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 bysorted bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort by
LCM-MVSNet99.43 199.49 199.24 199.95 198.13 199.37 199.57 199.82 199.86 199.85 199.52 199.73 197.58 199.94 199.85 1
UniMVSNet_ETH3D97.13 697.72 395.35 8999.51 287.38 13697.70 897.54 11198.16 298.94 299.33 297.84 499.08 10090.73 13099.73 1499.59 12
FOURS199.21 394.68 1298.45 498.81 897.73 698.27 20
PEN-MVS96.69 2097.39 894.61 12099.16 484.50 18896.54 3198.05 6198.06 498.64 1398.25 3195.01 4899.65 392.95 8099.83 699.68 4
MIMVSNet195.52 6795.45 7495.72 7799.14 589.02 10396.23 5196.87 16693.73 6197.87 2798.49 2490.73 15199.05 10586.43 22799.60 2599.10 46
PS-CasMVS96.69 2097.43 594.49 13199.13 684.09 19796.61 2897.97 7697.91 598.64 1398.13 3495.24 3699.65 393.39 6199.84 399.72 2
DTE-MVSNet96.74 1797.43 594.67 11899.13 684.68 18796.51 3297.94 8298.14 398.67 1298.32 2995.04 4599.69 293.27 6799.82 899.62 10
pmmvs696.80 1397.36 995.15 10199.12 887.82 13196.68 2697.86 8496.10 2698.14 2499.28 397.94 398.21 21791.38 12199.69 1599.42 19
HPM-MVS_fast97.01 796.89 1597.39 2299.12 893.92 2997.16 1298.17 4193.11 7296.48 8097.36 7596.92 699.34 6494.31 2399.38 5598.92 69
MP-MVS-pluss96.08 4995.92 5796.57 4699.06 1091.21 6693.25 15398.32 2187.89 19796.86 6697.38 7195.55 2499.39 5095.47 1099.47 3999.11 43
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
OurMVSNet-221017-096.80 1396.75 1896.96 3699.03 1191.85 5997.98 798.01 7094.15 5298.93 399.07 588.07 18699.57 1395.86 999.69 1599.46 18
WR-MVS_H96.60 2597.05 1495.24 9799.02 1286.44 16196.78 2498.08 5497.42 998.48 1697.86 4991.76 12299.63 694.23 2699.84 399.66 6
TDRefinement97.68 397.60 497.93 299.02 1295.95 598.61 398.81 897.41 1097.28 4998.46 2594.62 5898.84 13894.64 1799.53 3598.99 55
CP-MVSNet96.19 4696.80 1794.38 13798.99 1483.82 20096.31 4697.53 11397.60 798.34 1997.52 6391.98 11799.63 693.08 7699.81 999.70 3
PMVScopyleft87.21 1494.97 8895.33 7993.91 15298.97 1597.16 295.54 7795.85 21596.47 2193.40 20397.46 6795.31 3395.47 33086.18 23198.78 13989.11 357
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
zzz-MVS96.47 3196.14 4597.47 1598.95 1694.05 2393.69 14397.62 10394.46 4596.29 9096.94 10193.56 7499.37 5894.29 2499.42 4798.99 55
MTAPA96.65 2296.38 3397.47 1598.95 1694.05 2395.88 6497.62 10394.46 4596.29 9096.94 10193.56 7499.37 5894.29 2499.42 4798.99 55
ACMMP_NAP96.21 4596.12 4796.49 5098.90 1891.42 6494.57 11498.03 6690.42 14496.37 8397.35 7895.68 1999.25 7994.44 2099.34 5898.80 82
HPM-MVScopyleft96.81 1296.62 2397.36 2498.89 1993.53 3997.51 998.44 1392.35 8495.95 10896.41 13896.71 899.42 3193.99 3399.36 5699.13 40
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
VDDNet94.03 12794.27 12293.31 17298.87 2082.36 21695.51 7991.78 30697.19 1296.32 8798.60 1884.24 23298.75 15787.09 21598.83 13298.81 81
TSAR-MVS + MP.94.96 8994.75 10095.57 8398.86 2188.69 10996.37 4196.81 17085.23 23994.75 16497.12 9191.85 11999.40 4593.45 5498.33 18398.62 107
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
EGC-MVSNET80.97 32975.73 34196.67 4498.85 2294.55 1596.83 2096.60 1822.44 3765.32 37798.25 3192.24 10998.02 23391.85 10799.21 8297.45 204
mvs_tets96.83 996.71 1997.17 2798.83 2392.51 5096.58 3097.61 10687.57 20698.80 798.90 996.50 1099.59 1296.15 799.47 3999.40 21
PS-MVSNAJss96.01 5196.04 5295.89 6898.82 2488.51 11795.57 7697.88 8388.72 18098.81 698.86 1090.77 14799.60 895.43 1199.53 3599.57 13
MP-MVScopyleft96.14 4795.68 6797.51 1398.81 2594.06 2196.10 5497.78 9692.73 7493.48 20096.72 12194.23 6699.42 3191.99 10199.29 6899.05 50
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
LTVRE_ROB93.87 197.93 298.16 297.26 2698.81 2593.86 3299.07 298.98 597.01 1398.92 498.78 1495.22 3798.61 18096.85 299.77 1099.31 27
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
ZNCC-MVS96.42 3696.20 4197.07 3098.80 2792.79 4896.08 5598.16 4491.74 11195.34 13696.36 14695.68 1999.44 2694.41 2199.28 7398.97 61
jajsoiax96.59 2796.42 2997.12 2998.76 2892.49 5196.44 3897.42 11986.96 21598.71 1098.72 1795.36 3199.56 1695.92 899.45 4399.32 26
MSP-MVS95.34 7594.63 10897.48 1498.67 2994.05 2396.41 4098.18 3791.26 12395.12 14795.15 20586.60 21599.50 1993.43 5996.81 26398.89 72
Zhenlong Yuan, Cong Liu, Fei Shen, Zhaoxin Li, Jingguo luo, Tianlu Mao and Zhaoqi Wang: MSP-MVS: Multi-granularity Segmentation Prior Guided Multi-View Stereo. AAAI2025
GST-MVS96.24 4495.99 5497.00 3498.65 3092.71 4995.69 7198.01 7092.08 9295.74 11996.28 15195.22 3799.42 3193.17 7199.06 9898.88 74
SteuartSystems-ACMMP96.40 3896.30 3696.71 4298.63 3191.96 5795.70 6998.01 7093.34 6996.64 7596.57 13094.99 4999.36 6093.48 5199.34 5898.82 80
Skip Steuart: Steuart Systems R&D Blog.
region2R96.41 3796.09 4897.38 2398.62 3293.81 3696.32 4597.96 7792.26 8795.28 14096.57 13095.02 4799.41 3893.63 4299.11 9698.94 64
mPP-MVS96.46 3296.05 5197.69 598.62 3294.65 1396.45 3697.74 9792.59 7895.47 12996.68 12394.50 6199.42 3193.10 7499.26 7598.99 55
ACMMPcopyleft96.61 2496.34 3497.43 1998.61 3493.88 3096.95 1898.18 3792.26 8796.33 8696.84 11195.10 4399.40 4593.47 5399.33 6099.02 52
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
VPNet93.08 15193.76 13291.03 24598.60 3575.83 31291.51 22295.62 22091.84 10395.74 11997.10 9289.31 17398.32 20885.07 24499.06 9898.93 65
ACMMPR96.46 3296.14 4597.41 2198.60 3593.82 3496.30 4897.96 7792.35 8495.57 12696.61 12894.93 5199.41 3893.78 3899.15 9199.00 53
PGM-MVS96.32 4195.94 5597.43 1998.59 3793.84 3395.33 8398.30 2491.40 12095.76 11796.87 10795.26 3599.45 2592.77 8299.21 8299.00 53
XVS96.49 2996.18 4297.44 1798.56 3893.99 2796.50 3397.95 7994.58 4194.38 17496.49 13294.56 5999.39 5093.57 4499.05 10398.93 65
X-MVStestdata90.70 20988.45 25197.44 1798.56 3893.99 2796.50 3397.95 7994.58 4194.38 17426.89 37494.56 5999.39 5093.57 4499.05 10398.93 65
ACMH88.36 1296.59 2797.43 594.07 14498.56 3885.33 18196.33 4498.30 2494.66 4098.72 898.30 3097.51 598.00 23594.87 1499.59 2798.86 75
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
test_0728_SECOND94.88 10998.55 4186.72 15295.20 8998.22 3399.38 5693.44 5799.31 6398.53 114
test_djsdf96.62 2396.49 2897.01 3398.55 4191.77 6197.15 1397.37 12188.98 17498.26 2298.86 1093.35 8199.60 896.41 499.45 4399.66 6
v7n96.82 1097.31 1095.33 9198.54 4386.81 15096.83 2098.07 5796.59 2098.46 1798.43 2792.91 9599.52 1796.25 699.76 1199.65 8
abl_697.31 597.12 1397.86 398.54 4395.32 796.61 2898.35 2095.81 3197.55 3797.44 6896.51 999.40 4594.06 3099.23 7998.85 78
ACMH+88.43 1196.48 3096.82 1695.47 8698.54 4389.06 10295.65 7298.61 1196.10 2698.16 2397.52 6396.90 798.62 17990.30 14399.60 2598.72 93
SixPastTwentyTwo94.91 9095.21 8493.98 14698.52 4683.19 20795.93 6194.84 24594.86 3998.49 1598.74 1681.45 25799.60 894.69 1699.39 5499.15 38
SED-MVS96.00 5296.41 3294.76 11498.51 4786.97 14695.21 8798.10 5091.95 9497.63 3397.25 8396.48 1199.35 6193.29 6599.29 6897.95 162
IU-MVS98.51 4786.66 15596.83 16972.74 33695.83 11593.00 7899.29 6898.64 103
test_241102_ONE98.51 4786.97 14698.10 5091.85 10097.63 3397.03 9696.48 1198.95 123
DVP-MVScopyleft95.82 5896.18 4294.72 11698.51 4786.69 15395.20 8997.00 15391.85 10097.40 4797.35 7895.58 2299.34 6493.44 5799.31 6398.13 143
Zhenlong Yuan, Jinguo Luo, Fei Shen, Zhaoxin Li, Cong Liu, Tianlu Mao, Zhaoqi Wang: DVP-MVS: Synergize Depth-Edge and Visibility Prior for Multi-View Stereo. AAAI2025
test072698.51 4786.69 15395.34 8298.18 3791.85 10097.63 3397.37 7295.58 22
HFP-MVS96.39 3996.17 4497.04 3198.51 4793.37 4096.30 4897.98 7392.35 8495.63 12396.47 13395.37 2899.27 7793.78 3899.14 9298.48 118
#test#95.89 5495.51 7297.04 3198.51 4793.37 4095.14 9297.98 7389.34 16595.63 12396.47 13395.37 2899.27 7791.99 10199.14 9298.48 118
Baseline_NR-MVSNet94.47 11195.09 8992.60 19798.50 5480.82 23692.08 19696.68 17893.82 6096.29 9098.56 2090.10 16597.75 25990.10 15499.66 2199.24 31
OPM-MVS95.61 6595.45 7496.08 5698.49 5591.00 7192.65 16997.33 13090.05 14996.77 7196.85 10895.04 4598.56 18892.77 8299.06 9898.70 96
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
FC-MVSNet-test95.32 7695.88 5893.62 16098.49 5581.77 22195.90 6398.32 2193.93 5797.53 4097.56 6088.48 17999.40 4592.91 8199.83 699.68 4
XVG-ACMP-BASELINE95.68 6395.34 7896.69 4398.40 5793.04 4394.54 11998.05 6190.45 14396.31 8896.76 11592.91 9598.72 16291.19 12299.42 4798.32 127
ACMM88.83 996.30 4396.07 5096.97 3598.39 5892.95 4694.74 10698.03 6690.82 13397.15 5296.85 10896.25 1599.00 11593.10 7499.33 6098.95 63
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
pm-mvs195.43 7195.94 5593.93 15098.38 5985.08 18495.46 8097.12 14791.84 10397.28 4998.46 2595.30 3497.71 26190.17 15099.42 4798.99 55
COLMAP_ROBcopyleft91.06 596.75 1696.62 2397.13 2898.38 5994.31 1796.79 2398.32 2196.69 1796.86 6697.56 6095.48 2598.77 15690.11 15299.44 4598.31 129
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
TransMVSNet (Re)95.27 8196.04 5292.97 18098.37 6181.92 22095.07 9596.76 17593.97 5697.77 2998.57 1995.72 1897.90 24188.89 18199.23 7999.08 47
LPG-MVS_test96.38 4096.23 3996.84 4098.36 6292.13 5495.33 8398.25 2891.78 10797.07 5497.22 8696.38 1399.28 7592.07 9999.59 2799.11 43
LGP-MVS_train96.84 4098.36 6292.13 5498.25 2891.78 10797.07 5497.22 8696.38 1399.28 7592.07 9999.59 2799.11 43
CP-MVS96.44 3596.08 4997.54 1198.29 6494.62 1496.80 2298.08 5492.67 7795.08 15196.39 14394.77 5499.42 3193.17 7199.44 4598.58 112
FIs94.90 9195.35 7793.55 16398.28 6581.76 22295.33 8398.14 4593.05 7397.07 5497.18 8887.65 19399.29 7391.72 11199.69 1599.61 11
SMA-MVScopyleft95.77 5995.54 7196.47 5198.27 6691.19 6795.09 9397.79 9586.48 21997.42 4697.51 6594.47 6399.29 7393.55 4699.29 6898.93 65
Yufeng Yin; Xiaoyan Liu; Zichao Zhang: SMA-MVS: Segmentation-Guided Multi-Scale Anchor Deformation Patch Multi-View Stereo. IEEE Transactions on Circuits and Systems for Video Technology
test_one_060198.26 6787.14 14198.18 3794.25 4996.99 6197.36 7595.13 40
TranMVSNet+NR-MVSNet96.07 5096.26 3895.50 8598.26 6787.69 13293.75 14197.86 8495.96 3097.48 4297.14 9095.33 3299.44 2690.79 12999.76 1199.38 22
IS-MVSNet94.49 11094.35 11794.92 10798.25 6986.46 16097.13 1594.31 25996.24 2496.28 9396.36 14682.88 24199.35 6188.19 19399.52 3798.96 62
UA-Net97.35 497.24 1197.69 598.22 7093.87 3198.42 698.19 3696.95 1495.46 13199.23 493.45 7699.57 1395.34 1299.89 299.63 9
test_part298.21 7189.41 9796.72 72
test_040295.73 6096.22 4094.26 13998.19 7285.77 17693.24 15497.24 13896.88 1697.69 3197.77 5294.12 6899.13 9391.54 11899.29 6897.88 172
ACMP88.15 1395.71 6295.43 7696.54 4798.17 7391.73 6294.24 12598.08 5489.46 16196.61 7796.47 13395.85 1799.12 9590.45 13599.56 3398.77 86
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
CPTT-MVS94.74 10094.12 12596.60 4598.15 7493.01 4495.84 6597.66 10189.21 17193.28 20795.46 19488.89 17698.98 11689.80 15998.82 13397.80 181
SF-MVS95.88 5695.88 5895.87 6998.12 7589.65 9195.58 7598.56 1291.84 10396.36 8496.68 12394.37 6499.32 7092.41 9399.05 10398.64 103
Vis-MVSNetpermissive95.50 6895.48 7395.56 8498.11 7689.40 9895.35 8198.22 3392.36 8394.11 17898.07 3792.02 11499.44 2693.38 6297.67 23697.85 176
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
XVG-OURS-SEG-HR95.38 7395.00 9196.51 4898.10 7794.07 2092.46 17798.13 4690.69 13693.75 19296.25 15498.03 297.02 29092.08 9895.55 28998.45 121
EPP-MVSNet93.91 13093.68 13694.59 12598.08 7885.55 17997.44 1094.03 26494.22 5094.94 15696.19 15682.07 25299.57 1387.28 21298.89 12098.65 99
SR-MVS-dyc-post96.84 896.60 2597.56 1098.07 7995.27 896.37 4198.12 4795.66 3397.00 5997.03 9694.85 5299.42 3193.49 4898.84 12798.00 154
RE-MVS-def96.66 2098.07 7995.27 896.37 4198.12 4795.66 3397.00 5997.03 9695.40 2793.49 4898.84 12798.00 154
SR-MVS96.70 1996.42 2997.54 1198.05 8194.69 1196.13 5398.07 5795.17 3796.82 6896.73 12095.09 4499.43 3092.99 7998.71 14498.50 116
K. test v393.37 14093.27 15093.66 15998.05 8182.62 21494.35 12286.62 33796.05 2897.51 4198.85 1276.59 29699.65 393.21 6998.20 20298.73 92
lessismore_v093.87 15598.05 8183.77 20180.32 36997.13 5397.91 4677.49 28499.11 9792.62 8898.08 21398.74 90
test111190.39 21890.61 21289.74 28198.04 8471.50 34295.59 7379.72 37189.41 16295.94 11098.14 3370.79 31598.81 14588.52 18999.32 6298.90 71
test117296.79 1596.52 2797.60 998.03 8594.87 1096.07 5698.06 6095.76 3296.89 6496.85 10894.85 5299.42 3193.35 6398.81 13598.53 114
AllTest94.88 9394.51 11396.00 5898.02 8692.17 5295.26 8698.43 1490.48 14195.04 15396.74 11892.54 10597.86 24785.11 24298.98 11197.98 158
TestCases96.00 5898.02 8692.17 5298.43 1490.48 14195.04 15396.74 11892.54 10597.86 24785.11 24298.98 11197.98 158
anonymousdsp96.74 1796.42 2997.68 798.00 8894.03 2696.97 1797.61 10687.68 20398.45 1898.77 1594.20 6799.50 1996.70 399.40 5399.53 14
XVG-OURS94.72 10194.12 12596.50 4998.00 8894.23 1891.48 22398.17 4190.72 13595.30 13896.47 13387.94 19096.98 29191.41 12097.61 23998.30 130
114514_t90.51 21389.80 22992.63 19598.00 8882.24 21793.40 15197.29 13465.84 36189.40 29594.80 22586.99 20598.75 15783.88 25598.61 15396.89 230
Gipumacopyleft95.31 7895.80 6493.81 15797.99 9190.91 7396.42 3997.95 7996.69 1791.78 25598.85 1291.77 12195.49 32991.72 11199.08 9795.02 293
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
APD-MVS_3200maxsize96.82 1096.65 2197.32 2597.95 9293.82 3496.31 4698.25 2895.51 3596.99 6197.05 9595.63 2199.39 5093.31 6498.88 12298.75 87
DPE-MVScopyleft95.89 5495.88 5895.92 6597.93 9389.83 8893.46 14998.30 2492.37 8297.75 3096.95 10095.14 3999.51 1891.74 11099.28 7398.41 124
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
HPM-MVS++copyleft95.02 8694.39 11596.91 3897.88 9493.58 3894.09 13196.99 15591.05 12892.40 23995.22 20491.03 14599.25 7992.11 9698.69 14797.90 170
EG-PatchMatch MVS94.54 10994.67 10694.14 14297.87 9586.50 15792.00 20196.74 17688.16 19296.93 6397.61 5893.04 9297.90 24191.60 11598.12 20998.03 152
nrg03096.32 4196.55 2695.62 8097.83 9688.55 11595.77 6798.29 2792.68 7598.03 2697.91 4695.13 4098.95 12393.85 3699.49 3899.36 24
test250685.42 30084.57 30287.96 31097.81 9766.53 36296.14 5256.35 37989.04 17293.55 19998.10 3542.88 38198.68 17288.09 19799.18 8798.67 97
ECVR-MVScopyleft90.12 22890.16 22090.00 27897.81 9772.68 33695.76 6878.54 37289.04 17295.36 13598.10 3570.51 31698.64 17887.10 21499.18 8798.67 97
UniMVSNet (Re)95.32 7695.15 8695.80 7297.79 9988.91 10592.91 16198.07 5793.46 6796.31 8895.97 16690.14 16199.34 6492.11 9699.64 2399.16 37
VPA-MVSNet95.14 8495.67 6893.58 16297.76 10083.15 20894.58 11397.58 10893.39 6897.05 5798.04 3993.25 8398.51 19389.75 16299.59 2799.08 47
DU-MVS95.28 7995.12 8895.75 7697.75 10188.59 11392.58 17097.81 9193.99 5496.80 6995.90 16790.10 16599.41 3891.60 11599.58 3199.26 29
NR-MVSNet95.28 7995.28 8295.26 9697.75 10187.21 14095.08 9497.37 12193.92 5997.65 3295.90 16790.10 16599.33 6990.11 15299.66 2199.26 29
XXY-MVS92.58 17093.16 15290.84 25497.75 10179.84 25091.87 21096.22 20385.94 22995.53 12897.68 5492.69 10194.48 34283.21 26097.51 24198.21 137
PVSNet_Blended_VisFu91.63 19191.20 19892.94 18397.73 10483.95 19992.14 19497.46 11778.85 30492.35 24294.98 21584.16 23399.08 10086.36 22896.77 26595.79 273
tfpnnormal94.27 11994.87 9592.48 20297.71 10580.88 23594.55 11795.41 23293.70 6296.67 7497.72 5391.40 13098.18 22187.45 20899.18 8798.36 125
HQP_MVS94.26 12093.93 12795.23 9897.71 10588.12 12394.56 11597.81 9191.74 11193.31 20495.59 18486.93 20798.95 12389.26 17298.51 16598.60 110
plane_prior797.71 10588.68 110
UniMVSNet_NR-MVSNet95.35 7495.21 8495.76 7597.69 10888.59 11392.26 19097.84 8894.91 3896.80 6995.78 17790.42 15699.41 3891.60 11599.58 3199.29 28
APDe-MVS96.46 3296.64 2295.93 6397.68 10989.38 9996.90 1998.41 1792.52 7997.43 4497.92 4595.11 4299.50 1994.45 1999.30 6598.92 69
DeepC-MVS91.39 495.43 7195.33 7995.71 7897.67 11090.17 8293.86 13998.02 6887.35 20896.22 9697.99 4294.48 6299.05 10592.73 8599.68 1897.93 164
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
KD-MVS_self_test94.10 12594.73 10292.19 20897.66 11179.49 25994.86 10297.12 14789.59 16096.87 6597.65 5690.40 15998.34 20789.08 17799.35 5798.75 87
Vis-MVSNet (Re-imp)90.42 21690.16 22091.20 24197.66 11177.32 29294.33 12387.66 33091.20 12592.99 21995.13 20775.40 30098.28 21077.86 30999.19 8597.99 157
ETH3D-3000-0.194.86 9494.55 11095.81 7097.61 11389.72 8994.05 13298.37 1888.09 19395.06 15295.85 16992.58 10399.10 9990.33 14298.99 11098.62 107
dcpmvs_293.96 12995.01 9090.82 25597.60 11474.04 32693.68 14598.85 689.80 15597.82 2897.01 9991.14 14399.21 8390.56 13398.59 15599.19 35
FMVSNet194.84 9695.13 8793.97 14797.60 11484.29 19095.99 5796.56 18592.38 8197.03 5898.53 2190.12 16298.98 11688.78 18399.16 9098.65 99
RPSCF95.58 6694.89 9497.62 897.58 11696.30 495.97 6097.53 11392.42 8093.41 20197.78 5091.21 13897.77 25691.06 12397.06 25398.80 82
WR-MVS93.49 13793.72 13392.80 18997.57 11780.03 24690.14 25995.68 21993.70 6296.62 7695.39 20087.21 20199.04 10887.50 20799.64 2399.33 25
CSCG94.69 10294.75 10094.52 12897.55 11887.87 12995.01 9897.57 10992.68 7596.20 9893.44 26891.92 11898.78 15289.11 17699.24 7896.92 228
MCST-MVS92.91 15792.51 16794.10 14397.52 11985.72 17791.36 22797.13 14680.33 28692.91 22294.24 24291.23 13798.72 16289.99 15697.93 22397.86 174
F-COLMAP92.28 17991.06 20295.95 6097.52 11991.90 5893.53 14797.18 14183.98 25688.70 30894.04 24988.41 18198.55 19080.17 29095.99 28097.39 211
9.1494.81 9697.49 12194.11 13098.37 1887.56 20795.38 13396.03 16394.66 5699.08 10090.70 13198.97 115
VDD-MVS94.37 11394.37 11694.40 13697.49 12186.07 17193.97 13693.28 27694.49 4496.24 9497.78 5087.99 18998.79 14888.92 17999.14 9298.34 126
testgi90.38 21991.34 19587.50 31697.49 12171.54 34189.43 27895.16 23788.38 18894.54 17094.68 23092.88 9793.09 35671.60 34897.85 22797.88 172
xxxxxxxxxxxxxcwj95.03 8594.93 9295.33 9197.46 12488.05 12592.04 19898.42 1687.63 20496.36 8496.68 12394.37 6499.32 7092.41 9399.05 10398.64 103
save fliter97.46 12488.05 12592.04 19897.08 14987.63 204
Anonymous2023121196.60 2597.13 1295.00 10597.46 12486.35 16597.11 1698.24 3197.58 898.72 898.97 793.15 8799.15 8993.18 7099.74 1399.50 16
plane_prior197.38 127
APD-MVScopyleft95.00 8794.69 10395.93 6397.38 12790.88 7494.59 11197.81 9189.22 17095.46 13196.17 15993.42 7999.34 6489.30 16898.87 12597.56 198
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
ITE_SJBPF95.95 6097.34 12993.36 4296.55 18891.93 9694.82 16195.39 20091.99 11697.08 28885.53 23597.96 22197.41 207
Anonymous2024052995.50 6895.83 6294.50 12997.33 13085.93 17395.19 9196.77 17496.64 1997.61 3698.05 3893.23 8498.79 14888.60 18899.04 10898.78 84
OMC-MVS94.22 12293.69 13595.81 7097.25 13191.27 6592.27 18997.40 12087.10 21494.56 16995.42 19793.74 7198.11 22686.62 22298.85 12698.06 146
GeoE94.55 10794.68 10594.15 14197.23 13285.11 18394.14 12997.34 12988.71 18195.26 14195.50 19294.65 5799.12 9590.94 12798.40 17198.23 134
ZD-MVS97.23 13290.32 8197.54 11184.40 25494.78 16395.79 17492.76 10099.39 5088.72 18698.40 171
testtj94.81 9894.42 11496.01 5797.23 13290.51 8094.77 10597.85 8791.29 12294.92 15895.66 18291.71 12399.40 4588.07 19898.25 19498.11 145
plane_prior697.21 13588.23 12186.93 207
DP-MVS Recon92.31 17891.88 18093.60 16197.18 13686.87 14991.10 23297.37 12184.92 24992.08 25094.08 24888.59 17898.20 21883.50 25798.14 20695.73 275
新几何193.17 17697.16 13787.29 13794.43 25667.95 35591.29 26094.94 21786.97 20698.23 21681.06 28497.75 22993.98 317
DP-MVS95.62 6495.84 6194.97 10697.16 13788.62 11294.54 11997.64 10296.94 1596.58 7897.32 8193.07 9198.72 16290.45 13598.84 12797.57 196
112190.26 22589.23 23593.34 17097.15 13987.40 13591.94 20494.39 25767.88 35691.02 26694.91 21886.91 20998.59 18481.17 28297.71 23394.02 316
CHOSEN 1792x268887.19 28885.92 29691.00 24897.13 14079.41 26084.51 34595.60 22164.14 36490.07 28294.81 22278.26 28097.14 28673.34 33795.38 29696.46 246
HyFIR lowres test87.19 28885.51 29892.24 20697.12 14180.51 23785.03 33996.06 20866.11 36091.66 25692.98 27970.12 31799.14 9175.29 32895.23 29997.07 221
ab-mvs92.40 17592.62 16591.74 22297.02 14281.65 22395.84 6595.50 23086.95 21692.95 22197.56 6090.70 15297.50 26979.63 29797.43 24496.06 261
tttt051789.81 23988.90 24592.55 19997.00 14379.73 25595.03 9783.65 36089.88 15395.30 13894.79 22653.64 36899.39 5091.99 10198.79 13898.54 113
h-mvs3392.89 15891.99 17795.58 8296.97 14490.55 7893.94 13794.01 26789.23 16893.95 18696.19 15676.88 29399.14 9191.02 12495.71 28697.04 224
test22296.95 14585.27 18288.83 29393.61 27065.09 36390.74 27094.85 22184.62 23197.36 24693.91 318
CDPH-MVS92.67 16791.83 18195.18 10096.94 14688.46 11890.70 24197.07 15077.38 31192.34 24495.08 21092.67 10298.88 13085.74 23398.57 15798.20 138
CNVR-MVS94.58 10694.29 11995.46 8796.94 14689.35 10091.81 21696.80 17189.66 15793.90 18995.44 19692.80 9998.72 16292.74 8498.52 16398.32 127
DROMVSNet95.44 7095.62 6994.89 10896.93 14887.69 13296.48 3599.14 393.93 5792.77 22594.52 23493.95 7099.49 2293.62 4399.22 8197.51 201
原ACMM192.87 18696.91 14984.22 19397.01 15276.84 31689.64 29394.46 23588.00 18898.70 16881.53 27798.01 21995.70 277
CS-MVS-test95.15 8394.81 9696.19 5296.89 15091.14 6894.55 11798.85 694.31 4892.43 23691.91 30291.79 12099.49 2293.48 5199.06 9897.93 164
ambc92.98 17996.88 15183.01 21195.92 6296.38 19596.41 8197.48 6688.26 18297.80 25289.96 15798.93 11998.12 144
testdata91.03 24596.87 15282.01 21894.28 26071.55 34092.46 23395.42 19785.65 22597.38 28082.64 26597.27 24893.70 324
CS-MVS95.72 6195.58 7096.15 5396.86 15391.06 6996.74 2599.07 494.22 5092.42 23794.79 22693.58 7399.48 2493.45 5499.06 9897.91 168
OPU-MVS95.15 10196.84 15489.43 9695.21 8795.66 18293.12 8898.06 22886.28 23098.61 15397.95 162
ETH3D cwj APD-0.1693.99 12893.38 14695.80 7296.82 15589.92 8592.72 16598.02 6884.73 25293.65 19695.54 19191.68 12499.22 8288.78 18398.49 16898.26 133
NP-MVS96.82 15587.10 14293.40 269
3Dnovator+92.74 295.86 5795.77 6596.13 5596.81 15790.79 7696.30 4897.82 9096.13 2594.74 16597.23 8591.33 13299.16 8893.25 6898.30 18898.46 120
Test_1112_low_res87.50 28086.58 28690.25 27096.80 15877.75 28687.53 31096.25 19969.73 35086.47 32993.61 26475.67 29997.88 24379.95 29293.20 32995.11 291
PAPM_NR91.03 20390.81 20791.68 22696.73 15981.10 23293.72 14296.35 19688.19 19188.77 30692.12 30085.09 22897.25 28282.40 26993.90 32196.68 238
1112_ss88.42 26287.41 27191.45 23196.69 16080.99 23389.72 27296.72 17773.37 33287.00 32790.69 32277.38 28698.20 21881.38 27893.72 32495.15 289
patch_mono-292.46 17492.72 16391.71 22496.65 16178.91 27088.85 29297.17 14283.89 25892.45 23496.76 11589.86 16997.09 28790.24 14798.59 15599.12 42
v894.65 10495.29 8192.74 19096.65 16179.77 25494.59 11197.17 14291.86 9997.47 4397.93 4488.16 18499.08 10094.32 2299.47 3999.38 22
MVS_111021_HR93.63 13593.42 14594.26 13996.65 16186.96 14889.30 28396.23 20188.36 18993.57 19894.60 23193.45 7697.77 25690.23 14898.38 17698.03 152
ANet_high94.83 9796.28 3790.47 26396.65 16173.16 33194.33 12398.74 1096.39 2398.09 2598.93 893.37 8098.70 16890.38 13899.68 1899.53 14
SD-MVS95.19 8295.73 6693.55 16396.62 16588.88 10894.67 10898.05 6191.26 12397.25 5196.40 13995.42 2694.36 34692.72 8699.19 8597.40 210
Zhenlong Yuan, Jiakai Cao, Zhaoxin Li, Hao Jiang and Zhaoqi Wang: SD-MVS: Segmentation-driven Deformation Multi-View Stereo with Spherical Refinement and EM optimization. AAAI2024
ETH3 D test640091.91 18691.25 19793.89 15396.59 16684.41 18992.10 19597.72 9978.52 30591.82 25493.78 26188.70 17799.13 9383.61 25698.39 17498.14 141
PM-MVS93.33 14192.67 16495.33 9196.58 16794.06 2192.26 19092.18 29785.92 23096.22 9696.61 12885.64 22695.99 32290.35 14098.23 19795.93 266
Anonymous2024052192.86 16193.57 14090.74 25796.57 16875.50 31494.15 12895.60 22189.38 16395.90 11397.90 4880.39 26697.96 23992.60 8999.68 1898.75 87
v1094.68 10395.27 8392.90 18596.57 16880.15 24094.65 11097.57 10990.68 13797.43 4498.00 4188.18 18399.15 8994.84 1599.55 3499.41 20
Anonymous20240521192.58 17092.50 16892.83 18896.55 17083.22 20692.43 17991.64 30794.10 5395.59 12596.64 12681.88 25697.50 26985.12 24198.52 16397.77 183
DVP-MVS++95.93 5396.34 3494.70 11796.54 17186.66 15598.45 498.22 3393.26 7097.54 3897.36 7593.12 8899.38 5693.88 3498.68 14898.04 149
MSC_two_6792asdad95.90 6696.54 17189.57 9296.87 16699.41 3894.06 3099.30 6598.72 93
No_MVS95.90 6696.54 17189.57 9296.87 16699.41 3894.06 3099.30 6598.72 93
PLCcopyleft85.34 1590.40 21788.92 24394.85 11096.53 17490.02 8391.58 22196.48 19180.16 28786.14 33192.18 29785.73 22398.25 21576.87 31994.61 31296.30 252
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
TAPA-MVS88.58 1092.49 17391.75 18594.73 11596.50 17589.69 9092.91 16197.68 10078.02 30992.79 22494.10 24790.85 14697.96 23984.76 24898.16 20496.54 239
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
NCCC94.08 12693.54 14295.70 7996.49 17689.90 8792.39 18296.91 16290.64 13892.33 24594.60 23190.58 15598.96 12190.21 14997.70 23498.23 134
TAMVS90.16 22789.05 24093.49 16896.49 17686.37 16390.34 25292.55 29280.84 28492.99 21994.57 23381.94 25598.20 21873.51 33698.21 20095.90 269
TEST996.45 17889.46 9490.60 24396.92 16079.09 30090.49 27394.39 23891.31 13398.88 130
train_agg92.71 16691.83 18195.35 8996.45 17889.46 9490.60 24396.92 16079.37 29590.49 27394.39 23891.20 13998.88 13088.66 18798.43 17097.72 187
test_896.37 18089.14 10190.51 24696.89 16379.37 29590.42 27594.36 24091.20 13998.82 140
CLD-MVS91.82 18791.41 19393.04 17796.37 18083.65 20286.82 32497.29 13484.65 25392.27 24689.67 33492.20 11197.85 24983.95 25499.47 3997.62 194
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
HQP-NCC96.36 18291.37 22487.16 21188.81 302
ACMP_Plane96.36 18291.37 22487.16 21188.81 302
HQP-MVS92.09 18391.49 19193.88 15496.36 18284.89 18591.37 22497.31 13187.16 21188.81 30293.40 26984.76 22998.60 18286.55 22497.73 23098.14 141
v2v48293.29 14293.63 13792.29 20496.35 18578.82 27291.77 21896.28 19788.45 18695.70 12296.26 15386.02 22198.90 12793.02 7798.81 13599.14 39
MSLP-MVS++93.25 14793.88 12891.37 23396.34 18682.81 21393.11 15597.74 9789.37 16494.08 18095.29 20390.40 15996.35 31390.35 14098.25 19494.96 294
thisisatest053088.69 25987.52 27092.20 20796.33 18779.36 26192.81 16384.01 35986.44 22093.67 19592.68 28753.62 36999.25 7989.65 16498.45 16998.00 154
FPMVS84.50 30683.28 31088.16 30896.32 18894.49 1685.76 33485.47 34983.09 26585.20 33594.26 24163.79 34586.58 37063.72 36691.88 34783.40 365
Anonymous2023120688.77 25788.29 25590.20 27396.31 18978.81 27389.56 27693.49 27474.26 32792.38 24095.58 18782.21 24995.43 33272.07 34498.75 14396.34 250
MVP-Stereo90.07 23288.92 24393.54 16596.31 18986.49 15890.93 23595.59 22579.80 28891.48 25795.59 18480.79 26397.39 27878.57 30791.19 34996.76 236
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
v114493.50 13693.81 12992.57 19896.28 19179.61 25791.86 21496.96 15686.95 21695.91 11296.32 14887.65 19398.96 12193.51 4798.88 12299.13 40
LFMVS91.33 19991.16 20191.82 21996.27 19279.36 26195.01 9885.61 34896.04 2994.82 16197.06 9472.03 31298.46 20084.96 24598.70 14697.65 192
VNet92.67 16792.96 15391.79 22096.27 19280.15 24091.95 20294.98 24092.19 9094.52 17196.07 16187.43 19797.39 27884.83 24698.38 17697.83 177
IterMVS-LS93.78 13294.28 12092.27 20596.27 19279.21 26691.87 21096.78 17291.77 10996.57 7997.07 9387.15 20298.74 16091.99 10199.03 10998.86 75
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
v14892.87 16093.29 14791.62 22796.25 19577.72 28791.28 22895.05 23889.69 15695.93 11196.04 16287.34 19898.38 20390.05 15597.99 22098.78 84
MVS_111021_LR93.66 13493.28 14994.80 11296.25 19590.95 7290.21 25595.43 23187.91 19593.74 19494.40 23792.88 9796.38 31190.39 13798.28 18997.07 221
agg_prior192.60 16991.76 18495.10 10396.20 19788.89 10690.37 25096.88 16479.67 29290.21 27894.41 23691.30 13498.78 15288.46 19098.37 18197.64 193
agg_prior96.20 19788.89 10696.88 16490.21 27898.78 152
旧先验196.20 19784.17 19594.82 24695.57 18889.57 17197.89 22596.32 251
CNLPA91.72 18991.20 19893.26 17496.17 20091.02 7091.14 23095.55 22890.16 14890.87 26793.56 26686.31 21794.40 34579.92 29697.12 25294.37 307
hse-mvs292.24 18191.20 19895.38 8896.16 20190.65 7792.52 17292.01 30489.23 16893.95 18692.99 27876.88 29398.69 17091.02 12496.03 27896.81 233
v119293.49 13793.78 13192.62 19696.16 20179.62 25691.83 21597.22 14086.07 22796.10 10496.38 14487.22 20099.02 11194.14 2998.88 12299.22 32
test_part194.39 11294.55 11093.92 15196.14 20382.86 21295.54 7798.09 5395.36 3698.27 2098.36 2875.91 29899.44 2693.41 6099.84 399.47 17
thres100view90087.35 28386.89 28188.72 29896.14 20373.09 33293.00 15885.31 35192.13 9193.26 20990.96 31763.42 34698.28 21071.27 35096.54 27094.79 297
DeepC-MVS_fast89.96 793.73 13393.44 14494.60 12496.14 20387.90 12893.36 15297.14 14485.53 23693.90 18995.45 19591.30 13498.59 18489.51 16598.62 15297.31 216
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
DPM-MVS89.35 24488.40 25292.18 21196.13 20684.20 19486.96 31996.15 20775.40 32287.36 32491.55 31083.30 23798.01 23482.17 27296.62 26994.32 309
AUN-MVS90.05 23388.30 25495.32 9496.09 20790.52 7992.42 18092.05 30382.08 27788.45 31192.86 28065.76 33498.69 17088.91 18096.07 27796.75 237
baseline94.26 12094.80 9892.64 19396.08 20880.99 23393.69 14398.04 6590.80 13494.89 15996.32 14893.19 8598.48 19891.68 11398.51 16598.43 122
PCF-MVS84.52 1789.12 24887.71 26793.34 17096.06 20985.84 17586.58 33297.31 13168.46 35493.61 19793.89 25787.51 19698.52 19267.85 35998.11 21095.66 279
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
v14419293.20 15093.54 14292.16 21296.05 21078.26 27991.95 20297.14 14484.98 24895.96 10796.11 16087.08 20499.04 10893.79 3798.84 12799.17 36
thres600view787.66 27587.10 27989.36 28896.05 21073.17 33092.72 16585.31 35191.89 9893.29 20690.97 31663.42 34698.39 20173.23 33896.99 26096.51 241
casdiffmvs94.32 11794.80 9892.85 18796.05 21081.44 22792.35 18598.05 6191.53 11895.75 11896.80 11293.35 8198.49 19491.01 12698.32 18598.64 103
MIMVSNet87.13 29086.54 28888.89 29596.05 21076.11 30794.39 12188.51 32281.37 28088.27 31496.75 11772.38 30995.52 32765.71 36495.47 29295.03 292
v192192093.26 14593.61 13892.19 20896.04 21478.31 27891.88 20997.24 13885.17 24196.19 10096.19 15686.76 21299.05 10594.18 2898.84 12799.22 32
v124093.29 14293.71 13492.06 21596.01 21577.89 28491.81 21697.37 12185.12 24496.69 7396.40 13986.67 21399.07 10494.51 1898.76 14199.22 32
BH-untuned90.68 21090.90 20390.05 27795.98 21679.57 25890.04 26294.94 24287.91 19594.07 18193.00 27787.76 19297.78 25579.19 30395.17 30092.80 338
DeepPCF-MVS90.46 694.20 12393.56 14196.14 5495.96 21792.96 4589.48 27797.46 11785.14 24296.23 9595.42 19793.19 8598.08 22790.37 13998.76 14197.38 213
test_prior393.29 14292.85 15694.61 12095.95 21887.23 13890.21 25597.36 12689.33 16690.77 26894.81 22290.41 15798.68 17288.21 19198.55 15897.93 164
test_prior94.61 12095.95 21887.23 13897.36 12698.68 17297.93 164
test1294.43 13595.95 21886.75 15196.24 20089.76 29189.79 17098.79 14897.95 22297.75 186
LCM-MVSNet-Re94.20 12394.58 10993.04 17795.91 22183.13 20993.79 14099.19 292.00 9398.84 598.04 3993.64 7299.02 11181.28 27998.54 16196.96 227
PatchMatch-RL89.18 24688.02 26492.64 19395.90 22292.87 4788.67 29991.06 31080.34 28590.03 28391.67 30783.34 23694.42 34476.35 32394.84 30690.64 354
ETV-MVS92.99 15592.74 16093.72 15895.86 22386.30 16692.33 18697.84 8891.70 11492.81 22386.17 35892.22 11099.19 8688.03 19997.73 23095.66 279
TSAR-MVS + GP.93.07 15392.41 17095.06 10495.82 22490.87 7590.97 23492.61 29188.04 19494.61 16893.79 26088.08 18597.81 25189.41 16798.39 17496.50 244
QAPM92.88 15992.77 15893.22 17595.82 22483.31 20496.45 3697.35 12883.91 25793.75 19296.77 11389.25 17498.88 13084.56 25097.02 25597.49 202
EIA-MVS92.35 17792.03 17593.30 17395.81 22683.97 19892.80 16498.17 4187.71 20189.79 29087.56 34891.17 14299.18 8787.97 20097.27 24896.77 235
tfpn200view987.05 29186.52 28988.67 29995.77 22772.94 33391.89 20786.00 34390.84 13192.61 22989.80 32963.93 34398.28 21071.27 35096.54 27094.79 297
thres40087.20 28786.52 28989.24 29295.77 22772.94 33391.89 20786.00 34390.84 13192.61 22989.80 32963.93 34398.28 21071.27 35096.54 27096.51 241
pmmvs-eth3d91.54 19390.73 21093.99 14595.76 22987.86 13090.83 23793.98 26878.23 30894.02 18596.22 15582.62 24796.83 29786.57 22398.33 18397.29 217
jason89.17 24788.32 25391.70 22595.73 23080.07 24388.10 30293.22 27771.98 33990.09 28092.79 28378.53 27898.56 18887.43 20997.06 25396.46 246
jason: jason.
alignmvs93.26 14592.85 15694.50 12995.70 23187.45 13493.45 15095.76 21791.58 11695.25 14392.42 29581.96 25498.72 16291.61 11497.87 22697.33 215
xiu_mvs_v1_base_debu91.47 19591.52 18891.33 23495.69 23281.56 22489.92 26696.05 20983.22 26291.26 26190.74 31991.55 12798.82 14089.29 16995.91 28193.62 326
xiu_mvs_v1_base91.47 19591.52 18891.33 23495.69 23281.56 22489.92 26696.05 20983.22 26291.26 26190.74 31991.55 12798.82 14089.29 16995.91 28193.62 326
xiu_mvs_v1_base_debi91.47 19591.52 18891.33 23495.69 23281.56 22489.92 26696.05 20983.22 26291.26 26190.74 31991.55 12798.82 14089.29 16995.91 28193.62 326
PHI-MVS94.34 11693.80 13095.95 6095.65 23591.67 6394.82 10397.86 8487.86 19893.04 21894.16 24691.58 12698.78 15290.27 14598.96 11797.41 207
LF4IMVS92.72 16592.02 17694.84 11195.65 23591.99 5692.92 16096.60 18285.08 24692.44 23593.62 26386.80 21196.35 31386.81 21798.25 19496.18 257
test20.0390.80 20690.85 20690.63 26095.63 23779.24 26489.81 27192.87 28289.90 15294.39 17396.40 13985.77 22295.27 33773.86 33599.05 10397.39 211
TinyColmap92.00 18592.76 15989.71 28295.62 23877.02 29590.72 24096.17 20687.70 20295.26 14196.29 15092.54 10596.45 30881.77 27498.77 14095.66 279
canonicalmvs94.59 10594.69 10394.30 13895.60 23987.03 14595.59 7398.24 3191.56 11795.21 14692.04 30194.95 5098.66 17591.45 11997.57 24097.20 220
AdaColmapbinary91.63 19191.36 19492.47 20395.56 24086.36 16492.24 19296.27 19888.88 17889.90 28692.69 28691.65 12598.32 20877.38 31697.64 23792.72 340
UnsupCasMVSNet_bld88.50 26188.03 26389.90 27995.52 24178.88 27187.39 31294.02 26679.32 29893.06 21694.02 25180.72 26494.27 34775.16 32993.08 33396.54 239
3Dnovator92.54 394.80 9994.90 9394.47 13295.47 24287.06 14396.63 2797.28 13691.82 10694.34 17697.41 6990.60 15498.65 17792.47 9198.11 21097.70 188
Fast-Effi-MVS+91.28 20190.86 20592.53 20095.45 24382.53 21589.25 28696.52 18985.00 24789.91 28588.55 34492.94 9398.84 13884.72 24995.44 29396.22 255
GBi-Net93.21 14892.96 15393.97 14795.40 24484.29 19095.99 5796.56 18588.63 18295.10 14898.53 2181.31 25998.98 11686.74 21898.38 17698.65 99
test193.21 14892.96 15393.97 14795.40 24484.29 19095.99 5796.56 18588.63 18295.10 14898.53 2181.31 25998.98 11686.74 21898.38 17698.65 99
FMVSNet292.78 16392.73 16292.95 18295.40 24481.98 21994.18 12795.53 22988.63 18296.05 10597.37 7281.31 25998.81 14587.38 21198.67 15098.06 146
CDS-MVSNet89.55 24188.22 25993.53 16695.37 24786.49 15889.26 28493.59 27179.76 29091.15 26492.31 29677.12 28998.38 20377.51 31497.92 22495.71 276
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
V4293.43 13993.58 13992.97 18095.34 24881.22 23092.67 16896.49 19087.25 21096.20 9896.37 14587.32 19998.85 13792.39 9598.21 20098.85 78
Patchmatch-RL test88.81 25688.52 24989.69 28395.33 24979.94 24886.22 33392.71 28778.46 30695.80 11694.18 24566.25 33295.33 33589.22 17498.53 16293.78 321
CL-MVSNet_self_test90.04 23489.90 22890.47 26395.24 25077.81 28586.60 33192.62 29085.64 23593.25 21193.92 25583.84 23496.06 32079.93 29498.03 21797.53 200
BH-RMVSNet90.47 21590.44 21690.56 26295.21 25178.65 27689.15 28793.94 26988.21 19092.74 22694.22 24386.38 21697.88 24378.67 30695.39 29595.14 290
Effi-MVS+92.79 16292.74 16092.94 18395.10 25283.30 20594.00 13497.53 11391.36 12189.35 29690.65 32494.01 6998.66 17587.40 21095.30 29796.88 231
USDC89.02 24989.08 23988.84 29695.07 25374.50 32188.97 28996.39 19473.21 33393.27 20896.28 15182.16 25196.39 31077.55 31398.80 13795.62 282
WTY-MVS86.93 29386.50 29188.24 30794.96 25474.64 31787.19 31592.07 30278.29 30788.32 31391.59 30978.06 28194.27 34774.88 33093.15 33195.80 272
PS-MVSNAJ88.86 25588.99 24288.48 30394.88 25574.71 31686.69 32795.60 22180.88 28287.83 31987.37 35190.77 14798.82 14082.52 26794.37 31591.93 346
MG-MVS89.54 24289.80 22988.76 29794.88 25572.47 33889.60 27492.44 29485.82 23189.48 29495.98 16582.85 24297.74 26081.87 27395.27 29896.08 260
xiu_mvs_v2_base89.00 25189.19 23688.46 30494.86 25774.63 31886.97 31895.60 22180.88 28287.83 31988.62 34391.04 14498.81 14582.51 26894.38 31491.93 346
MAR-MVS90.32 22388.87 24694.66 11994.82 25891.85 5994.22 12694.75 24980.91 28187.52 32388.07 34786.63 21497.87 24676.67 32096.21 27694.25 310
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
PVSNet_BlendedMVS90.35 22189.96 22691.54 23094.81 25978.80 27490.14 25996.93 15879.43 29488.68 30995.06 21186.27 21898.15 22480.27 28798.04 21697.68 190
PVSNet_Blended88.74 25888.16 26290.46 26594.81 25978.80 27486.64 32896.93 15874.67 32488.68 30989.18 34086.27 21898.15 22480.27 28796.00 27994.44 306
BH-w/o87.21 28687.02 28087.79 31494.77 26177.27 29387.90 30393.21 27981.74 27989.99 28488.39 34683.47 23596.93 29471.29 34992.43 34189.15 356
bset_n11_16_dypcd89.99 23589.15 23892.53 20094.75 26281.34 22884.19 34887.56 33185.13 24393.77 19192.46 29072.82 30799.01 11392.46 9299.21 8297.23 218
LS3D96.11 4895.83 6296.95 3794.75 26294.20 1997.34 1197.98 7397.31 1195.32 13796.77 11393.08 9099.20 8591.79 10898.16 20497.44 206
Effi-MVS+-dtu93.90 13192.60 16697.77 494.74 26496.67 394.00 13495.41 23289.94 15091.93 25392.13 29990.12 16298.97 12087.68 20597.48 24297.67 191
mvs-test193.07 15391.80 18396.89 3994.74 26495.83 692.17 19395.41 23289.94 15089.85 28790.59 32590.12 16298.88 13087.68 20595.66 28795.97 264
MVSFormer92.18 18292.23 17192.04 21694.74 26480.06 24497.15 1397.37 12188.98 17488.83 30092.79 28377.02 29099.60 896.41 496.75 26696.46 246
lupinMVS88.34 26487.31 27291.45 23194.74 26480.06 24487.23 31392.27 29671.10 34388.83 30091.15 31377.02 29098.53 19186.67 22196.75 26695.76 274
baseline187.62 27787.31 27288.54 30194.71 26874.27 32493.10 15688.20 32686.20 22492.18 24893.04 27673.21 30695.52 32779.32 30185.82 36195.83 271
MDA-MVSNet-bldmvs91.04 20290.88 20491.55 22994.68 26980.16 23985.49 33692.14 30090.41 14594.93 15795.79 17485.10 22796.93 29485.15 23994.19 32097.57 196
Fast-Effi-MVS+-dtu92.77 16492.16 17294.58 12794.66 27088.25 12092.05 19796.65 18089.62 15890.08 28191.23 31292.56 10498.60 18286.30 22996.27 27596.90 229
UnsupCasMVSNet_eth90.33 22290.34 21890.28 26894.64 27180.24 23889.69 27395.88 21385.77 23293.94 18895.69 18081.99 25392.98 35784.21 25391.30 34897.62 194
OpenMVS_ROBcopyleft85.12 1689.52 24389.05 24090.92 25094.58 27281.21 23191.10 23293.41 27577.03 31593.41 20193.99 25383.23 23897.80 25279.93 29494.80 30793.74 323
OpenMVScopyleft89.45 892.27 18092.13 17492.68 19294.53 27384.10 19695.70 6997.03 15182.44 27491.14 26596.42 13788.47 18098.38 20385.95 23297.47 24395.55 283
thres20085.85 29885.18 29987.88 31394.44 27472.52 33789.08 28886.21 33988.57 18591.44 25888.40 34564.22 34198.00 23568.35 35895.88 28493.12 332
DELS-MVS92.05 18492.16 17291.72 22394.44 27480.13 24287.62 30597.25 13787.34 20992.22 24793.18 27589.54 17298.73 16189.67 16398.20 20296.30 252
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
N_pmnet88.90 25487.25 27493.83 15694.40 27693.81 3684.73 34187.09 33479.36 29793.26 20992.43 29479.29 27191.68 36177.50 31597.22 25096.00 263
pmmvs488.95 25387.70 26892.70 19194.30 27785.60 17887.22 31492.16 29974.62 32589.75 29294.19 24477.97 28296.41 30982.71 26496.36 27496.09 259
new-patchmatchnet88.97 25290.79 20883.50 34394.28 27855.83 37785.34 33793.56 27286.18 22595.47 12995.73 17983.10 23996.51 30685.40 23698.06 21498.16 139
API-MVS91.52 19491.61 18691.26 23794.16 27986.26 16894.66 10994.82 24691.17 12692.13 24991.08 31590.03 16897.06 28979.09 30497.35 24790.45 355
MSDG90.82 20590.67 21191.26 23794.16 27983.08 21086.63 32996.19 20490.60 14091.94 25291.89 30389.16 17595.75 32480.96 28594.51 31394.95 295
TR-MVS87.70 27387.17 27689.27 29094.11 28179.26 26388.69 29791.86 30581.94 27890.69 27189.79 33182.82 24397.42 27572.65 34291.98 34591.14 351
test_yl90.11 22989.73 23291.26 23794.09 28279.82 25190.44 24792.65 28890.90 12993.19 21393.30 27173.90 30398.03 23082.23 27096.87 26195.93 266
DCV-MVSNet90.11 22989.73 23291.26 23794.09 28279.82 25190.44 24792.65 28890.90 12993.19 21393.30 27173.90 30398.03 23082.23 27096.87 26195.93 266
D2MVS89.93 23689.60 23490.92 25094.03 28478.40 27788.69 29794.85 24478.96 30293.08 21595.09 20974.57 30196.94 29288.19 19398.96 11797.41 207
sss87.23 28586.82 28288.46 30493.96 28577.94 28186.84 32292.78 28677.59 31087.61 32291.83 30478.75 27491.92 36077.84 31094.20 31995.52 284
PVSNet76.22 2082.89 31582.37 31584.48 33893.96 28564.38 37078.60 36388.61 32171.50 34184.43 34286.36 35774.27 30294.60 34169.87 35693.69 32594.46 305
IterMVS-SCA-FT91.65 19091.55 18791.94 21793.89 28779.22 26587.56 30893.51 27391.53 11895.37 13496.62 12778.65 27598.90 12791.89 10694.95 30397.70 188
UGNet93.08 15192.50 16894.79 11393.87 28887.99 12795.07 9594.26 26190.64 13887.33 32597.67 5586.89 21098.49 19488.10 19698.71 14497.91 168
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
PAPM81.91 32380.11 33387.31 31893.87 28872.32 33984.02 35093.22 27769.47 35176.13 37089.84 32872.15 31097.23 28353.27 37289.02 35592.37 343
CANet92.38 17691.99 17793.52 16793.82 29083.46 20391.14 23097.00 15389.81 15486.47 32994.04 24987.90 19199.21 8389.50 16698.27 19097.90 170
HY-MVS82.50 1886.81 29485.93 29589.47 28493.63 29177.93 28294.02 13391.58 30875.68 31883.64 34693.64 26277.40 28597.42 27571.70 34792.07 34493.05 335
MVS_Test92.57 17293.29 14790.40 26693.53 29275.85 31092.52 17296.96 15688.73 17992.35 24296.70 12290.77 14798.37 20692.53 9095.49 29196.99 226
EU-MVSNet87.39 28286.71 28589.44 28593.40 29376.11 30794.93 10190.00 31757.17 37095.71 12197.37 7264.77 34097.68 26392.67 8794.37 31594.52 304
MS-PatchMatch88.05 26887.75 26688.95 29393.28 29477.93 28287.88 30492.49 29375.42 32192.57 23193.59 26580.44 26594.24 34981.28 27992.75 33694.69 302
GA-MVS87.70 27386.82 28290.31 26793.27 29577.22 29484.72 34392.79 28585.11 24589.82 28890.07 32666.80 32797.76 25884.56 25094.27 31895.96 265
pmmvs587.87 27087.14 27790.07 27593.26 29676.97 29988.89 29192.18 29773.71 33188.36 31293.89 25776.86 29596.73 30080.32 28696.81 26396.51 241
MVS_030490.96 20490.15 22393.37 16993.17 29787.06 14393.62 14692.43 29589.60 15982.25 35495.50 19282.56 24897.83 25084.41 25297.83 22895.22 287
IterMVS90.18 22690.16 22090.21 27293.15 29875.98 30987.56 30892.97 28186.43 22194.09 17996.40 13978.32 27997.43 27487.87 20294.69 31097.23 218
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
MVS-HIRNet78.83 33880.60 32973.51 35593.07 29947.37 37887.10 31778.00 37368.94 35277.53 36897.26 8271.45 31394.62 34063.28 36788.74 35678.55 370
diffmvs91.74 18891.93 17991.15 24393.06 30078.17 28088.77 29597.51 11686.28 22392.42 23793.96 25488.04 18797.46 27290.69 13296.67 26897.82 179
ET-MVSNet_ETH3D86.15 29684.27 30591.79 22093.04 30181.28 22987.17 31686.14 34079.57 29383.65 34588.66 34257.10 36198.18 22187.74 20495.40 29495.90 269
FMVSNet390.78 20790.32 21992.16 21293.03 30279.92 24992.54 17194.95 24186.17 22695.10 14896.01 16469.97 31898.75 15786.74 21898.38 17697.82 179
thisisatest051584.72 30582.99 31389.90 27992.96 30375.33 31584.36 34683.42 36177.37 31288.27 31486.65 35353.94 36798.72 16282.56 26697.40 24595.67 278
PAPR87.65 27686.77 28490.27 26992.85 30477.38 29188.56 30096.23 20176.82 31784.98 33789.75 33386.08 22097.16 28572.33 34393.35 32796.26 254
Regformer-194.55 10794.33 11895.19 9992.83 30588.54 11691.87 21095.84 21693.99 5495.95 10895.04 21292.00 11598.79 14893.14 7398.31 18698.23 134
Regformer-294.86 9494.55 11095.77 7492.83 30589.98 8491.87 21096.40 19394.38 4796.19 10095.04 21292.47 10899.04 10893.49 4898.31 18698.28 131
Regformer-394.28 11894.23 12494.46 13392.78 30786.28 16792.39 18294.70 25193.69 6595.97 10695.56 18991.34 13198.48 19893.45 5498.14 20698.62 107
Regformer-494.90 9194.67 10695.59 8192.78 30789.02 10392.39 18295.91 21294.50 4396.41 8195.56 18992.10 11399.01 11394.23 2698.14 20698.74 90
EI-MVSNet-Vis-set94.36 11494.28 12094.61 12092.55 30985.98 17292.44 17894.69 25293.70 6296.12 10395.81 17391.24 13698.86 13593.76 4198.22 19998.98 60
EI-MVSNet-UG-set94.35 11594.27 12294.59 12592.46 31085.87 17492.42 18094.69 25293.67 6696.13 10295.84 17291.20 13998.86 13593.78 3898.23 19799.03 51
FMVSNet587.82 27286.56 28791.62 22792.31 31179.81 25393.49 14894.81 24883.26 26191.36 25996.93 10352.77 37097.49 27176.07 32498.03 21797.55 199
c3_l91.32 20091.42 19291.00 24892.29 31276.79 30187.52 31196.42 19285.76 23394.72 16793.89 25782.73 24498.16 22390.93 12898.55 15898.04 149
MDA-MVSNet_test_wron88.16 26788.23 25887.93 31192.22 31373.71 32780.71 36188.84 31982.52 27294.88 16095.14 20682.70 24593.61 35283.28 25993.80 32396.46 246
YYNet188.17 26688.24 25787.93 31192.21 31473.62 32880.75 36088.77 32082.51 27394.99 15595.11 20882.70 24593.70 35183.33 25893.83 32296.48 245
CANet_DTU89.85 23889.17 23791.87 21892.20 31580.02 24790.79 23895.87 21486.02 22882.53 35391.77 30580.01 26798.57 18785.66 23497.70 23497.01 225
mvs_anonymous90.37 22091.30 19687.58 31592.17 31668.00 35589.84 27094.73 25083.82 25993.22 21297.40 7087.54 19597.40 27787.94 20195.05 30297.34 214
EI-MVSNet92.99 15593.26 15192.19 20892.12 31779.21 26692.32 18794.67 25491.77 10995.24 14495.85 16987.14 20398.49 19491.99 10198.26 19198.86 75
CVMVSNet85.16 30284.72 30086.48 32292.12 31770.19 34792.32 18788.17 32756.15 37190.64 27295.85 16967.97 32296.69 30188.78 18390.52 35292.56 341
eth_miper_zixun_eth90.72 20890.61 21291.05 24492.04 31976.84 30086.91 32096.67 17985.21 24094.41 17293.92 25579.53 27098.26 21489.76 16197.02 25598.06 146
SCA87.43 28187.21 27588.10 30992.01 32071.98 34089.43 27888.11 32882.26 27688.71 30792.83 28178.65 27597.59 26579.61 29893.30 32894.75 299
cl____90.65 21190.56 21490.91 25291.85 32176.98 29886.75 32595.36 23585.53 23694.06 18294.89 21977.36 28897.98 23890.27 14598.98 11197.76 184
DIV-MVS_self_test90.65 21190.56 21490.91 25291.85 32176.99 29786.75 32595.36 23585.52 23894.06 18294.89 21977.37 28797.99 23790.28 14498.97 11597.76 184
our_test_387.55 27887.59 26987.44 31791.76 32370.48 34683.83 35190.55 31579.79 28992.06 25192.17 29878.63 27795.63 32584.77 24794.73 30896.22 255
ppachtmachnet_test88.61 26088.64 24888.50 30291.76 32370.99 34584.59 34492.98 28079.30 29992.38 24093.53 26779.57 26997.45 27386.50 22697.17 25197.07 221
131486.46 29586.33 29286.87 32191.65 32574.54 31991.94 20494.10 26374.28 32684.78 33987.33 35283.03 24095.00 33978.72 30591.16 35091.06 352
miper_ehance_all_eth90.48 21490.42 21790.69 25891.62 32676.57 30386.83 32396.18 20583.38 26094.06 18292.66 28882.20 25098.04 22989.79 16097.02 25597.45 204
RRT_test8_iter0588.21 26588.17 26088.33 30691.62 32666.82 36191.73 21996.60 18286.34 22294.14 17795.38 20247.72 37499.11 9791.78 10998.26 19199.06 49
cascas87.02 29286.28 29389.25 29191.56 32876.45 30484.33 34796.78 17271.01 34486.89 32885.91 35981.35 25896.94 29283.09 26195.60 28894.35 308
baseline283.38 31181.54 32088.90 29491.38 32972.84 33588.78 29481.22 36678.97 30179.82 36587.56 34861.73 35497.80 25274.30 33390.05 35496.05 262
miper_lstm_enhance89.90 23789.80 22990.19 27491.37 33077.50 28983.82 35295.00 23984.84 25093.05 21794.96 21676.53 29795.20 33889.96 15798.67 15097.86 174
IB-MVS77.21 1983.11 31281.05 32389.29 28991.15 33175.85 31085.66 33586.00 34379.70 29182.02 35886.61 35448.26 37398.39 20177.84 31092.22 34293.63 325
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
MVS84.98 30484.30 30487.01 31991.03 33277.69 28891.94 20494.16 26259.36 36984.23 34387.50 35085.66 22496.80 29871.79 34593.05 33486.54 362
CR-MVSNet87.89 26987.12 27890.22 27191.01 33378.93 26892.52 17292.81 28373.08 33489.10 29796.93 10367.11 32497.64 26488.80 18292.70 33794.08 311
RPMNet90.31 22490.14 22490.81 25691.01 33378.93 26892.52 17298.12 4791.91 9789.10 29796.89 10668.84 31999.41 3890.17 15092.70 33794.08 311
new_pmnet81.22 32681.01 32581.86 34790.92 33570.15 34884.03 34980.25 37070.83 34585.97 33289.78 33267.93 32384.65 37167.44 36091.90 34690.78 353
PatchT87.51 27988.17 26085.55 32990.64 33666.91 35792.02 20086.09 34192.20 8989.05 29997.16 8964.15 34296.37 31289.21 17592.98 33593.37 330
Patchmatch-test86.10 29786.01 29486.38 32690.63 33774.22 32589.57 27586.69 33685.73 23489.81 28992.83 28165.24 33891.04 36377.82 31295.78 28593.88 320
PVSNet_070.34 2174.58 33972.96 34279.47 35190.63 33766.24 36373.26 36483.40 36263.67 36678.02 36778.35 37072.53 30889.59 36756.68 37060.05 37482.57 368
PMMVS281.31 32583.44 30974.92 35490.52 33946.49 37969.19 36885.23 35484.30 25587.95 31894.71 22976.95 29284.36 37264.07 36598.09 21293.89 319
tpm84.38 30784.08 30685.30 33390.47 34063.43 37289.34 28185.63 34777.24 31487.62 32195.03 21461.00 35797.30 28179.26 30291.09 35195.16 288
wuyk23d87.83 27190.79 20878.96 35290.46 34188.63 11192.72 16590.67 31491.65 11598.68 1197.64 5796.06 1677.53 37359.84 36899.41 5270.73 371
Patchmtry90.11 22989.92 22790.66 25990.35 34277.00 29692.96 15992.81 28390.25 14794.74 16596.93 10367.11 32497.52 26885.17 23798.98 11197.46 203
CHOSEN 280x42080.04 33577.97 34086.23 32790.13 34374.53 32072.87 36689.59 31866.38 35976.29 36985.32 36156.96 36295.36 33369.49 35794.72 30988.79 359
MVSTER89.32 24588.75 24791.03 24590.10 34476.62 30290.85 23694.67 25482.27 27595.24 14495.79 17461.09 35698.49 19490.49 13498.26 19197.97 161
tpm281.46 32480.35 33184.80 33589.90 34565.14 36690.44 24785.36 35065.82 36282.05 35792.44 29357.94 36096.69 30170.71 35388.49 35792.56 341
cl2289.02 24988.50 25090.59 26189.76 34676.45 30486.62 33094.03 26482.98 26892.65 22892.49 28972.05 31197.53 26788.93 17897.02 25597.78 182
test0.0.03 182.48 31781.47 32185.48 33089.70 34773.57 32984.73 34181.64 36583.07 26688.13 31686.61 35462.86 34989.10 36966.24 36390.29 35393.77 322
test-LLR83.58 31083.17 31184.79 33689.68 34866.86 35983.08 35384.52 35683.07 26682.85 35184.78 36262.86 34993.49 35382.85 26294.86 30494.03 314
test-mter81.21 32780.01 33484.79 33689.68 34866.86 35983.08 35384.52 35673.85 33082.85 35184.78 36243.66 37893.49 35382.85 26294.86 30494.03 314
DSMNet-mixed82.21 31981.56 31884.16 34089.57 35070.00 35190.65 24277.66 37454.99 37283.30 34997.57 5977.89 28390.50 36566.86 36295.54 29091.97 345
PatchmatchNetpermissive85.22 30184.64 30186.98 32089.51 35169.83 35290.52 24587.34 33378.87 30387.22 32692.74 28566.91 32696.53 30481.77 27486.88 36094.58 303
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
MDTV_nov1_ep1383.88 30889.42 35261.52 37388.74 29687.41 33273.99 32984.96 33894.01 25265.25 33795.53 32678.02 30893.16 330
CostFormer83.09 31382.21 31685.73 32889.27 35367.01 35690.35 25186.47 33870.42 34783.52 34893.23 27461.18 35596.85 29677.21 31788.26 35893.34 331
RRT_MVS91.36 19890.05 22595.29 9589.21 35488.15 12292.51 17694.89 24386.73 21895.54 12795.68 18161.82 35399.30 7294.91 1399.13 9598.43 122
ADS-MVSNet284.01 30982.20 31789.41 28689.04 35576.37 30687.57 30690.98 31172.71 33784.46 34092.45 29168.08 32096.48 30770.58 35483.97 36395.38 285
ADS-MVSNet82.25 31881.55 31984.34 33989.04 35565.30 36487.57 30685.13 35572.71 33784.46 34092.45 29168.08 32092.33 35970.58 35483.97 36395.38 285
tpm cat180.61 33379.46 33584.07 34188.78 35765.06 36889.26 28488.23 32562.27 36781.90 35989.66 33562.70 35195.29 33671.72 34680.60 37091.86 348
CMPMVSbinary68.83 2287.28 28485.67 29792.09 21488.77 35885.42 18090.31 25394.38 25870.02 34988.00 31793.30 27173.78 30594.03 35075.96 32696.54 27096.83 232
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
miper_enhance_ethall88.42 26287.87 26590.07 27588.67 35975.52 31385.10 33895.59 22575.68 31892.49 23289.45 33778.96 27297.88 24387.86 20397.02 25596.81 233
tpmrst82.85 31682.93 31482.64 34587.65 36058.99 37590.14 25987.90 32975.54 32083.93 34491.63 30866.79 32995.36 33381.21 28181.54 36993.57 329
JIA-IIPM85.08 30383.04 31291.19 24287.56 36186.14 17089.40 28084.44 35888.98 17482.20 35597.95 4356.82 36396.15 31676.55 32283.45 36591.30 350
TESTMET0.1,179.09 33778.04 33982.25 34687.52 36264.03 37183.08 35380.62 36870.28 34880.16 36483.22 36544.13 37790.56 36479.95 29293.36 32692.15 344
DWT-MVSNet_test80.74 33179.18 33685.43 33187.51 36366.87 35889.87 26986.01 34274.20 32880.86 36280.62 36848.84 37296.68 30381.54 27683.14 36792.75 339
gg-mvs-nofinetune82.10 32281.02 32485.34 33287.46 36471.04 34394.74 10667.56 37696.44 2279.43 36698.99 645.24 37596.15 31667.18 36192.17 34388.85 358
pmmvs380.83 33078.96 33786.45 32387.23 36577.48 29084.87 34082.31 36363.83 36585.03 33689.50 33649.66 37193.10 35573.12 34095.10 30188.78 360
tpmvs84.22 30883.97 30784.94 33487.09 36665.18 36591.21 22988.35 32382.87 26985.21 33490.96 31765.24 33896.75 29979.60 30085.25 36292.90 337
gm-plane-assit87.08 36759.33 37471.22 34283.58 36497.20 28473.95 334
MVEpermissive59.87 2373.86 34072.65 34377.47 35387.00 36874.35 32261.37 37060.93 37867.27 35769.69 37386.49 35681.24 26272.33 37456.45 37183.45 36585.74 363
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
EPNet_dtu85.63 29984.37 30389.40 28786.30 36974.33 32391.64 22088.26 32484.84 25072.96 37289.85 32771.27 31497.69 26276.60 32197.62 23896.18 257
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
dp79.28 33678.62 33881.24 34885.97 37056.45 37686.91 32085.26 35372.97 33581.45 36189.17 34156.01 36595.45 33173.19 33976.68 37191.82 349
EPMVS81.17 32880.37 33083.58 34285.58 37165.08 36790.31 25371.34 37577.31 31385.80 33391.30 31159.38 35892.70 35879.99 29182.34 36892.96 336
E-PMN80.72 33280.86 32680.29 35085.11 37268.77 35472.96 36581.97 36487.76 20083.25 35083.01 36662.22 35289.17 36877.15 31894.31 31782.93 366
GG-mvs-BLEND83.24 34485.06 37371.03 34494.99 10065.55 37774.09 37175.51 37144.57 37694.46 34359.57 36987.54 35984.24 364
EMVS80.35 33480.28 33280.54 34984.73 37469.07 35372.54 36780.73 36787.80 19981.66 36081.73 36762.89 34889.84 36675.79 32794.65 31182.71 367
EPNet89.80 24088.25 25694.45 13483.91 37586.18 16993.87 13887.07 33591.16 12780.64 36394.72 22878.83 27398.89 12985.17 23798.89 12098.28 131
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
PMMVS83.00 31481.11 32288.66 30083.81 37686.44 16182.24 35785.65 34661.75 36882.07 35685.64 36079.75 26891.59 36275.99 32593.09 33287.94 361
KD-MVS_2432*160082.17 32080.75 32786.42 32482.04 37770.09 34981.75 35890.80 31282.56 27090.37 27689.30 33842.90 37996.11 31874.47 33192.55 33993.06 333
miper_refine_blended82.17 32080.75 32786.42 32482.04 37770.09 34981.75 35890.80 31282.56 27090.37 27689.30 33842.90 37996.11 31874.47 33192.55 33993.06 333
DeepMVS_CXcopyleft53.83 35770.38 37964.56 36948.52 38133.01 37365.50 37474.21 37256.19 36446.64 37638.45 37570.07 37250.30 372
test_method50.44 34148.94 34454.93 35639.68 38012.38 38228.59 37190.09 3166.82 37441.10 37678.41 36954.41 36670.69 37550.12 37351.26 37581.72 369
tmp_tt37.97 34244.33 34518.88 35811.80 38121.54 38163.51 36945.66 3824.23 37551.34 37550.48 37359.08 35922.11 37744.50 37468.35 37313.00 373
test1239.49 34412.01 3471.91 3592.87 3821.30 38382.38 3561.34 3841.36 3772.84 3786.56 3762.45 3820.97 3782.73 3765.56 3763.47 374
testmvs9.02 34511.42 3481.81 3602.77 3831.13 38479.44 3621.90 3831.18 3782.65 3796.80 3751.95 3830.87 3792.62 3773.45 3773.44 375
test_blank0.00 3480.00 3510.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.00 3790.00 3840.00 3800.00 3780.00 3780.00 376
eth-test20.00 384
eth-test0.00 384
uanet_test0.00 3480.00 3510.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.00 3790.00 3840.00 3800.00 3780.00 3780.00 376
DCPMVS0.00 3480.00 3510.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.00 3790.00 3840.00 3800.00 3780.00 3780.00 376
cdsmvs_eth3d_5k23.35 34331.13 3460.00 3610.00 3840.00 3850.00 37295.58 2270.00 3790.00 38091.15 31393.43 780.00 3800.00 3780.00 3780.00 376
pcd_1.5k_mvsjas7.56 34610.09 3490.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.00 37990.77 1470.00 3800.00 3780.00 3780.00 376
sosnet-low-res0.00 3480.00 3510.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.00 3790.00 3840.00 3800.00 3780.00 3780.00 376
sosnet0.00 3480.00 3510.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.00 3790.00 3840.00 3800.00 3780.00 3780.00 376
uncertanet0.00 3480.00 3510.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.00 3790.00 3840.00 3800.00 3780.00 3780.00 376
Regformer0.00 3480.00 3510.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.00 3790.00 3840.00 3800.00 3780.00 3780.00 376
ab-mvs-re7.56 34610.08 3500.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 38090.69 3220.00 3840.00 3800.00 3780.00 3780.00 376
uanet0.00 3480.00 3510.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.00 3790.00 3840.00 3800.00 3780.00 3780.00 376
PC_three_145275.31 32395.87 11495.75 17892.93 9496.34 31587.18 21398.68 14898.04 149
test_241102_TWO98.10 5091.95 9497.54 3897.25 8395.37 2899.35 6193.29 6599.25 7698.49 117
test_0728_THIRD93.26 7097.40 4797.35 7894.69 5599.34 6493.88 3499.42 4798.89 72
GSMVS94.75 299
sam_mvs166.64 33094.75 299
sam_mvs66.41 331
MTGPAbinary97.62 103
test_post190.21 2555.85 37865.36 33696.00 32179.61 298
test_post6.07 37765.74 33595.84 323
patchmatchnet-post91.71 30666.22 33397.59 265
MTMP94.82 10354.62 380
test9_res88.16 19598.40 17197.83 177
agg_prior287.06 21698.36 18297.98 158
test_prior489.91 8690.74 239
test_prior290.21 25589.33 16690.77 26894.81 22290.41 15788.21 19198.55 158
旧先验290.00 26468.65 35392.71 22796.52 30585.15 239
新几何290.02 263
无先验89.94 26595.75 21870.81 34698.59 18481.17 28294.81 296
原ACMM289.34 281
testdata298.03 23080.24 289
segment_acmp92.14 112
testdata188.96 29088.44 187
plane_prior597.81 9198.95 12389.26 17298.51 16598.60 110
plane_prior495.59 184
plane_prior388.43 11990.35 14693.31 204
plane_prior294.56 11591.74 111
plane_prior88.12 12393.01 15788.98 17498.06 214
n20.00 385
nn0.00 385
door-mid92.13 301
test1196.65 180
door91.26 309
HQP5-MVS84.89 185
BP-MVS86.55 224
HQP4-MVS88.81 30298.61 18098.15 140
HQP3-MVS97.31 13197.73 230
HQP2-MVS84.76 229
MDTV_nov1_ep13_2view42.48 38088.45 30167.22 35883.56 34766.80 32772.86 34194.06 313
ACMMP++_ref98.82 133
ACMMP++99.25 76
Test By Simon90.61 153