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 bysorted bysort bysort bysort bysort bysort bysort by
EI-MVSNet-UG-set99.58 399.57 199.64 6599.78 3799.14 10399.60 9499.45 15599.01 1399.90 199.83 4098.98 1999.93 5799.59 299.95 699.86 6
EI-MVSNet-Vis-set99.58 399.56 399.64 6599.78 3799.15 10299.61 9199.45 15599.01 1399.89 299.82 4799.01 1299.92 6699.56 599.95 699.85 9
ESAPD99.46 2199.32 2699.91 299.78 3799.88 299.36 20599.51 8798.73 4499.88 399.84 3698.72 4899.96 1998.16 14399.87 3999.88 4
Regformer-499.59 299.54 499.73 4899.76 4699.41 7499.58 10499.49 10799.02 1099.88 399.80 6899.00 1899.94 4299.45 1599.92 1299.84 13
SD-MVS99.41 3499.52 699.05 15799.74 6999.68 3499.46 16499.52 7899.11 799.88 399.91 599.43 197.70 34298.72 8899.93 1199.77 52
APDe-MVS99.66 199.57 199.92 199.77 4399.89 199.75 3599.56 5099.02 1099.88 399.85 2799.18 599.96 1999.22 3499.92 1299.90 1
Regformer-399.57 699.53 599.68 5399.76 4699.29 8699.58 10499.44 16499.01 1399.87 799.80 6898.97 2099.91 7699.44 1699.92 1299.83 24
Vis-MVSNetpermissive99.12 7198.97 7699.56 7899.78 3799.10 10699.68 5799.66 2698.49 5799.86 899.87 2094.77 19399.84 12699.19 3699.41 11399.74 61
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
xiu_mvs_v1_base_debu99.29 4999.27 4299.34 11399.63 11498.97 13199.12 26299.51 8798.86 3199.84 999.47 21298.18 7799.99 199.50 899.31 11999.08 179
xiu_mvs_v1_base99.29 4999.27 4299.34 11399.63 11498.97 13199.12 26299.51 8798.86 3199.84 999.47 21298.18 7799.99 199.50 899.31 11999.08 179
xiu_mvs_v1_base_debi99.29 4999.27 4299.34 11399.63 11498.97 13199.12 26299.51 8798.86 3199.84 999.47 21298.18 7799.99 199.50 899.31 11999.08 179
Regformer-199.53 999.47 899.72 5099.71 8499.44 7199.49 15199.46 14398.95 2499.83 1299.76 9199.01 1299.93 5799.17 3999.87 3999.80 42
Regformer-299.54 799.47 899.75 4199.71 8499.52 6299.49 15199.49 10798.94 2699.83 1299.76 9199.01 1299.94 4299.15 4299.87 3999.80 42
DeepPCF-MVS98.18 398.81 11899.37 1797.12 31599.60 12591.75 34398.61 33299.44 16499.35 199.83 1299.85 2798.70 5099.81 14899.02 5299.91 1799.81 35
TSAR-MVS + GP.99.36 4199.36 1999.36 11199.67 9698.61 19199.07 27399.33 22299.00 1799.82 1599.81 5799.06 999.84 12699.09 4699.42 11299.65 93
abl_699.44 2699.31 3299.83 2599.85 2499.75 2599.66 6899.59 3998.13 8599.82 1599.81 5798.60 5699.96 1998.46 12399.88 3599.79 46
MVSFormer99.17 6299.12 5699.29 12699.51 14098.94 13999.88 199.46 14397.55 15699.80 1799.65 13997.39 9799.28 26399.03 5099.85 5599.65 93
lupinMVS99.13 6699.01 7199.46 10199.51 14098.94 13999.05 27999.16 26097.86 12199.80 1799.56 17497.39 9799.86 11398.94 5999.85 5599.58 116
tttt051798.42 14198.14 14999.28 12899.66 10698.38 21299.74 4096.85 35797.68 14599.79 1999.74 10191.39 29699.89 9798.83 7599.56 10599.57 117
APD-MVS_3200maxsize99.48 1799.35 2299.85 1899.76 4699.83 899.63 8299.54 6498.36 6699.79 1999.82 4798.86 3099.95 3498.62 9999.81 6999.78 50
jason99.13 6699.03 6799.45 10299.46 15698.87 14799.12 26299.26 24998.03 10499.79 1999.65 13997.02 10999.85 12099.02 5299.90 2499.65 93
jason: jason.
SteuartSystems-ACMMP99.54 799.42 1199.87 799.82 3099.81 1499.59 9799.51 8798.62 5099.79 1999.83 4099.28 399.97 1198.48 12099.90 2499.84 13
Skip Steuart: Steuart Systems R&D Blog.
DeepC-MVS_fast98.69 199.49 1399.39 1599.77 3899.63 11499.59 5099.36 20599.46 14399.07 999.79 1999.82 4798.85 3199.92 6698.68 9399.87 3999.82 31
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
SMA-MVS99.44 2699.30 3499.85 1899.73 7499.83 899.56 11799.47 13397.45 16799.78 2499.82 4799.18 599.91 7698.79 8099.89 3299.81 35
TSAR-MVS + MP.99.58 399.50 799.81 3099.91 199.66 3899.63 8299.39 18798.91 2999.78 2499.85 2799.36 299.94 4298.84 7299.88 3599.82 31
test_part299.81 3399.83 899.77 26
v1.041.40 34255.20 3430.00 35999.81 330.00 3740.00 36599.48 11797.97 11299.77 2699.78 820.00 3760.00 3710.00 3680.00 3690.00 369
HSP-MVS99.41 3499.26 4599.85 1899.89 899.80 1599.67 5999.37 20198.70 4699.77 2699.49 20298.21 7699.95 3498.46 12399.77 7799.81 35
UA-Net99.42 3199.29 3899.80 3299.62 11999.55 5599.50 14199.70 1598.79 4099.77 2699.96 197.45 9699.96 1998.92 6099.90 2499.89 2
APD-MVScopyleft99.27 5299.08 6099.84 2499.75 5899.79 1999.50 14199.50 10297.16 19399.77 2699.82 4798.78 3799.94 4297.56 19799.86 5099.80 42
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
ACMMP_Plus99.47 2099.34 2499.88 599.87 1599.86 499.47 16199.48 11798.05 10199.76 3199.86 2398.82 3399.93 5798.82 7999.91 1799.84 13
HPM-MVS_fast99.51 1299.40 1499.85 1899.91 199.79 1999.76 2799.56 5097.72 14099.76 3199.75 9699.13 799.92 6699.07 4899.92 1299.85 9
VNet99.11 7698.90 8699.73 4899.52 13899.56 5399.41 18599.39 18799.01 1399.74 3399.78 8295.56 14999.92 6699.52 798.18 19499.72 72
thisisatest053098.35 14798.03 16099.31 11999.63 11498.56 19399.54 12696.75 35997.53 16099.73 3499.65 13991.25 29999.89 9798.62 9999.56 10599.48 138
xiu_mvs_v2_base99.26 5499.25 4699.29 12699.53 13698.91 14499.02 28899.45 15598.80 3999.71 3599.26 26998.94 2599.98 599.34 2399.23 12398.98 192
PS-MVSNAJ99.32 4599.32 2699.30 12399.57 13098.94 13998.97 30199.46 14398.92 2899.71 3599.24 27199.01 1299.98 599.35 1999.66 9898.97 193
PGM-MVS99.45 2399.31 3299.86 1399.87 1599.78 2499.58 10499.65 3197.84 12699.71 3599.80 6899.12 899.97 1198.33 13499.87 3999.83 24
114514_t98.93 10198.67 11499.72 5099.85 2499.53 5999.62 8599.59 3992.65 33499.71 3599.78 8298.06 8199.90 8998.84 7299.91 1799.74 61
PVSNet_Blended_VisFu99.36 4199.28 4099.61 6999.86 2099.07 11199.47 16199.93 297.66 14999.71 3599.86 2397.73 8999.96 1999.47 1399.82 6899.79 46
tfpn100098.33 14898.02 16299.25 13599.78 3798.73 17699.70 4597.55 35397.48 16399.69 4099.53 18792.37 27399.85 12097.82 17098.26 18999.16 170
zzz-MVS99.49 1399.36 1999.89 399.90 399.86 499.36 20599.47 13398.79 4099.68 4199.81 5798.43 6499.97 1198.88 6299.90 2499.83 24
MTAPA99.52 1199.39 1599.89 399.90 399.86 499.66 6899.47 13398.79 4099.68 4199.81 5798.43 6499.97 1198.88 6299.90 2499.83 24
HFP-MVS99.49 1399.37 1799.86 1399.87 1599.80 1599.66 6899.67 2298.15 8399.68 4199.69 12299.06 999.96 1998.69 9199.87 3999.84 13
#test#99.43 2999.29 3899.86 1399.87 1599.80 1599.55 12399.67 2297.83 12799.68 4199.69 12299.06 999.96 1998.39 12699.87 3999.84 13
VDDNet97.55 25697.02 27299.16 14599.49 14998.12 22399.38 19999.30 23195.35 29499.68 4199.90 782.62 35399.93 5799.31 2698.13 20299.42 154
HPM-MVScopyleft99.42 3199.28 4099.83 2599.90 399.72 2999.81 1599.54 6497.59 15199.68 4199.63 15198.91 2799.94 4298.58 10799.91 1799.84 13
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
VDD-MVS97.73 23997.35 25398.88 19699.47 15497.12 25699.34 21398.85 29798.19 7999.67 4799.85 2782.98 35199.92 6699.49 1298.32 18399.60 108
ACMMPR99.49 1399.36 1999.86 1399.87 1599.79 1999.66 6899.67 2298.15 8399.67 4799.69 12298.95 2499.96 1998.69 9199.87 3999.84 13
PVSNet_BlendedMVS98.86 10798.80 10199.03 15899.76 4698.79 17099.28 22699.91 397.42 17299.67 4799.37 24097.53 9399.88 10698.98 5597.29 24798.42 308
PVSNet_Blended99.08 8398.97 7699.42 10899.76 4698.79 17098.78 32199.91 396.74 22899.67 4799.49 20297.53 9399.88 10698.98 5599.85 5599.60 108
sss99.17 6299.05 6299.53 8599.62 11998.97 13199.36 20599.62 3297.83 12799.67 4799.65 13997.37 10099.95 3499.19 3699.19 12699.68 85
region2R99.48 1799.35 2299.87 799.88 1199.80 1599.65 7899.66 2698.13 8599.66 5299.68 12798.96 2199.96 1998.62 9999.87 3999.84 13
RPSCF98.22 15998.62 12496.99 31699.82 3091.58 34499.72 4299.44 16496.61 23799.66 5299.89 1095.92 14099.82 14497.46 20899.10 13299.57 117
OMC-MVS99.08 8399.04 6599.20 14299.67 9698.22 21799.28 22699.52 7898.07 9699.66 5299.81 5797.79 8799.78 16397.79 17399.81 6999.60 108
LFMVS97.90 21097.35 25399.54 7999.52 13899.01 12499.39 19498.24 33497.10 20199.65 5599.79 7684.79 34799.91 7699.28 2898.38 17899.69 81
MVS_111021_LR99.41 3499.33 2599.65 6099.77 4399.51 6498.94 30999.85 698.82 3599.65 5599.74 10198.51 5999.80 15298.83 7599.89 3299.64 99
GST-MVS99.40 3899.24 4799.85 1899.86 2099.79 1999.60 9499.67 2297.97 11299.63 5799.68 12798.52 5899.95 3498.38 12899.86 5099.81 35
CPTT-MVS99.11 7698.90 8699.74 4699.80 3599.46 6999.59 9799.49 10797.03 21299.63 5799.69 12297.27 10299.96 1997.82 17099.84 6099.81 35
ACMMPcopyleft99.45 2399.32 2699.82 2799.89 899.67 3699.62 8599.69 1898.12 8799.63 5799.84 3698.73 4799.96 1998.55 11599.83 6499.81 35
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-MVS98.35 299.30 4799.19 5099.64 6599.82 3099.23 9399.62 8599.55 5798.94 2699.63 5799.95 295.82 14499.94 4299.37 1899.97 399.73 66
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
CHOSEN 280x42099.12 7199.13 5599.08 15399.66 10697.89 23198.43 34099.71 1398.88 3099.62 6199.76 9196.63 12299.70 19599.46 1499.99 199.66 89
PHI-MVS99.30 4799.17 5299.70 5299.56 13499.52 6299.58 10499.80 897.12 19799.62 6199.73 10798.58 5799.90 8998.61 10299.91 1799.68 85
0601test98.86 10798.63 11999.54 7999.49 14999.18 9799.50 14199.07 27198.22 7799.61 6399.51 19595.37 15499.84 12698.60 10498.33 17999.59 112
Anonymous2024052198.86 10798.63 11999.54 7999.49 14999.18 9799.50 14199.07 27198.22 7799.61 6399.51 19595.37 15499.84 12698.60 10498.33 17999.59 112
tfpn_ndepth98.17 16697.84 18499.15 14799.75 5898.76 17499.61 9197.39 35596.92 22099.61 6399.38 23692.19 27599.86 11397.57 19598.13 20298.82 210
MG-MVS99.13 6699.02 7099.45 10299.57 13098.63 18699.07 27399.34 21498.99 1899.61 6399.82 4797.98 8399.87 10997.00 23399.80 7199.85 9
MP-MVS-pluss99.37 4099.20 4999.88 599.90 399.87 399.30 22099.52 7897.18 19199.60 6799.79 7698.79 3699.95 3498.83 7599.91 1799.83 24
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
CDPH-MVS99.13 6698.91 8599.80 3299.75 5899.71 3099.15 25899.41 17796.60 23999.60 6799.55 17798.83 3299.90 8997.48 20599.83 6499.78 50
EPP-MVSNet99.13 6698.99 7399.53 8599.65 11099.06 11299.81 1599.33 22297.43 16999.60 6799.88 1597.14 10599.84 12699.13 4398.94 14699.69 81
HyFIR lowres test99.11 7698.92 8399.65 6099.90 399.37 7799.02 28899.91 397.67 14799.59 7099.75 9695.90 14199.73 17999.53 699.02 13899.86 6
MVS_030499.06 8598.86 9499.66 5699.51 14099.36 7899.22 24699.51 8798.95 2499.58 7199.65 13993.74 23599.98 599.66 199.95 699.64 99
MVS_Test99.10 7998.97 7699.48 9499.49 14999.14 10399.67 5999.34 21497.31 18099.58 7199.76 9197.65 9299.82 14498.87 6699.07 13599.46 147
MDTV_nov1_ep13_2view95.18 31699.35 21096.84 22499.58 7195.19 16597.82 17099.46 147
DELS-MVS99.48 1799.42 1199.65 6099.72 7899.40 7699.05 27999.66 2699.14 699.57 7499.80 6898.46 6299.94 4299.57 499.84 6099.60 108
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
CR-MVSNet98.17 16697.93 17198.87 20099.18 21598.49 20499.22 24699.33 22296.96 21599.56 7599.38 23694.33 21299.00 30394.83 29698.58 16799.14 171
RPMNet96.61 28395.85 29198.87 20099.18 21598.49 20499.22 24699.08 26888.72 35099.56 7597.38 34594.08 22399.00 30386.87 34898.58 16799.14 171
IS-MVSNet99.05 8798.87 9099.57 7699.73 7499.32 8299.75 3599.20 25698.02 10599.56 7599.86 2396.54 12499.67 20098.09 14799.13 12999.73 66
conf0.0198.21 16297.89 17699.15 14799.76 4699.04 11499.67 5997.71 34597.10 20199.55 7899.54 18092.70 25599.79 15596.90 24398.12 20498.61 287
conf0.00298.21 16297.89 17699.15 14799.76 4699.04 11499.67 5997.71 34597.10 20199.55 7899.54 18092.70 25599.79 15596.90 24398.12 20498.61 287
thresconf0.0298.24 15597.89 17699.27 13099.76 4699.04 11499.67 5997.71 34597.10 20199.55 7899.54 18092.70 25599.79 15596.90 24398.12 20498.97 193
tfpn_n40098.24 15597.89 17699.27 13099.76 4699.04 11499.67 5997.71 34597.10 20199.55 7899.54 18092.70 25599.79 15596.90 24398.12 20498.97 193
tfpnconf98.24 15597.89 17699.27 13099.76 4699.04 11499.67 5997.71 34597.10 20199.55 7899.54 18092.70 25599.79 15596.90 24398.12 20498.97 193
tfpnview1198.24 15597.89 17699.27 13099.76 4699.04 11499.67 5997.71 34597.10 20199.55 7899.54 18092.70 25599.79 15596.90 24398.12 20498.97 193
thisisatest051598.14 17097.79 18999.19 14399.50 14898.50 20398.61 33296.82 35896.95 21799.54 8499.43 22191.66 29299.86 11398.08 15199.51 10999.22 167
MVS_111021_HR99.41 3499.32 2699.66 5699.72 7899.47 6898.95 30799.85 698.82 3599.54 8499.73 10798.51 5999.74 17298.91 6199.88 3599.77 52
CP-MVS99.45 2399.32 2699.85 1899.83 2999.75 2599.69 4899.52 7898.07 9699.53 8699.63 15198.93 2699.97 1198.74 8499.91 1799.83 24
WTY-MVS99.06 8598.88 8999.61 6999.62 11999.16 9999.37 20199.56 5098.04 10299.53 8699.62 15696.84 11499.94 4298.85 7198.49 17499.72 72
MCST-MVS99.43 2999.30 3499.82 2799.79 3699.74 2899.29 22499.40 18498.79 4099.52 8899.62 15698.91 2799.90 8998.64 9699.75 8099.82 31
casdiffmvs199.23 5799.11 5899.58 7499.53 13699.36 7899.76 2799.43 17297.99 11099.52 8899.84 3697.50 9599.77 16599.42 1798.97 14399.61 107
PatchT97.03 28096.44 28198.79 21498.99 24998.34 21399.16 25599.07 27192.13 33599.52 8897.31 34794.54 20598.98 30588.54 34198.73 16399.03 186
CANet99.25 5599.14 5499.59 7199.41 16699.16 9999.35 21099.57 4598.82 3599.51 9199.61 16096.46 12599.95 3499.59 299.98 299.65 93
mPP-MVS99.44 2699.30 3499.86 1399.88 1199.79 1999.69 4899.48 11798.12 8799.50 9299.75 9698.78 3799.97 1198.57 10999.89 3299.83 24
PatchMatch-RL98.84 11798.62 12499.52 8999.71 8499.28 8799.06 27799.77 997.74 13899.50 9299.53 18795.41 15399.84 12697.17 22599.64 10199.44 151
PVSNet96.02 1798.85 11598.84 9798.89 18999.73 7497.28 24998.32 34499.60 3697.86 12199.50 9299.57 17296.75 11999.86 11398.56 11299.70 9299.54 121
LS3D99.27 5299.12 5699.74 4699.18 21599.75 2599.56 11799.57 4598.45 6099.49 9599.85 2797.77 8899.94 4298.33 13499.84 6099.52 127
MP-MVScopyleft99.33 4499.15 5399.87 799.88 1199.82 1399.66 6899.46 14398.09 9299.48 9699.74 10198.29 7399.96 1997.93 16299.87 3999.82 31
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
旧先验298.96 30396.70 23199.47 9799.94 4298.19 140
MSDG98.98 9798.80 10199.53 8599.76 4699.19 9598.75 32499.55 5797.25 18599.47 9799.77 8897.82 8699.87 10996.93 24099.90 2499.54 121
CDS-MVSNet99.09 8099.03 6799.25 13599.42 16398.73 17699.45 16599.46 14398.11 8999.46 9999.77 8898.01 8299.37 24098.70 8998.92 14999.66 89
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
MSLP-MVS++99.46 2199.47 899.44 10599.60 12599.16 9999.41 18599.71 1398.98 1999.45 10099.78 8299.19 499.54 22099.28 2899.84 6099.63 103
XVG-OURS98.73 12698.68 11398.88 19699.70 9097.73 24498.92 31099.55 5798.52 5699.45 10099.84 3695.27 15999.91 7698.08 15198.84 15699.00 189
tpmrst98.33 14898.48 13397.90 29199.16 22294.78 32199.31 21899.11 26597.27 18399.45 10099.59 16595.33 15699.84 12698.48 12098.61 16499.09 178
TAMVS99.12 7199.08 6099.24 13899.46 15698.55 19499.51 13699.46 14398.09 9299.45 10099.82 4798.34 7199.51 22198.70 8998.93 14799.67 88
CANet_DTU98.97 9998.87 9099.25 13599.33 18398.42 21199.08 27299.30 23199.16 599.43 10499.75 9695.27 15999.97 1198.56 11299.95 699.36 158
Patchmatch-test198.16 16898.14 14998.22 27199.30 19295.55 30499.07 27398.97 28297.57 15499.43 10499.60 16392.72 25299.60 21497.38 21399.20 12599.50 135
testdata99.54 7999.75 5898.95 13699.51 8797.07 20899.43 10499.70 11698.87 2999.94 4297.76 17799.64 10199.72 72
XVG-OURS-SEG-HR98.69 12898.62 12498.89 18999.71 8497.74 24399.12 26299.54 6498.44 6399.42 10799.71 11394.20 21699.92 6698.54 11798.90 15199.00 189
DP-MVS Recon99.12 7198.95 8199.65 6099.74 6999.70 3299.27 22999.57 4596.40 25799.42 10799.68 12798.75 4599.80 15297.98 15899.72 8699.44 151
Effi-MVS+-dtu98.78 12298.89 8898.47 24399.33 18396.91 27499.57 11099.30 23198.47 5899.41 10998.99 29196.78 11699.74 17298.73 8699.38 11498.74 224
MIMVSNet97.73 23997.45 23598.57 23299.45 16097.50 24799.02 28898.98 28196.11 28099.41 10999.14 27890.28 30698.74 31895.74 27798.93 14799.47 143
CSCG99.32 4599.32 2699.32 11899.85 2498.29 21499.71 4499.66 2698.11 8999.41 10999.80 6898.37 7099.96 1998.99 5499.96 599.72 72
F-COLMAP99.19 5999.04 6599.64 6599.78 3799.27 8999.42 18199.54 6497.29 18299.41 10999.59 16598.42 6799.93 5798.19 14099.69 9399.73 66
MDTV_nov1_ep1398.32 14199.11 23094.44 32599.27 22998.74 30997.51 16199.40 11399.62 15694.78 18999.76 17097.59 19298.81 160
CVMVSNet98.57 13598.67 11498.30 25899.35 17995.59 30399.50 14199.55 5798.60 5299.39 11499.83 4094.48 20799.45 22598.75 8398.56 17099.85 9
CNVR-MVS99.42 3199.30 3499.78 3699.62 11999.71 3099.26 23799.52 7898.82 3599.39 11499.71 11398.96 2199.85 12098.59 10699.80 7199.77 52
Effi-MVS+98.81 11898.59 12999.48 9499.46 15699.12 10598.08 35099.50 10297.50 16299.38 11699.41 22796.37 12999.81 14899.11 4598.54 17199.51 132
mvs_anonymous99.03 9098.99 7399.16 14599.38 17498.52 20099.51 13699.38 19397.79 13299.38 11699.81 5797.30 10199.45 22599.35 1998.99 14099.51 132
XVS99.53 999.42 1199.87 799.85 2499.83 899.69 4899.68 1998.98 1999.37 11899.74 10198.81 3499.94 4298.79 8099.86 5099.84 13
X-MVStestdata96.55 28495.45 30599.87 799.85 2499.83 899.69 4899.68 1998.98 1999.37 11864.01 36998.81 3499.94 4298.79 8099.86 5099.84 13
PatchmatchNetpermissive98.31 15098.36 13798.19 27499.16 22295.32 31199.27 22998.92 28897.37 17699.37 11899.58 16894.90 18199.70 19597.43 21199.21 12499.54 121
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
AllTest98.87 10498.72 10899.31 11999.86 2098.48 20699.56 11799.61 3397.85 12499.36 12199.85 2795.95 13799.85 12096.66 25999.83 6499.59 112
TestCases99.31 11999.86 2098.48 20699.61 3397.85 12499.36 12199.85 2795.95 13799.85 12096.66 25999.83 6499.59 112
diffmvs199.12 7199.00 7299.48 9499.51 14099.10 10699.61 9199.49 10797.67 14799.36 12199.74 10197.67 9199.88 10698.95 5798.99 14099.47 143
Vis-MVSNet (Re-imp)98.87 10498.72 10899.31 11999.71 8498.88 14699.80 1999.44 16497.91 11999.36 12199.78 8295.49 15299.43 23497.91 16399.11 13099.62 105
alignmvs98.81 11898.56 13199.58 7499.43 16299.42 7399.51 13698.96 28498.61 5199.35 12598.92 29794.78 18999.77 16599.35 1998.11 21099.54 121
VPA-MVSNet98.29 15297.95 16999.30 12399.16 22299.54 5699.50 14199.58 4498.27 7299.35 12599.37 24092.53 26699.65 20499.35 1994.46 30498.72 226
AdaColmapbinary99.01 9498.80 10199.66 5699.56 13499.54 5699.18 25399.70 1598.18 8299.35 12599.63 15196.32 13099.90 8997.48 20599.77 7799.55 119
test22299.75 5899.49 6598.91 31299.49 10796.42 25499.34 12899.65 13998.28 7499.69 9399.72 72
API-MVS99.04 8899.03 6799.06 15599.40 17199.31 8599.55 12399.56 5098.54 5499.33 12999.39 23598.76 4299.78 16396.98 23599.78 7598.07 320
v14419297.92 20897.60 21898.87 20098.83 28798.65 18499.55 12399.34 21496.20 27199.32 13099.40 23194.36 21199.26 27196.37 26895.03 29098.70 232
casdiffmvs99.09 8098.97 7699.47 9899.47 15499.10 10699.74 4099.38 19397.86 12199.32 13099.79 7697.08 10899.77 16599.24 3298.82 15799.54 121
canonicalmvs99.02 9198.86 9499.51 9199.42 16399.32 8299.80 1999.48 11798.63 4999.31 13298.81 30697.09 10699.75 17199.27 3097.90 21699.47 143
v698.12 17397.84 18498.94 17098.94 26498.83 15499.66 6899.34 21496.49 24499.30 13399.37 24094.95 17599.34 25097.77 17694.74 29498.67 253
V4298.06 18097.79 18998.86 20498.98 25398.84 15199.69 4899.34 21496.53 24399.30 13399.37 24094.67 19999.32 25497.57 19594.66 30098.42 308
ab-mvs98.86 10798.63 11999.54 7999.64 11199.19 9599.44 16999.54 6497.77 13499.30 13399.81 5794.20 21699.93 5799.17 3998.82 15799.49 136
TAPA-MVS97.07 1597.74 23897.34 25698.94 17099.70 9097.53 24699.25 23999.51 8791.90 33899.30 13399.63 15198.78 3799.64 20688.09 34399.87 3999.65 93
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
v1neww98.12 17397.84 18498.93 17398.97 25698.81 16399.66 6899.35 20696.49 24499.29 13799.37 24095.02 17199.32 25497.73 18194.73 29598.67 253
v7new98.12 17397.84 18498.93 17398.97 25698.81 16399.66 6899.35 20696.49 24499.29 13799.37 24095.02 17199.32 25497.73 18194.73 29598.67 253
新几何199.75 4199.75 5899.59 5099.54 6496.76 22799.29 13799.64 14798.43 6499.94 4296.92 24199.66 9899.72 72
v798.05 18697.78 19298.87 20098.99 24998.67 18199.64 8099.34 21496.31 26299.29 13799.51 19594.78 18999.27 26697.03 23195.15 28798.66 264
VPNet97.84 21797.44 24199.01 16099.21 20898.94 13999.48 15699.57 4598.38 6599.28 14199.73 10788.89 32199.39 23699.19 3693.27 32298.71 228
v198.05 18697.76 19998.93 17398.92 27198.80 16899.57 11099.35 20696.39 25899.28 14199.36 24794.86 18499.32 25497.38 21394.72 29798.68 242
HY-MVS97.30 798.85 11598.64 11899.47 9899.42 16399.08 11099.62 8599.36 20297.39 17599.28 14199.68 12796.44 12799.92 6698.37 13098.22 19099.40 156
PAPM_NR99.04 8898.84 9799.66 5699.74 6999.44 7199.39 19499.38 19397.70 14399.28 14199.28 26698.34 7199.85 12096.96 23799.45 11099.69 81
HPM-MVS++copyleft99.39 3999.23 4899.87 799.75 5899.84 799.43 17499.51 8798.68 4899.27 14599.53 18798.64 5499.96 1998.44 12599.80 7199.79 46
v124097.69 24597.32 25998.79 21498.85 28598.43 20999.48 15699.36 20296.11 28099.27 14599.36 24793.76 23399.24 27494.46 30295.23 28498.70 232
thres600view797.86 21497.51 22598.92 17899.72 7897.95 23099.59 9798.74 30997.94 11599.27 14598.62 31391.75 28499.86 11393.73 31898.19 19398.96 199
PLCcopyleft97.94 499.02 9198.85 9699.53 8599.66 10699.01 12499.24 24199.52 7896.85 22399.27 14599.48 20898.25 7599.91 7697.76 17799.62 10499.65 93
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
tfpn11197.81 22397.49 22998.78 21699.72 7897.86 23399.59 9798.74 30997.93 11699.26 14998.62 31391.75 28499.86 11393.57 31998.18 19498.61 287
conf200view1197.78 23097.45 23598.77 21799.72 7897.86 23399.59 9798.74 30997.93 11699.26 14998.62 31391.75 28499.83 13593.22 32398.18 19498.61 287
thres100view90097.76 23297.45 23598.69 22399.72 7897.86 23399.59 9798.74 30997.93 11699.26 14998.62 31391.75 28499.83 13593.22 32398.18 19498.37 312
EPMVS97.82 22297.65 21498.35 25498.88 27895.98 29899.49 15194.71 36497.57 15499.26 14999.48 20892.46 27199.71 18997.87 16699.08 13499.35 159
view60097.97 19997.66 20998.89 18999.75 5897.81 23799.69 4898.80 30198.02 10599.25 15398.88 29891.95 27799.89 9794.36 30598.29 18498.96 199
view80097.97 19997.66 20998.89 18999.75 5897.81 23799.69 4898.80 30198.02 10599.25 15398.88 29891.95 27799.89 9794.36 30598.29 18498.96 199
conf0.05thres100097.97 19997.66 20998.89 18999.75 5897.81 23799.69 4898.80 30198.02 10599.25 15398.88 29891.95 27799.89 9794.36 30598.29 18498.96 199
tfpn97.97 19997.66 20998.89 18999.75 5897.81 23799.69 4898.80 30198.02 10599.25 15398.88 29891.95 27799.89 9794.36 30598.29 18498.96 199
112199.09 8098.87 9099.75 4199.74 6999.60 4899.27 22999.48 11796.82 22699.25 15399.65 13998.38 6899.93 5797.53 20099.67 9799.73 66
Fast-Effi-MVS+-dtu98.77 12498.83 10098.60 22999.41 16696.99 26899.52 13299.49 10798.11 8999.24 15899.34 25496.96 11299.79 15597.95 16199.45 11099.02 188
v192192097.80 22697.45 23598.84 20898.80 28898.53 19699.52 13299.34 21496.15 27799.24 15899.47 21293.98 22599.29 26295.40 28695.13 28898.69 237
divwei89l23v2f11298.06 18097.78 19298.91 18298.90 27498.77 17399.57 11099.35 20696.45 25199.24 15899.37 24094.92 17999.27 26697.50 20394.71 29998.68 242
LPG-MVS_test98.22 15998.13 15198.49 23999.33 18397.05 26399.58 10499.55 5797.46 16499.24 15899.83 4092.58 26499.72 18398.09 14797.51 23198.68 242
LGP-MVS_train98.49 23999.33 18397.05 26399.55 5797.46 16499.24 15899.83 4092.58 26499.72 18398.09 14797.51 23198.68 242
v114497.98 19697.69 20698.85 20798.87 28198.66 18399.54 12699.35 20696.27 26599.23 16399.35 25194.67 19999.23 27596.73 25495.16 28698.68 242
v114198.05 18697.76 19998.91 18298.91 27398.78 17299.57 11099.35 20696.41 25699.23 16399.36 24794.93 17899.27 26697.38 21394.72 29798.68 242
Anonymous2024052998.09 17797.68 20799.34 11399.66 10698.44 20899.40 19299.43 17293.67 32399.22 16599.89 1090.23 31099.93 5799.26 3198.33 17999.66 89
OPM-MVS98.19 16598.10 15398.45 24598.88 27897.07 26199.28 22699.38 19398.57 5399.22 16599.81 5792.12 27699.66 20298.08 15197.54 23098.61 287
test_djsdf98.67 13098.57 13098.98 16498.70 30598.91 14499.88 199.46 14397.55 15699.22 16599.88 1595.73 14799.28 26399.03 5097.62 22398.75 221
test1299.75 4199.64 11199.61 4699.29 23699.21 16898.38 6899.89 9799.74 8299.74 61
NCCC99.34 4399.19 5099.79 3599.61 12399.65 4199.30 22099.48 11798.86 3199.21 16899.63 15198.72 4899.90 8998.25 13899.63 10399.80 42
PMMVS98.80 12198.62 12499.34 11399.27 20098.70 17998.76 32399.31 22997.34 17799.21 16899.07 28497.20 10499.82 14498.56 11298.87 15499.52 127
v119297.81 22397.44 24198.91 18298.88 27898.68 18099.51 13699.34 21496.18 27399.20 17199.34 25494.03 22499.36 24495.32 28895.18 28598.69 237
EI-MVSNet98.67 13098.67 11498.68 22499.35 17997.97 22799.50 14199.38 19396.93 21999.20 17199.83 4097.87 8499.36 24498.38 12897.56 22898.71 228
MVSTER98.49 13698.32 14199.00 16299.35 17999.02 12299.54 12699.38 19397.41 17399.20 17199.73 10793.86 23099.36 24498.87 6697.56 22898.62 278
Anonymous20240521198.30 15197.98 16699.26 13499.57 13098.16 21999.41 18598.55 32896.03 28599.19 17499.74 10191.87 28299.92 6699.16 4198.29 18499.70 80
v2v48298.06 18097.77 19698.92 17898.90 27498.82 16199.57 11099.36 20296.65 23499.19 17499.35 25194.20 21699.25 27297.72 18594.97 29198.69 237
CNLPA99.14 6598.99 7399.59 7199.58 12899.41 7499.16 25599.44 16498.45 6099.19 17499.49 20298.08 8099.89 9797.73 18199.75 8099.48 138
UGNet98.87 10498.69 11299.40 10999.22 20798.72 17899.44 16999.68 1999.24 399.18 17799.42 22492.74 25199.96 1999.34 2399.94 1099.53 126
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
tfpn200view997.72 24197.38 24998.72 22199.69 9297.96 22899.50 14198.73 31897.83 12799.17 17898.45 32291.67 29099.83 13593.22 32398.18 19498.37 312
thres40097.77 23197.38 24998.92 17899.69 9297.96 22899.50 14198.73 31897.83 12799.17 17898.45 32291.67 29099.83 13593.22 32398.18 19498.96 199
Test_1112_low_res98.89 10398.66 11799.57 7699.69 9298.95 13699.03 28599.47 13396.98 21499.15 18099.23 27296.77 11899.89 9798.83 7598.78 16199.86 6
diffmvs98.99 9698.87 9099.35 11299.45 16098.74 17599.62 8599.45 15597.43 16999.13 18199.72 11197.23 10399.87 10998.86 6998.90 15199.45 150
1112_ss98.98 9798.77 10499.59 7199.68 9599.02 12299.25 23999.48 11797.23 18899.13 18199.58 16896.93 11399.90 8998.87 6698.78 16199.84 13
CLD-MVS98.16 16898.10 15398.33 25599.29 19596.82 27798.75 32499.44 16497.83 12799.13 18199.55 17792.92 24599.67 20098.32 13697.69 22098.48 304
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
原ACMM199.65 6099.73 7499.33 8199.47 13397.46 16499.12 18499.66 13898.67 5399.91 7697.70 18699.69 9399.71 79
tpm97.67 25097.55 22098.03 28099.02 24695.01 31899.43 17498.54 32996.44 25299.12 18499.34 25491.83 28399.60 21497.75 17996.46 26199.48 138
HQP_MVS98.27 15498.22 14798.44 24899.29 19596.97 27099.39 19499.47 13398.97 2299.11 18699.61 16092.71 25399.69 19897.78 17497.63 22198.67 253
plane_prior397.00 26798.69 4799.11 186
CHOSEN 1792x268899.19 5999.10 5999.45 10299.89 898.52 20099.39 19499.94 198.73 4499.11 18699.89 1095.50 15199.94 4299.50 899.97 399.89 2
mvs-test198.86 10798.84 9798.89 18999.33 18397.77 24299.44 16999.30 23198.47 5899.10 18999.43 22196.78 11699.95 3498.73 8699.02 13898.96 199
v897.95 20497.63 21698.93 17398.95 26198.81 16399.80 1999.41 17796.03 28599.10 18999.42 22494.92 17999.30 26096.94 23994.08 31398.66 264
ADS-MVSNet298.02 19198.07 15897.87 29299.33 18395.19 31599.23 24299.08 26896.24 26899.10 18999.67 13394.11 22198.93 31496.81 25099.05 13699.48 138
ADS-MVSNet98.20 16498.08 15698.56 23499.33 18396.48 28799.23 24299.15 26196.24 26899.10 18999.67 13394.11 22199.71 18996.81 25099.05 13699.48 138
thres20097.61 25497.28 26398.62 22899.64 11198.03 22499.26 23798.74 30997.68 14599.09 19398.32 32491.66 29299.81 14892.88 32998.22 19098.03 324
dp97.75 23697.80 18897.59 30699.10 23393.71 33399.32 21598.88 29596.48 25099.08 19499.55 17792.67 26299.82 14496.52 26398.58 16799.24 166
GBi-Net97.68 24797.48 23098.29 25999.51 14097.26 25199.43 17499.48 11796.49 24499.07 19599.32 26090.26 30798.98 30597.10 22796.65 25698.62 278
test197.68 24797.48 23098.29 25999.51 14097.26 25199.43 17499.48 11796.49 24499.07 19599.32 26090.26 30798.98 30597.10 22796.65 25698.62 278
FMVSNet398.03 18997.76 19998.84 20899.39 17398.98 12899.40 19299.38 19396.67 23399.07 19599.28 26692.93 24498.98 30597.10 22796.65 25698.56 300
IterMVS-LS98.46 13898.42 13598.58 23199.59 12798.00 22599.37 20199.43 17296.94 21899.07 19599.59 16597.87 8499.03 29998.32 13695.62 27898.71 228
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
pmmvs498.13 17197.90 17298.81 21198.61 31598.87 14798.99 29499.21 25596.44 25299.06 19999.58 16895.90 14199.11 29197.18 22496.11 26898.46 307
XVG-ACMP-BASELINE97.83 21997.71 20598.20 27399.11 23096.33 29299.41 18599.52 7898.06 10099.05 20099.50 19989.64 31599.73 17997.73 18197.38 24498.53 301
CostFormer97.72 24197.73 20397.71 30399.15 22594.02 32999.54 12699.02 27894.67 30299.04 20199.35 25192.35 27499.77 16598.50 11997.94 21599.34 160
DP-MVS99.16 6498.95 8199.78 3699.77 4399.53 5999.41 18599.50 10297.03 21299.04 20199.88 1597.39 9799.92 6698.66 9499.90 2499.87 5
ACMM97.58 598.37 14698.34 13998.48 24199.41 16697.10 25799.56 11799.45 15598.53 5599.04 20199.85 2793.00 24399.71 18998.74 8497.45 23898.64 269
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
Fast-Effi-MVS+98.70 12798.43 13499.51 9199.51 14099.28 8799.52 13299.47 13396.11 28099.01 20499.34 25496.20 13499.84 12697.88 16598.82 15799.39 157
nrg03098.64 13398.42 13599.28 12899.05 24299.69 3399.81 1599.46 14398.04 10299.01 20499.82 4796.69 12199.38 23799.34 2394.59 30398.78 214
test_prior399.21 5899.05 6299.68 5399.67 9699.48 6698.96 30399.56 5098.34 6799.01 20499.52 19298.68 5199.83 13597.96 15999.74 8299.74 61
test_prior298.96 30398.34 6799.01 20499.52 19298.68 5197.96 15999.74 82
v5297.79 22897.50 22798.66 22798.80 28898.62 18899.87 499.44 16495.87 28899.01 20499.46 21694.44 21099.33 25196.65 26193.96 31698.05 321
V497.80 22697.51 22598.67 22698.79 29098.63 18699.87 499.44 16495.87 28899.01 20499.46 21694.52 20699.33 25196.64 26293.97 31598.05 321
MAR-MVS98.86 10798.63 11999.54 7999.37 17699.66 3899.45 16599.54 6496.61 23799.01 20499.40 23197.09 10699.86 11397.68 18999.53 10899.10 174
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
PS-MVSNAJss98.92 10298.92 8398.90 18698.78 29498.53 19699.78 2299.54 6498.07 9699.00 21199.76 9199.01 1299.37 24099.13 4397.23 24898.81 211
PAPR98.63 13498.34 13999.51 9199.40 17199.03 12198.80 31999.36 20296.33 25999.00 21199.12 28298.46 6299.84 12695.23 28999.37 11899.66 89
v1097.85 21597.52 22398.86 20498.99 24998.67 18199.75 3599.41 17795.70 29198.98 21399.41 22794.75 19599.23 27596.01 27394.63 30298.67 253
UniMVSNet (Re)98.29 15298.00 16499.13 15199.00 24899.36 7899.49 15199.51 8797.95 11498.97 21499.13 27996.30 13199.38 23798.36 13293.34 32198.66 264
TEST999.67 9699.65 4199.05 27999.41 17796.22 27098.95 21599.49 20298.77 4099.91 76
train_agg99.02 9198.77 10499.77 3899.67 9699.65 4199.05 27999.41 17796.28 26398.95 21599.49 20298.76 4299.91 7697.63 19099.72 8699.75 56
BH-RMVSNet98.41 14398.08 15699.40 10999.41 16698.83 15499.30 22098.77 30597.70 14398.94 21799.65 13992.91 24799.74 17296.52 26399.55 10799.64 99
test_899.67 9699.61 4699.03 28599.41 17796.28 26398.93 21899.48 20898.76 4299.91 76
3Dnovator97.25 999.24 5699.05 6299.81 3099.12 22899.66 3899.84 999.74 1099.09 898.92 21999.90 795.94 13999.98 598.95 5799.92 1299.79 46
v7n97.87 21397.52 22398.92 17898.76 29898.58 19299.84 999.46 14396.20 27198.91 22099.70 11694.89 18299.44 23096.03 27293.89 31798.75 221
JIA-IIPM97.50 26397.02 27298.93 17398.73 30097.80 24199.30 22098.97 28291.73 33998.91 22094.86 35495.10 16899.71 18997.58 19397.98 21499.28 164
v14897.79 22897.55 22098.50 23898.74 29997.72 24599.54 12699.33 22296.26 26698.90 22299.51 19594.68 19899.14 28597.83 16993.15 32498.63 276
GA-MVS97.85 21597.47 23299.00 16299.38 17497.99 22698.57 33599.15 26197.04 21198.90 22299.30 26389.83 31399.38 23796.70 25698.33 17999.62 105
tpm297.44 26897.34 25697.74 30299.15 22594.36 32699.45 16598.94 28593.45 32998.90 22299.44 22091.35 29799.59 21697.31 21698.07 21199.29 163
agg_prior398.97 9998.71 11099.75 4199.67 9699.60 4899.04 28499.41 17795.93 28798.87 22599.48 20898.61 5599.91 7697.63 19099.72 8699.75 56
agg_prior199.01 9498.76 10699.76 4099.67 9699.62 4498.99 29499.40 18496.26 26698.87 22599.49 20298.77 4099.91 7697.69 18799.72 8699.75 56
agg_prior99.67 9699.62 4499.40 18498.87 22599.91 76
anonymousdsp98.44 13998.28 14498.94 17098.50 32198.96 13599.77 2499.50 10297.07 20898.87 22599.77 8894.76 19499.28 26398.66 9497.60 22498.57 299
DSMNet-mixed97.25 27497.35 25396.95 31897.84 33193.61 33599.57 11096.63 36096.13 27998.87 22598.61 31794.59 20297.70 34295.08 29198.86 15599.55 119
FMVSNet297.72 24197.36 25198.80 21399.51 14098.84 15199.45 16599.42 17596.49 24498.86 23099.29 26590.26 30798.98 30596.44 26596.56 25998.58 298
PatchFormer-LS_test98.01 19498.05 15997.87 29299.15 22594.76 32299.42 18198.93 28697.12 19798.84 23198.59 31893.74 23599.80 15298.55 11598.17 20099.06 184
ITE_SJBPF98.08 27899.29 19596.37 29098.92 28898.34 6798.83 23299.75 9691.09 30099.62 21295.82 27597.40 24298.25 317
Anonymous2023121197.88 21197.54 22298.90 18699.71 8498.53 19699.48 15699.57 4594.16 31798.81 23399.68 12793.23 23999.42 23598.84 7294.42 30698.76 219
Patchmtry97.75 23697.40 24798.81 21199.10 23398.87 14799.11 26899.33 22294.83 29998.81 23399.38 23694.33 21299.02 30096.10 27095.57 27998.53 301
BH-untuned98.42 14198.36 13798.59 23099.49 14996.70 28099.27 22999.13 26497.24 18798.80 23599.38 23695.75 14699.74 17297.07 23099.16 12799.33 161
FIs98.78 12298.63 11999.23 14099.18 21599.54 5699.83 1299.59 3998.28 7198.79 23699.81 5796.75 11999.37 24099.08 4796.38 26398.78 214
OurMVSNet-221017-097.88 21197.77 19698.19 27498.71 30496.53 28599.88 199.00 27997.79 13298.78 23799.94 391.68 28999.35 24797.21 22096.99 25498.69 237
MVS-HIRNet95.75 30595.16 30997.51 30999.30 19293.69 33498.88 31495.78 36185.09 35398.78 23792.65 35691.29 29899.37 24094.85 29599.85 5599.46 147
tpmvs97.98 19698.02 16297.84 29599.04 24394.73 32399.31 21899.20 25696.10 28498.76 23999.42 22494.94 17699.81 14896.97 23698.45 17598.97 193
Patchmatch-test97.93 20597.65 21498.77 21799.18 21597.07 26199.03 28599.14 26396.16 27598.74 24099.57 17294.56 20399.72 18393.36 32299.11 13099.52 127
QAPM98.67 13098.30 14399.80 3299.20 21099.67 3699.77 2499.72 1194.74 30198.73 24199.90 795.78 14599.98 596.96 23799.88 3599.76 55
3Dnovator+97.12 1399.18 6198.97 7699.82 2799.17 22099.68 3499.81 1599.51 8799.20 498.72 24299.89 1095.68 14899.97 1198.86 6999.86 5099.81 35
semantic-postprocess98.06 27999.57 13096.36 29199.49 10797.18 19198.71 24399.72 11192.70 25599.14 28597.44 21095.86 27498.67 253
UniMVSNet_NR-MVSNet98.22 15997.97 16798.96 16798.92 27198.98 12899.48 15699.53 7497.76 13598.71 24399.46 21696.43 12899.22 27898.57 10992.87 32798.69 237
DU-MVS98.08 17997.79 18998.96 16798.87 28198.98 12899.41 18599.45 15597.87 12098.71 24399.50 19994.82 18699.22 27898.57 10992.87 32798.68 242
tpm cat197.39 27097.36 25197.50 31099.17 22093.73 33199.43 17499.31 22991.27 34098.71 24399.08 28394.31 21499.77 16596.41 26798.50 17399.00 189
XXY-MVS98.38 14598.09 15599.24 13899.26 20299.32 8299.56 11799.55 5797.45 16798.71 24399.83 4093.23 23999.63 21198.88 6296.32 26598.76 219
IterMVS97.83 21997.77 19698.02 28299.58 12896.27 29499.02 28899.48 11797.22 18998.71 24399.70 11692.75 24999.13 28897.46 20896.00 27198.67 253
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
FC-MVSNet-test98.75 12598.62 12499.15 14799.08 23699.45 7099.86 899.60 3698.23 7698.70 24999.82 4796.80 11599.22 27899.07 4896.38 26398.79 213
COLMAP_ROBcopyleft97.56 698.86 10798.75 10799.17 14499.88 1198.53 19699.34 21399.59 3997.55 15698.70 24999.89 1095.83 14399.90 8998.10 14699.90 2499.08 179
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
TR-MVS97.76 23297.41 24698.82 21099.06 23997.87 23298.87 31598.56 32796.63 23698.68 25199.22 27392.49 26799.65 20495.40 28697.79 21898.95 206
WR-MVS98.06 18097.73 20399.06 15598.86 28499.25 9199.19 25299.35 20697.30 18198.66 25299.43 22193.94 22699.21 28298.58 10794.28 30898.71 228
HQP-NCC99.19 21298.98 29898.24 7398.66 252
ACMP_Plane99.19 21298.98 29898.24 7398.66 252
HQP4-MVS98.66 25299.64 20698.64 269
HQP-MVS98.02 19197.90 17298.37 25399.19 21296.83 27598.98 29899.39 18798.24 7398.66 25299.40 23192.47 26899.64 20697.19 22297.58 22698.64 269
LF4IMVS97.52 25997.46 23497.70 30498.98 25395.55 30499.29 22498.82 30098.07 9698.66 25299.64 14789.97 31299.61 21397.01 23296.68 25597.94 328
mvs_tets98.40 14498.23 14698.91 18298.67 30998.51 20299.66 6899.53 7498.19 7998.65 25899.81 5792.75 24999.44 23099.31 2697.48 23798.77 217
TESTMET0.1,197.55 25697.27 26598.40 25198.93 26996.53 28598.67 32897.61 35296.96 21598.64 25999.28 26688.63 32799.45 22597.30 21799.38 11499.21 168
jajsoiax98.43 14098.28 14498.88 19698.60 31698.43 20999.82 1399.53 7498.19 7998.63 26099.80 6893.22 24199.44 23099.22 3497.50 23398.77 217
Baseline_NR-MVSNet97.76 23297.45 23598.68 22499.09 23598.29 21499.41 18598.85 29795.65 29298.63 26099.67 13394.82 18699.10 29398.07 15492.89 32698.64 269
EPNet98.86 10798.71 11099.30 12397.20 34298.18 21899.62 8598.91 29199.28 298.63 26099.81 5795.96 13699.99 199.24 3299.72 8699.73 66
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
test-LLR98.06 18097.90 17298.55 23698.79 29097.10 25798.67 32897.75 34297.34 17798.61 26398.85 30294.45 20899.45 22597.25 21899.38 11499.10 174
test-mter97.49 26597.13 26998.55 23698.79 29097.10 25798.67 32897.75 34296.65 23498.61 26398.85 30288.23 33299.45 22597.25 21899.38 11499.10 174
FMVSNet196.84 28196.36 28298.29 25999.32 19097.26 25199.43 17499.48 11795.11 29698.55 26599.32 26083.95 35098.98 30595.81 27696.26 26698.62 278
v74897.52 25997.23 26698.41 25098.69 30697.23 25499.87 499.45 15595.72 29098.51 26699.53 18794.13 22099.30 26096.78 25292.39 33198.70 232
PCF-MVS97.08 1497.66 25197.06 27199.47 9899.61 12399.09 10998.04 35199.25 25191.24 34198.51 26699.70 11694.55 20499.91 7692.76 33099.85 5599.42 154
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
TranMVSNet+NR-MVSNet97.93 20597.66 20998.76 21998.78 29498.62 18899.65 7899.49 10797.76 13598.49 26899.60 16394.23 21598.97 31298.00 15792.90 32598.70 232
CP-MVSNet98.09 17797.78 19299.01 16098.97 25699.24 9299.67 5999.46 14397.25 18598.48 26999.64 14793.79 23199.06 29598.63 9794.10 31298.74 224
ACMP97.20 1198.06 18097.94 17098.45 24599.37 17697.01 26699.44 16999.49 10797.54 15998.45 27099.79 7691.95 27799.72 18397.91 16397.49 23698.62 278
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
cascas97.69 24597.43 24498.48 24198.60 31697.30 24898.18 34999.39 18792.96 33198.41 27198.78 30993.77 23299.27 26698.16 14398.61 16498.86 208
WR-MVS_H98.13 17197.87 18398.90 18699.02 24698.84 15199.70 4599.59 3997.27 18398.40 27299.19 27595.53 15099.23 27598.34 13393.78 31898.61 287
BH-w/o98.00 19597.89 17698.32 25699.35 17996.20 29699.01 29298.90 29396.42 25498.38 27399.00 29095.26 16199.72 18396.06 27198.61 16499.03 186
pmmvs597.52 25997.30 26198.16 27698.57 31896.73 27999.27 22998.90 29396.14 27898.37 27499.53 18791.54 29599.14 28597.51 20295.87 27398.63 276
DWT-MVSNet_test97.53 25897.40 24797.93 28899.03 24594.86 32099.57 11098.63 32396.59 24198.36 27598.79 30789.32 31799.74 17298.14 14598.16 20199.20 169
EU-MVSNet97.98 19698.03 16097.81 29898.72 30296.65 28399.66 6899.66 2698.09 9298.35 27699.82 4795.25 16298.01 33597.41 21295.30 28398.78 214
FMVSNet596.43 28796.19 28497.15 31399.11 23095.89 30099.32 21599.52 7894.47 31198.34 27799.07 28487.54 33697.07 34592.61 33195.72 27698.47 305
PS-CasMVS97.93 20597.59 21998.95 16998.99 24999.06 11299.68 5799.52 7897.13 19598.31 27899.68 12792.44 27299.05 29698.51 11894.08 31398.75 221
USDC97.34 27197.20 26797.75 30199.07 23795.20 31498.51 33899.04 27697.99 11098.31 27899.86 2389.02 31999.55 21995.67 28197.36 24598.49 303
PEN-MVS97.76 23297.44 24198.72 22198.77 29798.54 19599.78 2299.51 8797.06 21098.29 28099.64 14792.63 26398.89 31598.09 14793.16 32398.72 226
tfpnnormal97.84 21797.47 23298.98 16499.20 21099.22 9499.64 8099.61 3396.32 26098.27 28199.70 11693.35 23899.44 23095.69 27995.40 28198.27 315
ppachtmachnet_test97.49 26597.45 23597.61 30598.62 31395.24 31298.80 31999.46 14396.11 28098.22 28299.62 15696.45 12698.97 31293.77 31795.97 27298.61 287
tpmp4_e2397.34 27197.29 26297.52 30899.25 20493.73 33199.58 10499.19 25994.00 31998.20 28399.41 22790.74 30499.74 17297.13 22698.07 21199.07 183
our_test_397.65 25297.68 20797.55 30798.62 31394.97 31998.84 31799.30 23196.83 22598.19 28499.34 25497.01 11099.02 30095.00 29396.01 27098.64 269
LTVRE_ROB97.16 1298.02 19197.90 17298.40 25199.23 20596.80 27899.70 4599.60 3697.12 19798.18 28599.70 11691.73 28899.72 18398.39 12697.45 23898.68 242
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
ACMH97.28 898.10 17697.99 16598.44 24899.41 16696.96 27299.60 9499.56 5098.09 9298.15 28699.91 590.87 30399.70 19598.88 6297.45 23898.67 253
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
MS-PatchMatch97.24 27597.32 25996.99 31698.45 32393.51 33698.82 31899.32 22897.41 17398.13 28799.30 26388.99 32099.56 21795.68 28099.80 7197.90 331
LP97.04 27996.80 27597.77 30098.90 27495.23 31398.97 30199.06 27494.02 31898.09 28899.41 22793.88 22898.82 31690.46 33698.42 17799.26 165
MVS97.28 27396.55 28099.48 9498.78 29498.95 13699.27 22999.39 18783.53 35498.08 28999.54 18096.97 11199.87 10994.23 31399.16 12799.63 103
PAPM97.59 25597.09 27099.07 15499.06 23998.26 21698.30 34599.10 26694.88 29898.08 28999.34 25496.27 13299.64 20689.87 33898.92 14999.31 162
OpenMVScopyleft96.50 1698.47 13798.12 15299.52 8999.04 24399.53 5999.82 1399.72 1194.56 30798.08 28999.88 1594.73 19699.98 597.47 20799.76 7999.06 184
gg-mvs-nofinetune96.17 30095.32 30798.73 22098.79 29098.14 22199.38 19994.09 36591.07 34398.07 29291.04 36089.62 31699.35 24796.75 25399.09 13398.68 242
test0.0.03 197.71 24497.42 24598.56 23498.41 32497.82 23698.78 32198.63 32397.34 17798.05 29398.98 29494.45 20898.98 30595.04 29297.15 25298.89 207
131498.68 12998.54 13299.11 15298.89 27798.65 18499.27 22999.49 10796.89 22197.99 29499.56 17497.72 9099.83 13597.74 18099.27 12298.84 209
DTE-MVSNet97.51 26297.19 26898.46 24498.63 31298.13 22299.84 999.48 11796.68 23297.97 29599.67 13392.92 24598.56 32196.88 24992.60 33098.70 232
SixPastTwentyTwo97.50 26397.33 25898.03 28098.65 31096.23 29599.77 2498.68 32197.14 19497.90 29699.93 490.45 30599.18 28497.00 23396.43 26298.67 253
pm-mvs197.68 24797.28 26398.88 19699.06 23998.62 18899.50 14199.45 15596.32 26097.87 29799.79 7692.47 26899.35 24797.54 19993.54 32098.67 253
testgi97.65 25297.50 22798.13 27799.36 17896.45 28899.42 18199.48 11797.76 13597.87 29799.45 21991.09 30098.81 31794.53 30098.52 17299.13 173
EPNet_dtu98.03 18997.96 16898.23 26998.27 32695.54 30699.23 24298.75 30699.02 1097.82 29999.71 11396.11 13599.48 22293.04 32799.65 10099.69 81
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
TinyColmap97.12 27796.89 27497.83 29699.07 23795.52 30798.57 33598.74 30997.58 15397.81 30099.79 7688.16 33399.56 21795.10 29097.21 24998.39 311
ACMH+97.24 1097.92 20897.78 19298.32 25699.46 15696.68 28299.56 11799.54 6498.41 6497.79 30199.87 2090.18 31199.66 20298.05 15697.18 25198.62 278
N_pmnet94.95 31495.83 29292.31 33798.47 32279.33 36099.12 26292.81 37093.87 32197.68 30299.13 27993.87 22999.01 30291.38 33496.19 26798.59 295
PVSNet_094.43 1996.09 30295.47 30497.94 28799.31 19194.34 32797.81 35299.70 1597.12 19797.46 30398.75 31089.71 31499.79 15597.69 18781.69 35599.68 85
pmmvs696.53 28596.09 28697.82 29798.69 30695.47 30899.37 20199.47 13393.46 32897.41 30499.78 8287.06 33999.33 25196.92 24192.70 32998.65 267
new_pmnet96.38 29196.03 28797.41 31198.13 32995.16 31799.05 27999.20 25693.94 32097.39 30598.79 30791.61 29499.04 29790.43 33795.77 27598.05 321
IB-MVS95.67 1896.22 29895.44 30698.57 23299.21 20896.70 28098.65 33197.74 34496.71 23097.27 30698.54 32086.03 34199.92 6698.47 12286.30 35299.10 174
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
GG-mvs-BLEND98.45 24598.55 31998.16 21999.43 17493.68 36697.23 30798.46 32189.30 31899.22 27895.43 28598.22 19097.98 326
MVP-Stereo97.81 22397.75 20297.99 28597.53 33596.60 28498.96 30398.85 29797.22 18997.23 30799.36 24795.28 15899.46 22495.51 28399.78 7597.92 330
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
TransMVSNet (Re)97.15 27696.58 27998.86 20499.12 22898.85 15099.49 15198.91 29195.48 29397.16 30999.80 6893.38 23799.11 29194.16 31591.73 33298.62 278
NR-MVSNet97.97 19997.61 21799.02 15998.87 28199.26 9099.47 16199.42 17597.63 15097.08 31099.50 19995.07 16999.13 28897.86 16793.59 31998.68 242
Anonymous2023120696.22 29896.03 28796.79 32297.31 34094.14 32899.63 8299.08 26896.17 27497.04 31199.06 28693.94 22697.76 34186.96 34795.06 28998.47 305
testpf95.66 30696.02 28994.58 33098.35 32592.32 34197.25 35797.91 34192.83 33297.03 31298.99 29188.69 32498.61 32095.72 27897.40 24292.80 355
test_040296.64 28296.24 28397.85 29498.85 28596.43 28999.44 16999.26 24993.52 32696.98 31399.52 19288.52 32899.20 28392.58 33297.50 23397.93 329
MIMVSNet195.51 30795.04 31096.92 31997.38 33795.60 30299.52 13299.50 10293.65 32496.97 31499.17 27685.28 34596.56 34988.36 34295.55 28098.60 294
TDRefinement95.42 30994.57 31497.97 28689.83 36096.11 29799.48 15698.75 30696.74 22896.68 31599.88 1588.65 32699.71 18998.37 13082.74 35498.09 319
testus94.61 31595.30 30892.54 33696.44 34384.18 35298.36 34199.03 27794.18 31696.49 31698.57 31988.74 32295.09 35487.41 34598.45 17598.36 314
pmmvs394.09 32093.25 32296.60 32494.76 35094.49 32498.92 31098.18 33789.66 34596.48 31798.06 32786.28 34097.33 34489.68 33987.20 34697.97 327
DeepMVS_CXcopyleft93.34 33299.29 19582.27 35799.22 25485.15 35296.33 31899.05 28790.97 30299.73 17993.57 31997.77 21998.01 325
LCM-MVSNet-Re97.83 21998.15 14896.87 32099.30 19292.25 34299.59 9798.26 33397.43 16996.20 31999.13 27996.27 13298.73 31998.17 14298.99 14099.64 99
test20.0396.12 30195.96 29096.63 32397.44 33695.45 30999.51 13699.38 19396.55 24296.16 32099.25 27093.76 23396.17 35087.35 34694.22 31098.27 315
K. test v397.10 27896.79 27698.01 28398.72 30296.33 29299.87 497.05 35697.59 15196.16 32099.80 6888.71 32399.04 29796.69 25796.55 26098.65 267
test235694.07 32194.46 31692.89 33495.18 34886.13 35097.60 35599.06 27493.61 32596.15 32298.28 32585.60 34493.95 35686.68 34998.00 21398.59 295
UnsupCasMVSNet_eth96.44 28696.12 28597.40 31298.65 31095.65 30199.36 20599.51 8797.13 19596.04 32398.99 29188.40 33098.17 32496.71 25590.27 33598.40 310
lessismore_v097.79 29998.69 30695.44 31094.75 36395.71 32499.87 2088.69 32499.32 25495.89 27494.93 29398.62 278
Patchmatch-RL test95.84 30495.81 29395.95 32795.61 34590.57 34598.24 34698.39 33095.10 29795.20 32598.67 31294.78 18997.77 34096.28 26990.02 33699.51 132
ambc93.06 33392.68 35582.36 35698.47 33998.73 31895.09 32697.41 34455.55 36399.10 29396.42 26691.32 33397.71 341
PM-MVS92.96 32392.23 32595.14 32995.61 34589.98 34799.37 20198.21 33594.80 30095.04 32797.69 33565.06 36097.90 33894.30 31089.98 33797.54 345
OpenMVS_ROBcopyleft92.34 2094.38 31893.70 31996.41 32697.38 33793.17 33799.06 27798.75 30686.58 35194.84 32898.26 32681.53 35499.32 25489.01 34097.87 21796.76 346
v1796.42 28895.81 29398.25 26698.94 26498.80 16899.76 2799.28 24394.57 30594.18 32997.71 33295.23 16398.16 32594.86 29487.73 34497.80 334
v1896.42 28895.80 29598.26 26298.95 26198.82 16199.76 2799.28 24394.58 30494.12 33097.70 33395.22 16498.16 32594.83 29687.80 34297.79 339
v1696.39 29095.76 29698.26 26298.96 25998.81 16399.76 2799.28 24394.57 30594.10 33197.70 33395.04 17098.16 32594.70 29887.77 34397.80 334
EG-PatchMatch MVS95.97 30395.69 29796.81 32197.78 33292.79 33999.16 25598.93 28696.16 27594.08 33299.22 27382.72 35299.47 22395.67 28197.50 23398.17 318
v1196.23 29795.57 30398.21 27298.93 26998.83 15499.72 4299.29 23694.29 31594.05 33397.64 33794.88 18398.04 33392.89 32888.43 34097.77 340
v1596.28 29295.62 29898.25 26698.94 26498.83 15499.76 2799.29 23694.52 30994.02 33497.61 33995.02 17198.13 32994.53 30086.92 34797.80 334
DI_MVS_plusplus_test97.45 26796.79 27699.44 10597.76 33399.04 11499.21 24998.61 32597.74 13894.01 33598.83 30487.38 33899.83 13598.63 9798.90 15199.44 151
V1496.26 29395.60 29998.26 26298.94 26498.83 15499.76 2799.29 23694.49 31093.96 33697.66 33694.99 17498.13 32994.41 30386.90 34897.80 334
V996.25 29495.58 30098.26 26298.94 26498.83 15499.75 3599.29 23694.45 31293.96 33697.62 33894.94 17698.14 32894.40 30486.87 34997.81 332
test_normal97.44 26896.77 27899.44 10597.75 33499.00 12699.10 27098.64 32297.71 14193.93 33898.82 30587.39 33799.83 13598.61 10298.97 14399.49 136
v1396.24 29595.58 30098.25 26698.98 25398.83 15499.75 3599.29 23694.35 31493.89 33997.60 34095.17 16698.11 33194.27 31286.86 35097.81 332
v1296.24 29595.58 30098.23 26998.96 25998.81 16399.76 2799.29 23694.42 31393.85 34097.60 34095.12 16798.09 33294.32 30986.85 35197.80 334
pmmvs-eth3d95.34 31194.73 31297.15 31395.53 34795.94 29999.35 21099.10 26695.13 29593.55 34197.54 34388.15 33497.91 33794.58 29989.69 33897.61 342
new-patchmatchnet94.48 31694.08 31795.67 32895.08 34992.41 34099.18 25399.28 24394.55 30893.49 34297.37 34687.86 33597.01 34691.57 33388.36 34197.61 342
UnsupCasMVSNet_bld93.53 32292.51 32496.58 32597.38 33793.82 33098.24 34699.48 11791.10 34293.10 34396.66 34974.89 35598.37 32294.03 31687.71 34597.56 344
test123567892.91 32493.30 32191.71 34093.14 35483.01 35498.75 32498.58 32692.80 33392.45 34497.91 32988.51 32993.54 35782.26 35395.35 28298.59 295
Gipumacopyleft90.99 32790.15 32893.51 33198.73 30090.12 34693.98 36199.45 15579.32 35692.28 34594.91 35369.61 35797.98 33687.42 34495.67 27792.45 357
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
CMPMVSbinary69.68 2394.13 31994.90 31191.84 33897.24 34180.01 35998.52 33799.48 11789.01 34891.99 34699.67 13385.67 34399.13 28895.44 28497.03 25396.39 348
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
test1235691.74 32692.19 32790.37 34391.22 35682.41 35598.61 33298.28 33290.66 34491.82 34797.92 32884.90 34692.61 35881.64 35494.66 30096.09 350
PMMVS286.87 32985.37 33291.35 34290.21 35983.80 35398.89 31397.45 35483.13 35591.67 34895.03 35248.49 36594.70 35585.86 35077.62 35695.54 351
111192.30 32592.21 32692.55 33593.30 35286.27 34899.15 25898.74 30991.94 33690.85 34997.82 33084.18 34895.21 35279.65 35594.27 30996.19 349
.test124583.42 33286.17 33075.15 35493.30 35286.27 34899.15 25898.74 30991.94 33690.85 34997.82 33084.18 34895.21 35279.65 35539.90 36543.98 366
LCM-MVSNet86.80 33085.22 33391.53 34187.81 36280.96 35898.23 34898.99 28071.05 35990.13 35196.51 35048.45 36696.88 34790.51 33585.30 35396.76 346
Test495.05 31293.67 32099.22 14196.07 34498.94 13999.20 25199.27 24897.71 14189.96 35297.59 34266.18 35999.25 27298.06 15598.96 14599.47 143
testmv87.91 32887.80 32988.24 34487.68 36377.50 36299.07 27397.66 35189.27 34686.47 35396.22 35168.35 35892.49 36076.63 35988.82 33994.72 353
testing_294.44 31792.93 32398.98 16494.16 35199.00 12699.42 18199.28 24396.60 23984.86 35496.84 34870.91 35699.27 26698.23 13996.08 26998.68 242
E-PMN80.61 33579.88 33682.81 35090.75 35876.38 36497.69 35395.76 36266.44 36383.52 35592.25 35762.54 36287.16 36568.53 36361.40 35984.89 364
FPMVS84.93 33185.65 33182.75 35186.77 36463.39 36998.35 34398.92 28874.11 35883.39 35698.98 29450.85 36492.40 36184.54 35194.97 29192.46 356
EMVS80.02 33679.22 33782.43 35291.19 35776.40 36397.55 35692.49 37266.36 36483.01 35791.27 35864.63 36185.79 36665.82 36460.65 36085.08 363
YYNet195.36 31094.51 31597.92 28997.89 33097.10 25799.10 27099.23 25393.26 33080.77 35899.04 28892.81 24898.02 33494.30 31094.18 31198.64 269
MDA-MVSNet_test_wron95.45 30894.60 31398.01 28398.16 32897.21 25599.11 26899.24 25293.49 32780.73 35998.98 29493.02 24298.18 32394.22 31494.45 30598.64 269
MDA-MVSNet-bldmvs94.96 31393.98 31897.92 28998.24 32797.27 25099.15 25899.33 22293.80 32280.09 36099.03 28988.31 33197.86 33993.49 32194.36 30798.62 278
tmp_tt82.80 33481.52 33486.66 34566.61 37168.44 36892.79 36397.92 33968.96 36180.04 36199.85 2785.77 34296.15 35197.86 16743.89 36495.39 352
no-one83.04 33380.12 33591.79 33989.44 36185.65 35199.32 21598.32 33189.06 34779.79 36289.16 36244.86 36796.67 34884.33 35246.78 36393.05 354
PNet_i23d79.43 33777.68 33884.67 34786.18 36571.69 36796.50 35993.68 36675.17 35771.33 36391.18 35932.18 37090.62 36278.57 35874.34 35791.71 359
MVEpermissive76.82 2176.91 33974.31 34184.70 34685.38 36776.05 36596.88 35893.17 36867.39 36271.28 36489.01 36321.66 37587.69 36471.74 36272.29 35890.35 360
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
ANet_high77.30 33874.86 34084.62 34875.88 36977.61 36197.63 35493.15 36988.81 34964.27 36589.29 36136.51 36883.93 36775.89 36052.31 36292.33 358
wuykxyi23d74.42 34171.19 34284.14 34976.16 36874.29 36696.00 36092.57 37169.57 36063.84 36687.49 36421.98 37288.86 36375.56 36157.50 36189.26 362
PMVScopyleft70.75 2275.98 34074.97 33979.01 35370.98 37055.18 37093.37 36298.21 33565.08 36561.78 36793.83 35521.74 37492.53 35978.59 35791.12 33489.34 361
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
test12339.01 34642.50 34628.53 35739.17 37220.91 37298.75 32419.17 37519.83 36838.57 36866.67 36633.16 36915.42 36937.50 36729.66 36749.26 365
testmvs39.17 34543.78 34425.37 35836.04 37316.84 37398.36 34126.56 37320.06 36738.51 36967.32 36529.64 37115.30 37037.59 36639.90 36543.98 366
wuyk23d40.18 34441.29 34736.84 35586.18 36549.12 37179.73 36422.81 37427.64 36625.46 37028.45 37021.98 37248.89 36855.80 36523.56 36812.51 368
cdsmvs_eth3d_5k24.64 34732.85 3480.00 3590.00 3740.00 3740.00 36599.51 870.00 3690.00 37199.56 17496.58 1230.00 3710.00 3680.00 3690.00 369
pcd_1.5k_mvsjas8.27 34911.03 3500.00 3590.00 3740.00 3740.00 3650.00 3760.00 3690.00 3710.27 37199.01 120.00 3710.00 3680.00 3690.00 369
pcd1.5k->3k40.85 34343.49 34532.93 35698.95 2610.00 3740.00 36599.53 740.00 3690.00 3710.27 37195.32 1570.00 3710.00 36897.30 24698.80 212
sosnet-low-res0.02 3500.03 3510.00 3590.00 3740.00 3740.00 3650.00 3760.00 3690.00 3710.27 3710.00 3760.00 3710.00 3680.00 3690.00 369
sosnet0.02 3500.03 3510.00 3590.00 3740.00 3740.00 3650.00 3760.00 3690.00 3710.27 3710.00 3760.00 3710.00 3680.00 3690.00 369
uncertanet0.02 3500.03 3510.00 3590.00 3740.00 3740.00 3650.00 3760.00 3690.00 3710.27 3710.00 3760.00 3710.00 3680.00 3690.00 369
Regformer0.02 3500.03 3510.00 3590.00 3740.00 3740.00 3650.00 3760.00 3690.00 3710.27 3710.00 3760.00 3710.00 3680.00 3690.00 369
ab-mvs-re8.30 34811.06 3490.00 3590.00 3740.00 3740.00 3650.00 3760.00 3690.00 37199.58 1680.00 3760.00 3710.00 3680.00 3690.00 369
uanet0.02 3500.03 3510.00 3590.00 3740.00 3740.00 3650.00 3760.00 3690.00 3710.27 3710.00 3760.00 3710.00 3680.00 3690.00 369
GSMVS99.52 127
test_part10.00 3590.00 3740.00 36599.48 1170.00 3760.00 3710.00 3680.00 3690.00 369
sam_mvs194.86 18499.52 127
sam_mvs94.72 197
MTGPAbinary99.47 133
test_post199.23 24265.14 36894.18 21999.71 18997.58 193
test_post65.99 36794.65 20199.73 179
patchmatchnet-post98.70 31194.79 18899.74 172
MTMP99.54 12698.88 295
gm-plane-assit98.54 32092.96 33894.65 30399.15 27799.64 20697.56 197
test9_res97.49 20499.72 8699.75 56
agg_prior297.21 22099.73 8599.75 56
test_prior499.56 5398.99 294
test_prior99.68 5399.67 9699.48 6699.56 5099.83 13599.74 61
新几何299.01 292
旧先验199.74 6999.59 5099.54 6499.69 12298.47 6199.68 9699.73 66
无先验98.99 29499.51 8796.89 22199.93 5797.53 20099.72 72
原ACMM298.95 307
testdata299.95 3496.67 258
segment_acmp98.96 21
testdata198.85 31698.32 70
plane_prior799.29 19597.03 265
plane_prior699.27 20096.98 26992.71 253
plane_prior599.47 13399.69 19897.78 17497.63 22198.67 253
plane_prior499.61 160
plane_prior299.39 19498.97 22
plane_prior199.26 202
plane_prior96.97 27099.21 24998.45 6097.60 224
n20.00 376
nn0.00 376
door-mid98.05 338
test1199.35 206
door97.92 339
HQP5-MVS96.83 275
BP-MVS97.19 222
HQP3-MVS99.39 18797.58 226
HQP2-MVS92.47 268
NP-MVS99.23 20596.92 27399.40 231
ACMMP++_ref97.19 250
ACMMP++97.43 241
Test By Simon98.75 45