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

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

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

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

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




Method Infoallhigh-res
multi-view
indooroutdoorbotani.boulde.bridgedoorexhibi.lectur.living.loungeobserv.old co.statueterrac.
sort bysort bysort bysort bysort bysort bysorted bysort bysort bysort bysort bysort bysort bysort bysort bysort by
DVP-MVS++98.06 197.99 198.28 998.67 6695.39 1199.29 198.28 2894.78 3798.93 698.87 696.04 299.86 997.45 999.58 2299.59 20
FOURS199.55 193.34 7399.29 198.35 2094.98 2798.49 15
CS-MVS96.86 3997.06 1596.26 11298.16 11191.16 14699.09 397.87 11395.30 1297.06 5398.03 7491.72 5398.71 18097.10 1499.17 7998.90 109
CS-MVS-test96.89 3797.04 1896.45 9798.29 9691.66 12199.03 497.85 11895.84 396.90 5697.97 8091.24 6798.75 17496.92 1899.33 5998.94 104
DROMVSNet96.42 5896.47 5296.26 11297.01 16891.52 12798.89 597.75 12494.42 4896.64 6597.68 10189.32 9298.60 18997.45 999.11 8898.67 129
HPM-MVScopyleft96.69 4996.45 5597.40 5699.36 2093.11 7898.87 698.06 7791.17 16296.40 7897.99 7890.99 7499.58 7595.61 7099.61 1699.49 45
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
APDe-MVS97.82 597.73 498.08 1899.15 3594.82 2998.81 798.30 2594.76 3998.30 1798.90 393.77 1799.68 5197.93 199.69 399.75 5
CP-MVS97.02 2796.81 3397.64 4999.33 2393.54 6598.80 898.28 2892.99 9996.45 7798.30 5391.90 5099.85 1895.61 7099.68 499.54 34
HPM-MVS_fast96.51 5596.27 5997.22 6799.32 2492.74 8698.74 998.06 7790.57 18396.77 5798.35 4290.21 8699.53 9394.80 9799.63 1499.38 62
EPP-MVSNet95.22 9095.04 8895.76 13297.49 14789.56 19398.67 1097.00 21390.69 17394.24 13397.62 11089.79 9198.81 16893.39 12896.49 16198.92 107
3Dnovator91.36 595.19 9294.44 10597.44 5596.56 19093.36 7298.65 1198.36 1794.12 5689.25 25898.06 7282.20 20499.77 3393.41 12699.32 6099.18 78
XVS97.18 1796.96 2397.81 3399.38 1594.03 5398.59 1298.20 4694.85 3096.59 6998.29 5491.70 5699.80 3195.66 6399.40 5199.62 16
X-MVStestdata91.71 21089.67 26797.81 3399.38 1594.03 5398.59 1298.20 4694.85 3096.59 6932.69 37691.70 5699.80 3195.66 6399.40 5199.62 16
mvsmamba93.83 13093.46 12694.93 18094.88 27590.85 15698.55 1495.49 29394.24 5491.29 20196.97 14583.04 18398.14 22595.56 7591.17 24295.78 241
MSP-MVS97.59 897.54 697.73 4199.40 1293.77 6198.53 1598.29 2695.55 698.56 1497.81 9293.90 1599.65 5796.62 2899.21 7699.77 1
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
HFP-MVS97.14 2096.92 2597.83 2999.42 794.12 4898.52 1698.32 2293.21 9097.18 4498.29 5492.08 4499.83 2695.63 6899.59 1799.54 34
region2R97.07 2396.84 3097.77 3899.46 293.79 5898.52 1698.24 3893.19 9397.14 4798.34 4591.59 6099.87 895.46 7699.59 1799.64 13
ACMMPR97.07 2396.84 3097.79 3599.44 693.88 5598.52 1698.31 2493.21 9097.15 4698.33 4891.35 6599.86 995.63 6899.59 1799.62 16
mPP-MVS96.86 3996.60 4597.64 4999.40 1293.44 6898.50 1998.09 6793.27 8995.95 9598.33 4891.04 7399.88 595.20 8199.57 2499.60 19
ZNCC-MVS96.96 3196.67 4397.85 2899.37 1794.12 4898.49 2098.18 5092.64 11896.39 7998.18 6691.61 5899.88 595.59 7399.55 2599.57 24
3Dnovator+91.43 495.40 8394.48 10398.16 1596.90 17295.34 1698.48 2197.87 11394.65 4488.53 27398.02 7683.69 16899.71 4293.18 13098.96 9499.44 53
RRT_MVS93.10 15892.83 14593.93 23394.76 28088.04 24498.47 2296.55 25093.44 8290.01 23297.04 14180.64 22897.93 26794.33 10690.21 25995.83 237
IS-MVSNet94.90 10094.52 10196.05 12297.67 13590.56 16598.44 2396.22 26493.21 9093.99 13797.74 9785.55 14598.45 20189.98 18597.86 12499.14 82
SteuartSystems-ACMMP97.62 797.53 797.87 2798.39 8794.25 4298.43 2498.27 3195.34 1198.11 2098.56 2094.53 1299.71 4296.57 3199.62 1599.65 12
Skip Steuart: Steuart Systems R&D Blog.
MP-MVScopyleft96.77 4696.45 5597.72 4299.39 1493.80 5798.41 2598.06 7793.37 8595.54 11298.34 4590.59 8299.88 594.83 9499.54 2799.49 45
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
QAPM93.45 14492.27 17196.98 7796.77 17992.62 9198.39 2698.12 6084.50 31588.27 27997.77 9582.39 20199.81 3085.40 27798.81 9898.51 137
nrg03094.05 12293.31 13396.27 11195.22 25794.59 3298.34 2797.46 16192.93 10791.21 20496.64 16487.23 12498.22 21694.99 9085.80 29695.98 232
CPTT-MVS95.57 8195.19 8496.70 8099.27 2891.48 12898.33 2898.11 6387.79 25995.17 11898.03 7487.09 12599.61 6693.51 12299.42 4999.02 92
test072699.45 395.36 1398.31 2998.29 2694.92 2898.99 498.92 295.08 8
CSCG96.05 6995.91 6796.46 9699.24 3090.47 16898.30 3098.57 1289.01 21893.97 13997.57 11492.62 3399.76 3494.66 10199.27 6899.15 81
GST-MVS96.85 4196.52 5097.82 3299.36 2094.14 4798.29 3198.13 5892.72 11596.70 6098.06 7291.35 6599.86 994.83 9499.28 6699.47 50
canonicalmvs96.02 7095.45 7697.75 4097.59 14395.15 2598.28 3297.60 14394.52 4696.27 8296.12 19587.65 11499.18 13196.20 4694.82 18898.91 108
bld_raw_conf00593.06 16192.54 16394.60 19494.64 28889.95 18398.28 3294.50 33194.06 5790.23 21896.99 14478.34 27298.12 23194.73 10091.09 24595.74 249
test250691.60 21490.78 22294.04 22297.66 13783.81 31798.27 3475.53 38093.43 8395.23 11698.21 6267.21 34499.07 14793.01 13798.49 10799.25 74
OpenMVScopyleft89.19 1292.86 17291.68 18996.40 10095.34 24692.73 8798.27 3498.12 6084.86 31085.78 31697.75 9678.89 26499.74 3587.50 24398.65 10396.73 211
test_low_dy_conf_00193.13 15692.80 14894.14 21794.47 29488.64 22598.26 3696.94 21692.53 12090.93 20797.16 13380.39 23497.99 25293.40 12791.12 24395.77 246
Vis-MVSNetpermissive95.23 8994.81 9196.51 9197.18 15391.58 12598.26 3698.12 6094.38 5194.90 12098.15 6782.28 20298.92 15991.45 16798.58 10699.01 96
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
SED-MVS98.05 297.99 198.24 1099.42 795.30 1898.25 3898.27 3195.13 1999.19 198.89 495.54 599.85 1897.52 599.66 1099.56 27
OPU-MVS98.55 398.82 6096.86 398.25 3898.26 5896.04 299.24 12695.36 7899.59 1799.56 27
ACMMPcopyleft96.27 6495.93 6697.28 6299.24 3092.62 9198.25 3898.81 392.99 9994.56 12798.39 3988.96 9699.85 1894.57 10497.63 13099.36 64
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
GeoE93.89 12793.28 13495.72 13896.96 17189.75 18798.24 4196.92 22289.47 20692.12 18097.21 13184.42 15898.39 20687.71 23296.50 16099.01 96
SF-MVS97.39 1197.13 1398.17 1499.02 4695.28 2098.23 4298.27 3192.37 12598.27 1898.65 1693.33 2199.72 3996.49 3399.52 2999.51 39
MVSFormer95.37 8495.16 8595.99 12696.34 20391.21 13998.22 4397.57 14791.42 15296.22 8397.32 12586.20 13797.92 26894.07 11099.05 9098.85 115
test_djsdf93.07 16092.76 14994.00 22493.49 32588.70 22498.22 4397.57 14791.42 15290.08 23095.55 22882.85 18997.92 26894.07 11091.58 23295.40 267
test111193.19 15292.82 14694.30 21297.58 14584.56 30998.21 4589.02 36893.53 7894.58 12698.21 6272.69 31499.05 15093.06 13398.48 10999.28 71
ECVR-MVScopyleft93.19 15292.73 15394.57 20097.66 13785.41 29498.21 4588.23 36993.43 8394.70 12498.21 6272.57 31599.07 14793.05 13498.49 10799.25 74
DVP-MVScopyleft97.91 397.81 398.22 1299.45 395.36 1398.21 4597.85 11894.92 2898.73 1098.87 695.08 899.84 2397.52 599.67 699.48 47
Zhenlong Yuan, Jinguo Luo, Fei Shen, Zhaoxin Li, Cong Liu, Tianlu Mao, Zhaoqi Wang: DVP-MVS: Synergize Depth-Edge and Visibility Prior for Multi-View Stereo. AAAI2025
test_0728_SECOND98.51 499.45 395.93 598.21 4598.28 2899.86 997.52 599.67 699.75 5
PHI-MVS96.77 4696.46 5497.71 4498.40 8594.07 5198.21 4598.45 1689.86 19597.11 5098.01 7792.52 3799.69 4896.03 5399.53 2899.36 64
#test#97.02 2796.75 3897.83 2999.42 794.12 4898.15 5098.32 2292.57 11997.18 4498.29 5492.08 4499.83 2695.12 8499.59 1799.54 34
FC-MVSNet-test93.94 12693.57 11995.04 16895.48 23791.45 13198.12 5198.71 693.37 8590.23 21896.70 15887.66 11397.85 27491.49 16590.39 25795.83 237
FIs94.09 12093.70 11595.27 16095.70 22992.03 11198.10 5298.68 893.36 8790.39 21596.70 15887.63 11597.94 26492.25 14590.50 25695.84 236
Vis-MVSNet (Re-imp)94.15 11593.88 11194.95 17797.61 14187.92 24798.10 5295.80 27892.22 12793.02 15997.45 12084.53 15797.91 27188.24 22297.97 12299.02 92
VDDNet93.05 16292.07 17496.02 12496.84 17490.39 17298.08 5495.85 27686.22 29095.79 10098.46 3067.59 34199.19 12994.92 9194.85 18698.47 143
TSAR-MVS + MP.97.42 997.33 1197.69 4599.25 2994.24 4398.07 5597.85 11893.72 6998.57 1398.35 4293.69 1899.40 11397.06 1599.46 4499.44 53
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
Anonymous2023121190.63 26089.42 27194.27 21398.24 10189.19 21498.05 5697.89 10979.95 34988.25 28094.96 24672.56 31698.13 22689.70 19385.14 30695.49 257
WR-MVS_H92.00 20391.35 19993.95 22995.09 26489.47 19898.04 5798.68 891.46 15088.34 27594.68 26185.86 14197.56 29985.77 27284.24 32194.82 301
test_part192.21 19891.10 21295.51 15097.80 12992.66 8998.02 5897.68 13589.79 20088.80 26796.02 20076.85 28798.18 22190.86 17484.11 32395.69 252
Anonymous2024052991.98 20490.73 22595.73 13798.14 11289.40 20297.99 5997.72 13079.63 35193.54 14797.41 12369.94 33299.56 8591.04 17391.11 24498.22 159
SR-MVS-dyc-post96.88 3896.80 3497.11 7399.02 4692.34 9897.98 6098.03 8893.52 7997.43 3698.51 2691.40 6399.56 8596.05 5099.26 7099.43 55
RE-MVS-def96.72 4099.02 4692.34 9897.98 6098.03 8893.52 7997.43 3698.51 2690.71 8096.05 5099.26 7099.43 55
SR-MVS97.01 2996.86 2797.47 5499.09 3893.27 7597.98 6098.07 7493.75 6897.45 3398.48 2991.43 6299.59 7296.22 4199.27 6899.54 34
APD-MVS_3200maxsize96.81 4496.71 4197.12 7299.01 4992.31 10197.98 6098.06 7793.11 9697.44 3498.55 2290.93 7599.55 8896.06 4999.25 7299.51 39
tttt051792.96 16692.33 17094.87 18197.11 15887.16 26497.97 6492.09 35690.63 17893.88 14197.01 14376.50 28999.06 14990.29 18495.45 17798.38 153
test117296.93 3496.86 2797.15 7099.10 3692.34 9897.96 6598.04 8593.79 6797.35 3998.53 2491.40 6399.56 8596.30 3799.30 6399.55 31
SMA-MVScopyleft97.35 1397.03 1998.30 899.06 4295.42 1097.94 6698.18 5090.57 18398.85 998.94 193.33 2199.83 2696.72 2699.68 499.63 14
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
LFMVS93.60 13892.63 15696.52 8898.13 11391.27 13697.94 6693.39 34790.57 18396.29 8198.31 5169.00 33499.16 13394.18 10995.87 16999.12 86
iter_conf_final93.60 13893.11 13795.04 16897.13 15791.30 13497.92 6895.65 28692.98 10491.60 18896.64 16479.28 25498.13 22695.34 7991.49 23495.70 251
SD-MVS97.41 1097.53 797.06 7498.57 7994.46 3497.92 6898.14 5794.82 3499.01 398.55 2294.18 1497.41 31496.94 1799.64 1399.32 66
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
abl_696.40 5996.21 6196.98 7798.89 5892.20 10697.89 7098.03 8893.34 8897.22 4398.42 3587.93 11099.72 3995.10 8599.07 8999.02 92
UGNet94.04 12393.28 13496.31 10796.85 17391.19 14297.88 7197.68 13594.40 4993.00 16096.18 19173.39 31399.61 6691.72 15898.46 11098.13 162
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
MTMP97.86 7282.03 377
alignmvs95.87 7595.23 8397.78 3697.56 14695.19 2297.86 7297.17 19494.39 5096.47 7596.40 18385.89 14099.20 12896.21 4595.11 18498.95 103
VPA-MVSNet93.24 15092.48 16795.51 15095.70 22992.39 9797.86 7298.66 1092.30 12692.09 18295.37 23480.49 23198.40 20393.95 11385.86 29595.75 247
EPNet95.20 9194.56 9897.14 7192.80 33892.68 8897.85 7594.87 32496.64 192.46 16897.80 9486.23 13499.65 5793.72 12098.62 10499.10 88
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
PS-CasMVS91.55 21990.84 22093.69 24494.96 26888.28 23597.84 7698.24 3891.46 15088.04 28595.80 21179.67 24897.48 30787.02 25284.54 31895.31 273
EIA-MVS95.53 8295.47 7595.71 13997.06 16389.63 18997.82 7797.87 11393.57 7393.92 14095.04 24590.61 8198.95 15794.62 10298.68 10298.54 133
CP-MVSNet91.89 20691.24 20693.82 23795.05 26588.57 22897.82 7798.19 4891.70 14388.21 28195.76 21681.96 20897.52 30587.86 22784.65 31395.37 270
API-MVS94.84 10394.49 10295.90 12897.90 12492.00 11397.80 7997.48 15689.19 21494.81 12296.71 15688.84 9899.17 13288.91 21498.76 10096.53 214
pm-mvs190.72 25789.65 26993.96 22894.29 30389.63 18997.79 8096.82 23189.07 21686.12 31595.48 23278.61 26797.78 28186.97 25381.67 33994.46 317
testtj96.93 3496.56 4898.05 2099.10 3694.66 3197.78 8198.22 4392.74 11497.59 2998.20 6591.96 4999.86 994.21 10899.25 7299.63 14
PEN-MVS91.20 23890.44 23493.48 25394.49 29387.91 24997.76 8298.18 5091.29 15587.78 29095.74 21880.35 23597.33 31885.46 27682.96 33595.19 282
PS-MVSNAJss93.74 13493.51 12494.44 20393.91 31289.28 21097.75 8397.56 15092.50 12289.94 23396.54 17688.65 10198.18 22193.83 11990.90 25095.86 233
HQP_MVS93.78 13393.43 12994.82 18396.21 20789.99 17897.74 8497.51 15394.85 3091.34 19596.64 16481.32 21898.60 18993.02 13592.23 22095.86 233
plane_prior297.74 8494.85 30
9.1496.75 3898.93 5197.73 8698.23 4291.28 15897.88 2798.44 3293.00 2599.65 5795.76 6199.47 42
jajsoiax92.42 18491.89 18294.03 22393.33 33088.50 23197.73 8697.53 15192.00 13888.85 26496.50 17875.62 30098.11 23393.88 11791.56 23395.48 258
TransMVSNet (Re)88.94 28687.56 29393.08 26994.35 29988.45 23397.73 8695.23 30687.47 26884.26 33095.29 23679.86 24597.33 31879.44 32974.44 35893.45 337
VDD-MVS93.82 13193.08 13896.02 12497.88 12589.96 18297.72 8995.85 27692.43 12395.86 9798.44 3268.42 33899.39 11496.31 3694.85 18698.71 126
APD-MVScopyleft96.95 3296.60 4598.01 2299.03 4594.93 2897.72 8998.10 6591.50 14898.01 2298.32 5092.33 4099.58 7594.85 9299.51 3399.53 38
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
bld_raw_dy_0_6492.37 18791.69 18894.39 20694.28 30489.73 18897.71 9193.65 34492.78 11390.46 21396.67 16275.88 29597.97 25692.92 13990.89 25195.48 258
thres100view90092.43 18391.58 19294.98 17497.92 12289.37 20497.71 9194.66 32692.20 12993.31 15494.90 25078.06 27899.08 14481.40 31394.08 19796.48 217
v7n90.76 25489.86 25893.45 25693.54 32287.60 25597.70 9397.37 17988.85 22587.65 29294.08 29381.08 22098.10 23484.68 28583.79 32994.66 313
ETH3D-3000-0.197.07 2396.71 4198.14 1698.90 5595.33 1797.68 9498.24 3891.57 14697.90 2698.37 4092.61 3499.66 5695.59 7399.51 3399.43 55
MSLP-MVS++96.94 3397.06 1596.59 8698.72 6391.86 11697.67 9598.49 1394.66 4397.24 4298.41 3892.31 4298.94 15896.61 2999.46 4498.96 101
MAR-MVS94.22 11393.46 12696.51 9198.00 11792.19 10797.67 9597.47 15988.13 25093.00 16095.84 20884.86 15399.51 9887.99 22598.17 11897.83 177
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
LS3D93.57 14192.61 15996.47 9497.59 14391.61 12297.67 9597.72 13085.17 30590.29 21798.34 4584.60 15599.73 3683.85 29698.27 11498.06 167
UA-Net95.95 7395.53 7297.20 6997.67 13592.98 8297.65 9898.13 5894.81 3596.61 6798.35 4288.87 9799.51 9890.36 18297.35 14099.11 87
thres600view792.49 18291.60 19195.18 16397.91 12389.47 19897.65 9894.66 32692.18 13393.33 15394.91 24978.06 27899.10 13981.61 31094.06 20096.98 201
PGM-MVS96.81 4496.53 4997.65 4799.35 2293.53 6697.65 9898.98 192.22 12797.14 4798.44 3291.17 7199.85 1894.35 10599.46 4499.57 24
LPG-MVS_test92.94 16892.56 16094.10 21896.16 21288.26 23697.65 9897.46 16191.29 15590.12 22697.16 13379.05 25798.73 17692.25 14591.89 22895.31 273
DTE-MVSNet90.56 26189.75 26593.01 27093.95 31087.25 25997.64 10297.65 13990.74 17187.12 30195.68 22279.97 24397.00 32983.33 29781.66 34094.78 308
mvs_tets92.31 19091.76 18493.94 23193.41 32788.29 23497.63 10397.53 15192.04 13688.76 26896.45 18074.62 30498.09 23793.91 11591.48 23595.45 263
h-mvs3394.15 11593.52 12396.04 12397.81 12890.22 17397.62 10497.58 14695.19 1696.74 5897.45 12083.67 16999.61 6695.85 5779.73 34598.29 158
ACMMP_NAP97.20 1696.86 2798.23 1199.09 3895.16 2497.60 10598.19 4892.82 11097.93 2598.74 1391.60 5999.86 996.26 3899.52 2999.67 11
iter_conf0593.18 15592.63 15694.83 18296.64 18390.69 16297.60 10595.53 29292.52 12191.58 18996.64 16476.35 29398.13 22695.43 7791.42 23795.68 254
Anonymous20240521192.07 20290.83 22195.76 13298.19 10888.75 22297.58 10795.00 31586.00 29393.64 14497.45 12066.24 35199.53 9390.68 17992.71 21399.01 96
ACMM89.79 892.96 16692.50 16694.35 20896.30 20588.71 22397.58 10797.36 18191.40 15490.53 21196.65 16379.77 24698.75 17491.24 17191.64 23095.59 256
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
dcpmvs_296.37 6197.05 1794.31 21198.96 5084.11 31497.56 10997.51 15393.92 6197.43 3698.52 2592.75 2899.32 12097.32 1399.50 3699.51 39
tfpnnormal89.70 28088.40 28593.60 24795.15 26090.10 17497.56 10998.16 5487.28 27486.16 31494.63 26477.57 28398.05 24474.48 34884.59 31692.65 346
HPM-MVS++copyleft97.34 1496.97 2298.47 599.08 4096.16 497.55 11197.97 10395.59 596.61 6797.89 8292.57 3599.84 2395.95 5499.51 3399.40 59
TranMVSNet+NR-MVSNet92.50 18091.63 19095.14 16594.76 28092.07 10997.53 11298.11 6392.90 10889.56 24696.12 19583.16 17797.60 29789.30 20383.20 33495.75 247
anonymousdsp92.16 19991.55 19393.97 22792.58 34289.55 19497.51 11397.42 17489.42 20888.40 27494.84 25380.66 22797.88 27391.87 15591.28 24094.48 316
VNet95.89 7495.45 7697.21 6898.07 11692.94 8397.50 11498.15 5593.87 6397.52 3097.61 11185.29 14799.53 9395.81 6095.27 18099.16 79
GBi-Net91.35 23090.27 24294.59 19596.51 19391.18 14397.50 11496.93 21888.82 22889.35 25294.51 26773.87 30897.29 32086.12 26588.82 26995.31 273
test191.35 23090.27 24294.59 19596.51 19391.18 14397.50 11496.93 21888.82 22889.35 25294.51 26773.87 30897.29 32086.12 26588.82 26995.31 273
FMVSNet189.88 27788.31 28694.59 19595.41 23991.18 14397.50 11496.93 21886.62 28487.41 29694.51 26765.94 35397.29 32083.04 30087.43 28295.31 273
thisisatest053093.03 16392.21 17295.49 15397.07 16089.11 21697.49 11892.19 35590.16 19094.09 13596.41 18276.43 29299.05 15090.38 18195.68 17598.31 157
ETV-MVS96.02 7095.89 6896.40 10097.16 15492.44 9697.47 11997.77 12294.55 4596.48 7494.51 26791.23 6998.92 15995.65 6698.19 11697.82 178
XXY-MVS92.16 19991.23 20794.95 17794.75 28290.94 15297.47 11997.43 17389.14 21588.90 26196.43 18179.71 24798.24 21489.56 19787.68 27995.67 255
114514_t93.95 12593.06 13996.63 8399.07 4191.61 12297.46 12197.96 10477.99 35793.00 16097.57 11486.14 13999.33 11889.22 20799.15 8198.94 104
tfpn200view992.38 18691.52 19594.95 17797.85 12689.29 20897.41 12294.88 32192.19 13193.27 15694.46 27278.17 27499.08 14481.40 31394.08 19796.48 217
thres40092.42 18491.52 19595.12 16797.85 12689.29 20897.41 12294.88 32192.19 13193.27 15694.46 27278.17 27499.08 14481.40 31394.08 19796.98 201
FMVSNet291.31 23390.08 25194.99 17296.51 19392.21 10497.41 12296.95 21588.82 22888.62 27094.75 25873.87 30897.42 31385.20 28088.55 27495.35 271
DeepC-MVS_fast93.89 296.93 3496.64 4497.78 3698.64 7494.30 3897.41 12298.04 8594.81 3596.59 6998.37 4091.24 6799.64 6595.16 8299.52 2999.42 58
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
UniMVSNet (Re)93.31 14892.55 16195.61 14495.39 24093.34 7397.39 12698.71 693.14 9590.10 22894.83 25487.71 11298.03 24891.67 16383.99 32495.46 262
NR-MVSNet92.34 18891.27 20595.53 14994.95 26993.05 7997.39 12698.07 7492.65 11784.46 32795.71 21985.00 15197.77 28389.71 19283.52 33195.78 241
DP-MVS92.76 17791.51 19796.52 8898.77 6190.99 14997.38 12896.08 26982.38 33489.29 25597.87 8583.77 16799.69 4881.37 31696.69 15698.89 112
ACMP89.59 1092.62 17992.14 17394.05 22196.40 20088.20 23997.36 12997.25 19091.52 14788.30 27796.64 16478.46 26998.72 17991.86 15691.48 23595.23 280
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
pmmvs687.81 30186.19 30592.69 28191.32 35186.30 28097.34 13096.41 25680.59 34884.05 33594.37 27667.37 34397.67 28984.75 28479.51 34794.09 329
v891.29 23590.53 23393.57 25094.15 30588.12 24397.34 13097.06 20688.99 21988.32 27694.26 28583.08 18098.01 25087.62 24083.92 32794.57 315
NCCC97.30 1597.03 1998.11 1798.77 6195.06 2697.34 13098.04 8595.96 297.09 5197.88 8493.18 2499.71 4295.84 5999.17 7999.56 27
v1091.04 24490.23 24593.49 25294.12 30688.16 24297.32 13397.08 20388.26 24488.29 27894.22 28882.17 20597.97 25686.45 25984.12 32294.33 321
V4291.58 21790.87 21693.73 24094.05 30988.50 23197.32 13396.97 21488.80 23189.71 23994.33 27882.54 19698.05 24489.01 21285.07 30894.64 314
DeepC-MVS93.07 396.06 6895.66 7197.29 6197.96 11893.17 7797.30 13598.06 7793.92 6193.38 15298.66 1486.83 12799.73 3695.60 7299.22 7598.96 101
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
casdiffmvs95.64 7895.49 7496.08 11996.76 18190.45 16997.29 13697.44 17094.00 5995.46 11497.98 7987.52 11898.73 17695.64 6797.33 14199.08 89
CNVR-MVS97.68 697.44 998.37 798.90 5595.86 697.27 13798.08 6895.81 497.87 2898.31 5194.26 1399.68 5197.02 1699.49 4099.57 24
PVSNet_Blended_VisFu95.27 8794.91 9096.38 10398.20 10690.86 15597.27 13798.25 3690.21 18894.18 13497.27 12787.48 11999.73 3693.53 12197.77 12898.55 132
mvs-test193.63 13793.69 11693.46 25596.02 21984.61 30897.24 13996.72 23493.85 6492.30 17595.76 21683.08 18098.89 16391.69 16196.54 15996.87 207
MTAPA97.08 2296.78 3697.97 2599.37 1794.42 3697.24 13998.08 6895.07 2496.11 8698.59 1890.88 7799.90 296.18 4799.50 3699.58 22
plane_prior89.99 17897.24 13994.06 5792.16 224
PAPM_NR95.01 9494.59 9796.26 11298.89 5890.68 16397.24 13997.73 12791.80 14192.93 16596.62 17389.13 9599.14 13689.21 20897.78 12798.97 100
ACMH87.59 1690.53 26289.42 27193.87 23596.21 20787.92 24797.24 13996.94 21688.45 23983.91 33696.27 18971.92 31798.62 18884.43 28989.43 26595.05 286
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
UniMVSNet_ETH3D91.34 23290.22 24794.68 19394.86 27687.86 25097.23 14497.46 16187.99 25189.90 23496.92 14966.35 34998.23 21590.30 18390.99 24897.96 168
VPNet92.23 19691.31 20294.99 17295.56 23390.96 15197.22 14597.86 11792.96 10690.96 20696.62 17375.06 30298.20 21891.90 15383.65 33095.80 240
DPE-MVScopyleft97.86 497.65 598.47 599.17 3495.78 797.21 14698.35 2095.16 1898.71 1298.80 1195.05 1099.89 496.70 2799.73 199.73 9
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
baseline192.82 17591.90 18195.55 14897.20 15290.77 16097.19 14794.58 32992.20 12992.36 17296.34 18684.16 16398.21 21789.20 20983.90 32897.68 183
F-COLMAP93.58 14092.98 14195.37 15998.40 8588.98 21897.18 14897.29 18787.75 26290.49 21297.10 13885.21 14899.50 10186.70 25596.72 15597.63 184
UniMVSNet_NR-MVSNet93.37 14692.67 15595.47 15695.34 24692.83 8497.17 14998.58 1192.98 10490.13 22495.80 21188.37 10697.85 27491.71 15983.93 32595.73 250
DU-MVS92.90 17092.04 17595.49 15394.95 26992.83 8497.16 15098.24 3893.02 9890.13 22495.71 21983.47 17297.85 27491.71 15983.93 32595.78 241
baseline95.58 8095.42 7896.08 11996.78 17890.41 17197.16 15097.45 16693.69 7295.65 10897.85 8887.29 12298.68 18295.66 6397.25 14499.13 83
zzz-MVS97.07 2396.77 3797.97 2599.37 1794.42 3697.15 15298.08 6895.07 2496.11 8698.59 1890.88 7799.90 296.18 4799.50 3699.58 22
Effi-MVS+-dtu93.08 15993.21 13692.68 28296.02 21983.25 32497.14 15396.72 23493.85 6491.20 20593.44 31483.08 18098.30 21291.69 16195.73 17396.50 216
MCST-MVS97.18 1796.84 3098.20 1399.30 2695.35 1597.12 15498.07 7493.54 7796.08 8897.69 10093.86 1699.71 4296.50 3299.39 5399.55 31
MVSTER93.20 15192.81 14794.37 20796.56 19089.59 19297.06 15597.12 19891.24 15991.30 19895.96 20282.02 20798.05 24493.48 12390.55 25495.47 261
ETH3 D test640096.16 6795.52 7398.07 1998.90 5595.06 2697.03 15698.21 4488.16 24896.64 6597.70 9991.18 7099.67 5392.44 14299.47 4299.48 47
Fast-Effi-MVS+-dtu92.29 19291.99 17893.21 26595.27 25385.52 29297.03 15696.63 24692.09 13489.11 26095.14 24280.33 23698.08 23887.54 24294.74 19196.03 231
DP-MVS Recon95.68 7795.12 8797.37 5799.19 3394.19 4497.03 15698.08 6888.35 24295.09 11997.65 10589.97 8999.48 10392.08 15298.59 10598.44 148
xxxxxxxxxxxxxcwj97.36 1297.20 1297.83 2998.91 5394.28 3997.02 15997.22 19195.35 998.27 1898.65 1693.33 2199.72 3996.49 3399.52 2999.51 39
save fliter98.91 5394.28 3997.02 15998.02 9295.35 9
CANet96.39 6096.02 6597.50 5397.62 14093.38 7097.02 15997.96 10495.42 894.86 12197.81 9287.38 12199.82 2996.88 2099.20 7799.29 68
FMVSNet391.78 20890.69 22795.03 17096.53 19292.27 10397.02 15996.93 21889.79 20089.35 25294.65 26377.01 28697.47 30886.12 26588.82 26995.35 271
Baseline_NR-MVSNet91.20 23890.62 22892.95 27393.83 31588.03 24597.01 16395.12 31188.42 24089.70 24095.13 24383.47 17297.44 31189.66 19583.24 33393.37 338
ETH3D cwj APD-0.1696.56 5496.06 6498.05 2098.26 10095.19 2296.99 16498.05 8489.85 19797.26 4198.22 6191.80 5299.69 4894.84 9399.28 6699.27 73
ACMH+87.92 1490.20 27089.18 27693.25 26296.48 19686.45 27896.99 16496.68 24088.83 22784.79 32696.22 19070.16 33098.53 19584.42 29088.04 27694.77 309
patch_mono-296.83 4397.44 995.01 17199.05 4385.39 29696.98 16698.77 594.70 4197.99 2398.66 1493.61 1999.91 197.67 499.50 3699.72 10
OurMVSNet-221017-090.51 26390.19 24991.44 31093.41 32781.25 33796.98 16696.28 26091.68 14486.55 31196.30 18774.20 30797.98 25388.96 21387.40 28495.09 283
MP-MVS-pluss96.70 4896.27 5997.98 2499.23 3294.71 3096.96 16898.06 7790.67 17495.55 11098.78 1291.07 7299.86 996.58 3099.55 2599.38 62
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
Regformer-396.85 4196.80 3497.01 7598.34 9092.02 11296.96 16897.76 12395.01 2697.08 5298.42 3591.71 5599.54 9096.80 2299.13 8399.48 47
Regformer-496.97 3096.87 2697.25 6498.34 9092.66 8996.96 16898.01 9595.12 2297.14 4798.42 3591.82 5199.61 6696.90 1999.13 8399.50 43
v2v48291.59 21590.85 21993.80 23893.87 31488.17 24196.94 17196.88 22689.54 20389.53 24794.90 25081.70 21498.02 24989.25 20685.04 31095.20 281
LCM-MVSNet-Re92.50 18092.52 16592.44 28596.82 17781.89 33396.92 17293.71 34392.41 12484.30 32994.60 26585.08 15097.03 32591.51 16497.36 13998.40 151
COLMAP_ROBcopyleft87.81 1590.40 26589.28 27493.79 23997.95 11987.13 26596.92 17295.89 27582.83 33286.88 30997.18 13273.77 31199.29 12378.44 33393.62 20594.95 288
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
EI-MVSNet-Vis-set96.51 5596.47 5296.63 8398.24 10191.20 14196.89 17497.73 12794.74 4096.49 7398.49 2890.88 7799.58 7596.44 3598.32 11399.13 83
EI-MVSNet-UG-set96.34 6296.30 5896.47 9498.20 10690.93 15396.86 17597.72 13094.67 4296.16 8598.46 3090.43 8399.58 7596.23 4097.96 12398.90 109
test_yl94.78 10594.23 10796.43 9897.74 13291.22 13796.85 17697.10 20091.23 16095.71 10296.93 14684.30 16099.31 12193.10 13195.12 18298.75 120
DCV-MVSNet94.78 10594.23 10796.43 9897.74 13291.22 13796.85 17697.10 20091.23 16095.71 10296.93 14684.30 16099.31 12193.10 13195.12 18298.75 120
v114491.37 22990.60 22993.68 24593.89 31388.23 23896.84 17897.03 21188.37 24189.69 24194.39 27482.04 20697.98 25387.80 22985.37 30194.84 298
v14419291.06 24390.28 24193.39 25793.66 32087.23 26196.83 17997.07 20487.43 26989.69 24194.28 28281.48 21698.00 25187.18 25084.92 31294.93 292
Regformer-197.10 2196.96 2397.54 5298.32 9393.48 6796.83 17997.99 10195.20 1597.46 3298.25 5992.48 3999.58 7596.79 2499.29 6499.55 31
Regformer-297.16 1996.99 2197.67 4698.32 9393.84 5696.83 17998.10 6595.24 1397.49 3198.25 5992.57 3599.61 6696.80 2299.29 6499.56 27
Fast-Effi-MVS+93.46 14392.75 15195.59 14596.77 17990.03 17596.81 18297.13 19788.19 24591.30 19894.27 28386.21 13698.63 18687.66 23896.46 16398.12 163
TSAR-MVS + GP.96.69 4996.49 5197.27 6398.31 9593.39 6996.79 18396.72 23494.17 5597.44 3497.66 10492.76 2799.33 11896.86 2197.76 12999.08 89
TAPA-MVS90.10 792.30 19191.22 20895.56 14698.33 9289.60 19196.79 18397.65 13981.83 33891.52 19197.23 13087.94 10998.91 16171.31 36098.37 11298.17 161
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
v14890.99 24690.38 23692.81 27893.83 31585.80 28896.78 18596.68 24089.45 20788.75 26993.93 29882.96 18797.82 27887.83 22883.25 33294.80 304
v192192090.85 25290.03 25593.29 26193.55 32186.96 26996.74 18697.04 20987.36 27189.52 24894.34 27780.23 23897.97 25686.27 26085.21 30594.94 290
Anonymous2024052186.42 31085.44 31089.34 33590.33 35679.79 35196.73 18795.92 27283.71 32583.25 33991.36 34263.92 35796.01 34178.39 33485.36 30292.22 352
v119291.07 24290.23 24593.58 24993.70 31887.82 25196.73 18797.07 20487.77 26089.58 24494.32 28080.90 22597.97 25686.52 25785.48 29994.95 288
PVSNet_BlendedMVS94.06 12193.92 11094.47 20298.27 9789.46 20096.73 18798.36 1790.17 18994.36 13095.24 23988.02 10799.58 7593.44 12490.72 25394.36 320
TAMVS94.01 12493.46 12695.64 14196.16 21290.45 16996.71 19096.89 22589.27 21293.46 15096.92 14987.29 12297.94 26488.70 21895.74 17298.53 134
MVS_Test94.89 10194.62 9695.68 14096.83 17689.55 19496.70 19197.17 19491.17 16295.60 10996.11 19887.87 11198.76 17393.01 13797.17 14798.72 124
SixPastTwentyTwo89.15 28488.54 28490.98 31793.49 32580.28 34796.70 19194.70 32590.78 16984.15 33295.57 22671.78 31997.71 28784.63 28685.07 30894.94 290
hse-mvs293.45 14492.99 14094.81 18597.02 16788.59 22796.69 19396.47 25395.19 1696.74 5896.16 19483.67 16998.48 20095.85 5779.13 34997.35 196
EPNet_dtu91.71 21091.28 20492.99 27193.76 31783.71 32096.69 19395.28 30293.15 9487.02 30595.95 20383.37 17597.38 31679.46 32896.84 15097.88 173
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
PLCcopyleft91.00 694.11 11993.43 12996.13 11898.58 7891.15 14796.69 19397.39 17687.29 27391.37 19496.71 15688.39 10599.52 9787.33 24697.13 14897.73 180
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
testgi87.97 29887.21 29890.24 32992.86 33680.76 33996.67 19694.97 31791.74 14285.52 31895.83 20962.66 36094.47 35976.25 34388.36 27595.48 258
AUN-MVS91.76 20990.75 22494.81 18597.00 16988.57 22896.65 19796.49 25289.63 20292.15 17896.12 19578.66 26698.50 19790.83 17579.18 34897.36 195
OPM-MVS93.28 14992.76 14994.82 18394.63 28990.77 16096.65 19797.18 19293.72 6991.68 18797.26 12879.33 25398.63 18692.13 14992.28 21995.07 284
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
HQP-NCC95.86 22296.65 19793.55 7490.14 220
ACMP_Plane95.86 22296.65 19793.55 7490.14 220
HQP-MVS93.19 15292.74 15294.54 20195.86 22289.33 20696.65 19797.39 17693.55 7490.14 22095.87 20680.95 22198.50 19792.13 14992.10 22595.78 241
EU-MVSNet88.72 29288.90 27988.20 33993.15 33374.21 36696.63 20294.22 33885.18 30487.32 29995.97 20176.16 29494.98 35585.27 27886.17 29295.41 264
v124090.70 25889.85 25993.23 26393.51 32486.80 27096.61 20397.02 21287.16 27689.58 24494.31 28179.55 25097.98 25385.52 27585.44 30094.90 295
K. test v387.64 30286.75 30390.32 32893.02 33579.48 35496.61 20392.08 35790.66 17680.25 35394.09 29267.21 34496.65 33685.96 27080.83 34394.83 299
thres20092.23 19691.39 19894.75 19297.61 14189.03 21796.60 20595.09 31292.08 13593.28 15594.00 29578.39 27199.04 15381.26 31794.18 19696.19 222
WTY-MVS94.71 10794.02 10996.79 7997.71 13492.05 11096.59 20697.35 18290.61 18094.64 12596.93 14686.41 13399.39 11491.20 17294.71 19298.94 104
CNLPA94.28 11293.53 12296.52 8898.38 8892.55 9396.59 20696.88 22690.13 19191.91 18497.24 12985.21 14899.09 14287.64 23997.83 12597.92 170
AdaColmapbinary94.34 11193.68 11796.31 10798.59 7691.68 12096.59 20697.81 12189.87 19492.15 17897.06 14083.62 17199.54 9089.34 20298.07 12097.70 182
IterMVS-LS92.29 19291.94 18093.34 25996.25 20686.97 26896.57 20997.05 20790.67 17489.50 24994.80 25686.59 12897.64 29289.91 18786.11 29495.40 267
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
AllTest90.23 26988.98 27893.98 22597.94 12086.64 27396.51 21095.54 29085.38 30185.49 31996.77 15470.28 32899.15 13480.02 32392.87 21096.15 225
EI-MVSNet93.03 16392.88 14493.48 25395.77 22786.98 26796.44 21197.12 19890.66 17691.30 19897.64 10886.56 12998.05 24489.91 18790.55 25495.41 264
CVMVSNet91.23 23691.75 18589.67 33495.77 22774.69 36596.44 21194.88 32185.81 29592.18 17797.64 10879.07 25695.58 35188.06 22495.86 17098.74 122
OMC-MVS95.09 9394.70 9596.25 11598.46 8191.28 13596.43 21397.57 14792.04 13694.77 12397.96 8187.01 12699.09 14291.31 16996.77 15298.36 155
test_prior493.66 6296.42 214
Effi-MVS+94.93 9994.45 10496.36 10596.61 18491.47 12996.41 21597.41 17591.02 16794.50 12895.92 20487.53 11798.78 17093.89 11696.81 15198.84 117
TEST998.70 6494.19 4496.41 21598.02 9288.17 24696.03 8997.56 11692.74 2999.59 72
train_agg96.30 6395.83 6997.72 4298.70 6494.19 4496.41 21598.02 9288.58 23596.03 8997.56 11692.73 3099.59 7295.04 8699.37 5899.39 60
MVS_030488.79 29087.57 29292.46 28494.65 28686.15 28696.40 21897.17 19486.44 28688.02 28691.71 33956.68 36697.03 32584.47 28892.58 21694.19 326
WR-MVS92.34 18891.53 19494.77 19095.13 26290.83 15796.40 21897.98 10291.88 14089.29 25595.54 22982.50 19797.80 27989.79 19185.27 30495.69 252
BH-untuned92.94 16892.62 15893.92 23497.22 15086.16 28596.40 21896.25 26390.06 19289.79 23896.17 19383.19 17698.35 20887.19 24997.27 14397.24 198
TDRefinement86.53 30884.76 31891.85 29782.23 37384.25 31196.38 22195.35 29884.97 30984.09 33394.94 24765.76 35498.34 21184.60 28774.52 35792.97 340
test_898.67 6694.06 5296.37 22298.01 9588.58 23595.98 9497.55 11892.73 3099.58 75
test_prior396.46 5796.20 6297.23 6598.67 6692.99 8096.35 22398.00 9792.80 11196.03 8997.59 11292.01 4699.41 11195.01 8799.38 5499.29 68
test_prior296.35 22392.80 11196.03 8997.59 11292.01 4695.01 8799.38 54
CDPH-MVS95.97 7295.38 7997.77 3898.93 5194.44 3596.35 22397.88 11186.98 27896.65 6497.89 8291.99 4899.47 10492.26 14399.46 4499.39 60
CDS-MVSNet94.14 11893.54 12195.93 12796.18 21091.46 13096.33 22697.04 20988.97 22193.56 14596.51 17787.55 11697.89 27289.80 19095.95 16798.44 148
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
sss94.51 10993.80 11396.64 8197.07 16091.97 11496.32 22798.06 7788.94 22294.50 12896.78 15384.60 15599.27 12491.90 15396.02 16598.68 128
1112_ss93.37 14692.42 16896.21 11697.05 16590.99 14996.31 22896.72 23486.87 28189.83 23796.69 16086.51 13199.14 13688.12 22393.67 20398.50 138
LTVRE_ROB88.41 1390.99 24689.92 25794.19 21496.18 21089.55 19496.31 22897.09 20287.88 25585.67 31795.91 20578.79 26598.57 19381.50 31189.98 26094.44 318
Andreas Kuhn, Heiko Hirschmüller, Daniel Scharstein, Helmut Mayer: A TV Prior for High-Quality Scalable Multi-View Stereo Reconstruction. International Journal of Computer Vision 2016
test_040286.46 30984.79 31791.45 30995.02 26685.55 29196.29 23094.89 32080.90 34382.21 34393.97 29768.21 33997.29 32062.98 36888.68 27391.51 357
agg_prior196.22 6695.77 7097.56 5198.67 6693.79 5896.28 23198.00 9788.76 23295.68 10497.55 11892.70 3299.57 8395.01 8799.32 6099.32 66
pmmvs589.86 27888.87 28092.82 27792.86 33686.23 28296.26 23295.39 29584.24 31787.12 30194.51 26774.27 30697.36 31787.61 24187.57 28094.86 297
xiu_mvs_v1_base_debu95.01 9494.76 9295.75 13496.58 18791.71 11796.25 23397.35 18292.99 9996.70 6096.63 17082.67 19299.44 10896.22 4197.46 13396.11 228
xiu_mvs_v1_base95.01 9494.76 9295.75 13496.58 18791.71 11796.25 23397.35 18292.99 9996.70 6096.63 17082.67 19299.44 10896.22 4197.46 13396.11 228
xiu_mvs_v1_base_debi95.01 9494.76 9295.75 13496.58 18791.71 11796.25 23397.35 18292.99 9996.70 6096.63 17082.67 19299.44 10896.22 4197.46 13396.11 228
MVS_111021_LR96.24 6596.19 6396.39 10298.23 10591.35 13396.24 23698.79 493.99 6095.80 9997.65 10589.92 9099.24 12695.87 5599.20 7798.58 131
CANet_DTU94.37 11093.65 11896.55 8796.46 19792.13 10896.21 23796.67 24294.38 5193.53 14897.03 14279.34 25299.71 4290.76 17698.45 11197.82 178
MVS_111021_HR96.68 5196.58 4796.99 7698.46 8192.31 10196.20 23898.90 294.30 5395.86 9797.74 9792.33 4099.38 11696.04 5299.42 4999.28 71
D2MVS91.30 23490.95 21492.35 28794.71 28485.52 29296.18 23998.21 4488.89 22486.60 31093.82 30179.92 24497.95 26389.29 20490.95 24993.56 334
BH-RMVSNet92.72 17891.97 17994.97 17597.16 15487.99 24696.15 24095.60 28790.62 17991.87 18597.15 13678.41 27098.57 19383.16 29897.60 13198.36 155
Anonymous2023120687.09 30586.14 30689.93 33291.22 35280.35 34496.11 24195.35 29883.57 32784.16 33193.02 31973.54 31295.61 34972.16 35786.14 29393.84 332
jason94.84 10394.39 10696.18 11795.52 23590.93 15396.09 24296.52 25189.28 21196.01 9397.32 12584.70 15498.77 17295.15 8398.91 9798.85 115
jason: jason.
EG-PatchMatch MVS87.02 30685.44 31091.76 30492.67 34085.00 30296.08 24396.45 25483.41 32979.52 35593.49 31257.10 36597.72 28679.34 33090.87 25292.56 347
131492.81 17692.03 17695.14 16595.33 24989.52 19796.04 24497.44 17087.72 26386.25 31395.33 23583.84 16698.79 16989.26 20597.05 14997.11 199
112194.71 10793.83 11297.34 5898.57 7993.64 6396.04 24497.73 12781.56 34195.68 10497.85 8890.23 8599.65 5787.68 23699.12 8698.73 123
MVS91.71 21090.44 23495.51 15095.20 25991.59 12496.04 24497.45 16673.44 36487.36 29895.60 22585.42 14699.10 13985.97 26997.46 13395.83 237
MG-MVS95.61 7995.38 7996.31 10798.42 8490.53 16696.04 24497.48 15693.47 8195.67 10798.10 6889.17 9499.25 12591.27 17098.77 9999.13 83
DeepPCF-MVS93.97 196.61 5297.09 1495.15 16498.09 11486.63 27696.00 24898.15 5595.43 797.95 2498.56 2093.40 2099.36 11796.77 2599.48 4199.45 51
diffmvs95.25 8895.13 8695.63 14296.43 19989.34 20595.99 24997.35 18292.83 10996.31 8097.37 12486.44 13298.67 18396.26 3897.19 14698.87 114
DELS-MVS96.61 5296.38 5797.30 6097.79 13093.19 7695.96 25098.18 5095.23 1495.87 9697.65 10591.45 6199.70 4795.87 5599.44 4899.00 99
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
旧先验295.94 25181.66 33997.34 4098.82 16792.26 143
baseline291.63 21390.86 21793.94 23194.33 30086.32 27995.92 25291.64 36089.37 20986.94 30694.69 26081.62 21598.69 18188.64 21994.57 19396.81 209
test20.0386.14 31485.40 31288.35 33790.12 35780.06 34995.90 25395.20 30788.59 23481.29 34693.62 31071.43 32192.65 36771.26 36181.17 34292.34 350
MVP-Stereo90.74 25690.08 25192.71 28093.19 33288.20 23995.86 25496.27 26186.07 29284.86 32594.76 25777.84 28197.75 28483.88 29598.01 12192.17 354
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
lupinMVS94.99 9894.56 9896.29 11096.34 20391.21 13995.83 25596.27 26188.93 22396.22 8396.88 15186.20 13798.85 16595.27 8099.05 9098.82 118
mvs_anonymous93.82 13193.74 11494.06 22096.44 19885.41 29495.81 25697.05 20789.85 19790.09 22996.36 18587.44 12097.75 28493.97 11296.69 15699.02 92
新几何295.79 257
无先验95.79 25797.87 11383.87 32399.65 5787.68 23698.89 112
OpenMVS_ROBcopyleft81.14 2084.42 32582.28 32890.83 31990.06 35884.05 31695.73 25994.04 34073.89 36380.17 35491.53 34159.15 36397.64 29266.92 36689.05 26890.80 361
原ACMM295.67 260
BH-w/o92.14 20191.75 18593.31 26096.99 17085.73 28995.67 26095.69 28288.73 23389.26 25794.82 25582.97 18698.07 24185.26 27996.32 16496.13 227
TR-MVS91.48 22390.59 23094.16 21696.40 20087.33 25695.67 26095.34 30187.68 26491.46 19295.52 23076.77 28898.35 20882.85 30293.61 20696.79 210
HY-MVS89.66 993.87 12892.95 14296.63 8397.10 15992.49 9595.64 26396.64 24389.05 21793.00 16095.79 21485.77 14399.45 10789.16 21194.35 19497.96 168
RPSCF90.75 25590.86 21790.42 32796.84 17476.29 36395.61 26496.34 25883.89 32191.38 19397.87 8576.45 29098.78 17087.16 25192.23 22096.20 221
MS-PatchMatch90.27 26789.77 26391.78 30294.33 30084.72 30795.55 26596.73 23386.17 29186.36 31295.28 23871.28 32297.80 27984.09 29198.14 11992.81 343
PAPR94.18 11493.42 13196.48 9397.64 13991.42 13295.55 26597.71 13488.99 21992.34 17495.82 21089.19 9399.11 13886.14 26497.38 13898.90 109
Test_1112_low_res92.84 17491.84 18395.85 13097.04 16689.97 18195.53 26796.64 24385.38 30189.65 24395.18 24085.86 14199.10 13987.70 23393.58 20898.49 140
FMVSNet587.29 30485.79 30891.78 30294.80 27987.28 25795.49 26895.28 30284.09 31983.85 33791.82 33662.95 35994.17 36078.48 33285.34 30393.91 331
PVSNet_Blended94.87 10294.56 9895.81 13198.27 9789.46 20095.47 26998.36 1788.84 22694.36 13096.09 19988.02 10799.58 7593.44 12498.18 11798.40 151
xiu_mvs_v2_base95.32 8695.29 8295.40 15897.22 15090.50 16795.44 27097.44 17093.70 7196.46 7696.18 19188.59 10499.53 9394.79 9997.81 12696.17 223
ab-mvs93.57 14192.55 16196.64 8197.28 14991.96 11595.40 27197.45 16689.81 19993.22 15896.28 18879.62 24999.46 10590.74 17793.11 20998.50 138
MIMVSNet184.93 32283.05 32490.56 32589.56 36284.84 30695.40 27195.35 29883.91 32080.38 35192.21 33457.23 36493.34 36570.69 36382.75 33893.50 335
ET-MVSNet_ETH3D91.49 22290.11 25095.63 14296.40 20091.57 12695.34 27393.48 34690.60 18275.58 36195.49 23180.08 24096.79 33494.25 10789.76 26398.52 135
test22298.24 10192.21 10495.33 27497.60 14379.22 35395.25 11597.84 9188.80 9999.15 8198.72 124
XVG-ACMP-BASELINE90.93 25090.21 24893.09 26894.31 30285.89 28795.33 27497.26 18891.06 16689.38 25195.44 23368.61 33698.60 18989.46 19991.05 24694.79 306
PS-MVSNAJ95.37 8495.33 8195.49 15397.35 14890.66 16495.31 27697.48 15693.85 6496.51 7295.70 22188.65 10199.65 5794.80 9798.27 11496.17 223
XVG-OURS-SEG-HR93.86 12993.55 12094.81 18597.06 16388.53 23095.28 27797.45 16691.68 14494.08 13697.68 10182.41 20098.90 16293.84 11892.47 21796.98 201
CLD-MVS92.98 16592.53 16494.32 21096.12 21689.20 21295.28 27797.47 15992.66 11689.90 23495.62 22480.58 22998.40 20392.73 14092.40 21895.38 269
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
DPM-MVS95.69 7694.92 8998.01 2298.08 11595.71 995.27 27997.62 14290.43 18695.55 11097.07 13991.72 5399.50 10189.62 19698.94 9598.82 118
PatchMatch-RL92.90 17092.02 17795.56 14698.19 10890.80 15895.27 27997.18 19287.96 25291.86 18695.68 22280.44 23298.99 15584.01 29297.54 13296.89 206
testdata195.26 28193.10 97
test0.0.03 189.37 28388.70 28191.41 31192.47 34485.63 29095.22 28292.70 35291.11 16486.91 30893.65 30979.02 25993.19 36678.00 33589.18 26795.41 264
CHOSEN 1792x268894.15 11593.51 12496.06 12198.27 9789.38 20395.18 28398.48 1585.60 29893.76 14397.11 13783.15 17899.61 6691.33 16898.72 10199.19 77
KD-MVS_self_test85.95 31684.95 31588.96 33689.55 36379.11 35795.13 28496.42 25585.91 29484.07 33490.48 34570.03 33194.82 35680.04 32272.94 36192.94 341
IB-MVS87.33 1789.91 27588.28 28794.79 18995.26 25687.70 25395.12 28593.95 34289.35 21087.03 30492.49 32570.74 32699.19 12989.18 21081.37 34197.49 193
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
DSMNet-mixed86.34 31186.12 30787.00 34489.88 36070.43 36994.93 28690.08 36677.97 35885.42 32192.78 32174.44 30593.96 36174.43 34995.14 18196.62 213
XVG-OURS93.72 13593.35 13294.80 18897.07 16088.61 22694.79 28797.46 16191.97 13993.99 13797.86 8781.74 21398.88 16492.64 14192.67 21596.92 205
SCA91.84 20791.18 21093.83 23695.59 23184.95 30494.72 28895.58 28990.82 16892.25 17693.69 30575.80 29798.10 23486.20 26295.98 16698.45 145
c3_l91.38 22790.89 21592.88 27595.58 23286.30 28094.68 28996.84 23088.17 24688.83 26694.23 28685.65 14497.47 30889.36 20184.63 31494.89 296
pmmvs490.93 25089.85 25994.17 21593.34 32990.79 15994.60 29096.02 27084.62 31387.45 29495.15 24181.88 21197.45 31087.70 23387.87 27894.27 325
HyFIR lowres test93.66 13692.92 14395.87 12998.24 10189.88 18494.58 29198.49 1385.06 30793.78 14295.78 21582.86 18898.67 18391.77 15795.71 17499.07 91
MDA-MVSNet-bldmvs85.00 32182.95 32591.17 31693.13 33483.33 32394.56 29295.00 31584.57 31465.13 36992.65 32270.45 32795.85 34573.57 35377.49 35194.33 321
PMMVS92.86 17292.34 16994.42 20594.92 27186.73 27294.53 29396.38 25784.78 31294.27 13295.12 24483.13 17998.40 20391.47 16696.49 16198.12 163
miper_ehance_all_eth91.59 21591.13 21192.97 27295.55 23486.57 27794.47 29496.88 22687.77 26088.88 26394.01 29486.22 13597.54 30189.49 19886.93 28694.79 306
pmmvs-eth3d86.22 31384.45 31991.53 30788.34 36787.25 25994.47 29495.01 31483.47 32879.51 35689.61 35269.75 33395.71 34883.13 29976.73 35491.64 355
cl____90.96 24990.32 23892.89 27495.37 24386.21 28394.46 29696.64 24387.82 25688.15 28394.18 28982.98 18597.54 30187.70 23385.59 29794.92 294
DIV-MVS_self_test90.97 24890.33 23792.88 27595.36 24486.19 28494.46 29696.63 24687.82 25688.18 28294.23 28682.99 18497.53 30387.72 23085.57 29894.93 292
cl2291.21 23790.56 23293.14 26796.09 21886.80 27094.41 29896.58 24987.80 25888.58 27293.99 29680.85 22697.62 29589.87 18986.93 28694.99 287
LF4IMVS87.94 29987.25 29689.98 33192.38 34780.05 35094.38 29995.25 30587.59 26684.34 32894.74 25964.31 35697.66 29184.83 28287.45 28192.23 351
thisisatest051592.29 19291.30 20395.25 16196.60 18588.90 22094.36 30092.32 35487.92 25393.43 15194.57 26677.28 28599.00 15489.42 20095.86 17097.86 174
GA-MVS91.38 22790.31 23994.59 19594.65 28687.62 25494.34 30196.19 26690.73 17290.35 21693.83 29971.84 31897.96 26187.22 24893.61 20698.21 160
IterMVS90.15 27289.67 26791.61 30695.48 23783.72 31994.33 30296.12 26889.99 19387.31 30094.15 29175.78 29996.27 34086.97 25386.89 28994.83 299
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
IterMVS-SCA-FT90.31 26689.81 26191.82 29995.52 23584.20 31394.30 30396.15 26790.61 18087.39 29794.27 28375.80 29796.44 33787.34 24586.88 29094.82 301
test-LLR91.42 22591.19 20992.12 29194.59 29080.66 34094.29 30492.98 34991.11 16490.76 20992.37 32779.02 25998.07 24188.81 21596.74 15397.63 184
TESTMET0.1,190.06 27389.42 27191.97 29494.41 29880.62 34294.29 30491.97 35887.28 27490.44 21492.47 32668.79 33597.67 28988.50 22196.60 15897.61 188
test-mter90.19 27189.54 27092.12 29194.59 29080.66 34094.29 30492.98 34987.68 26490.76 20992.37 32767.67 34098.07 24188.81 21596.74 15397.63 184
CMPMVSbinary62.92 2185.62 31984.92 31687.74 34189.14 36473.12 36894.17 30796.80 23273.98 36273.65 36394.93 24866.36 34897.61 29683.95 29491.28 24092.48 349
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
N_pmnet78.73 33278.71 33478.79 35092.80 33846.50 38194.14 30843.71 38478.61 35580.83 34791.66 34074.94 30396.36 33867.24 36584.45 31993.50 335
eth_miper_zixun_eth91.02 24590.59 23092.34 28895.33 24984.35 31094.10 30996.90 22388.56 23788.84 26594.33 27884.08 16497.60 29788.77 21784.37 32095.06 285
CostFormer91.18 24190.70 22692.62 28394.84 27781.76 33494.09 31094.43 33284.15 31892.72 16793.77 30379.43 25198.20 21890.70 17892.18 22397.90 171
tpm90.25 26889.74 26691.76 30493.92 31179.73 35293.98 31193.54 34588.28 24391.99 18393.25 31777.51 28497.44 31187.30 24787.94 27798.12 163
miper_enhance_ethall91.54 22091.01 21393.15 26695.35 24587.07 26693.97 31296.90 22386.79 28289.17 25993.43 31686.55 13097.64 29289.97 18686.93 28694.74 310
EGC-MVSNET68.77 33663.01 34186.07 34792.49 34382.24 33293.96 31390.96 3640.71 3812.62 38290.89 34353.66 36893.46 36357.25 37084.55 31782.51 367
TinyColmap86.82 30785.35 31391.21 31494.91 27382.99 32593.94 31494.02 34183.58 32681.56 34594.68 26162.34 36198.13 22675.78 34487.35 28592.52 348
CL-MVSNet_self_test86.31 31285.15 31489.80 33388.83 36581.74 33593.93 31596.22 26486.67 28385.03 32390.80 34478.09 27794.50 35774.92 34771.86 36293.15 339
miper_lstm_enhance90.50 26490.06 25491.83 29895.33 24983.74 31893.86 31696.70 23987.56 26787.79 28993.81 30283.45 17496.92 33187.39 24484.62 31594.82 301
USDC88.94 28687.83 29192.27 28994.66 28584.96 30393.86 31695.90 27487.34 27283.40 33895.56 22767.43 34298.19 22082.64 30689.67 26493.66 333
tpm289.96 27489.21 27592.23 29094.91 27381.25 33793.78 31894.42 33380.62 34791.56 19093.44 31476.44 29197.94 26485.60 27492.08 22797.49 193
ppachtmachnet_test88.35 29687.29 29591.53 30792.45 34583.57 32293.75 31995.97 27184.28 31685.32 32294.18 28979.00 26396.93 33075.71 34584.99 31194.10 327
new-patchmatchnet83.18 32781.87 32987.11 34386.88 37075.99 36493.70 32095.18 30885.02 30877.30 35988.40 35565.99 35293.88 36274.19 35270.18 36491.47 359
MSDG91.42 22590.24 24494.96 17697.15 15688.91 21993.69 32196.32 25985.72 29786.93 30796.47 17980.24 23798.98 15680.57 31995.05 18596.98 201
EPMVS90.70 25889.81 26193.37 25894.73 28384.21 31293.67 32288.02 37089.50 20592.38 17193.49 31277.82 28297.78 28186.03 26892.68 21498.11 166
cascas91.20 23890.08 25194.58 19994.97 26789.16 21593.65 32397.59 14579.90 35089.40 25092.92 32075.36 30198.36 20792.14 14894.75 19096.23 220
UnsupCasMVSNet_eth85.99 31584.45 31990.62 32489.97 35982.40 33093.62 32497.37 17989.86 19578.59 35892.37 32765.25 35595.35 35482.27 30870.75 36394.10 327
our_test_388.78 29187.98 29091.20 31592.45 34582.53 32793.61 32595.69 28285.77 29684.88 32493.71 30479.99 24296.78 33579.47 32786.24 29194.28 324
PM-MVS83.48 32681.86 33088.31 33887.83 36977.59 36193.43 32691.75 35986.91 27980.63 34989.91 35044.42 37295.84 34685.17 28176.73 35491.50 358
tpmrst91.44 22491.32 20191.79 30195.15 26079.20 35693.42 32795.37 29788.55 23893.49 14993.67 30882.49 19898.27 21390.41 18089.34 26697.90 171
PAPM91.52 22190.30 24095.20 16295.30 25289.83 18593.38 32896.85 22986.26 28988.59 27195.80 21184.88 15298.15 22475.67 34695.93 16897.63 184
testmvs13.36 34716.33 3504.48 3635.04 3852.26 38793.18 3293.28 3862.70 3798.24 38021.66 3772.29 3862.19 3817.58 3792.96 3799.00 377
YYNet185.87 31784.23 32190.78 32392.38 34782.46 32993.17 33095.14 31082.12 33667.69 36492.36 33078.16 27695.50 35377.31 33879.73 34594.39 319
MDA-MVSNet_test_wron85.87 31784.23 32190.80 32292.38 34782.57 32693.17 33095.15 30982.15 33567.65 36592.33 33378.20 27395.51 35277.33 33779.74 34494.31 323
PatchmatchNetpermissive91.91 20591.35 19993.59 24895.38 24184.11 31493.15 33295.39 29589.54 20392.10 18193.68 30782.82 19098.13 22684.81 28395.32 17998.52 135
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
tpmvs89.83 27989.15 27791.89 29694.92 27180.30 34693.11 33395.46 29486.28 28888.08 28492.65 32280.44 23298.52 19681.47 31289.92 26196.84 208
MDTV_nov1_ep13_2view70.35 37093.10 33483.88 32293.55 14682.47 19986.25 26198.38 153
MDTV_nov1_ep1390.76 22395.22 25780.33 34593.03 33595.28 30288.14 24992.84 16693.83 29981.34 21798.08 23882.86 30194.34 195
PVSNet86.66 1892.24 19591.74 18793.73 24097.77 13183.69 32192.88 33696.72 23487.91 25493.00 16094.86 25278.51 26899.05 15086.53 25697.45 13798.47 143
dp88.90 28888.26 28890.81 32094.58 29276.62 36292.85 33794.93 31985.12 30690.07 23193.07 31875.81 29698.12 23180.53 32087.42 28397.71 181
test_post192.81 33816.58 38080.53 23097.68 28886.20 262
pmmvs379.97 33177.50 33587.39 34282.80 37279.38 35592.70 33990.75 36570.69 36578.66 35787.47 36251.34 37093.40 36473.39 35469.65 36589.38 364
tpm cat188.36 29587.21 29891.81 30095.13 26280.55 34392.58 34095.70 28174.97 36187.45 29491.96 33578.01 28098.17 22380.39 32188.74 27296.72 212
PCF-MVS89.48 1191.56 21889.95 25696.36 10596.60 18592.52 9492.51 34197.26 18879.41 35288.90 26196.56 17584.04 16599.55 8877.01 34297.30 14297.01 200
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
test12313.04 34815.66 3515.18 3624.51 3863.45 38692.50 3421.81 3872.50 3807.58 38120.15 3783.67 3852.18 3827.13 3801.07 3809.90 376
GG-mvs-BLEND93.62 24693.69 31989.20 21292.39 34383.33 37687.98 28889.84 35171.00 32496.87 33282.08 30995.40 17894.80 304
new_pmnet82.89 32881.12 33288.18 34089.63 36180.18 34891.77 34492.57 35376.79 36075.56 36288.23 35761.22 36294.48 35871.43 35982.92 33689.87 363
MIMVSNet88.50 29486.76 30293.72 24294.84 27787.77 25291.39 34594.05 33986.41 28787.99 28792.59 32463.27 35895.82 34777.44 33692.84 21297.57 191
FPMVS71.27 33469.85 33675.50 35274.64 37559.03 37791.30 34691.50 36158.80 36957.92 37188.28 35629.98 37785.53 37253.43 37182.84 33781.95 368
KD-MVS_2432*160084.81 32382.64 32691.31 31291.07 35385.34 29891.22 34795.75 27985.56 29983.09 34090.21 34767.21 34495.89 34377.18 34062.48 36992.69 344
miper_refine_blended84.81 32382.64 32691.31 31291.07 35385.34 29891.22 34795.75 27985.56 29983.09 34090.21 34767.21 34495.89 34377.18 34062.48 36992.69 344
gg-mvs-nofinetune87.82 30085.61 30994.44 20394.46 29589.27 21191.21 34984.61 37580.88 34489.89 23674.98 36871.50 32097.53 30385.75 27397.21 14596.51 215
ADS-MVSNet289.45 28188.59 28392.03 29395.86 22282.26 33190.93 35094.32 33783.23 33091.28 20291.81 33779.01 26195.99 34279.52 32591.39 23897.84 175
ADS-MVSNet89.89 27688.68 28293.53 25195.86 22284.89 30590.93 35095.07 31383.23 33091.28 20291.81 33779.01 26197.85 27479.52 32591.39 23897.84 175
UnsupCasMVSNet_bld82.13 33079.46 33390.14 33088.00 36882.47 32890.89 35296.62 24878.94 35475.61 36084.40 36456.63 36796.31 33977.30 33966.77 36791.63 356
PVSNet_082.17 1985.46 32083.64 32390.92 31895.27 25379.49 35390.55 35395.60 28783.76 32483.00 34289.95 34971.09 32397.97 25682.75 30460.79 37195.31 273
CHOSEN 280x42093.12 15792.72 15494.34 20996.71 18287.27 25890.29 35497.72 13086.61 28591.34 19595.29 23684.29 16298.41 20293.25 12998.94 9597.35 196
CR-MVSNet90.82 25389.77 26393.95 22994.45 29687.19 26290.23 35595.68 28486.89 28092.40 16992.36 33080.91 22397.05 32481.09 31893.95 20197.60 189
RPMNet88.98 28587.05 30094.77 19094.45 29687.19 26290.23 35598.03 8877.87 35992.40 16987.55 36180.17 23999.51 9868.84 36493.95 20197.60 189
LCM-MVSNet72.55 33369.39 33782.03 34870.81 38065.42 37590.12 35794.36 33655.02 37065.88 36781.72 36524.16 38189.96 36874.32 35168.10 36690.71 362
Patchmtry88.64 29387.25 29692.78 27994.09 30786.64 27389.82 35895.68 28480.81 34687.63 29392.36 33080.91 22397.03 32578.86 33185.12 30794.67 312
PatchT88.87 28987.42 29493.22 26494.08 30885.10 30189.51 35994.64 32881.92 33792.36 17288.15 35880.05 24197.01 32872.43 35693.65 20497.54 192
JIA-IIPM88.26 29787.04 30191.91 29593.52 32381.42 33689.38 36094.38 33480.84 34590.93 20780.74 36679.22 25597.92 26882.76 30391.62 23196.38 219
Patchmatch-test89.42 28287.99 28993.70 24395.27 25385.11 30088.98 36194.37 33581.11 34287.10 30393.69 30582.28 20297.50 30674.37 35094.76 18998.48 142
MVS-HIRNet82.47 32981.21 33186.26 34695.38 24169.21 37288.96 36289.49 36766.28 36680.79 34874.08 37068.48 33797.39 31571.93 35895.47 17692.18 353
Patchmatch-RL test87.38 30386.24 30490.81 32088.74 36678.40 36088.12 36393.17 34887.11 27782.17 34489.29 35381.95 20995.60 35088.64 21977.02 35298.41 150
PMMVS270.19 33566.92 33880.01 34976.35 37465.67 37486.22 36487.58 37264.83 36862.38 37080.29 36726.78 37988.49 37063.79 36754.07 37285.88 365
ambc86.56 34583.60 37170.00 37185.69 36594.97 31780.60 35088.45 35437.42 37496.84 33382.69 30575.44 35692.86 342
ANet_high63.94 33959.58 34277.02 35161.24 38266.06 37385.66 36687.93 37178.53 35642.94 37471.04 37125.42 38080.71 37452.60 37230.83 37584.28 366
EMVS52.08 34351.31 34654.39 35972.62 37845.39 38283.84 36775.51 38141.13 37440.77 37659.65 37530.08 37673.60 37728.31 37729.90 37644.18 374
E-PMN53.28 34152.56 34555.43 35874.43 37647.13 38083.63 36876.30 37942.23 37342.59 37562.22 37428.57 37874.40 37631.53 37631.51 37444.78 373
PMVScopyleft53.92 2258.58 34055.40 34368.12 35651.00 38348.64 37978.86 36987.10 37446.77 37235.84 37874.28 3698.76 38286.34 37142.07 37473.91 35969.38 370
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
tmp_tt51.94 34453.82 34446.29 36033.73 38445.30 38378.32 37067.24 38318.02 37750.93 37387.05 36352.99 36953.11 37970.76 36225.29 37740.46 375
MVEpermissive50.73 2353.25 34248.81 34766.58 35765.34 38157.50 37872.49 37170.94 38240.15 37539.28 37763.51 3736.89 38473.48 37838.29 37542.38 37368.76 371
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
Gipumacopyleft67.86 33765.41 33975.18 35392.66 34173.45 36766.50 37294.52 33053.33 37157.80 37266.07 37230.81 37589.20 36948.15 37378.88 35062.90 372
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
test_method66.11 33864.89 34069.79 35572.62 37835.23 38565.19 37392.83 35120.35 37665.20 36888.08 35943.14 37382.70 37373.12 35563.46 36891.45 360
wuyk23d25.11 34524.57 34926.74 36173.98 37739.89 38457.88 3749.80 38512.27 37810.39 3796.97 3817.03 38336.44 38025.43 37817.39 3783.89 378
test_blank0.00 3510.00 3540.00 3640.00 3870.00 3880.00 3750.00 3880.00 3820.00 3830.00 3820.00 3870.00 3830.00 3810.00 3810.00 379
uanet_test0.00 3510.00 3540.00 3640.00 3870.00 3880.00 3750.00 3880.00 3820.00 3830.00 3820.00 3870.00 3830.00 3810.00 3810.00 379
DCPMVS0.00 3510.00 3540.00 3640.00 3870.00 3880.00 3750.00 3880.00 3820.00 3830.00 3820.00 3870.00 3830.00 3810.00 3810.00 379
cdsmvs_eth3d_5k23.24 34630.99 3480.00 3640.00 3870.00 3880.00 37597.63 1410.00 3820.00 38396.88 15184.38 1590.00 3830.00 3810.00 3810.00 379
pcd_1.5k_mvsjas7.39 3509.85 3530.00 3640.00 3870.00 3880.00 3750.00 3880.00 3820.00 3830.00 38288.65 1010.00 3830.00 3810.00 3810.00 379
sosnet-low-res0.00 3510.00 3540.00 3640.00 3870.00 3880.00 3750.00 3880.00 3820.00 3830.00 3820.00 3870.00 3830.00 3810.00 3810.00 379
sosnet0.00 3510.00 3540.00 3640.00 3870.00 3880.00 3750.00 3880.00 3820.00 3830.00 3820.00 3870.00 3830.00 3810.00 3810.00 379
uncertanet0.00 3510.00 3540.00 3640.00 3870.00 3880.00 3750.00 3880.00 3820.00 3830.00 3820.00 3870.00 3830.00 3810.00 3810.00 379
Regformer0.00 3510.00 3540.00 3640.00 3870.00 3880.00 3750.00 3880.00 3820.00 3830.00 3820.00 3870.00 3830.00 3810.00 3810.00 379
ab-mvs-re8.06 34910.74 3520.00 3640.00 3870.00 3880.00 3750.00 3880.00 3820.00 38396.69 1600.00 3870.00 3830.00 3810.00 3810.00 379
uanet0.00 3510.00 3540.00 3640.00 3870.00 3880.00 3750.00 3880.00 3820.00 3830.00 3820.00 3870.00 3830.00 3810.00 3810.00 379
MSC_two_6792asdad98.86 198.67 6696.94 197.93 10799.86 997.68 299.67 699.77 1
PC_three_145290.77 17098.89 898.28 5796.24 198.35 20895.76 6199.58 2299.59 20
No_MVS98.86 198.67 6696.94 197.93 10799.86 997.68 299.67 699.77 1
test_one_060199.32 2495.20 2198.25 3695.13 1998.48 1698.87 695.16 7
eth-test20.00 387
eth-test0.00 387
ZD-MVS99.05 4394.59 3298.08 6889.22 21397.03 5498.10 6892.52 3799.65 5794.58 10399.31 62
IU-MVS99.42 795.39 1197.94 10690.40 18798.94 597.41 1299.66 1099.74 7
test_241102_TWO98.27 3195.13 1998.93 698.89 494.99 1199.85 1897.52 599.65 1299.74 7
test_241102_ONE99.42 795.30 1898.27 3195.09 2399.19 198.81 1095.54 599.65 57
test_0728_THIRD94.78 3798.73 1098.87 695.87 499.84 2397.45 999.72 299.77 1
GSMVS98.45 145
test_part299.28 2795.74 898.10 21
sam_mvs182.76 19198.45 145
sam_mvs81.94 210
MTGPAbinary98.08 68
test_post17.58 37981.76 21298.08 238
patchmatchnet-post90.45 34682.65 19598.10 234
gm-plane-assit93.22 33178.89 35984.82 31193.52 31198.64 18587.72 230
test9_res94.81 9699.38 5499.45 51
agg_prior293.94 11499.38 5499.50 43
agg_prior98.67 6693.79 5898.00 9795.68 10499.57 83
TestCases93.98 22597.94 12086.64 27395.54 29085.38 30185.49 31996.77 15470.28 32899.15 13480.02 32392.87 21096.15 225
test_prior97.23 6598.67 6692.99 8098.00 9799.41 11199.29 68
新几何197.32 5998.60 7593.59 6497.75 12481.58 34095.75 10197.85 8890.04 8899.67 5386.50 25899.13 8398.69 127
旧先验198.38 8893.38 7097.75 12498.09 7092.30 4399.01 9299.16 79
原ACMM196.38 10398.59 7691.09 14897.89 10987.41 27095.22 11797.68 10190.25 8499.54 9087.95 22699.12 8698.49 140
testdata299.67 5385.96 270
segment_acmp92.89 26
testdata95.46 15798.18 11088.90 22097.66 13782.73 33397.03 5498.07 7190.06 8798.85 16589.67 19498.98 9398.64 130
test1297.65 4798.46 8194.26 4197.66 13795.52 11390.89 7699.46 10599.25 7299.22 76
plane_prior796.21 20789.98 180
plane_prior696.10 21790.00 17681.32 218
plane_prior597.51 15398.60 18993.02 13592.23 22095.86 233
plane_prior496.64 164
plane_prior390.00 17694.46 4791.34 195
plane_prior196.14 215
n20.00 388
nn0.00 388
door-mid91.06 363
lessismore_v090.45 32691.96 35079.09 35887.19 37380.32 35294.39 27466.31 35097.55 30084.00 29376.84 35394.70 311
LGP-MVS_train94.10 21896.16 21288.26 23697.46 16191.29 15590.12 22697.16 13379.05 25798.73 17692.25 14591.89 22895.31 273
test1197.88 111
door91.13 362
HQP5-MVS89.33 206
BP-MVS92.13 149
HQP4-MVS90.14 22098.50 19795.78 241
HQP3-MVS97.39 17692.10 225
HQP2-MVS80.95 221
NP-MVS95.99 22189.81 18695.87 206
ACMMP++_ref90.30 258
ACMMP++91.02 247
Test By Simon88.73 100
ITE_SJBPF92.43 28695.34 24685.37 29795.92 27291.47 14987.75 29196.39 18471.00 32497.96 26182.36 30789.86 26293.97 330
DeepMVS_CXcopyleft74.68 35490.84 35564.34 37681.61 37865.34 36767.47 36688.01 36048.60 37180.13 37562.33 36973.68 36079.58 369