.02 206 | 97.95 45 | 80.91 356 | 98.22 209 |
|
UnsupCasMVSNet_eth | | | 90.99 310 | 89.92 313 | 94.19 322 | 94.08 352 | 89.83 321 | 97.13 303 | 98.67 133 | 93.69 205 | 85.83 353 | 96.19 325 | 75.15 351 | 96.74 347 | 89.14 315 | 79.41 357 | 96.00 329 |
|
test_method | | | 79.03 330 | 78.17 333 | 81.63 350 | 86.06 370 | 54.40 380 | 82.75 369 | 96.89 329 | 39.54 373 | 80.98 361 | 95.57 340 | 58.37 369 | 94.73 364 | 84.74 345 | 78.61 358 | 95.75 334 |
|
TDRefinement | | | 91.06 309 | 89.68 314 | 95.21 292 | 85.35 371 | 91.49 295 | 98.51 169 | 97.07 316 | 91.47 284 | 88.83 341 | 97.84 216 | 77.31 342 | 99.09 196 | 92.79 247 | 77.98 359 | 95.04 347 |
|
new-patchmatchnet | | | 88.50 325 | 87.45 328 | 91.67 341 | 90.31 367 | 85.89 358 | 97.16 301 | 97.33 306 | 89.47 327 | 83.63 358 | 92.77 356 | 76.38 346 | 95.06 363 | 82.70 350 | 77.29 360 | 94.06 357 |
|
KD-MVS_self_test | | | 90.38 314 | 89.38 317 | 93.40 329 | 92.85 360 | 88.94 338 | 97.95 240 | 97.94 267 | 90.35 313 | 90.25 328 | 93.96 352 | 79.82 323 | 95.94 357 | 84.62 346 | 76.69 361 | 95.33 340 |
|
pmmvs3 | | | 86.67 329 | 84.86 332 | 92.11 340 | 88.16 368 | 87.19 356 | 96.63 330 | 94.75 357 | 79.88 360 | 87.22 347 | 92.75 357 | 66.56 365 | 95.20 362 | 81.24 354 | 76.56 362 | 93.96 358 |
|
CL-MVSNet_self_test | | | 90.11 316 | 89.14 319 | 93.02 334 | 91.86 363 | 88.23 348 | 96.51 334 | 98.07 254 | 90.49 307 | 90.49 327 | 94.41 347 | 84.75 280 | 95.34 360 | 80.79 355 | 74.95 363 | 95.50 338 |
|
LCM-MVSNet | | | 78.70 331 | 76.24 336 | 86.08 346 | 77.26 377 | 71.99 372 | 94.34 358 | 96.72 335 | 61.62 368 | 76.53 363 | 89.33 362 | 33.91 377 | 92.78 368 | 81.85 352 | 74.60 364 | 93.46 360 |
|
UnsupCasMVSNet_bld | | | 87.17 327 | 85.12 331 | 93.31 331 | 91.94 362 | 88.77 339 | 94.92 353 | 98.30 212 | 84.30 355 | 82.30 359 | 90.04 361 | 63.96 368 | 97.25 339 | 85.85 336 | 74.47 365 | 93.93 359 |
|
PVSNet_0 | | 88.72 19 | 91.28 306 | 90.03 312 | 95.00 299 | 97.99 203 | 87.29 355 | 94.84 354 | 98.50 172 | 92.06 269 | 89.86 331 | 95.19 341 | 79.81 324 | 99.39 164 | 92.27 261 | 69.79 366 | 98.33 206 |
|
KD-MVS_2432*1600 | | | 89.61 321 | 87.96 325 | 94.54 313 | 94.06 353 | 91.59 293 | 95.59 347 | 97.63 282 | 89.87 321 | 88.95 339 | 94.38 349 | 78.28 333 | 96.82 345 | 84.83 342 | 68.05 367 | 95.21 342 |
|
miper_refine_blended | | | 89.61 321 | 87.96 325 | 94.54 313 | 94.06 353 | 91.59 293 | 95.59 347 | 97.63 282 | 89.87 321 | 88.95 339 | 94.38 349 | 78.28 333 | 96.82 345 | 84.83 342 | 68.05 367 | 95.21 342 |
|
PMMVS2 | | | 77.95 333 | 75.44 337 | 85.46 347 | 82.54 372 | 74.95 370 | 94.23 359 | 93.08 367 | 72.80 365 | 74.68 364 | 87.38 363 | 36.36 376 | 91.56 369 | 73.95 366 | 63.94 369 | 89.87 364 |
|
MVE |  | 62.14 22 | 63.28 341 | 59.38 344 | 74.99 353 | 74.33 378 | 65.47 374 | 85.55 367 | 80.50 379 | 52.02 371 | 51.10 373 | 75.00 372 | 10.91 382 | 80.50 373 | 51.60 372 | 53.40 370 | 78.99 368 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
E-PMN | | | 64.94 339 | 64.25 341 | 67.02 356 | 82.28 373 | 59.36 378 | 91.83 364 | 85.63 376 | 52.69 370 | 60.22 371 | 77.28 370 | 41.06 374 | 80.12 374 | 46.15 373 | 41.14 371 | 61.57 372 |
|
EMVS | | | 64.07 340 | 63.26 343 | 66.53 357 | 81.73 374 | 58.81 379 | 91.85 363 | 84.75 377 | 51.93 372 | 59.09 372 | 75.13 371 | 43.32 373 | 79.09 375 | 42.03 374 | 39.47 372 | 61.69 371 |
|
ANet_high | | | 69.08 336 | 65.37 340 | 80.22 351 | 65.99 379 | 71.96 373 | 90.91 365 | 90.09 373 | 82.62 356 | 49.93 374 | 78.39 369 | 29.36 378 | 81.75 372 | 62.49 370 | 38.52 373 | 86.95 367 |
|
tmp_tt | | | 68.90 337 | 66.97 339 | 74.68 354 | 50.78 381 | 59.95 377 | 87.13 366 | 83.47 378 | 38.80 374 | 62.21 370 | 96.23 322 | 64.70 367 | 76.91 376 | 88.91 317 | 30.49 374 | 87.19 366 |
|
wuyk23d | | | 30.17 342 | 30.18 346 | 30.16 358 | 78.61 376 | 43.29 382 | 66.79 371 | 14.21 382 | 17.31 375 | 14.82 378 | 11.93 378 | 11.55 381 | 41.43 377 | 37.08 375 | 19.30 375 | 5.76 375 |
|
testmvs | | | 21.48 344 | 24.95 347 | 11.09 360 | 14.89 382 | 6.47 384 | 96.56 332 | 9.87 383 | 7.55 376 | 17.93 376 | 39.02 374 | 9.43 383 | 5.90 379 | 16.56 377 | 12.72 376 | 20.91 374 |
|
test123 | | | 20.95 345 | 23.72 348 | 12.64 359 | 13.54 383 | 8.19 383 | 96.55 333 | 6.13 384 | 7.48 377 | 16.74 377 | 37.98 375 | 12.97 380 | 6.05 378 | 16.69 376 | 5.43 377 | 23.68 373 |
|
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 | | | 23.98 343 | 31.98 345 | 0.00 361 | 0.00 384 | 0.00 385 | 0.00 372 | 98.59 148 | 0.00 379 | 0.00 380 | 98.61 140 | 90.60 164 | 0.00 380 | 0.00 378 | 0.00 378 | 0.00 376 |
|
pcd_1.5k_mvsjas | | | 7.88 347 | 10.50 350 | 0.00 361 | 0.00 384 | 0.00 385 | 0.00 372 | 0.00 385 | 0.00 379 | 0.00 380 | 0.00 379 | 94.51 91 | 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 | | | 8.20 346 | 10.94 349 | 0.00 361 | 0.00 384 | 0.00 385 | 0.00 372 | 0.00 385 | 0.00 379 | 0.00 380 | 98.43 158 | 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 |
|
FOURS1 | | | | | | 99.82 1 | 98.66 26 | 99.69 1 | 98.95 35 | 97.46 23 | 99.39 15 | | | | | | |
|
test_one_0601 | | | | | | 99.66 28 | 99.25 2 | | 98.86 64 | 97.55 16 | 99.20 26 | 99.47 10 | 97.57 6 | | | | |
|
eth-test2 | | | | | | 0.00 384 | | | | | | | | | | | |
|
eth-test | | | | | | 0.00 384 | | | | | | | | | | | |
|
test_241102_ONE | | | | | | 99.71 21 | 99.24 5 | | 98.87 58 | 97.62 12 | 99.73 1 | 99.39 18 | 97.53 7 | 99.74 111 | | | |
|
save fliter | | | | | | 99.46 55 | 98.38 40 | 98.21 208 | 98.71 118 | 97.95 3 | | | | | | | |
|
test0726 | | | | | | 99.72 13 | 99.25 2 | 99.06 57 | 98.88 51 | 97.62 12 | 99.56 6 | 99.50 5 | 97.42 9 | | | | |
|
GSMVS | | | | | | | | | | | | | | | | | 99.20 139 |
|
test_part2 | | | | | | 99.63 31 | 99.18 10 | | | | 99.27 21 | | | | | | |
|
sam_mvs1 | | | | | | | | | | | | | 89.45 182 | | | | 99.20 139 |
|
sam_mvs | | | | | | | | | | | | | 88.99 195 | | | | |
|
MTGPA |  | | | | | | | | 98.74 108 | | | | | | | | |
|
test_post1 | | | | | | | | 96.68 329 | | | | 30.43 377 | 87.85 227 | 98.69 242 | 92.59 252 | | |
|
test_post | | | | | | | | | | | | 31.83 376 | 88.83 202 | 98.91 221 | | | |
|
patchmatchnet-post | | | | | | | | | | | | 95.10 343 | 89.42 183 | 98.89 225 | | | |
|
MTMP | | | | | | | | 98.89 92 | 94.14 364 | | | | | | | | |
|
gm-plane-assit | | | | | | 95.88 323 | 87.47 353 | | | 89.74 324 | | 96.94 293 | | 99.19 179 | 93.32 231 | | |
|
TEST9 | | | | | | 99.31 74 | 98.50 34 | 97.92 242 | 98.73 112 | 92.63 246 | 97.74 125 | 98.68 134 | 96.20 27 | 99.80 84 | | | |
|
test_8 | | | | | | 99.29 82 | 98.44 36 | 97.89 248 | 98.72 114 | 92.98 235 | 97.70 128 | 98.66 137 | 96.20 27 | 99.80 84 | | | |
|
agg_prior | | | | | | 99.30 79 | 98.38 40 | | 98.72 114 | | 97.57 138 | | | 99.81 75 | | | |
|
test_prior4 | | | | | | | 98.01 67 | 97.86 251 | | | | | | | | | |
|
test_prior | | | | | 99.19 46 | 99.31 74 | 98.22 55 | | 98.84 69 | | | | | 99.70 119 | | | 99.65 73 |
|
旧先验2 | | | | | | | | 97.57 273 | | 91.30 293 | 98.67 67 | | | 99.80 84 | 95.70 160 | | |
|
新几何2 | | | | | | | | 97.64 267 | | | | | | | | | |
|
无先验 | | | | | | | | 97.58 272 | 98.72 114 | 91.38 287 | | | | 99.87 48 | 93.36 229 | | 99.60 85 |
|
原ACMM2 | | | | | | | | 97.67 265 | | | | | | | | | |
|
testdata2 | | | | | | | | | | | | | | 99.89 39 | 91.65 277 | | |
|
segment_acmp | | | | | | | | | | | | | 96.85 14 | | | | |
|
testdata1 | | | | | | | | 97.32 289 | | 96.34 84 | | | | | | | |
|
plane_prior7 | | | | | | 97.42 244 | 94.63 215 | | | | | | | | | | |
|
plane_prior6 | | | | | | 97.35 249 | 94.61 218 | | | | | | 87.09 240 | | | | |
|
plane_prior4 | | | | | | | | | | | | 98.28 177 | | | | | |
|
plane_prior3 | | | | | | | 94.61 218 | | | 97.02 55 | 95.34 200 | | | | | | |
|
plane_prior2 | | | | | | | | 98.80 114 | | 97.28 36 | | | | | | | |
|
plane_prior1 | | | | | | 97.37 248 | | | | | | | | | | | |
|
n2 | | | | | | | | | 0.00 385 | | | | | | | | |
|
nn | | | | | | | | | 0.00 385 | | | | | | | | |
|
door-mid | | | | | | | | | 94.37 360 | | | | | | | | |
|
test11 | | | | | | | | | 98.66 136 | | | | | | | | |
|
door | | | | | | | | | 94.64 358 | | | | | | | | |
|
HQP5-MVS | | | | | | | 94.25 234 | | | | | | | | | | |
|
HQP-NCC | | | | | | 97.20 258 | | 98.05 231 | | 96.43 80 | 94.45 223 | | | | | | |
|
ACMP_Plane | | | | | | 97.20 258 | | 98.05 231 | | 96.43 80 | 94.45 223 | | | | | | |
|
BP-MVS | | | | | | | | | | | | | | | 95.30 169 | | |
|
HQP4-MVS | | | | | | | | | | | 94.45 223 | | | 98.96 214 | | | 96.87 260 |
|
HQP2-MVS | | | | | | | | | | | | | 86.75 246 | | | | |
|
NP-MVS | | | | | | 97.28 252 | 94.51 223 | | | | | 97.73 225 | | | | | |
|
MDTV_nov1_ep13_2view | | | | | | | 84.26 360 | 96.89 319 | | 90.97 303 | 97.90 118 | | 89.89 175 | | 93.91 213 | | 99.18 148 |
|
Test By Simon | | | | | | | | | | | | | 94.64 87 | | | | |
|