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 bysorted bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort by
LCM-MVSNet99.86 199.86 199.87 199.99 199.77 199.77 199.80 199.97 199.97 199.95 199.74 199.98 199.56 1100.00 199.85 4
pmmvs699.07 399.24 398.56 4499.81 296.38 5698.87 999.30 899.01 1599.63 999.66 399.27 299.68 10397.75 4599.89 3299.62 32
OurMVSNet-221017-098.61 1898.61 2698.63 4099.77 396.35 5799.17 599.05 3898.05 4399.61 1199.52 493.72 16799.88 1898.72 2099.88 3399.65 25
Gipumacopyleft98.07 4298.31 3897.36 12999.76 496.28 6098.51 2299.10 2598.76 2196.79 18999.34 2096.61 6398.82 29696.38 8799.50 11496.98 295
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
MIMVSNet198.51 2498.45 3298.67 3799.72 596.71 4598.76 1198.89 7998.49 2699.38 1899.14 4295.44 10799.84 2796.47 8599.80 4799.47 66
LTVRE_ROB96.88 199.18 299.34 298.72 3499.71 696.99 3999.69 299.57 399.02 1499.62 1099.36 1698.53 799.52 16598.58 2499.95 1399.66 24
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
mvs_tets98.90 498.94 798.75 2999.69 796.48 5498.54 2199.22 996.23 11499.71 499.48 698.77 699.93 298.89 1099.95 1399.84 6
PS-MVSNAJss98.53 2398.63 2298.21 6999.68 894.82 10598.10 4599.21 1096.91 9099.75 399.45 895.82 8999.92 498.80 1399.96 1199.89 1
jajsoiax98.77 1098.79 1498.74 3199.66 996.48 5498.45 2699.12 2295.83 13199.67 699.37 1498.25 1099.92 498.77 1499.94 1999.82 7
pcd1.5k->3k41.47 33844.19 34033.29 35199.65 100.00 3690.00 36099.07 340.00 3640.00 3660.00 36699.04 30.00 3660.00 36399.96 1199.87 2
v7n98.73 1298.99 697.95 8299.64 1194.20 12898.67 1399.14 2099.08 999.42 1699.23 2996.53 6699.91 1299.27 499.93 2199.73 15
test_djsdf98.73 1298.74 1898.69 3699.63 1296.30 5998.67 1399.02 5196.50 10399.32 2199.44 997.43 2999.92 498.73 1799.95 1399.86 3
anonymousdsp98.72 1598.63 2298.99 1099.62 1397.29 3498.65 1699.19 1395.62 13799.35 2099.37 1497.38 3199.90 1398.59 2399.91 2699.77 9
v74898.58 1998.89 997.67 10199.61 1493.53 15298.59 1798.90 7798.97 1799.43 1599.15 4196.53 6699.85 2398.88 1199.91 2699.64 28
v5298.85 799.01 498.37 5599.61 1495.53 8399.01 699.04 4598.48 2799.31 2299.41 1196.82 5699.87 2099.44 299.95 1399.70 19
V498.85 799.01 498.37 5599.61 1495.53 8399.01 699.04 4598.48 2799.31 2299.41 1196.81 5799.87 2099.44 299.95 1399.70 19
PEN-MVS98.75 1198.85 1298.44 5099.58 1795.67 7698.45 2699.15 1899.33 499.30 2499.00 4997.27 3699.92 497.64 4899.92 2399.75 13
Baseline_NR-MVSNet97.72 7597.79 6197.50 11499.56 1893.29 15795.44 19298.86 8598.20 3998.37 7999.24 2794.69 12799.55 15795.98 10199.79 4899.65 25
SixPastTwentyTwo97.49 9297.57 8297.26 13599.56 1892.33 17098.28 3296.97 26498.30 3599.45 1499.35 1888.43 25999.89 1698.01 3599.76 5199.54 46
PS-CasMVS98.73 1298.85 1298.39 5499.55 2095.47 8598.49 2399.13 2199.22 799.22 3098.96 5397.35 3299.92 497.79 4399.93 2199.79 8
DTE-MVSNet98.79 998.86 1098.59 4299.55 2096.12 6498.48 2599.10 2599.36 399.29 2599.06 4897.27 3699.93 297.71 4799.91 2699.70 19
HPM-MVS_fast98.32 3198.13 4598.88 2299.54 2297.48 2798.35 2999.03 5095.88 12797.88 13698.22 11498.15 1299.74 5896.50 8499.62 8099.42 88
TDRefinement98.90 498.86 1099.02 899.54 2298.06 699.34 499.44 698.85 1999.00 4299.20 3197.42 3099.59 14597.21 6599.76 5199.40 93
Anonymous2024052198.58 1998.65 2198.36 5899.52 2495.60 7898.96 898.95 7398.36 3199.25 2799.17 3995.28 11399.80 3798.46 2599.88 3399.68 23
pm-mvs198.47 2598.67 1997.86 8799.52 2494.58 11398.28 3299.00 6297.57 6699.27 2699.22 3098.32 999.50 17797.09 7299.75 5599.50 52
TransMVSNet (Re)98.38 2998.67 1997.51 11199.51 2693.39 15698.20 4098.87 8398.23 3799.48 1299.27 2598.47 899.55 15796.52 8299.53 10799.60 35
WR-MVS_H98.65 1798.62 2498.75 2999.51 2696.61 5098.55 2099.17 1499.05 1299.17 3398.79 6295.47 10599.89 1697.95 3699.91 2699.75 13
PMVScopyleft89.60 1796.71 14696.97 12395.95 21699.51 2697.81 1397.42 9097.49 24497.93 4795.95 22798.58 7896.88 5196.91 35089.59 26199.36 15593.12 349
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
MP-MVS-pluss97.69 7897.36 9298.70 3599.50 2996.84 4295.38 20198.99 6592.45 24398.11 10598.31 10197.25 3899.77 4896.60 7999.62 8099.48 63
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
FC-MVSNet-test98.16 3798.37 3497.56 10699.49 3093.10 16098.35 2999.21 1098.43 2998.89 4698.83 6194.30 14499.81 3297.87 3999.91 2699.77 9
VPNet97.26 10897.49 8896.59 17099.47 3190.58 20696.27 14598.53 14897.77 5198.46 7498.41 9194.59 13399.68 10394.61 15499.29 17299.52 49
CP-MVSNet98.42 2798.46 3098.30 6499.46 3295.22 9398.27 3498.84 8999.05 1299.01 4098.65 7595.37 10899.90 1397.57 5299.91 2699.77 9
XXY-MVS97.54 8997.70 6797.07 14399.46 3292.21 17497.22 9799.00 6294.93 17098.58 6498.92 5797.31 3499.41 21194.44 15899.43 14099.59 36
zzz-MVS98.01 4797.66 7199.06 599.44 3497.90 895.66 18398.73 11497.69 6097.90 13297.96 14595.81 9399.82 3096.13 9299.61 8599.45 73
MTAPA98.14 3897.84 5999.06 599.44 3497.90 897.25 9498.73 11497.69 6097.90 13297.96 14595.81 9399.82 3096.13 9299.61 8599.45 73
wuykxyi23d98.68 1698.53 2799.13 399.44 3497.97 796.85 12199.02 5195.81 13299.88 299.38 1398.14 1399.69 9798.32 2999.95 1399.73 15
SteuartSystems-ACMMP98.02 4597.76 6498.79 2799.43 3797.21 3697.15 9998.90 7796.58 10198.08 11197.87 15697.02 4699.76 4995.25 12899.59 9099.40 93
Skip Steuart: Steuart Systems R&D Blog.
ACMH93.61 998.44 2698.76 1597.51 11199.43 3793.54 15198.23 3599.05 3897.40 8299.37 1999.08 4798.79 599.47 18597.74 4699.71 6499.50 52
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
HPM-MVScopyleft98.11 4197.83 6098.92 1999.42 3997.46 2898.57 1899.05 3895.43 14697.41 16097.50 18697.98 1699.79 3995.58 11899.57 9599.50 52
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
K. test v396.44 15896.28 16096.95 14999.41 4091.53 19297.65 7390.31 34198.89 1898.93 4599.36 1684.57 28599.92 497.81 4199.56 9899.39 96
VDDNet96.98 11896.84 13097.41 12699.40 4193.26 15897.94 5495.31 29399.26 698.39 7899.18 3587.85 26699.62 12895.13 13899.09 19299.35 105
ACMH+93.58 1098.23 3698.31 3897.98 8199.39 4295.22 9397.55 8399.20 1298.21 3899.25 2798.51 8598.21 1199.40 21494.79 14999.72 6099.32 107
TSAR-MVS + MP.97.42 9697.23 10598.00 8099.38 4395.00 9997.63 7598.20 19393.00 22998.16 10098.06 13695.89 8499.72 6995.67 10999.10 19199.28 118
FIs97.93 5698.07 4897.48 11899.38 4392.95 16298.03 5199.11 2398.04 4498.62 5998.66 7393.75 16699.78 4097.23 6499.84 4199.73 15
lessismore_v097.05 14499.36 4592.12 17884.07 36198.77 5398.98 5185.36 27999.74 5897.34 6299.37 15299.30 111
ACMMP_Plus97.89 6197.63 7698.67 3799.35 4696.84 4296.36 14198.79 10395.07 16697.88 13698.35 9697.24 3999.72 6996.05 9599.58 9299.45 73
Vis-MVSNetpermissive98.27 3398.34 3698.07 7499.33 4795.21 9598.04 4999.46 597.32 8597.82 14599.11 4496.75 5999.86 2297.84 4099.36 15599.15 135
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
ANet_high98.31 3298.94 796.41 18299.33 4789.64 21997.92 5699.56 499.27 599.66 899.50 597.67 2499.83 2997.55 5399.98 399.77 9
MP-MVScopyleft97.64 8197.18 10899.00 999.32 4997.77 1497.49 8698.73 11496.27 11195.59 24097.75 16696.30 7799.78 4093.70 18799.48 12499.45 73
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
PVSNet_Blended_VisFu95.95 17595.80 17796.42 18199.28 5090.62 20595.31 20799.08 3088.40 28596.97 18398.17 12192.11 21099.78 4093.64 18899.21 17998.86 186
tfpnnormal97.72 7597.97 5396.94 15099.26 5192.23 17397.83 6298.45 15598.25 3699.13 3498.66 7396.65 6199.69 9793.92 18199.62 8098.91 175
HSP-MVS97.37 10096.85 12998.92 1999.26 5197.70 1597.66 7298.23 18995.65 13598.51 6896.46 24792.15 20899.81 3295.14 13798.58 24099.26 122
testgi96.07 17196.50 15294.80 25599.26 5187.69 27495.96 16798.58 14695.08 16598.02 11896.25 25897.92 1797.60 34688.68 27698.74 22599.11 146
IS-MVSNet96.93 12396.68 13997.70 9799.25 5494.00 13498.57 1896.74 27298.36 3198.14 10397.98 14488.23 26099.71 8093.10 19899.72 6099.38 98
ACMMPcopyleft98.05 4397.75 6598.93 1899.23 5597.60 1998.09 4698.96 7195.75 13497.91 13198.06 13696.89 4999.76 4995.32 12699.57 9599.43 86
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
nrg03098.54 2298.62 2498.32 6199.22 5695.66 7797.90 5799.08 3098.31 3499.02 3998.74 6797.68 2399.61 13497.77 4499.85 4099.70 19
region2R97.92 5797.59 8098.92 1999.22 5697.55 2397.60 7998.84 8996.00 12297.22 16597.62 17696.87 5299.76 4995.48 12099.43 14099.46 68
mPP-MVS97.91 5997.53 8499.04 799.22 5697.87 1197.74 6998.78 10696.04 12097.10 17297.73 16996.53 6699.78 4095.16 13599.50 11499.46 68
COLMAP_ROBcopyleft94.48 698.25 3598.11 4698.64 3999.21 5997.35 3297.96 5399.16 1598.34 3398.78 5098.52 8497.32 3399.45 19494.08 17299.67 7499.13 138
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
ACMMPR97.95 5297.62 7898.94 1599.20 6097.56 2297.59 8098.83 9796.05 11897.46 15897.63 17596.77 5899.76 4995.61 11599.46 12899.49 60
PGM-MVS97.88 6297.52 8598.96 1399.20 6097.62 1897.09 10899.06 3695.45 14497.55 14997.94 14997.11 4199.78 4094.77 15199.46 12899.48 63
test_040297.84 6597.97 5397.47 11999.19 6294.07 13196.71 12898.73 11498.66 2398.56 6598.41 9196.84 5499.69 9794.82 14699.81 4498.64 204
EPP-MVSNet96.84 13296.58 14397.65 10299.18 6393.78 14398.68 1296.34 27597.91 4897.30 16398.06 13688.46 25899.85 2393.85 18399.40 15099.32 107
abl_698.42 2798.19 4299.09 499.16 6498.10 597.73 7199.11 2397.76 5298.62 5998.27 10897.88 2099.80 3795.67 10999.50 11499.38 98
XVG-ACMP-BASELINE97.58 8797.28 9898.49 4799.16 6496.90 4196.39 13698.98 6895.05 16798.06 11498.02 14095.86 8599.56 15394.37 16399.64 7899.00 159
CHOSEN 1792x268894.10 24293.41 24796.18 19999.16 6490.04 21292.15 31698.68 12779.90 34396.22 21897.83 15787.92 26599.42 20089.18 26799.65 7799.08 151
HFP-MVS97.94 5497.64 7498.83 2499.15 6797.50 2597.59 8098.84 8996.05 11897.49 15397.54 18197.07 4499.70 8895.61 11599.46 12899.30 111
#test#97.62 8397.22 10698.83 2499.15 6797.50 2596.81 12398.84 8994.25 19397.49 15397.54 18197.07 4499.70 8894.37 16399.46 12899.30 111
XVS97.96 4997.63 7698.94 1599.15 6797.66 1697.77 6498.83 9797.42 7496.32 21197.64 17496.49 7099.72 6995.66 11199.37 15299.45 73
X-MVStestdata92.86 26490.83 29898.94 1599.15 6797.66 1697.77 6498.83 9797.42 7496.32 21136.50 36196.49 7099.72 6995.66 11199.37 15299.45 73
LPG-MVS_test97.94 5497.67 7098.74 3199.15 6797.02 3797.09 10899.02 5195.15 15998.34 8398.23 11197.91 1899.70 8894.41 16099.73 5799.50 52
LGP-MVS_train98.74 3199.15 6797.02 3799.02 5195.15 15998.34 8398.23 11197.91 1899.70 8894.41 16099.73 5799.50 52
RPSCF97.87 6397.51 8698.95 1499.15 6798.43 397.56 8299.06 3696.19 11598.48 7198.70 7094.72 12599.24 24994.37 16399.33 16699.17 131
ACMM93.33 1198.05 4397.79 6198.85 2399.15 6797.55 2396.68 12998.83 9795.21 15498.36 8198.13 12698.13 1599.62 12896.04 9699.54 10499.39 96
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
FMVSNet197.95 5298.08 4797.56 10699.14 7593.67 14598.23 3598.66 13397.41 8199.00 4299.19 3295.47 10599.73 6395.83 10599.76 5199.30 111
Vis-MVSNet (Re-imp)95.11 20894.85 20595.87 22199.12 7689.17 23697.54 8594.92 29596.50 10396.58 19597.27 20083.64 28699.48 18388.42 27999.67 7498.97 163
OPM-MVS97.54 8997.25 9998.41 5299.11 7796.61 5095.24 21398.46 15494.58 18198.10 10898.07 13397.09 4399.39 22095.16 13599.44 13399.21 126
UA-Net98.88 698.76 1599.22 299.11 7797.89 1099.47 399.32 799.08 997.87 14199.67 296.47 7299.92 497.88 3899.98 399.85 4
AllTest97.20 11196.92 12798.06 7599.08 7996.16 6297.14 10199.16 1594.35 19097.78 14698.07 13395.84 8699.12 25991.41 22199.42 14398.91 175
TestCases98.06 7599.08 7996.16 6299.16 1594.35 19097.78 14698.07 13395.84 8699.12 25991.41 22199.42 14398.91 175
TranMVSNet+NR-MVSNet98.33 3098.30 4098.43 5199.07 8195.87 6996.73 12799.05 3898.67 2298.84 4798.45 8997.58 2699.88 1896.45 8699.86 3899.54 46
VPA-MVSNet98.27 3398.46 3097.70 9799.06 8293.80 14197.76 6699.00 6298.40 3099.07 3798.98 5196.89 4999.75 5397.19 6899.79 4899.55 45
114514_t93.96 24693.22 25196.19 19899.06 8290.97 19995.99 16198.94 7473.88 35793.43 30696.93 21892.38 20699.37 22889.09 26899.28 17398.25 241
EG-PatchMatch MVS97.69 7897.79 6197.40 12799.06 8293.52 15395.96 16798.97 7094.55 18298.82 4898.76 6597.31 3499.29 24297.20 6799.44 13399.38 98
ACMP92.54 1397.47 9497.10 11698.55 4599.04 8596.70 4696.24 14998.89 7993.71 21297.97 12397.75 16697.44 2899.63 12293.22 19599.70 6799.32 107
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
test_part299.03 8696.07 6598.08 111
v1.040.70 33954.26 3390.00 35499.03 860.00 3690.00 36098.84 8994.84 17198.08 11197.60 1780.00 3710.00 3660.00 3630.00 3640.00 364
v1398.02 4598.52 2896.51 17599.02 8890.14 21098.07 4799.09 2998.10 4299.13 3499.35 1894.84 12399.74 5899.12 599.98 399.65 25
XVG-OURS-SEG-HR97.38 9997.07 11998.30 6499.01 8997.41 3194.66 24199.02 5195.20 15598.15 10297.52 18498.83 498.43 32494.87 14496.41 31899.07 153
XVG-OURS97.12 11296.74 13798.26 6698.99 9097.45 2993.82 27799.05 3895.19 15698.32 8697.70 17295.22 11598.41 32594.27 16898.13 25898.93 171
CP-MVS97.92 5797.56 8398.99 1098.99 9097.82 1297.93 5598.96 7196.11 11796.89 18797.45 18996.85 5399.78 4095.19 13199.63 7999.38 98
v1297.97 4898.47 2996.46 17998.98 9290.01 21497.97 5299.08 3098.00 4599.11 3699.34 2094.70 12699.73 6399.07 699.98 399.64 28
CSCG97.40 9897.30 9597.69 9998.95 9394.83 10497.28 9398.99 6596.35 11098.13 10495.95 27295.99 8299.66 11594.36 16699.73 5798.59 209
v1197.82 6998.36 3596.17 20098.93 9489.16 23797.79 6399.08 3097.64 6399.19 3199.32 2294.28 14599.72 6999.07 699.97 899.63 30
V997.90 6098.40 3396.40 18398.93 9489.86 21697.86 5999.07 3497.88 4999.05 3899.30 2394.53 13799.72 6999.01 899.98 399.63 30
HyFIR lowres test93.72 25092.65 26196.91 15398.93 9491.81 18991.23 33098.52 14982.69 33196.46 20296.52 24580.38 29699.90 1390.36 25298.79 22099.03 157
testing_297.43 9597.71 6696.60 16798.91 9790.85 20096.01 16098.54 14794.78 17498.78 5098.96 5396.35 7699.54 15997.25 6399.82 4399.40 93
PM-MVS97.36 10397.10 11698.14 7298.91 9796.77 4496.20 15198.63 14093.82 20998.54 6698.33 9993.98 15699.05 26995.99 10099.45 13298.61 208
CPTT-MVS96.69 14796.08 16698.49 4798.89 9996.64 4997.25 9498.77 10792.89 23696.01 22697.13 20592.23 20799.67 11092.24 20799.34 16199.17 131
V1497.83 6698.33 3796.35 18498.88 10089.72 21797.75 6799.05 3897.74 5399.01 4099.27 2594.35 14299.71 8098.95 999.97 899.62 32
ESAPD97.64 8197.35 9398.50 4698.85 10196.18 6195.21 21598.99 6595.84 13098.78 5098.08 13196.84 5499.81 3293.98 17999.57 9599.52 49
SMA-MVS97.48 9397.11 11598.60 4198.83 10296.67 4796.74 12598.73 11491.61 25698.48 7198.36 9596.53 6699.68 10395.17 13399.54 10499.45 73
v1597.77 7298.26 4196.30 18998.81 10389.59 22497.62 7699.04 4597.59 6598.97 4499.24 2794.19 15099.70 8898.88 1199.97 899.61 34
UniMVSNet (Re)97.83 6697.65 7298.35 6098.80 10495.86 7095.92 17299.04 4597.51 7198.22 9597.81 16194.68 12999.78 4097.14 7099.75 5599.41 90
Anonymous2023121198.55 2198.76 1597.94 8398.79 10594.37 12098.84 1099.15 1899.37 299.67 699.43 1095.61 10099.72 6998.12 3199.86 3899.73 15
APD-MVS_3200maxsize98.13 4097.90 5698.79 2798.79 10597.31 3397.55 8398.92 7597.72 5798.25 9398.13 12697.10 4299.75 5395.44 12299.24 17799.32 107
DeepC-MVS95.41 497.82 6997.70 6798.16 7098.78 10795.72 7396.23 15099.02 5193.92 20298.62 5998.99 5097.69 2299.62 12896.18 9199.87 3699.15 135
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
v1797.70 7798.17 4396.28 19298.77 10889.59 22497.62 7699.01 6097.54 6898.72 5699.18 3594.06 15499.68 10398.74 1699.92 2399.58 37
v1697.69 7898.16 4496.29 19198.75 10989.60 22297.62 7699.01 6097.53 7098.69 5899.18 3594.05 15599.68 10398.73 1799.88 3399.58 37
MCST-MVS96.24 16495.80 17797.56 10698.75 10994.13 13094.66 24198.17 19890.17 27196.21 21996.10 26695.14 11699.43 19994.13 17198.85 21999.13 138
DU-MVS97.79 7197.60 7998.36 5898.73 11195.78 7195.65 18598.87 8397.57 6698.31 8897.83 15794.69 12799.85 2397.02 7499.71 6499.46 68
NR-MVSNet97.96 4997.86 5898.26 6698.73 11195.54 8198.14 4398.73 11497.79 5099.42 1697.83 15794.40 14199.78 4095.91 10499.76 5199.46 68
Anonymous2023120695.27 20495.06 19895.88 22098.72 11389.37 23395.70 17997.85 22088.00 29296.98 17897.62 17691.95 21599.34 23289.21 26699.53 10798.94 167
APDe-MVS98.14 3898.03 5298.47 4998.72 11396.04 6698.07 4799.10 2595.96 12498.59 6398.69 7196.94 4799.81 3296.64 7899.58 9299.57 41
UniMVSNet_NR-MVSNet97.83 6697.65 7298.37 5598.72 11395.78 7195.66 18399.02 5198.11 4198.31 8897.69 17394.65 13199.85 2397.02 7499.71 6499.48 63
v897.60 8598.06 4996.23 19398.71 11689.44 22997.43 8998.82 10197.29 8698.74 5499.10 4593.86 15899.68 10398.61 2299.94 1999.56 42
v696.97 11997.24 10196.15 20198.71 11689.44 22995.97 16398.33 17595.25 15197.89 13498.15 12293.86 15899.61 13497.51 5599.50 11499.42 88
v1neww96.97 11997.24 10196.15 20198.70 11889.44 22995.97 16398.33 17595.25 15197.88 13698.15 12293.83 16199.61 13497.50 5699.50 11499.41 90
v7new96.97 11997.24 10196.15 20198.70 11889.44 22995.97 16398.33 17595.25 15197.88 13698.15 12293.83 16199.61 13497.50 5699.50 11499.41 90
HQP_MVS96.66 14996.33 15997.68 10098.70 11894.29 12296.50 13398.75 11196.36 10896.16 22196.77 22991.91 21999.46 19092.59 20399.20 18099.28 118
plane_prior798.70 11894.67 111
Anonymous2024052997.96 4998.04 5197.71 9598.69 12294.28 12597.86 5998.31 18498.79 2099.23 2998.86 6095.76 9699.61 13495.49 11999.36 15599.23 124
VDD-MVS97.37 10097.25 9997.74 9498.69 12294.50 11697.04 11195.61 29098.59 2498.51 6898.72 6892.54 20099.58 14796.02 9899.49 12199.12 143
v1897.60 8598.06 4996.23 19398.68 12489.46 22897.48 8798.98 6897.33 8498.60 6299.13 4393.86 15899.67 11098.62 2199.87 3699.56 42
HPM-MVS++copyleft96.99 11596.38 15598.81 2698.64 12597.59 2095.97 16398.20 19395.51 14295.06 24896.53 24394.10 15399.70 8894.29 16799.15 18499.13 138
ab-mvs96.59 15196.59 14296.60 16798.64 12592.21 17498.35 2997.67 23294.45 18396.99 17798.79 6294.96 12199.49 18090.39 25199.07 19598.08 251
F-COLMAP95.30 20294.38 22698.05 7898.64 12596.04 6695.61 18998.66 13389.00 27993.22 31196.40 25392.90 18899.35 23187.45 29897.53 29498.77 196
ITE_SJBPF97.85 8898.64 12596.66 4898.51 15195.63 13697.22 16597.30 19995.52 10298.55 31990.97 23098.90 21098.34 232
v14896.58 15296.97 12395.42 23598.63 12987.57 27595.09 22097.90 21795.91 12698.24 9497.96 14593.42 17399.39 22096.04 9699.52 11199.29 117
UnsupCasMVSNet_bld94.72 22194.26 22896.08 20698.62 13090.54 20993.38 29398.05 21290.30 26997.02 17596.80 22789.54 24799.16 25888.44 27896.18 32198.56 211
DP-MVS97.87 6397.89 5797.81 9098.62 13094.82 10597.13 10298.79 10398.98 1698.74 5498.49 8695.80 9599.49 18095.04 14299.44 13399.11 146
v1097.55 8897.97 5396.31 18898.60 13289.64 21997.44 8899.02 5196.60 9998.72 5699.16 4093.48 17199.72 6998.76 1599.92 2399.58 37
Test_1112_low_res93.53 25692.86 25695.54 23298.60 13288.86 24692.75 30598.69 12582.66 33292.65 32196.92 21984.75 28399.56 15390.94 23197.76 27298.19 247
v796.93 12397.17 10996.23 19398.59 13489.64 21995.96 16798.66 13394.41 18697.87 14198.38 9493.47 17299.64 11997.93 3799.24 17799.43 86
V4297.04 11397.16 11096.68 16598.59 13491.05 19796.33 14398.36 17094.60 17897.99 11998.30 10493.32 17799.62 12897.40 6199.53 10799.38 98
1112_ss94.12 24193.42 24696.23 19398.59 13490.85 20094.24 25498.85 8685.49 31492.97 31494.94 29286.01 27699.64 11991.78 21597.92 26798.20 246
v2v48296.78 14097.06 12095.95 21698.57 13788.77 25095.36 20298.26 18795.18 15797.85 14398.23 11192.58 19799.63 12297.80 4299.69 6899.45 73
WR-MVS96.90 12796.81 13397.16 13798.56 13892.20 17694.33 24998.12 20497.34 8398.20 9797.33 19892.81 18999.75 5394.79 14999.81 4499.54 46
v114196.86 12997.14 11296.04 20898.55 13989.06 24095.44 19298.33 17595.14 16197.93 12998.19 11693.36 17599.62 12897.61 4999.69 6899.44 82
v196.86 12997.14 11296.04 20898.55 13989.06 24095.44 19298.33 17595.14 16197.94 12698.18 12093.39 17499.61 13497.61 4999.69 6899.44 82
APD-MVScopyleft97.00 11496.53 14998.41 5298.55 13996.31 5896.32 14498.77 10792.96 23597.44 15997.58 18095.84 8699.74 5891.96 20999.35 15999.19 128
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
Patchmatch-RL test94.66 22394.49 22095.19 24198.54 14288.91 24492.57 30998.74 11391.46 25998.32 8697.75 16677.31 31098.81 29896.06 9499.61 8597.85 267
divwei89l23v2f11296.86 12997.14 11296.04 20898.54 14289.06 24095.44 19298.33 17595.14 16197.93 12998.19 11693.36 17599.61 13497.61 4999.68 7299.44 82
111188.78 31889.39 31186.96 34398.53 14462.84 36291.49 32597.48 24694.45 18396.56 19796.45 24843.83 36798.87 29286.33 30599.40 15099.18 130
.test124573.49 33679.27 33756.15 34998.53 14462.84 36291.49 32597.48 24694.45 18396.56 19796.45 24843.83 36798.87 29286.33 3058.32 3626.75 362
IterMVS-LS96.92 12597.29 9695.79 22398.51 14688.13 26095.10 21898.66 13396.99 8798.46 7498.68 7292.55 19899.74 5896.91 7699.79 4899.50 52
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
DP-MVS Recon95.55 18695.13 19496.80 15698.51 14693.99 13594.60 24398.69 12590.20 27095.78 23496.21 26192.73 19298.98 27990.58 24598.86 21797.42 282
test20.0396.58 15296.61 14196.48 17898.49 14891.72 19095.68 18297.69 23196.81 9598.27 9297.92 15294.18 15198.71 30690.78 23799.66 7699.00 159
plane_prior198.49 148
MDA-MVSNet-bldmvs95.69 18095.67 18095.74 22498.48 15088.76 25192.84 30297.25 25296.00 12297.59 14897.95 14891.38 22799.46 19093.16 19796.35 31998.99 162
UnsupCasMVSNet_eth95.91 17695.73 17996.44 18098.48 15091.52 19395.31 20798.45 15595.76 13397.48 15697.54 18189.53 24998.69 30894.43 15994.61 33599.13 138
view60092.56 26892.11 26893.91 28198.45 15284.76 31097.10 10490.23 34297.42 7496.98 17894.48 30173.62 32699.60 14182.49 33098.28 24997.36 283
view80092.56 26892.11 26893.91 28198.45 15284.76 31097.10 10490.23 34297.42 7496.98 17894.48 30173.62 32699.60 14182.49 33098.28 24997.36 283
conf0.05thres100092.56 26892.11 26893.91 28198.45 15284.76 31097.10 10490.23 34297.42 7496.98 17894.48 30173.62 32699.60 14182.49 33098.28 24997.36 283
tfpn92.56 26892.11 26893.91 28198.45 15284.76 31097.10 10490.23 34297.42 7496.98 17894.48 30173.62 32699.60 14182.49 33098.28 24997.36 283
v114496.84 13297.08 11896.13 20598.42 15689.28 23595.41 19998.67 13094.21 19597.97 12398.31 10193.06 18299.65 11698.06 3499.62 8099.45 73
plane_prior698.38 15794.37 12091.91 219
FPMVS89.92 31288.63 31993.82 28698.37 15896.94 4091.58 32493.34 31288.00 29290.32 34197.10 20870.87 34191.13 35971.91 35596.16 32293.39 348
PAPM_NR94.61 22694.17 23395.96 21498.36 15991.23 19595.93 17197.95 21492.98 23093.42 30794.43 30690.53 23598.38 32987.60 29596.29 32098.27 239
MVS_111021_HR96.73 14396.54 14897.27 13398.35 16093.66 14893.42 29198.36 17094.74 17596.58 19596.76 23196.54 6598.99 27794.87 14499.27 17599.15 135
TAMVS95.49 18994.94 20097.16 13798.31 16193.41 15595.07 22396.82 26991.09 26297.51 15197.82 16089.96 24499.42 20088.42 27999.44 13398.64 204
OMC-MVS96.48 15696.00 16997.91 8598.30 16296.01 6894.86 23498.60 14391.88 25497.18 16797.21 20296.11 8099.04 27090.49 24999.34 16198.69 202
新几何197.25 13698.29 16394.70 11097.73 22877.98 35094.83 25596.67 23692.08 21299.45 19488.17 28398.65 23397.61 276
jason94.39 23294.04 23695.41 23798.29 16387.85 27092.74 30796.75 27185.38 31995.29 24496.15 26288.21 26199.65 11694.24 16999.34 16198.74 198
jason: jason.
no-one94.84 21694.76 20995.09 24698.29 16387.49 27791.82 32297.49 24488.21 28897.84 14498.75 6691.51 22499.27 24588.96 27199.99 298.52 214
v119296.83 13597.06 12096.15 20198.28 16689.29 23495.36 20298.77 10793.73 21198.11 10598.34 9793.02 18799.67 11098.35 2799.58 9299.50 52
CDPH-MVS95.45 19594.65 21297.84 8998.28 16694.96 10193.73 28098.33 17585.03 32195.44 24196.60 23995.31 11199.44 19890.01 25699.13 18799.11 146
conf0.0191.90 28490.98 28994.67 25998.27 16888.03 26296.98 11488.58 35093.90 20394.64 25991.45 33769.62 34599.52 16587.62 28997.74 27396.46 314
conf0.00291.90 28490.98 28994.67 25998.27 16888.03 26296.98 11488.58 35093.90 20394.64 25991.45 33769.62 34599.52 16587.62 28997.74 27396.46 314
thresconf0.0291.72 29190.98 28993.97 27798.27 16888.03 26296.98 11488.58 35093.90 20394.64 25991.45 33769.62 34599.52 16587.62 28997.74 27394.35 340
tfpn_n40091.72 29190.98 28993.97 27798.27 16888.03 26296.98 11488.58 35093.90 20394.64 25991.45 33769.62 34599.52 16587.62 28997.74 27394.35 340
tfpnconf91.72 29190.98 28993.97 27798.27 16888.03 26296.98 11488.58 35093.90 20394.64 25991.45 33769.62 34599.52 16587.62 28997.74 27394.35 340
tfpnview1191.72 29190.98 28993.97 27798.27 16888.03 26296.98 11488.58 35093.90 20394.64 25991.45 33769.62 34599.52 16587.62 28997.74 27394.35 340
MVS_111021_LR96.82 13696.55 14697.62 10398.27 16895.34 8893.81 27898.33 17594.59 18096.56 19796.63 23896.61 6398.73 30494.80 14899.34 16198.78 195
CLD-MVS95.47 19295.07 19696.69 16498.27 16892.53 16791.36 32898.67 13091.22 26195.78 23494.12 31095.65 9998.98 27990.81 23599.72 6098.57 210
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
112194.26 23393.26 24997.27 13398.26 17694.73 10795.86 17397.71 23077.96 35194.53 26796.71 23391.93 21799.40 21487.71 28598.64 23497.69 273
Anonymous20240521196.34 16295.98 17197.43 12498.25 17793.85 13996.74 12594.41 30097.72 5798.37 7998.03 13987.15 27199.53 16194.06 17399.07 19598.92 174
pmmvs-eth3d96.49 15596.18 16297.42 12598.25 17794.29 12294.77 23998.07 21089.81 27497.97 12398.33 9993.11 18199.08 26695.46 12199.84 4198.89 179
v14419296.69 14796.90 12896.03 21198.25 17788.92 24395.49 19098.77 10793.05 22898.09 10998.29 10592.51 20299.70 8898.11 3299.56 9899.47 66
ambc96.56 17498.23 18091.68 19197.88 5898.13 20398.42 7798.56 8194.22 14999.04 27094.05 17699.35 15998.95 165
testmv95.51 18795.33 18996.05 20798.23 18089.51 22793.50 28998.63 14094.25 19398.22 9597.73 16992.51 20299.47 18585.22 31599.72 6099.17 131
tfpn11191.92 28391.39 27893.49 29398.21 18284.50 31596.39 13690.39 33796.87 9196.33 20793.08 31873.44 33299.51 17579.87 33897.94 26696.46 314
conf200view1191.81 28891.26 28393.46 29498.21 18284.50 31596.39 13690.39 33796.87 9196.33 20793.08 31873.44 33299.42 20078.85 34397.74 27396.46 314
thres100view90091.76 29091.26 28393.26 29898.21 18284.50 31596.39 13690.39 33796.87 9196.33 20793.08 31873.44 33299.42 20078.85 34397.74 27395.85 324
v192192096.72 14496.96 12595.99 21298.21 18288.79 24995.42 19798.79 10393.22 22098.19 9898.26 10992.68 19399.70 8898.34 2899.55 10299.49 60
thres600view792.03 28191.43 27793.82 28698.19 18684.61 31496.27 14590.39 33796.81 9596.37 20693.11 31673.44 33299.49 18080.32 33797.95 26397.36 283
PatchMatch-RL94.61 22693.81 24197.02 14898.19 18695.72 7393.66 28297.23 25388.17 28994.94 25295.62 28091.43 22698.57 31687.36 29997.68 28696.76 305
LF4IMVS96.07 17195.63 18297.36 12998.19 18695.55 8095.44 19298.82 10192.29 24695.70 23896.55 24192.63 19698.69 30891.75 21899.33 16697.85 267
v124096.74 14197.02 12295.91 21998.18 18988.52 25295.39 20098.88 8193.15 22698.46 7498.40 9392.80 19099.71 8098.45 2699.49 12199.49 60
TAPA-MVS93.32 1294.93 21494.23 22997.04 14598.18 18994.51 11495.22 21498.73 11481.22 33896.25 21795.95 27293.80 16598.98 27989.89 25798.87 21597.62 275
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
test22298.17 19193.24 15992.74 30797.61 24275.17 35594.65 25896.69 23590.96 23298.66 23297.66 274
MIMVSNet93.42 25792.86 25695.10 24598.17 19188.19 25798.13 4493.69 30592.07 24795.04 25098.21 11580.95 29499.03 27381.42 33598.06 26098.07 253
原ACMM196.58 17198.16 19392.12 17898.15 20185.90 31193.49 30296.43 25092.47 20499.38 22587.66 28898.62 23598.23 243
testdata95.70 22798.16 19390.58 20697.72 22980.38 34195.62 23997.02 21292.06 21398.98 27989.06 27098.52 24197.54 279
MVP-Stereo95.69 18095.28 19096.92 15198.15 19593.03 16195.64 18798.20 19390.39 26896.63 19497.73 16991.63 22299.10 26491.84 21497.31 30398.63 206
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
SD-MVS97.37 10097.70 6796.35 18498.14 19695.13 9696.54 13198.92 7595.94 12599.19 3198.08 13197.74 2195.06 35695.24 12999.54 10498.87 185
EU-MVSNet94.25 23494.47 22193.60 29098.14 19682.60 32697.24 9692.72 32085.08 32098.48 7198.94 5582.59 28998.76 30297.47 5999.53 10799.44 82
NP-MVS98.14 19693.72 14495.08 288
LCM-MVSNet-Re97.33 10497.33 9497.32 13198.13 19993.79 14296.99 11399.65 296.74 9799.47 1398.93 5696.91 4899.84 2790.11 25499.06 19898.32 233
3Dnovator+96.13 397.73 7497.59 8098.15 7198.11 20095.60 7898.04 4998.70 12498.13 4096.93 18598.45 8995.30 11299.62 12895.64 11398.96 20499.24 123
Test495.39 19795.24 19195.82 22298.07 20189.60 22294.40 24798.49 15291.39 26097.40 16196.32 25687.32 27099.41 21195.09 14198.71 23098.44 220
VNet96.84 13296.83 13296.88 15498.06 20292.02 18196.35 14297.57 24397.70 5997.88 13697.80 16292.40 20599.54 15994.73 15398.96 20499.08 151
DI_MVS_plusplus_test95.46 19395.43 18795.55 23198.05 20388.84 24794.18 25995.75 28691.92 25397.32 16296.94 21691.44 22599.39 22094.81 14798.48 24498.43 221
LFMVS95.32 20194.88 20496.62 16698.03 20491.47 19497.65 7390.72 33699.11 897.89 13498.31 10179.20 29999.48 18393.91 18299.12 19098.93 171
tfpn200view991.55 29691.00 28793.21 30098.02 20584.35 31995.70 17990.79 33496.26 11295.90 23192.13 33373.62 32699.42 20078.85 34397.74 27395.85 324
thres40091.68 29591.00 28793.71 28898.02 20584.35 31995.70 17990.79 33496.26 11295.90 23192.13 33373.62 32699.42 20078.85 34397.74 27397.36 283
xiu_mvs_v1_base_debu95.62 18395.96 17294.60 26398.01 20788.42 25393.99 26998.21 19092.98 23095.91 22894.53 29896.39 7399.72 6995.43 12398.19 25595.64 328
xiu_mvs_v1_base95.62 18395.96 17294.60 26398.01 20788.42 25393.99 26998.21 19092.98 23095.91 22894.53 29896.39 7399.72 6995.43 12398.19 25595.64 328
xiu_mvs_v1_base_debi95.62 18395.96 17294.60 26398.01 20788.42 25393.99 26998.21 19092.98 23095.91 22894.53 29896.39 7399.72 6995.43 12398.19 25595.64 328
casdiffmvs196.82 13696.84 13096.77 15898.01 20792.02 18197.20 9898.67 13092.30 24596.09 22398.64 7693.81 16399.50 17798.22 3098.62 23598.79 192
CNVR-MVS96.92 12596.55 14698.03 7998.00 21195.54 8194.87 23398.17 19894.60 17896.38 20597.05 21095.67 9899.36 22995.12 13999.08 19399.19 128
PLCcopyleft91.02 1694.05 24592.90 25597.51 11198.00 21195.12 9794.25 25398.25 18886.17 30791.48 33295.25 28691.01 23099.19 25385.02 31796.69 31498.22 244
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
test_normal95.51 18795.46 18695.68 22897.97 21389.12 23993.73 28095.86 28491.98 25097.17 16896.94 21691.55 22399.42 20095.21 13098.73 22898.51 215
tfpn100091.88 28791.20 28593.89 28597.96 21487.13 28597.13 10288.16 35794.41 18694.87 25492.77 32568.34 35299.47 18589.24 26597.95 26395.06 334
GBi-Net96.99 11596.80 13497.56 10697.96 21493.67 14598.23 3598.66 13395.59 13997.99 11999.19 3289.51 25099.73 6394.60 15599.44 13399.30 111
test196.99 11596.80 13497.56 10697.96 21493.67 14598.23 3598.66 13395.59 13997.99 11999.19 3289.51 25099.73 6394.60 15599.44 13399.30 111
FMVSNet296.72 14496.67 14096.87 15597.96 21491.88 18697.15 9998.06 21195.59 13998.50 7098.62 7789.51 25099.65 11694.99 14399.60 8899.07 153
BH-untuned94.69 22294.75 21094.52 26897.95 21887.53 27694.07 26697.01 26293.99 20097.10 17295.65 27892.65 19598.95 28487.60 29596.74 31397.09 291
QAPM95.88 17895.57 18396.80 15697.90 21991.84 18898.18 4298.73 11488.41 28496.42 20398.13 12694.73 12499.75 5388.72 27498.94 20898.81 190
TinyColmap96.00 17496.34 15894.96 24997.90 21987.91 26894.13 26498.49 15294.41 18698.16 10097.76 16396.29 7898.68 31190.52 24699.42 14398.30 236
HQP-NCC97.85 22194.26 25093.18 22292.86 316
ACMP_Plane97.85 22194.26 25093.18 22292.86 316
N_pmnet95.18 20694.23 22998.06 7597.85 22196.55 5292.49 31191.63 32889.34 27698.09 10997.41 19090.33 23899.06 26891.58 22099.31 16898.56 211
HQP-MVS95.17 20794.58 21796.92 15197.85 22192.47 16894.26 25098.43 15993.18 22292.86 31695.08 28890.33 23899.23 25190.51 24798.74 22599.05 156
TEST997.84 22595.23 9093.62 28498.39 16686.81 30293.78 28995.99 26794.68 12999.52 165
train_agg95.46 19394.66 21197.88 8697.84 22595.23 9093.62 28498.39 16687.04 30093.78 28995.99 26794.58 13499.52 16591.76 21698.90 21098.89 179
MSLP-MVS++96.42 16196.71 13895.57 23097.82 22790.56 20895.71 17898.84 8994.72 17696.71 19297.39 19494.91 12298.10 34095.28 12799.02 20098.05 257
test_897.81 22895.07 9893.54 28798.38 16887.04 30093.71 29395.96 27194.58 13499.52 165
NCCC96.52 15495.99 17098.10 7397.81 22895.68 7595.00 22998.20 19395.39 14795.40 24396.36 25493.81 16399.45 19493.55 19098.42 24699.17 131
WTY-MVS93.55 25593.00 25495.19 24197.81 22887.86 26993.89 27496.00 27989.02 27894.07 28095.44 28486.27 27499.33 23587.69 28796.82 31098.39 224
CNLPA95.04 21194.47 22196.75 16097.81 22895.25 8994.12 26597.89 21894.41 18694.57 26595.69 27690.30 24198.35 33286.72 30498.76 22396.64 309
agg_prior395.30 20294.46 22497.80 9197.80 23295.00 9993.63 28398.34 17486.33 30693.40 30995.84 27494.15 15299.50 17791.76 21698.90 21098.89 179
agg_prior195.39 19794.60 21597.75 9397.80 23294.96 10193.39 29298.36 17087.20 29893.49 30295.97 27094.65 13199.53 16191.69 21998.86 21798.77 196
agg_prior97.80 23294.96 10198.36 17093.49 30299.53 161
旧先验197.80 23293.87 13797.75 22697.04 21193.57 17098.68 23198.72 200
PCF-MVS89.43 1892.12 28090.64 30196.57 17397.80 23293.48 15489.88 34498.45 15574.46 35696.04 22595.68 27790.71 23499.31 23773.73 35199.01 20296.91 299
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
test_prior395.91 17695.39 18897.46 12097.79 23794.26 12693.33 29598.42 16294.21 19594.02 28296.25 25893.64 16899.34 23291.90 21098.96 20498.79 192
test_prior97.46 12097.79 23794.26 12698.42 16299.34 23298.79 192
PVSNet_BlendedMVS95.02 21394.93 20295.27 23997.79 23787.40 28094.14 26398.68 12788.94 28094.51 26898.01 14193.04 18399.30 23989.77 25999.49 12199.11 146
PVSNet_Blended93.96 24693.65 24394.91 25097.79 23787.40 28091.43 32798.68 12784.50 32594.51 26894.48 30193.04 18399.30 23989.77 25998.61 23798.02 262
USDC94.56 22894.57 21994.55 26797.78 24186.43 29392.75 30598.65 13985.96 30996.91 18697.93 15190.82 23398.74 30390.71 24199.59 9098.47 217
alignmvs96.01 17395.52 18497.50 11497.77 24294.71 10996.07 15696.84 26797.48 7296.78 19194.28 30985.50 27899.40 21496.22 9098.73 22898.40 222
TSAR-MVS + GP.96.47 15796.12 16397.49 11797.74 24395.23 9094.15 26296.90 26693.26 21998.04 11696.70 23494.41 14098.89 28894.77 15199.14 18598.37 226
3Dnovator96.53 297.61 8497.64 7497.50 11497.74 24393.65 14998.49 2398.88 8196.86 9497.11 17198.55 8295.82 8999.73 6395.94 10299.42 14399.13 138
tfpn_ndepth90.98 30290.24 30793.20 30297.72 24587.18 28496.52 13288.20 35692.63 23993.69 29590.70 35068.22 35399.42 20086.98 30197.47 29893.00 350
sss94.22 23593.72 24295.74 22497.71 24689.95 21593.84 27696.98 26388.38 28793.75 29195.74 27587.94 26298.89 28891.02 22898.10 25998.37 226
DeepC-MVS_fast94.34 796.74 14196.51 15197.44 12397.69 24794.15 12996.02 15998.43 15993.17 22597.30 16397.38 19695.48 10499.28 24393.74 18699.34 16198.88 183
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
semantic-postprocess94.85 25497.68 24885.53 29797.63 24096.99 8798.36 8198.54 8387.44 26899.75 5397.07 7399.08 19399.27 121
MVSFormer96.14 16996.36 15795.49 23497.68 24887.81 27298.67 1399.02 5196.50 10394.48 27096.15 26286.90 27299.92 498.73 1799.13 18798.74 198
lupinMVS93.77 24893.28 24895.24 24097.68 24887.81 27292.12 31796.05 27884.52 32494.48 27095.06 29086.90 27299.63 12293.62 18999.13 18798.27 239
Fast-Effi-MVS+95.49 18995.07 19696.75 16097.67 25192.82 16394.22 25698.60 14391.61 25693.42 30792.90 32396.73 6099.70 8892.60 20297.89 27097.74 272
canonicalmvs97.23 11097.21 10797.30 13297.65 25294.39 11897.84 6199.05 3897.42 7496.68 19393.85 31297.63 2599.33 23596.29 8998.47 24598.18 249
CDS-MVSNet94.88 21594.12 23497.14 13997.64 25393.57 15093.96 27297.06 26190.05 27296.30 21496.55 24186.10 27599.47 18590.10 25599.31 16898.40 222
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
pmmvs594.63 22594.34 22795.50 23397.63 25488.34 25694.02 26797.13 25887.15 29995.22 24697.15 20487.50 26799.27 24593.99 17899.26 17698.88 183
test1297.46 12097.61 25594.07 13197.78 22593.57 30093.31 17899.42 20098.78 22198.89 179
PMMVS293.66 25294.07 23592.45 31597.57 25680.67 33486.46 35196.00 27993.99 20097.10 17297.38 19689.90 24597.82 34388.76 27399.47 12698.86 186
BH-RMVSNet94.56 22894.44 22594.91 25097.57 25687.44 27993.78 27996.26 27693.69 21396.41 20496.50 24692.10 21199.00 27685.96 30797.71 28398.31 234
PVSNet86.72 1991.10 29990.97 29591.49 32297.56 25878.04 34387.17 34994.60 29884.65 32392.34 32592.20 33287.37 26998.47 32285.17 31697.69 28597.96 264
DELS-MVS96.17 16896.23 16195.99 21297.55 25990.04 21292.38 31498.52 14994.13 19896.55 20097.06 20994.99 12099.58 14795.62 11499.28 17398.37 226
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
IterMVS95.42 19695.83 17694.20 27597.52 26083.78 32392.41 31397.47 24995.49 14398.06 11498.49 8687.94 26299.58 14796.02 9899.02 20099.23 124
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
casdiffmvs96.43 16096.38 15596.60 16797.51 26191.95 18597.08 11098.41 16493.69 21393.95 28698.34 9793.03 18599.45 19498.09 3397.30 30498.39 224
new-patchmatchnet95.67 18296.58 14392.94 30897.48 26280.21 33592.96 30198.19 19794.83 17298.82 4898.79 6293.31 17899.51 17595.83 10599.04 19999.12 143
MDA-MVSNet_test_wron94.73 21994.83 20894.42 26997.48 26285.15 30390.28 33995.87 28392.52 24097.48 15697.76 16391.92 21899.17 25793.32 19196.80 31298.94 167
PHI-MVS96.96 12296.53 14998.25 6897.48 26296.50 5396.76 12498.85 8693.52 21696.19 22096.85 22295.94 8399.42 20093.79 18599.43 14098.83 189
DeepPCF-MVS94.58 596.90 12796.43 15398.31 6397.48 26297.23 3592.56 31098.60 14392.84 23798.54 6697.40 19196.64 6298.78 30094.40 16299.41 14998.93 171
thres20091.00 30190.42 30592.77 31097.47 26683.98 32294.01 26891.18 33295.12 16495.44 24191.21 34573.93 32299.31 23777.76 34797.63 29195.01 335
YYNet194.73 21994.84 20694.41 27097.47 26685.09 30590.29 33895.85 28592.52 24097.53 15097.76 16391.97 21499.18 25493.31 19296.86 30998.95 165
Effi-MVS+96.19 16796.01 16896.71 16297.43 26892.19 17796.12 15599.10 2595.45 14493.33 31094.71 29697.23 4099.56 15393.21 19697.54 29398.37 226
pmmvs494.82 21894.19 23296.70 16397.42 26992.75 16592.09 31996.76 27086.80 30395.73 23797.22 20189.28 25398.89 28893.28 19399.14 18598.46 219
MSDG95.33 20095.13 19495.94 21897.40 27091.85 18791.02 33198.37 16995.30 14996.31 21395.99 26794.51 13898.38 32989.59 26197.65 28997.60 277
EI-MVSNet-Vis-set97.32 10597.39 9197.11 14097.36 27192.08 18095.34 20497.65 23697.74 5398.29 9198.11 12995.05 11799.68 10397.50 5699.50 11499.56 42
PS-MVSNAJ94.10 24294.47 22193.00 30697.35 27284.88 30791.86 32197.84 22191.96 25194.17 27592.50 33095.82 8999.71 8091.27 22497.48 29694.40 339
Regformer-397.25 10997.29 9697.11 14097.35 27292.32 17195.26 21197.62 24197.67 6298.17 9997.89 15495.05 11799.56 15397.16 6999.42 14399.46 68
Regformer-497.53 9197.47 8997.71 9597.35 27293.91 13695.26 21198.14 20297.97 4698.34 8397.89 15495.49 10399.71 8097.41 6099.42 14399.51 51
EI-MVSNet-UG-set97.32 10597.40 9097.09 14297.34 27592.01 18395.33 20597.65 23697.74 5398.30 9098.14 12595.04 11999.69 9797.55 5399.52 11199.58 37
AdaColmapbinary95.11 20894.62 21496.58 17197.33 27694.45 11794.92 23198.08 20893.15 22693.98 28595.53 28394.34 14399.10 26485.69 31098.61 23796.20 321
xiu_mvs_v2_base94.22 23594.63 21392.99 30797.32 27784.84 30892.12 31797.84 22191.96 25194.17 27593.43 31396.07 8199.71 8091.27 22497.48 29694.42 338
OpenMVS_ROBcopyleft91.80 1493.64 25393.05 25295.42 23597.31 27891.21 19695.08 22296.68 27481.56 33596.88 18896.41 25190.44 23799.25 24885.39 31497.67 28795.80 326
EI-MVSNet96.63 15096.93 12695.74 22497.26 27988.13 26095.29 20997.65 23696.99 8797.94 12698.19 11692.55 19899.58 14796.91 7699.56 9899.50 52
CVMVSNet92.33 27692.79 25890.95 32897.26 27975.84 35095.29 20992.33 32381.86 33396.27 21598.19 11681.44 29198.46 32394.23 17098.29 24898.55 213
Regformer-197.27 10797.16 11097.61 10497.21 28193.86 13894.85 23598.04 21397.62 6498.03 11797.50 18695.34 10999.63 12296.52 8299.31 16899.35 105
Regformer-297.41 9797.24 10197.93 8497.21 28194.72 10894.85 23598.27 18597.74 5398.11 10597.50 18695.58 10199.69 9796.57 8199.31 16899.37 103
Fast-Effi-MVS+-dtu96.44 15896.12 16397.39 12897.18 28394.39 11895.46 19198.73 11496.03 12194.72 25694.92 29496.28 7999.69 9793.81 18497.98 26298.09 250
OpenMVScopyleft94.22 895.48 19195.20 19296.32 18797.16 28491.96 18497.74 6998.84 8987.26 29694.36 27298.01 14193.95 15799.67 11090.70 24298.75 22497.35 289
BH-w/o92.14 27991.94 27292.73 31197.13 28585.30 30092.46 31295.64 28989.33 27794.21 27492.74 32789.60 24698.24 33581.68 33494.66 33494.66 337
MG-MVS94.08 24494.00 23894.32 27297.09 28685.89 29493.19 29995.96 28192.52 24094.93 25397.51 18589.54 24798.77 30187.52 29797.71 28398.31 234
MVS_030496.22 16595.94 17597.04 14597.07 28792.54 16694.19 25899.04 4595.17 15893.74 29296.92 21991.77 22199.73 6395.76 10799.81 4498.85 188
MVS-HIRNet88.40 32290.20 30882.99 34697.01 28860.04 36493.11 30085.61 35984.45 32688.72 34999.09 4684.72 28498.23 33682.52 32996.59 31690.69 356
GA-MVS92.83 26592.15 26794.87 25396.97 28987.27 28390.03 34096.12 27791.83 25594.05 28194.57 29776.01 31798.97 28392.46 20597.34 30298.36 231
0601test94.40 23194.00 23895.59 22996.95 29089.52 22694.75 24095.55 29296.18 11696.79 18996.14 26481.09 29399.18 25490.75 23897.77 27198.07 253
test123567892.95 26392.40 26394.61 26296.95 29086.87 28890.75 33397.75 22691.00 26496.33 20795.38 28585.21 28098.92 28579.00 34199.20 18098.03 260
MVS_Test96.27 16396.79 13694.73 25896.94 29286.63 29196.18 15298.33 17594.94 16896.07 22498.28 10695.25 11499.26 24797.21 6597.90 26998.30 236
MAR-MVS94.21 23893.03 25397.76 9296.94 29297.44 3096.97 12097.15 25787.89 29492.00 32892.73 32892.14 20999.12 25983.92 32397.51 29596.73 306
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
Effi-MVS+-dtu96.81 13896.09 16598.99 1096.90 29498.69 296.42 13598.09 20695.86 12895.15 24795.54 28294.26 14799.81 3294.06 17398.51 24398.47 217
mvs-test196.20 16695.50 18598.32 6196.90 29498.16 495.07 22398.09 20695.86 12893.63 29694.32 30894.26 14799.71 8094.06 17397.27 30697.07 292
MS-PatchMatch94.83 21794.91 20394.57 26696.81 29687.10 28694.23 25597.34 25088.74 28297.14 16997.11 20791.94 21698.23 33692.99 20097.92 26798.37 226
UGNet96.81 13896.56 14597.58 10596.64 29793.84 14097.75 6797.12 25996.47 10693.62 29798.88 5993.22 18099.53 16195.61 11599.69 6899.36 104
Wanjuan Su, Qingshan Xu, Wenbing Tao: Uncertainty-guided Multi-view Stereo Network for Depth Estimation. IEEE Transactions on Circuits and Systems for Video Technology, 2022
API-MVS95.09 21095.01 19995.31 23896.61 29894.02 13396.83 12297.18 25695.60 13895.79 23394.33 30794.54 13698.37 33185.70 30998.52 24193.52 346
PAPM87.64 32985.84 33293.04 30496.54 29984.99 30688.42 34895.57 29179.52 34483.82 35893.05 32280.57 29598.41 32562.29 35992.79 34195.71 327
FMVSNet395.26 20594.94 20096.22 19796.53 30090.06 21195.99 16197.66 23494.11 19997.99 11997.91 15380.22 29799.63 12294.60 15599.44 13398.96 164
diffmvs96.10 17096.43 15395.12 24396.52 30187.85 27095.95 17097.91 21596.52 10293.02 31398.25 11094.28 14599.28 24397.11 7198.26 25398.24 242
HY-MVS91.43 1592.58 26791.81 27594.90 25296.49 30288.87 24597.31 9194.62 29785.92 31090.50 34096.84 22385.05 28199.40 21483.77 32695.78 32696.43 318
TR-MVS92.54 27292.20 26693.57 29196.49 30286.66 29093.51 28894.73 29689.96 27394.95 25193.87 31190.24 24398.61 31481.18 33694.88 33295.45 332
CANet95.86 17995.65 18196.49 17796.41 30490.82 20294.36 24898.41 16494.94 16892.62 32396.73 23292.68 19399.71 8095.12 13999.60 8898.94 167
mvs_anonymous95.36 19996.07 16793.21 30096.29 30581.56 32994.60 24397.66 23493.30 21896.95 18498.91 5893.03 18599.38 22596.60 7997.30 30498.69 202
Patchmatch-test193.38 25993.59 24492.73 31196.24 30681.40 33093.24 29794.00 30391.58 25894.57 26596.67 23687.94 26299.03 27390.42 25097.66 28897.77 271
LS3D97.77 7297.50 8798.57 4396.24 30697.58 2198.45 2698.85 8698.58 2597.51 15197.94 14995.74 9799.63 12295.19 13198.97 20398.51 215
new_pmnet92.34 27591.69 27694.32 27296.23 30889.16 23792.27 31592.88 31784.39 32795.29 24496.35 25585.66 27796.74 35384.53 32097.56 29297.05 293
MVEpermissive73.61 2286.48 33185.92 33188.18 34096.23 30885.28 30181.78 35975.79 36386.01 30882.53 36091.88 33592.74 19187.47 36171.42 35694.86 33391.78 352
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
DSMNet-mixed92.19 27891.83 27493.25 29996.18 31083.68 32496.27 14593.68 30776.97 35492.54 32499.18 3589.20 25598.55 31983.88 32498.60 23997.51 280
our_test_394.20 24094.58 21793.07 30396.16 31181.20 33190.42 33796.84 26790.72 26697.14 16997.13 20590.47 23699.11 26294.04 17798.25 25498.91 175
ppachtmachnet_test94.49 23094.84 20693.46 29496.16 31182.10 32890.59 33597.48 24690.53 26797.01 17697.59 17991.01 23099.36 22993.97 18099.18 18398.94 167
Patchmatch-test93.60 25493.25 25094.63 26196.14 31387.47 27896.04 15894.50 29993.57 21596.47 20196.97 21476.50 31398.61 31490.67 24398.41 24797.81 270
testus90.90 30490.51 30392.06 31996.07 31479.45 33788.99 34598.44 15885.46 31694.15 27790.77 34789.12 25698.01 34273.66 35297.95 26398.71 201
PNet_i23d83.82 33483.39 33485.10 34596.07 31465.16 36081.87 35894.37 30190.87 26593.92 28792.89 32452.80 36596.44 35577.52 34970.22 35993.70 345
wuyk23d93.25 26195.20 19287.40 34296.07 31495.38 8697.04 11194.97 29495.33 14899.70 598.11 12998.14 1391.94 35877.76 34799.68 7274.89 358
CANet_DTU94.65 22494.21 23195.96 21495.90 31789.68 21893.92 27397.83 22393.19 22190.12 34395.64 27988.52 25799.57 15293.27 19499.47 12698.62 207
test1235687.98 32688.41 32186.69 34495.84 31863.49 36187.15 35097.32 25187.21 29791.78 33193.36 31470.66 34398.39 32774.70 35097.64 29098.19 247
MVSTER94.21 23893.93 24095.05 24895.83 31986.46 29295.18 21697.65 23692.41 24497.94 12698.00 14372.39 33699.58 14796.36 8899.56 9899.12 143
FMVSNet593.39 25892.35 26496.50 17695.83 31990.81 20497.31 9198.27 18592.74 23896.27 21598.28 10662.23 35799.67 11090.86 23399.36 15599.03 157
PVSNet_081.89 2184.49 33383.21 33688.34 33995.76 32174.97 35383.49 35592.70 32178.47 34987.94 35286.90 35883.38 28796.63 35473.44 35366.86 36093.40 347
PAPR92.22 27791.27 28295.07 24795.73 32288.81 24891.97 32097.87 21985.80 31290.91 33492.73 32891.16 22898.33 33379.48 33995.76 32798.08 251
CHOSEN 280x42089.98 31089.19 31692.37 31695.60 32381.13 33286.22 35297.09 26081.44 33787.44 35493.15 31573.99 32199.47 18588.69 27599.07 19596.52 313
ADS-MVSNet291.47 29790.51 30394.36 27195.51 32485.63 29595.05 22695.70 28783.46 32992.69 31996.84 22379.15 30099.41 21185.66 31190.52 34598.04 258
ADS-MVSNet90.95 30390.26 30693.04 30495.51 32482.37 32795.05 22693.41 31183.46 32992.69 31996.84 22379.15 30098.70 30785.66 31190.52 34598.04 258
CR-MVSNet93.29 26092.79 25894.78 25695.44 32688.15 25896.18 15297.20 25484.94 32294.10 27898.57 7977.67 30599.39 22095.17 13395.81 32396.81 303
RPMNet94.22 23594.03 23794.78 25695.44 32688.15 25896.18 15293.73 30497.43 7394.10 27898.49 8679.40 29899.39 22095.69 10895.81 32396.81 303
131492.38 27492.30 26592.64 31395.42 32885.15 30395.86 17396.97 26485.40 31890.62 33693.06 32191.12 22997.80 34486.74 30395.49 33194.97 336
tpm91.08 30090.85 29791.75 32195.33 32978.09 34195.03 22891.27 33188.75 28193.53 30197.40 19171.24 33999.30 23991.25 22693.87 33797.87 266
IB-MVS85.98 2088.63 31986.95 32893.68 28995.12 33084.82 30990.85 33290.17 34687.55 29588.48 35091.34 34458.01 35999.59 14587.24 30093.80 33896.63 311
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
PatchT93.75 24993.57 24594.29 27495.05 33187.32 28296.05 15792.98 31597.54 6894.25 27398.72 6875.79 31899.24 24995.92 10395.81 32396.32 319
tpm288.47 32087.69 32390.79 32994.98 33277.34 34695.09 22091.83 32677.51 35389.40 34696.41 25167.83 35498.73 30483.58 32892.60 34396.29 320
Patchmtry95.03 21294.59 21696.33 18694.83 33390.82 20296.38 14097.20 25496.59 10097.49 15398.57 7977.67 30599.38 22592.95 20199.62 8098.80 191
MVS90.02 30889.20 31592.47 31494.71 33486.90 28795.86 17396.74 27264.72 35990.62 33692.77 32592.54 20098.39 32779.30 34095.56 33092.12 351
CostFormer89.75 31389.25 31291.26 32594.69 33578.00 34495.32 20691.98 32581.50 33690.55 33896.96 21571.06 34098.89 28888.59 27792.63 34296.87 300
PatchmatchNetpermissive91.98 28291.87 27392.30 31794.60 33679.71 33695.12 21793.59 31089.52 27593.61 29897.02 21277.94 30399.18 25490.84 23494.57 33698.01 263
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
tpmp4_e2388.46 32187.54 32491.22 32694.56 33778.08 34295.63 18893.17 31379.08 34785.85 35696.80 22765.86 35698.85 29584.10 32292.85 34096.72 307
LP93.12 26292.78 26094.14 27694.50 33885.48 29895.73 17795.68 28892.97 23495.05 24997.17 20381.93 29099.40 21493.06 19988.96 35097.55 278
tpm cat188.01 32587.33 32590.05 33494.48 33976.28 34994.47 24694.35 30273.84 35889.26 34795.61 28173.64 32598.30 33484.13 32186.20 35495.57 331
MDTV_nov1_ep1391.28 28194.31 34073.51 35494.80 23793.16 31486.75 30493.45 30597.40 19176.37 31498.55 31988.85 27296.43 317
cascas91.89 28691.35 28093.51 29294.27 34185.60 29688.86 34798.61 14279.32 34592.16 32791.44 34389.22 25498.12 33990.80 23697.47 29896.82 302
test-LLR89.97 31189.90 30990.16 33294.24 34274.98 35189.89 34189.06 34792.02 24889.97 34490.77 34773.92 32398.57 31691.88 21297.36 30096.92 297
test-mter87.92 32787.17 32690.16 33294.24 34274.98 35189.89 34189.06 34786.44 30589.97 34490.77 34754.96 36398.57 31691.88 21297.36 30096.92 297
pmmvs390.00 30988.90 31893.32 29694.20 34485.34 29991.25 32992.56 32278.59 34893.82 28895.17 28767.36 35598.69 30889.08 26998.03 26195.92 322
tpmrst90.31 30690.61 30289.41 33594.06 34572.37 35795.06 22593.69 30588.01 29192.32 32696.86 22177.45 30798.82 29691.04 22787.01 35397.04 294
test0.0.03 190.11 30789.21 31492.83 30993.89 34686.87 28891.74 32388.74 34992.02 24894.71 25791.14 34673.92 32394.48 35783.75 32792.94 33997.16 290
JIA-IIPM91.79 28990.69 30095.11 24493.80 34790.98 19894.16 26191.78 32796.38 10790.30 34299.30 2372.02 33898.90 28688.28 28190.17 34795.45 332
TESTMET0.1,187.20 33086.57 33089.07 33693.62 34872.84 35689.89 34187.01 35885.46 31689.12 34890.20 35256.00 36297.72 34590.91 23296.92 30796.64 309
PatchFormer-LS_test89.62 31489.12 31791.11 32793.62 34878.42 34094.57 24593.62 30988.39 28690.54 33988.40 35572.33 33799.03 27392.41 20688.20 35195.89 323
CMPMVSbinary73.10 2392.74 26691.39 27896.77 15893.57 35094.67 11194.21 25797.67 23280.36 34293.61 29896.60 23982.85 28897.35 34784.86 31898.78 22198.29 238
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
DWT-MVSNet_test87.92 32786.77 32991.39 32393.18 35178.62 33995.10 21891.42 32985.58 31388.00 35188.73 35460.60 35898.90 28690.60 24487.70 35296.65 308
E-PMN89.52 31589.78 31088.73 33793.14 35277.61 34583.26 35692.02 32494.82 17393.71 29393.11 31675.31 31996.81 35185.81 30896.81 31191.77 353
PMMVS92.39 27391.08 28696.30 18993.12 35392.81 16490.58 33695.96 28179.17 34691.85 33092.27 33190.29 24298.66 31389.85 25896.68 31597.43 281
EMVS89.06 31789.22 31388.61 33893.00 35477.34 34682.91 35790.92 33394.64 17792.63 32291.81 33676.30 31597.02 34983.83 32596.90 30891.48 354
dp88.08 32488.05 32288.16 34192.85 35568.81 35994.17 26092.88 31785.47 31591.38 33396.14 26468.87 35198.81 29886.88 30283.80 35796.87 300
gg-mvs-nofinetune88.28 32386.96 32792.23 31892.84 35684.44 31898.19 4174.60 36499.08 987.01 35599.47 756.93 36098.23 33678.91 34295.61 32994.01 344
tpmvs90.79 30590.87 29690.57 33192.75 35776.30 34895.79 17693.64 30891.04 26391.91 32996.26 25777.19 31198.86 29489.38 26489.85 34896.56 312
EPMVS89.26 31688.55 32091.39 32392.36 35879.11 33895.65 18579.86 36288.60 28393.12 31296.53 24370.73 34298.10 34090.75 23889.32 34996.98 295
gm-plane-assit91.79 35971.40 35881.67 33490.11 35398.99 27784.86 318
test235685.45 33283.26 33592.01 32091.12 36080.76 33385.16 35392.90 31683.90 32890.63 33587.71 35753.10 36497.24 34869.20 35795.65 32898.03 260
GG-mvs-BLEND90.60 33091.00 36184.21 32198.23 3572.63 36782.76 35984.11 35956.14 36196.79 35272.20 35492.09 34490.78 355
DeepMVS_CXcopyleft77.17 34890.94 36285.28 30174.08 36652.51 36080.87 36288.03 35675.25 32070.63 36259.23 36084.94 35575.62 357
EPNet_dtu91.39 29890.75 29993.31 29790.48 36382.61 32594.80 23792.88 31793.39 21781.74 36194.90 29581.36 29299.11 26288.28 28198.87 21598.21 245
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
testpf82.70 33584.35 33377.74 34788.97 36473.23 35593.85 27584.33 36088.10 29085.06 35790.42 35152.62 36691.05 36091.00 22984.82 35668.93 359
EPNet93.72 25092.62 26297.03 14787.61 36592.25 17296.27 14591.28 33096.74 9787.65 35397.39 19485.00 28299.64 11992.14 20899.48 12499.20 127
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
tmp_tt57.23 33762.50 33841.44 35034.77 36649.21 36683.93 35460.22 36815.31 36171.11 36379.37 36070.09 34444.86 36364.76 35882.93 35830.25 360
test12312.59 34115.49 3423.87 3526.07 3672.55 36790.75 3332.59 3702.52 3625.20 36513.02 3634.96 3691.85 3655.20 3619.09 3617.23 361
testmvs12.33 34215.23 3433.64 3535.77 3682.23 36888.99 3453.62 3692.30 3635.29 36413.09 3624.52 3701.95 3645.16 3628.32 3626.75 362
cdsmvs_eth3d_5k24.22 34032.30 3410.00 3540.00 3690.00 3690.00 36098.10 2050.00 3640.00 36695.06 29097.54 270.00 3660.00 3630.00 3640.00 364
pcd_1.5k_mvsjas7.98 34310.65 3440.00 3540.00 3690.00 3690.00 3600.00 3710.00 3640.00 3660.00 36695.82 890.00 3660.00 3630.00 3640.00 364
sosnet-low-res0.00 3450.00 3460.00 3540.00 3690.00 3690.00 3600.00 3710.00 3640.00 3660.00 3660.00 3710.00 3660.00 3630.00 3640.00 364
sosnet0.00 3450.00 3460.00 3540.00 3690.00 3690.00 3600.00 3710.00 3640.00 3660.00 3660.00 3710.00 3660.00 3630.00 3640.00 364
uncertanet0.00 3450.00 3460.00 3540.00 3690.00 3690.00 3600.00 3710.00 3640.00 3660.00 3660.00 3710.00 3660.00 3630.00 3640.00 364
Regformer0.00 3450.00 3460.00 3540.00 3690.00 3690.00 3600.00 3710.00 3640.00 3660.00 3660.00 3710.00 3660.00 3630.00 3640.00 364
ab-mvs-re7.91 34410.55 3450.00 3540.00 3690.00 3690.00 3600.00 3710.00 3640.00 36694.94 2920.00 3710.00 3660.00 3630.00 3640.00 364
uanet0.00 3450.00 3460.00 3540.00 3690.00 3690.00 3600.00 3710.00 3640.00 3660.00 3660.00 3710.00 3660.00 3630.00 3640.00 364
GSMVS98.06 255
test_part10.00 3540.00 3690.00 36098.84 890.00 3710.00 3660.00 3630.00 3640.00 364
sam_mvs177.80 30498.06 255
sam_mvs77.38 308
MTGPAbinary98.73 114
test_post194.98 23010.37 36576.21 31699.04 27089.47 263
test_post10.87 36476.83 31299.07 267
patchmatchnet-post96.84 22377.36 30999.42 200
MTMP96.55 13074.60 364
test9_res91.29 22398.89 21499.00 159
agg_prior290.34 25398.90 21099.10 150
test_prior495.38 8693.61 286
test_prior293.33 29594.21 19594.02 28296.25 25893.64 16891.90 21098.96 204
旧先验293.35 29477.95 35295.77 23698.67 31290.74 240
新几何293.43 290
无先验93.20 29897.91 21580.78 33999.40 21487.71 28597.94 265
原ACMM292.82 303
testdata299.46 19087.84 284
segment_acmp95.34 109
testdata192.77 30493.78 210
plane_prior598.75 11199.46 19092.59 20399.20 18099.28 118
plane_prior496.77 229
plane_prior394.51 11495.29 15096.16 221
plane_prior296.50 13396.36 108
plane_prior94.29 12295.42 19794.31 19298.93 209
n20.00 371
nn0.00 371
door-mid98.17 198
test1198.08 208
door97.81 224
HQP5-MVS92.47 168
BP-MVS90.51 247
HQP4-MVS92.87 31599.23 25199.06 155
HQP3-MVS98.43 15998.74 225
HQP2-MVS90.33 238
MDTV_nov1_ep13_2view57.28 36594.89 23280.59 34094.02 28278.66 30285.50 31397.82 269
ACMMP++_ref99.52 111
ACMMP++99.55 102
Test By Simon94.51 138