HPM-MVS++ | | | 89.02 3 | 89.15 3 | 88.63 1 | 95.01 1 | 76.03 1 | 92.38 14 | 92.85 33 | 80.26 14 | 87.78 11 | 94.27 16 | 75.89 7 | 96.81 8 | 87.45 9 | 96.44 1 | 93.05 62 |
|
CNVR-MVS | | | 88.93 4 | 89.13 4 | 88.33 3 | 94.77 2 | 73.82 6 | 90.51 39 | 93.00 25 | 80.90 10 | 88.06 9 | 94.06 24 | 76.43 4 | 96.84 7 | 88.48 4 | 95.99 4 | 94.34 15 |
|
ACMMPR | | | 87.44 15 | 87.23 17 | 88.08 7 | 94.64 3 | 73.59 8 | 93.04 5 | 93.20 18 | 76.78 52 | 84.66 35 | 94.52 7 | 68.81 55 | 96.65 14 | 84.53 23 | 94.90 25 | 94.00 28 |
|
region2R | | | 87.42 17 | 87.20 18 | 88.09 6 | 94.63 4 | 73.55 9 | 93.03 7 | 93.12 21 | 76.73 55 | 84.45 38 | 94.52 7 | 69.09 53 | 96.70 12 | 84.37 26 | 94.83 28 | 94.03 25 |
|
HFP-MVS | | | 87.58 13 | 87.47 14 | 87.94 11 | 94.58 5 | 73.54 11 | 93.04 5 | 93.24 16 | 76.78 52 | 84.91 29 | 94.44 12 | 70.78 38 | 96.61 16 | 84.53 23 | 94.89 26 | 93.66 36 |
|
#test# | | | 87.33 19 | 87.13 19 | 87.94 11 | 94.58 5 | 73.54 11 | 92.34 15 | 93.24 16 | 75.23 80 | 84.91 29 | 94.44 12 | 70.78 38 | 96.61 16 | 83.75 31 | 94.89 26 | 93.66 36 |
|
MCST-MVS | | | 87.37 18 | 87.25 16 | 87.73 20 | 94.53 7 | 72.46 31 | 89.82 53 | 93.82 5 | 73.07 121 | 84.86 34 | 92.89 45 | 76.22 5 | 96.33 23 | 84.89 19 | 95.13 22 | 94.40 12 |
|
APDe-MVS | | | 89.15 2 | 89.63 2 | 87.73 20 | 94.49 8 | 71.69 41 | 93.83 2 | 93.96 3 | 75.70 72 | 91.06 2 | 96.03 1 | 76.84 3 | 97.03 5 | 89.09 2 | 95.65 13 | 94.47 11 |
|
DP-MVS Recon | | | 83.11 67 | 82.09 72 | 86.15 50 | 94.44 9 | 70.92 51 | 88.79 81 | 92.20 53 | 70.53 161 | 79.17 91 | 91.03 79 | 64.12 89 | 96.03 31 | 68.39 159 | 90.14 73 | 91.50 102 |
|
XVS | | | 87.18 21 | 86.91 23 | 88.00 9 | 94.42 10 | 73.33 16 | 92.78 9 | 92.99 27 | 79.14 21 | 83.67 50 | 94.17 19 | 67.45 64 | 96.60 18 | 83.06 36 | 94.50 33 | 94.07 23 |
|
X-MVStestdata | | | 80.37 117 | 77.83 151 | 88.00 9 | 94.42 10 | 73.33 16 | 92.78 9 | 92.99 27 | 79.14 21 | 83.67 50 | 12.47 336 | 67.45 64 | 96.60 18 | 83.06 36 | 94.50 33 | 94.07 23 |
|
mPP-MVS | | | 86.67 28 | 86.32 29 | 87.72 22 | 94.41 12 | 73.55 9 | 92.74 11 | 92.22 52 | 76.87 50 | 82.81 60 | 94.25 17 | 66.44 71 | 96.24 26 | 82.88 40 | 94.28 39 | 93.38 49 |
|
NCCC | | | 88.06 7 | 88.01 10 | 88.24 5 | 94.41 12 | 73.62 7 | 91.22 30 | 92.83 34 | 81.50 7 | 85.79 21 | 93.47 33 | 73.02 24 | 97.00 6 | 84.90 17 | 94.94 24 | 94.10 21 |
|
MP-MVS | | | 87.71 11 | 87.64 12 | 87.93 14 | 94.36 14 | 73.88 4 | 92.71 13 | 92.65 41 | 77.57 35 | 83.84 47 | 94.40 15 | 72.24 30 | 96.28 25 | 85.65 13 | 95.30 21 | 93.62 43 |
|
HSP-MVS | | | 89.28 1 | 89.76 1 | 87.85 18 | 94.28 15 | 73.46 14 | 92.90 8 | 92.73 38 | 80.27 13 | 91.35 1 | 94.16 20 | 78.35 2 | 96.77 9 | 89.59 1 | 94.22 42 | 93.33 52 |
|
APD-MVS | | | 87.44 15 | 87.52 13 | 87.19 31 | 94.24 16 | 72.39 32 | 91.86 22 | 92.83 34 | 73.01 122 | 88.58 6 | 94.52 7 | 73.36 21 | 96.49 21 | 84.26 27 | 95.01 23 | 92.70 69 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
PGM-MVS | | | 86.68 27 | 86.27 30 | 87.90 15 | 94.22 17 | 73.38 15 | 90.22 48 | 93.04 22 | 75.53 74 | 83.86 46 | 94.42 14 | 67.87 61 | 96.64 15 | 82.70 41 | 94.57 32 | 93.66 36 |
|
CP-MVS | | | 87.11 22 | 86.92 22 | 87.68 25 | 94.20 18 | 73.86 5 | 93.98 1 | 92.82 36 | 76.62 57 | 83.68 49 | 94.46 11 | 67.93 59 | 95.95 35 | 84.20 29 | 94.39 36 | 93.23 54 |
|
MPTG | | | 87.53 14 | 87.41 15 | 87.90 15 | 94.18 19 | 74.25 2 | 90.23 47 | 92.02 59 | 79.45 19 | 85.88 18 | 94.80 4 | 68.07 57 | 96.21 27 | 86.69 10 | 95.34 17 | 93.23 54 |
|
MTAPA | | | 87.23 20 | 87.00 20 | 87.90 15 | 94.18 19 | 74.25 2 | 86.58 160 | 92.02 59 | 79.45 19 | 85.88 18 | 94.80 4 | 68.07 57 | 96.21 27 | 86.69 10 | 95.34 17 | 93.23 54 |
|
114514_t | | | 80.68 106 | 79.51 111 | 84.20 89 | 94.09 21 | 67.27 118 | 89.64 61 | 91.11 95 | 58.75 278 | 74.08 187 | 90.72 84 | 58.10 170 | 95.04 63 | 69.70 149 | 89.42 81 | 90.30 144 |
|
HPM-MVS | | | 87.11 22 | 86.98 21 | 87.50 28 | 93.88 22 | 72.16 36 | 92.19 18 | 93.33 15 | 76.07 69 | 83.81 48 | 93.95 26 | 69.77 48 | 96.01 32 | 85.15 14 | 94.66 30 | 94.32 17 |
|
ACMMP_Plus | | | 88.05 9 | 88.08 9 | 87.94 11 | 93.70 23 | 73.05 18 | 90.86 33 | 93.59 8 | 76.27 66 | 88.14 7 | 95.09 3 | 71.06 36 | 96.67 13 | 87.67 6 | 96.37 2 | 94.09 22 |
|
HPM-MVS_fast | | | 85.35 48 | 84.95 49 | 86.57 44 | 93.69 24 | 70.58 56 | 92.15 19 | 91.62 79 | 73.89 98 | 82.67 62 | 94.09 23 | 62.60 120 | 95.54 42 | 80.93 49 | 92.93 48 | 93.57 44 |
|
TSAR-MVS + MP. | | | 88.02 10 | 88.11 8 | 87.72 22 | 93.68 25 | 72.13 37 | 91.41 26 | 92.35 49 | 74.62 89 | 88.90 5 | 93.85 27 | 75.75 8 | 96.00 33 | 87.80 5 | 94.63 31 | 95.04 2 |
|
MP-MVS-pluss | | | 87.67 12 | 87.72 11 | 87.54 26 | 93.64 26 | 72.04 38 | 89.80 55 | 93.50 10 | 75.17 83 | 86.34 16 | 95.29 2 | 70.86 37 | 96.00 33 | 88.78 3 | 96.04 3 | 94.58 7 |
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
ACMMP | | | 85.89 40 | 85.39 42 | 87.38 29 | 93.59 27 | 72.63 26 | 92.74 11 | 93.18 20 | 76.78 52 | 80.73 82 | 93.82 28 | 64.33 87 | 96.29 24 | 82.67 42 | 90.69 67 | 93.23 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 |
DeepC-MVS_fast | | 79.65 3 | 86.91 25 | 86.62 26 | 87.76 19 | 93.52 28 | 72.37 34 | 91.26 27 | 93.04 22 | 76.62 57 | 84.22 43 | 93.36 35 | 71.44 34 | 96.76 10 | 80.82 51 | 95.33 19 | 94.16 19 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
CDPH-MVS | | | 85.76 41 | 85.29 46 | 87.17 32 | 93.49 29 | 71.08 45 | 88.58 90 | 92.42 47 | 68.32 197 | 84.61 36 | 93.48 31 | 72.32 29 | 96.15 30 | 79.00 60 | 95.43 15 | 94.28 18 |
|
agg_prior3 | | | 86.16 37 | 85.85 38 | 87.10 34 | 93.31 30 | 72.86 23 | 88.77 82 | 91.68 78 | 68.29 198 | 84.26 42 | 92.83 47 | 72.83 25 | 95.42 47 | 84.97 15 | 95.71 10 | 93.02 63 |
|
DP-MVS | | | 76.78 194 | 74.57 206 | 83.42 112 | 93.29 31 | 69.46 76 | 88.55 91 | 83.70 235 | 63.98 237 | 70.20 225 | 88.89 118 | 54.01 202 | 94.80 73 | 46.66 293 | 81.88 166 | 86.01 260 |
|
CPTT-MVS | | | 83.73 56 | 83.33 57 | 84.92 72 | 93.28 32 | 70.86 52 | 92.09 20 | 90.38 112 | 68.75 191 | 79.57 87 | 92.83 47 | 60.60 156 | 93.04 150 | 80.92 50 | 91.56 59 | 90.86 117 |
|
TEST9 | | | | | | 93.26 33 | 72.96 19 | 88.75 84 | 91.89 68 | 68.44 196 | 85.00 27 | 93.10 39 | 74.36 16 | 95.41 48 | | | |
|
train_agg | | | 86.43 31 | 86.20 31 | 87.13 33 | 93.26 33 | 72.96 19 | 88.75 84 | 91.89 68 | 68.69 192 | 85.00 27 | 93.10 39 | 74.43 13 | 95.41 48 | 84.97 15 | 95.71 10 | 93.02 63 |
|
test_8 | | | | | | 93.13 35 | 72.57 28 | 88.68 87 | 91.84 71 | 68.69 192 | 84.87 33 | 93.10 39 | 74.43 13 | 95.16 56 | | | |
|
新几何1 | | | | | 83.42 112 | 93.13 35 | 70.71 54 | | 85.48 220 | 57.43 287 | 81.80 70 | 91.98 56 | 63.28 96 | 92.27 171 | 64.60 188 | 92.99 47 | 87.27 236 |
|
1121 | | | 80.84 97 | 79.77 102 | 84.05 94 | 93.11 37 | 70.78 53 | 84.66 205 | 85.42 221 | 57.37 288 | 81.76 71 | 92.02 55 | 63.41 94 | 94.12 93 | 67.28 165 | 92.93 48 | 87.26 237 |
|
AdaColmap | | | 80.58 110 | 79.42 113 | 84.06 93 | 93.09 38 | 68.91 84 | 89.36 64 | 88.97 166 | 69.27 179 | 75.70 163 | 89.69 100 | 57.20 179 | 95.77 37 | 63.06 195 | 88.41 96 | 87.50 231 |
|
原ACMM1 | | | | | 84.35 85 | 93.01 39 | 68.79 85 | | 92.44 44 | 63.96 238 | 81.09 78 | 91.57 66 | 66.06 75 | 95.45 45 | 67.19 167 | 94.82 29 | 88.81 194 |
|
CSCG | | | 86.41 33 | 86.19 32 | 87.07 35 | 92.91 40 | 72.48 30 | 90.81 34 | 93.56 9 | 73.95 97 | 83.16 55 | 91.07 76 | 75.94 6 | 95.19 55 | 79.94 58 | 94.38 37 | 93.55 45 |
|
agg_prior1 | | | 86.22 36 | 86.09 35 | 86.62 42 | 92.85 41 | 71.94 39 | 88.59 89 | 91.78 74 | 68.96 189 | 84.41 39 | 93.18 38 | 74.94 9 | 94.93 65 | 84.75 22 | 95.33 19 | 93.01 65 |
|
agg_prior | | | | | | 92.85 41 | 71.94 39 | | 91.78 74 | | 84.41 39 | | | 94.93 65 | | | |
|
MG-MVS | | | 83.41 62 | 83.45 55 | 83.28 117 | 92.74 43 | 62.28 216 | 88.17 105 | 89.50 144 | 75.22 81 | 81.49 72 | 92.74 51 | 66.75 68 | 95.11 58 | 72.85 121 | 91.58 58 | 92.45 76 |
|
APD-MVS_3200maxsize | | | 85.97 38 | 85.88 36 | 86.22 49 | 92.69 44 | 69.53 73 | 91.93 21 | 92.99 27 | 73.54 109 | 85.94 17 | 94.51 10 | 65.80 78 | 95.61 39 | 83.04 38 | 92.51 53 | 93.53 47 |
|
test12 | | | | | 86.80 38 | 92.63 45 | 70.70 55 | | 91.79 73 | | 82.71 61 | | 71.67 32 | 96.16 29 | | 94.50 33 | 93.54 46 |
|
test_prior3 | | | 86.73 26 | 86.86 25 | 86.33 46 | 92.61 46 | 69.59 71 | 88.85 79 | 92.97 30 | 75.41 76 | 84.91 29 | 93.54 29 | 74.28 17 | 95.48 43 | 83.31 32 | 95.86 6 | 93.91 30 |
|
test_prior | | | | | 86.33 46 | 92.61 46 | 69.59 71 | | 92.97 30 | | | | | 95.48 43 | | | 93.91 30 |
|
SD-MVS | | | 88.06 7 | 88.50 7 | 86.71 40 | 92.60 48 | 72.71 24 | 91.81 23 | 93.19 19 | 77.87 32 | 90.32 3 | 94.00 25 | 74.83 10 | 93.78 112 | 87.63 7 | 94.27 40 | 93.65 41 |
|
PAPM_NR | | | 83.02 68 | 82.41 67 | 84.82 74 | 92.47 49 | 66.37 130 | 87.93 112 | 91.80 72 | 73.82 103 | 77.32 131 | 90.66 85 | 67.90 60 | 94.90 69 | 70.37 144 | 89.48 80 | 93.19 58 |
|
DeepPCF-MVS | | 80.84 1 | 88.10 6 | 88.56 6 | 86.73 39 | 92.24 50 | 69.03 79 | 89.57 62 | 93.39 14 | 77.53 39 | 89.79 4 | 94.12 22 | 78.98 1 | 96.58 20 | 85.66 12 | 95.72 9 | 94.58 7 |
|
abl_6 | | | 85.23 49 | 84.95 49 | 86.07 52 | 92.23 51 | 70.48 57 | 90.80 35 | 92.08 57 | 73.51 110 | 85.26 24 | 94.16 20 | 62.75 113 | 95.92 36 | 82.46 44 | 91.30 62 | 91.81 96 |
|
SteuartSystems-ACMMP | | | 88.72 5 | 88.86 5 | 88.32 4 | 92.14 52 | 72.96 19 | 93.73 3 | 93.67 7 | 80.19 15 | 88.10 8 | 94.80 4 | 73.76 20 | 97.11 3 | 87.51 8 | 95.82 8 | 94.90 4 |
Skip Steuart: Steuart Systems R&D Blog. |
UA-Net | | | 85.08 52 | 84.96 48 | 85.45 57 | 92.07 53 | 68.07 105 | 89.78 56 | 90.86 100 | 82.48 2 | 84.60 37 | 93.20 37 | 69.35 51 | 95.22 54 | 71.39 140 | 90.88 66 | 93.07 61 |
|
旧先验1 | | | | | | 91.96 54 | 65.79 140 | | 86.37 212 | | | 93.08 43 | 69.31 52 | | | 92.74 50 | 88.74 197 |
|
MSLP-MVS++ | | | 85.43 46 | 85.76 40 | 84.45 81 | 91.93 55 | 70.24 58 | 90.71 36 | 92.86 32 | 77.46 41 | 84.22 43 | 92.81 50 | 67.16 67 | 92.94 152 | 80.36 54 | 94.35 38 | 90.16 147 |
|
LFMVS | | | 81.82 83 | 81.23 82 | 83.57 109 | 91.89 56 | 63.43 197 | 89.84 52 | 81.85 261 | 77.04 47 | 83.21 53 | 93.10 39 | 52.26 214 | 93.43 132 | 71.98 134 | 89.95 76 | 93.85 33 |
|
PLC | | 70.83 11 | 78.05 164 | 76.37 175 | 83.08 126 | 91.88 57 | 67.80 109 | 88.19 104 | 89.46 146 | 64.33 233 | 69.87 235 | 88.38 132 | 53.66 204 | 93.58 123 | 58.86 231 | 82.73 157 | 87.86 223 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
MVS_111021_HR | | | 85.14 51 | 84.75 51 | 86.32 48 | 91.65 58 | 72.70 25 | 85.98 175 | 90.33 117 | 76.11 68 | 82.08 66 | 91.61 65 | 71.36 35 | 94.17 92 | 81.02 48 | 92.58 52 | 92.08 89 |
|
test222 | | | | | | 91.50 59 | 68.26 101 | 84.16 220 | 83.20 243 | 54.63 299 | 79.74 85 | 91.63 64 | 58.97 165 | | | 91.42 60 | 86.77 248 |
|
TSAR-MVS + GP. | | | 85.71 42 | 85.33 43 | 86.84 37 | 91.34 60 | 72.50 29 | 89.07 74 | 87.28 202 | 76.41 59 | 85.80 20 | 90.22 92 | 74.15 19 | 95.37 52 | 81.82 45 | 91.88 55 | 92.65 72 |
|
MAR-MVS | | | 81.84 82 | 80.70 88 | 85.27 61 | 91.32 61 | 71.53 43 | 89.82 53 | 90.92 98 | 69.77 170 | 78.50 100 | 86.21 198 | 62.36 127 | 94.52 79 | 65.36 181 | 92.05 54 | 89.77 172 |
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 |
DeepC-MVS | | 79.81 2 | 87.08 24 | 86.88 24 | 87.69 24 | 91.16 62 | 72.32 35 | 90.31 45 | 93.94 4 | 77.12 44 | 82.82 59 | 94.23 18 | 72.13 31 | 97.09 4 | 84.83 20 | 95.37 16 | 93.65 41 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
3Dnovator+ | | 77.84 4 | 85.48 44 | 84.47 52 | 88.51 2 | 91.08 63 | 73.49 13 | 93.18 4 | 93.78 6 | 80.79 11 | 76.66 142 | 93.37 34 | 60.40 160 | 96.75 11 | 77.20 78 | 93.73 45 | 95.29 1 |
|
VDD-MVS | | | 83.01 69 | 82.36 69 | 84.96 69 | 91.02 64 | 66.40 129 | 88.91 76 | 88.11 186 | 77.57 35 | 84.39 41 | 93.29 36 | 52.19 215 | 93.91 103 | 77.05 81 | 88.70 88 | 94.57 9 |
|
API-MVS | | | 81.99 80 | 81.23 82 | 84.26 88 | 90.94 65 | 70.18 64 | 91.10 31 | 89.32 149 | 71.51 149 | 78.66 98 | 88.28 135 | 65.26 80 | 95.10 61 | 64.74 187 | 91.23 63 | 87.51 230 |
|
testdata | | | | | 79.97 206 | 90.90 66 | 64.21 181 | | 84.71 226 | 59.27 274 | 85.40 22 | 92.91 44 | 62.02 133 | 89.08 239 | 68.95 154 | 91.37 61 | 86.63 252 |
|
PHI-MVS | | | 86.43 31 | 86.17 33 | 87.24 30 | 90.88 67 | 70.96 47 | 92.27 17 | 94.07 2 | 72.45 133 | 85.22 25 | 91.90 58 | 69.47 50 | 96.42 22 | 83.28 34 | 95.94 5 | 94.35 14 |
|
VNet | | | 82.21 76 | 82.41 67 | 81.62 177 | 90.82 68 | 60.93 223 | 84.47 210 | 89.78 137 | 76.36 64 | 84.07 45 | 91.88 59 | 64.71 85 | 90.26 221 | 70.68 141 | 88.89 84 | 93.66 36 |
|
PVSNet_Blended_VisFu | | | 82.62 72 | 81.83 77 | 84.96 69 | 90.80 69 | 69.76 68 | 88.74 86 | 91.70 77 | 69.39 175 | 78.96 93 | 88.46 130 | 65.47 79 | 94.87 71 | 74.42 105 | 88.57 91 | 90.24 145 |
|
LS3D | | | 76.95 192 | 74.82 204 | 83.37 115 | 90.45 70 | 67.36 117 | 89.15 72 | 86.94 205 | 61.87 256 | 69.52 238 | 90.61 86 | 51.71 227 | 94.53 78 | 46.38 296 | 86.71 114 | 88.21 216 |
|
VDDNet | | | 81.52 88 | 80.67 89 | 84.05 94 | 90.44 71 | 64.13 183 | 89.73 58 | 85.91 218 | 71.11 152 | 83.18 54 | 93.48 31 | 50.54 240 | 93.49 127 | 73.40 117 | 88.25 97 | 94.54 10 |
|
CNLPA | | | 78.08 163 | 76.79 169 | 81.97 164 | 90.40 72 | 71.07 46 | 87.59 118 | 84.55 228 | 66.03 218 | 72.38 203 | 89.64 102 | 57.56 174 | 86.04 267 | 59.61 224 | 83.35 149 | 88.79 195 |
|
PAPR | | | 81.66 86 | 80.89 87 | 83.99 99 | 90.27 73 | 64.00 187 | 86.76 156 | 91.77 76 | 68.84 190 | 77.13 138 | 89.50 104 | 67.63 62 | 94.88 70 | 67.55 162 | 88.52 94 | 93.09 60 |
|
Vis-MVSNet | | | 83.46 61 | 82.80 65 | 85.43 58 | 90.25 74 | 68.74 89 | 90.30 46 | 90.13 126 | 76.33 65 | 80.87 81 | 92.89 45 | 61.00 149 | 94.20 89 | 72.45 128 | 90.97 64 | 93.35 51 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
MVS_0304 | | | 86.37 35 | 85.81 39 | 88.02 8 | 90.13 75 | 72.39 32 | 89.66 60 | 92.75 37 | 81.64 6 | 82.66 63 | 92.04 54 | 64.44 86 | 97.35 1 | 84.76 21 | 94.25 41 | 94.33 16 |
|
EPP-MVSNet | | | 83.40 63 | 83.02 61 | 84.57 77 | 90.13 75 | 64.47 177 | 92.32 16 | 90.73 101 | 74.45 91 | 79.35 90 | 91.10 74 | 69.05 54 | 95.12 57 | 72.78 122 | 87.22 108 | 94.13 20 |
|
CANet | | | 86.45 30 | 86.10 34 | 87.51 27 | 90.09 77 | 70.94 49 | 89.70 59 | 92.59 42 | 81.78 4 | 81.32 73 | 91.43 71 | 70.34 41 | 97.23 2 | 84.26 27 | 93.36 46 | 94.37 13 |
|
HQP_MVS | | | 83.64 58 | 83.14 58 | 85.14 64 | 90.08 78 | 68.71 91 | 91.25 28 | 92.44 44 | 79.12 23 | 78.92 94 | 91.00 80 | 60.42 158 | 95.38 50 | 78.71 63 | 86.32 119 | 91.33 105 |
|
plane_prior7 | | | | | | 90.08 78 | 68.51 97 | | | | | | | | | | |
|
CHOSEN 1792x2688 | | | 77.63 178 | 75.69 190 | 83.44 111 | 89.98 80 | 68.58 96 | 78.70 268 | 87.50 199 | 56.38 293 | 75.80 158 | 86.84 170 | 58.67 166 | 91.40 199 | 61.58 210 | 85.75 126 | 90.34 143 |
|
IS-MVSNet | | | 83.15 65 | 82.81 64 | 84.18 90 | 89.94 81 | 63.30 199 | 91.59 24 | 88.46 183 | 79.04 25 | 79.49 88 | 92.16 52 | 65.10 82 | 94.28 84 | 67.71 160 | 91.86 56 | 94.95 3 |
|
plane_prior1 | | | | | | 89.90 82 | | | | | | | | | | | |
|
canonicalmvs | | | 85.91 39 | 85.87 37 | 86.04 53 | 89.84 83 | 69.44 77 | 90.45 43 | 93.00 25 | 76.70 56 | 88.01 10 | 91.23 73 | 73.28 22 | 93.91 103 | 81.50 47 | 88.80 86 | 94.77 5 |
|
plane_prior6 | | | | | | 89.84 83 | 68.70 93 | | | | | | 60.42 158 | | | | |
|
view600 | | | 76.20 202 | 75.21 198 | 79.16 220 | 89.64 85 | 55.82 276 | 85.74 182 | 82.06 256 | 73.88 99 | 75.74 159 | 87.85 143 | 51.84 222 | 91.66 191 | 46.75 289 | 83.42 145 | 90.00 158 |
|
view800 | | | 76.20 202 | 75.21 198 | 79.16 220 | 89.64 85 | 55.82 276 | 85.74 182 | 82.06 256 | 73.88 99 | 75.74 159 | 87.85 143 | 51.84 222 | 91.66 191 | 46.75 289 | 83.42 145 | 90.00 158 |
|
conf0.05thres1000 | | | 76.20 202 | 75.21 198 | 79.16 220 | 89.64 85 | 55.82 276 | 85.74 182 | 82.06 256 | 73.88 99 | 75.74 159 | 87.85 143 | 51.84 222 | 91.66 191 | 46.75 289 | 83.42 145 | 90.00 158 |
|
tfpn | | | 76.20 202 | 75.21 198 | 79.16 220 | 89.64 85 | 55.82 276 | 85.74 182 | 82.06 256 | 73.88 99 | 75.74 159 | 87.85 143 | 51.84 222 | 91.66 191 | 46.75 289 | 83.42 145 | 90.00 158 |
|
NP-MVS | | | | | | 89.62 89 | 68.32 99 | | | | | 90.24 90 | | | | | |
|
HyFIR lowres test | | | 77.53 179 | 75.40 195 | 83.94 102 | 89.59 90 | 66.62 126 | 80.36 252 | 88.64 180 | 56.29 294 | 76.45 145 | 85.17 218 | 57.64 173 | 93.28 135 | 61.34 213 | 83.10 153 | 91.91 92 |
|
TAPA-MVS | | 73.13 9 | 79.15 144 | 77.94 149 | 82.79 148 | 89.59 90 | 62.99 209 | 88.16 106 | 91.51 84 | 65.77 219 | 77.14 137 | 91.09 75 | 60.91 150 | 93.21 137 | 50.26 275 | 87.05 110 | 92.17 87 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
alignmvs | | | 85.48 44 | 85.32 44 | 85.96 54 | 89.51 92 | 69.47 75 | 89.74 57 | 92.47 43 | 76.17 67 | 87.73 12 | 91.46 70 | 70.32 42 | 93.78 112 | 81.51 46 | 88.95 83 | 94.63 6 |
|
PS-MVSNAJ | | | 81.69 84 | 81.02 86 | 83.70 105 | 89.51 92 | 68.21 103 | 84.28 218 | 90.09 127 | 70.79 156 | 81.26 77 | 85.62 210 | 63.15 101 | 94.29 83 | 75.62 96 | 88.87 85 | 88.59 206 |
|
ACMP | | 74.13 6 | 81.51 90 | 80.57 90 | 84.36 84 | 89.42 94 | 68.69 94 | 89.97 51 | 91.50 86 | 74.46 90 | 75.04 180 | 90.41 88 | 53.82 203 | 94.54 77 | 77.56 74 | 82.91 154 | 89.86 168 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
thres600view7 | | | 76.50 197 | 75.44 193 | 79.68 211 | 89.40 95 | 57.16 257 | 85.53 192 | 83.23 242 | 73.79 104 | 76.26 149 | 87.09 167 | 51.89 221 | 91.89 178 | 48.05 285 | 83.72 142 | 90.00 158 |
|
BH-RMVSNet | | | 79.61 133 | 78.44 139 | 83.14 123 | 89.38 96 | 65.93 136 | 84.95 201 | 87.15 203 | 73.56 108 | 78.19 115 | 89.79 99 | 56.67 182 | 93.36 133 | 59.53 226 | 86.74 113 | 90.13 149 |
|
Regformer-1 | | | 86.41 33 | 86.33 28 | 86.64 41 | 89.33 97 | 70.93 50 | 88.43 92 | 91.39 88 | 82.14 3 | 86.65 15 | 90.09 94 | 74.39 15 | 95.01 64 | 83.97 30 | 90.63 68 | 93.97 29 |
|
Regformer-2 | | | 86.63 29 | 86.53 27 | 86.95 36 | 89.33 97 | 71.24 44 | 88.43 92 | 92.05 58 | 82.50 1 | 86.88 14 | 90.09 94 | 74.45 12 | 95.61 39 | 84.38 25 | 90.63 68 | 94.01 27 |
|
HQP-NCC | | | | | | 89.33 97 | | 89.17 68 | | 76.41 59 | 77.23 134 | | | | | | |
|
ACMP_Plane | | | | | | 89.33 97 | | 89.17 68 | | 76.41 59 | 77.23 134 | | | | | | |
|
HQP-MVS | | | 82.61 73 | 82.02 74 | 84.37 83 | 89.33 97 | 66.98 122 | 89.17 68 | 92.19 54 | 76.41 59 | 77.23 134 | 90.23 91 | 60.17 161 | 95.11 58 | 77.47 75 | 85.99 123 | 91.03 111 |
|
ACMM | | 73.20 8 | 80.78 105 | 79.84 101 | 83.58 108 | 89.31 102 | 68.37 98 | 89.99 50 | 91.60 80 | 70.28 164 | 77.25 132 | 89.66 101 | 53.37 206 | 93.53 126 | 74.24 108 | 82.85 155 | 88.85 192 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
Test_1112_low_res | | | 76.40 199 | 75.44 193 | 79.27 216 | 89.28 103 | 58.09 244 | 81.69 242 | 87.07 204 | 59.53 272 | 72.48 201 | 86.67 180 | 61.30 142 | 89.33 234 | 60.81 217 | 80.15 185 | 90.41 141 |
|
F-COLMAP | | | 76.38 200 | 74.33 211 | 82.50 155 | 89.28 103 | 66.95 125 | 88.41 95 | 89.03 158 | 64.05 235 | 66.83 266 | 88.61 125 | 46.78 260 | 92.89 153 | 57.48 243 | 78.55 195 | 87.67 226 |
|
LPG-MVS_test | | | 82.08 77 | 81.27 81 | 84.50 79 | 89.23 105 | 68.76 87 | 90.22 48 | 91.94 66 | 75.37 78 | 76.64 143 | 91.51 67 | 54.29 198 | 94.91 67 | 78.44 65 | 83.78 139 | 89.83 169 |
|
LGP-MVS_train | | | | | 84.50 79 | 89.23 105 | 68.76 87 | | 91.94 66 | 75.37 78 | 76.64 143 | 91.51 67 | 54.29 198 | 94.91 67 | 78.44 65 | 83.78 139 | 89.83 169 |
|
BH-untuned | | | 79.47 138 | 78.60 132 | 82.05 162 | 89.19 107 | 65.91 137 | 86.07 174 | 88.52 182 | 72.18 139 | 75.42 167 | 87.69 149 | 61.15 146 | 93.54 125 | 60.38 218 | 86.83 112 | 86.70 250 |
|
xiu_mvs_v2_base | | | 81.69 84 | 81.05 85 | 83.60 107 | 89.15 108 | 68.03 106 | 84.46 212 | 90.02 131 | 70.67 159 | 81.30 76 | 86.53 190 | 63.17 100 | 94.19 90 | 75.60 97 | 88.54 93 | 88.57 208 |
|
thres400 | | | 76.50 197 | 75.37 196 | 79.86 207 | 89.13 109 | 57.65 253 | 85.17 197 | 83.60 236 | 73.41 112 | 76.45 145 | 86.39 193 | 52.12 216 | 91.95 177 | 48.33 282 | 83.75 141 | 90.00 158 |
|
1112_ss | | | 77.40 188 | 76.43 173 | 80.32 200 | 89.11 110 | 60.41 229 | 83.65 226 | 87.72 196 | 62.13 254 | 73.05 195 | 86.72 174 | 62.58 122 | 89.97 225 | 62.11 205 | 80.80 175 | 90.59 131 |
|
Regformer-3 | | | 85.23 49 | 85.07 47 | 85.70 56 | 88.95 111 | 69.01 81 | 88.29 101 | 89.91 135 | 80.95 9 | 85.01 26 | 90.01 96 | 72.45 28 | 94.19 90 | 82.50 43 | 87.57 101 | 93.90 32 |
|
Regformer-4 | | | 85.68 43 | 85.45 41 | 86.35 45 | 88.95 111 | 69.67 70 | 88.29 101 | 91.29 90 | 81.73 5 | 85.36 23 | 90.01 96 | 72.62 27 | 95.35 53 | 83.28 34 | 87.57 101 | 94.03 25 |
|
Fast-Effi-MVS+ | | | 80.81 100 | 79.92 99 | 83.47 110 | 88.85 113 | 64.51 171 | 85.53 192 | 89.39 147 | 70.79 156 | 78.49 101 | 85.06 221 | 67.54 63 | 93.58 123 | 67.03 170 | 86.58 115 | 92.32 80 |
|
PVSNet_BlendedMVS | | | 80.60 108 | 80.02 97 | 82.36 158 | 88.85 113 | 65.40 146 | 86.16 171 | 92.00 62 | 69.34 178 | 78.11 117 | 86.09 201 | 66.02 76 | 94.27 85 | 71.52 138 | 82.06 163 | 87.39 232 |
|
PVSNet_Blended | | | 80.98 94 | 80.34 93 | 82.90 138 | 88.85 113 | 65.40 146 | 84.43 214 | 92.00 62 | 67.62 202 | 78.11 117 | 85.05 222 | 66.02 76 | 94.27 85 | 71.52 138 | 89.50 79 | 89.01 188 |
|
MVS_111021_LR | | | 82.61 73 | 82.11 71 | 84.11 91 | 88.82 116 | 71.58 42 | 85.15 198 | 86.16 215 | 74.69 88 | 80.47 83 | 91.04 77 | 62.29 128 | 90.55 219 | 80.33 55 | 90.08 74 | 90.20 146 |
|
BH-w/o | | | 78.21 159 | 77.33 161 | 80.84 192 | 88.81 117 | 65.13 156 | 84.87 202 | 87.85 194 | 69.75 171 | 74.52 185 | 84.74 227 | 61.34 141 | 93.11 145 | 58.24 238 | 85.84 125 | 84.27 275 |
|
FIs | | | 82.07 78 | 82.42 66 | 81.04 190 | 88.80 118 | 58.34 242 | 88.26 103 | 93.49 11 | 76.93 49 | 78.47 102 | 91.04 77 | 69.92 46 | 92.34 170 | 69.87 148 | 84.97 128 | 92.44 77 |
|
OPM-MVS | | | 83.50 60 | 82.95 62 | 85.14 64 | 88.79 119 | 70.95 48 | 89.13 73 | 91.52 83 | 77.55 38 | 80.96 80 | 91.75 60 | 60.71 152 | 94.50 80 | 79.67 59 | 86.51 117 | 89.97 165 |
|
WR-MVS | | | 79.49 137 | 79.22 124 | 80.27 202 | 88.79 119 | 58.35 241 | 85.06 199 | 88.61 181 | 78.56 29 | 77.65 125 | 88.34 133 | 63.81 93 | 90.66 218 | 64.98 185 | 77.22 209 | 91.80 97 |
|
OMC-MVS | | | 82.69 71 | 81.97 76 | 84.85 73 | 88.75 121 | 67.42 114 | 87.98 108 | 90.87 99 | 74.92 86 | 79.72 86 | 91.65 62 | 62.19 131 | 93.96 98 | 75.26 101 | 86.42 118 | 93.16 59 |
|
ACMH | | 67.68 16 | 75.89 209 | 73.93 214 | 81.77 168 | 88.71 122 | 66.61 127 | 88.62 88 | 89.01 161 | 69.81 169 | 66.78 267 | 86.70 179 | 41.95 288 | 91.51 198 | 55.64 253 | 78.14 201 | 87.17 239 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
Vis-MVSNet (Re-imp) | | | 78.36 157 | 78.45 137 | 78.07 238 | 88.64 123 | 51.78 296 | 86.70 157 | 79.63 281 | 74.14 95 | 75.11 178 | 90.83 83 | 61.29 143 | 89.75 227 | 58.10 239 | 91.60 57 | 92.69 71 |
|
PatchMatch-RL | | | 72.38 240 | 70.90 239 | 76.80 253 | 88.60 124 | 67.38 116 | 79.53 259 | 76.17 296 | 62.75 248 | 69.36 241 | 82.00 256 | 45.51 269 | 84.89 275 | 53.62 262 | 80.58 178 | 78.12 306 |
|
ACMH+ | | 68.96 14 | 76.01 208 | 74.01 213 | 82.03 163 | 88.60 124 | 65.31 151 | 88.86 78 | 87.55 198 | 70.25 165 | 67.75 257 | 87.47 156 | 41.27 289 | 93.19 140 | 58.37 236 | 75.94 231 | 87.60 228 |
|
LTVRE_ROB | | 69.57 13 | 76.25 201 | 74.54 208 | 81.41 182 | 88.60 124 | 64.38 180 | 79.24 262 | 89.12 157 | 70.76 158 | 69.79 237 | 87.86 142 | 49.09 250 | 93.20 139 | 56.21 252 | 80.16 184 | 86.65 251 |
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 |
DELS-MVS | | | 85.41 47 | 85.30 45 | 85.77 55 | 88.49 127 | 67.93 107 | 85.52 194 | 93.44 12 | 78.70 28 | 83.63 52 | 89.03 117 | 74.57 11 | 95.71 38 | 80.26 56 | 94.04 43 | 93.66 36 |
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 |
CLD-MVS | | | 82.31 75 | 81.65 78 | 84.29 87 | 88.47 128 | 67.73 111 | 85.81 181 | 92.35 49 | 75.78 70 | 78.33 108 | 86.58 187 | 64.01 90 | 94.35 82 | 76.05 88 | 87.48 106 | 90.79 118 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
UniMVSNet_NR-MVSNet | | | 81.88 81 | 81.54 79 | 82.92 137 | 88.46 129 | 63.46 195 | 87.13 140 | 92.37 48 | 80.19 15 | 78.38 106 | 89.14 114 | 71.66 33 | 93.05 148 | 70.05 145 | 76.46 226 | 92.25 83 |
|
ab-mvs | | | 79.51 135 | 78.97 128 | 81.14 188 | 88.46 129 | 60.91 224 | 83.84 224 | 89.24 154 | 70.36 163 | 79.03 92 | 88.87 119 | 63.23 99 | 90.21 223 | 65.12 182 | 82.57 160 | 92.28 82 |
|
FC-MVSNet-test | | | 81.52 88 | 82.02 74 | 80.03 205 | 88.42 131 | 55.97 275 | 87.95 110 | 93.42 13 | 77.10 45 | 77.38 129 | 90.98 82 | 69.96 45 | 91.79 180 | 68.46 158 | 84.50 133 | 92.33 79 |
|
Effi-MVS+ | | | 83.62 59 | 83.08 59 | 85.24 62 | 88.38 132 | 67.45 113 | 88.89 77 | 89.15 156 | 75.50 75 | 82.27 64 | 88.28 135 | 69.61 49 | 94.45 81 | 77.81 72 | 87.84 99 | 93.84 34 |
|
UniMVSNet (Re) | | | 81.60 87 | 81.11 84 | 83.09 125 | 88.38 132 | 64.41 179 | 87.60 117 | 93.02 24 | 78.42 31 | 78.56 99 | 88.16 137 | 69.78 47 | 93.26 136 | 69.58 150 | 76.49 225 | 91.60 98 |
|
VPNet | | | 78.69 152 | 78.66 131 | 78.76 228 | 88.31 134 | 55.72 281 | 84.45 213 | 86.63 208 | 76.79 51 | 78.26 113 | 90.55 87 | 59.30 163 | 89.70 229 | 66.63 171 | 77.05 211 | 90.88 116 |
|
TR-MVS | | | 77.44 186 | 76.18 181 | 81.20 186 | 88.24 135 | 63.24 201 | 84.61 208 | 86.40 211 | 67.55 203 | 77.81 122 | 86.48 192 | 54.10 200 | 93.15 142 | 57.75 242 | 82.72 158 | 87.20 238 |
|
EI-MVSNet-Vis-set | | | 84.19 53 | 83.81 53 | 85.31 59 | 88.18 136 | 67.85 108 | 87.66 116 | 89.73 139 | 80.05 17 | 82.95 56 | 89.59 103 | 70.74 40 | 94.82 72 | 80.66 53 | 84.72 132 | 93.28 53 |
|
test_0402 | | | 72.79 238 | 70.44 241 | 79.84 208 | 88.13 137 | 65.99 135 | 85.93 177 | 84.29 230 | 65.57 222 | 67.40 262 | 85.49 213 | 46.92 259 | 92.61 161 | 35.88 315 | 74.38 250 | 80.94 298 |
|
VPA-MVSNet | | | 80.60 108 | 80.55 91 | 80.76 194 | 88.07 138 | 60.80 226 | 86.86 150 | 91.58 81 | 75.67 73 | 80.24 84 | 89.45 110 | 63.34 95 | 90.25 222 | 70.51 143 | 79.22 194 | 91.23 108 |
|
UGNet | | | 80.83 99 | 79.59 107 | 84.54 78 | 88.04 139 | 68.09 104 | 89.42 63 | 88.16 185 | 76.95 48 | 76.22 150 | 89.46 108 | 49.30 248 | 93.94 100 | 68.48 157 | 90.31 70 | 91.60 98 |
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 |
WR-MVS_H | | | 78.51 154 | 78.49 136 | 78.56 231 | 88.02 140 | 56.38 270 | 88.43 92 | 92.67 39 | 77.14 43 | 73.89 188 | 87.55 153 | 66.25 72 | 89.24 236 | 58.92 230 | 73.55 258 | 90.06 156 |
|
QAPM | | | 80.88 95 | 79.50 112 | 85.03 67 | 88.01 141 | 68.97 83 | 91.59 24 | 92.00 62 | 66.63 211 | 75.15 177 | 92.16 52 | 57.70 172 | 95.45 45 | 63.52 191 | 88.76 87 | 90.66 126 |
|
3Dnovator | | 76.31 5 | 83.38 64 | 82.31 70 | 86.59 43 | 87.94 142 | 72.94 22 | 90.64 37 | 92.14 56 | 77.21 42 | 75.47 164 | 92.83 47 | 58.56 167 | 94.72 75 | 73.24 119 | 92.71 51 | 92.13 88 |
|
EI-MVSNet-UG-set | | | 83.81 55 | 83.38 56 | 85.09 66 | 87.87 143 | 67.53 112 | 87.44 127 | 89.66 140 | 79.74 18 | 82.23 65 | 89.41 112 | 70.24 43 | 94.74 74 | 79.95 57 | 83.92 138 | 92.99 66 |
|
TranMVSNet+NR-MVSNet | | | 80.84 97 | 80.31 94 | 82.42 156 | 87.85 144 | 62.33 214 | 87.74 115 | 91.33 89 | 80.55 12 | 77.99 120 | 89.86 98 | 65.23 81 | 92.62 160 | 67.05 169 | 75.24 244 | 92.30 81 |
|
CP-MVSNet | | | 78.22 158 | 78.34 142 | 77.84 240 | 87.83 145 | 54.54 285 | 87.94 111 | 91.17 94 | 77.65 33 | 73.48 190 | 88.49 129 | 62.24 130 | 88.43 249 | 62.19 202 | 74.07 251 | 90.55 135 |
|
DU-MVS | | | 81.12 93 | 80.52 92 | 82.90 138 | 87.80 146 | 63.46 195 | 87.02 145 | 91.87 70 | 79.01 26 | 78.38 106 | 89.07 115 | 65.02 83 | 93.05 148 | 70.05 145 | 76.46 226 | 92.20 85 |
|
NR-MVSNet | | | 80.23 120 | 79.38 115 | 82.78 149 | 87.80 146 | 63.34 198 | 86.31 168 | 91.09 96 | 79.01 26 | 72.17 205 | 89.07 115 | 67.20 66 | 92.81 158 | 66.08 176 | 75.65 235 | 92.20 85 |
|
TAMVS | | | 78.89 150 | 77.51 158 | 83.03 129 | 87.80 146 | 67.79 110 | 84.72 204 | 85.05 225 | 67.63 201 | 76.75 140 | 87.70 148 | 62.25 129 | 90.82 215 | 58.53 235 | 87.13 109 | 90.49 137 |
|
thres200 | | | 75.55 213 | 74.47 209 | 78.82 227 | 87.78 149 | 57.85 250 | 83.07 232 | 83.51 238 | 72.44 135 | 75.84 157 | 84.42 229 | 52.08 217 | 91.75 183 | 47.41 287 | 83.64 143 | 86.86 246 |
|
PS-CasMVS | | | 78.01 166 | 78.09 146 | 77.77 242 | 87.71 150 | 54.39 287 | 88.02 107 | 91.22 91 | 77.50 40 | 73.26 192 | 88.64 124 | 60.73 151 | 88.41 250 | 61.88 206 | 73.88 255 | 90.53 136 |
|
PCF-MVS | | 73.52 7 | 80.38 116 | 78.84 129 | 85.01 68 | 87.71 150 | 68.99 82 | 83.65 226 | 91.46 87 | 63.00 243 | 77.77 124 | 90.28 89 | 66.10 73 | 95.09 62 | 61.40 211 | 88.22 98 | 90.94 115 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
GBi-Net | | | 78.40 155 | 77.40 159 | 81.40 183 | 87.60 152 | 63.01 206 | 88.39 96 | 89.28 150 | 71.63 145 | 75.34 170 | 87.28 159 | 54.80 191 | 91.11 206 | 62.72 196 | 79.57 188 | 90.09 152 |
|
test1 | | | 78.40 155 | 77.40 159 | 81.40 183 | 87.60 152 | 63.01 206 | 88.39 96 | 89.28 150 | 71.63 145 | 75.34 170 | 87.28 159 | 54.80 191 | 91.11 206 | 62.72 196 | 79.57 188 | 90.09 152 |
|
FMVSNet2 | | | 78.20 160 | 77.21 162 | 81.20 186 | 87.60 152 | 62.89 210 | 87.47 126 | 89.02 159 | 71.63 145 | 75.29 174 | 87.28 159 | 54.80 191 | 91.10 209 | 62.38 200 | 79.38 191 | 89.61 175 |
|
CDS-MVSNet | | | 79.07 146 | 77.70 155 | 83.17 121 | 87.60 152 | 68.23 102 | 84.40 216 | 86.20 214 | 67.49 204 | 76.36 148 | 86.54 189 | 61.54 137 | 90.79 216 | 61.86 207 | 87.33 107 | 90.49 137 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
HY-MVS | | 69.67 12 | 77.95 168 | 77.15 163 | 80.36 198 | 87.57 156 | 60.21 230 | 83.37 231 | 87.78 195 | 66.11 215 | 75.37 169 | 87.06 169 | 63.27 97 | 90.48 220 | 61.38 212 | 82.43 161 | 90.40 142 |
|
xiu_mvs_v1_base_debu | | | 80.80 102 | 79.72 104 | 84.03 96 | 87.35 157 | 70.19 61 | 85.56 187 | 88.77 175 | 69.06 184 | 81.83 67 | 88.16 137 | 50.91 234 | 92.85 154 | 78.29 69 | 87.56 103 | 89.06 181 |
|
xiu_mvs_v1_base | | | 80.80 102 | 79.72 104 | 84.03 96 | 87.35 157 | 70.19 61 | 85.56 187 | 88.77 175 | 69.06 184 | 81.83 67 | 88.16 137 | 50.91 234 | 92.85 154 | 78.29 69 | 87.56 103 | 89.06 181 |
|
xiu_mvs_v1_base_debi | | | 80.80 102 | 79.72 104 | 84.03 96 | 87.35 157 | 70.19 61 | 85.56 187 | 88.77 175 | 69.06 184 | 81.83 67 | 88.16 137 | 50.91 234 | 92.85 154 | 78.29 69 | 87.56 103 | 89.06 181 |
|
MVSFormer | | | 82.85 70 | 82.05 73 | 85.24 62 | 87.35 157 | 70.21 59 | 90.50 40 | 90.38 112 | 68.55 194 | 81.32 73 | 89.47 106 | 61.68 134 | 93.46 128 | 78.98 61 | 90.26 71 | 92.05 90 |
|
lupinMVS | | | 81.39 91 | 80.27 96 | 84.76 75 | 87.35 157 | 70.21 59 | 85.55 190 | 86.41 210 | 62.85 246 | 81.32 73 | 88.61 125 | 61.68 134 | 92.24 173 | 78.41 67 | 90.26 71 | 91.83 94 |
|
PAPM | | | 77.68 175 | 76.40 174 | 81.51 180 | 87.29 162 | 61.85 220 | 83.78 225 | 89.59 141 | 64.74 228 | 71.23 216 | 88.70 121 | 62.59 121 | 93.66 122 | 52.66 266 | 87.03 111 | 89.01 188 |
|
LCM-MVSNet-Re | | | 77.05 190 | 76.94 166 | 77.36 247 | 87.20 163 | 51.60 297 | 80.06 254 | 80.46 273 | 75.20 82 | 67.69 258 | 86.72 174 | 62.48 125 | 88.98 241 | 63.44 192 | 89.25 82 | 91.51 101 |
|
COLMAP_ROB | | 66.92 17 | 73.01 235 | 70.41 242 | 80.81 193 | 87.13 164 | 65.63 141 | 88.30 100 | 84.19 232 | 62.96 244 | 63.80 286 | 87.69 149 | 38.04 301 | 92.56 163 | 46.66 293 | 74.91 245 | 84.24 276 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
PEN-MVS | | | 77.73 173 | 77.69 156 | 77.84 240 | 87.07 165 | 53.91 289 | 87.91 113 | 91.18 93 | 77.56 37 | 73.14 194 | 88.82 120 | 61.23 144 | 89.17 237 | 59.95 221 | 72.37 264 | 90.43 140 |
|
pcd1.5k->3k | | | 34.07 310 | 35.26 310 | 30.50 325 | 86.92 166 | 0.00 345 | 0.00 336 | 91.58 81 | 0.00 340 | 0.00 341 | 0.00 342 | 56.23 184 | 0.00 343 | 0.00 340 | 82.60 159 | 91.49 103 |
|
MVS_Test | | | 83.15 65 | 83.06 60 | 83.41 114 | 86.86 167 | 63.21 202 | 86.11 173 | 92.00 62 | 74.31 92 | 82.87 58 | 89.44 111 | 70.03 44 | 93.21 137 | 77.39 77 | 88.50 95 | 93.81 35 |
|
FMVSNet3 | | | 77.88 171 | 76.85 167 | 80.97 191 | 86.84 168 | 62.36 213 | 86.52 162 | 88.77 175 | 71.13 151 | 75.34 170 | 86.66 181 | 54.07 201 | 91.10 209 | 62.72 196 | 79.57 188 | 89.45 177 |
|
FMVSNet1 | | | 77.44 186 | 76.12 182 | 81.40 183 | 86.81 169 | 63.01 206 | 88.39 96 | 89.28 150 | 70.49 162 | 74.39 186 | 87.28 159 | 49.06 251 | 91.11 206 | 60.91 215 | 78.52 196 | 90.09 152 |
|
nrg030 | | | 83.88 54 | 83.53 54 | 84.96 69 | 86.77 170 | 69.28 78 | 90.46 42 | 92.67 39 | 74.79 87 | 82.95 56 | 91.33 72 | 72.70 26 | 93.09 146 | 80.79 52 | 79.28 193 | 92.50 75 |
|
jason | | | 81.39 91 | 80.29 95 | 84.70 76 | 86.63 171 | 69.90 66 | 85.95 176 | 86.77 206 | 63.24 240 | 81.07 79 | 89.47 106 | 61.08 148 | 92.15 174 | 78.33 68 | 90.07 75 | 92.05 90 |
jason: jason. |
PS-MVSNAJss | | | 82.07 78 | 81.31 80 | 84.34 86 | 86.51 172 | 67.27 118 | 89.27 66 | 91.51 84 | 71.75 143 | 79.37 89 | 90.22 92 | 63.15 101 | 94.27 85 | 77.69 73 | 82.36 162 | 91.49 103 |
|
WTY-MVS | | | 75.65 212 | 75.68 191 | 75.57 261 | 86.40 173 | 56.82 261 | 77.92 274 | 82.40 250 | 65.10 225 | 76.18 152 | 87.72 147 | 63.13 104 | 80.90 289 | 60.31 219 | 81.96 164 | 89.00 190 |
|
DTE-MVSNet | | | 76.99 191 | 76.80 168 | 77.54 246 | 86.24 174 | 53.06 293 | 87.52 124 | 90.66 104 | 77.08 46 | 72.50 200 | 88.67 123 | 60.48 157 | 89.52 231 | 57.33 246 | 70.74 275 | 90.05 157 |
|
PVSNet | | 64.34 18 | 72.08 242 | 70.87 240 | 75.69 259 | 86.21 175 | 56.44 268 | 74.37 292 | 80.73 270 | 62.06 255 | 70.17 227 | 82.23 250 | 42.86 281 | 83.31 282 | 54.77 257 | 84.45 135 | 87.32 235 |
|
IterMVS-LS | | | 80.06 125 | 79.38 115 | 82.11 161 | 85.89 176 | 63.20 203 | 86.79 153 | 89.34 148 | 74.19 93 | 75.45 166 | 86.72 174 | 66.62 69 | 92.39 167 | 72.58 126 | 76.86 217 | 90.75 120 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
Baseline_NR-MVSNet | | | 78.15 162 | 78.33 143 | 77.61 244 | 85.79 177 | 56.21 273 | 86.78 154 | 85.76 219 | 73.60 107 | 77.93 121 | 87.57 152 | 65.02 83 | 88.99 240 | 67.14 168 | 75.33 241 | 87.63 227 |
|
cascas | | | 76.72 195 | 74.64 205 | 82.99 131 | 85.78 178 | 65.88 138 | 82.33 236 | 89.21 155 | 60.85 262 | 72.74 197 | 81.02 269 | 47.28 257 | 93.75 116 | 67.48 163 | 85.02 127 | 89.34 178 |
|
MVS | | | 78.19 161 | 76.99 165 | 81.78 167 | 85.66 179 | 66.99 121 | 84.66 205 | 90.47 110 | 55.08 298 | 72.02 209 | 85.27 217 | 63.83 92 | 94.11 95 | 66.10 175 | 89.80 77 | 84.24 276 |
|
XVG-OURS | | | 80.41 112 | 79.23 123 | 83.97 100 | 85.64 180 | 69.02 80 | 83.03 233 | 90.39 111 | 71.09 153 | 77.63 126 | 91.49 69 | 54.62 197 | 91.35 200 | 75.71 94 | 83.47 144 | 91.54 100 |
|
CANet_DTU | | | 80.61 107 | 79.87 100 | 82.83 144 | 85.60 181 | 63.17 205 | 87.36 128 | 88.65 179 | 76.37 63 | 75.88 156 | 88.44 131 | 53.51 205 | 93.07 147 | 73.30 118 | 89.74 78 | 92.25 83 |
|
XVG-OURS-SEG-HR | | | 80.81 100 | 79.76 103 | 83.96 101 | 85.60 181 | 68.78 86 | 83.54 229 | 90.50 109 | 70.66 160 | 76.71 141 | 91.66 61 | 60.69 153 | 91.26 202 | 76.94 82 | 81.58 168 | 91.83 94 |
|
TransMVSNet (Re) | | | 75.39 216 | 74.56 207 | 77.86 239 | 85.50 183 | 57.10 259 | 86.78 154 | 86.09 217 | 72.17 140 | 71.53 214 | 87.34 158 | 63.01 105 | 89.31 235 | 56.84 249 | 61.83 305 | 87.17 239 |
|
MVP-Stereo | | | 76.12 206 | 74.46 210 | 81.13 189 | 85.37 184 | 69.79 67 | 84.42 215 | 87.95 192 | 65.03 226 | 67.46 260 | 85.33 216 | 53.28 207 | 91.73 184 | 58.01 240 | 83.27 150 | 81.85 295 |
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
OpenMVS | | 72.83 10 | 79.77 131 | 78.33 143 | 84.09 92 | 85.17 185 | 69.91 65 | 90.57 38 | 90.97 97 | 66.70 207 | 72.17 205 | 91.91 57 | 54.70 195 | 93.96 98 | 61.81 208 | 90.95 65 | 88.41 214 |
|
AllTest | | | 70.96 248 | 68.09 258 | 79.58 214 | 85.15 186 | 63.62 190 | 84.58 209 | 79.83 279 | 62.31 252 | 60.32 295 | 86.73 172 | 32.02 312 | 88.96 243 | 50.28 273 | 71.57 271 | 86.15 256 |
|
TestCases | | | | | 79.58 214 | 85.15 186 | 63.62 190 | | 79.83 279 | 62.31 252 | 60.32 295 | 86.73 172 | 32.02 312 | 88.96 243 | 50.28 273 | 71.57 271 | 86.15 256 |
|
Effi-MVS+-dtu | | | 80.03 126 | 78.57 135 | 84.42 82 | 85.13 188 | 68.74 89 | 88.77 82 | 88.10 188 | 74.99 84 | 74.97 181 | 83.49 239 | 57.27 176 | 93.36 133 | 73.53 115 | 80.88 173 | 91.18 109 |
|
mvs-test1 | | | 80.88 95 | 79.40 114 | 85.29 60 | 85.13 188 | 69.75 69 | 89.28 65 | 88.10 188 | 74.99 84 | 76.44 147 | 86.72 174 | 57.27 176 | 94.26 88 | 73.53 115 | 83.18 152 | 91.87 93 |
|
SixPastTwentyTwo | | | 73.37 229 | 71.26 236 | 79.70 210 | 85.08 190 | 57.89 249 | 85.57 186 | 83.56 237 | 71.03 154 | 65.66 274 | 85.88 203 | 42.10 286 | 92.57 162 | 59.11 229 | 63.34 302 | 88.65 199 |
|
EG-PatchMatch MVS | | | 74.04 222 | 71.82 230 | 80.71 195 | 84.92 191 | 67.42 114 | 85.86 179 | 88.08 190 | 66.04 217 | 64.22 283 | 83.85 233 | 35.10 310 | 92.56 163 | 57.44 244 | 80.83 174 | 82.16 294 |
|
IB-MVS | | 68.01 15 | 75.85 210 | 73.36 218 | 83.31 116 | 84.76 192 | 66.03 133 | 83.38 230 | 85.06 224 | 70.21 166 | 69.40 239 | 81.05 268 | 45.76 267 | 94.66 76 | 65.10 183 | 75.49 238 | 89.25 180 |
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 |
mvs_tets | | | 79.13 145 | 77.77 154 | 83.22 120 | 84.70 193 | 66.37 130 | 89.17 68 | 90.19 124 | 69.38 177 | 75.40 168 | 89.46 108 | 44.17 274 | 93.15 142 | 76.78 85 | 80.70 177 | 90.14 148 |
|
jajsoiax | | | 79.29 142 | 77.96 148 | 83.27 118 | 84.68 194 | 66.57 128 | 89.25 67 | 90.16 125 | 69.20 181 | 75.46 165 | 89.49 105 | 45.75 268 | 93.13 144 | 76.84 84 | 80.80 175 | 90.11 150 |
|
MIMVSNet | | | 70.69 250 | 69.30 246 | 74.88 266 | 84.52 195 | 56.35 271 | 75.87 284 | 79.42 282 | 64.59 229 | 67.76 256 | 82.41 247 | 41.10 290 | 81.54 288 | 46.64 295 | 81.34 169 | 86.75 249 |
|
MSDG | | | 73.36 231 | 70.99 238 | 80.49 196 | 84.51 196 | 65.80 139 | 80.71 249 | 86.13 216 | 65.70 220 | 65.46 275 | 83.74 236 | 44.60 271 | 90.91 214 | 51.13 270 | 76.89 216 | 84.74 272 |
|
mvs_anonymous | | | 79.42 140 | 79.11 125 | 80.34 199 | 84.45 197 | 57.97 247 | 82.59 234 | 87.62 197 | 67.40 206 | 76.17 154 | 88.56 128 | 68.47 56 | 89.59 230 | 70.65 142 | 86.05 122 | 93.47 48 |
|
EI-MVSNet | | | 80.52 111 | 79.98 98 | 82.12 160 | 84.28 198 | 63.19 204 | 86.41 165 | 88.95 168 | 74.18 94 | 78.69 96 | 87.54 154 | 66.62 69 | 92.43 165 | 72.57 127 | 80.57 179 | 90.74 121 |
|
CVMVSNet | | | 72.99 236 | 72.58 223 | 74.25 272 | 84.28 198 | 50.85 303 | 86.41 165 | 83.45 240 | 44.56 319 | 73.23 193 | 87.54 154 | 49.38 246 | 85.70 269 | 65.90 177 | 78.44 198 | 86.19 255 |
|
v13 | | | 77.50 184 | 76.07 187 | 81.77 168 | 84.23 200 | 65.07 157 | 87.34 129 | 88.91 173 | 72.92 123 | 68.35 254 | 81.97 257 | 62.53 124 | 91.69 190 | 72.20 133 | 66.22 296 | 88.56 209 |
|
pm-mvs1 | | | 77.25 189 | 76.68 170 | 78.93 225 | 84.22 201 | 58.62 239 | 86.41 165 | 88.36 184 | 71.37 150 | 73.31 191 | 88.01 141 | 61.22 145 | 89.15 238 | 64.24 189 | 73.01 260 | 89.03 187 |
|
v12 | | | 77.51 182 | 76.09 186 | 81.76 170 | 84.22 201 | 64.99 158 | 87.30 132 | 88.93 172 | 72.92 123 | 68.48 253 | 81.97 257 | 62.54 123 | 91.70 189 | 72.24 132 | 66.21 297 | 88.58 207 |
|
v11 | | | 77.45 185 | 76.06 188 | 81.59 179 | 84.22 201 | 64.52 169 | 87.11 142 | 89.02 159 | 72.76 128 | 68.76 247 | 81.90 262 | 62.09 132 | 91.71 188 | 71.98 134 | 66.73 289 | 88.56 209 |
|
EPNet | | | 83.72 57 | 82.92 63 | 86.14 51 | 84.22 201 | 69.48 74 | 91.05 32 | 85.27 222 | 81.30 8 | 76.83 139 | 91.65 62 | 66.09 74 | 95.56 41 | 76.00 89 | 93.85 44 | 93.38 49 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
V9 | | | 77.52 180 | 76.11 185 | 81.73 171 | 84.19 205 | 64.89 161 | 87.26 134 | 88.94 171 | 72.87 126 | 68.65 249 | 81.96 259 | 62.65 119 | 91.72 186 | 72.27 131 | 66.24 295 | 88.60 204 |
|
v17 | | | 77.68 175 | 76.35 179 | 81.69 173 | 84.15 206 | 64.65 166 | 87.33 130 | 88.99 163 | 72.70 130 | 69.25 244 | 82.07 253 | 62.82 111 | 91.79 180 | 72.69 125 | 67.15 288 | 88.63 200 |
|
v16 | | | 77.69 174 | 76.36 178 | 81.68 174 | 84.15 206 | 64.63 168 | 87.33 130 | 88.99 163 | 72.69 131 | 69.31 243 | 82.08 252 | 62.80 112 | 91.79 180 | 72.70 124 | 67.23 286 | 88.63 200 |
|
V14 | | | 77.52 180 | 76.12 182 | 81.70 172 | 84.15 206 | 64.77 164 | 87.21 136 | 88.95 168 | 72.80 127 | 68.79 246 | 81.94 260 | 62.69 116 | 91.72 186 | 72.31 130 | 66.27 294 | 88.60 204 |
|
v1neww | | | 80.40 113 | 79.54 108 | 82.98 132 | 84.10 209 | 64.51 171 | 87.57 119 | 90.22 121 | 73.25 114 | 78.47 102 | 86.65 182 | 62.83 109 | 93.86 106 | 75.72 92 | 77.02 212 | 90.58 132 |
|
v7new | | | 80.40 113 | 79.54 108 | 82.98 132 | 84.10 209 | 64.51 171 | 87.57 119 | 90.22 121 | 73.25 114 | 78.47 102 | 86.65 182 | 62.83 109 | 93.86 106 | 75.72 92 | 77.02 212 | 90.58 132 |
|
v18 | | | 77.67 177 | 76.35 179 | 81.64 176 | 84.09 211 | 64.47 177 | 87.27 133 | 89.01 161 | 72.59 132 | 69.39 240 | 82.04 254 | 62.85 107 | 91.80 179 | 72.72 123 | 67.20 287 | 88.63 200 |
|
v15 | | | 77.51 182 | 76.12 182 | 81.66 175 | 84.09 211 | 64.65 166 | 87.14 137 | 88.96 167 | 72.76 128 | 68.90 245 | 81.91 261 | 62.74 114 | 91.73 184 | 72.32 129 | 66.29 293 | 88.61 203 |
|
v8 | | | 79.97 128 | 79.02 127 | 82.80 146 | 84.09 211 | 64.50 175 | 87.96 109 | 90.29 120 | 74.13 96 | 75.24 175 | 86.81 171 | 62.88 106 | 93.89 105 | 74.39 106 | 75.40 240 | 90.00 158 |
|
v6 | | | 80.40 113 | 79.54 108 | 82.98 132 | 84.09 211 | 64.50 175 | 87.57 119 | 90.22 121 | 73.25 114 | 78.47 102 | 86.63 184 | 62.84 108 | 93.86 106 | 75.73 91 | 77.02 212 | 90.58 132 |
|
v7 | | | 80.24 119 | 79.26 122 | 83.15 122 | 84.07 215 | 64.94 160 | 87.56 122 | 90.67 102 | 72.26 138 | 78.28 109 | 86.51 191 | 61.45 139 | 94.03 97 | 75.14 102 | 77.41 206 | 90.49 137 |
|
v10 | | | 79.74 132 | 78.67 130 | 82.97 136 | 84.06 216 | 64.95 159 | 87.88 114 | 90.62 105 | 73.11 120 | 75.11 178 | 86.56 188 | 61.46 138 | 94.05 96 | 73.68 111 | 75.55 237 | 89.90 166 |
|
Patchmatch-test1 | | | 73.49 227 | 71.85 229 | 78.41 235 | 84.05 217 | 62.17 217 | 79.96 256 | 79.29 283 | 66.30 214 | 72.38 203 | 79.58 281 | 51.95 220 | 85.08 274 | 55.46 254 | 77.67 204 | 87.99 219 |
|
test_djsdf | | | 80.30 118 | 79.32 117 | 83.27 118 | 83.98 218 | 65.37 149 | 90.50 40 | 90.38 112 | 68.55 194 | 76.19 151 | 88.70 121 | 56.44 183 | 93.46 128 | 78.98 61 | 80.14 186 | 90.97 114 |
|
1314 | | | 76.53 196 | 75.30 197 | 80.21 203 | 83.93 219 | 62.32 215 | 84.66 205 | 88.81 174 | 60.23 266 | 70.16 228 | 84.07 232 | 55.30 190 | 90.73 217 | 67.37 164 | 83.21 151 | 87.59 229 |
|
MS-PatchMatch | | | 73.83 224 | 72.67 222 | 77.30 249 | 83.87 220 | 66.02 134 | 81.82 239 | 84.66 227 | 61.37 260 | 68.61 251 | 82.82 244 | 47.29 256 | 88.21 251 | 59.27 227 | 84.32 136 | 77.68 308 |
|
v1141 | | | 80.19 122 | 79.31 118 | 82.85 141 | 83.84 221 | 64.12 184 | 87.14 137 | 90.08 128 | 73.13 117 | 78.27 110 | 86.39 193 | 62.67 118 | 93.75 116 | 75.40 99 | 76.83 220 | 90.68 123 |
|
divwei89l23v2f112 | | | 80.19 122 | 79.31 118 | 82.85 141 | 83.84 221 | 64.11 186 | 87.13 140 | 90.08 128 | 73.13 117 | 78.27 110 | 86.39 193 | 62.69 116 | 93.75 116 | 75.40 99 | 76.82 221 | 90.68 123 |
|
v1 | | | 80.19 122 | 79.31 118 | 82.85 141 | 83.83 223 | 64.12 184 | 87.14 137 | 90.07 130 | 73.13 117 | 78.27 110 | 86.38 196 | 62.72 115 | 93.75 116 | 75.41 98 | 76.82 221 | 90.68 123 |
|
v1144 | | | 80.03 126 | 79.03 126 | 83.01 130 | 83.78 224 | 64.51 171 | 87.11 142 | 90.57 107 | 71.96 142 | 78.08 119 | 86.20 199 | 61.41 140 | 93.94 100 | 74.93 103 | 77.23 208 | 90.60 129 |
|
OurMVSNet-221017-0 | | | 74.26 221 | 72.42 225 | 79.80 209 | 83.76 225 | 59.59 232 | 85.92 178 | 86.64 207 | 66.39 213 | 66.96 265 | 87.58 151 | 39.46 295 | 91.60 196 | 65.76 179 | 69.27 279 | 88.22 215 |
|
v2v482 | | | 80.23 120 | 79.29 121 | 83.05 128 | 83.62 226 | 64.14 182 | 87.04 144 | 89.97 132 | 73.61 106 | 78.18 116 | 87.22 163 | 61.10 147 | 93.82 109 | 76.11 87 | 76.78 223 | 91.18 109 |
|
XXY-MVS | | | 75.41 215 | 75.56 192 | 74.96 265 | 83.59 227 | 57.82 251 | 80.59 251 | 83.87 234 | 66.54 212 | 74.93 182 | 88.31 134 | 63.24 98 | 80.09 293 | 62.16 203 | 76.85 218 | 86.97 244 |
|
v1192 | | | 79.59 134 | 78.43 140 | 83.07 127 | 83.55 228 | 64.52 169 | 86.93 148 | 90.58 106 | 70.83 155 | 77.78 123 | 85.90 202 | 59.15 164 | 93.94 100 | 73.96 110 | 77.19 210 | 90.76 119 |
|
tpmp4_e23 | | | 73.45 228 | 71.17 237 | 80.31 201 | 83.55 228 | 59.56 234 | 81.88 238 | 82.33 251 | 57.94 283 | 70.51 222 | 81.62 263 | 51.19 232 | 91.63 195 | 53.96 260 | 77.51 205 | 89.75 173 |
|
v7n | | | 78.97 149 | 77.58 157 | 83.14 123 | 83.45 230 | 65.51 144 | 88.32 99 | 91.21 92 | 73.69 105 | 72.41 202 | 86.32 197 | 57.93 171 | 93.81 110 | 69.18 153 | 75.65 235 | 90.11 150 |
|
v144192 | | | 79.47 138 | 78.37 141 | 82.78 149 | 83.35 231 | 63.96 188 | 86.96 146 | 90.36 115 | 69.99 167 | 77.50 127 | 85.67 208 | 60.66 154 | 93.77 114 | 74.27 107 | 76.58 224 | 90.62 127 |
|
tpm2 | | | 73.26 232 | 71.46 232 | 78.63 229 | 83.34 232 | 56.71 264 | 80.65 250 | 80.40 274 | 56.63 292 | 73.55 189 | 82.02 255 | 51.80 226 | 91.24 203 | 56.35 251 | 78.42 199 | 87.95 220 |
|
diffmvs | | | 79.51 135 | 78.59 133 | 82.25 159 | 83.31 233 | 62.66 211 | 84.17 219 | 88.11 186 | 67.64 200 | 76.09 155 | 87.47 156 | 64.01 90 | 91.15 205 | 71.71 137 | 84.82 131 | 92.94 67 |
|
v1921920 | | | 79.22 143 | 78.03 147 | 82.80 146 | 83.30 234 | 63.94 189 | 86.80 152 | 90.33 117 | 69.91 168 | 77.48 128 | 85.53 212 | 58.44 168 | 93.75 116 | 73.60 114 | 76.85 218 | 90.71 122 |
|
v1240 | | | 78.99 148 | 77.78 153 | 82.64 153 | 83.21 235 | 63.54 192 | 86.62 159 | 90.30 119 | 69.74 173 | 77.33 130 | 85.68 207 | 57.04 181 | 93.76 115 | 73.13 120 | 76.92 215 | 90.62 127 |
|
XVG-ACMP-BASELINE | | | 76.11 207 | 74.27 212 | 81.62 177 | 83.20 236 | 64.67 165 | 83.60 228 | 89.75 138 | 69.75 171 | 71.85 210 | 87.09 167 | 32.78 311 | 92.11 175 | 69.99 147 | 80.43 182 | 88.09 218 |
|
MDTV_nov1_ep13 | | | | 69.97 245 | | 83.18 237 | 53.48 291 | 77.10 278 | 80.18 278 | 60.45 263 | 69.33 242 | 80.44 273 | 48.89 252 | 86.90 260 | 51.60 268 | 78.51 197 | |
|
PatchmatchNet | | | 73.12 234 | 71.33 234 | 78.49 234 | 83.18 237 | 60.85 225 | 79.63 258 | 78.57 285 | 64.13 234 | 71.73 211 | 79.81 280 | 51.20 231 | 85.97 268 | 57.40 245 | 76.36 228 | 88.66 198 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
Fast-Effi-MVS+-dtu | | | 78.02 165 | 76.49 172 | 82.62 154 | 83.16 239 | 66.96 124 | 86.94 147 | 87.45 201 | 72.45 133 | 71.49 215 | 84.17 230 | 54.79 194 | 91.58 197 | 67.61 161 | 80.31 183 | 89.30 179 |
|
gg-mvs-nofinetune | | | 69.95 257 | 67.96 259 | 75.94 257 | 83.07 240 | 54.51 286 | 77.23 277 | 70.29 318 | 63.11 241 | 70.32 224 | 62.33 320 | 43.62 276 | 88.69 247 | 53.88 261 | 87.76 100 | 84.62 274 |
|
MVSTER | | | 79.01 147 | 77.88 150 | 82.38 157 | 83.07 240 | 64.80 163 | 84.08 223 | 88.95 168 | 69.01 188 | 78.69 96 | 87.17 166 | 54.70 195 | 92.43 165 | 74.69 104 | 80.57 179 | 89.89 167 |
|
K. test v3 | | | 71.19 246 | 68.51 252 | 79.21 218 | 83.04 242 | 57.78 252 | 84.35 217 | 76.91 294 | 72.90 125 | 62.99 289 | 82.86 243 | 39.27 296 | 91.09 211 | 61.65 209 | 52.66 320 | 88.75 196 |
|
FMVSNet5 | | | 69.50 259 | 67.96 259 | 74.15 273 | 82.97 243 | 55.35 282 | 80.01 255 | 82.12 255 | 62.56 250 | 63.02 287 | 81.53 264 | 36.92 305 | 81.92 286 | 48.42 281 | 74.06 252 | 85.17 268 |
|
PatchFormer-LS_test | | | 74.50 219 | 73.05 220 | 78.86 226 | 82.95 244 | 59.55 235 | 81.65 243 | 82.30 252 | 67.44 205 | 71.62 213 | 78.15 288 | 52.34 212 | 88.92 245 | 65.05 184 | 75.90 232 | 88.12 217 |
|
DWT-MVSNet_test | | | 73.70 225 | 71.86 228 | 79.21 218 | 82.91 245 | 58.94 237 | 82.34 235 | 82.17 253 | 65.21 223 | 71.05 218 | 78.31 286 | 44.21 273 | 90.17 224 | 63.29 194 | 77.28 207 | 88.53 211 |
|
DI_MVS_plusplus_test | | | 79.89 129 | 78.58 134 | 83.85 104 | 82.89 246 | 65.32 150 | 86.12 172 | 89.55 142 | 69.64 174 | 70.55 220 | 85.82 206 | 57.24 178 | 93.81 110 | 76.85 83 | 88.55 92 | 92.41 78 |
|
sss | | | 73.60 226 | 73.64 216 | 73.51 276 | 82.80 247 | 55.01 283 | 76.12 280 | 81.69 262 | 62.47 251 | 74.68 184 | 85.85 205 | 57.32 175 | 78.11 301 | 60.86 216 | 80.93 172 | 87.39 232 |
|
GA-MVS | | | 76.87 193 | 75.17 202 | 81.97 164 | 82.75 248 | 62.58 212 | 81.44 246 | 86.35 213 | 72.16 141 | 74.74 183 | 82.89 242 | 46.20 263 | 92.02 176 | 68.85 155 | 81.09 171 | 91.30 107 |
|
v148 | | | 78.72 151 | 77.80 152 | 81.47 181 | 82.73 249 | 61.96 219 | 86.30 169 | 88.08 190 | 73.26 113 | 76.18 152 | 85.47 214 | 62.46 126 | 92.36 169 | 71.92 136 | 73.82 256 | 90.09 152 |
|
test_normal | | | 79.81 130 | 78.45 137 | 83.89 103 | 82.70 250 | 65.40 146 | 85.82 180 | 89.48 145 | 69.39 175 | 70.12 229 | 85.66 209 | 57.15 180 | 93.71 121 | 77.08 80 | 88.62 90 | 92.56 74 |
|
semantic-postprocess | | | | | 80.11 204 | 82.69 251 | 64.85 162 | | 83.47 239 | 69.16 182 | 70.49 223 | 84.15 231 | 50.83 238 | 88.15 252 | 69.23 152 | 72.14 267 | 87.34 234 |
|
CostFormer | | | 75.24 217 | 73.90 215 | 79.27 216 | 82.65 252 | 58.27 243 | 80.80 247 | 82.73 248 | 61.57 257 | 75.33 173 | 83.13 241 | 55.52 188 | 91.07 212 | 64.98 185 | 78.34 200 | 88.45 212 |
|
EPNet_dtu | | | 75.46 214 | 74.86 203 | 77.23 250 | 82.57 253 | 54.60 284 | 86.89 149 | 83.09 244 | 71.64 144 | 66.25 272 | 85.86 204 | 55.99 185 | 88.04 254 | 54.92 256 | 86.55 116 | 89.05 185 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
RPSCF | | | 73.23 233 | 71.46 232 | 78.54 232 | 82.50 254 | 59.85 231 | 82.18 237 | 82.84 247 | 58.96 275 | 71.15 217 | 89.41 112 | 45.48 270 | 84.77 276 | 58.82 232 | 71.83 269 | 91.02 113 |
|
tpm cat1 | | | 70.57 251 | 68.31 254 | 77.35 248 | 82.41 255 | 57.95 248 | 78.08 273 | 80.22 277 | 52.04 310 | 68.54 252 | 77.66 293 | 52.00 219 | 87.84 256 | 51.77 267 | 72.07 268 | 86.25 254 |
|
v748 | | | 77.97 167 | 76.65 171 | 81.92 166 | 82.29 256 | 63.28 200 | 87.53 123 | 90.35 116 | 73.50 111 | 70.76 219 | 85.55 211 | 58.28 169 | 92.81 158 | 68.81 156 | 72.76 263 | 89.67 174 |
|
tpm | | | 72.37 241 | 71.71 231 | 74.35 271 | 82.19 257 | 52.00 294 | 79.22 263 | 77.29 292 | 64.56 230 | 72.95 196 | 83.68 238 | 51.35 229 | 83.26 283 | 58.33 237 | 75.80 233 | 87.81 224 |
|
tpmvs | | | 71.09 247 | 69.29 247 | 76.49 254 | 82.04 258 | 56.04 274 | 78.92 266 | 81.37 266 | 64.05 235 | 67.18 264 | 78.28 287 | 49.74 245 | 89.77 226 | 49.67 278 | 72.37 264 | 83.67 280 |
|
pmmvs4 | | | 74.03 223 | 71.91 227 | 80.39 197 | 81.96 259 | 68.32 99 | 81.45 245 | 82.14 254 | 59.32 273 | 69.87 235 | 85.13 219 | 52.40 211 | 88.13 253 | 60.21 220 | 74.74 247 | 84.73 273 |
|
TinyColmap | | | 67.30 270 | 64.81 272 | 74.76 268 | 81.92 260 | 56.68 265 | 80.29 253 | 81.49 265 | 60.33 264 | 56.27 310 | 83.22 240 | 24.77 321 | 87.66 258 | 45.52 299 | 69.47 278 | 79.95 302 |
|
ITE_SJBPF | | | | | 78.22 237 | 81.77 261 | 60.57 227 | | 83.30 241 | 69.25 180 | 67.54 259 | 87.20 164 | 36.33 307 | 87.28 259 | 54.34 258 | 74.62 248 | 86.80 247 |
|
MVS-HIRNet | | | 59.14 289 | 57.67 291 | 63.57 305 | 81.65 262 | 43.50 318 | 71.73 296 | 65.06 330 | 39.59 324 | 51.43 318 | 57.73 324 | 38.34 300 | 82.58 285 | 39.53 310 | 73.95 253 | 64.62 323 |
|
GG-mvs-BLEND | | | | | 75.38 263 | 81.59 263 | 55.80 280 | 79.32 261 | 69.63 320 | | 67.19 263 | 73.67 307 | 43.24 277 | 88.90 246 | 50.41 272 | 84.50 133 | 81.45 297 |
|
IterMVS | | | 74.29 220 | 72.94 221 | 78.35 236 | 81.53 264 | 63.49 194 | 81.58 244 | 82.49 249 | 68.06 199 | 69.99 232 | 83.69 237 | 51.66 228 | 85.54 270 | 65.85 178 | 71.64 270 | 86.01 260 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
CHOSEN 280x420 | | | 66.51 274 | 64.71 273 | 71.90 281 | 81.45 265 | 63.52 193 | 57.98 326 | 68.95 325 | 53.57 305 | 62.59 290 | 76.70 296 | 46.22 262 | 75.29 313 | 55.25 255 | 79.68 187 | 76.88 314 |
|
gm-plane-assit | | | | | | 81.40 266 | 53.83 290 | | | 62.72 249 | | 80.94 271 | | 92.39 167 | 63.40 193 | | |
|
pmmvs6 | | | 74.69 218 | 73.39 217 | 78.61 230 | 81.38 267 | 57.48 255 | 86.64 158 | 87.95 192 | 64.99 227 | 70.18 226 | 86.61 185 | 50.43 241 | 89.52 231 | 62.12 204 | 70.18 277 | 88.83 193 |
|
test-LLR | | | 72.94 237 | 72.43 224 | 74.48 269 | 81.35 268 | 58.04 245 | 78.38 269 | 77.46 290 | 66.66 208 | 69.95 233 | 79.00 284 | 48.06 254 | 79.24 295 | 66.13 173 | 84.83 129 | 86.15 256 |
|
test-mter | | | 71.41 245 | 70.39 243 | 74.48 269 | 81.35 268 | 58.04 245 | 78.38 269 | 77.46 290 | 60.32 265 | 69.95 233 | 79.00 284 | 36.08 308 | 79.24 295 | 66.13 173 | 84.83 129 | 86.15 256 |
|
CR-MVSNet | | | 73.37 229 | 71.27 235 | 79.67 212 | 81.32 270 | 65.19 154 | 75.92 282 | 80.30 275 | 59.92 269 | 72.73 198 | 81.19 265 | 52.50 209 | 86.69 261 | 59.84 222 | 77.71 202 | 87.11 242 |
|
RPMNet | | | 71.62 243 | 68.94 250 | 79.67 212 | 81.32 270 | 65.19 154 | 75.92 282 | 78.30 287 | 57.60 286 | 72.73 198 | 76.45 298 | 52.30 213 | 86.69 261 | 48.14 284 | 77.71 202 | 87.11 242 |
|
V42 | | | 79.38 141 | 78.24 145 | 82.83 144 | 81.10 272 | 65.50 145 | 85.55 190 | 89.82 136 | 71.57 148 | 78.21 114 | 86.12 200 | 60.66 154 | 93.18 141 | 75.64 95 | 75.46 239 | 89.81 171 |
|
lessismore_v0 | | | | | 78.97 224 | 81.01 273 | 57.15 258 | | 65.99 328 | | 61.16 292 | 82.82 244 | 39.12 297 | 91.34 201 | 59.67 223 | 46.92 324 | 88.43 213 |
|
Patchmtry | | | 70.74 249 | 69.16 248 | 75.49 262 | 80.72 274 | 54.07 288 | 74.94 291 | 80.30 275 | 58.34 279 | 70.01 230 | 81.19 265 | 52.50 209 | 86.54 263 | 53.37 263 | 71.09 273 | 85.87 262 |
|
PatchT | | | 68.46 265 | 67.85 261 | 70.29 290 | 80.70 275 | 43.93 317 | 72.47 295 | 74.88 302 | 60.15 267 | 70.55 220 | 76.57 297 | 49.94 244 | 81.59 287 | 50.58 271 | 74.83 246 | 85.34 265 |
|
USDC | | | 70.33 254 | 68.37 253 | 76.21 256 | 80.60 276 | 56.23 272 | 79.19 264 | 86.49 209 | 60.89 261 | 61.29 291 | 85.47 214 | 31.78 314 | 89.47 233 | 53.37 263 | 76.21 229 | 82.94 291 |
|
tpmrst | | | 72.39 239 | 72.13 226 | 73.18 278 | 80.54 277 | 49.91 307 | 79.91 257 | 79.08 284 | 63.11 241 | 71.69 212 | 79.95 277 | 55.32 189 | 82.77 284 | 65.66 180 | 73.89 254 | 86.87 245 |
|
anonymousdsp | | | 78.60 153 | 77.15 163 | 82.98 132 | 80.51 278 | 67.08 120 | 87.24 135 | 89.53 143 | 65.66 221 | 75.16 176 | 87.19 165 | 52.52 208 | 92.25 172 | 77.17 79 | 79.34 192 | 89.61 175 |
|
OpenMVS_ROB | | 64.09 19 | 70.56 252 | 68.19 255 | 77.65 243 | 80.26 279 | 59.41 236 | 85.01 200 | 82.96 246 | 58.76 277 | 65.43 276 | 82.33 248 | 37.63 304 | 91.23 204 | 45.34 301 | 76.03 230 | 82.32 292 |
|
Test4 | | | 77.83 172 | 75.90 189 | 83.62 106 | 80.24 280 | 65.25 152 | 85.27 196 | 90.67 102 | 69.03 187 | 66.48 270 | 83.75 235 | 43.07 279 | 93.00 151 | 75.93 90 | 88.66 89 | 92.62 73 |
|
Anonymous20231206 | | | 68.60 262 | 67.80 263 | 71.02 288 | 80.23 281 | 50.75 304 | 78.30 272 | 80.47 272 | 56.79 291 | 66.11 273 | 82.63 246 | 46.35 261 | 78.95 297 | 43.62 304 | 75.70 234 | 83.36 283 |
|
MIMVSNet1 | | | 68.58 263 | 66.78 268 | 73.98 274 | 80.07 282 | 51.82 295 | 80.77 248 | 84.37 229 | 64.40 232 | 59.75 298 | 82.16 251 | 36.47 306 | 83.63 280 | 42.73 305 | 70.33 276 | 86.48 253 |
|
ADS-MVSNet2 | | | 66.20 277 | 63.33 277 | 74.82 267 | 79.92 283 | 58.75 238 | 67.55 314 | 75.19 300 | 53.37 306 | 65.25 277 | 75.86 299 | 42.32 284 | 80.53 291 | 41.57 307 | 68.91 281 | 85.18 266 |
|
ADS-MVSNet | | | 64.36 282 | 62.88 281 | 68.78 297 | 79.92 283 | 47.17 312 | 67.55 314 | 71.18 316 | 53.37 306 | 65.25 277 | 75.86 299 | 42.32 284 | 73.99 318 | 41.57 307 | 68.91 281 | 85.18 266 |
|
dp | | | 66.80 271 | 65.43 271 | 70.90 289 | 79.74 285 | 48.82 310 | 75.12 289 | 74.77 304 | 59.61 271 | 64.08 284 | 77.23 294 | 42.89 280 | 80.72 290 | 48.86 280 | 66.58 291 | 83.16 285 |
|
EPMVS | | | 69.02 261 | 68.16 256 | 71.59 282 | 79.61 286 | 49.80 309 | 77.40 276 | 66.93 327 | 62.82 247 | 70.01 230 | 79.05 282 | 45.79 266 | 77.86 303 | 56.58 250 | 75.26 243 | 87.13 241 |
|
PVSNet_0 | | 57.27 20 | 61.67 286 | 59.27 287 | 68.85 296 | 79.61 286 | 57.44 256 | 68.01 312 | 73.44 312 | 55.93 295 | 58.54 300 | 70.41 313 | 44.58 272 | 77.55 304 | 47.01 288 | 35.91 326 | 71.55 318 |
|
Patchmatch-test | | | 64.82 280 | 63.24 278 | 69.57 292 | 79.42 288 | 49.82 308 | 63.49 321 | 69.05 324 | 51.98 311 | 59.95 297 | 80.13 276 | 50.91 234 | 70.98 324 | 40.66 309 | 73.57 257 | 87.90 222 |
|
V4 | | | 77.95 168 | 76.37 175 | 82.67 151 | 79.40 289 | 65.52 142 | 86.43 163 | 89.94 133 | 72.28 136 | 72.14 208 | 84.95 223 | 55.72 186 | 93.44 130 | 73.64 112 | 72.86 261 | 89.05 185 |
|
v52 | | | 77.94 170 | 76.37 175 | 82.67 151 | 79.39 290 | 65.52 142 | 86.43 163 | 89.94 133 | 72.28 136 | 72.15 207 | 84.94 224 | 55.70 187 | 93.44 130 | 73.64 112 | 72.84 262 | 89.06 181 |
|
MDA-MVSNet-bldmvs | | | 66.68 272 | 63.66 276 | 75.75 258 | 79.28 291 | 60.56 228 | 73.92 293 | 78.35 286 | 64.43 231 | 50.13 320 | 79.87 279 | 44.02 275 | 83.67 279 | 46.10 297 | 56.86 314 | 83.03 288 |
|
TESTMET0.1,1 | | | 69.89 258 | 69.00 249 | 72.55 279 | 79.27 292 | 56.85 260 | 78.38 269 | 74.71 306 | 57.64 285 | 68.09 255 | 77.19 295 | 37.75 302 | 76.70 306 | 63.92 190 | 84.09 137 | 84.10 279 |
|
N_pmnet | | | 52.79 299 | 53.26 297 | 51.40 318 | 78.99 293 | 7.68 342 | 69.52 304 | 3.89 343 | 51.63 313 | 57.01 307 | 74.98 302 | 40.83 291 | 65.96 331 | 37.78 313 | 64.67 300 | 80.56 301 |
|
EU-MVSNet | | | 68.53 264 | 67.61 266 | 71.31 287 | 78.51 294 | 47.01 313 | 84.47 210 | 84.27 231 | 42.27 320 | 66.44 271 | 84.79 226 | 40.44 293 | 83.76 278 | 58.76 233 | 68.54 285 | 83.17 284 |
|
pmmvs5 | | | 71.55 244 | 70.20 244 | 75.61 260 | 77.83 295 | 56.39 269 | 81.74 241 | 80.89 267 | 57.76 284 | 67.46 260 | 84.49 228 | 49.26 249 | 85.32 273 | 57.08 248 | 75.29 242 | 85.11 269 |
|
test0.0.03 1 | | | 68.00 266 | 67.69 265 | 68.90 295 | 77.55 296 | 47.43 311 | 75.70 285 | 72.95 313 | 66.66 208 | 66.56 268 | 82.29 249 | 48.06 254 | 75.87 310 | 44.97 302 | 74.51 249 | 83.41 282 |
|
Patchmatch-RL test | | | 70.24 255 | 67.78 264 | 77.61 244 | 77.43 297 | 59.57 233 | 71.16 297 | 70.33 317 | 62.94 245 | 68.65 249 | 72.77 308 | 50.62 239 | 85.49 271 | 69.58 150 | 66.58 291 | 87.77 225 |
|
pmmvs-eth3d | | | 70.50 253 | 67.83 262 | 78.52 233 | 77.37 298 | 66.18 132 | 81.82 239 | 81.51 264 | 58.90 276 | 63.90 285 | 80.42 274 | 42.69 282 | 86.28 266 | 58.56 234 | 65.30 299 | 83.11 286 |
|
testing_2 | | | 75.73 211 | 73.34 219 | 82.89 140 | 77.37 298 | 65.22 153 | 84.10 222 | 90.54 108 | 69.09 183 | 60.46 294 | 81.15 267 | 40.48 292 | 92.84 157 | 76.36 86 | 80.54 181 | 90.60 129 |
|
Anonymous20231211 | | | 64.82 280 | 61.79 284 | 73.91 275 | 77.11 300 | 50.92 302 | 85.29 195 | 81.53 263 | 54.19 300 | 57.98 302 | 78.03 289 | 26.90 317 | 87.83 257 | 37.92 312 | 57.12 313 | 82.99 289 |
|
JIA-IIPM | | | 66.32 276 | 62.82 282 | 76.82 252 | 77.09 301 | 61.72 221 | 65.34 318 | 75.38 298 | 58.04 282 | 64.51 281 | 62.32 321 | 42.05 287 | 86.51 264 | 51.45 269 | 69.22 280 | 82.21 293 |
|
Gipuma | | | 45.18 305 | 41.86 306 | 55.16 314 | 77.03 302 | 51.52 298 | 32.50 334 | 80.52 271 | 32.46 328 | 27.12 329 | 35.02 331 | 9.52 338 | 75.50 311 | 22.31 331 | 60.21 311 | 38.45 330 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
MDA-MVSNet_test_wron | | | 65.03 278 | 62.92 279 | 71.37 284 | 75.93 303 | 56.73 262 | 69.09 309 | 74.73 305 | 57.28 289 | 54.03 313 | 77.89 290 | 45.88 264 | 74.39 316 | 49.89 277 | 61.55 306 | 82.99 289 |
|
YYNet1 | | | 65.03 278 | 62.91 280 | 71.38 283 | 75.85 304 | 56.60 266 | 69.12 308 | 74.66 308 | 57.28 289 | 54.12 312 | 77.87 291 | 45.85 265 | 74.48 315 | 49.95 276 | 61.52 307 | 83.05 287 |
|
PMMVS | | | 69.34 260 | 68.67 251 | 71.35 286 | 75.67 305 | 62.03 218 | 75.17 286 | 73.46 311 | 50.00 315 | 68.68 248 | 79.05 282 | 52.07 218 | 78.13 300 | 61.16 214 | 82.77 156 | 73.90 316 |
|
testgi | | | 66.67 273 | 66.53 269 | 67.08 300 | 75.62 306 | 41.69 322 | 75.93 281 | 76.50 295 | 66.11 215 | 65.20 279 | 86.59 186 | 35.72 309 | 74.71 314 | 43.71 303 | 73.38 259 | 84.84 271 |
|
LP | | | 61.36 287 | 57.78 290 | 72.09 280 | 75.54 307 | 58.53 240 | 67.16 316 | 75.22 299 | 51.90 312 | 54.13 311 | 69.97 314 | 37.73 303 | 80.45 292 | 32.74 319 | 55.63 316 | 77.29 310 |
|
test20.03 | | | 67.45 268 | 66.95 267 | 68.94 294 | 75.48 308 | 44.84 315 | 77.50 275 | 77.67 289 | 66.66 208 | 63.01 288 | 83.80 234 | 47.02 258 | 78.40 299 | 42.53 306 | 68.86 283 | 83.58 281 |
|
PM-MVS | | | 66.41 275 | 64.14 275 | 73.20 277 | 73.92 309 | 56.45 267 | 78.97 265 | 64.96 331 | 63.88 239 | 64.72 280 | 80.24 275 | 19.84 327 | 83.44 281 | 66.24 172 | 64.52 301 | 79.71 303 |
|
UnsupCasMVSNet_bld | | | 63.70 284 | 61.53 286 | 70.21 291 | 73.69 310 | 51.39 300 | 72.82 294 | 81.89 260 | 55.63 296 | 57.81 303 | 71.80 310 | 38.67 298 | 78.61 298 | 49.26 279 | 52.21 321 | 80.63 299 |
|
UnsupCasMVSNet_eth | | | 67.33 269 | 65.99 270 | 71.37 284 | 73.48 311 | 51.47 299 | 75.16 287 | 85.19 223 | 65.20 224 | 60.78 293 | 80.93 272 | 42.35 283 | 77.20 305 | 57.12 247 | 53.69 319 | 85.44 264 |
|
TDRefinement | | | 67.49 267 | 64.34 274 | 76.92 251 | 73.47 312 | 61.07 222 | 84.86 203 | 82.98 245 | 59.77 270 | 58.30 301 | 85.13 219 | 26.06 319 | 87.89 255 | 47.92 286 | 60.59 310 | 81.81 296 |
|
ambc | | | | | 75.24 264 | 73.16 313 | 50.51 305 | 63.05 322 | 87.47 200 | | 64.28 282 | 77.81 292 | 17.80 330 | 89.73 228 | 57.88 241 | 60.64 309 | 85.49 263 |
|
CMPMVS | | 51.72 21 | 70.19 256 | 68.16 256 | 76.28 255 | 73.15 314 | 57.55 254 | 79.47 260 | 83.92 233 | 48.02 317 | 56.48 309 | 84.81 225 | 43.13 278 | 86.42 265 | 62.67 199 | 81.81 167 | 84.89 270 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
new-patchmatchnet | | | 61.73 285 | 61.73 285 | 61.70 308 | 72.74 315 | 24.50 338 | 69.16 307 | 78.03 288 | 61.40 258 | 56.72 308 | 75.53 301 | 38.42 299 | 76.48 308 | 45.95 298 | 57.67 312 | 84.13 278 |
|
testus | | | 59.00 290 | 57.91 289 | 62.25 307 | 72.25 316 | 39.09 325 | 69.74 302 | 75.02 301 | 53.04 308 | 57.21 306 | 73.72 306 | 18.76 329 | 70.33 325 | 32.86 318 | 68.57 284 | 77.35 309 |
|
testpf | | | 56.51 295 | 57.58 292 | 53.30 315 | 71.99 317 | 41.19 323 | 46.89 331 | 69.32 323 | 58.06 281 | 52.87 317 | 69.45 316 | 27.99 316 | 72.73 320 | 59.59 225 | 62.07 304 | 45.98 328 |
|
test2356 | | | 59.50 288 | 58.08 288 | 63.74 304 | 71.23 318 | 41.88 320 | 67.59 313 | 72.42 315 | 53.72 304 | 57.65 304 | 70.74 312 | 26.31 318 | 72.40 321 | 32.03 322 | 71.06 274 | 76.93 312 |
|
LF4IMVS | | | 64.02 283 | 62.19 283 | 69.50 293 | 70.90 319 | 53.29 292 | 76.13 279 | 77.18 293 | 52.65 309 | 58.59 299 | 80.98 270 | 23.55 322 | 76.52 307 | 53.06 265 | 66.66 290 | 78.68 305 |
|
test1235678 | | | 58.74 291 | 56.89 294 | 64.30 302 | 69.70 320 | 41.87 321 | 71.05 298 | 74.87 303 | 54.06 301 | 50.63 319 | 71.53 311 | 25.30 320 | 74.10 317 | 31.80 323 | 63.10 303 | 76.93 312 |
|
1111 | | | 57.11 294 | 56.82 295 | 57.97 312 | 69.10 321 | 28.28 333 | 68.90 310 | 74.54 309 | 54.01 302 | 53.71 314 | 74.51 303 | 23.09 323 | 67.90 329 | 32.28 320 | 61.26 308 | 77.73 307 |
|
.test1245 | | | 45.55 304 | 50.02 301 | 32.14 324 | 69.10 321 | 28.28 333 | 68.90 310 | 74.54 309 | 54.01 302 | 53.71 314 | 74.51 303 | 23.09 323 | 67.90 329 | 32.28 320 | 0.02 338 | 0.25 337 |
|
new_pmnet | | | 50.91 301 | 50.29 300 | 52.78 316 | 68.58 323 | 34.94 331 | 63.71 320 | 56.63 333 | 39.73 323 | 44.95 321 | 65.47 319 | 21.93 325 | 58.48 333 | 34.98 316 | 56.62 315 | 64.92 322 |
|
DSMNet-mixed | | | 57.77 293 | 56.90 293 | 60.38 309 | 67.70 324 | 35.61 328 | 69.18 306 | 53.97 334 | 32.30 330 | 57.49 305 | 79.88 278 | 40.39 294 | 68.57 328 | 38.78 311 | 72.37 264 | 76.97 311 |
|
FPMVS | | | 53.68 298 | 51.64 298 | 59.81 310 | 65.08 325 | 51.03 301 | 69.48 305 | 69.58 321 | 41.46 321 | 40.67 323 | 72.32 309 | 16.46 332 | 70.00 326 | 24.24 330 | 65.42 298 | 58.40 325 |
|
pmmvs3 | | | 57.79 292 | 54.26 296 | 68.37 298 | 64.02 326 | 56.72 263 | 75.12 289 | 65.17 329 | 40.20 322 | 52.93 316 | 69.86 315 | 20.36 326 | 75.48 312 | 45.45 300 | 55.25 318 | 72.90 317 |
|
test12356 | | | 49.28 303 | 48.51 303 | 51.59 317 | 62.06 327 | 19.11 339 | 60.40 323 | 72.45 314 | 47.60 318 | 40.64 324 | 65.68 318 | 13.84 334 | 68.72 327 | 27.29 327 | 46.67 325 | 66.94 321 |
|
testmv | | | 53.85 297 | 51.03 299 | 62.31 306 | 61.46 328 | 38.88 326 | 70.95 301 | 74.69 307 | 51.11 314 | 41.26 322 | 66.85 317 | 14.28 333 | 72.13 322 | 29.19 325 | 49.51 323 | 75.93 315 |
|
PNet_i23d | | | 38.26 309 | 35.42 309 | 46.79 319 | 58.74 329 | 35.48 329 | 59.65 324 | 51.25 335 | 32.45 329 | 23.44 333 | 47.53 329 | 2.04 343 | 58.96 332 | 25.60 329 | 18.09 333 | 45.92 329 |
|
wuyk23d | | | 16.82 316 | 15.94 317 | 19.46 327 | 58.74 329 | 31.45 332 | 39.22 332 | 3.74 344 | 6.84 336 | 6.04 338 | 2.70 339 | 1.27 344 | 24.29 339 | 10.54 337 | 14.40 337 | 2.63 335 |
|
no-one | | | 51.08 300 | 45.79 305 | 66.95 301 | 57.92 331 | 50.49 306 | 59.63 325 | 76.04 297 | 48.04 316 | 31.85 326 | 56.10 327 | 19.12 328 | 80.08 294 | 36.89 314 | 26.52 328 | 70.29 319 |
|
PMMVS2 | | | 40.82 307 | 38.86 308 | 46.69 320 | 53.84 332 | 16.45 340 | 48.61 330 | 49.92 336 | 37.49 325 | 31.67 327 | 60.97 323 | 8.14 340 | 56.42 334 | 28.42 326 | 30.72 327 | 67.19 320 |
|
LCM-MVSNet | | | 54.25 296 | 49.68 302 | 67.97 299 | 53.73 333 | 45.28 314 | 66.85 317 | 80.78 269 | 35.96 326 | 39.45 325 | 62.23 322 | 8.70 339 | 78.06 302 | 48.24 283 | 51.20 322 | 80.57 300 |
|
E-PMN | | | 31.77 311 | 30.64 312 | 35.15 322 | 52.87 334 | 27.67 335 | 57.09 328 | 47.86 337 | 24.64 331 | 16.40 335 | 33.05 333 | 11.23 336 | 54.90 335 | 14.46 335 | 18.15 332 | 22.87 332 |
|
EMVS | | | 30.81 312 | 29.65 313 | 34.27 323 | 50.96 335 | 25.95 337 | 56.58 329 | 46.80 338 | 24.01 333 | 15.53 336 | 30.68 334 | 12.47 335 | 54.43 336 | 12.81 336 | 17.05 334 | 22.43 333 |
|
ANet_high | | | 50.57 302 | 46.10 304 | 63.99 303 | 48.67 336 | 39.13 324 | 70.99 300 | 80.85 268 | 61.39 259 | 31.18 328 | 57.70 325 | 17.02 331 | 73.65 319 | 31.22 324 | 15.89 335 | 79.18 304 |
|
wuykxyi23d | | | 39.76 308 | 33.18 311 | 59.51 311 | 46.98 337 | 44.01 316 | 57.70 327 | 67.74 326 | 24.13 332 | 13.98 337 | 34.33 332 | 1.27 344 | 71.33 323 | 34.23 317 | 18.23 331 | 63.18 324 |
|
MVE | | 26.22 23 | 30.37 313 | 25.89 315 | 43.81 321 | 44.55 338 | 35.46 330 | 28.87 335 | 39.07 339 | 18.20 334 | 18.58 334 | 40.18 330 | 2.68 342 | 47.37 337 | 17.07 334 | 23.78 330 | 48.60 327 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
PMVS | | 37.38 22 | 44.16 306 | 40.28 307 | 55.82 313 | 40.82 339 | 42.54 319 | 65.12 319 | 63.99 332 | 34.43 327 | 24.48 330 | 57.12 326 | 3.92 341 | 76.17 309 | 17.10 333 | 55.52 317 | 48.75 326 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
DeepMVS_CX | | | | | 27.40 326 | 40.17 340 | 26.90 336 | | 24.59 342 | 17.44 335 | 23.95 331 | 48.61 328 | 9.77 337 | 26.48 338 | 18.06 332 | 24.47 329 | 28.83 331 |
|
tmp_tt | | | 18.61 315 | 21.40 316 | 10.23 328 | 4.82 341 | 10.11 341 | 34.70 333 | 30.74 341 | 1.48 337 | 23.91 332 | 26.07 335 | 28.42 315 | 13.41 340 | 27.12 328 | 15.35 336 | 7.17 334 |
|
testmvs | | | 6.04 319 | 8.02 320 | 0.10 330 | 0.08 342 | 0.03 344 | 69.74 302 | 0.04 345 | 0.05 338 | 0.31 339 | 1.68 340 | 0.02 347 | 0.04 341 | 0.24 338 | 0.02 338 | 0.25 337 |
|
test123 | | | 6.12 318 | 8.11 319 | 0.14 329 | 0.06 343 | 0.09 343 | 71.05 298 | 0.03 346 | 0.04 339 | 0.25 340 | 1.30 341 | 0.05 346 | 0.03 342 | 0.21 339 | 0.01 340 | 0.29 336 |
|
cdsmvs_eth3d_5k | | | 19.96 314 | 26.61 314 | 0.00 331 | 0.00 344 | 0.00 345 | 0.00 336 | 89.26 153 | 0.00 340 | 0.00 341 | 88.61 125 | 61.62 136 | 0.00 343 | 0.00 340 | 0.00 341 | 0.00 339 |
|
pcd_1.5k_mvsjas | | | 5.26 320 | 7.02 321 | 0.00 331 | 0.00 344 | 0.00 345 | 0.00 336 | 0.00 347 | 0.00 340 | 0.00 341 | 0.00 342 | 63.15 101 | 0.00 343 | 0.00 340 | 0.00 341 | 0.00 339 |
|
sosnet-low-res | | | 0.00 321 | 0.00 322 | 0.00 331 | 0.00 344 | 0.00 345 | 0.00 336 | 0.00 347 | 0.00 340 | 0.00 341 | 0.00 342 | 0.00 348 | 0.00 343 | 0.00 340 | 0.00 341 | 0.00 339 |
|
sosnet | | | 0.00 321 | 0.00 322 | 0.00 331 | 0.00 344 | 0.00 345 | 0.00 336 | 0.00 347 | 0.00 340 | 0.00 341 | 0.00 342 | 0.00 348 | 0.00 343 | 0.00 340 | 0.00 341 | 0.00 339 |
|
uncertanet | | | 0.00 321 | 0.00 322 | 0.00 331 | 0.00 344 | 0.00 345 | 0.00 336 | 0.00 347 | 0.00 340 | 0.00 341 | 0.00 342 | 0.00 348 | 0.00 343 | 0.00 340 | 0.00 341 | 0.00 339 |
|
Regformer | | | 0.00 321 | 0.00 322 | 0.00 331 | 0.00 344 | 0.00 345 | 0.00 336 | 0.00 347 | 0.00 340 | 0.00 341 | 0.00 342 | 0.00 348 | 0.00 343 | 0.00 340 | 0.00 341 | 0.00 339 |
|
ab-mvs-re | | | 7.23 317 | 9.64 318 | 0.00 331 | 0.00 344 | 0.00 345 | 0.00 336 | 0.00 347 | 0.00 340 | 0.00 341 | 86.72 174 | 0.00 348 | 0.00 343 | 0.00 340 | 0.00 341 | 0.00 339 |
|
uanet | | | 0.00 321 | 0.00 322 | 0.00 331 | 0.00 344 | 0.00 345 | 0.00 336 | 0.00 347 | 0.00 340 | 0.00 341 | 0.00 342 | 0.00 348 | 0.00 343 | 0.00 340 | 0.00 341 | 0.00 339 |
|
ESAPD | | | | | | | | | 94.22 1 | | | | | | | | |
|
sam_mvs1 | | | | | | | | | | | | | 51.32 230 | | | | |
|
sam_mvs | | | | | | | | | | | | | 50.01 243 | | | | |
|
MTGPA | | | | | | | | | 92.02 59 | | | | | | | | |
|
test_post1 | | | | | | | | 78.90 267 | | | | 5.43 338 | 48.81 253 | 85.44 272 | 59.25 228 | | |
|
test_post | | | | | | | | | | | | 5.46 337 | 50.36 242 | 84.24 277 | | | |
|
patchmatchnet-post | | | | | | | | | | | | 74.00 305 | 51.12 233 | 88.60 248 | | | |
|
MTMP | | | | | | | | | 32.83 340 | | | | | | | | |
|
test9_res | | | | | | | | | | | | | | | 84.90 17 | 95.70 12 | 92.87 68 |
|
agg_prior2 | | | | | | | | | | | | | | | 82.91 39 | 95.45 14 | 92.70 69 |
|
test_prior4 | | | | | | | 72.60 27 | 89.01 75 | | | | | | | | | |
|
test_prior2 | | | | | | | | 88.85 79 | | 75.41 76 | 84.91 29 | 93.54 29 | 74.28 17 | | 83.31 32 | 95.86 6 | |
|
旧先验2 | | | | | | | | 86.56 161 | | 58.10 280 | 87.04 13 | | | 88.98 241 | 74.07 109 | | |
|
新几何2 | | | | | | | | 86.29 170 | | | | | | | | | |
|
无先验 | | | | | | | | 87.48 125 | 88.98 165 | 60.00 268 | | | | 94.12 93 | 67.28 165 | | 88.97 191 |
|
原ACMM2 | | | | | | | | 86.86 150 | | | | | | | | | |
|
testdata2 | | | | | | | | | | | | | | 91.01 213 | 62.37 201 | | |
|
segment_acmp | | | | | | | | | | | | | 73.08 23 | | | | |
|
testdata1 | | | | | | | | 84.14 221 | | 75.71 71 | | | | | | | |
|
plane_prior5 | | | | | | | | | 92.44 44 | | | | | 95.38 50 | 78.71 63 | 86.32 119 | 91.33 105 |
|
plane_prior4 | | | | | | | | | | | | 91.00 80 | | | | | |
|
plane_prior3 | | | | | | | 68.60 95 | | | 78.44 30 | 78.92 94 | | | | | | |
|
plane_prior2 | | | | | | | | 91.25 28 | | 79.12 23 | | | | | | | |
|
plane_prior | | | | | | | 68.71 91 | 90.38 44 | | 77.62 34 | | | | | | 86.16 121 | |
|
n2 | | | | | | | | | 0.00 347 | | | | | | | | |
|
nn | | | | | | | | | 0.00 347 | | | | | | | | |
|
door-mid | | | | | | | | | 69.98 319 | | | | | | | | |
|
test11 | | | | | | | | | 92.23 51 | | | | | | | | |
|
door | | | | | | | | | 69.44 322 | | | | | | | | |
|
HQP5-MVS | | | | | | | 66.98 122 | | | | | | | | | | |
|
BP-MVS | | | | | | | | | | | | | | | 77.47 75 | | |
|
HQP4-MVS | | | | | | | | | | | 77.24 133 | | | 95.11 58 | | | 91.03 111 |
|
HQP3-MVS | | | | | | | | | 92.19 54 | | | | | | | 85.99 123 | |
|
HQP2-MVS | | | | | | | | | | | | | 60.17 161 | | | | |
|
MDTV_nov1_ep13_2view | | | | | | | 37.79 327 | 75.16 287 | | 55.10 297 | 66.53 269 | | 49.34 247 | | 53.98 259 | | 87.94 221 |
|
ACMMP++_ref | | | | | | | | | | | | | | | | 81.95 165 | |
|
ACMMP++ | | | | | | | | | | | | | | | | 81.25 170 | |
|
Test By Simon | | | | | | | | | | | | | 64.33 87 | | | | |
|