This table lists the benchmark results for the high-res multi-view scenario. The following metrics are evaluated:

(*) For exact definitions, detailing how potentially incomplete ground truth is taken into account, see our paper.

The datasets are grouped into different categories, and result averages are computed for a category and method if results of the method are available for all datasets within the category. Note that the category "all" includes both the high-res multi-view and the low-res many-view scenarios.

Methods with suffix _ROB may participate in the Robust Vision Challenge.

Click a dataset result cell to show a visualization of the reconstruction. For training datasets, ground truth and accuracy / completeness visualizations are also available. The visualizations may not work with mobile browsers.




Method Infoallhigh-res
multi-view
indooroutdoorbotani.boulde.bridgedoorexhibi.lectur.living.loungeobserv.old co.statueterrac.
sort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysorted bysort bysort bysort by
patch_mono-299.26 6699.62 198.16 27899.81 4194.59 34099.52 12399.64 3399.33 299.73 4999.90 1099.00 2599.99 199.69 199.98 299.89 2
h-mvs3397.70 25797.28 27598.97 18199.70 10197.27 25899.36 20299.45 18698.94 4099.66 7299.64 17594.93 20599.99 199.48 1784.36 35999.65 121
xiu_mvs_v1_base_debu99.29 6199.27 5599.34 13399.63 12898.97 15399.12 26299.51 10598.86 4799.84 1499.47 24198.18 10299.99 199.50 1299.31 15199.08 207
xiu_mvs_v1_base99.29 6199.27 5599.34 13399.63 12898.97 15399.12 26299.51 10598.86 4799.84 1499.47 24198.18 10299.99 199.50 1299.31 15199.08 207
xiu_mvs_v1_base_debi99.29 6199.27 5599.34 13399.63 12898.97 15399.12 26299.51 10598.86 4799.84 1499.47 24198.18 10299.99 199.50 1299.31 15199.08 207
EPNet98.86 12398.71 12899.30 14397.20 35898.18 22299.62 7098.91 31899.28 398.63 28099.81 6695.96 16999.99 199.24 4299.72 11199.73 89
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
xiu_mvs_v2_base99.26 6699.25 5999.29 14699.53 15698.91 16699.02 28699.45 18698.80 5599.71 5499.26 29698.94 3599.98 799.34 3299.23 15698.98 221
PS-MVSNAJ99.32 5799.32 3599.30 14399.57 14898.94 16298.97 30099.46 17498.92 4499.71 5499.24 29899.01 1999.98 799.35 2899.66 12598.97 222
QAPM98.67 14898.30 16599.80 4399.20 24499.67 5799.77 2899.72 1194.74 32998.73 26199.90 1095.78 17999.98 796.96 27199.88 3799.76 76
3Dnovator97.25 999.24 7099.05 7899.81 4199.12 26299.66 5999.84 1099.74 1099.09 1598.92 23699.90 1095.94 17299.98 798.95 6999.92 1299.79 61
OpenMVScopyleft96.50 1698.47 15698.12 17499.52 10899.04 27899.53 8599.82 1499.72 1194.56 33298.08 31299.88 1994.73 22099.98 797.47 23999.76 10399.06 213
CANet_DTU98.97 11598.87 10899.25 15299.33 21098.42 21499.08 27199.30 26699.16 699.43 12699.75 11795.27 19699.97 1298.56 13899.95 799.36 187
zzz-MVS99.49 1799.36 2699.89 499.90 499.86 1399.36 20299.47 16498.79 5699.68 6199.81 6698.43 8699.97 1298.88 7899.90 2499.83 32
MTAPA99.52 1499.39 2099.89 499.90 499.86 1399.66 5299.47 16498.79 5699.68 6199.81 6698.43 8699.97 1298.88 7899.90 2499.83 32
PGM-MVS99.45 2899.31 4299.86 2199.87 1699.78 4099.58 9299.65 3297.84 14999.71 5499.80 8299.12 1399.97 1298.33 16299.87 4199.83 32
mPP-MVS99.44 3299.30 4599.86 2199.88 1299.79 3399.69 4199.48 14698.12 11799.50 11399.75 11798.78 5299.97 1298.57 13599.89 3499.83 32
CP-MVS99.45 2899.32 3599.85 2899.83 3799.75 4399.69 4199.52 9298.07 12799.53 10899.63 18198.93 3999.97 1298.74 10699.91 1799.83 32
SteuartSystems-ACMMP99.54 1099.42 1699.87 1299.82 3899.81 2799.59 8499.51 10598.62 6699.79 2999.83 4699.28 499.97 1298.48 14699.90 2499.84 21
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3Dnovator+97.12 1399.18 7598.97 9599.82 3899.17 25599.68 5499.81 1699.51 10599.20 598.72 26299.89 1495.68 18399.97 1298.86 8799.86 5299.81 45
DVP-MVS++99.59 399.50 999.88 699.51 16099.88 899.87 699.51 10598.99 3099.88 599.81 6699.27 599.96 2098.85 8999.80 8899.81 45
MSC_two_6792asdad99.87 1299.51 16099.76 4199.33 24999.96 2098.87 8299.84 6699.89 2
No_MVS99.87 1299.51 16099.76 4199.33 24999.96 2098.87 8299.84 6699.89 2
ZD-MVS99.71 9499.79 3399.61 3696.84 24999.56 10199.54 21598.58 7599.96 2096.93 27499.75 104
SED-MVS99.61 299.52 799.88 699.84 3399.90 299.60 7799.48 14699.08 1699.91 199.81 6699.20 799.96 2098.91 7599.85 5999.79 61
test_241102_TWO99.48 14699.08 1699.88 599.81 6698.94 3599.96 2098.91 7599.84 6699.88 8
ZNCC-MVS99.47 2499.33 3399.87 1299.87 1699.81 2799.64 6299.67 2298.08 12699.55 10599.64 17598.91 4099.96 2098.72 11099.90 2499.82 39
testtj99.12 8998.87 10899.86 2199.72 8899.79 3399.44 16399.51 10597.29 20999.59 9699.74 12398.15 10699.96 2096.74 28299.69 11799.81 45
DVP-MVScopyleft99.57 899.47 1299.88 699.85 2699.89 499.57 9899.37 23299.10 1299.81 2499.80 8298.94 3599.96 2098.93 7299.86 5299.81 45
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_THIRD98.99 3099.81 2499.80 8299.09 1499.96 2098.85 8999.90 2499.88 8
test_0728_SECOND99.91 299.84 3399.89 499.57 9899.51 10599.96 2098.93 7299.86 5299.88 8
SR-MVS99.43 3699.29 4999.86 2199.75 6799.83 1799.59 8499.62 3498.21 10799.73 4999.79 9498.68 6899.96 2098.44 15299.77 10099.79 61
DPE-MVScopyleft99.46 2699.32 3599.91 299.78 4799.88 899.36 20299.51 10598.73 6099.88 599.84 4298.72 6599.96 2098.16 17699.87 4199.88 8
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
UA-Net99.42 4199.29 4999.80 4399.62 13499.55 8099.50 13499.70 1598.79 5699.77 3699.96 197.45 12299.96 2098.92 7499.90 2499.89 2
HFP-MVS99.49 1799.37 2499.86 2199.87 1699.80 2999.66 5299.67 2298.15 11399.68 6199.69 14899.06 1699.96 2098.69 11599.87 4199.84 21
region2R99.48 2199.35 2999.87 1299.88 1299.80 2999.65 5999.66 2798.13 11599.66 7299.68 15598.96 2999.96 2098.62 12499.87 4199.84 21
#test#99.43 3699.29 4999.86 2199.87 1699.80 2999.55 11499.67 2297.83 15099.68 6199.69 14899.06 1699.96 2098.39 15499.87 4199.84 21
HPM-MVS++copyleft99.39 5099.23 6299.87 1299.75 6799.84 1699.43 16999.51 10598.68 6499.27 16799.53 21998.64 7399.96 2098.44 15299.80 8899.79 61
APDe-MVS99.66 199.57 299.92 199.77 5299.89 499.75 3299.56 5899.02 2099.88 599.85 3399.18 1099.96 2099.22 4399.92 1299.90 1
ACMMPR99.49 1799.36 2699.86 2199.87 1699.79 3399.66 5299.67 2298.15 11399.67 6799.69 14898.95 3299.96 2098.69 11599.87 4199.84 21
MP-MVScopyleft99.33 5699.15 6899.87 1299.88 1299.82 2399.66 5299.46 17498.09 12299.48 11799.74 12398.29 9799.96 2097.93 19499.87 4199.82 39
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
abl_699.44 3299.31 4299.83 3699.85 2699.75 4399.66 5299.59 4498.13 11599.82 2299.81 6698.60 7499.96 2098.46 15099.88 3799.79 61
CPTT-MVS99.11 9498.90 10499.74 5999.80 4499.46 9699.59 8499.49 13397.03 23699.63 8399.69 14897.27 13099.96 2097.82 20399.84 6699.81 45
PVSNet_Blended_VisFu99.36 5399.28 5399.61 8599.86 2299.07 14299.47 15599.93 297.66 17299.71 5499.86 2797.73 11799.96 2099.47 1999.82 8199.79 61
UGNet98.87 12098.69 13099.40 12899.22 24098.72 18499.44 16399.68 1999.24 499.18 19299.42 25392.74 27199.96 2099.34 3299.94 1099.53 156
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
CSCG99.32 5799.32 3599.32 13899.85 2698.29 21799.71 3899.66 2798.11 11999.41 13399.80 8298.37 9399.96 2098.99 6599.96 699.72 95
ACMMPcopyleft99.45 2899.32 3599.82 3899.89 999.67 5799.62 7099.69 1898.12 11799.63 8399.84 4298.73 6499.96 2098.55 14199.83 7599.81 45
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
test117299.43 3699.29 4999.85 2899.75 6799.82 2399.60 7799.56 5898.28 9899.74 4799.79 9498.53 7799.95 4798.55 14199.78 9599.79 61
SR-MVS-dyc-post99.45 2899.31 4299.85 2899.76 5699.82 2399.63 6499.52 9298.38 8699.76 4399.82 5398.53 7799.95 4798.61 12799.81 8499.77 71
GST-MVS99.40 4999.24 6099.85 2899.86 2299.79 3399.60 7799.67 2297.97 13899.63 8399.68 15598.52 7999.95 4798.38 15699.86 5299.81 45
CANet99.25 6999.14 6999.59 8799.41 19199.16 12899.35 20899.57 5298.82 5199.51 11299.61 19196.46 15599.95 4799.59 599.98 299.65 121
MP-MVS-pluss99.37 5299.20 6499.88 699.90 499.87 1299.30 21899.52 9297.18 21999.60 9399.79 9498.79 5199.95 4798.83 9599.91 1799.83 32
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
MSP-MVS99.42 4199.27 5599.88 699.89 999.80 2999.67 4899.50 12598.70 6299.77 3699.49 23298.21 10099.95 4798.46 15099.77 10099.88 8
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
mvs-test198.86 12398.84 11498.89 19899.33 21097.77 24499.44 16399.30 26698.47 7799.10 20499.43 25096.78 14499.95 4798.73 10899.02 17698.96 224
testdata299.95 4796.67 287
APD-MVS_3200maxsize99.48 2199.35 2999.85 2899.76 5699.83 1799.63 6499.54 7598.36 9099.79 2999.82 5398.86 4499.95 4798.62 12499.81 8499.78 69
RPMNet96.72 29595.90 30599.19 15899.18 24998.49 20799.22 24899.52 9288.72 35999.56 10197.38 35694.08 24599.95 4786.87 36698.58 19899.14 199
sss99.17 7799.05 7899.53 10299.62 13498.97 15399.36 20299.62 3497.83 15099.67 6799.65 16897.37 12799.95 4799.19 4699.19 15999.68 111
TSAR-MVS + MP.99.58 599.50 999.81 4199.91 199.66 5999.63 6499.39 21798.91 4599.78 3499.85 3399.36 299.94 5898.84 9299.88 3799.82 39
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
Regformer-499.59 399.54 599.73 6199.76 5699.41 10199.58 9299.49 13399.02 2099.88 599.80 8299.00 2599.94 5899.45 2199.92 1299.84 21
Regformer-299.54 1099.47 1299.75 5499.71 9499.52 8899.49 14499.49 13398.94 4099.83 1999.76 11299.01 1999.94 5899.15 5299.87 4199.80 55
XVS99.53 1299.42 1699.87 1299.85 2699.83 1799.69 4199.68 1998.98 3399.37 14599.74 12398.81 4999.94 5898.79 10199.86 5299.84 21
X-MVStestdata96.55 29795.45 31299.87 1299.85 2699.83 1799.69 4199.68 1998.98 3399.37 14564.01 37698.81 4999.94 5898.79 10199.86 5299.84 21
旧先验298.96 30196.70 25799.47 11899.94 5898.19 171
新几何199.75 5499.75 6799.59 7399.54 7596.76 25399.29 16299.64 17598.43 8699.94 5896.92 27699.66 12599.72 95
testdata99.54 9699.75 6798.95 15999.51 10597.07 23199.43 12699.70 13998.87 4399.94 5897.76 20899.64 12899.72 95
HPM-MVScopyleft99.42 4199.28 5399.83 3699.90 499.72 4799.81 1699.54 7597.59 17699.68 6199.63 18198.91 4099.94 5898.58 13399.91 1799.84 21
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
CHOSEN 1792x268899.19 7399.10 7399.45 12299.89 998.52 20399.39 19099.94 198.73 6099.11 20199.89 1495.50 18899.94 5899.50 1299.97 499.89 2
APD-MVScopyleft99.27 6499.08 7699.84 3599.75 6799.79 3399.50 13499.50 12597.16 22199.77 3699.82 5398.78 5299.94 5897.56 23099.86 5299.80 55
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
DELS-MVS99.48 2199.42 1699.65 7599.72 8899.40 10399.05 27799.66 2799.14 799.57 10099.80 8298.46 8499.94 5899.57 799.84 6699.60 138
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
WTY-MVS99.06 10298.88 10799.61 8599.62 13499.16 12899.37 19899.56 5898.04 13399.53 10899.62 18796.84 14299.94 5898.85 8998.49 20599.72 95
DeepC-MVS98.35 299.30 5999.19 6599.64 8099.82 3899.23 12199.62 7099.55 6798.94 4099.63 8399.95 295.82 17899.94 5899.37 2799.97 499.73 89
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
LS3D99.27 6499.12 7199.74 5999.18 24999.75 4399.56 10599.57 5298.45 8099.49 11699.85 3397.77 11699.94 5898.33 16299.84 6699.52 157
xxxxxxxxxxxxxcwj99.43 3699.32 3599.75 5499.76 5699.59 7399.14 26099.53 8699.00 2799.71 5499.80 8298.95 3299.93 7398.19 17199.84 6699.74 82
SF-MVS99.38 5199.24 6099.79 4699.79 4599.68 5499.57 9899.54 7597.82 15599.71 5499.80 8298.95 3299.93 7398.19 17199.84 6699.74 82
Anonymous2024052998.09 19197.68 22599.34 13399.66 11898.44 21199.40 18699.43 20393.67 33999.22 18099.89 1490.23 32299.93 7399.26 4198.33 20899.66 117
ACMMP_NAP99.47 2499.34 3199.88 699.87 1699.86 1399.47 15599.48 14698.05 13299.76 4399.86 2798.82 4899.93 7398.82 9999.91 1799.84 21
EI-MVSNet-UG-set99.58 599.57 299.64 8099.78 4799.14 13399.60 7799.45 18699.01 2399.90 399.83 4698.98 2799.93 7399.59 599.95 799.86 14
Regformer-199.53 1299.47 1299.72 6499.71 9499.44 9899.49 14499.46 17498.95 3999.83 1999.76 11299.01 1999.93 7399.17 4999.87 4199.80 55
无先验98.99 29399.51 10596.89 24699.93 7397.53 23399.72 95
112199.09 9898.87 10899.75 5499.74 7599.60 7099.27 22999.48 14696.82 25299.25 17499.65 16898.38 9199.93 7397.53 23399.67 12499.73 89
VDDNet97.55 26997.02 28699.16 16199.49 17298.12 22799.38 19599.30 26695.35 31899.68 6199.90 1082.62 36399.93 7399.31 3598.13 22499.42 180
ab-mvs98.86 12398.63 13799.54 9699.64 12599.19 12399.44 16399.54 7597.77 15899.30 15999.81 6694.20 23999.93 7399.17 4998.82 18999.49 167
F-COLMAP99.19 7399.04 8199.64 8099.78 4799.27 11799.42 17699.54 7597.29 20999.41 13399.59 19798.42 8999.93 7398.19 17199.69 11799.73 89
ETH3D cwj APD-0.1699.06 10298.84 11499.72 6499.51 16099.60 7099.23 24399.44 19597.04 23499.39 14099.67 16198.30 9699.92 8497.27 24999.69 11799.64 128
Anonymous20240521198.30 17197.98 19199.26 15199.57 14898.16 22399.41 17898.55 34496.03 31199.19 18999.74 12391.87 29499.92 8499.16 5198.29 21399.70 104
EI-MVSNet-Vis-set99.58 599.56 499.64 8099.78 4799.15 13299.61 7699.45 18699.01 2399.89 499.82 5399.01 1999.92 8499.56 899.95 799.85 17
VDD-MVS97.73 25097.35 26698.88 20199.47 18097.12 26499.34 21198.85 32498.19 10899.67 6799.85 3382.98 36199.92 8499.49 1698.32 21299.60 138
VNet99.11 9498.90 10499.73 6199.52 15899.56 7899.41 17899.39 21799.01 2399.74 4799.78 10195.56 18699.92 8499.52 1098.18 21999.72 95
XVG-OURS-SEG-HR98.69 14698.62 14298.89 19899.71 9497.74 24599.12 26299.54 7598.44 8399.42 12999.71 13594.20 23999.92 8498.54 14398.90 18599.00 218
HPM-MVS_fast99.51 1599.40 1999.85 2899.91 199.79 3399.76 3199.56 5897.72 16499.76 4399.75 11799.13 1299.92 8499.07 5999.92 1299.85 17
HY-MVS97.30 798.85 13198.64 13699.47 11999.42 18899.08 14099.62 7099.36 23397.39 20299.28 16499.68 15596.44 15799.92 8498.37 15898.22 21499.40 185
DP-MVS99.16 7998.95 9999.78 4899.77 5299.53 8599.41 17899.50 12597.03 23699.04 21799.88 1997.39 12399.92 8498.66 12099.90 2499.87 13
IB-MVS95.67 1896.22 30395.44 31398.57 23699.21 24296.70 29098.65 33497.74 35896.71 25697.27 33298.54 34386.03 35499.92 8498.47 14986.30 35799.10 202
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
DeepC-MVS_fast98.69 199.49 1799.39 2099.77 5099.63 12899.59 7399.36 20299.46 17499.07 1899.79 2999.82 5398.85 4599.92 8498.68 11799.87 4199.82 39
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
ETH3 D test640098.70 14498.35 16099.73 6199.69 10499.60 7099.16 25499.45 18695.42 31799.27 16799.60 19497.39 12399.91 9595.36 31599.83 7599.70 104
9.1499.10 7399.72 8899.40 18699.51 10597.53 18699.64 8299.78 10198.84 4699.91 9597.63 22199.82 81
ETH3D-3000-0.199.21 7199.02 8699.77 5099.73 8399.69 5299.38 19599.51 10597.45 19399.61 8999.75 11798.51 8099.91 9597.45 24299.83 7599.71 102
SMA-MVScopyleft99.44 3299.30 4599.85 2899.73 8399.83 1799.56 10599.47 16497.45 19399.78 3499.82 5399.18 1099.91 9598.79 10199.89 3499.81 45
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
TEST999.67 10999.65 6299.05 27799.41 20796.22 29598.95 23199.49 23298.77 5599.91 95
train_agg99.02 10898.77 12299.77 5099.67 10999.65 6299.05 27799.41 20796.28 28898.95 23199.49 23298.76 5799.91 9597.63 22199.72 11199.75 77
test_899.67 10999.61 6899.03 28399.41 20796.28 28898.93 23599.48 23898.76 5799.91 95
agg_prior199.01 11198.76 12499.76 5399.67 10999.62 6698.99 29399.40 21396.26 29198.87 24499.49 23298.77 5599.91 9597.69 21899.72 11199.75 77
agg_prior99.67 10999.62 6699.40 21398.87 24499.91 95
Regformer-399.57 899.53 699.68 6899.76 5699.29 11499.58 9299.44 19599.01 2399.87 1199.80 8298.97 2899.91 9599.44 2399.92 1299.83 32
原ACMM199.65 7599.73 8399.33 10899.47 16497.46 19099.12 19999.66 16798.67 7199.91 9597.70 21799.69 11799.71 102
LFMVS97.90 22197.35 26699.54 9699.52 15899.01 14899.39 19098.24 34897.10 22999.65 7899.79 9484.79 35899.91 9599.28 3898.38 20799.69 107
XVG-OURS98.73 14398.68 13198.88 20199.70 10197.73 24698.92 30899.55 6798.52 7499.45 12199.84 4295.27 19699.91 9598.08 18498.84 18899.00 218
PLCcopyleft97.94 499.02 10898.85 11399.53 10299.66 11899.01 14899.24 24299.52 9296.85 24899.27 16799.48 23898.25 9999.91 9597.76 20899.62 13199.65 121
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
PCF-MVS97.08 1497.66 26497.06 28599.47 11999.61 13899.09 13998.04 35999.25 27791.24 35398.51 28999.70 13994.55 22999.91 9592.76 34699.85 5999.42 180
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
MCST-MVS99.43 3699.30 4599.82 3899.79 4599.74 4699.29 22299.40 21398.79 5699.52 11099.62 18798.91 4099.90 11098.64 12299.75 10499.82 39
CDPH-MVS99.13 8398.91 10399.80 4399.75 6799.71 4999.15 25899.41 20796.60 26799.60 9399.55 21098.83 4799.90 11097.48 23799.83 7599.78 69
NCCC99.34 5599.19 6599.79 4699.61 13899.65 6299.30 21899.48 14698.86 4799.21 18399.63 18198.72 6599.90 11098.25 16799.63 13099.80 55
114514_t98.93 11798.67 13299.72 6499.85 2699.53 8599.62 7099.59 4492.65 34899.71 5499.78 10198.06 10999.90 11098.84 9299.91 1799.74 82
1112_ss98.98 11398.77 12299.59 8799.68 10899.02 14699.25 24099.48 14697.23 21699.13 19799.58 20096.93 14199.90 11098.87 8298.78 19299.84 21
PHI-MVS99.30 5999.17 6799.70 6799.56 15299.52 8899.58 9299.80 897.12 22599.62 8799.73 13098.58 7599.90 11098.61 12799.91 1799.68 111
AdaColmapbinary99.01 11198.80 11999.66 7199.56 15299.54 8299.18 25299.70 1598.18 11199.35 15199.63 18196.32 16099.90 11097.48 23799.77 10099.55 149
COLMAP_ROBcopyleft97.56 698.86 12398.75 12599.17 16099.88 1298.53 19999.34 21199.59 4497.55 18198.70 26999.89 1495.83 17799.90 11098.10 17999.90 2499.08 207
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
thisisatest053098.35 16798.03 18699.31 13999.63 12898.56 19699.54 11796.75 36597.53 18699.73 4999.65 16891.25 31099.89 11898.62 12499.56 13499.48 168
tttt051798.42 16098.14 17299.28 14999.66 11898.38 21599.74 3596.85 36397.68 16899.79 2999.74 12391.39 30799.89 11898.83 9599.56 13499.57 147
test1299.75 5499.64 12599.61 6899.29 27199.21 18398.38 9199.89 11899.74 10799.74 82
Test_1112_low_res98.89 11998.66 13599.57 9299.69 10498.95 15999.03 28399.47 16496.98 23899.15 19599.23 29996.77 14699.89 11898.83 9598.78 19299.86 14
CNLPA99.14 8198.99 9199.59 8799.58 14699.41 10199.16 25499.44 19598.45 8099.19 18999.49 23298.08 10899.89 11897.73 21299.75 10499.48 168
diffmvs99.14 8199.02 8699.51 11299.61 13898.96 15799.28 22499.49 13398.46 7999.72 5399.71 13596.50 15499.88 12399.31 3599.11 16599.67 114
PVSNet_BlendedMVS98.86 12398.80 11999.03 17399.76 5698.79 18099.28 22499.91 397.42 19999.67 6799.37 26897.53 12099.88 12398.98 6697.29 26098.42 323
PVSNet_Blended99.08 10098.97 9599.42 12799.76 5698.79 18098.78 32299.91 396.74 25499.67 6799.49 23297.53 12099.88 12398.98 6699.85 5999.60 138
MVS97.28 28496.55 29399.48 11698.78 31198.95 15999.27 22999.39 21783.53 36398.08 31299.54 21596.97 13999.87 12694.23 32999.16 16099.63 132
MG-MVS99.13 8399.02 8699.45 12299.57 14898.63 19199.07 27299.34 24298.99 3099.61 8999.82 5397.98 11199.87 12697.00 26799.80 8899.85 17
MSDG98.98 11398.80 11999.53 10299.76 5699.19 12398.75 32599.55 6797.25 21399.47 11899.77 10897.82 11499.87 12696.93 27499.90 2499.54 151
ETV-MVS99.26 6699.21 6399.40 12899.46 18199.30 11399.56 10599.52 9298.52 7499.44 12599.27 29498.41 9099.86 12999.10 5699.59 13399.04 214
thisisatest051598.14 18697.79 21099.19 15899.50 17098.50 20698.61 33696.82 36496.95 24299.54 10699.43 25091.66 30399.86 12998.08 18499.51 13899.22 196
thres600view797.86 22697.51 24298.92 18999.72 8897.95 23699.59 8498.74 33297.94 14099.27 16798.62 34091.75 29799.86 12993.73 33498.19 21898.96 224
lupinMVS99.13 8399.01 9099.46 12199.51 16098.94 16299.05 27799.16 29097.86 14599.80 2799.56 20797.39 12399.86 12998.94 7099.85 5999.58 146
PVSNet96.02 1798.85 13198.84 11498.89 19899.73 8397.28 25798.32 35299.60 4197.86 14599.50 11399.57 20496.75 14799.86 12998.56 13899.70 11699.54 151
MAR-MVS98.86 12398.63 13799.54 9699.37 20299.66 5999.45 15999.54 7596.61 26599.01 22099.40 26097.09 13499.86 12997.68 22099.53 13799.10 202
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
test250696.81 29396.65 29197.29 32199.74 7592.21 36199.60 7785.06 38099.13 899.77 3699.93 487.82 35099.85 13599.38 2699.38 14399.80 55
AllTest98.87 12098.72 12699.31 13999.86 2298.48 20999.56 10599.61 3697.85 14799.36 14899.85 3395.95 17099.85 13596.66 28899.83 7599.59 142
TestCases99.31 13999.86 2298.48 20999.61 3697.85 14799.36 14899.85 3395.95 17099.85 13596.66 28899.83 7599.59 142
jason99.13 8399.03 8399.45 12299.46 18198.87 16999.12 26299.26 27598.03 13599.79 2999.65 16897.02 13799.85 13599.02 6399.90 2499.65 121
jason: jason.
CNVR-MVS99.42 4199.30 4599.78 4899.62 13499.71 4999.26 23899.52 9298.82 5199.39 14099.71 13598.96 2999.85 13598.59 13299.80 8899.77 71
PAPM_NR99.04 10598.84 11499.66 7199.74 7599.44 9899.39 19099.38 22397.70 16699.28 16499.28 29198.34 9499.85 13596.96 27199.45 13999.69 107
test111198.04 20098.11 17597.83 30199.74 7593.82 34899.58 9295.40 37099.12 1099.65 7899.93 490.73 31599.84 14199.43 2499.38 14399.82 39
ECVR-MVScopyleft98.04 20098.05 18498.00 29099.74 7594.37 34399.59 8494.98 37199.13 899.66 7299.93 490.67 31699.84 14199.40 2599.38 14399.80 55
test_yl98.86 12398.63 13799.54 9699.49 17299.18 12599.50 13499.07 30198.22 10599.61 8999.51 22695.37 19299.84 14198.60 13098.33 20899.59 142
DCV-MVSNet98.86 12398.63 13799.54 9699.49 17299.18 12599.50 13499.07 30198.22 10599.61 8999.51 22695.37 19299.84 14198.60 13098.33 20899.59 142
Fast-Effi-MVS+98.70 14498.43 15599.51 11299.51 16099.28 11599.52 12399.47 16496.11 30699.01 22099.34 27796.20 16499.84 14197.88 19798.82 18999.39 186
TSAR-MVS + GP.99.36 5399.36 2699.36 13299.67 10998.61 19499.07 27299.33 24999.00 2799.82 2299.81 6699.06 1699.84 14199.09 5799.42 14199.65 121
tpmrst98.33 16898.48 15397.90 29799.16 25794.78 33899.31 21699.11 29597.27 21199.45 12199.59 19795.33 19499.84 14198.48 14698.61 19599.09 206
Vis-MVSNetpermissive99.12 8998.97 9599.56 9499.78 4799.10 13899.68 4699.66 2798.49 7699.86 1299.87 2494.77 21799.84 14199.19 4699.41 14299.74 82
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
PAPR98.63 15298.34 16199.51 11299.40 19699.03 14598.80 32099.36 23396.33 28599.00 22599.12 31398.46 8499.84 14195.23 31799.37 15099.66 117
PatchMatch-RL98.84 13498.62 14299.52 10899.71 9499.28 11599.06 27599.77 997.74 16399.50 11399.53 21995.41 19099.84 14197.17 26099.64 12899.44 178
EPP-MVSNet99.13 8398.99 9199.53 10299.65 12399.06 14399.81 1699.33 24997.43 19799.60 9399.88 1997.14 13299.84 14199.13 5398.94 18099.69 107
thres100view90097.76 24297.45 24998.69 22799.72 8897.86 24199.59 8498.74 33297.93 14199.26 17298.62 34091.75 29799.83 15293.22 33998.18 21998.37 329
tfpn200view997.72 25297.38 26298.72 22599.69 10497.96 23499.50 13498.73 33797.83 15099.17 19398.45 34591.67 30199.83 15293.22 33998.18 21998.37 329
test_prior399.21 7199.05 7899.68 6899.67 10999.48 9398.96 30199.56 5898.34 9299.01 22099.52 22298.68 6899.83 15297.96 19199.74 10799.74 82
test_prior99.68 6899.67 10999.48 9399.56 5899.83 15299.74 82
131498.68 14798.54 15199.11 16598.89 29598.65 18999.27 22999.49 13396.89 24697.99 31799.56 20797.72 11899.83 15297.74 21199.27 15498.84 231
thres40097.77 24197.38 26298.92 18999.69 10497.96 23499.50 13498.73 33797.83 15099.17 19398.45 34591.67 30199.83 15293.22 33998.18 21998.96 224
casdiffmvs99.13 8398.98 9499.56 9499.65 12399.16 12899.56 10599.50 12598.33 9599.41 13399.86 2795.92 17399.83 15299.45 2199.16 16099.70 104
MVS_Test99.10 9798.97 9599.48 11699.49 17299.14 13399.67 4899.34 24297.31 20799.58 9899.76 11297.65 11999.82 15998.87 8299.07 17199.46 175
dp97.75 24697.80 20997.59 31299.10 26793.71 35199.32 21498.88 32296.48 27799.08 21099.55 21092.67 27799.82 15996.52 29098.58 19899.24 195
RPSCF98.22 17598.62 14296.99 32699.82 3891.58 36399.72 3699.44 19596.61 26599.66 7299.89 1495.92 17399.82 15997.46 24099.10 16899.57 147
PMMVS98.80 13898.62 14299.34 13399.27 22898.70 18598.76 32499.31 26297.34 20499.21 18399.07 31597.20 13199.82 15998.56 13898.87 18699.52 157
EIA-MVS99.18 7599.09 7599.45 12299.49 17299.18 12599.67 4899.53 8697.66 17299.40 13899.44 24798.10 10799.81 16398.94 7099.62 13199.35 188
Effi-MVS+98.81 13598.59 14899.48 11699.46 18199.12 13798.08 35899.50 12597.50 18999.38 14399.41 25796.37 15999.81 16399.11 5598.54 20299.51 163
thres20097.61 26797.28 27598.62 23099.64 12598.03 22899.26 23898.74 33297.68 16899.09 20998.32 34991.66 30399.81 16392.88 34398.22 21498.03 343
tpmvs97.98 21198.02 18897.84 30099.04 27894.73 33999.31 21699.20 28596.10 31098.76 25999.42 25394.94 20499.81 16396.97 27098.45 20698.97 222
DeepPCF-MVS98.18 398.81 13599.37 2497.12 32599.60 14291.75 36298.61 33699.44 19599.35 199.83 1999.85 3398.70 6799.81 16399.02 6399.91 1799.81 45
DPM-MVS98.95 11698.71 12899.66 7199.63 12899.55 8098.64 33599.10 29697.93 14199.42 12999.55 21098.67 7199.80 16895.80 30499.68 12299.61 136
DP-MVS Recon99.12 8998.95 9999.65 7599.74 7599.70 5199.27 22999.57 5296.40 28499.42 12999.68 15598.75 6099.80 16897.98 19099.72 11199.44 178
MVS_111021_LR99.41 4699.33 3399.65 7599.77 5299.51 9098.94 30799.85 698.82 5199.65 7899.74 12398.51 8099.80 16898.83 9599.89 3499.64 128
Fast-Effi-MVS+-dtu98.77 14198.83 11898.60 23199.41 19196.99 27899.52 12399.49 13398.11 11999.24 17599.34 27796.96 14099.79 17197.95 19399.45 13999.02 217
baseline198.31 16997.95 19699.38 13199.50 17098.74 18299.59 8498.93 31398.41 8499.14 19699.60 19494.59 22699.79 17198.48 14693.29 33699.61 136
baseline99.15 8099.02 8699.53 10299.66 11899.14 13399.72 3699.48 14698.35 9199.42 12999.84 4296.07 16699.79 17199.51 1199.14 16399.67 114
PVSNet_094.43 1996.09 30895.47 31197.94 29399.31 21894.34 34597.81 36199.70 1597.12 22597.46 32898.75 33789.71 32799.79 17197.69 21881.69 36399.68 111
API-MVS99.04 10599.03 8399.06 16899.40 19699.31 11299.55 11499.56 5898.54 7299.33 15599.39 26498.76 5799.78 17596.98 26999.78 9598.07 340
OMC-MVS99.08 10099.04 8199.20 15799.67 10998.22 22199.28 22499.52 9298.07 12799.66 7299.81 6697.79 11599.78 17597.79 20599.81 8499.60 138
GeoE98.85 13198.62 14299.53 10299.61 13899.08 14099.80 2099.51 10597.10 22999.31 15799.78 10195.23 20099.77 17798.21 16999.03 17499.75 77
CS-MVS99.50 1699.49 1199.52 10899.76 5699.35 10699.90 199.55 6798.56 7099.77 3699.70 13998.75 6099.77 17799.64 299.78 9599.42 180
CS-MVS-test99.42 4199.39 2099.52 10899.77 5299.35 10699.80 2099.57 5298.56 7099.77 3699.44 24798.16 10599.77 17799.64 299.78 9599.42 180
alignmvs98.81 13598.56 15099.58 9099.43 18799.42 10099.51 12898.96 31198.61 6799.35 15198.92 33094.78 21499.77 17799.35 2898.11 22599.54 151
tpm cat197.39 28197.36 26497.50 31699.17 25593.73 35099.43 16999.31 26291.27 35298.71 26399.08 31494.31 23799.77 17796.41 29498.50 20499.00 218
CostFormer97.72 25297.73 22197.71 30899.15 26094.02 34799.54 11799.02 30594.67 33099.04 21799.35 27492.35 28999.77 17798.50 14597.94 22899.34 190
test_241102_ONE99.84 3399.90 299.48 14699.07 1899.91 199.74 12399.20 799.76 183
MDTV_nov1_ep1398.32 16399.11 26494.44 34299.27 22998.74 33297.51 18899.40 13899.62 18794.78 21499.76 18397.59 22498.81 191
canonicalmvs99.02 10898.86 11299.51 11299.42 18899.32 10999.80 2099.48 14698.63 6599.31 15798.81 33397.09 13499.75 18599.27 4097.90 22999.47 173
Effi-MVS+-dtu98.78 13998.89 10698.47 25099.33 21096.91 28499.57 9899.30 26698.47 7799.41 13398.99 32496.78 14499.74 18698.73 10899.38 14398.74 247
patchmatchnet-post98.70 33894.79 21399.74 186
SCA98.19 17998.16 17098.27 27399.30 21995.55 31999.07 27298.97 30997.57 17999.43 12699.57 20492.72 27299.74 18697.58 22599.20 15899.52 157
DWT-MVSNet_test97.53 27197.40 26097.93 29499.03 28094.86 33799.57 9898.63 34196.59 26998.36 30098.79 33489.32 33199.74 18698.14 17898.16 22399.20 198
BH-untuned98.42 16098.36 15898.59 23299.49 17296.70 29099.27 22999.13 29497.24 21598.80 25499.38 26595.75 18099.74 18697.07 26599.16 16099.33 191
BH-RMVSNet98.41 16298.08 18099.40 12899.41 19198.83 17699.30 21898.77 32897.70 16698.94 23399.65 16892.91 26799.74 18696.52 29099.55 13699.64 128
MVS_111021_HR99.41 4699.32 3599.66 7199.72 8899.47 9598.95 30599.85 698.82 5199.54 10699.73 13098.51 8099.74 18698.91 7599.88 3799.77 71
test_post65.99 37494.65 22599.73 193
XVG-ACMP-BASELINE97.83 23297.71 22398.20 27599.11 26496.33 30399.41 17899.52 9298.06 13199.05 21699.50 22989.64 32999.73 19397.73 21297.38 25898.53 310
HyFIR lowres test99.11 9498.92 10199.65 7599.90 499.37 10499.02 28699.91 397.67 17199.59 9699.75 11795.90 17599.73 19399.53 999.02 17699.86 14
DeepMVS_CXcopyleft93.34 34399.29 22382.27 36999.22 28185.15 36196.33 34599.05 31890.97 31399.73 19393.57 33697.77 23298.01 344
Patchmatch-test97.93 21697.65 22898.77 22199.18 24997.07 26999.03 28399.14 29396.16 30198.74 26099.57 20494.56 22899.72 19793.36 33899.11 16599.52 157
LPG-MVS_test98.22 17598.13 17398.49 24499.33 21097.05 27199.58 9299.55 6797.46 19099.24 17599.83 4692.58 27999.72 19798.09 18097.51 24598.68 264
LGP-MVS_train98.49 24499.33 21097.05 27199.55 6797.46 19099.24 17599.83 4692.58 27999.72 19798.09 18097.51 24598.68 264
BH-w/o98.00 20997.89 20598.32 26699.35 20596.20 30799.01 29198.90 32096.42 28298.38 29899.00 32395.26 19899.72 19796.06 29898.61 19599.03 215
ACMP97.20 1198.06 19497.94 19898.45 25299.37 20297.01 27699.44 16399.49 13397.54 18498.45 29399.79 9491.95 29399.72 19797.91 19597.49 25098.62 293
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
LTVRE_ROB97.16 1298.02 20497.90 20198.40 25999.23 23696.80 28899.70 3999.60 4197.12 22598.18 30999.70 13991.73 29999.72 19798.39 15497.45 25298.68 264
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
test_post199.23 24365.14 37594.18 24299.71 20397.58 225
ADS-MVSNet98.20 17898.08 18098.56 23899.33 21096.48 29899.23 24399.15 29196.24 29399.10 20499.67 16194.11 24399.71 20396.81 27999.05 17299.48 168
JIA-IIPM97.50 27597.02 28698.93 18798.73 31797.80 24399.30 21898.97 30991.73 35198.91 23794.86 36495.10 20299.71 20397.58 22597.98 22799.28 194
EPMVS97.82 23597.65 22898.35 26398.88 29695.98 31199.49 14494.71 37397.57 17999.26 17299.48 23892.46 28699.71 20397.87 19899.08 17099.35 188
TDRefinement95.42 31494.57 32097.97 29289.83 37396.11 30999.48 15098.75 32996.74 25496.68 34299.88 1988.65 33899.71 20398.37 15882.74 36298.09 339
ACMM97.58 598.37 16698.34 16198.48 24699.41 19197.10 26599.56 10599.45 18698.53 7399.04 21799.85 3393.00 26399.71 20398.74 10697.45 25298.64 283
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
CHOSEN 280x42099.12 8999.13 7099.08 16699.66 11897.89 23898.43 34699.71 1398.88 4699.62 8799.76 11296.63 15099.70 20999.46 2099.99 199.66 117
DROMVSNet99.44 3299.39 2099.58 9099.56 15299.49 9199.88 299.58 5098.38 8699.73 4999.69 14898.20 10199.70 20999.64 299.82 8199.54 151
PatchmatchNetpermissive98.31 16998.36 15898.19 27699.16 25795.32 32799.27 22998.92 31597.37 20399.37 14599.58 20094.90 20899.70 20997.43 24499.21 15799.54 151
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
ACMH97.28 898.10 19097.99 19098.44 25599.41 19196.96 28299.60 7799.56 5898.09 12298.15 31099.91 890.87 31499.70 20998.88 7897.45 25298.67 271
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
HQP_MVS98.27 17498.22 16998.44 25599.29 22396.97 28099.39 19099.47 16498.97 3699.11 20199.61 19192.71 27499.69 21397.78 20697.63 23498.67 271
plane_prior599.47 16499.69 21397.78 20697.63 23498.67 271
D2MVS98.41 16298.50 15298.15 28099.26 23096.62 29499.40 18699.61 3697.71 16598.98 22799.36 27196.04 16799.67 21598.70 11297.41 25698.15 338
IS-MVSNet99.05 10498.87 10899.57 9299.73 8399.32 10999.75 3299.20 28598.02 13699.56 10199.86 2796.54 15399.67 21598.09 18099.13 16499.73 89
CLD-MVS98.16 18398.10 17698.33 26499.29 22396.82 28798.75 32599.44 19597.83 15099.13 19799.55 21092.92 26599.67 21598.32 16497.69 23398.48 314
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
AUN-MVS96.88 29196.31 29798.59 23299.48 17997.04 27499.27 22999.22 28197.44 19698.51 28999.41 25791.97 29299.66 21897.71 21583.83 36099.07 212
UniMVSNet_ETH3D97.32 28396.81 28998.87 20599.40 19697.46 25399.51 12899.53 8695.86 31398.54 28899.77 10882.44 36499.66 21898.68 11797.52 24499.50 166
OPM-MVS98.19 17998.10 17698.45 25298.88 29697.07 26999.28 22499.38 22398.57 6999.22 18099.81 6692.12 29099.66 21898.08 18497.54 24398.61 302
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
ACMH+97.24 1097.92 21997.78 21398.32 26699.46 18196.68 29299.56 10599.54 7598.41 8497.79 32499.87 2490.18 32399.66 21898.05 18897.18 26498.62 293
hse-mvs297.50 27597.14 28298.59 23299.49 17297.05 27199.28 22499.22 28198.94 4099.66 7299.42 25394.93 20599.65 22299.48 1783.80 36199.08 207
VPA-MVSNet98.29 17297.95 19699.30 14399.16 25799.54 8299.50 13499.58 5098.27 10099.35 15199.37 26892.53 28199.65 22299.35 2894.46 32098.72 249
TR-MVS97.76 24297.41 25998.82 21499.06 27497.87 23998.87 31498.56 34396.63 26498.68 27199.22 30092.49 28299.65 22295.40 31397.79 23198.95 227
gm-plane-assit98.54 33692.96 35794.65 33199.15 30899.64 22597.56 230
HQP4-MVS98.66 27299.64 22598.64 283
HQP-MVS98.02 20497.90 20198.37 26299.19 24696.83 28598.98 29799.39 21798.24 10198.66 27299.40 26092.47 28399.64 22597.19 25797.58 23998.64 283
PAPM97.59 26897.09 28499.07 16799.06 27498.26 22098.30 35399.10 29694.88 32698.08 31299.34 27796.27 16299.64 22589.87 35598.92 18399.31 192
TAPA-MVS97.07 1597.74 24997.34 26998.94 18599.70 10197.53 25199.25 24099.51 10591.90 35099.30 15999.63 18198.78 5299.64 22588.09 36299.87 4199.65 121
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
XXY-MVS98.38 16598.09 17999.24 15499.26 23099.32 10999.56 10599.55 6797.45 19398.71 26399.83 4693.23 25999.63 23098.88 7896.32 28198.76 241
ITE_SJBPF98.08 28299.29 22396.37 30198.92 31598.34 9298.83 25099.75 11791.09 31199.62 23195.82 30297.40 25798.25 334
LF4IMVS97.52 27297.46 24897.70 30998.98 28795.55 31999.29 22298.82 32798.07 12798.66 27299.64 17589.97 32499.61 23297.01 26696.68 26997.94 350
tpm97.67 26397.55 23698.03 28599.02 28195.01 33399.43 16998.54 34596.44 28099.12 19999.34 27791.83 29699.60 23397.75 21096.46 27799.48 168
tpm297.44 28097.34 26997.74 30799.15 26094.36 34499.45 15998.94 31293.45 34498.90 23999.44 24791.35 30899.59 23497.31 24798.07 22699.29 193
baseline297.87 22497.55 23698.82 21499.18 24998.02 22999.41 17896.58 36796.97 23996.51 34399.17 30593.43 25699.57 23597.71 21599.03 17498.86 229
MS-PatchMatch97.24 28697.32 27296.99 32698.45 33993.51 35598.82 31899.32 25997.41 20098.13 31199.30 28788.99 33499.56 23695.68 30799.80 8897.90 353
TinyColmap97.12 28896.89 28897.83 30199.07 27295.52 32298.57 33998.74 33297.58 17897.81 32399.79 9488.16 34499.56 23695.10 31897.21 26298.39 327
USDC97.34 28297.20 28097.75 30699.07 27295.20 32998.51 34399.04 30497.99 13798.31 30399.86 2789.02 33399.55 23895.67 30897.36 25998.49 313
MSLP-MVS++99.46 2699.47 1299.44 12699.60 14299.16 12899.41 17899.71 1398.98 3399.45 12199.78 10199.19 999.54 23999.28 3899.84 6699.63 132
TAMVS99.12 8999.08 7699.24 15499.46 18198.55 19799.51 12899.46 17498.09 12299.45 12199.82 5398.34 9499.51 24098.70 11298.93 18199.67 114
EPNet_dtu98.03 20297.96 19498.23 27498.27 34195.54 32199.23 24398.75 32999.02 2097.82 32299.71 13596.11 16599.48 24193.04 34299.65 12799.69 107
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
test_part197.75 24697.24 27999.29 14699.59 14499.63 6599.65 5999.49 13396.17 29998.44 29499.69 14889.80 32699.47 24298.68 11793.66 33298.78 235
EG-PatchMatch MVS95.97 30995.69 30996.81 33297.78 34992.79 35899.16 25498.93 31396.16 30194.08 35699.22 30082.72 36299.47 24295.67 30897.50 24798.17 337
MVP-Stereo97.81 23797.75 21997.99 29197.53 35196.60 29598.96 30198.85 32497.22 21797.23 33399.36 27195.28 19599.46 24495.51 31099.78 9597.92 352
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
CVMVSNet98.57 15498.67 13298.30 26899.35 20595.59 31899.50 13499.55 6798.60 6899.39 14099.83 4694.48 23199.45 24598.75 10598.56 20199.85 17
test-LLR98.06 19497.90 20198.55 24098.79 30897.10 26598.67 33197.75 35697.34 20498.61 28398.85 33194.45 23299.45 24597.25 25199.38 14399.10 202
TESTMET0.1,197.55 26997.27 27898.40 25998.93 29296.53 29698.67 33197.61 35996.96 24098.64 27999.28 29188.63 33999.45 24597.30 24899.38 14399.21 197
test-mter97.49 27897.13 28398.55 24098.79 30897.10 26598.67 33197.75 35696.65 26198.61 28398.85 33188.23 34399.45 24597.25 25199.38 14399.10 202
mvs_anonymous99.03 10798.99 9199.16 16199.38 20098.52 20399.51 12899.38 22397.79 15699.38 14399.81 6697.30 12899.45 24599.35 2898.99 17899.51 163
tfpnnormal97.84 23097.47 24698.98 17999.20 24499.22 12299.64 6299.61 3696.32 28698.27 30699.70 13993.35 25899.44 25095.69 30695.40 30498.27 332
v7n97.87 22497.52 24098.92 18998.76 31598.58 19599.84 1099.46 17496.20 29698.91 23799.70 13994.89 20999.44 25096.03 29993.89 33098.75 243
jajsoiax98.43 15998.28 16698.88 20198.60 33298.43 21299.82 1499.53 8698.19 10898.63 28099.80 8293.22 26199.44 25099.22 4397.50 24798.77 239
mvs_tets98.40 16498.23 16898.91 19398.67 32598.51 20599.66 5299.53 8698.19 10898.65 27899.81 6692.75 26999.44 25099.31 3597.48 25198.77 239
Vis-MVSNet (Re-imp)98.87 12098.72 12699.31 13999.71 9498.88 16899.80 2099.44 19597.91 14399.36 14899.78 10195.49 18999.43 25497.91 19599.11 16599.62 134
OPU-MVS99.64 8099.56 15299.72 4799.60 7799.70 13999.27 599.42 25598.24 16899.80 8899.79 61
Anonymous2023121197.88 22297.54 23998.90 19599.71 9498.53 19999.48 15099.57 5294.16 33598.81 25299.68 15593.23 25999.42 25598.84 9294.42 32298.76 241
MVS_030496.79 29496.52 29497.59 31299.22 24094.92 33699.04 28299.59 4496.49 27398.43 29598.99 32480.48 36799.39 25797.15 26199.27 15498.47 316
VPNet97.84 23097.44 25499.01 17599.21 24298.94 16299.48 15099.57 5298.38 8699.28 16499.73 13088.89 33599.39 25799.19 4693.27 33798.71 251
nrg03098.64 15198.42 15699.28 14999.05 27799.69 5299.81 1699.46 17498.04 13399.01 22099.82 5396.69 14999.38 25999.34 3294.59 31998.78 235
GA-MVS97.85 22797.47 24699.00 17799.38 20097.99 23198.57 33999.15 29197.04 23498.90 23999.30 28789.83 32599.38 25996.70 28598.33 20899.62 134
UniMVSNet (Re)98.29 17298.00 18999.13 16499.00 28399.36 10599.49 14499.51 10597.95 13998.97 22999.13 31096.30 16199.38 25998.36 16093.34 33598.66 279
FIs98.78 13998.63 13799.23 15699.18 24999.54 8299.83 1399.59 4498.28 9898.79 25699.81 6696.75 14799.37 26299.08 5896.38 27998.78 235
PS-MVSNAJss98.92 11898.92 10198.90 19598.78 31198.53 19999.78 2699.54 7598.07 12799.00 22599.76 11299.01 1999.37 26299.13 5397.23 26198.81 232
CDS-MVSNet99.09 9899.03 8399.25 15299.42 18898.73 18399.45 15999.46 17498.11 11999.46 12099.77 10898.01 11099.37 26298.70 11298.92 18399.66 117
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
MVS-HIRNet95.75 31195.16 31597.51 31599.30 21993.69 35298.88 31295.78 36885.09 36298.78 25792.65 36691.29 30999.37 26294.85 32299.85 5999.46 175
v119297.81 23797.44 25498.91 19398.88 29698.68 18699.51 12899.34 24296.18 29899.20 18699.34 27794.03 24699.36 26695.32 31695.18 30898.69 259
RRT_MVS98.60 15398.44 15499.05 17098.88 29699.14 13399.49 14499.38 22397.76 15999.29 16299.86 2795.38 19199.36 26698.81 10097.16 26598.64 283
EI-MVSNet98.67 14898.67 13298.68 22899.35 20597.97 23299.50 13499.38 22396.93 24599.20 18699.83 4697.87 11299.36 26698.38 15697.56 24198.71 251
MVSTER98.49 15598.32 16399.00 17799.35 20599.02 14699.54 11799.38 22397.41 20099.20 18699.73 13093.86 25199.36 26698.87 8297.56 24198.62 293
gg-mvs-nofinetune96.17 30695.32 31498.73 22398.79 30898.14 22599.38 19594.09 37491.07 35598.07 31591.04 36989.62 33099.35 27096.75 28199.09 16998.68 264
pm-mvs197.68 26097.28 27598.88 20199.06 27498.62 19299.50 13499.45 18696.32 28697.87 32099.79 9492.47 28399.35 27097.54 23293.54 33498.67 271
RRT_test8_iter0597.72 25297.60 23398.08 28299.23 23696.08 31099.63 6499.49 13397.54 18498.94 23399.81 6687.99 34699.35 27099.21 4596.51 27698.81 232
OurMVSNet-221017-097.88 22297.77 21598.19 27698.71 32196.53 29699.88 299.00 30697.79 15698.78 25799.94 391.68 30099.35 27097.21 25396.99 26898.69 259
EGC-MVSNET82.80 33477.86 34097.62 31097.91 34696.12 30899.33 21399.28 2738.40 37725.05 37899.27 29484.11 35999.33 27489.20 35798.22 21497.42 359
pmmvs696.53 29896.09 30197.82 30398.69 32395.47 32399.37 19899.47 16493.46 34397.41 32999.78 10187.06 35299.33 27496.92 27692.70 34498.65 281
V4298.06 19497.79 21098.86 20898.98 28798.84 17399.69 4199.34 24296.53 27199.30 15999.37 26894.67 22399.32 27697.57 22994.66 31798.42 323
lessismore_v097.79 30598.69 32395.44 32594.75 37295.71 35199.87 2488.69 33799.32 27695.89 30194.93 31598.62 293
OpenMVS_ROBcopyleft92.34 2094.38 32493.70 32896.41 33797.38 35393.17 35699.06 27598.75 32986.58 36094.84 35598.26 35081.53 36599.32 27689.01 35897.87 23096.76 360
v897.95 21597.63 23198.93 18798.95 29198.81 17999.80 2099.41 20796.03 31199.10 20499.42 25394.92 20799.30 27996.94 27394.08 32898.66 279
v192192097.80 23997.45 24998.84 21298.80 30798.53 19999.52 12399.34 24296.15 30399.24 17599.47 24193.98 24799.29 28095.40 31395.13 31098.69 259
anonymousdsp98.44 15898.28 16698.94 18598.50 33798.96 15799.77 2899.50 12597.07 23198.87 24499.77 10894.76 21899.28 28198.66 12097.60 23798.57 308
MVSFormer99.17 7799.12 7199.29 14699.51 16098.94 16299.88 299.46 17497.55 18199.80 2799.65 16897.39 12399.28 28199.03 6199.85 5999.65 121
test_djsdf98.67 14898.57 14998.98 17998.70 32298.91 16699.88 299.46 17497.55 18199.22 18099.88 1995.73 18199.28 28199.03 6197.62 23698.75 243
cascas97.69 25897.43 25798.48 24698.60 33297.30 25698.18 35799.39 21792.96 34798.41 29698.78 33693.77 25399.27 28498.16 17698.61 19598.86 229
v14419297.92 21997.60 23398.87 20598.83 30698.65 18999.55 11499.34 24296.20 29699.32 15699.40 26094.36 23499.26 28596.37 29595.03 31298.70 255
v2v48298.06 19497.77 21598.92 18998.90 29498.82 17799.57 9899.36 23396.65 26199.19 18999.35 27494.20 23999.25 28697.72 21494.97 31398.69 259
v124097.69 25897.32 27298.79 21998.85 30498.43 21299.48 15099.36 23396.11 30699.27 16799.36 27193.76 25499.24 28794.46 32695.23 30798.70 255
v114497.98 21197.69 22498.85 21198.87 30098.66 18899.54 11799.35 23896.27 29099.23 17999.35 27494.67 22399.23 28896.73 28395.16 30998.68 264
v1097.85 22797.52 24098.86 20898.99 28498.67 18799.75 3299.41 20795.70 31498.98 22799.41 25794.75 21999.23 28896.01 30094.63 31898.67 271
WR-MVS_H98.13 18797.87 20698.90 19599.02 28198.84 17399.70 3999.59 4497.27 21198.40 29799.19 30495.53 18799.23 28898.34 16193.78 33198.61 302
miper_enhance_ethall98.16 18398.08 18098.41 25798.96 29097.72 24798.45 34599.32 25996.95 24298.97 22999.17 30597.06 13699.22 29197.86 19995.99 28898.29 331
GG-mvs-BLEND98.45 25298.55 33598.16 22399.43 16993.68 37597.23 33398.46 34489.30 33299.22 29195.43 31298.22 21497.98 348
FC-MVSNet-test98.75 14298.62 14299.15 16399.08 27199.45 9799.86 999.60 4198.23 10498.70 26999.82 5396.80 14399.22 29199.07 5996.38 27998.79 234
UniMVSNet_NR-MVSNet98.22 17597.97 19298.96 18298.92 29398.98 15099.48 15099.53 8697.76 15998.71 26399.46 24596.43 15899.22 29198.57 13592.87 34298.69 259
DU-MVS98.08 19397.79 21098.96 18298.87 30098.98 15099.41 17899.45 18697.87 14498.71 26399.50 22994.82 21199.22 29198.57 13592.87 34298.68 264
cl____98.01 20797.84 20898.55 24099.25 23497.97 23298.71 32999.34 24296.47 27998.59 28699.54 21595.65 18599.21 29697.21 25395.77 29498.46 320
WR-MVS98.06 19497.73 22199.06 16898.86 30399.25 11999.19 25199.35 23897.30 20898.66 27299.43 25093.94 24899.21 29698.58 13394.28 32498.71 251
test_040296.64 29696.24 29897.85 29998.85 30496.43 30099.44 16399.26 27593.52 34196.98 34099.52 22288.52 34099.20 29892.58 34897.50 24797.93 351
SixPastTwentyTwo97.50 27597.33 27198.03 28598.65 32696.23 30699.77 2898.68 34097.14 22297.90 31999.93 490.45 31799.18 29997.00 26796.43 27898.67 271
cl2297.85 22797.64 23098.48 24699.09 26997.87 23998.60 33899.33 24997.11 22898.87 24499.22 30092.38 28899.17 30098.21 16995.99 28898.42 323
bset_n11_16_dypcd98.16 18397.97 19298.73 22398.26 34298.28 21997.99 36098.01 35397.68 16899.10 20499.63 18195.68 18399.15 30198.78 10496.55 27498.75 243
IterMVS-SCA-FT97.82 23597.75 21998.06 28499.57 14896.36 30299.02 28699.49 13397.18 21998.71 26399.72 13492.72 27299.14 30297.44 24395.86 29398.67 271
pmmvs597.52 27297.30 27498.16 27898.57 33496.73 28999.27 22998.90 32096.14 30498.37 29999.53 21991.54 30699.14 30297.51 23595.87 29298.63 291
v14897.79 24097.55 23698.50 24398.74 31697.72 24799.54 11799.33 24996.26 29198.90 23999.51 22694.68 22299.14 30297.83 20293.15 33998.63 291
miper_ehance_all_eth98.18 18198.10 17698.41 25799.23 23697.72 24798.72 32899.31 26296.60 26798.88 24299.29 28997.29 12999.13 30597.60 22395.99 28898.38 328
NR-MVSNet97.97 21497.61 23299.02 17498.87 30099.26 11899.47 15599.42 20597.63 17497.08 33899.50 22995.07 20399.13 30597.86 19993.59 33398.68 264
IterMVS97.83 23297.77 21598.02 28799.58 14696.27 30599.02 28699.48 14697.22 21798.71 26399.70 13992.75 26999.13 30597.46 24096.00 28798.67 271
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
CMPMVSbinary69.68 2394.13 32594.90 31791.84 34697.24 35780.01 37198.52 34299.48 14689.01 35791.99 36199.67 16185.67 35699.13 30595.44 31197.03 26796.39 362
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
eth_miper_zixun_eth98.05 19997.96 19498.33 26499.26 23097.38 25598.56 34199.31 26296.65 26198.88 24299.52 22296.58 15199.12 30997.39 24695.53 30298.47 316
pmmvs498.13 18797.90 20198.81 21698.61 33198.87 16998.99 29399.21 28496.44 28099.06 21599.58 20095.90 17599.11 31097.18 25996.11 28598.46 320
TransMVSNet (Re)97.15 28796.58 29298.86 20899.12 26298.85 17299.49 14498.91 31895.48 31697.16 33699.80 8293.38 25799.11 31094.16 33191.73 34798.62 293
ambc93.06 34492.68 36982.36 36898.47 34498.73 33795.09 35397.41 35555.55 37399.10 31296.42 29391.32 34897.71 354
Baseline_NR-MVSNet97.76 24297.45 24998.68 22899.09 26998.29 21799.41 17898.85 32495.65 31598.63 28099.67 16194.82 21199.10 31298.07 18792.89 34198.64 283
CP-MVSNet98.09 19197.78 21399.01 17598.97 28999.24 12099.67 4899.46 17497.25 21398.48 29299.64 17593.79 25299.06 31498.63 12394.10 32798.74 247
PS-CasMVS97.93 21697.59 23598.95 18498.99 28499.06 14399.68 4699.52 9297.13 22398.31 30399.68 15592.44 28799.05 31598.51 14494.08 32898.75 243
K. test v397.10 28996.79 29098.01 28898.72 31996.33 30399.87 697.05 36297.59 17696.16 34799.80 8288.71 33699.04 31696.69 28696.55 27498.65 281
new_pmnet96.38 30296.03 30297.41 31798.13 34595.16 33299.05 27799.20 28593.94 33697.39 33098.79 33491.61 30599.04 31690.43 35395.77 29498.05 342
DIV-MVS_self_test98.01 20797.85 20798.48 24699.24 23597.95 23698.71 32999.35 23896.50 27298.60 28599.54 21595.72 18299.03 31897.21 25395.77 29498.46 320
IterMVS-LS98.46 15798.42 15698.58 23599.59 14498.00 23099.37 19899.43 20396.94 24499.07 21199.59 19797.87 11299.03 31898.32 16495.62 29998.71 251
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
our_test_397.65 26597.68 22597.55 31498.62 32994.97 33498.84 31699.30 26696.83 25198.19 30899.34 27797.01 13899.02 32095.00 32196.01 28698.64 283
Patchmtry97.75 24697.40 26098.81 21699.10 26798.87 16999.11 26899.33 24994.83 32798.81 25299.38 26594.33 23599.02 32096.10 29795.57 30098.53 310
N_pmnet94.95 31995.83 30792.31 34598.47 33879.33 37299.12 26292.81 37893.87 33797.68 32599.13 31093.87 25099.01 32291.38 35096.19 28398.59 306
CR-MVSNet98.17 18297.93 19998.87 20599.18 24998.49 20799.22 24899.33 24996.96 24099.56 10199.38 26594.33 23599.00 32394.83 32398.58 19899.14 199
c3_l98.12 18998.04 18598.38 26199.30 21997.69 25098.81 31999.33 24996.67 25998.83 25099.34 27797.11 13398.99 32497.58 22595.34 30598.48 314
test0.0.03 197.71 25697.42 25898.56 23898.41 34097.82 24298.78 32298.63 34197.34 20498.05 31698.98 32794.45 23298.98 32595.04 32097.15 26698.89 228
PatchT97.03 29096.44 29598.79 21998.99 28498.34 21699.16 25499.07 30192.13 34999.52 11097.31 35994.54 23098.98 32588.54 36098.73 19499.03 215
GBi-Net97.68 26097.48 24498.29 26999.51 16097.26 26099.43 16999.48 14696.49 27399.07 21199.32 28490.26 31998.98 32597.10 26296.65 27098.62 293
test197.68 26097.48 24498.29 26999.51 16097.26 26099.43 16999.48 14696.49 27399.07 21199.32 28490.26 31998.98 32597.10 26296.65 27098.62 293
FMVSNet398.03 20297.76 21898.84 21299.39 19998.98 15099.40 18699.38 22396.67 25999.07 21199.28 29192.93 26498.98 32597.10 26296.65 27098.56 309
FMVSNet297.72 25297.36 26498.80 21899.51 16098.84 17399.45 15999.42 20596.49 27398.86 24999.29 28990.26 31998.98 32596.44 29296.56 27398.58 307
FMVSNet196.84 29296.36 29698.29 26999.32 21797.26 26099.43 16999.48 14695.11 32198.55 28799.32 28483.95 36098.98 32595.81 30396.26 28298.62 293
ppachtmachnet_test97.49 27897.45 24997.61 31198.62 32995.24 32898.80 32099.46 17496.11 30698.22 30799.62 18796.45 15698.97 33293.77 33395.97 29198.61 302
TranMVSNet+NR-MVSNet97.93 21697.66 22798.76 22298.78 31198.62 19299.65 5999.49 13397.76 15998.49 29199.60 19494.23 23898.97 33298.00 18992.90 34098.70 255
test_method91.10 32991.36 33290.31 34995.85 36373.72 37794.89 36699.25 27768.39 36995.82 35099.02 32280.50 36698.95 33493.64 33594.89 31698.25 334
ADS-MVSNet298.02 20498.07 18397.87 29899.33 21095.19 33099.23 24399.08 29996.24 29399.10 20499.67 16194.11 24398.93 33596.81 27999.05 17299.48 168
ET-MVSNet_ETH3D96.49 29995.64 31099.05 17099.53 15698.82 17798.84 31697.51 36097.63 17484.77 36499.21 30392.09 29198.91 33698.98 6692.21 34699.41 184
miper_lstm_enhance98.00 20997.91 20098.28 27299.34 20997.43 25498.88 31299.36 23396.48 27798.80 25499.55 21095.98 16898.91 33697.27 24995.50 30398.51 312
PEN-MVS97.76 24297.44 25498.72 22598.77 31498.54 19899.78 2699.51 10597.06 23398.29 30599.64 17592.63 27898.89 33898.09 18093.16 33898.72 249
testgi97.65 26597.50 24398.13 28199.36 20496.45 29999.42 17699.48 14697.76 15997.87 32099.45 24691.09 31198.81 33994.53 32598.52 20399.13 201
MIMVSNet97.73 25097.45 24998.57 23699.45 18697.50 25299.02 28698.98 30896.11 30699.41 13399.14 30990.28 31898.74 34095.74 30598.93 18199.47 173
LCM-MVSNet-Re97.83 23298.15 17196.87 33199.30 21992.25 36099.59 8498.26 34797.43 19796.20 34699.13 31096.27 16298.73 34198.17 17598.99 17899.64 128
DTE-MVSNet97.51 27497.19 28198.46 25198.63 32898.13 22699.84 1099.48 14696.68 25897.97 31899.67 16192.92 26598.56 34296.88 27892.60 34598.70 255
PC_three_145298.18 11199.84 1499.70 13999.31 398.52 34398.30 16699.80 8899.81 45
UnsupCasMVSNet_bld93.53 32792.51 33096.58 33697.38 35393.82 34898.24 35499.48 14691.10 35493.10 35996.66 36074.89 36898.37 34494.03 33287.71 35597.56 357
Anonymous2024052196.20 30595.89 30697.13 32497.72 35094.96 33599.79 2599.29 27193.01 34697.20 33599.03 32089.69 32898.36 34591.16 35196.13 28498.07 340
MDA-MVSNet_test_wron95.45 31394.60 31998.01 28898.16 34497.21 26399.11 26899.24 27993.49 34280.73 36998.98 32793.02 26298.18 34694.22 33094.45 32198.64 283
UnsupCasMVSNet_eth96.44 30096.12 30097.40 31898.65 32695.65 31699.36 20299.51 10597.13 22396.04 34998.99 32488.40 34198.17 34796.71 28490.27 35098.40 326
KD-MVS_2432*160094.62 32093.72 32697.31 31997.19 35995.82 31498.34 34999.20 28595.00 32497.57 32698.35 34787.95 34798.10 34892.87 34477.00 36798.01 344
miper_refine_blended94.62 32093.72 32697.31 31997.19 35995.82 31498.34 34999.20 28595.00 32497.57 32698.35 34787.95 34798.10 34892.87 34477.00 36798.01 344
YYNet195.36 31594.51 32197.92 29597.89 34797.10 26599.10 27099.23 28093.26 34580.77 36899.04 31992.81 26898.02 35094.30 32794.18 32698.64 283
EU-MVSNet97.98 21198.03 18697.81 30498.72 31996.65 29399.66 5299.66 2798.09 12298.35 30199.82 5395.25 19998.01 35197.41 24595.30 30698.78 235
Gipumacopyleft90.99 33090.15 33393.51 34298.73 31790.12 36593.98 36799.45 18679.32 36592.28 36094.91 36369.61 36997.98 35287.42 36395.67 29892.45 366
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
pmmvs-eth3d95.34 31694.73 31897.15 32295.53 36695.94 31299.35 20899.10 29695.13 31993.55 35797.54 35488.15 34597.91 35394.58 32489.69 35397.61 355
PM-MVS92.96 32892.23 33195.14 34195.61 36489.98 36699.37 19898.21 34994.80 32895.04 35497.69 35365.06 37097.90 35494.30 32789.98 35297.54 358
MDA-MVSNet-bldmvs94.96 31893.98 32497.92 29598.24 34397.27 25899.15 25899.33 24993.80 33880.09 37099.03 32088.31 34297.86 35593.49 33794.36 32398.62 293
Patchmatch-RL test95.84 31095.81 30895.95 33995.61 36490.57 36498.24 35498.39 34695.10 32395.20 35298.67 33994.78 21497.77 35696.28 29690.02 35199.51 163
Anonymous2023120696.22 30396.03 30296.79 33397.31 35694.14 34699.63 6499.08 29996.17 29997.04 33999.06 31793.94 24897.76 35786.96 36595.06 31198.47 316
SD-MVS99.41 4699.52 799.05 17099.74 7599.68 5499.46 15899.52 9299.11 1199.88 599.91 899.43 197.70 35898.72 11099.93 1199.77 71
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
DSMNet-mixed97.25 28597.35 26696.95 32997.84 34893.61 35499.57 9896.63 36696.13 30598.87 24498.61 34294.59 22697.70 35895.08 31998.86 18799.55 149
pmmvs394.09 32693.25 32996.60 33594.76 36894.49 34198.92 30898.18 35189.66 35696.48 34498.06 35286.28 35397.33 36089.68 35687.20 35697.97 349
KD-MVS_self_test95.00 31794.34 32296.96 32897.07 36195.39 32699.56 10599.44 19595.11 32197.13 33797.32 35891.86 29597.27 36190.35 35481.23 36498.23 336
FMVSNet596.43 30196.19 29997.15 32299.11 26495.89 31399.32 21499.52 9294.47 33498.34 30299.07 31587.54 35197.07 36292.61 34795.72 29798.47 316
new-patchmatchnet94.48 32394.08 32395.67 34095.08 36792.41 35999.18 25299.28 27394.55 33393.49 35897.37 35787.86 34997.01 36391.57 34988.36 35497.61 355
LCM-MVSNet86.80 33285.22 33691.53 34787.81 37480.96 37098.23 35698.99 30771.05 36790.13 36396.51 36148.45 37696.88 36490.51 35285.30 35896.76 360
CL-MVSNet_self_test94.49 32293.97 32596.08 33896.16 36293.67 35398.33 35199.38 22395.13 31997.33 33198.15 35192.69 27696.57 36588.67 35979.87 36597.99 347
MIMVSNet195.51 31295.04 31696.92 33097.38 35395.60 31799.52 12399.50 12593.65 34096.97 34199.17 30585.28 35796.56 36688.36 36195.55 30198.60 305
test20.0396.12 30795.96 30496.63 33497.44 35295.45 32499.51 12899.38 22396.55 27096.16 34799.25 29793.76 25496.17 36787.35 36494.22 32598.27 332
tmp_tt82.80 33481.52 33786.66 35066.61 38068.44 37892.79 36997.92 35468.96 36880.04 37199.85 3385.77 35596.15 36897.86 19943.89 37395.39 364
PMMVS286.87 33185.37 33591.35 34890.21 37283.80 36798.89 31197.45 36183.13 36491.67 36295.03 36248.49 37594.70 36985.86 36777.62 36695.54 363
PMVScopyleft70.75 2275.98 34074.97 34179.01 35670.98 37955.18 38093.37 36898.21 34965.08 37361.78 37493.83 36521.74 38192.53 37078.59 36991.12 34989.34 369
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
FPMVS84.93 33385.65 33482.75 35486.77 37563.39 37998.35 34898.92 31574.11 36683.39 36698.98 32750.85 37492.40 37184.54 36894.97 31392.46 365
MVEpermissive76.82 2176.91 33974.31 34384.70 35185.38 37776.05 37696.88 36593.17 37667.39 37071.28 37289.01 37121.66 38287.69 37271.74 37172.29 36990.35 368
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
E-PMN80.61 33679.88 33882.81 35390.75 37176.38 37597.69 36295.76 36966.44 37183.52 36592.25 36762.54 37287.16 37368.53 37261.40 37084.89 371
EMVS80.02 33779.22 33982.43 35591.19 37076.40 37497.55 36492.49 37966.36 37283.01 36791.27 36864.63 37185.79 37465.82 37360.65 37185.08 370
ANet_high77.30 33874.86 34284.62 35275.88 37877.61 37397.63 36393.15 37788.81 35864.27 37389.29 37036.51 37783.93 37575.89 37052.31 37292.33 367
wuyk23d40.18 34141.29 34636.84 35786.18 37649.12 38179.73 37022.81 38227.64 37425.46 37728.45 37721.98 38048.89 37655.80 37423.56 37612.51 374
test12339.01 34342.50 34528.53 35839.17 38120.91 38298.75 32519.17 38319.83 37638.57 37566.67 37333.16 37815.42 37737.50 37629.66 37549.26 372
testmvs39.17 34243.78 34425.37 35936.04 38216.84 38398.36 34726.56 38120.06 37538.51 37667.32 37229.64 37915.30 37837.59 37539.90 37443.98 373
test_blank0.13 3470.17 3500.00 3600.00 3830.00 3840.00 3710.00 3840.00 3780.00 3791.57 3780.00 3830.00 3790.00 3770.00 3770.00 375
uanet_test0.02 3480.03 3510.00 3600.00 3830.00 3840.00 3710.00 3840.00 3780.00 3790.27 3790.00 3830.00 3790.00 3770.00 3770.00 375
cdsmvs_eth3d_5k24.64 34432.85 3470.00 3600.00 3830.00 3840.00 37199.51 1050.00 3780.00 37999.56 20796.58 1510.00 3790.00 3770.00 3770.00 375
pcd_1.5k_mvsjas8.27 34611.03 3490.00 3600.00 3830.00 3840.00 3710.00 3840.00 3780.00 3790.27 37999.01 190.00 3790.00 3770.00 3770.00 375
sosnet-low-res0.02 3480.03 3510.00 3600.00 3830.00 3840.00 3710.00 3840.00 3780.00 3790.27 3790.00 3830.00 3790.00 3770.00 3770.00 375
sosnet0.02 3480.03 3510.00 3600.00 3830.00 3840.00 3710.00 3840.00 3780.00 3790.27 3790.00 3830.00 3790.00 3770.00 3770.00 375
uncertanet0.02 3480.03 3510.00 3600.00 3830.00 3840.00 3710.00 3840.00 3780.00 3790.27 3790.00 3830.00 3790.00 3770.00 3770.00 375
Regformer0.02 3480.03 3510.00 3600.00 3830.00 3840.00 3710.00 3840.00 3780.00 3790.27 3790.00 3830.00 3790.00 3770.00 3770.00 375
ab-mvs-re8.30 34511.06 3480.00 3600.00 3830.00 3840.00 3710.00 3840.00 3780.00 37999.58 2000.00 3830.00 3790.00 3770.00 3770.00 375
uanet0.02 3480.03 3510.00 3600.00 3830.00 3840.00 3710.00 3840.00 3780.00 3790.27 3790.00 3830.00 3790.00 3770.00 3770.00 375
FOURS199.91 199.93 199.87 699.56 5899.10 1299.81 24
test_one_060199.81 4199.88 899.49 13398.97 3699.65 7899.81 6699.09 14
eth-test20.00 383
eth-test0.00 383
RE-MVS-def99.34 3199.76 5699.82 2399.63 6499.52 9298.38 8699.76 4399.82 5398.75 6098.61 12799.81 8499.77 71
IU-MVS99.84 3399.88 899.32 25998.30 9799.84 1498.86 8799.85 5999.89 2
save fliter99.76 5699.59 7399.14 26099.40 21399.00 27
test072699.85 2699.89 499.62 7099.50 12599.10 1299.86 1299.82 5398.94 35
GSMVS99.52 157
test_part299.81 4199.83 1799.77 36
sam_mvs194.86 21099.52 157
sam_mvs94.72 221
MTGPAbinary99.47 164
MTMP99.54 11798.88 322
test9_res97.49 23699.72 11199.75 77
agg_prior297.21 25399.73 11099.75 77
test_prior499.56 7898.99 293
test_prior298.96 30198.34 9299.01 22099.52 22298.68 6897.96 19199.74 107
新几何299.01 291
旧先验199.74 7599.59 7399.54 7599.69 14898.47 8399.68 12299.73 89
原ACMM298.95 305
test22299.75 6799.49 9198.91 31099.49 13396.42 28299.34 15499.65 16898.28 9899.69 11799.72 95
segment_acmp98.96 29
testdata198.85 31598.32 96
plane_prior799.29 22397.03 275
plane_prior699.27 22896.98 27992.71 274
plane_prior499.61 191
plane_prior397.00 27798.69 6399.11 201
plane_prior299.39 19098.97 36
plane_prior199.26 230
plane_prior96.97 28099.21 25098.45 8097.60 237
n20.00 384
nn0.00 384
door-mid98.05 352
test1199.35 238
door97.92 354
HQP5-MVS96.83 285
HQP-NCC99.19 24698.98 29798.24 10198.66 272
ACMP_Plane99.19 24698.98 29798.24 10198.66 272
BP-MVS97.19 257
HQP3-MVS99.39 21797.58 239
HQP2-MVS92.47 283
NP-MVS99.23 23696.92 28399.40 260
MDTV_nov1_ep13_2view95.18 33199.35 20896.84 24999.58 9895.19 20197.82 20399.46 175
ACMMP++_ref97.19 263
ACMMP++97.43 255
Test By Simon98.75 60