LTVRE_ROB | | 86.10 1 | 93.04 3 | 93.44 2 | 91.82 23 | 93.73 66 | 85.72 33 | 96.79 1 | 95.51 8 | 88.86 14 | 95.63 8 | 96.99 8 | 84.81 70 | 93.16 141 | 91.10 1 | 97.53 74 | 96.58 30 |
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 |
DVP-MVS++ | | | 90.07 42 | 91.09 35 | 87.00 101 | 91.55 133 | 72.64 144 | 96.19 2 | 94.10 38 | 85.33 32 | 93.49 38 | 94.64 58 | 81.12 120 | 95.88 16 | 87.41 21 | 95.94 132 | 92.48 163 |
|
FOURS1 | | | | | | 96.08 12 | 87.41 13 | 96.19 2 | 95.83 4 | 92.95 2 | 96.57 2 | | | | | | |
|
TDRefinement | | | 93.52 2 | 93.39 3 | 93.88 1 | 95.94 15 | 90.26 3 | 95.70 4 | 96.46 2 | 90.58 8 | 92.86 48 | 96.29 16 | 88.16 35 | 94.17 98 | 86.07 44 | 98.48 18 | 97.22 18 |
|
LCM-MVSNet | | | 95.70 1 | 96.40 1 | 93.61 2 | 98.67 1 | 85.39 34 | 95.54 5 | 97.36 1 | 96.97 1 | 99.04 1 | 99.05 1 | 96.61 1 | 95.92 14 | 85.07 53 | 99.27 1 | 99.54 1 |
|
LS3D | | | 90.60 33 | 90.34 50 | 91.38 27 | 89.03 188 | 84.23 47 | 93.58 6 | 94.68 19 | 90.65 7 | 90.33 93 | 93.95 97 | 84.50 72 | 95.37 53 | 80.87 99 | 95.50 149 | 94.53 80 |
|
UA-Net | | | 91.49 17 | 91.53 22 | 91.39 26 | 94.98 36 | 82.95 56 | 93.52 7 | 92.79 96 | 88.22 20 | 88.53 132 | 97.64 2 | 83.45 84 | 94.55 84 | 86.02 47 | 98.60 13 | 96.67 27 |
|
HPM-MVS |  | | 92.13 9 | 92.20 11 | 91.91 17 | 95.58 26 | 84.67 43 | 93.51 8 | 94.85 16 | 82.88 57 | 91.77 70 | 93.94 98 | 90.55 13 | 95.73 30 | 88.50 7 | 98.23 29 | 95.33 54 |
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023 |
CP-MVS | | | 91.67 14 | 91.58 21 | 91.96 14 | 95.29 32 | 87.62 12 | 93.38 9 | 93.36 65 | 83.16 53 | 91.06 81 | 94.00 90 | 88.26 32 | 95.71 31 | 87.28 26 | 98.39 21 | 92.55 160 |
|
COLMAP_ROB |  | 83.01 3 | 91.97 11 | 91.95 12 | 92.04 12 | 93.68 67 | 86.15 23 | 93.37 10 | 95.10 14 | 90.28 9 | 92.11 62 | 95.03 44 | 89.75 21 | 94.93 69 | 79.95 109 | 98.27 27 | 95.04 64 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
ACMMP |  | | 91.91 12 | 91.87 17 | 92.03 13 | 95.53 27 | 85.91 27 | 93.35 11 | 94.16 31 | 82.52 61 | 92.39 59 | 94.14 84 | 89.15 23 | 95.62 35 | 87.35 23 | 98.24 28 | 94.56 77 |
Qingshan Xu, Weihang Kong, Wenbing Tao, Marc Pollefeys: Multi-Scale Geometric Consistency Guided and Planar Prior Assisted Multi-View Stereo. IEEE Transactions on Pattern Analysis and Machine Intelligence |
abl_6 | | | 93.02 4 | 93.16 4 | 92.60 4 | 94.73 44 | 88.99 7 | 93.26 12 | 94.19 30 | 89.11 12 | 94.43 16 | 95.27 38 | 91.86 3 | 95.09 64 | 87.54 18 | 98.02 40 | 93.71 116 |
|
HPM-MVS_fast | | | 92.50 5 | 92.54 6 | 92.37 6 | 95.93 16 | 85.81 32 | 92.99 13 | 94.23 26 | 85.21 34 | 92.51 56 | 95.13 42 | 90.65 10 | 95.34 54 | 88.06 9 | 98.15 35 | 95.95 41 |
|
SR-MVS-dyc-post | | | 92.41 6 | 92.41 7 | 92.39 5 | 94.13 55 | 88.95 8 | 92.87 14 | 94.16 31 | 88.75 16 | 93.79 29 | 94.43 65 | 88.83 24 | 95.51 45 | 87.16 28 | 97.60 67 | 92.73 151 |
|
RE-MVS-def | | | | 92.61 5 | | 94.13 55 | 88.95 8 | 92.87 14 | 94.16 31 | 88.75 16 | 93.79 29 | 94.43 65 | 90.64 11 | | 87.16 28 | 97.60 67 | 92.73 151 |
|
APDe-MVS | | | 91.22 24 | 91.92 13 | 89.14 67 | 92.97 83 | 78.04 93 | 92.84 16 | 94.14 35 | 83.33 51 | 93.90 25 | 95.73 27 | 88.77 26 | 96.41 1 | 87.60 16 | 97.98 44 | 92.98 142 |
|
MSP-MVS | | | 89.08 65 | 88.16 78 | 91.83 21 | 95.76 18 | 86.14 24 | 92.75 17 | 93.90 46 | 78.43 112 | 89.16 122 | 92.25 145 | 72.03 217 | 96.36 2 | 88.21 8 | 90.93 256 | 92.98 142 |
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 |
mPP-MVS | | | 91.69 13 | 91.47 24 | 92.37 6 | 96.04 13 | 88.48 10 | 92.72 18 | 92.60 101 | 83.09 54 | 91.54 72 | 94.25 77 | 87.67 43 | 95.51 45 | 87.21 27 | 98.11 36 | 93.12 137 |
|
XVS | | | 91.54 15 | 91.36 26 | 92.08 10 | 95.64 24 | 86.25 21 | 92.64 19 | 93.33 67 | 85.07 35 | 89.99 99 | 94.03 88 | 86.57 56 | 95.80 24 | 87.35 23 | 97.62 65 | 94.20 92 |
|
X-MVStestdata | | | 85.04 124 | 82.70 168 | 92.08 10 | 95.64 24 | 86.25 21 | 92.64 19 | 93.33 67 | 85.07 35 | 89.99 99 | 16.05 374 | 86.57 56 | 95.80 24 | 87.35 23 | 97.62 65 | 94.20 92 |
|
region2R | | | 91.44 20 | 91.30 32 | 91.87 19 | 95.75 19 | 85.90 28 | 92.63 21 | 93.30 72 | 81.91 68 | 90.88 86 | 94.21 78 | 87.75 41 | 95.87 18 | 87.60 16 | 97.71 61 | 93.83 108 |
|
HFP-MVS | | | 91.30 21 | 91.39 25 | 91.02 33 | 95.43 29 | 84.66 44 | 92.58 22 | 93.29 73 | 81.99 66 | 91.47 73 | 93.96 94 | 88.35 30 | 95.56 38 | 87.74 11 | 97.74 59 | 92.85 146 |
|
ACMMPR | | | 91.49 17 | 91.35 28 | 91.92 16 | 95.74 20 | 85.88 29 | 92.58 22 | 93.25 76 | 81.99 66 | 91.40 75 | 94.17 82 | 87.51 44 | 95.87 18 | 87.74 11 | 97.76 57 | 93.99 101 |
|
SR-MVS | | | 92.23 8 | 92.34 9 | 91.91 17 | 94.89 39 | 87.85 11 | 92.51 24 | 93.87 49 | 88.20 21 | 93.24 42 | 94.02 89 | 90.15 17 | 95.67 33 | 86.82 32 | 97.34 80 | 92.19 180 |
|
TSAR-MVS + MP. | | | 88.14 76 | 87.82 81 | 89.09 68 | 95.72 22 | 76.74 116 | 92.49 25 | 91.19 138 | 67.85 242 | 86.63 168 | 94.84 49 | 79.58 136 | 95.96 13 | 87.62 14 | 94.50 181 | 94.56 77 |
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition |
APD-MVS_3200maxsize | | | 92.05 10 | 92.24 10 | 91.48 24 | 93.02 81 | 85.17 36 | 92.47 26 | 95.05 15 | 87.65 24 | 93.21 43 | 94.39 71 | 90.09 18 | 95.08 65 | 86.67 34 | 97.60 67 | 94.18 94 |
|
MP-MVS |  | | 91.14 27 | 90.91 43 | 91.83 21 | 96.18 11 | 86.88 16 | 92.20 27 | 93.03 87 | 82.59 60 | 88.52 133 | 94.37 72 | 86.74 53 | 95.41 52 | 86.32 38 | 98.21 30 | 93.19 135 |
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo. |
ZNCC-MVS | | | 91.26 23 | 91.34 29 | 91.01 35 | 95.73 21 | 83.05 54 | 92.18 28 | 94.22 27 | 80.14 89 | 91.29 78 | 93.97 91 | 87.93 40 | 95.87 18 | 88.65 4 | 97.96 47 | 94.12 98 |
|
CPTT-MVS | | | 89.39 59 | 88.98 68 | 90.63 41 | 95.09 34 | 86.95 15 | 92.09 29 | 92.30 107 | 79.74 92 | 87.50 149 | 92.38 138 | 81.42 117 | 93.28 136 | 83.07 74 | 97.24 83 | 91.67 196 |
|
MTAPA | | | 91.52 16 | 91.60 20 | 91.29 29 | 96.59 4 | 86.29 19 | 92.02 30 | 91.81 121 | 84.07 40 | 92.00 65 | 94.40 69 | 86.63 54 | 95.28 57 | 88.59 5 | 98.31 24 | 92.30 172 |
|
test1172 | | | 92.40 7 | 92.41 7 | 92.37 6 | 94.68 45 | 89.04 6 | 91.98 31 | 93.62 57 | 90.14 11 | 93.63 36 | 94.16 83 | 88.83 24 | 95.51 45 | 87.11 30 | 97.54 73 | 92.54 161 |
|
MVSFormer | | | 82.23 178 | 81.57 187 | 84.19 161 | 85.54 255 | 69.26 183 | 91.98 31 | 90.08 172 | 71.54 200 | 76.23 303 | 85.07 287 | 58.69 286 | 94.27 89 | 86.26 39 | 88.77 281 | 89.03 249 |
|
test_djsdf | | | 89.62 54 | 89.01 66 | 91.45 25 | 92.36 99 | 82.98 55 | 91.98 31 | 90.08 172 | 71.54 200 | 94.28 21 | 96.54 13 | 81.57 115 | 94.27 89 | 86.26 39 | 96.49 107 | 97.09 20 |
|
OurMVSNet-221017-0 | | | 90.01 46 | 89.74 55 | 90.83 37 | 93.16 79 | 80.37 71 | 91.91 34 | 93.11 80 | 81.10 77 | 95.32 10 | 97.24 5 | 72.94 205 | 94.85 72 | 85.07 53 | 97.78 56 | 97.26 16 |
|
EGC-MVSNET | | | 74.79 269 | 69.99 303 | 89.19 66 | 94.89 39 | 87.00 14 | 91.89 35 | 86.28 232 | 1.09 375 | 2.23 377 | 95.98 24 | 81.87 112 | 89.48 242 | 79.76 111 | 95.96 130 | 91.10 206 |
|
GST-MVS | | | 90.96 28 | 91.01 39 | 90.82 38 | 95.45 28 | 82.73 57 | 91.75 36 | 93.74 52 | 80.98 79 | 91.38 76 | 93.80 101 | 87.20 48 | 95.80 24 | 87.10 31 | 97.69 62 | 93.93 104 |
|
EPP-MVSNet | | | 85.47 115 | 85.04 128 | 86.77 106 | 91.52 136 | 69.37 180 | 91.63 37 | 87.98 208 | 81.51 73 | 87.05 158 | 91.83 154 | 66.18 245 | 95.29 55 | 70.75 207 | 96.89 91 | 95.64 46 |
|
SteuartSystems-ACMMP | | | 91.16 26 | 91.36 26 | 90.55 42 | 93.91 61 | 80.97 68 | 91.49 38 | 93.48 63 | 82.82 58 | 92.60 55 | 93.97 91 | 88.19 33 | 96.29 4 | 87.61 15 | 98.20 32 | 94.39 86 |
Skip Steuart: Steuart Systems R&D Blog. |
bld_raw_conf005 | | | 88.83 70 | 88.48 75 | 89.85 52 | 92.53 94 | 76.54 117 | 91.30 39 | 93.28 75 | 74.96 153 | 93.26 41 | 96.02 23 | 70.41 225 | 95.63 34 | 86.73 33 | 97.87 52 | 97.39 14 |
|
3Dnovator+ | | 83.92 2 | 89.97 49 | 89.66 56 | 90.92 36 | 91.27 142 | 81.66 64 | 91.25 40 | 94.13 36 | 88.89 13 | 88.83 127 | 94.26 76 | 77.55 153 | 95.86 21 | 84.88 56 | 95.87 136 | 95.24 58 |
|
IS-MVSNet | | | 86.66 96 | 86.82 99 | 86.17 122 | 92.05 112 | 66.87 203 | 91.21 41 | 88.64 194 | 86.30 30 | 89.60 115 | 92.59 131 | 69.22 229 | 94.91 70 | 73.89 177 | 97.89 51 | 96.72 25 |
|
SF-MVS | | | 90.27 39 | 90.80 45 | 88.68 78 | 92.86 87 | 77.09 111 | 91.19 42 | 95.74 5 | 81.38 74 | 92.28 60 | 93.80 101 | 86.89 51 | 94.64 78 | 85.52 49 | 97.51 75 | 94.30 90 |
|
SMA-MVS |  | | 90.31 38 | 90.48 49 | 89.83 53 | 95.31 31 | 79.52 80 | 90.98 43 | 93.24 77 | 75.37 149 | 92.84 49 | 95.28 37 | 85.58 66 | 96.09 7 | 87.92 10 | 97.76 57 | 93.88 106 |
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 |
MTMP | | | | | | | | 90.66 44 | 33.14 380 | | | | | | | | |
|
#test# | | | 90.49 36 | 90.31 51 | 91.02 33 | 95.43 29 | 84.66 44 | 90.65 45 | 93.29 73 | 77.00 126 | 91.47 73 | 93.96 94 | 88.35 30 | 95.56 38 | 84.88 56 | 97.74 59 | 92.85 146 |
|
test0726 | | | | | | 94.16 53 | 72.56 148 | 90.63 46 | 93.90 46 | 83.61 47 | 93.75 31 | 94.49 62 | 89.76 19 | | | | |
|
DVP-MVS |  | | 90.06 43 | 91.32 30 | 86.29 115 | 94.16 53 | 72.56 148 | 90.54 47 | 91.01 142 | 83.61 47 | 93.75 31 | 94.65 55 | 89.76 19 | 95.78 27 | 86.42 35 | 97.97 45 | 90.55 223 |
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 | | | | | 86.79 105 | 94.25 49 | 72.45 152 | 90.54 47 | 94.10 38 | | | | | 95.88 16 | 86.42 35 | 97.97 45 | 92.02 184 |
|
anonymousdsp | | | 89.73 53 | 88.88 70 | 92.27 9 | 89.82 176 | 86.67 17 | 90.51 49 | 90.20 169 | 69.87 220 | 95.06 11 | 96.14 21 | 84.28 75 | 93.07 146 | 87.68 13 | 96.34 114 | 97.09 20 |
|
SED-MVS | | | 90.46 37 | 91.64 19 | 86.93 102 | 94.18 50 | 72.65 142 | 90.47 50 | 93.69 54 | 83.77 44 | 94.11 23 | 94.27 73 | 90.28 15 | 95.84 22 | 86.03 45 | 97.92 48 | 92.29 174 |
|
OPU-MVS | | | | | 88.27 87 | 91.89 118 | 77.83 97 | 90.47 50 | | | | 91.22 168 | 81.12 120 | 94.68 76 | 74.48 170 | 95.35 152 | 92.29 174 |
|
CS-MVS | | | 88.14 76 | 87.67 84 | 89.54 61 | 89.56 178 | 79.18 83 | 90.47 50 | 94.77 18 | 79.37 99 | 84.32 210 | 89.33 216 | 83.87 77 | 94.53 85 | 82.45 81 | 94.89 171 | 94.90 65 |
|
DROMVSNet | | | 88.01 78 | 88.32 77 | 87.09 100 | 89.28 183 | 72.03 158 | 90.31 53 | 96.31 3 | 80.88 80 | 85.12 195 | 89.67 211 | 84.47 74 | 95.46 49 | 82.56 80 | 96.26 119 | 93.77 114 |
|
PMVS |  | 80.48 6 | 90.08 41 | 90.66 47 | 88.34 86 | 96.71 3 | 92.97 1 | 90.31 53 | 89.57 182 | 88.51 19 | 90.11 95 | 95.12 43 | 90.98 7 | 88.92 251 | 77.55 140 | 97.07 87 | 83.13 318 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
APD-MVS |  | | 89.54 56 | 89.63 57 | 89.26 65 | 92.57 92 | 81.34 66 | 90.19 55 | 93.08 83 | 80.87 81 | 91.13 79 | 93.19 112 | 86.22 61 | 95.97 12 | 82.23 85 | 97.18 85 | 90.45 225 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
testtj | | | 89.51 57 | 89.48 60 | 89.59 59 | 92.26 103 | 80.80 69 | 90.14 56 | 93.54 61 | 83.37 50 | 90.57 90 | 92.55 134 | 84.99 68 | 96.15 5 | 81.26 93 | 96.61 102 | 91.83 191 |
|
PGM-MVS | | | 91.20 25 | 90.95 42 | 91.93 15 | 95.67 23 | 85.85 30 | 90.00 57 | 93.90 46 | 80.32 86 | 91.74 71 | 94.41 68 | 88.17 34 | 95.98 11 | 86.37 37 | 97.99 42 | 93.96 103 |
|
LPG-MVS_test | | | 91.47 19 | 91.68 18 | 90.82 38 | 94.75 42 | 81.69 61 | 90.00 57 | 94.27 23 | 82.35 63 | 93.67 34 | 94.82 50 | 91.18 5 | 95.52 43 | 85.36 51 | 98.73 7 | 95.23 59 |
|
v7n | | | 90.13 40 | 90.96 41 | 87.65 95 | 91.95 114 | 71.06 169 | 89.99 59 | 93.05 84 | 86.53 28 | 94.29 19 | 96.27 17 | 82.69 91 | 94.08 102 | 86.25 41 | 97.63 64 | 97.82 8 |
|
ACMMP_NAP | | | 90.65 31 | 91.07 38 | 89.42 62 | 95.93 16 | 79.54 79 | 89.95 60 | 93.68 56 | 77.65 119 | 91.97 67 | 94.89 47 | 88.38 28 | 95.45 50 | 89.27 3 | 97.87 52 | 93.27 131 |
|
QAPM | | | 82.59 173 | 82.59 172 | 82.58 196 | 86.44 237 | 66.69 204 | 89.94 61 | 90.36 159 | 67.97 239 | 84.94 199 | 92.58 133 | 72.71 208 | 92.18 168 | 70.63 210 | 87.73 295 | 88.85 252 |
|
mvs_tets | | | 89.78 52 | 89.27 63 | 91.30 28 | 93.51 69 | 84.79 41 | 89.89 62 | 90.63 152 | 70.00 219 | 94.55 15 | 96.67 11 | 87.94 39 | 93.59 123 | 84.27 63 | 95.97 129 | 95.52 49 |
|
SD-MVS | | | 88.96 67 | 89.88 53 | 86.22 118 | 91.63 126 | 77.07 112 | 89.82 63 | 93.77 51 | 78.90 105 | 92.88 46 | 92.29 143 | 86.11 62 | 90.22 225 | 86.24 42 | 97.24 83 | 91.36 203 |
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 |
jajsoiax | | | 89.41 58 | 88.81 72 | 91.19 32 | 93.38 73 | 84.72 42 | 89.70 64 | 90.29 166 | 69.27 223 | 94.39 17 | 96.38 15 | 86.02 64 | 93.52 127 | 83.96 65 | 95.92 134 | 95.34 53 |
|
HPM-MVS++ |  | | 88.93 68 | 88.45 76 | 90.38 45 | 94.92 37 | 85.85 30 | 89.70 64 | 91.27 135 | 78.20 114 | 86.69 167 | 92.28 144 | 80.36 130 | 95.06 66 | 86.17 43 | 96.49 107 | 90.22 228 |
|
RPSCF | | | 88.00 79 | 86.93 96 | 91.22 31 | 90.08 170 | 89.30 5 | 89.68 66 | 91.11 139 | 79.26 100 | 89.68 109 | 94.81 53 | 82.44 94 | 87.74 265 | 76.54 152 | 88.74 283 | 96.61 29 |
|
UniMVSNet_ETH3D | | | 89.12 64 | 90.72 46 | 84.31 157 | 97.00 2 | 64.33 221 | 89.67 67 | 88.38 198 | 88.84 15 | 94.29 19 | 97.57 3 | 90.48 14 | 91.26 193 | 72.57 195 | 97.65 63 | 97.34 15 |
|
ACMH+ | | 77.89 11 | 90.73 30 | 91.50 23 | 88.44 83 | 93.00 82 | 76.26 123 | 89.65 68 | 95.55 7 | 87.72 23 | 93.89 27 | 94.94 46 | 91.62 4 | 93.44 131 | 78.35 126 | 98.76 4 | 95.61 48 |
|
ACMM | | 79.39 9 | 90.65 31 | 90.99 40 | 89.63 57 | 95.03 35 | 83.53 49 | 89.62 69 | 93.35 66 | 79.20 101 | 93.83 28 | 93.60 108 | 90.81 8 | 92.96 148 | 85.02 55 | 98.45 19 | 92.41 166 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
ACMH | | 76.49 14 | 89.34 60 | 91.14 34 | 83.96 165 | 92.50 96 | 70.36 174 | 89.55 70 | 93.84 50 | 81.89 69 | 94.70 13 | 95.44 35 | 90.69 9 | 88.31 261 | 83.33 72 | 98.30 26 | 93.20 134 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
Gipuma |  | | 84.44 136 | 86.33 103 | 78.78 252 | 84.20 275 | 73.57 135 | 89.55 70 | 90.44 156 | 84.24 39 | 84.38 208 | 94.89 47 | 76.35 171 | 80.40 326 | 76.14 156 | 96.80 97 | 82.36 326 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
WR-MVS_H | | | 89.91 50 | 91.31 31 | 85.71 131 | 96.32 10 | 62.39 243 | 89.54 72 | 93.31 70 | 90.21 10 | 95.57 9 | 95.66 30 | 81.42 117 | 95.90 15 | 80.94 98 | 98.80 3 | 98.84 5 |
|
AllTest | | | 87.97 80 | 87.40 89 | 89.68 55 | 91.59 127 | 83.40 50 | 89.50 73 | 95.44 9 | 79.47 95 | 88.00 142 | 93.03 115 | 82.66 92 | 91.47 185 | 70.81 204 | 96.14 123 | 94.16 95 |
|
XVG-ACMP-BASELINE | | | 89.98 47 | 89.84 54 | 90.41 44 | 94.91 38 | 84.50 46 | 89.49 74 | 93.98 42 | 79.68 93 | 92.09 63 | 93.89 99 | 83.80 80 | 93.10 145 | 82.67 79 | 98.04 37 | 93.64 121 |
|
HQP_MVS | | | 87.75 85 | 87.43 88 | 88.70 77 | 93.45 70 | 76.42 121 | 89.45 75 | 93.61 58 | 79.44 97 | 86.55 169 | 92.95 120 | 74.84 180 | 95.22 59 | 80.78 101 | 95.83 137 | 94.46 82 |
|
plane_prior2 | | | | | | | | 89.45 75 | | 79.44 97 | | | | | | | |
|
CS-MVS-test | | | 87.00 90 | 86.43 102 | 88.71 76 | 89.46 179 | 77.46 103 | 89.42 77 | 95.73 6 | 77.87 117 | 81.64 255 | 87.25 250 | 82.43 95 | 94.53 85 | 77.65 138 | 96.46 109 | 94.14 97 |
|
PHI-MVS | | | 86.38 100 | 85.81 114 | 88.08 89 | 88.44 201 | 77.34 107 | 89.35 78 | 93.05 84 | 73.15 179 | 84.76 202 | 87.70 241 | 78.87 140 | 94.18 96 | 80.67 103 | 96.29 115 | 92.73 151 |
|
ACMP | | 79.16 10 | 90.54 34 | 90.60 48 | 90.35 46 | 94.36 47 | 80.98 67 | 89.16 79 | 94.05 40 | 79.03 104 | 92.87 47 | 93.74 105 | 90.60 12 | 95.21 61 | 82.87 77 | 98.76 4 | 94.87 67 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
DPE-MVS |  | | 90.53 35 | 91.08 36 | 88.88 69 | 93.38 73 | 78.65 89 | 89.15 80 | 94.05 40 | 84.68 38 | 93.90 25 | 94.11 86 | 88.13 36 | 96.30 3 | 84.51 61 | 97.81 55 | 91.70 195 |
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025 |
PS-CasMVS | | | 90.06 43 | 91.92 13 | 84.47 152 | 96.56 7 | 58.83 287 | 89.04 81 | 92.74 98 | 91.40 5 | 96.12 4 | 96.06 22 | 87.23 47 | 95.57 37 | 79.42 118 | 98.74 6 | 99.00 2 |
|
PEN-MVS | | | 90.03 45 | 91.88 16 | 84.48 151 | 96.57 6 | 58.88 284 | 88.95 82 | 93.19 78 | 91.62 4 | 96.01 6 | 96.16 20 | 87.02 49 | 95.60 36 | 78.69 123 | 98.72 9 | 98.97 3 |
|
zzz-MVS | | | 91.27 22 | 91.26 33 | 91.29 29 | 96.59 4 | 86.29 19 | 88.94 83 | 91.81 121 | 84.07 40 | 92.00 65 | 94.40 69 | 86.63 54 | 95.28 57 | 88.59 5 | 98.31 24 | 92.30 172 |
|
DTE-MVSNet | | | 89.98 47 | 91.91 15 | 84.21 159 | 96.51 8 | 57.84 292 | 88.93 84 | 92.84 95 | 91.92 3 | 96.16 3 | 96.23 18 | 86.95 50 | 95.99 10 | 79.05 120 | 98.57 15 | 98.80 6 |
|
Anonymous20231211 | | | 88.40 73 | 89.62 58 | 84.73 147 | 90.46 164 | 65.27 212 | 88.86 85 | 93.02 88 | 87.15 25 | 93.05 44 | 97.10 6 | 82.28 100 | 92.02 173 | 76.70 149 | 97.99 42 | 96.88 24 |
|
F-COLMAP | | | 84.97 127 | 83.42 157 | 89.63 57 | 92.39 98 | 83.40 50 | 88.83 86 | 91.92 117 | 73.19 178 | 80.18 275 | 89.15 220 | 77.04 160 | 93.28 136 | 65.82 250 | 92.28 229 | 92.21 179 |
|
9.14 | | | | 89.29 62 | | 91.84 122 | | 88.80 87 | 95.32 11 | 75.14 151 | 91.07 80 | 92.89 122 | 87.27 46 | 93.78 114 | 83.69 69 | 97.55 70 | |
|
3Dnovator | | 80.37 7 | 84.80 128 | 84.71 136 | 85.06 142 | 86.36 242 | 74.71 129 | 88.77 88 | 90.00 174 | 75.65 144 | 84.96 197 | 93.17 113 | 74.06 189 | 91.19 195 | 78.28 128 | 91.09 248 | 89.29 243 |
|
ETH3D-3000-0.1 | | | 88.85 69 | 88.96 69 | 88.52 79 | 91.94 116 | 77.27 110 | 88.71 89 | 95.26 13 | 76.08 133 | 90.66 89 | 92.69 129 | 84.48 73 | 93.83 113 | 83.38 71 | 97.48 77 | 94.47 81 |
|
API-MVS | | | 82.28 177 | 82.61 171 | 81.30 215 | 86.29 245 | 69.79 175 | 88.71 89 | 87.67 211 | 78.42 113 | 82.15 244 | 84.15 299 | 77.98 147 | 91.59 183 | 65.39 252 | 92.75 218 | 82.51 325 |
|
CP-MVSNet | | | 89.27 61 | 90.91 43 | 84.37 153 | 96.34 9 | 58.61 289 | 88.66 91 | 92.06 112 | 90.78 6 | 95.67 7 | 95.17 41 | 81.80 113 | 95.54 42 | 79.00 121 | 98.69 10 | 98.95 4 |
|
DeepC-MVS | | 82.31 4 | 89.15 63 | 89.08 65 | 89.37 63 | 93.64 68 | 79.07 84 | 88.54 92 | 94.20 28 | 73.53 168 | 89.71 108 | 94.82 50 | 85.09 67 | 95.77 29 | 84.17 64 | 98.03 39 | 93.26 132 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
OpenMVS |  | 76.72 13 | 81.98 184 | 82.00 180 | 81.93 204 | 84.42 268 | 68.22 192 | 88.50 93 | 89.48 183 | 66.92 248 | 81.80 252 | 91.86 151 | 72.59 210 | 90.16 227 | 71.19 203 | 91.25 247 | 87.40 268 |
|
ambc | | | | | 82.98 186 | 90.55 163 | 64.86 215 | 88.20 94 | 89.15 188 | | 89.40 119 | 93.96 94 | 71.67 220 | 91.38 192 | 78.83 122 | 96.55 104 | 92.71 154 |
|
PAPM_NR | | | 83.23 166 | 83.19 162 | 83.33 178 | 90.90 153 | 65.98 208 | 88.19 95 | 90.78 148 | 78.13 116 | 80.87 264 | 87.92 239 | 73.49 198 | 92.42 160 | 70.07 214 | 88.40 284 | 91.60 198 |
|
MP-MVS-pluss | | | 90.81 29 | 91.08 36 | 89.99 51 | 95.97 14 | 79.88 74 | 88.13 96 | 94.51 21 | 75.79 142 | 92.94 45 | 94.96 45 | 88.36 29 | 95.01 67 | 90.70 2 | 98.40 20 | 95.09 63 |
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
test_part1 | | | 87.15 89 | 87.82 81 | 85.15 140 | 88.88 192 | 63.04 233 | 87.98 97 | 94.85 16 | 82.52 61 | 93.61 37 | 95.73 27 | 67.51 237 | 95.71 31 | 80.48 106 | 98.83 2 | 96.69 26 |
|
CSCG | | | 86.26 102 | 86.47 101 | 85.60 133 | 90.87 154 | 74.26 132 | 87.98 97 | 91.85 118 | 80.35 85 | 89.54 118 | 88.01 235 | 79.09 138 | 92.13 169 | 75.51 162 | 95.06 165 | 90.41 226 |
|
PS-MVSNAJss | | | 88.31 74 | 87.90 80 | 89.56 60 | 93.31 75 | 77.96 96 | 87.94 99 | 91.97 115 | 70.73 210 | 94.19 22 | 96.67 11 | 76.94 162 | 94.57 82 | 83.07 74 | 96.28 116 | 96.15 33 |
|
nrg030 | | | 87.85 82 | 88.49 74 | 85.91 125 | 90.07 172 | 69.73 177 | 87.86 100 | 94.20 28 | 74.04 162 | 92.70 54 | 94.66 54 | 85.88 65 | 91.50 184 | 79.72 112 | 97.32 81 | 96.50 31 |
|
SixPastTwentyTwo | | | 87.20 88 | 87.45 87 | 86.45 111 | 92.52 95 | 69.19 186 | 87.84 101 | 88.05 205 | 81.66 71 | 94.64 14 | 96.53 14 | 65.94 246 | 94.75 74 | 83.02 76 | 96.83 95 | 95.41 51 |
|
Effi-MVS+-dtu | | | 85.82 111 | 83.38 158 | 93.14 3 | 87.13 226 | 91.15 2 | 87.70 102 | 88.42 196 | 74.57 157 | 83.56 226 | 85.65 272 | 78.49 143 | 94.21 94 | 72.04 198 | 92.88 216 | 94.05 100 |
|
canonicalmvs | | | 85.50 114 | 86.14 108 | 83.58 174 | 87.97 208 | 67.13 199 | 87.55 103 | 94.32 22 | 73.44 170 | 88.47 134 | 87.54 244 | 86.45 58 | 91.06 200 | 75.76 161 | 93.76 195 | 92.54 161 |
|
DP-MVS | | | 88.60 72 | 89.01 66 | 87.36 98 | 91.30 140 | 77.50 102 | 87.55 103 | 92.97 90 | 87.95 22 | 89.62 112 | 92.87 123 | 84.56 71 | 93.89 109 | 77.65 138 | 96.62 101 | 90.70 217 |
|
OMC-MVS | | | 88.19 75 | 87.52 86 | 90.19 49 | 91.94 116 | 81.68 63 | 87.49 105 | 93.17 79 | 76.02 136 | 88.64 130 | 91.22 168 | 84.24 76 | 93.37 134 | 77.97 136 | 97.03 88 | 95.52 49 |
|
Vis-MVSNet |  | | 86.86 92 | 86.58 100 | 87.72 93 | 92.09 110 | 77.43 106 | 87.35 106 | 92.09 111 | 78.87 106 | 84.27 216 | 94.05 87 | 78.35 145 | 93.65 117 | 80.54 105 | 91.58 244 | 92.08 182 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
ETH3D cwj APD-0.16 | | | 87.83 83 | 87.62 85 | 88.47 81 | 91.21 143 | 78.20 91 | 87.26 107 | 94.54 20 | 72.05 196 | 88.89 124 | 92.31 142 | 83.86 78 | 94.24 92 | 81.59 92 | 96.87 92 | 92.97 145 |
|
DeepC-MVS_fast | | 80.27 8 | 86.23 103 | 85.65 119 | 87.96 92 | 91.30 140 | 76.92 113 | 87.19 108 | 91.99 114 | 70.56 211 | 84.96 197 | 90.69 188 | 80.01 133 | 95.14 62 | 78.37 125 | 95.78 142 | 91.82 192 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
EPNet | | | 80.37 207 | 78.41 228 | 86.23 117 | 76.75 342 | 73.28 137 | 87.18 109 | 77.45 299 | 76.24 132 | 68.14 342 | 88.93 224 | 65.41 248 | 93.85 110 | 69.47 218 | 96.12 125 | 91.55 200 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
plane_prior | | | | | | | 76.42 121 | 87.15 110 | | 75.94 140 | | | | | | 95.03 166 | |
|
TAPA-MVS | | 77.73 12 | 85.71 113 | 84.83 132 | 88.37 85 | 88.78 194 | 79.72 76 | 87.15 110 | 93.50 62 | 69.17 224 | 85.80 186 | 89.56 212 | 80.76 124 | 92.13 169 | 73.21 191 | 95.51 148 | 93.25 133 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
tttt0517 | | | 81.07 193 | 79.58 214 | 85.52 134 | 88.99 190 | 66.45 206 | 87.03 112 | 75.51 312 | 73.76 166 | 88.32 139 | 90.20 200 | 37.96 363 | 94.16 101 | 79.36 119 | 95.13 161 | 95.93 42 |
|
UGNet | | | 82.78 170 | 81.64 184 | 86.21 120 | 86.20 248 | 76.24 124 | 86.86 113 | 85.68 240 | 77.07 125 | 73.76 322 | 92.82 124 | 69.64 226 | 91.82 180 | 69.04 225 | 93.69 198 | 90.56 222 |
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 |
XVG-OURS-SEG-HR | | | 89.59 55 | 89.37 61 | 90.28 47 | 94.47 46 | 85.95 26 | 86.84 114 | 93.91 45 | 80.07 90 | 86.75 164 | 93.26 111 | 93.64 2 | 90.93 203 | 84.60 60 | 90.75 261 | 93.97 102 |
|
GBi-Net | | | 82.02 182 | 82.07 178 | 81.85 207 | 86.38 239 | 61.05 258 | 86.83 115 | 88.27 202 | 72.43 186 | 86.00 181 | 95.64 31 | 63.78 255 | 90.68 213 | 65.95 246 | 93.34 203 | 93.82 110 |
|
test1 | | | 82.02 182 | 82.07 178 | 81.85 207 | 86.38 239 | 61.05 258 | 86.83 115 | 88.27 202 | 72.43 186 | 86.00 181 | 95.64 31 | 63.78 255 | 90.68 213 | 65.95 246 | 93.34 203 | 93.82 110 |
|
FMVSNet1 | | | 84.55 133 | 85.45 122 | 81.85 207 | 90.27 167 | 61.05 258 | 86.83 115 | 88.27 202 | 78.57 111 | 89.66 111 | 95.64 31 | 75.43 173 | 90.68 213 | 69.09 224 | 95.33 153 | 93.82 110 |
|
OPM-MVS | | | 89.80 51 | 89.97 52 | 89.27 64 | 94.76 41 | 79.86 75 | 86.76 118 | 92.78 97 | 78.78 107 | 92.51 56 | 93.64 107 | 88.13 36 | 93.84 112 | 84.83 58 | 97.55 70 | 94.10 99 |
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS). |
MSLP-MVS++ | | | 85.00 126 | 86.03 110 | 81.90 205 | 91.84 122 | 71.56 167 | 86.75 119 | 93.02 88 | 75.95 139 | 87.12 153 | 89.39 214 | 77.98 147 | 89.40 247 | 77.46 141 | 94.78 174 | 84.75 295 |
|
114514_t | | | 83.10 169 | 82.54 173 | 84.77 146 | 92.90 84 | 69.10 188 | 86.65 120 | 90.62 153 | 54.66 326 | 81.46 257 | 90.81 185 | 76.98 161 | 94.38 88 | 72.62 194 | 96.18 121 | 90.82 214 |
|
v10 | | | 86.54 97 | 87.10 91 | 84.84 144 | 88.16 207 | 63.28 230 | 86.64 121 | 92.20 109 | 75.42 148 | 92.81 51 | 94.50 61 | 74.05 190 | 94.06 103 | 83.88 66 | 96.28 116 | 97.17 19 |
|
NCCC | | | 87.36 86 | 86.87 97 | 88.83 70 | 92.32 102 | 78.84 87 | 86.58 122 | 91.09 140 | 78.77 108 | 84.85 201 | 90.89 182 | 80.85 123 | 95.29 55 | 81.14 95 | 95.32 154 | 92.34 170 |
|
Effi-MVS+ | | | 83.90 154 | 84.01 151 | 83.57 175 | 87.22 224 | 65.61 211 | 86.55 123 | 92.40 104 | 78.64 110 | 81.34 260 | 84.18 298 | 83.65 82 | 92.93 150 | 74.22 172 | 87.87 293 | 92.17 181 |
|
v8 | | | 86.22 104 | 86.83 98 | 84.36 155 | 87.82 211 | 62.35 245 | 86.42 124 | 91.33 133 | 76.78 128 | 92.73 53 | 94.48 63 | 73.41 199 | 93.72 116 | 83.10 73 | 95.41 150 | 97.01 22 |
|
RRT_MVS | | | 83.25 165 | 81.08 193 | 89.74 54 | 80.55 316 | 79.32 81 | 86.41 125 | 86.69 228 | 72.33 191 | 87.00 159 | 91.08 173 | 44.98 347 | 95.55 41 | 84.47 62 | 96.24 120 | 94.36 88 |
|
xxxxxxxxxxxxxcwj | | | 89.04 66 | 89.13 64 | 88.79 73 | 93.75 64 | 77.44 104 | 86.31 126 | 95.27 12 | 70.80 208 | 92.28 60 | 93.80 101 | 86.89 51 | 94.64 78 | 85.52 49 | 97.51 75 | 94.30 90 |
|
save fliter | | | | | | 93.75 64 | 77.44 104 | 86.31 126 | 89.72 177 | 70.80 208 | | | | | | | |
|
AdaColmap |  | | 83.66 157 | 83.69 156 | 83.57 175 | 90.05 173 | 72.26 155 | 86.29 128 | 90.00 174 | 78.19 115 | 81.65 254 | 87.16 252 | 83.40 85 | 94.24 92 | 61.69 278 | 94.76 177 | 84.21 300 |
|
XVG-OURS | | | 89.18 62 | 88.83 71 | 90.23 48 | 94.28 48 | 86.11 25 | 85.91 129 | 93.60 60 | 80.16 88 | 89.13 123 | 93.44 109 | 83.82 79 | 90.98 201 | 83.86 67 | 95.30 157 | 93.60 123 |
|
ETH3 D test6400 | | | 85.09 122 | 84.87 131 | 85.75 130 | 90.80 156 | 69.34 181 | 85.90 130 | 93.31 70 | 65.43 262 | 86.11 179 | 89.95 205 | 80.92 122 | 94.86 71 | 75.90 159 | 95.57 147 | 93.05 139 |
|
PLC |  | 73.85 16 | 82.09 181 | 80.31 202 | 87.45 97 | 90.86 155 | 80.29 72 | 85.88 131 | 90.65 151 | 68.17 236 | 76.32 302 | 86.33 262 | 73.12 204 | 92.61 158 | 61.40 282 | 90.02 269 | 89.44 238 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
GeoE | | | 85.45 116 | 85.81 114 | 84.37 153 | 90.08 170 | 67.07 200 | 85.86 132 | 91.39 132 | 72.33 191 | 87.59 147 | 90.25 199 | 84.85 69 | 92.37 163 | 78.00 134 | 91.94 238 | 93.66 118 |
|
FC-MVSNet-test | | | 85.93 110 | 87.05 93 | 82.58 196 | 92.25 104 | 56.44 303 | 85.75 133 | 93.09 82 | 77.33 122 | 91.94 68 | 94.65 55 | 74.78 182 | 93.41 133 | 75.11 168 | 98.58 14 | 97.88 7 |
|
MAR-MVS | | | 80.24 211 | 78.74 223 | 84.73 147 | 86.87 236 | 78.18 92 | 85.75 133 | 87.81 210 | 65.67 261 | 77.84 292 | 78.50 345 | 73.79 193 | 90.53 217 | 61.59 281 | 90.87 258 | 85.49 288 |
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 |
EU-MVSNet | | | 75.12 263 | 74.43 265 | 77.18 278 | 83.11 290 | 59.48 276 | 85.71 135 | 82.43 271 | 39.76 369 | 85.64 188 | 88.76 225 | 44.71 349 | 87.88 264 | 73.86 178 | 85.88 310 | 84.16 301 |
|
LF4IMVS | | | 82.75 171 | 81.93 181 | 85.19 138 | 82.08 295 | 80.15 73 | 85.53 136 | 88.76 192 | 68.01 237 | 85.58 189 | 87.75 240 | 71.80 218 | 86.85 277 | 74.02 175 | 93.87 194 | 88.58 254 |
|
K. test v3 | | | 85.14 120 | 84.73 133 | 86.37 112 | 91.13 148 | 69.63 179 | 85.45 137 | 76.68 304 | 84.06 42 | 92.44 58 | 96.99 8 | 62.03 265 | 94.65 77 | 80.58 104 | 93.24 206 | 94.83 73 |
|
VDDNet | | | 84.35 138 | 85.39 123 | 81.25 216 | 95.13 33 | 59.32 277 | 85.42 138 | 81.11 279 | 86.41 29 | 87.41 150 | 96.21 19 | 73.61 194 | 90.61 216 | 66.33 244 | 96.85 93 | 93.81 113 |
|
CNVR-MVS | | | 87.81 84 | 87.68 83 | 88.21 88 | 92.87 85 | 77.30 109 | 85.25 139 | 91.23 136 | 77.31 123 | 87.07 157 | 91.47 164 | 82.94 89 | 94.71 75 | 84.67 59 | 96.27 118 | 92.62 158 |
|
LFMVS | | | 80.15 214 | 80.56 198 | 78.89 250 | 89.19 186 | 55.93 305 | 85.22 140 | 73.78 324 | 82.96 56 | 84.28 215 | 92.72 128 | 57.38 295 | 90.07 234 | 63.80 262 | 95.75 143 | 90.68 218 |
|
FIs | | | 85.35 117 | 86.27 105 | 82.60 195 | 91.86 119 | 57.31 296 | 85.10 141 | 93.05 84 | 75.83 141 | 91.02 82 | 93.97 91 | 73.57 195 | 92.91 152 | 73.97 176 | 98.02 40 | 97.58 12 |
|
mvs-test1 | | | 84.55 133 | 82.12 177 | 91.84 20 | 87.13 226 | 89.54 4 | 85.05 142 | 88.42 196 | 74.57 157 | 80.60 266 | 82.98 308 | 78.49 143 | 93.98 106 | 72.04 198 | 89.77 270 | 92.00 185 |
|
HQP-NCC | | | | | | 91.19 144 | | 84.77 143 | | 73.30 174 | 80.55 269 | | | | | | |
|
ACMP_Plane | | | | | | 91.19 144 | | 84.77 143 | | 73.30 174 | 80.55 269 | | | | | | |
|
HQP-MVS | | | 84.61 131 | 84.06 150 | 86.27 116 | 91.19 144 | 70.66 171 | 84.77 143 | 92.68 99 | 73.30 174 | 80.55 269 | 90.17 203 | 72.10 213 | 94.61 80 | 77.30 144 | 94.47 182 | 93.56 125 |
|
ab-mvs | | | 79.67 217 | 80.56 198 | 76.99 279 | 88.48 199 | 56.93 299 | 84.70 146 | 86.06 235 | 68.95 228 | 80.78 265 | 93.08 114 | 75.30 175 | 84.62 304 | 56.78 304 | 90.90 257 | 89.43 239 |
|
pmmvs6 | | | 86.52 98 | 88.06 79 | 81.90 205 | 92.22 106 | 62.28 246 | 84.66 147 | 89.15 188 | 83.54 49 | 89.85 104 | 97.32 4 | 88.08 38 | 86.80 278 | 70.43 212 | 97.30 82 | 96.62 28 |
|
test_prior4 | | | | | | | 78.97 85 | 84.59 148 | | | | | | | | | |
|
Anonymous20240529 | | | 86.20 105 | 87.13 90 | 83.42 177 | 90.19 168 | 64.55 219 | 84.55 149 | 90.71 149 | 85.85 31 | 89.94 102 | 95.24 40 | 82.13 102 | 90.40 220 | 69.19 223 | 96.40 112 | 95.31 55 |
|
baseline | | | 85.20 119 | 85.93 111 | 83.02 185 | 86.30 244 | 62.37 244 | 84.55 149 | 93.96 43 | 74.48 159 | 87.12 153 | 92.03 148 | 82.30 98 | 91.94 174 | 78.39 124 | 94.21 187 | 94.74 74 |
|
alignmvs | | | 83.94 153 | 83.98 152 | 83.80 167 | 87.80 212 | 67.88 196 | 84.54 151 | 91.42 131 | 73.27 177 | 88.41 136 | 87.96 236 | 72.33 212 | 90.83 208 | 76.02 158 | 94.11 189 | 92.69 155 |
|
CNLPA | | | 83.55 160 | 83.10 164 | 84.90 143 | 89.34 182 | 83.87 48 | 84.54 151 | 88.77 191 | 79.09 102 | 83.54 227 | 88.66 228 | 74.87 179 | 81.73 320 | 66.84 241 | 92.29 228 | 89.11 245 |
|
ETV-MVS | | | 84.31 139 | 83.91 154 | 85.52 134 | 88.58 197 | 70.40 173 | 84.50 153 | 93.37 64 | 78.76 109 | 84.07 219 | 78.72 344 | 80.39 129 | 95.13 63 | 73.82 179 | 92.98 214 | 91.04 207 |
|
TranMVSNet+NR-MVSNet | | | 87.86 81 | 88.76 73 | 85.18 139 | 94.02 58 | 64.13 222 | 84.38 154 | 91.29 134 | 84.88 37 | 92.06 64 | 93.84 100 | 86.45 58 | 93.73 115 | 73.22 186 | 98.66 11 | 97.69 9 |
|
PVSNet_Blended_VisFu | | | 81.55 188 | 80.49 200 | 84.70 149 | 91.58 130 | 73.24 139 | 84.21 155 | 91.67 124 | 62.86 277 | 80.94 262 | 87.16 252 | 67.27 239 | 92.87 153 | 69.82 216 | 88.94 280 | 87.99 260 |
|
GG-mvs-BLEND | | | | | 67.16 332 | 73.36 362 | 46.54 360 | 84.15 156 | 55.04 373 | | 58.64 369 | 61.95 370 | 29.93 374 | 83.87 311 | 38.71 367 | 76.92 356 | 71.07 359 |
|
iter_conf05 | | | 78.81 224 | 77.35 237 | 83.21 181 | 82.98 292 | 60.75 265 | 84.09 157 | 88.34 199 | 63.12 275 | 84.25 218 | 89.48 213 | 31.41 371 | 94.51 87 | 76.64 150 | 95.83 137 | 94.38 87 |
|
Regformer-3 | | | 85.06 123 | 84.67 138 | 86.22 118 | 84.27 272 | 73.43 136 | 84.07 158 | 85.26 246 | 80.77 82 | 88.62 131 | 85.48 275 | 80.56 128 | 90.39 221 | 81.99 87 | 91.04 250 | 94.85 71 |
|
Regformer-4 | | | 86.41 99 | 85.71 117 | 88.52 79 | 84.27 272 | 77.57 101 | 84.07 158 | 88.00 207 | 82.82 58 | 89.84 105 | 85.48 275 | 82.06 104 | 92.77 154 | 83.83 68 | 91.04 250 | 95.22 61 |
|
test2506 | | | 74.12 274 | 73.39 274 | 76.28 290 | 91.85 120 | 44.20 365 | 84.06 160 | 48.20 377 | 72.30 193 | 81.90 247 | 94.20 79 | 27.22 378 | 89.77 239 | 64.81 256 | 96.02 127 | 94.87 67 |
|
test_0402 | | | 88.65 71 | 89.58 59 | 85.88 127 | 92.55 93 | 72.22 156 | 84.01 161 | 89.44 184 | 88.63 18 | 94.38 18 | 95.77 26 | 86.38 60 | 93.59 123 | 79.84 110 | 95.21 158 | 91.82 192 |
|
h-mvs33 | | | 84.25 142 | 82.76 167 | 88.72 75 | 91.82 124 | 82.60 58 | 84.00 162 | 84.98 255 | 71.27 202 | 86.70 165 | 90.55 193 | 63.04 261 | 93.92 108 | 78.26 129 | 94.20 188 | 89.63 235 |
|
TEST9 | | | | | | 92.34 100 | 79.70 77 | 83.94 163 | 90.32 160 | 65.41 266 | 84.49 206 | 90.97 178 | 82.03 106 | 93.63 119 | | | |
|
train_agg | | | 85.98 109 | 85.28 124 | 88.07 90 | 92.34 100 | 79.70 77 | 83.94 163 | 90.32 160 | 65.79 256 | 84.49 206 | 90.97 178 | 81.93 108 | 93.63 119 | 81.21 94 | 96.54 105 | 90.88 212 |
|
FMVSNet2 | | | 81.31 190 | 81.61 185 | 80.41 232 | 86.38 239 | 58.75 288 | 83.93 165 | 86.58 230 | 72.43 186 | 87.65 146 | 92.98 117 | 63.78 255 | 90.22 225 | 66.86 239 | 93.92 193 | 92.27 176 |
|
EI-MVSNet-Vis-set | | | 85.12 121 | 84.53 141 | 86.88 103 | 84.01 279 | 72.76 141 | 83.91 166 | 85.18 248 | 80.44 83 | 88.75 128 | 85.49 274 | 80.08 132 | 91.92 175 | 82.02 86 | 90.85 259 | 95.97 39 |
|
CDPH-MVS | | | 86.17 106 | 85.54 120 | 88.05 91 | 92.25 104 | 75.45 126 | 83.85 167 | 92.01 113 | 65.91 255 | 86.19 176 | 91.75 158 | 83.77 81 | 94.98 68 | 77.43 143 | 96.71 99 | 93.73 115 |
|
test_8 | | | | | | 92.09 110 | 78.87 86 | 83.82 168 | 90.31 162 | 65.79 256 | 84.36 209 | 90.96 180 | 81.93 108 | 93.44 131 | | | |
|
EI-MVSNet-UG-set | | | 85.04 124 | 84.44 143 | 86.85 104 | 83.87 282 | 72.52 150 | 83.82 168 | 85.15 249 | 80.27 87 | 88.75 128 | 85.45 278 | 79.95 134 | 91.90 176 | 81.92 89 | 90.80 260 | 96.13 34 |
|
UniMVSNet (Re) | | | 86.87 91 | 86.98 95 | 86.55 109 | 93.11 80 | 68.48 190 | 83.80 170 | 92.87 92 | 80.37 84 | 89.61 114 | 91.81 156 | 77.72 150 | 94.18 96 | 75.00 169 | 98.53 16 | 96.99 23 |
|
CANet | | | 83.79 155 | 82.85 166 | 86.63 107 | 86.17 249 | 72.21 157 | 83.76 171 | 91.43 129 | 77.24 124 | 74.39 319 | 87.45 246 | 75.36 174 | 95.42 51 | 77.03 147 | 92.83 217 | 92.25 178 |
|
TSAR-MVS + GP. | | | 83.95 152 | 82.69 169 | 87.72 93 | 89.27 184 | 81.45 65 | 83.72 172 | 81.58 278 | 74.73 155 | 85.66 187 | 86.06 267 | 72.56 211 | 92.69 156 | 75.44 164 | 95.21 158 | 89.01 251 |
|
agg_prior1 | | | 85.72 112 | 85.20 125 | 87.28 99 | 91.58 130 | 77.69 99 | 83.69 173 | 90.30 163 | 66.29 253 | 84.32 210 | 91.07 175 | 82.13 102 | 93.18 139 | 81.02 96 | 96.36 113 | 90.98 208 |
|
ECVR-MVS |  | | 78.44 230 | 78.63 224 | 77.88 270 | 91.85 120 | 48.95 349 | 83.68 174 | 69.91 347 | 72.30 193 | 84.26 217 | 94.20 79 | 51.89 314 | 89.82 238 | 63.58 263 | 96.02 127 | 94.87 67 |
|
thisisatest0530 | | | 79.07 219 | 77.33 238 | 84.26 158 | 87.13 226 | 64.58 217 | 83.66 175 | 75.95 307 | 68.86 229 | 85.22 194 | 87.36 248 | 38.10 361 | 93.57 126 | 75.47 163 | 94.28 186 | 94.62 75 |
|
gg-mvs-nofinetune | | | 68.96 310 | 69.11 306 | 68.52 329 | 76.12 349 | 45.32 361 | 83.59 176 | 55.88 372 | 86.68 26 | 64.62 359 | 97.01 7 | 30.36 373 | 83.97 310 | 44.78 357 | 82.94 332 | 76.26 352 |
|
Regformer-1 | | | 86.00 107 | 85.50 121 | 87.49 96 | 84.18 276 | 76.90 114 | 83.52 177 | 87.94 209 | 82.18 65 | 89.19 121 | 85.07 287 | 82.28 100 | 91.89 177 | 82.40 83 | 92.72 221 | 93.69 117 |
|
Regformer-2 | | | 86.74 95 | 86.08 109 | 88.73 74 | 84.18 276 | 79.20 82 | 83.52 177 | 89.33 186 | 83.33 51 | 89.92 103 | 85.07 287 | 83.23 87 | 93.16 141 | 83.39 70 | 92.72 221 | 93.83 108 |
|
MCST-MVS | | | 84.36 137 | 83.93 153 | 85.63 132 | 91.59 127 | 71.58 166 | 83.52 177 | 92.13 110 | 61.82 284 | 83.96 220 | 89.75 210 | 79.93 135 | 93.46 130 | 78.33 127 | 94.34 185 | 91.87 190 |
|
EI-MVSNet | | | 82.61 172 | 82.42 175 | 83.20 182 | 83.25 286 | 63.66 225 | 83.50 180 | 85.07 250 | 76.06 134 | 86.55 169 | 85.10 284 | 73.41 199 | 90.25 222 | 78.15 133 | 90.67 263 | 95.68 45 |
|
CVMVSNet | | | 72.62 285 | 71.41 294 | 76.28 290 | 83.25 286 | 60.34 268 | 83.50 180 | 79.02 293 | 37.77 370 | 76.33 301 | 85.10 284 | 49.60 322 | 87.41 269 | 70.54 211 | 77.54 355 | 81.08 342 |
|
DeepPCF-MVS | | 81.24 5 | 87.28 87 | 86.21 107 | 90.49 43 | 91.48 137 | 84.90 39 | 83.41 182 | 92.38 106 | 70.25 216 | 89.35 120 | 90.68 189 | 82.85 90 | 94.57 82 | 79.55 114 | 95.95 131 | 92.00 185 |
|
test_prior3 | | | 86.31 101 | 86.31 104 | 86.32 113 | 90.59 161 | 71.99 159 | 83.37 183 | 92.85 93 | 75.43 146 | 84.58 204 | 91.57 160 | 81.92 110 | 94.17 98 | 79.54 115 | 96.97 89 | 92.80 148 |
|
test_prior2 | | | | | | | | 83.37 183 | | 75.43 146 | 84.58 204 | 91.57 160 | 81.92 110 | | 79.54 115 | 96.97 89 | |
|
Vis-MVSNet (Re-imp) | | | 77.82 236 | 77.79 233 | 77.92 269 | 88.82 193 | 51.29 339 | 83.28 185 | 71.97 337 | 74.04 162 | 82.23 242 | 89.78 209 | 57.38 295 | 89.41 246 | 57.22 303 | 95.41 150 | 93.05 139 |
|
CANet_DTU | | | 77.81 237 | 77.05 240 | 80.09 237 | 81.37 303 | 59.90 272 | 83.26 186 | 88.29 201 | 69.16 225 | 67.83 345 | 83.72 301 | 60.93 268 | 89.47 243 | 69.22 222 | 89.70 271 | 90.88 212 |
|
VDD-MVS | | | 84.23 144 | 84.58 140 | 83.20 182 | 91.17 147 | 65.16 214 | 83.25 187 | 84.97 256 | 79.79 91 | 87.18 152 | 94.27 73 | 74.77 183 | 90.89 206 | 69.24 220 | 96.54 105 | 93.55 127 |
|
IterMVS-LS | | | 84.73 129 | 84.98 129 | 83.96 165 | 87.35 221 | 63.66 225 | 83.25 187 | 89.88 176 | 76.06 134 | 89.62 112 | 92.37 141 | 73.40 201 | 92.52 159 | 78.16 131 | 94.77 176 | 95.69 44 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
DP-MVS Recon | | | 84.05 149 | 83.22 160 | 86.52 110 | 91.73 125 | 75.27 127 | 83.23 189 | 92.40 104 | 72.04 197 | 82.04 245 | 88.33 231 | 77.91 149 | 93.95 107 | 66.17 245 | 95.12 163 | 90.34 227 |
|
EIA-MVS | | | 82.19 179 | 81.23 191 | 85.10 141 | 87.95 209 | 69.17 187 | 83.22 190 | 93.33 67 | 70.42 212 | 78.58 287 | 79.77 341 | 77.29 155 | 94.20 95 | 71.51 201 | 88.96 279 | 91.93 189 |
|
DU-MVS | | | 86.80 94 | 86.99 94 | 86.21 120 | 93.24 77 | 67.02 201 | 83.16 191 | 92.21 108 | 81.73 70 | 90.92 83 | 91.97 149 | 77.20 156 | 93.99 104 | 74.16 173 | 98.35 22 | 97.61 10 |
|
Fast-Effi-MVS+-dtu | | | 82.54 174 | 81.41 188 | 85.90 126 | 85.60 253 | 76.53 120 | 83.07 192 | 89.62 181 | 73.02 181 | 79.11 284 | 83.51 303 | 80.74 125 | 90.24 224 | 68.76 227 | 89.29 274 | 90.94 210 |
|
casdiffmvs | | | 85.21 118 | 85.85 113 | 83.31 179 | 86.17 249 | 62.77 237 | 83.03 193 | 93.93 44 | 74.69 156 | 88.21 140 | 92.68 130 | 82.29 99 | 91.89 177 | 77.87 137 | 93.75 197 | 95.27 57 |
|
v1192 | | | 84.57 132 | 84.69 137 | 84.21 159 | 87.75 213 | 62.88 235 | 83.02 194 | 91.43 129 | 69.08 226 | 89.98 101 | 90.89 182 | 72.70 209 | 93.62 122 | 82.41 82 | 94.97 168 | 96.13 34 |
|
v1144 | | | 84.54 135 | 84.72 135 | 84.00 163 | 87.67 215 | 62.55 241 | 82.97 195 | 90.93 145 | 70.32 215 | 89.80 106 | 90.99 177 | 73.50 196 | 93.48 129 | 81.69 91 | 94.65 179 | 95.97 39 |
|
v144192 | | | 84.24 143 | 84.41 144 | 83.71 171 | 87.59 218 | 61.57 251 | 82.95 196 | 91.03 141 | 67.82 243 | 89.80 106 | 90.49 194 | 73.28 202 | 93.51 128 | 81.88 90 | 94.89 171 | 96.04 38 |
|
v1921920 | | | 84.23 144 | 84.37 146 | 83.79 168 | 87.64 217 | 61.71 250 | 82.91 197 | 91.20 137 | 67.94 240 | 90.06 96 | 90.34 196 | 72.04 216 | 93.59 123 | 82.32 84 | 94.91 169 | 96.07 36 |
|
dcpmvs_2 | | | 84.23 144 | 85.14 126 | 81.50 213 | 88.61 196 | 61.98 249 | 82.90 198 | 93.11 80 | 68.66 232 | 92.77 52 | 92.39 137 | 78.50 142 | 87.63 267 | 76.99 148 | 92.30 226 | 94.90 65 |
|
v1240 | | | 84.30 140 | 84.51 142 | 83.65 172 | 87.65 216 | 61.26 255 | 82.85 199 | 91.54 126 | 67.94 240 | 90.68 88 | 90.65 191 | 71.71 219 | 93.64 118 | 82.84 78 | 94.78 174 | 96.07 36 |
|
无先验 | | | | | | | | 82.81 200 | 85.62 241 | 58.09 308 | | | | 91.41 190 | 67.95 236 | | 84.48 296 |
|
MIMVSNet1 | | | 83.63 158 | 84.59 139 | 80.74 226 | 94.06 57 | 62.77 237 | 82.72 201 | 84.53 259 | 77.57 121 | 90.34 92 | 95.92 25 | 76.88 168 | 85.83 293 | 61.88 276 | 97.42 78 | 93.62 122 |
|
v2v482 | | | 84.09 147 | 84.24 148 | 83.62 173 | 87.13 226 | 61.40 252 | 82.71 202 | 89.71 178 | 72.19 195 | 89.55 116 | 91.41 165 | 70.70 224 | 93.20 138 | 81.02 96 | 93.76 195 | 96.25 32 |
|
test1111 | | | 78.53 229 | 78.85 220 | 77.56 274 | 92.22 106 | 47.49 355 | 82.61 203 | 69.24 349 | 72.43 186 | 85.28 193 | 94.20 79 | 51.91 313 | 90.07 234 | 65.36 253 | 96.45 110 | 95.11 62 |
|
hse-mvs2 | | | 83.47 162 | 81.81 182 | 88.47 81 | 91.03 150 | 82.27 59 | 82.61 203 | 83.69 261 | 71.27 202 | 86.70 165 | 86.05 268 | 63.04 261 | 92.41 161 | 78.26 129 | 93.62 201 | 90.71 216 |
|
CR-MVSNet | | | 74.00 275 | 73.04 278 | 76.85 284 | 79.58 322 | 62.64 239 | 82.58 205 | 76.90 301 | 50.50 352 | 75.72 309 | 92.38 138 | 48.07 325 | 84.07 308 | 68.72 229 | 82.91 333 | 83.85 305 |
|
RPMNet | | | 78.88 222 | 78.28 229 | 80.68 229 | 79.58 322 | 62.64 239 | 82.58 205 | 94.16 31 | 74.80 154 | 75.72 309 | 92.59 131 | 48.69 323 | 95.56 38 | 73.48 183 | 82.91 333 | 83.85 305 |
|
UniMVSNet_NR-MVSNet | | | 86.84 93 | 87.06 92 | 86.17 122 | 92.86 87 | 67.02 201 | 82.55 207 | 91.56 125 | 83.08 55 | 90.92 83 | 91.82 155 | 78.25 146 | 93.99 104 | 74.16 173 | 98.35 22 | 97.49 13 |
|
MVS_Test | | | 82.47 175 | 83.22 160 | 80.22 235 | 82.62 294 | 57.75 294 | 82.54 208 | 91.96 116 | 71.16 206 | 82.89 234 | 92.52 136 | 77.41 154 | 90.50 218 | 80.04 108 | 87.84 294 | 92.40 167 |
|
AUN-MVS | | | 81.18 192 | 78.78 221 | 88.39 84 | 90.93 152 | 82.14 60 | 82.51 209 | 83.67 262 | 64.69 270 | 80.29 272 | 85.91 271 | 51.07 317 | 92.38 162 | 76.29 155 | 93.63 200 | 90.65 220 |
|
Anonymous20240521 | | | 80.18 213 | 81.25 189 | 76.95 280 | 83.15 289 | 60.84 263 | 82.46 210 | 85.99 237 | 68.76 230 | 86.78 162 | 93.73 106 | 59.13 283 | 77.44 333 | 73.71 180 | 97.55 70 | 92.56 159 |
|
pm-mvs1 | | | 83.69 156 | 84.95 130 | 79.91 238 | 90.04 174 | 59.66 274 | 82.43 211 | 87.44 212 | 75.52 145 | 87.85 144 | 95.26 39 | 81.25 119 | 85.65 295 | 68.74 228 | 96.04 126 | 94.42 85 |
|
Patchmtry | | | 76.56 251 | 77.46 234 | 73.83 303 | 79.37 327 | 46.60 359 | 82.41 212 | 76.90 301 | 73.81 165 | 85.56 190 | 92.38 138 | 48.07 325 | 83.98 309 | 63.36 266 | 95.31 156 | 90.92 211 |
|
EPNet_dtu | | | 72.87 284 | 71.33 295 | 77.49 276 | 77.72 336 | 60.55 267 | 82.35 213 | 75.79 308 | 66.49 252 | 58.39 370 | 81.06 328 | 53.68 310 | 85.98 290 | 53.55 324 | 92.97 215 | 85.95 282 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
TinyColmap | | | 81.25 191 | 82.34 176 | 77.99 268 | 85.33 257 | 60.68 266 | 82.32 214 | 88.33 200 | 71.26 204 | 86.97 160 | 92.22 147 | 77.10 159 | 86.98 275 | 62.37 271 | 95.17 160 | 86.31 279 |
|
TransMVSNet (Re) | | | 84.02 150 | 85.74 116 | 78.85 251 | 91.00 151 | 55.20 313 | 82.29 215 | 87.26 215 | 79.65 94 | 88.38 137 | 95.52 34 | 83.00 88 | 86.88 276 | 67.97 235 | 96.60 103 | 94.45 84 |
|
Baseline_NR-MVSNet | | | 84.00 151 | 85.90 112 | 78.29 263 | 91.47 138 | 53.44 322 | 82.29 215 | 87.00 227 | 79.06 103 | 89.55 116 | 95.72 29 | 77.20 156 | 86.14 289 | 72.30 197 | 98.51 17 | 95.28 56 |
|
MG-MVS | | | 80.32 209 | 80.94 195 | 78.47 259 | 88.18 205 | 52.62 329 | 82.29 215 | 85.01 254 | 72.01 198 | 79.24 283 | 92.54 135 | 69.36 228 | 93.36 135 | 70.65 209 | 89.19 277 | 89.45 237 |
|
原ACMM2 | | | | | | | | 82.26 218 | | | | | | | | | |
|
NR-MVSNet | | | 86.00 107 | 86.22 106 | 85.34 137 | 93.24 77 | 64.56 218 | 82.21 219 | 90.46 155 | 80.99 78 | 88.42 135 | 91.97 149 | 77.56 152 | 93.85 110 | 72.46 196 | 98.65 12 | 97.61 10 |
|
PAPR | | | 78.84 223 | 78.10 231 | 81.07 220 | 85.17 258 | 60.22 269 | 82.21 219 | 90.57 154 | 62.51 279 | 75.32 314 | 84.61 294 | 74.99 178 | 92.30 166 | 59.48 293 | 88.04 291 | 90.68 218 |
|
EG-PatchMatch MVS | | | 84.08 148 | 84.11 149 | 83.98 164 | 92.22 106 | 72.61 147 | 82.20 221 | 87.02 224 | 72.63 185 | 88.86 125 | 91.02 176 | 78.52 141 | 91.11 198 | 73.41 184 | 91.09 248 | 88.21 256 |
|
HY-MVS | | 64.64 18 | 73.03 282 | 72.47 286 | 74.71 299 | 83.36 285 | 54.19 316 | 82.14 222 | 81.96 274 | 56.76 319 | 69.57 339 | 86.21 266 | 60.03 275 | 84.83 303 | 49.58 342 | 82.65 335 | 85.11 291 |
|
FMVSNet3 | | | 78.80 225 | 78.55 225 | 79.57 244 | 82.89 293 | 56.89 301 | 81.76 223 | 85.77 239 | 69.04 227 | 86.00 181 | 90.44 195 | 51.75 315 | 90.09 233 | 65.95 246 | 93.34 203 | 91.72 194 |
|
旧先验2 | | | | | | | | 81.73 224 | | 56.88 318 | 86.54 174 | | | 84.90 301 | 72.81 193 | | |
|
新几何2 | | | | | | | | 81.72 225 | | | | | | | | | |
|
1314 | | | 73.22 280 | 72.56 285 | 75.20 296 | 80.41 318 | 57.84 292 | 81.64 226 | 85.36 243 | 51.68 344 | 73.10 325 | 76.65 354 | 61.45 267 | 85.19 298 | 63.54 264 | 79.21 349 | 82.59 321 |
|
1121 | | | 80.86 196 | 79.81 213 | 84.02 162 | 93.93 60 | 78.70 88 | 81.64 226 | 80.18 286 | 55.43 323 | 83.67 223 | 91.15 171 | 71.29 221 | 91.41 190 | 67.95 236 | 93.06 211 | 81.96 330 |
|
MVS | | | 73.21 281 | 72.59 283 | 75.06 298 | 80.97 307 | 60.81 264 | 81.64 226 | 85.92 238 | 46.03 360 | 71.68 331 | 77.54 348 | 68.47 233 | 89.77 239 | 55.70 311 | 85.39 312 | 74.60 355 |
|
v148 | | | 82.31 176 | 82.48 174 | 81.81 210 | 85.59 254 | 59.66 274 | 81.47 229 | 86.02 236 | 72.85 182 | 88.05 141 | 90.65 191 | 70.73 223 | 90.91 205 | 75.15 167 | 91.79 239 | 94.87 67 |
|
MVS_0304 | | | 78.17 232 | 77.23 239 | 80.99 224 | 84.13 278 | 69.07 189 | 81.39 230 | 80.81 282 | 76.28 131 | 67.53 347 | 89.11 221 | 62.87 263 | 86.77 279 | 60.90 286 | 92.01 237 | 87.13 271 |
|
V42 | | | 83.47 162 | 83.37 159 | 83.75 170 | 83.16 288 | 63.33 229 | 81.31 231 | 90.23 168 | 69.51 222 | 90.91 85 | 90.81 185 | 74.16 188 | 92.29 167 | 80.06 107 | 90.22 267 | 95.62 47 |
|
PM-MVS | | | 80.20 212 | 79.00 219 | 83.78 169 | 88.17 206 | 86.66 18 | 81.31 231 | 66.81 357 | 69.64 221 | 88.33 138 | 90.19 201 | 64.58 249 | 83.63 312 | 71.99 200 | 90.03 268 | 81.06 344 |
|
VPA-MVSNet | | | 83.47 162 | 84.73 133 | 79.69 242 | 90.29 166 | 57.52 295 | 81.30 233 | 88.69 193 | 76.29 130 | 87.58 148 | 94.44 64 | 80.60 127 | 87.20 271 | 66.60 243 | 96.82 96 | 94.34 89 |
|
CMPMVS |  | 59.41 20 | 75.12 263 | 73.57 271 | 79.77 239 | 75.84 350 | 67.22 198 | 81.21 234 | 82.18 272 | 50.78 349 | 76.50 299 | 87.66 242 | 55.20 307 | 82.99 314 | 62.17 275 | 90.64 266 | 89.09 248 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
OpenMVS_ROB |  | 70.19 17 | 77.77 238 | 77.46 234 | 78.71 254 | 84.39 269 | 61.15 256 | 81.18 235 | 82.52 269 | 62.45 281 | 83.34 228 | 87.37 247 | 66.20 244 | 88.66 257 | 64.69 258 | 85.02 317 | 86.32 278 |
|
thres100view900 | | | 75.45 259 | 75.05 259 | 76.66 286 | 87.27 222 | 51.88 334 | 81.07 236 | 73.26 328 | 75.68 143 | 83.25 229 | 86.37 261 | 45.54 338 | 88.80 252 | 51.98 333 | 90.99 252 | 89.31 241 |
|
MVS_111021_LR | | | 84.28 141 | 83.76 155 | 85.83 129 | 89.23 185 | 83.07 53 | 80.99 237 | 83.56 263 | 72.71 184 | 86.07 180 | 89.07 222 | 81.75 114 | 86.19 288 | 77.11 146 | 93.36 202 | 88.24 255 |
|
wuyk23d | | | 75.13 262 | 79.30 217 | 62.63 342 | 75.56 351 | 75.18 128 | 80.89 238 | 73.10 330 | 75.06 152 | 94.76 12 | 95.32 36 | 87.73 42 | 52.85 371 | 34.16 370 | 97.11 86 | 59.85 367 |
|
pmmvs-eth3d | | | 78.42 231 | 77.04 241 | 82.57 198 | 87.44 220 | 74.41 131 | 80.86 239 | 79.67 289 | 55.68 321 | 84.69 203 | 90.31 198 | 60.91 269 | 85.42 296 | 62.20 273 | 91.59 243 | 87.88 263 |
|
tfpnnormal | | | 81.79 186 | 82.95 165 | 78.31 261 | 88.93 191 | 55.40 309 | 80.83 240 | 82.85 268 | 76.81 127 | 85.90 185 | 94.14 84 | 74.58 186 | 86.51 283 | 66.82 242 | 95.68 146 | 93.01 141 |
|
PCF-MVS | | 74.62 15 | 82.15 180 | 80.92 196 | 85.84 128 | 89.43 180 | 72.30 154 | 80.53 241 | 91.82 120 | 57.36 315 | 87.81 145 | 89.92 207 | 77.67 151 | 93.63 119 | 58.69 295 | 95.08 164 | 91.58 199 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
thres600view7 | | | 75.97 256 | 75.35 258 | 77.85 272 | 87.01 232 | 51.84 335 | 80.45 242 | 73.26 328 | 75.20 150 | 83.10 232 | 86.31 264 | 45.54 338 | 89.05 248 | 55.03 318 | 92.24 230 | 92.66 156 |
|
KD-MVS_self_test | | | 81.93 185 | 83.14 163 | 78.30 262 | 84.75 263 | 52.75 326 | 80.37 243 | 89.42 185 | 70.24 217 | 90.26 94 | 93.39 110 | 74.55 187 | 86.77 279 | 68.61 230 | 96.64 100 | 95.38 52 |
|
BH-untuned | | | 80.96 195 | 80.99 194 | 80.84 225 | 88.55 198 | 68.23 191 | 80.33 244 | 88.46 195 | 72.79 183 | 86.55 169 | 86.76 257 | 74.72 184 | 91.77 181 | 61.79 277 | 88.99 278 | 82.52 324 |
|
MVP-Stereo | | | 75.81 258 | 73.51 273 | 82.71 193 | 89.35 181 | 73.62 134 | 80.06 245 | 85.20 247 | 60.30 298 | 73.96 321 | 87.94 237 | 57.89 293 | 89.45 245 | 52.02 332 | 74.87 359 | 85.06 292 |
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
LCM-MVSNet-Re | | | 83.48 161 | 85.06 127 | 78.75 253 | 85.94 252 | 55.75 308 | 80.05 246 | 94.27 23 | 76.47 129 | 96.09 5 | 94.54 60 | 83.31 86 | 89.75 241 | 59.95 290 | 94.89 171 | 90.75 215 |
|
USDC | | | 76.63 249 | 76.73 245 | 76.34 289 | 83.46 284 | 57.20 298 | 80.02 247 | 88.04 206 | 52.14 341 | 83.65 224 | 91.25 167 | 63.24 258 | 86.65 282 | 54.66 320 | 94.11 189 | 85.17 290 |
|
ANet_high | | | 83.17 168 | 85.68 118 | 75.65 294 | 81.24 304 | 45.26 362 | 79.94 248 | 92.91 91 | 83.83 43 | 91.33 77 | 96.88 10 | 80.25 131 | 85.92 291 | 68.89 226 | 95.89 135 | 95.76 43 |
|
baseline1 | | | 73.26 279 | 73.54 272 | 72.43 312 | 84.92 260 | 47.79 354 | 79.89 249 | 74.00 320 | 65.93 254 | 78.81 286 | 86.28 265 | 56.36 300 | 81.63 321 | 56.63 305 | 79.04 350 | 87.87 264 |
|
tpm2 | | | 68.45 311 | 66.83 317 | 73.30 305 | 78.93 332 | 48.50 350 | 79.76 250 | 71.76 339 | 47.50 356 | 69.92 338 | 83.60 302 | 42.07 355 | 88.40 259 | 48.44 347 | 79.51 345 | 83.01 319 |
|
tpmvs | | | 70.16 301 | 69.56 305 | 71.96 314 | 74.71 359 | 48.13 351 | 79.63 251 | 75.45 313 | 65.02 268 | 70.26 336 | 81.88 321 | 45.34 343 | 85.68 294 | 58.34 297 | 75.39 358 | 82.08 329 |
|
testdata1 | | | | | | | | 79.62 252 | | 73.95 164 | | | | | | | |
|
xiu_mvs_v1_base_debu | | | 80.84 197 | 80.14 208 | 82.93 188 | 88.31 202 | 71.73 162 | 79.53 253 | 87.17 216 | 65.43 262 | 79.59 277 | 82.73 315 | 76.94 162 | 90.14 230 | 73.22 186 | 88.33 285 | 86.90 274 |
|
xiu_mvs_v1_base | | | 80.84 197 | 80.14 208 | 82.93 188 | 88.31 202 | 71.73 162 | 79.53 253 | 87.17 216 | 65.43 262 | 79.59 277 | 82.73 315 | 76.94 162 | 90.14 230 | 73.22 186 | 88.33 285 | 86.90 274 |
|
xiu_mvs_v1_base_debi | | | 80.84 197 | 80.14 208 | 82.93 188 | 88.31 202 | 71.73 162 | 79.53 253 | 87.17 216 | 65.43 262 | 79.59 277 | 82.73 315 | 76.94 162 | 90.14 230 | 73.22 186 | 88.33 285 | 86.90 274 |
|
PVSNet_BlendedMVS | | | 78.80 225 | 77.84 232 | 81.65 212 | 84.43 266 | 63.41 227 | 79.49 256 | 90.44 156 | 61.70 287 | 75.43 312 | 87.07 255 | 69.11 230 | 91.44 187 | 60.68 287 | 92.24 230 | 90.11 232 |
|
test222 | | | | | | 93.31 75 | 76.54 117 | 79.38 257 | 77.79 297 | 52.59 336 | 82.36 240 | 90.84 184 | 66.83 242 | | | 91.69 241 | 81.25 339 |
|
PatchmatchNet |  | | 69.71 307 | 68.83 308 | 72.33 313 | 77.66 337 | 53.60 320 | 79.29 258 | 69.99 346 | 57.66 312 | 72.53 327 | 82.93 311 | 46.45 329 | 80.08 328 | 60.91 285 | 72.09 362 | 83.31 315 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
CostFormer | | | 69.98 305 | 68.68 310 | 73.87 302 | 77.14 339 | 50.72 344 | 79.26 259 | 74.51 317 | 51.94 343 | 70.97 335 | 84.75 292 | 45.16 346 | 87.49 268 | 55.16 317 | 79.23 348 | 83.40 312 |
|
tfpn200view9 | | | 74.86 267 | 74.23 266 | 76.74 285 | 86.24 246 | 52.12 331 | 79.24 260 | 73.87 322 | 73.34 172 | 81.82 250 | 84.60 295 | 46.02 332 | 88.80 252 | 51.98 333 | 90.99 252 | 89.31 241 |
|
thres400 | | | 75.14 261 | 74.23 266 | 77.86 271 | 86.24 246 | 52.12 331 | 79.24 260 | 73.87 322 | 73.34 172 | 81.82 250 | 84.60 295 | 46.02 332 | 88.80 252 | 51.98 333 | 90.99 252 | 92.66 156 |
|
MVS_111021_HR | | | 84.63 130 | 84.34 147 | 85.49 136 | 90.18 169 | 75.86 125 | 79.23 262 | 87.13 219 | 73.35 171 | 85.56 190 | 89.34 215 | 83.60 83 | 90.50 218 | 76.64 150 | 94.05 191 | 90.09 233 |
|
TAMVS | | | 78.08 234 | 76.36 247 | 83.23 180 | 90.62 160 | 72.87 140 | 79.08 263 | 80.01 288 | 61.72 286 | 81.35 259 | 86.92 256 | 63.96 254 | 88.78 255 | 50.61 337 | 93.01 213 | 88.04 259 |
|
MIMVSNet | | | 71.09 296 | 71.59 291 | 69.57 322 | 87.23 223 | 50.07 347 | 78.91 264 | 71.83 338 | 60.20 300 | 71.26 332 | 91.76 157 | 55.08 308 | 76.09 337 | 41.06 363 | 87.02 301 | 82.54 323 |
|
SCA | | | 73.32 278 | 72.57 284 | 75.58 295 | 81.62 299 | 55.86 306 | 78.89 265 | 71.37 342 | 61.73 285 | 74.93 317 | 83.42 306 | 60.46 271 | 87.01 272 | 58.11 300 | 82.63 337 | 83.88 302 |
|
DPM-MVS | | | 80.10 215 | 79.18 218 | 82.88 191 | 90.71 159 | 69.74 176 | 78.87 266 | 90.84 146 | 60.29 299 | 75.64 311 | 85.92 270 | 67.28 238 | 93.11 144 | 71.24 202 | 91.79 239 | 85.77 285 |
|
test_post1 | | | | | | | | 78.85 267 | | | | 3.13 375 | 45.19 345 | 80.13 327 | 58.11 300 | | |
|
mvs_anonymous | | | 78.13 233 | 78.76 222 | 76.23 292 | 79.24 328 | 50.31 346 | 78.69 268 | 84.82 257 | 61.60 288 | 83.09 233 | 92.82 124 | 73.89 192 | 87.01 272 | 68.33 233 | 86.41 305 | 91.37 202 |
|
WR-MVS | | | 83.56 159 | 84.40 145 | 81.06 221 | 93.43 72 | 54.88 314 | 78.67 269 | 85.02 253 | 81.24 75 | 90.74 87 | 91.56 162 | 72.85 206 | 91.08 199 | 68.00 234 | 98.04 37 | 97.23 17 |
|
c3_l | | | 81.64 187 | 81.59 186 | 81.79 211 | 80.86 310 | 59.15 281 | 78.61 270 | 90.18 170 | 68.36 233 | 87.20 151 | 87.11 254 | 69.39 227 | 91.62 182 | 78.16 131 | 94.43 184 | 94.60 76 |
|
test_yl | | | 78.71 227 | 78.51 226 | 79.32 247 | 84.32 270 | 58.84 285 | 78.38 271 | 85.33 244 | 75.99 137 | 82.49 237 | 86.57 258 | 58.01 289 | 90.02 236 | 62.74 269 | 92.73 219 | 89.10 246 |
|
DCV-MVSNet | | | 78.71 227 | 78.51 226 | 79.32 247 | 84.32 270 | 58.84 285 | 78.38 271 | 85.33 244 | 75.99 137 | 82.49 237 | 86.57 258 | 58.01 289 | 90.02 236 | 62.74 269 | 92.73 219 | 89.10 246 |
|
Fast-Effi-MVS+ | | | 81.04 194 | 80.57 197 | 82.46 200 | 87.50 219 | 63.22 231 | 78.37 273 | 89.63 180 | 68.01 237 | 81.87 248 | 82.08 320 | 82.31 97 | 92.65 157 | 67.10 238 | 88.30 289 | 91.51 201 |
|
tpmrst | | | 66.28 321 | 66.69 319 | 65.05 339 | 72.82 367 | 39.33 370 | 78.20 274 | 70.69 344 | 53.16 334 | 67.88 344 | 80.36 335 | 48.18 324 | 74.75 342 | 58.13 299 | 70.79 364 | 81.08 342 |
|
tpm cat1 | | | 66.76 318 | 65.21 324 | 71.42 315 | 77.09 340 | 50.62 345 | 78.01 275 | 73.68 326 | 44.89 362 | 68.64 340 | 79.00 342 | 45.51 340 | 82.42 318 | 49.91 340 | 70.15 365 | 81.23 341 |
|
jason | | | 77.42 240 | 75.75 253 | 82.43 201 | 87.10 230 | 69.27 182 | 77.99 276 | 81.94 275 | 51.47 345 | 77.84 292 | 85.07 287 | 60.32 273 | 89.00 249 | 70.74 208 | 89.27 276 | 89.03 249 |
jason: jason. |
CLD-MVS | | | 83.18 167 | 82.64 170 | 84.79 145 | 89.05 187 | 67.82 197 | 77.93 277 | 92.52 102 | 68.33 234 | 85.07 196 | 81.54 325 | 82.06 104 | 92.96 148 | 69.35 219 | 97.91 50 | 93.57 124 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
CDS-MVSNet | | | 77.32 241 | 75.40 256 | 83.06 184 | 89.00 189 | 72.48 151 | 77.90 278 | 82.17 273 | 60.81 294 | 78.94 285 | 83.49 304 | 59.30 281 | 88.76 256 | 54.64 321 | 92.37 225 | 87.93 262 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
eth_miper_zixun_eth | | | 80.84 197 | 80.22 206 | 82.71 193 | 81.41 302 | 60.98 261 | 77.81 279 | 90.14 171 | 67.31 246 | 86.95 161 | 87.24 251 | 64.26 251 | 92.31 165 | 75.23 166 | 91.61 242 | 94.85 71 |
|
BH-RMVSNet | | | 80.53 202 | 80.22 206 | 81.49 214 | 87.19 225 | 66.21 207 | 77.79 280 | 86.23 233 | 74.21 161 | 83.69 222 | 88.50 229 | 73.25 203 | 90.75 210 | 63.18 268 | 87.90 292 | 87.52 266 |
|
miper_ehance_all_eth | | | 80.34 208 | 80.04 211 | 81.24 218 | 79.82 321 | 58.95 283 | 77.66 281 | 89.66 179 | 65.75 259 | 85.99 184 | 85.11 283 | 68.29 234 | 91.42 189 | 76.03 157 | 92.03 234 | 93.33 128 |
|
PatchT | | | 70.52 299 | 72.76 281 | 63.79 341 | 79.38 326 | 33.53 375 | 77.63 282 | 65.37 359 | 73.61 167 | 71.77 330 | 92.79 127 | 44.38 350 | 75.65 340 | 64.53 261 | 85.37 313 | 82.18 328 |
|
BH-w/o | | | 76.57 250 | 76.07 251 | 78.10 266 | 86.88 235 | 65.92 209 | 77.63 282 | 86.33 231 | 65.69 260 | 80.89 263 | 79.95 338 | 68.97 232 | 90.74 211 | 53.01 329 | 85.25 315 | 77.62 350 |
|
diffmvs | | | 80.40 206 | 80.48 201 | 80.17 236 | 79.02 331 | 60.04 270 | 77.54 284 | 90.28 167 | 66.65 251 | 82.40 239 | 87.33 249 | 73.50 196 | 87.35 270 | 77.98 135 | 89.62 272 | 93.13 136 |
|
MSDG | | | 80.06 216 | 79.99 212 | 80.25 234 | 83.91 281 | 68.04 195 | 77.51 285 | 89.19 187 | 77.65 119 | 81.94 246 | 83.45 305 | 76.37 170 | 86.31 286 | 63.31 267 | 86.59 303 | 86.41 277 |
|
MVSTER | | | 77.09 243 | 75.70 254 | 81.25 216 | 75.27 355 | 61.08 257 | 77.49 286 | 85.07 250 | 60.78 295 | 86.55 169 | 88.68 227 | 43.14 353 | 90.25 222 | 73.69 181 | 90.67 263 | 92.42 165 |
|
cl22 | | | 78.97 220 | 78.21 230 | 81.24 218 | 77.74 335 | 59.01 282 | 77.46 287 | 87.13 219 | 65.79 256 | 84.32 210 | 85.10 284 | 58.96 285 | 90.88 207 | 75.36 165 | 92.03 234 | 93.84 107 |
|
TR-MVS | | | 76.77 248 | 75.79 252 | 79.72 241 | 86.10 251 | 65.79 210 | 77.14 288 | 83.02 266 | 65.20 267 | 81.40 258 | 82.10 319 | 66.30 243 | 90.73 212 | 55.57 312 | 85.27 314 | 82.65 320 |
|
ET-MVSNet_ETH3D | | | 75.28 260 | 72.77 280 | 82.81 192 | 83.03 291 | 68.11 193 | 77.09 289 | 76.51 305 | 60.67 297 | 77.60 296 | 80.52 333 | 38.04 362 | 91.15 197 | 70.78 206 | 90.68 262 | 89.17 244 |
|
cl____ | | | 80.42 205 | 80.23 204 | 81.02 222 | 79.99 319 | 59.25 278 | 77.07 290 | 87.02 224 | 67.37 245 | 86.18 178 | 89.21 218 | 63.08 260 | 90.16 227 | 76.31 154 | 95.80 140 | 93.65 120 |
|
DIV-MVS_self_test | | | 80.43 204 | 80.23 204 | 81.02 222 | 79.99 319 | 59.25 278 | 77.07 290 | 87.02 224 | 67.38 244 | 86.19 176 | 89.22 217 | 63.09 259 | 90.16 227 | 76.32 153 | 95.80 140 | 93.66 118 |
|
lupinMVS | | | 76.37 254 | 74.46 264 | 82.09 202 | 85.54 255 | 69.26 183 | 76.79 292 | 80.77 283 | 50.68 351 | 76.23 303 | 82.82 313 | 58.69 286 | 88.94 250 | 69.85 215 | 88.77 281 | 88.07 257 |
|
FMVSNet5 | | | 72.10 290 | 71.69 290 | 73.32 304 | 81.57 300 | 53.02 325 | 76.77 293 | 78.37 295 | 63.31 273 | 76.37 300 | 91.85 152 | 36.68 365 | 78.98 329 | 47.87 349 | 92.45 224 | 87.95 261 |
|
VPNet | | | 80.25 210 | 81.68 183 | 75.94 293 | 92.46 97 | 47.98 353 | 76.70 294 | 81.67 277 | 73.45 169 | 84.87 200 | 92.82 124 | 74.66 185 | 86.51 283 | 61.66 279 | 96.85 93 | 93.33 128 |
|
Anonymous202405211 | | | 80.51 203 | 81.19 192 | 78.49 258 | 88.48 199 | 57.26 297 | 76.63 295 | 82.49 270 | 81.21 76 | 84.30 214 | 92.24 146 | 67.99 235 | 86.24 287 | 62.22 272 | 95.13 161 | 91.98 188 |
|
PAPM | | | 71.77 292 | 70.06 302 | 76.92 281 | 86.39 238 | 53.97 317 | 76.62 296 | 86.62 229 | 53.44 332 | 63.97 360 | 84.73 293 | 57.79 294 | 92.34 164 | 39.65 365 | 81.33 341 | 84.45 297 |
|
DWT-MVSNet_test | | | 66.43 319 | 64.37 325 | 72.63 309 | 74.86 358 | 50.86 343 | 76.52 297 | 72.74 331 | 54.06 329 | 65.50 352 | 68.30 366 | 32.13 370 | 84.84 302 | 61.63 280 | 73.59 360 | 82.19 327 |
|
1112_ss | | | 74.82 268 | 73.74 269 | 78.04 267 | 89.57 177 | 60.04 270 | 76.49 298 | 87.09 223 | 54.31 327 | 73.66 323 | 79.80 339 | 60.25 274 | 86.76 281 | 58.37 296 | 84.15 326 | 87.32 269 |
|
DELS-MVS | | | 81.44 189 | 81.25 189 | 82.03 203 | 84.27 272 | 62.87 236 | 76.47 299 | 92.49 103 | 70.97 207 | 81.64 255 | 83.83 300 | 75.03 177 | 92.70 155 | 74.29 171 | 92.22 232 | 90.51 224 |
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 |
IterMVS | | | 76.91 245 | 76.34 248 | 78.64 255 | 80.91 308 | 64.03 223 | 76.30 300 | 79.03 292 | 64.88 269 | 83.11 231 | 89.16 219 | 59.90 277 | 84.46 305 | 68.61 230 | 85.15 316 | 87.42 267 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
IterMVS-SCA-FT | | | 80.64 201 | 79.41 215 | 84.34 156 | 83.93 280 | 69.66 178 | 76.28 301 | 81.09 280 | 72.43 186 | 86.47 175 | 90.19 201 | 60.46 271 | 93.15 143 | 77.45 142 | 86.39 306 | 90.22 228 |
|
pmmvs4 | | | 74.92 266 | 72.98 279 | 80.73 227 | 84.95 259 | 71.71 165 | 76.23 302 | 77.59 298 | 52.83 335 | 77.73 295 | 86.38 260 | 56.35 301 | 84.97 300 | 57.72 302 | 87.05 300 | 85.51 287 |
|
baseline2 | | | 69.77 306 | 66.89 316 | 78.41 260 | 79.51 324 | 58.09 290 | 76.23 302 | 69.57 348 | 57.50 314 | 64.82 358 | 77.45 350 | 46.02 332 | 88.44 258 | 53.08 326 | 77.83 352 | 88.70 253 |
|
PatchMatch-RL | | | 74.48 271 | 73.22 276 | 78.27 264 | 87.70 214 | 85.26 35 | 75.92 304 | 70.09 345 | 64.34 271 | 76.09 305 | 81.25 327 | 65.87 247 | 78.07 332 | 53.86 323 | 83.82 327 | 71.48 358 |
|
JIA-IIPM | | | 69.41 308 | 66.64 320 | 77.70 273 | 73.19 363 | 71.24 168 | 75.67 305 | 65.56 358 | 70.42 212 | 65.18 354 | 92.97 119 | 33.64 369 | 83.06 313 | 53.52 325 | 69.61 368 | 78.79 349 |
|
patch_mono-2 | | | 78.89 221 | 79.39 216 | 77.41 277 | 84.78 262 | 68.11 193 | 75.60 306 | 83.11 265 | 60.96 293 | 79.36 280 | 89.89 208 | 75.18 176 | 72.97 344 | 73.32 185 | 92.30 226 | 91.15 205 |
|
tpm | | | 67.95 312 | 68.08 313 | 67.55 331 | 78.74 333 | 43.53 367 | 75.60 306 | 67.10 356 | 54.92 325 | 72.23 328 | 88.10 234 | 42.87 354 | 75.97 338 | 52.21 331 | 80.95 344 | 83.15 317 |
|
VNet | | | 79.31 218 | 80.27 203 | 76.44 287 | 87.92 210 | 53.95 318 | 75.58 308 | 84.35 260 | 74.39 160 | 82.23 242 | 90.72 187 | 72.84 207 | 84.39 306 | 60.38 289 | 93.98 192 | 90.97 209 |
|
xiu_mvs_v2_base | | | 77.19 242 | 76.75 244 | 78.52 257 | 87.01 232 | 61.30 254 | 75.55 309 | 87.12 222 | 61.24 290 | 74.45 318 | 78.79 343 | 77.20 156 | 90.93 203 | 64.62 260 | 84.80 323 | 83.32 314 |
|
miper_enhance_ethall | | | 77.83 235 | 76.93 242 | 80.51 230 | 76.15 348 | 58.01 291 | 75.47 310 | 88.82 190 | 58.05 309 | 83.59 225 | 80.69 329 | 64.41 250 | 91.20 194 | 73.16 192 | 92.03 234 | 92.33 171 |
|
PS-MVSNAJ | | | 77.04 244 | 76.53 246 | 78.56 256 | 87.09 231 | 61.40 252 | 75.26 311 | 87.13 219 | 61.25 289 | 74.38 320 | 77.22 352 | 76.94 162 | 90.94 202 | 64.63 259 | 84.83 322 | 83.35 313 |
|
PVSNet_Blended | | | 76.49 252 | 75.40 256 | 79.76 240 | 84.43 266 | 63.41 227 | 75.14 312 | 90.44 156 | 57.36 315 | 75.43 312 | 78.30 346 | 69.11 230 | 91.44 187 | 60.68 287 | 87.70 296 | 84.42 298 |
|
thres200 | | | 72.34 288 | 71.55 293 | 74.70 300 | 83.48 283 | 51.60 336 | 75.02 313 | 73.71 325 | 70.14 218 | 78.56 288 | 80.57 332 | 46.20 330 | 88.20 262 | 46.99 352 | 89.29 274 | 84.32 299 |
|
EPMVS | | | 62.47 326 | 62.63 330 | 62.01 343 | 70.63 371 | 38.74 371 | 74.76 314 | 52.86 374 | 53.91 330 | 67.71 346 | 80.01 337 | 39.40 359 | 66.60 361 | 55.54 313 | 68.81 369 | 80.68 346 |
|
DSMNet-mixed | | | 60.98 334 | 61.61 333 | 59.09 351 | 72.88 366 | 45.05 363 | 74.70 315 | 46.61 378 | 26.20 372 | 65.34 353 | 90.32 197 | 55.46 305 | 63.12 368 | 41.72 362 | 81.30 342 | 69.09 362 |
|
FPMVS | | | 72.29 289 | 72.00 288 | 73.14 306 | 88.63 195 | 85.00 37 | 74.65 316 | 67.39 351 | 71.94 199 | 77.80 294 | 87.66 242 | 50.48 320 | 75.83 339 | 49.95 339 | 79.51 345 | 58.58 369 |
|
pmmvs5 | | | 70.73 298 | 70.07 301 | 72.72 308 | 77.03 341 | 52.73 327 | 74.14 317 | 75.65 311 | 50.36 353 | 72.17 329 | 85.37 281 | 55.42 306 | 80.67 325 | 52.86 330 | 87.59 297 | 84.77 294 |
|
MDTV_nov1_ep13 | | | | 68.29 312 | | 78.03 334 | 43.87 366 | 74.12 318 | 72.22 335 | 52.17 339 | 67.02 348 | 85.54 273 | 45.36 342 | 80.85 324 | 55.73 309 | 84.42 325 | |
|
IB-MVS | | 62.13 19 | 71.64 293 | 68.97 307 | 79.66 243 | 80.80 312 | 62.26 247 | 73.94 319 | 76.90 301 | 63.27 274 | 68.63 341 | 76.79 353 | 33.83 368 | 91.84 179 | 59.28 294 | 87.26 298 | 84.88 293 |
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 |
cascas | | | 76.29 255 | 74.81 260 | 80.72 228 | 84.47 265 | 62.94 234 | 73.89 320 | 87.34 213 | 55.94 320 | 75.16 316 | 76.53 355 | 63.97 253 | 91.16 196 | 65.00 254 | 90.97 255 | 88.06 258 |
|
MS-PatchMatch | | | 70.93 297 | 70.22 300 | 73.06 307 | 81.85 298 | 62.50 242 | 73.82 321 | 77.90 296 | 52.44 338 | 75.92 307 | 81.27 326 | 55.67 304 | 81.75 319 | 55.37 314 | 77.70 353 | 74.94 354 |
|
D2MVS | | | 76.84 246 | 75.67 255 | 80.34 233 | 80.48 317 | 62.16 248 | 73.50 322 | 84.80 258 | 57.61 313 | 82.24 241 | 87.54 244 | 51.31 316 | 87.65 266 | 70.40 213 | 93.19 208 | 91.23 204 |
|
GA-MVS | | | 75.83 257 | 74.61 261 | 79.48 246 | 81.87 297 | 59.25 278 | 73.42 323 | 82.88 267 | 68.68 231 | 79.75 276 | 81.80 322 | 50.62 319 | 89.46 244 | 66.85 240 | 85.64 311 | 89.72 234 |
|
Test_1112_low_res | | | 73.90 276 | 73.08 277 | 76.35 288 | 90.35 165 | 55.95 304 | 73.40 324 | 86.17 234 | 50.70 350 | 73.14 324 | 85.94 269 | 58.31 288 | 85.90 292 | 56.51 306 | 83.22 330 | 87.20 270 |
|
CL-MVSNet_self_test | | | 76.81 247 | 77.38 236 | 75.12 297 | 86.90 234 | 51.34 337 | 73.20 325 | 80.63 284 | 68.30 235 | 81.80 252 | 88.40 230 | 66.92 241 | 80.90 323 | 55.35 315 | 94.90 170 | 93.12 137 |
|
thisisatest0515 | | | 73.00 283 | 70.52 297 | 80.46 231 | 81.45 301 | 59.90 272 | 73.16 326 | 74.31 319 | 57.86 310 | 76.08 306 | 77.78 347 | 37.60 364 | 92.12 171 | 65.00 254 | 91.45 245 | 89.35 240 |
|
HyFIR lowres test | | | 75.12 263 | 72.66 282 | 82.50 199 | 91.44 139 | 65.19 213 | 72.47 327 | 87.31 214 | 46.79 357 | 80.29 272 | 84.30 297 | 52.70 312 | 92.10 172 | 51.88 336 | 86.73 302 | 90.22 228 |
|
Patchmatch-RL test | | | 74.48 271 | 73.68 270 | 76.89 283 | 84.83 261 | 66.54 205 | 72.29 328 | 69.16 350 | 57.70 311 | 86.76 163 | 86.33 262 | 45.79 337 | 82.59 315 | 69.63 217 | 90.65 265 | 81.54 335 |
|
MVS-HIRNet | | | 61.16 332 | 62.92 329 | 55.87 352 | 79.09 329 | 35.34 374 | 71.83 329 | 57.98 371 | 46.56 358 | 59.05 367 | 91.14 172 | 49.95 321 | 76.43 336 | 38.74 366 | 71.92 363 | 55.84 370 |
|
XXY-MVS | | | 74.44 273 | 76.19 249 | 69.21 323 | 84.61 264 | 52.43 330 | 71.70 330 | 77.18 300 | 60.73 296 | 80.60 266 | 90.96 180 | 75.44 172 | 69.35 352 | 56.13 308 | 88.33 285 | 85.86 284 |
|
ppachtmachnet_test | | | 74.73 270 | 74.00 268 | 76.90 282 | 80.71 313 | 56.89 301 | 71.53 331 | 78.42 294 | 58.24 307 | 79.32 282 | 82.92 312 | 57.91 292 | 84.26 307 | 65.60 251 | 91.36 246 | 89.56 236 |
|
dp | | | 60.70 335 | 60.29 337 | 61.92 345 | 72.04 369 | 38.67 372 | 70.83 332 | 64.08 360 | 51.28 346 | 60.75 363 | 77.28 351 | 36.59 366 | 71.58 348 | 47.41 350 | 62.34 371 | 75.52 353 |
|
MDTV_nov1_ep13_2view | | | | | | | 27.60 378 | 70.76 333 | | 46.47 359 | 61.27 362 | | 45.20 344 | | 49.18 343 | | 83.75 307 |
|
pmmvs3 | | | 62.47 326 | 60.02 338 | 69.80 320 | 71.58 370 | 64.00 224 | 70.52 334 | 58.44 370 | 39.77 368 | 66.05 349 | 75.84 356 | 27.10 379 | 72.28 345 | 46.15 354 | 84.77 324 | 73.11 356 |
|
Anonymous20231206 | | | 71.38 295 | 71.88 289 | 69.88 319 | 86.31 243 | 54.37 315 | 70.39 335 | 74.62 315 | 52.57 337 | 76.73 298 | 88.76 225 | 59.94 276 | 72.06 346 | 44.35 358 | 93.23 207 | 83.23 316 |
|
test20.03 | | | 73.75 277 | 74.59 263 | 71.22 316 | 81.11 306 | 51.12 341 | 70.15 336 | 72.10 336 | 70.42 212 | 80.28 274 | 91.50 163 | 64.21 252 | 74.72 343 | 46.96 353 | 94.58 180 | 87.82 265 |
|
UnsupCasMVSNet_eth | | | 71.63 294 | 72.30 287 | 69.62 321 | 76.47 345 | 52.70 328 | 70.03 337 | 80.97 281 | 59.18 302 | 79.36 280 | 88.21 233 | 60.50 270 | 69.12 353 | 58.33 298 | 77.62 354 | 87.04 272 |
|
our_test_3 | | | 71.85 291 | 71.59 291 | 72.62 310 | 80.71 313 | 53.78 319 | 69.72 338 | 71.71 341 | 58.80 304 | 78.03 289 | 80.51 334 | 56.61 299 | 78.84 330 | 62.20 273 | 86.04 309 | 85.23 289 |
|
Patchmatch-test | | | 65.91 322 | 67.38 314 | 61.48 347 | 75.51 352 | 43.21 368 | 68.84 339 | 63.79 361 | 62.48 280 | 72.80 326 | 83.42 306 | 44.89 348 | 59.52 369 | 48.27 348 | 86.45 304 | 81.70 332 |
|
CHOSEN 1792x2688 | | | 72.45 286 | 70.56 296 | 78.13 265 | 90.02 175 | 63.08 232 | 68.72 340 | 83.16 264 | 42.99 366 | 75.92 307 | 85.46 277 | 57.22 297 | 85.18 299 | 49.87 341 | 81.67 338 | 86.14 280 |
|
testgi | | | 72.36 287 | 74.61 261 | 65.59 336 | 80.56 315 | 42.82 369 | 68.29 341 | 73.35 327 | 66.87 249 | 81.84 249 | 89.93 206 | 72.08 215 | 66.92 360 | 46.05 355 | 92.54 223 | 87.01 273 |
|
test-LLR | | | 67.21 314 | 66.74 318 | 68.63 327 | 76.45 346 | 55.21 311 | 67.89 342 | 67.14 354 | 62.43 282 | 65.08 355 | 72.39 360 | 43.41 351 | 69.37 350 | 61.00 283 | 84.89 320 | 81.31 337 |
|
TESTMET0.1,1 | | | 61.29 331 | 60.32 336 | 64.19 340 | 72.06 368 | 51.30 338 | 67.89 342 | 62.09 362 | 45.27 361 | 60.65 364 | 69.01 363 | 27.93 377 | 64.74 366 | 56.31 307 | 81.65 340 | 76.53 351 |
|
test-mter | | | 65.00 324 | 63.79 327 | 68.63 327 | 76.45 346 | 55.21 311 | 67.89 342 | 67.14 354 | 50.98 348 | 65.08 355 | 72.39 360 | 28.27 376 | 69.37 350 | 61.00 283 | 84.89 320 | 81.31 337 |
|
UnsupCasMVSNet_bld | | | 69.21 309 | 69.68 304 | 67.82 330 | 79.42 325 | 51.15 340 | 67.82 345 | 75.79 308 | 54.15 328 | 77.47 297 | 85.36 282 | 59.26 282 | 70.64 349 | 48.46 346 | 79.35 347 | 81.66 333 |
|
ADS-MVSNet2 | | | 65.87 323 | 63.64 328 | 72.55 311 | 73.16 364 | 56.92 300 | 67.10 346 | 74.81 314 | 49.74 354 | 66.04 350 | 82.97 309 | 46.71 327 | 77.26 334 | 42.29 360 | 69.96 366 | 83.46 310 |
|
ADS-MVSNet | | | 61.90 328 | 62.19 331 | 61.03 348 | 73.16 364 | 36.42 373 | 67.10 346 | 61.75 364 | 49.74 354 | 66.04 350 | 82.97 309 | 46.71 327 | 63.21 367 | 42.29 360 | 69.96 366 | 83.46 310 |
|
MDA-MVSNet-bldmvs | | | 77.47 239 | 76.90 243 | 79.16 249 | 79.03 330 | 64.59 216 | 66.58 348 | 75.67 310 | 73.15 179 | 88.86 125 | 88.99 223 | 66.94 240 | 81.23 322 | 64.71 257 | 88.22 290 | 91.64 197 |
|
WTY-MVS | | | 67.91 313 | 68.35 311 | 66.58 334 | 80.82 311 | 48.12 352 | 65.96 349 | 72.60 332 | 53.67 331 | 71.20 333 | 81.68 324 | 58.97 284 | 69.06 354 | 48.57 345 | 81.67 338 | 82.55 322 |
|
sss | | | 66.92 315 | 67.26 315 | 65.90 335 | 77.23 338 | 51.10 342 | 64.79 350 | 71.72 340 | 52.12 342 | 70.13 337 | 80.18 336 | 57.96 291 | 65.36 365 | 50.21 338 | 81.01 343 | 81.25 339 |
|
miper_lstm_enhance | | | 76.45 253 | 76.10 250 | 77.51 275 | 76.72 343 | 60.97 262 | 64.69 351 | 85.04 252 | 63.98 272 | 83.20 230 | 88.22 232 | 56.67 298 | 78.79 331 | 73.22 186 | 93.12 209 | 92.78 150 |
|
test0.0.03 1 | | | 64.66 325 | 64.36 326 | 65.57 337 | 75.03 357 | 46.89 358 | 64.69 351 | 61.58 366 | 62.43 282 | 71.18 334 | 77.54 348 | 43.41 351 | 68.47 355 | 40.75 364 | 82.65 335 | 81.35 336 |
|
PMMVS | | | 61.65 329 | 60.38 335 | 65.47 338 | 65.40 376 | 69.26 183 | 63.97 353 | 61.73 365 | 36.80 371 | 60.11 365 | 68.43 364 | 59.42 280 | 66.35 362 | 48.97 344 | 78.57 351 | 60.81 366 |
|
test123 | | | 6.27 346 | 8.08 349 | 0.84 359 | 1.11 383 | 0.57 383 | 62.90 354 | 0.82 383 | 0.54 377 | 1.07 379 | 2.75 378 | 1.26 382 | 0.30 378 | 1.04 376 | 1.26 377 | 1.66 374 |
|
KD-MVS_2432*1600 | | | 66.87 316 | 65.81 321 | 70.04 317 | 67.50 372 | 47.49 355 | 62.56 355 | 79.16 290 | 61.21 291 | 77.98 290 | 80.61 330 | 25.29 380 | 82.48 316 | 53.02 327 | 84.92 318 | 80.16 347 |
|
miper_refine_blended | | | 66.87 316 | 65.81 321 | 70.04 317 | 67.50 372 | 47.49 355 | 62.56 355 | 79.16 290 | 61.21 291 | 77.98 290 | 80.61 330 | 25.29 380 | 82.48 316 | 53.02 327 | 84.92 318 | 80.16 347 |
|
PVSNet | | 58.17 21 | 66.41 320 | 65.63 323 | 68.75 326 | 81.96 296 | 49.88 348 | 62.19 357 | 72.51 334 | 51.03 347 | 68.04 343 | 75.34 358 | 50.84 318 | 74.77 341 | 45.82 356 | 82.96 331 | 81.60 334 |
|
new_pmnet | | | 55.69 338 | 57.66 340 | 49.76 354 | 75.47 353 | 30.59 376 | 59.56 358 | 51.45 375 | 43.62 365 | 62.49 361 | 75.48 357 | 40.96 357 | 49.15 373 | 37.39 368 | 72.52 361 | 69.55 361 |
|
new-patchmatchnet | | | 70.10 302 | 73.37 275 | 60.29 349 | 81.23 305 | 16.95 379 | 59.54 359 | 74.62 315 | 62.93 276 | 80.97 261 | 87.93 238 | 62.83 264 | 71.90 347 | 55.24 316 | 95.01 167 | 92.00 185 |
|
testmvs | | | 5.91 347 | 7.65 350 | 0.72 360 | 1.20 382 | 0.37 384 | 59.14 360 | 0.67 384 | 0.49 378 | 1.11 378 | 2.76 377 | 0.94 383 | 0.24 379 | 1.02 377 | 1.47 376 | 1.55 375 |
|
N_pmnet | | | 70.20 300 | 68.80 309 | 74.38 301 | 80.91 308 | 84.81 40 | 59.12 361 | 76.45 306 | 55.06 324 | 75.31 315 | 82.36 318 | 55.74 303 | 54.82 370 | 47.02 351 | 87.24 299 | 83.52 309 |
|
YYNet1 | | | 70.06 303 | 70.44 298 | 68.90 324 | 73.76 361 | 53.42 323 | 58.99 362 | 67.20 353 | 58.42 306 | 87.10 155 | 85.39 280 | 59.82 278 | 67.32 357 | 59.79 291 | 83.50 329 | 85.96 281 |
|
MDA-MVSNet_test_wron | | | 70.05 304 | 70.44 298 | 68.88 325 | 73.84 360 | 53.47 321 | 58.93 363 | 67.28 352 | 58.43 305 | 87.09 156 | 85.40 279 | 59.80 279 | 67.25 358 | 59.66 292 | 83.54 328 | 85.92 283 |
|
PVSNet_0 | | 51.08 22 | 56.10 337 | 54.97 342 | 59.48 350 | 75.12 356 | 53.28 324 | 55.16 364 | 61.89 363 | 44.30 363 | 59.16 366 | 62.48 369 | 54.22 309 | 65.91 364 | 35.40 369 | 47.01 372 | 59.25 368 |
|
E-PMN | | | 61.59 330 | 61.62 332 | 61.49 346 | 66.81 374 | 55.40 309 | 53.77 365 | 60.34 367 | 66.80 250 | 58.90 368 | 65.50 367 | 40.48 358 | 66.12 363 | 55.72 310 | 86.25 307 | 62.95 365 |
|
EMVS | | | 61.10 333 | 60.81 334 | 61.99 344 | 65.96 375 | 55.86 306 | 53.10 366 | 58.97 369 | 67.06 247 | 56.89 371 | 63.33 368 | 40.98 356 | 67.03 359 | 54.79 319 | 86.18 308 | 63.08 364 |
|
CHOSEN 280x420 | | | 59.08 336 | 56.52 341 | 66.76 333 | 76.51 344 | 64.39 220 | 49.62 367 | 59.00 368 | 43.86 364 | 55.66 372 | 68.41 365 | 35.55 367 | 68.21 356 | 43.25 359 | 76.78 357 | 67.69 363 |
|
PMMVS2 | | | 55.64 339 | 59.27 339 | 44.74 355 | 64.30 377 | 12.32 380 | 40.60 368 | 49.79 376 | 53.19 333 | 65.06 357 | 84.81 291 | 53.60 311 | 49.76 372 | 32.68 372 | 89.41 273 | 72.15 357 |
|
tmp_tt | | | 20.25 343 | 24.50 346 | 7.49 358 | 4.47 381 | 8.70 381 | 34.17 369 | 25.16 381 | 1.00 376 | 32.43 375 | 18.49 373 | 39.37 360 | 9.21 377 | 21.64 374 | 43.75 373 | 4.57 373 |
|
MVE |  | 40.22 23 | 51.82 340 | 50.47 343 | 55.87 352 | 62.66 378 | 51.91 333 | 31.61 370 | 39.28 379 | 40.65 367 | 50.76 373 | 74.98 359 | 56.24 302 | 44.67 374 | 33.94 371 | 64.11 370 | 71.04 360 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
test_method | | | 30.46 341 | 29.60 344 | 33.06 356 | 17.99 380 | 3.84 382 | 13.62 371 | 73.92 321 | 2.79 374 | 18.29 376 | 53.41 371 | 28.53 375 | 43.25 375 | 22.56 373 | 35.27 374 | 52.11 371 |
|
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 | | | 20.81 342 | 27.75 345 | 0.00 361 | 0.00 384 | 0.00 385 | 0.00 372 | 85.44 242 | 0.00 379 | 0.00 380 | 82.82 313 | 81.46 116 | 0.00 380 | 0.00 378 | 0.00 378 | 0.00 376 |
|
pcd_1.5k_mvsjas | | | 6.41 345 | 8.55 348 | 0.00 361 | 0.00 384 | 0.00 385 | 0.00 372 | 0.00 385 | 0.00 379 | 0.00 380 | 0.00 379 | 76.94 162 | 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 | | | 6.65 344 | 8.87 347 | 0.00 361 | 0.00 384 | 0.00 385 | 0.00 372 | 0.00 385 | 0.00 379 | 0.00 380 | 79.80 339 | 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 | | | | | 88.81 71 | 91.55 133 | 77.99 94 | | 91.01 142 | | | | | 96.05 8 | 87.45 19 | 98.17 33 | 92.40 167 |
|
PC_three_1452 | | | | | | | | | | 58.96 303 | 90.06 96 | 91.33 166 | 80.66 126 | 93.03 147 | 75.78 160 | 95.94 132 | 92.48 163 |
|
No_MVS | | | | | 88.81 71 | 91.55 133 | 77.99 94 | | 91.01 142 | | | | | 96.05 8 | 87.45 19 | 98.17 33 | 92.40 167 |
|
test_one_0601 | | | | | | 93.85 63 | 73.27 138 | | 94.11 37 | 86.57 27 | 93.47 40 | 94.64 58 | 88.42 27 | | | | |
|
eth-test2 | | | | | | 0.00 384 | | | | | | | | | | | |
|
eth-test | | | | | | 0.00 384 | | | | | | | | | | | |
|
ZD-MVS | | | | | | 92.22 106 | 80.48 70 | | 91.85 118 | 71.22 205 | 90.38 91 | 92.98 117 | 86.06 63 | 96.11 6 | 81.99 87 | 96.75 98 | |
|
IU-MVS | | | | | | 94.18 50 | 72.64 144 | | 90.82 147 | 56.98 317 | 89.67 110 | | | | 85.78 48 | 97.92 48 | 93.28 130 |
|
test_241102_TWO | | | | | | | | | 93.71 53 | 83.77 44 | 93.49 38 | 94.27 73 | 89.27 22 | 95.84 22 | 86.03 45 | 97.82 54 | 92.04 183 |
|
test_241102_ONE | | | | | | 94.18 50 | 72.65 142 | | 93.69 54 | 83.62 46 | 94.11 23 | 93.78 104 | 90.28 15 | 95.50 48 | | | |
|
test_0728_THIRD | | | | | | | | | | 85.33 32 | 93.75 31 | 94.65 55 | 87.44 45 | 95.78 27 | 87.41 21 | 98.21 30 | 92.98 142 |
|
GSMVS | | | | | | | | | | | | | | | | | 83.88 302 |
|
test_part2 | | | | | | 93.86 62 | 77.77 98 | | | | 92.84 49 | | | | | | |
|
sam_mvs1 | | | | | | | | | | | | | 46.11 331 | | | | 83.88 302 |
|
sam_mvs | | | | | | | | | | | | | 45.92 336 | | | | |
|
MTGPA |  | | | | | | | | 91.81 121 | | | | | | | | |
|
test_post | | | | | | | | | | | | 3.10 376 | 45.43 341 | 77.22 335 | | | |
|
patchmatchnet-post | | | | | | | | | | | | 81.71 323 | 45.93 335 | 87.01 272 | | | |
|
gm-plane-assit | | | | | | 75.42 354 | 44.97 364 | | | 52.17 339 | | 72.36 362 | | 87.90 263 | 54.10 322 | | |
|
test9_res | | | | | | | | | | | | | | | 80.83 100 | 96.45 110 | 90.57 221 |
|
agg_prior2 | | | | | | | | | | | | | | | 79.68 113 | 96.16 122 | 90.22 228 |
|
agg_prior | | | | | | 91.58 130 | 77.69 99 | | 90.30 163 | | 84.32 210 | | | 93.18 139 | | | |
|
TestCases | | | | | 89.68 55 | 91.59 127 | 83.40 50 | | 95.44 9 | 79.47 95 | 88.00 142 | 93.03 115 | 82.66 92 | 91.47 185 | 70.81 204 | 96.14 123 | 94.16 95 |
|
test_prior | | | | | 86.32 113 | 90.59 161 | 71.99 159 | | 92.85 93 | | | | | 94.17 98 | | | 92.80 148 |
|
新几何1 | | | | | 82.95 187 | 93.96 59 | 78.56 90 | | 80.24 285 | 55.45 322 | 83.93 221 | 91.08 173 | 71.19 222 | 88.33 260 | 65.84 249 | 93.07 210 | 81.95 331 |
|
旧先验1 | | | | | | 91.97 113 | 71.77 161 | | 81.78 276 | | | 91.84 153 | 73.92 191 | | | 93.65 199 | 83.61 308 |
|
原ACMM1 | | | | | 84.60 150 | 92.81 90 | 74.01 133 | | 91.50 127 | 62.59 278 | 82.73 236 | 90.67 190 | 76.53 169 | 94.25 91 | 69.24 220 | 95.69 145 | 85.55 286 |
|
testdata2 | | | | | | | | | | | | | | 86.43 285 | 63.52 265 | | |
|
segment_acmp | | | | | | | | | | | | | 81.94 107 | | | | |
|
testdata | | | | | 79.54 245 | 92.87 85 | 72.34 153 | | 80.14 287 | 59.91 301 | 85.47 192 | 91.75 158 | 67.96 236 | 85.24 297 | 68.57 232 | 92.18 233 | 81.06 344 |
|
test12 | | | | | 86.57 108 | 90.74 157 | 72.63 146 | | 90.69 150 | | 82.76 235 | | 79.20 137 | 94.80 73 | | 95.32 154 | 92.27 176 |
|
plane_prior7 | | | | | | 93.45 70 | 77.31 108 | | | | | | | | | | |
|
plane_prior6 | | | | | | 92.61 91 | 76.54 117 | | | | | | 74.84 180 | | | | |
|
plane_prior5 | | | | | | | | | 93.61 58 | | | | | 95.22 59 | 80.78 101 | 95.83 137 | 94.46 82 |
|
plane_prior4 | | | | | | | | | | | | 92.95 120 | | | | | |
|
plane_prior3 | | | | | | | 76.85 115 | | | 77.79 118 | 86.55 169 | | | | | | |
|
plane_prior1 | | | | | | 92.83 89 | | | | | | | | | | | |
|
n2 | | | | | | | | | 0.00 385 | | | | | | | | |
|
nn | | | | | | | | | 0.00 385 | | | | | | | | |
|
door-mid | | | | | | | | | 74.45 318 | | | | | | | | |
|
lessismore_v0 | | | | | 85.95 124 | 91.10 149 | 70.99 170 | | 70.91 343 | | 91.79 69 | 94.42 67 | 61.76 266 | 92.93 150 | 79.52 117 | 93.03 212 | 93.93 104 |
|
LGP-MVS_train | | | | | 90.82 38 | 94.75 42 | 81.69 61 | | 94.27 23 | 82.35 63 | 93.67 34 | 94.82 50 | 91.18 5 | 95.52 43 | 85.36 51 | 98.73 7 | 95.23 59 |
|
test11 | | | | | | | | | 91.46 128 | | | | | | | | |
|
door | | | | | | | | | 72.57 333 | | | | | | | | |
|
HQP5-MVS | | | | | | | 70.66 171 | | | | | | | | | | |
|
BP-MVS | | | | | | | | | | | | | | | 77.30 144 | | |
|
HQP4-MVS | | | | | | | | | | | 80.56 268 | | | 94.61 80 | | | 93.56 125 |
|
HQP3-MVS | | | | | | | | | 92.68 99 | | | | | | | 94.47 182 | |
|
HQP2-MVS | | | | | | | | | | | | | 72.10 213 | | | | |
|
NP-MVS | | | | | | 91.95 114 | 74.55 130 | | | | | 90.17 203 | | | | | |
|
ACMMP++_ref | | | | | | | | | | | | | | | | 95.74 144 | |
|
ACMMP++ | | | | | | | | | | | | | | | | 97.35 79 | |
|
Test By Simon | | | | | | | | | | | | | 79.09 138 | | | | |
|
ITE_SJBPF | | | | | 90.11 50 | 90.72 158 | 84.97 38 | | 90.30 163 | 81.56 72 | 90.02 98 | 91.20 170 | 82.40 96 | 90.81 209 | 73.58 182 | 94.66 178 | 94.56 77 |
|
DeepMVS_CX |  | | | | 24.13 357 | 32.95 379 | 29.49 377 | | 21.63 382 | 12.07 373 | 37.95 374 | 45.07 372 | 30.84 372 | 19.21 376 | 17.94 375 | 33.06 375 | 23.69 372 |
|