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

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

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

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

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




Method Infoallhigh-res
multi-view
indooroutdoorbotani.boulde.bridgedoorexhibi.lectur.living.loungeobserv.old co.statueterrac.
sort bysort bysort bysort bysort bysort bysort bysorted 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
LCM-MVSNet-Re94.20 12194.58 10693.04 17595.91 21783.13 20793.79 13999.19 292.00 9198.84 598.04 3993.64 7299.02 11081.28 27798.54 15896.96 223
DROMVSNet95.44 6995.62 6994.89 10696.93 14787.69 13096.48 3499.14 393.93 5592.77 22494.52 23193.95 7099.49 2293.62 4399.22 8197.51 197
LTVRE_ROB93.87 197.93 298.16 297.26 2698.81 2593.86 3299.07 298.98 497.01 1398.92 498.78 1495.22 3798.61 17996.85 299.77 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
CS-MVS-test93.33 13893.53 14192.71 18995.74 22683.08 20894.55 11698.85 591.02 12789.30 29491.91 29991.79 11999.23 8090.23 14598.41 16895.82 268
FOURS199.21 394.68 1298.45 498.81 697.73 698.27 20
TDRefinement97.68 397.60 497.93 299.02 1295.95 598.61 398.81 697.41 1097.28 4898.46 2594.62 5898.84 13794.64 1799.53 3598.99 53
ANet_high94.83 9596.28 3790.47 26196.65 15873.16 32994.33 12298.74 896.39 2398.09 2598.93 893.37 7998.70 16790.38 13599.68 1899.53 14
ACMH+88.43 1196.48 3096.82 1695.47 8498.54 4389.06 10095.65 7198.61 996.10 2698.16 2397.52 6396.90 798.62 17890.30 14199.60 2598.72 91
CS-MVS92.12 18092.62 16290.60 25894.57 27078.12 27992.00 19998.58 1087.75 19990.08 27791.88 30189.79 16799.10 9790.35 13798.60 15394.58 300
SF-MVS95.88 5695.88 5895.87 6798.12 7589.65 8995.58 7498.56 1191.84 10196.36 8396.68 12194.37 6499.32 6892.41 9199.05 10198.64 101
HPM-MVScopyleft96.81 1296.62 2397.36 2498.89 1993.53 3997.51 998.44 1292.35 8295.95 10796.41 13696.71 899.42 2993.99 3399.36 5699.13 39
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
AllTest94.88 9194.51 11096.00 5698.02 8692.17 5295.26 8598.43 1390.48 14095.04 15296.74 11692.54 10497.86 24685.11 24098.98 10997.98 156
TestCases96.00 5698.02 8692.17 5298.43 1390.48 14095.04 15296.74 11692.54 10497.86 24685.11 24098.98 10997.98 156
xxxxxxxxxxxxxcwj95.03 8394.93 9095.33 8997.46 12388.05 12392.04 19698.42 1587.63 20396.36 8396.68 12194.37 6499.32 6892.41 9199.05 10198.64 101
APDe-MVS96.46 3296.64 2295.93 6197.68 10989.38 9796.90 1998.41 1692.52 7797.43 4397.92 4595.11 4299.50 1994.45 1999.30 6598.92 67
9.1494.81 9497.49 12094.11 12998.37 1787.56 20695.38 13296.03 16194.66 5699.08 9990.70 12998.97 113
ETH3D-3000-0.194.86 9294.55 10795.81 6897.61 11389.72 8794.05 13198.37 1788.09 19195.06 15195.85 16792.58 10299.10 9790.33 14098.99 10898.62 105
abl_697.31 597.12 1397.86 398.54 4395.32 796.61 2798.35 1995.81 3197.55 3697.44 6896.51 999.40 4394.06 3099.23 7998.85 76
MP-MVS-pluss96.08 4995.92 5796.57 4699.06 1091.21 6693.25 15198.32 2087.89 19596.86 6597.38 7195.55 2499.39 4895.47 1099.47 3999.11 41
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
FC-MVSNet-test95.32 7595.88 5893.62 15898.49 5581.77 22095.90 6298.32 2093.93 5597.53 3997.56 6088.48 17799.40 4392.91 7999.83 699.68 4
COLMAP_ROBcopyleft91.06 596.75 1696.62 2397.13 2898.38 5994.31 1796.79 2398.32 2096.69 1796.86 6597.56 6095.48 2598.77 15590.11 15099.44 4598.31 127
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
DPE-MVScopyleft95.89 5495.88 5895.92 6397.93 9389.83 8693.46 14798.30 2392.37 8097.75 2996.95 9995.14 3999.51 1891.74 10899.28 7398.41 122
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
PGM-MVS96.32 4195.94 5597.43 1998.59 3793.84 3395.33 8298.30 2391.40 11895.76 11696.87 10695.26 3599.45 2392.77 8099.21 8299.00 51
ACMH88.36 1296.59 2797.43 594.07 14298.56 3885.33 17996.33 4398.30 2394.66 4098.72 898.30 3097.51 598.00 23494.87 1499.59 2798.86 73
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
nrg03096.32 4196.55 2695.62 7897.83 9688.55 11395.77 6698.29 2692.68 7398.03 2697.91 4695.13 4098.95 12293.85 3699.49 3899.36 24
APD-MVS_3200maxsize96.82 1096.65 2197.32 2597.95 9293.82 3496.31 4598.25 2795.51 3596.99 6097.05 9595.63 2199.39 4893.31 6298.88 12098.75 85
LPG-MVS_test96.38 4096.23 3996.84 4098.36 6292.13 5495.33 8298.25 2791.78 10597.07 5397.22 8696.38 1399.28 7392.07 9799.59 2799.11 41
LGP-MVS_train96.84 4098.36 6292.13 5498.25 2791.78 10597.07 5397.22 8696.38 1399.28 7392.07 9799.59 2799.11 41
Anonymous2023121196.60 2597.13 1295.00 10397.46 12386.35 16397.11 1698.24 3097.58 898.72 898.97 793.15 8699.15 8793.18 6899.74 1399.50 16
canonicalmvs94.59 10394.69 10094.30 13695.60 23687.03 14395.59 7298.24 3091.56 11595.21 14592.04 29894.95 5098.66 17491.45 11797.57 23897.20 216
DVP-MVS++95.93 5396.34 3494.70 11596.54 16786.66 15398.45 498.22 3293.26 6897.54 3797.36 7593.12 8799.38 5493.88 3498.68 14698.04 147
test_0728_SECOND94.88 10798.55 4186.72 15095.20 8898.22 3299.38 5493.44 5599.31 6398.53 112
Vis-MVSNetpermissive95.50 6795.48 7295.56 8298.11 7689.40 9695.35 8098.22 3292.36 8194.11 17798.07 3792.02 11399.44 2493.38 6097.67 23497.85 172
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
UA-Net97.35 497.24 1197.69 598.22 7093.87 3198.42 698.19 3596.95 1495.46 13099.23 493.45 7599.57 1395.34 1299.89 299.63 9
test_one_060198.26 6787.14 13998.18 3694.25 4896.99 6097.36 7595.13 40
test072698.51 4786.69 15195.34 8198.18 3691.85 9897.63 3297.37 7295.58 22
MSP-MVS95.34 7494.63 10597.48 1498.67 2994.05 2396.41 3998.18 3691.26 12195.12 14695.15 20386.60 21399.50 1993.43 5796.81 26198.89 70
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
ACMMPcopyleft96.61 2496.34 3497.43 1998.61 3493.88 3096.95 1898.18 3692.26 8596.33 8596.84 11095.10 4399.40 4393.47 5299.33 6099.02 50
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
EIA-MVS92.35 17492.03 17393.30 17195.81 22283.97 19692.80 16298.17 4087.71 20089.79 28787.56 34691.17 14199.18 8587.97 19897.27 24696.77 231
HPM-MVS_fast97.01 796.89 1597.39 2299.12 893.92 2997.16 1298.17 4093.11 7096.48 7997.36 7596.92 699.34 6294.31 2399.38 5598.92 67
XVG-OURS94.72 9994.12 12296.50 4998.00 8894.23 1891.48 22298.17 4090.72 13495.30 13796.47 13187.94 18896.98 28991.41 11897.61 23798.30 128
ZNCC-MVS96.42 3696.20 4197.07 3098.80 2792.79 4896.08 5498.16 4391.74 10995.34 13596.36 14495.68 1999.44 2494.41 2199.28 7398.97 59
FIs94.90 8995.35 7693.55 16198.28 6581.76 22195.33 8298.14 4493.05 7197.07 5397.18 8887.65 19199.29 7191.72 10999.69 1599.61 11
XVG-OURS-SEG-HR95.38 7295.00 8996.51 4898.10 7794.07 2092.46 17598.13 4590.69 13593.75 19196.25 15298.03 297.02 28892.08 9695.55 28798.45 119
SR-MVS-dyc-post96.84 896.60 2597.56 1098.07 7995.27 896.37 4098.12 4695.66 3397.00 5897.03 9694.85 5299.42 2993.49 4898.84 12598.00 152
RE-MVS-def96.66 2098.07 7995.27 896.37 4098.12 4695.66 3397.00 5897.03 9695.40 2793.49 4898.84 12598.00 152
RPMNet90.31 22290.14 22290.81 25391.01 33178.93 26792.52 17098.12 4691.91 9589.10 29596.89 10568.84 31799.41 3690.17 14892.70 33594.08 309
SED-MVS96.00 5296.41 3294.76 11298.51 4786.97 14495.21 8698.10 4991.95 9297.63 3297.25 8396.48 1199.35 5993.29 6399.29 6897.95 160
test_241102_TWO98.10 4991.95 9297.54 3797.25 8395.37 2899.35 5993.29 6399.25 7698.49 115
test_241102_ONE98.51 4786.97 14498.10 4991.85 9897.63 3297.03 9696.48 1198.95 122
test_part194.39 11094.55 10793.92 14996.14 19982.86 21195.54 7698.09 5295.36 3698.27 2098.36 2875.91 29699.44 2493.41 5899.84 399.47 17
WR-MVS_H96.60 2597.05 1495.24 9599.02 1286.44 15996.78 2498.08 5397.42 998.48 1697.86 4991.76 12199.63 694.23 2699.84 399.66 6
CP-MVS96.44 3596.08 4997.54 1198.29 6494.62 1496.80 2298.08 5392.67 7595.08 15096.39 14194.77 5499.42 2993.17 6999.44 4598.58 110
ACMP88.15 1395.71 6195.43 7596.54 4798.17 7391.73 6294.24 12498.08 5389.46 15996.61 7696.47 13195.85 1799.12 9390.45 13299.56 3398.77 84
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
SR-MVS96.70 1996.42 2997.54 1198.05 8194.69 1196.13 5298.07 5695.17 3796.82 6796.73 11895.09 4499.43 2892.99 7798.71 14298.50 114
v7n96.82 1097.31 1095.33 8998.54 4386.81 14896.83 2098.07 5696.59 2098.46 1798.43 2792.91 9499.52 1796.25 699.76 1199.65 8
UniMVSNet (Re)95.32 7595.15 8595.80 7097.79 9988.91 10392.91 15998.07 5693.46 6596.31 8795.97 16490.14 15999.34 6292.11 9499.64 2399.16 36
test117296.79 1596.52 2797.60 998.03 8594.87 1096.07 5598.06 5995.76 3296.89 6396.85 10794.85 5299.42 2993.35 6198.81 13398.53 112
SD-MVS95.19 8195.73 6693.55 16196.62 16188.88 10694.67 10798.05 6091.26 12197.25 5096.40 13795.42 2694.36 34492.72 8499.19 8597.40 206
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
casdiffmvs94.32 11594.80 9592.85 18596.05 20681.44 22692.35 18398.05 6091.53 11695.75 11796.80 11193.35 8098.49 19391.01 12498.32 18398.64 101
PEN-MVS96.69 2097.39 894.61 11899.16 484.50 18696.54 3098.05 6098.06 498.64 1398.25 3195.01 4899.65 392.95 7899.83 699.68 4
XVG-ACMP-BASELINE95.68 6295.34 7796.69 4398.40 5793.04 4394.54 11898.05 6090.45 14296.31 8796.76 11492.91 9498.72 16191.19 12099.42 4798.32 125
baseline94.26 11894.80 9592.64 19296.08 20480.99 23293.69 14298.04 6490.80 13394.89 15896.32 14693.19 8498.48 19791.68 11198.51 16298.43 120
ACMMP_NAP96.21 4596.12 4796.49 5098.90 1891.42 6494.57 11398.03 6590.42 14396.37 8297.35 7895.68 1999.25 7794.44 2099.34 5898.80 80
ACMM88.83 996.30 4396.07 5096.97 3598.39 5892.95 4694.74 10598.03 6590.82 13297.15 5196.85 10796.25 1599.00 11493.10 7299.33 6098.95 61
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
ETH3D cwj APD-0.1693.99 12693.38 14495.80 7096.82 15289.92 8392.72 16398.02 6784.73 25193.65 19595.54 18991.68 12399.22 8188.78 18198.49 16598.26 131
DeepC-MVS91.39 495.43 7095.33 7895.71 7697.67 11090.17 8093.86 13898.02 6787.35 20796.22 9597.99 4294.48 6299.05 10492.73 8399.68 1897.93 162
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
GST-MVS96.24 4495.99 5497.00 3498.65 3092.71 4995.69 7098.01 6992.08 9095.74 11896.28 14995.22 3799.42 2993.17 6999.06 9898.88 72
OurMVSNet-221017-096.80 1396.75 1896.96 3699.03 1191.85 5997.98 798.01 6994.15 5098.93 399.07 588.07 18499.57 1395.86 999.69 1599.46 18
SteuartSystems-ACMMP96.40 3896.30 3696.71 4298.63 3191.96 5795.70 6898.01 6993.34 6796.64 7496.57 12894.99 4999.36 5893.48 5199.34 5898.82 78
Skip Steuart: Steuart Systems R&D Blog.
HFP-MVS96.39 3996.17 4497.04 3198.51 4793.37 4096.30 4797.98 7292.35 8295.63 12296.47 13195.37 2899.27 7593.78 3899.14 9298.48 116
#test#95.89 5495.51 7197.04 3198.51 4793.37 4095.14 9197.98 7289.34 16395.63 12296.47 13195.37 2899.27 7591.99 9999.14 9298.48 116
LS3D96.11 4895.83 6296.95 3794.75 25994.20 1997.34 1197.98 7297.31 1195.32 13696.77 11293.08 8999.20 8391.79 10698.16 20297.44 202
PS-CasMVS96.69 2097.43 594.49 12999.13 684.09 19596.61 2797.97 7597.91 598.64 1398.13 3495.24 3699.65 393.39 5999.84 399.72 2
region2R96.41 3796.09 4897.38 2398.62 3293.81 3696.32 4497.96 7692.26 8595.28 13996.57 12895.02 4799.41 3693.63 4299.11 9698.94 62
ACMMPR96.46 3296.14 4597.41 2198.60 3593.82 3496.30 4797.96 7692.35 8295.57 12596.61 12694.93 5199.41 3693.78 3899.15 9199.00 51
XVS96.49 2996.18 4297.44 1798.56 3893.99 2796.50 3297.95 7894.58 4194.38 17396.49 13094.56 5999.39 4893.57 4499.05 10198.93 63
X-MVStestdata90.70 20788.45 24997.44 1798.56 3893.99 2796.50 3297.95 7894.58 4194.38 17326.89 37294.56 5999.39 4893.57 4499.05 10198.93 63
Gipumacopyleft95.31 7795.80 6493.81 15597.99 9190.91 7196.42 3897.95 7896.69 1791.78 25198.85 1291.77 12095.49 32791.72 10999.08 9795.02 290
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
DTE-MVSNet96.74 1797.43 594.67 11699.13 684.68 18596.51 3197.94 8198.14 398.67 1298.32 2995.04 4599.69 293.27 6599.82 899.62 10
PS-MVSNAJss96.01 5196.04 5295.89 6698.82 2488.51 11595.57 7597.88 8288.72 17898.81 698.86 1090.77 14599.60 895.43 1199.53 3599.57 13
pmmvs696.80 1397.36 995.15 9999.12 887.82 12996.68 2597.86 8396.10 2698.14 2499.28 397.94 398.21 21691.38 11999.69 1599.42 19
TranMVSNet+NR-MVSNet96.07 5096.26 3895.50 8398.26 6787.69 13093.75 14097.86 8395.96 3097.48 4197.14 9095.33 3299.44 2490.79 12799.76 1199.38 22
PHI-MVS94.34 11493.80 12795.95 5895.65 23291.67 6394.82 10297.86 8387.86 19693.04 21794.16 24391.58 12598.78 15190.27 14398.96 11597.41 203
testtj94.81 9694.42 11196.01 5597.23 13190.51 7894.77 10497.85 8691.29 12094.92 15795.66 18091.71 12299.40 4388.07 19698.25 19298.11 143
ETV-MVS92.99 15392.74 15893.72 15695.86 21986.30 16492.33 18497.84 8791.70 11292.81 22286.17 35692.22 10999.19 8488.03 19797.73 22895.66 276
UniMVSNet_NR-MVSNet95.35 7395.21 8395.76 7397.69 10888.59 11192.26 18897.84 8794.91 3896.80 6895.78 17590.42 15499.41 3691.60 11399.58 3199.29 28
3Dnovator+92.74 295.86 5795.77 6596.13 5396.81 15490.79 7496.30 4797.82 8996.13 2594.74 16497.23 8591.33 13199.16 8693.25 6698.30 18698.46 118
HQP_MVS94.26 11893.93 12495.23 9697.71 10588.12 12194.56 11497.81 9091.74 10993.31 20395.59 18286.93 20598.95 12289.26 17098.51 16298.60 108
plane_prior597.81 9098.95 12289.26 17098.51 16298.60 108
DU-MVS95.28 7895.12 8795.75 7497.75 10188.59 11192.58 16897.81 9093.99 5296.80 6895.90 16590.10 16399.41 3691.60 11399.58 3199.26 29
APD-MVScopyleft95.00 8594.69 10095.93 6197.38 12690.88 7294.59 11097.81 9089.22 16895.46 13096.17 15793.42 7899.34 6289.30 16698.87 12397.56 194
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
SMA-MVScopyleft95.77 5995.54 7096.47 5198.27 6691.19 6795.09 9297.79 9486.48 21897.42 4597.51 6594.47 6399.29 7193.55 4699.29 6898.93 63
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
MP-MVScopyleft96.14 4795.68 6797.51 1398.81 2594.06 2196.10 5397.78 9592.73 7293.48 19996.72 11994.23 6699.42 2991.99 9999.29 6899.05 48
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
MSLP-MVS++93.25 14593.88 12591.37 23196.34 18282.81 21293.11 15397.74 9689.37 16294.08 17995.29 20190.40 15796.35 31190.35 13798.25 19294.96 291
mPP-MVS96.46 3296.05 5197.69 598.62 3294.65 1396.45 3597.74 9692.59 7695.47 12896.68 12194.50 6199.42 2993.10 7299.26 7598.99 53
ETH3 D test640091.91 18491.25 19593.89 15196.59 16284.41 18792.10 19397.72 9878.52 30391.82 25093.78 25888.70 17599.13 9183.61 25498.39 17298.14 139
TAPA-MVS88.58 1092.49 17191.75 18394.73 11396.50 17189.69 8892.91 15997.68 9978.02 30792.79 22394.10 24490.85 14497.96 23884.76 24698.16 20296.54 235
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
CPTT-MVS94.74 9894.12 12296.60 4598.15 7493.01 4495.84 6497.66 10089.21 16993.28 20695.46 19288.89 17498.98 11589.80 15798.82 13197.80 177
DP-MVS95.62 6395.84 6194.97 10497.16 13688.62 11094.54 11897.64 10196.94 1596.58 7797.32 8193.07 9098.72 16190.45 13298.84 12597.57 192
zzz-MVS96.47 3196.14 4597.47 1598.95 1694.05 2393.69 14297.62 10294.46 4596.29 8996.94 10093.56 7399.37 5694.29 2499.42 4798.99 53
MTGPAbinary97.62 102
MTAPA96.65 2296.38 3397.47 1598.95 1694.05 2395.88 6397.62 10294.46 4596.29 8996.94 10093.56 7399.37 5694.29 2499.42 4798.99 53
anonymousdsp96.74 1796.42 2997.68 798.00 8894.03 2696.97 1797.61 10587.68 20298.45 1898.77 1594.20 6799.50 1996.70 399.40 5399.53 14
mvs_tets96.83 996.71 1997.17 2798.83 2392.51 5096.58 2997.61 10587.57 20598.80 798.90 996.50 1099.59 1296.15 799.47 3999.40 21
VPA-MVSNet95.14 8295.67 6893.58 16097.76 10083.15 20694.58 11297.58 10793.39 6697.05 5698.04 3993.25 8298.51 19289.75 16099.59 2799.08 45
v1094.68 10195.27 8292.90 18396.57 16480.15 23994.65 10997.57 10890.68 13697.43 4398.00 4188.18 18199.15 8794.84 1599.55 3499.41 20
CSCG94.69 10094.75 9794.52 12697.55 11787.87 12795.01 9797.57 10892.68 7396.20 9793.44 26591.92 11798.78 15189.11 17499.24 7896.92 224
ZD-MVS97.23 13190.32 7997.54 11084.40 25394.78 16295.79 17292.76 9999.39 4888.72 18498.40 169
UniMVSNet_ETH3D97.13 697.72 395.35 8799.51 287.38 13497.70 897.54 11098.16 298.94 299.33 297.84 499.08 9990.73 12899.73 1499.59 12
Effi-MVS+92.79 16092.74 15892.94 18195.10 24983.30 20394.00 13397.53 11291.36 11989.35 29390.65 32294.01 6998.66 17487.40 20895.30 29596.88 227
CP-MVSNet96.19 4696.80 1794.38 13598.99 1483.82 19896.31 4597.53 11297.60 798.34 1997.52 6391.98 11699.63 693.08 7499.81 999.70 3
RPSCF95.58 6594.89 9297.62 897.58 11596.30 495.97 5997.53 11292.42 7893.41 20097.78 5091.21 13797.77 25591.06 12197.06 25198.80 80
diffmvs91.74 18691.93 17791.15 24193.06 29878.17 27888.77 29397.51 11586.28 22292.42 23493.96 25188.04 18597.46 27190.69 13096.67 26697.82 175
PVSNet_Blended_VisFu91.63 18991.20 19692.94 18197.73 10483.95 19792.14 19297.46 11678.85 30292.35 23894.98 21384.16 23199.08 9986.36 22696.77 26395.79 270
DeepPCF-MVS90.46 694.20 12193.56 13896.14 5295.96 21392.96 4589.48 27697.46 11685.14 24196.23 9495.42 19593.19 8498.08 22690.37 13698.76 13997.38 209
jajsoiax96.59 2796.42 2997.12 2998.76 2892.49 5196.44 3797.42 11886.96 21498.71 1098.72 1795.36 3199.56 1695.92 899.45 4399.32 26
OMC-MVS94.22 12093.69 13295.81 6897.25 13091.27 6592.27 18797.40 11987.10 21394.56 16895.42 19593.74 7198.11 22586.62 22098.85 12498.06 144
v124093.29 14093.71 13192.06 21496.01 21177.89 28391.81 21597.37 12085.12 24396.69 7296.40 13786.67 21199.07 10394.51 1898.76 13999.22 32
NR-MVSNet95.28 7895.28 8195.26 9497.75 10187.21 13895.08 9397.37 12093.92 5797.65 3195.90 16590.10 16399.33 6790.11 15099.66 2199.26 29
MVSFormer92.18 17992.23 16992.04 21594.74 26180.06 24397.15 1397.37 12088.98 17288.83 29892.79 28077.02 28899.60 896.41 496.75 26496.46 242
test_djsdf96.62 2396.49 2897.01 3398.55 4191.77 6197.15 1397.37 12088.98 17298.26 2298.86 1093.35 8099.60 896.41 499.45 4399.66 6
DP-MVS Recon92.31 17591.88 17893.60 15997.18 13586.87 14791.10 23197.37 12084.92 24892.08 24694.08 24588.59 17698.20 21783.50 25598.14 20495.73 272
test_prior393.29 14092.85 15494.61 11895.95 21487.23 13690.21 25497.36 12589.33 16490.77 26494.81 22090.41 15598.68 17188.21 18998.55 15597.93 162
test_prior94.61 11895.95 21487.23 13697.36 12598.68 17197.93 162
QAPM92.88 15792.77 15693.22 17395.82 22083.31 20296.45 3597.35 12783.91 25693.75 19196.77 11289.25 17298.88 12984.56 24897.02 25397.49 198
GeoE94.55 10594.68 10294.15 13997.23 13185.11 18194.14 12897.34 12888.71 17995.26 14095.50 19094.65 5799.12 9390.94 12598.40 16998.23 132
OPM-MVS95.61 6495.45 7396.08 5498.49 5591.00 6992.65 16797.33 12990.05 14896.77 7096.85 10795.04 4598.56 18792.77 8099.06 9898.70 94
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
HQP3-MVS97.31 13097.73 228
HQP-MVS92.09 18191.49 18993.88 15296.36 17884.89 18391.37 22397.31 13087.16 21088.81 30093.40 26684.76 22798.60 18186.55 22297.73 22898.14 139
PCF-MVS84.52 1789.12 24687.71 26593.34 16896.06 20585.84 17386.58 33097.31 13068.46 35293.61 19693.89 25487.51 19498.52 19167.85 35798.11 20895.66 276
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
114514_t90.51 21189.80 22792.63 19498.00 8882.24 21693.40 14997.29 13365.84 35989.40 29294.80 22386.99 20398.75 15683.88 25398.61 15196.89 226
CLD-MVS91.82 18591.41 19193.04 17596.37 17683.65 20086.82 32297.29 13384.65 25292.27 24289.67 33292.20 11097.85 24883.95 25299.47 3997.62 190
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
3Dnovator92.54 394.80 9794.90 9194.47 13095.47 23987.06 14196.63 2697.28 13591.82 10494.34 17597.41 6990.60 15298.65 17692.47 8998.11 20897.70 184
DELS-MVS92.05 18292.16 17091.72 22294.44 27280.13 24187.62 30397.25 13687.34 20892.22 24393.18 27289.54 17098.73 16089.67 16198.20 20096.30 248
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
v192192093.26 14393.61 13592.19 20796.04 21078.31 27691.88 20897.24 13785.17 24096.19 9996.19 15486.76 21099.05 10494.18 2898.84 12599.22 32
test_040295.73 6096.22 4094.26 13798.19 7285.77 17493.24 15297.24 13796.88 1697.69 3097.77 5294.12 6899.13 9191.54 11699.29 6897.88 168
v119293.49 13493.78 12892.62 19596.16 19779.62 25591.83 21497.22 13986.07 22696.10 10396.38 14287.22 19899.02 11094.14 2998.88 12099.22 32
F-COLMAP92.28 17691.06 20095.95 5897.52 11891.90 5893.53 14597.18 14083.98 25588.70 30694.04 24688.41 17998.55 18980.17 28895.99 27897.39 207
v894.65 10295.29 8092.74 18896.65 15879.77 25394.59 11097.17 14191.86 9797.47 4297.93 4488.16 18299.08 9994.32 2299.47 3999.38 22
v14419293.20 14893.54 13992.16 21196.05 20678.26 27791.95 20197.14 14284.98 24795.96 10696.11 15887.08 20299.04 10793.79 3798.84 12599.17 35
DeepC-MVS_fast89.96 793.73 13093.44 14294.60 12296.14 19987.90 12693.36 15097.14 14285.53 23593.90 18895.45 19391.30 13398.59 18389.51 16398.62 15097.31 212
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
MCST-MVS92.91 15592.51 16594.10 14197.52 11885.72 17591.36 22697.13 14480.33 28492.91 22194.24 23991.23 13698.72 16189.99 15497.93 22197.86 170
KD-MVS_self_test94.10 12394.73 9992.19 20797.66 11179.49 25894.86 10197.12 14589.59 15896.87 6497.65 5690.40 15798.34 20689.08 17599.35 5798.75 85
pm-mvs195.43 7095.94 5593.93 14898.38 5985.08 18295.46 7997.12 14591.84 10197.28 4898.46 2595.30 3497.71 26090.17 14899.42 4798.99 53
save fliter97.46 12388.05 12392.04 19697.08 14787.63 203
CDPH-MVS92.67 16591.83 17995.18 9896.94 14588.46 11690.70 24097.07 14877.38 30992.34 24095.08 20892.67 10198.88 12985.74 23198.57 15498.20 136
OpenMVScopyleft89.45 892.27 17792.13 17292.68 19194.53 27184.10 19495.70 6897.03 14982.44 27291.14 26196.42 13588.47 17898.38 20285.95 23097.47 24195.55 280
原ACMM192.87 18496.91 14884.22 19197.01 15076.84 31489.64 29094.46 23288.00 18698.70 16781.53 27598.01 21795.70 274
DVP-MVScopyleft95.82 5896.18 4294.72 11498.51 4786.69 15195.20 8897.00 15191.85 9897.40 4697.35 7895.58 2299.34 6293.44 5599.31 6398.13 141
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
CANet92.38 17391.99 17593.52 16593.82 28883.46 20191.14 22997.00 15189.81 15386.47 32794.04 24687.90 18999.21 8289.50 16498.27 18897.90 166
HPM-MVS++copyleft95.02 8494.39 11296.91 3897.88 9493.58 3894.09 13096.99 15391.05 12692.40 23595.22 20291.03 14399.25 7792.11 9498.69 14597.90 166
v114493.50 13393.81 12692.57 19796.28 18779.61 25691.86 21396.96 15486.95 21595.91 11196.32 14687.65 19198.96 12093.51 4798.88 12099.13 39
MVS_Test92.57 17093.29 14590.40 26493.53 29075.85 30992.52 17096.96 15488.73 17792.35 23896.70 12090.77 14598.37 20592.53 8895.49 28996.99 222
PVSNet_BlendedMVS90.35 21989.96 22491.54 22894.81 25678.80 27290.14 25896.93 15679.43 29288.68 30795.06 20986.27 21698.15 22380.27 28598.04 21497.68 186
PVSNet_Blended88.74 25688.16 26090.46 26394.81 25678.80 27286.64 32696.93 15674.67 32288.68 30789.18 33886.27 21698.15 22380.27 28596.00 27794.44 304
TEST996.45 17489.46 9290.60 24296.92 15879.09 29890.49 26994.39 23591.31 13298.88 129
train_agg92.71 16491.83 17995.35 8796.45 17489.46 9290.60 24296.92 15879.37 29390.49 26994.39 23591.20 13898.88 12988.66 18598.43 16797.72 183
NCCC94.08 12493.54 13995.70 7796.49 17289.90 8592.39 18096.91 16090.64 13792.33 24194.60 22890.58 15398.96 12090.21 14797.70 23298.23 132
test_896.37 17689.14 9990.51 24596.89 16179.37 29390.42 27194.36 23791.20 13898.82 139
agg_prior192.60 16791.76 18295.10 10196.20 19388.89 10490.37 24996.88 16279.67 29090.21 27494.41 23391.30 13398.78 15188.46 18898.37 17997.64 189
agg_prior96.20 19388.89 10496.88 16290.21 27498.78 151
MSC_two_6792asdad95.90 6496.54 16789.57 9096.87 16499.41 3694.06 3099.30 6598.72 91
No_MVS95.90 6496.54 16789.57 9096.87 16499.41 3694.06 3099.30 6598.72 91
MIMVSNet195.52 6695.45 7395.72 7599.14 589.02 10196.23 5096.87 16493.73 5997.87 2798.49 2490.73 14999.05 10486.43 22599.60 2599.10 44
IU-MVS98.51 4786.66 15396.83 16772.74 33495.83 11493.00 7699.29 6898.64 101
TSAR-MVS + MP.94.96 8794.75 9795.57 8198.86 2188.69 10796.37 4096.81 16885.23 23894.75 16397.12 9191.85 11899.40 4393.45 5398.33 18198.62 105
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
CNVR-MVS94.58 10494.29 11695.46 8596.94 14589.35 9891.81 21596.80 16989.66 15593.90 18895.44 19492.80 9898.72 16192.74 8298.52 16098.32 125
cascas87.02 29086.28 29189.25 28991.56 32676.45 30384.33 34596.78 17071.01 34286.89 32685.91 35781.35 25696.94 29083.09 25995.60 28694.35 306
IterMVS-LS93.78 12994.28 11792.27 20496.27 18879.21 26591.87 20996.78 17091.77 10796.57 7897.07 9387.15 20098.74 15991.99 9999.03 10798.86 73
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
Anonymous2024052995.50 6795.83 6294.50 12797.33 12985.93 17195.19 9096.77 17296.64 1997.61 3598.05 3893.23 8398.79 14788.60 18699.04 10698.78 82
TransMVSNet (Re)95.27 8096.04 5292.97 17898.37 6181.92 21995.07 9496.76 17393.97 5497.77 2898.57 1995.72 1897.90 24088.89 17999.23 7999.08 45
EG-PatchMatch MVS94.54 10794.67 10394.14 14097.87 9586.50 15592.00 19996.74 17488.16 19096.93 6297.61 5893.04 9197.90 24091.60 11398.12 20798.03 150
1112_ss88.42 26087.41 26991.45 22996.69 15780.99 23289.72 27196.72 17573.37 33087.00 32590.69 32077.38 28498.20 21781.38 27693.72 32295.15 286
Baseline_NR-MVSNet94.47 10995.09 8892.60 19698.50 5480.82 23592.08 19496.68 17693.82 5896.29 8998.56 2090.10 16397.75 25890.10 15299.66 2199.24 31
eth_miper_zixun_eth90.72 20690.61 21091.05 24292.04 31776.84 29986.91 31896.67 17785.21 23994.41 17193.92 25279.53 26898.26 21389.76 15997.02 25398.06 144
Fast-Effi-MVS+-dtu92.77 16292.16 17094.58 12594.66 26788.25 11892.05 19596.65 17889.62 15690.08 27791.23 31092.56 10398.60 18186.30 22796.27 27396.90 225
test1196.65 178
EGC-MVSNET80.97 32775.73 33996.67 4498.85 2294.55 1596.83 2096.60 1802.44 3745.32 37598.25 3192.24 10898.02 23291.85 10599.21 8297.45 200
RRT_test8_iter0588.21 26388.17 25888.33 30491.62 32466.82 35991.73 21896.60 18086.34 22194.14 17695.38 20047.72 37299.11 9591.78 10798.26 18999.06 47
LF4IMVS92.72 16392.02 17494.84 10995.65 23291.99 5692.92 15896.60 18085.08 24592.44 23393.62 26086.80 20996.35 31186.81 21598.25 19296.18 253
GBi-Net93.21 14692.96 15193.97 14595.40 24184.29 18895.99 5696.56 18388.63 18095.10 14798.53 2181.31 25798.98 11586.74 21698.38 17498.65 97
test193.21 14692.96 15193.97 14595.40 24184.29 18895.99 5696.56 18388.63 18095.10 14798.53 2181.31 25798.98 11586.74 21698.38 17498.65 97
FMVSNet194.84 9495.13 8693.97 14597.60 11484.29 18895.99 5696.56 18392.38 7997.03 5798.53 2190.12 16098.98 11588.78 18199.16 9098.65 97
ITE_SJBPF95.95 5897.34 12893.36 4296.55 18691.93 9494.82 16095.39 19891.99 11597.08 28685.53 23397.96 21997.41 203
Fast-Effi-MVS+91.28 19990.86 20392.53 19995.45 24082.53 21489.25 28596.52 18785.00 24689.91 28288.55 34292.94 9298.84 13784.72 24795.44 29196.22 251
V4293.43 13693.58 13692.97 17895.34 24581.22 22992.67 16696.49 18887.25 20996.20 9796.37 14387.32 19798.85 13692.39 9398.21 19898.85 76
PLCcopyleft85.34 1590.40 21588.92 24194.85 10896.53 17090.02 8191.58 22096.48 18980.16 28586.14 32992.18 29485.73 22198.25 21476.87 31794.61 31096.30 248
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
c3_l91.32 19891.42 19091.00 24692.29 31076.79 30087.52 30996.42 19085.76 23294.72 16693.89 25482.73 24298.16 22290.93 12698.55 15598.04 147
Regformer-294.86 9294.55 10795.77 7292.83 30389.98 8291.87 20996.40 19194.38 4796.19 9995.04 21092.47 10799.04 10793.49 4898.31 18498.28 129
USDC89.02 24789.08 23788.84 29495.07 25074.50 32088.97 28896.39 19273.21 33193.27 20796.28 14982.16 24996.39 30877.55 31198.80 13595.62 279
ambc92.98 17796.88 14983.01 21095.92 6196.38 19396.41 8097.48 6688.26 18097.80 25189.96 15598.93 11798.12 142
PAPM_NR91.03 20190.81 20591.68 22496.73 15681.10 23193.72 14196.35 19488.19 18988.77 30492.12 29785.09 22697.25 28182.40 26793.90 31996.68 234
v2v48293.29 14093.63 13492.29 20396.35 18178.82 27091.77 21796.28 19588.45 18495.70 12196.26 15186.02 21998.90 12693.02 7598.81 13399.14 38
AdaColmapbinary91.63 18991.36 19292.47 20295.56 23786.36 16292.24 19096.27 19688.88 17689.90 28392.69 28391.65 12498.32 20777.38 31497.64 23592.72 338
Test_1112_low_res87.50 27886.58 28490.25 26896.80 15577.75 28587.53 30896.25 19769.73 34886.47 32793.61 26175.67 29797.88 24279.95 29093.20 32795.11 288
test1294.43 13395.95 21486.75 14996.24 19889.76 28889.79 16798.79 14797.95 22097.75 182
PAPR87.65 27486.77 28290.27 26792.85 30277.38 29088.56 29896.23 19976.82 31584.98 33589.75 33186.08 21897.16 28472.33 34193.35 32596.26 250
MVS_111021_HR93.63 13293.42 14394.26 13796.65 15886.96 14689.30 28296.23 19988.36 18793.57 19794.60 22893.45 7597.77 25590.23 14598.38 17498.03 150
XXY-MVS92.58 16893.16 15090.84 25297.75 10179.84 24991.87 20996.22 20185.94 22895.53 12797.68 5492.69 10094.48 34083.21 25897.51 23998.21 135
MSDG90.82 20390.67 20991.26 23594.16 27783.08 20886.63 32796.19 20290.60 13991.94 24891.89 30089.16 17395.75 32280.96 28394.51 31194.95 292
miper_ehance_all_eth90.48 21290.42 21590.69 25591.62 32476.57 30286.83 32196.18 20383.38 25894.06 18192.66 28582.20 24898.04 22889.79 15897.02 25397.45 200
TinyColmap92.00 18392.76 15789.71 28095.62 23577.02 29490.72 23996.17 20487.70 20195.26 14096.29 14892.54 10496.45 30681.77 27298.77 13895.66 276
DPM-MVS89.35 24288.40 25092.18 21096.13 20284.20 19286.96 31796.15 20575.40 32087.36 32291.55 30883.30 23598.01 23382.17 27096.62 26794.32 307
HyFIR lowres test87.19 28685.51 29692.24 20597.12 14080.51 23685.03 33796.06 20666.11 35891.66 25292.98 27670.12 31599.14 8975.29 32695.23 29797.07 217
xiu_mvs_v1_base_debu91.47 19391.52 18691.33 23295.69 22981.56 22389.92 26596.05 20783.22 26091.26 25790.74 31791.55 12698.82 13989.29 16795.91 27993.62 324
xiu_mvs_v1_base91.47 19391.52 18691.33 23295.69 22981.56 22389.92 26596.05 20783.22 26091.26 25790.74 31791.55 12698.82 13989.29 16795.91 27993.62 324
xiu_mvs_v1_base_debi91.47 19391.52 18691.33 23295.69 22981.56 22389.92 26596.05 20783.22 26091.26 25790.74 31791.55 12698.82 13989.29 16795.91 27993.62 324
Regformer-494.90 8994.67 10395.59 7992.78 30589.02 10192.39 18095.91 21094.50 4396.41 8095.56 18792.10 11299.01 11294.23 2698.14 20498.74 88
UnsupCasMVSNet_eth90.33 22090.34 21690.28 26694.64 26880.24 23789.69 27295.88 21185.77 23193.94 18795.69 17881.99 25192.98 35584.21 25191.30 34697.62 190
CANet_DTU89.85 23689.17 23591.87 21792.20 31380.02 24690.79 23795.87 21286.02 22782.53 35191.77 30380.01 26598.57 18685.66 23297.70 23297.01 221
PMVScopyleft87.21 1494.97 8695.33 7893.91 15098.97 1597.16 295.54 7695.85 21396.47 2193.40 20297.46 6795.31 3395.47 32886.18 22998.78 13789.11 355
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
Regformer-194.55 10594.33 11595.19 9792.83 30388.54 11491.87 20995.84 21493.99 5295.95 10795.04 21092.00 11498.79 14793.14 7198.31 18498.23 132
alignmvs93.26 14392.85 15494.50 12795.70 22887.45 13293.45 14895.76 21591.58 11495.25 14292.42 29281.96 25298.72 16191.61 11297.87 22497.33 211
无先验89.94 26495.75 21670.81 34498.59 18381.17 28094.81 293
WR-MVS93.49 13493.72 13092.80 18797.57 11680.03 24590.14 25895.68 21793.70 6096.62 7595.39 19887.21 19999.04 10787.50 20599.64 2399.33 25
VPNet93.08 14993.76 12991.03 24398.60 3575.83 31191.51 22195.62 21891.84 10195.74 11897.10 9289.31 17198.32 20785.07 24299.06 9898.93 63
Anonymous2024052192.86 15993.57 13790.74 25496.57 16475.50 31394.15 12795.60 21989.38 16195.90 11297.90 4880.39 26497.96 23892.60 8799.68 1898.75 85
xiu_mvs_v2_base89.00 24989.19 23488.46 30294.86 25474.63 31786.97 31695.60 21980.88 28087.83 31788.62 34191.04 14298.81 14482.51 26694.38 31291.93 344
PS-MVSNAJ88.86 25388.99 24088.48 30194.88 25274.71 31586.69 32595.60 21980.88 28087.83 31787.37 34990.77 14598.82 13982.52 26594.37 31391.93 344
CHOSEN 1792x268887.19 28685.92 29491.00 24697.13 13979.41 25984.51 34395.60 21964.14 36290.07 27994.81 22078.26 27897.14 28573.34 33595.38 29496.46 242
miper_enhance_ethall88.42 26087.87 26390.07 27388.67 35775.52 31285.10 33695.59 22375.68 31692.49 23189.45 33578.96 27097.88 24287.86 20197.02 25396.81 229
MVP-Stereo90.07 23088.92 24193.54 16396.31 18586.49 15690.93 23495.59 22379.80 28691.48 25395.59 18280.79 26197.39 27778.57 30591.19 34796.76 232
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
cdsmvs_eth3d_5k23.35 34131.13 3440.00 3590.00 3820.00 3830.00 37095.58 2250.00 3770.00 37891.15 31193.43 770.00 3780.00 3760.00 3760.00 374
CNLPA91.72 18791.20 19693.26 17296.17 19691.02 6891.14 22995.55 22690.16 14790.87 26393.56 26386.31 21594.40 34379.92 29497.12 25094.37 305
FMVSNet292.78 16192.73 16092.95 18095.40 24181.98 21894.18 12695.53 22788.63 18096.05 10497.37 7281.31 25798.81 14487.38 20998.67 14898.06 144
ab-mvs92.40 17292.62 16291.74 22197.02 14181.65 22295.84 6495.50 22886.95 21592.95 22097.56 6090.70 15097.50 26879.63 29597.43 24296.06 257
MVS_111021_LR93.66 13193.28 14794.80 11096.25 19190.95 7090.21 25495.43 22987.91 19393.74 19394.40 23492.88 9696.38 30990.39 13498.28 18797.07 217
tfpnnormal94.27 11794.87 9392.48 20197.71 10580.88 23494.55 11695.41 23093.70 6096.67 7397.72 5391.40 12998.18 22087.45 20699.18 8798.36 123
Effi-MVS+-dtu93.90 12892.60 16497.77 494.74 26196.67 394.00 13395.41 23089.94 14991.93 24992.13 29690.12 16098.97 11987.68 20397.48 24097.67 187
mvs-test193.07 15191.80 18196.89 3994.74 26195.83 692.17 19195.41 23089.94 14989.85 28490.59 32390.12 16098.88 12987.68 20395.66 28595.97 260
cl____90.65 20990.56 21290.91 25091.85 31976.98 29786.75 32395.36 23385.53 23594.06 18194.89 21777.36 28697.98 23790.27 14398.98 10997.76 180
DIV-MVS_self_test90.65 20990.56 21290.91 25091.85 31976.99 29686.75 32395.36 23385.52 23794.06 18194.89 21777.37 28597.99 23690.28 14298.97 11397.76 180
testgi90.38 21791.34 19387.50 31497.49 12071.54 33989.43 27795.16 23588.38 18694.54 16994.68 22792.88 9693.09 35471.60 34697.85 22597.88 168
v14892.87 15893.29 14591.62 22596.25 19177.72 28691.28 22795.05 23689.69 15495.93 11096.04 16087.34 19698.38 20290.05 15397.99 21898.78 82
miper_lstm_enhance89.90 23589.80 22790.19 27291.37 32877.50 28883.82 35095.00 23784.84 24993.05 21694.96 21476.53 29595.20 33689.96 15598.67 14897.86 170
VNet92.67 16592.96 15191.79 21996.27 18880.15 23991.95 20194.98 23892.19 8894.52 17096.07 15987.43 19597.39 27784.83 24498.38 17497.83 173
FMVSNet390.78 20590.32 21792.16 21193.03 30079.92 24892.54 16994.95 23986.17 22595.10 14796.01 16269.97 31698.75 15686.74 21698.38 17497.82 175
BH-untuned90.68 20890.90 20190.05 27595.98 21279.57 25790.04 26194.94 24087.91 19394.07 18093.00 27487.76 19097.78 25479.19 30195.17 29892.80 336
RRT_MVS91.36 19690.05 22395.29 9389.21 35288.15 12092.51 17494.89 24186.73 21795.54 12695.68 17961.82 35199.30 7094.91 1399.13 9598.43 120
D2MVS89.93 23489.60 23290.92 24894.03 28278.40 27588.69 29594.85 24278.96 30093.08 21495.09 20774.57 29996.94 29088.19 19198.96 11597.41 203
SixPastTwentyTwo94.91 8895.21 8393.98 14498.52 4683.19 20595.93 6094.84 24394.86 3998.49 1598.74 1681.45 25599.60 894.69 1699.39 5499.15 37
旧先验196.20 19384.17 19394.82 24495.57 18689.57 16997.89 22396.32 247
API-MVS91.52 19291.61 18491.26 23594.16 27786.26 16694.66 10894.82 24491.17 12492.13 24591.08 31390.03 16697.06 28779.09 30297.35 24590.45 353
FMVSNet587.82 27086.56 28591.62 22592.31 30979.81 25293.49 14694.81 24683.26 25991.36 25596.93 10252.77 36897.49 27076.07 32298.03 21597.55 195
MAR-MVS90.32 22188.87 24494.66 11794.82 25591.85 5994.22 12594.75 24780.91 27987.52 32188.07 34586.63 21297.87 24576.67 31896.21 27494.25 308
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
mvs_anonymous90.37 21891.30 19487.58 31392.17 31468.00 35389.84 26994.73 24883.82 25793.22 21197.40 7087.54 19397.40 27687.94 19995.05 30097.34 210
Regformer-394.28 11694.23 12194.46 13192.78 30586.28 16592.39 18094.70 24993.69 6395.97 10595.56 18791.34 13098.48 19793.45 5398.14 20498.62 105
EI-MVSNet-UG-set94.35 11394.27 11994.59 12392.46 30885.87 17292.42 17894.69 25093.67 6496.13 10195.84 17091.20 13898.86 13493.78 3898.23 19599.03 49
EI-MVSNet-Vis-set94.36 11294.28 11794.61 11892.55 30785.98 17092.44 17694.69 25093.70 6096.12 10295.81 17191.24 13598.86 13493.76 4198.22 19798.98 58
EI-MVSNet92.99 15393.26 14992.19 20792.12 31579.21 26592.32 18594.67 25291.77 10795.24 14395.85 16787.14 20198.49 19391.99 9998.26 18998.86 73
MVSTER89.32 24388.75 24591.03 24390.10 34276.62 30190.85 23594.67 25282.27 27395.24 14395.79 17261.09 35498.49 19390.49 13198.26 18997.97 159
新几何193.17 17497.16 13687.29 13594.43 25467.95 35391.29 25694.94 21586.97 20498.23 21581.06 28297.75 22793.98 315
112190.26 22389.23 23393.34 16897.15 13887.40 13391.94 20394.39 25567.88 35491.02 26294.91 21686.91 20798.59 18381.17 28097.71 23194.02 314
CMPMVSbinary68.83 2287.28 28285.67 29592.09 21388.77 35685.42 17890.31 25294.38 25670.02 34788.00 31593.30 26873.78 30394.03 34875.96 32496.54 26896.83 228
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
IS-MVSNet94.49 10894.35 11494.92 10598.25 6986.46 15897.13 1594.31 25796.24 2496.28 9296.36 14482.88 23999.35 5988.19 19199.52 3798.96 60
testdata91.03 24396.87 15082.01 21794.28 25871.55 33892.46 23295.42 19585.65 22397.38 27982.64 26397.27 24693.70 322
UGNet93.08 14992.50 16694.79 11193.87 28687.99 12595.07 9494.26 25990.64 13787.33 32397.67 5586.89 20898.49 19388.10 19498.71 14297.91 165
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
MVS84.98 30284.30 30287.01 31791.03 33077.69 28791.94 20394.16 26059.36 36784.23 34187.50 34885.66 22296.80 29671.79 34393.05 33286.54 360
131486.46 29386.33 29086.87 31991.65 32374.54 31891.94 20394.10 26174.28 32484.78 33787.33 35083.03 23895.00 33778.72 30391.16 34891.06 350
cl2289.02 24788.50 24890.59 25989.76 34476.45 30386.62 32894.03 26282.98 26692.65 22792.49 28672.05 30997.53 26688.93 17697.02 25397.78 178
EPP-MVSNet93.91 12793.68 13394.59 12398.08 7885.55 17797.44 1094.03 26294.22 4994.94 15596.19 15482.07 25099.57 1387.28 21098.89 11898.65 97
UnsupCasMVSNet_bld88.50 25988.03 26189.90 27795.52 23878.88 26987.39 31094.02 26479.32 29693.06 21594.02 24880.72 26294.27 34575.16 32793.08 33196.54 235
h-mvs3392.89 15691.99 17595.58 8096.97 14390.55 7693.94 13694.01 26589.23 16693.95 18596.19 15476.88 29199.14 8991.02 12295.71 28497.04 220
pmmvs-eth3d91.54 19190.73 20893.99 14395.76 22587.86 12890.83 23693.98 26678.23 30694.02 18496.22 15382.62 24596.83 29586.57 22198.33 18197.29 213
BH-RMVSNet90.47 21390.44 21490.56 26095.21 24878.65 27489.15 28693.94 26788.21 18892.74 22594.22 24086.38 21497.88 24278.67 30495.39 29395.14 287
test22296.95 14485.27 18088.83 29193.61 26865.09 36190.74 26694.85 21984.62 22997.36 24493.91 316
CDS-MVSNet89.55 23988.22 25793.53 16495.37 24486.49 15689.26 28393.59 26979.76 28891.15 26092.31 29377.12 28798.38 20277.51 31297.92 22295.71 273
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
new-patchmatchnet88.97 25090.79 20683.50 34194.28 27655.83 37585.34 33593.56 27086.18 22495.47 12895.73 17783.10 23796.51 30485.40 23498.06 21298.16 137
IterMVS-SCA-FT91.65 18891.55 18591.94 21693.89 28579.22 26487.56 30693.51 27191.53 11695.37 13396.62 12578.65 27398.90 12691.89 10494.95 30197.70 184
Anonymous2023120688.77 25588.29 25390.20 27196.31 18578.81 27189.56 27593.49 27274.26 32592.38 23695.58 18582.21 24795.43 33072.07 34298.75 14196.34 246
OpenMVS_ROBcopyleft85.12 1689.52 24189.05 23890.92 24894.58 26981.21 23091.10 23193.41 27377.03 31393.41 20093.99 25083.23 23697.80 25179.93 29294.80 30593.74 321
VDD-MVS94.37 11194.37 11394.40 13497.49 12086.07 16993.97 13593.28 27494.49 4496.24 9397.78 5087.99 18798.79 14788.92 17799.14 9298.34 124
jason89.17 24588.32 25191.70 22395.73 22780.07 24288.10 30093.22 27571.98 33790.09 27692.79 28078.53 27698.56 18787.43 20797.06 25196.46 242
jason: jason.
PAPM81.91 32180.11 33187.31 31693.87 28672.32 33784.02 34893.22 27569.47 34976.13 36889.84 32672.15 30897.23 28253.27 37089.02 35392.37 341
BH-w/o87.21 28487.02 27887.79 31294.77 25877.27 29287.90 30193.21 27781.74 27789.99 28188.39 34483.47 23396.93 29271.29 34792.43 33989.15 354
ppachtmachnet_test88.61 25888.64 24688.50 30091.76 32170.99 34384.59 34292.98 27879.30 29792.38 23693.53 26479.57 26797.45 27286.50 22497.17 24997.07 217
IterMVS90.18 22490.16 21890.21 27093.15 29675.98 30887.56 30692.97 27986.43 22094.09 17896.40 13778.32 27797.43 27387.87 20094.69 30897.23 214
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
test20.0390.80 20490.85 20490.63 25795.63 23479.24 26389.81 27092.87 28089.90 15194.39 17296.40 13785.77 22095.27 33573.86 33399.05 10197.39 207
CR-MVSNet87.89 26787.12 27690.22 26991.01 33178.93 26792.52 17092.81 28173.08 33289.10 29596.93 10267.11 32297.64 26388.80 18092.70 33594.08 309
Patchmtry90.11 22789.92 22590.66 25690.35 34077.00 29592.96 15792.81 28190.25 14694.74 16496.93 10267.11 32297.52 26785.17 23598.98 10997.46 199
GA-MVS87.70 27186.82 28090.31 26593.27 29377.22 29384.72 34192.79 28385.11 24489.82 28590.07 32466.80 32597.76 25784.56 24894.27 31695.96 261
sss87.23 28386.82 28088.46 30293.96 28377.94 28086.84 32092.78 28477.59 30887.61 32091.83 30278.75 27291.92 35877.84 30894.20 31795.52 281
Patchmatch-RL test88.81 25488.52 24789.69 28195.33 24679.94 24786.22 33192.71 28578.46 30495.80 11594.18 24266.25 33095.33 33389.22 17298.53 15993.78 319
test_yl90.11 22789.73 23091.26 23594.09 28079.82 25090.44 24692.65 28690.90 12893.19 21293.30 26873.90 30198.03 22982.23 26896.87 25995.93 262
DCV-MVSNet90.11 22789.73 23091.26 23594.09 28079.82 25090.44 24692.65 28690.90 12893.19 21293.30 26873.90 30198.03 22982.23 26896.87 25995.93 262
CL-MVSNet_self_test90.04 23289.90 22690.47 26195.24 24777.81 28486.60 32992.62 28885.64 23493.25 21093.92 25283.84 23296.06 31879.93 29298.03 21597.53 196
TSAR-MVS + GP.93.07 15192.41 16895.06 10295.82 22090.87 7390.97 23392.61 28988.04 19294.61 16793.79 25788.08 18397.81 25089.41 16598.39 17296.50 240
TAMVS90.16 22589.05 23893.49 16696.49 17286.37 16190.34 25192.55 29080.84 28292.99 21894.57 23081.94 25398.20 21773.51 33498.21 19895.90 265
MS-PatchMatch88.05 26687.75 26488.95 29193.28 29277.93 28187.88 30292.49 29175.42 31992.57 23093.59 26280.44 26394.24 34781.28 27792.75 33494.69 299
MG-MVS89.54 24089.80 22788.76 29594.88 25272.47 33689.60 27392.44 29285.82 23089.48 29195.98 16382.85 24097.74 25981.87 27195.27 29696.08 256
MVS_030490.96 20290.15 22193.37 16793.17 29587.06 14193.62 14492.43 29389.60 15782.25 35295.50 19082.56 24697.83 24984.41 25097.83 22695.22 284
lupinMVS88.34 26287.31 27091.45 22994.74 26180.06 24387.23 31192.27 29471.10 34188.83 29891.15 31177.02 28898.53 19086.67 21996.75 26495.76 271
pmmvs587.87 26887.14 27590.07 27393.26 29476.97 29888.89 29092.18 29573.71 32988.36 31093.89 25476.86 29396.73 29880.32 28496.81 26196.51 237
PM-MVS93.33 13892.67 16195.33 8996.58 16394.06 2192.26 18892.18 29585.92 22996.22 9596.61 12685.64 22495.99 32090.35 13798.23 19595.93 262
pmmvs488.95 25187.70 26692.70 19094.30 27585.60 17687.22 31292.16 29774.62 32389.75 28994.19 24177.97 28096.41 30782.71 26296.36 27296.09 255
MDA-MVSNet-bldmvs91.04 20090.88 20291.55 22794.68 26680.16 23885.49 33492.14 29890.41 14494.93 15695.79 17285.10 22596.93 29285.15 23794.19 31897.57 192
door-mid92.13 299
WTY-MVS86.93 29186.50 28988.24 30594.96 25174.64 31687.19 31392.07 30078.29 30588.32 31191.59 30778.06 27994.27 34574.88 32893.15 32995.80 269
AUN-MVS90.05 23188.30 25295.32 9296.09 20390.52 7792.42 17892.05 30182.08 27588.45 30992.86 27765.76 33298.69 16988.91 17896.07 27596.75 233
hse-mvs292.24 17891.20 19695.38 8696.16 19790.65 7592.52 17092.01 30289.23 16693.95 18592.99 27576.88 29198.69 16991.02 12296.03 27696.81 229
TR-MVS87.70 27187.17 27489.27 28894.11 27979.26 26288.69 29591.86 30381.94 27690.69 26789.79 32982.82 24197.42 27472.65 34091.98 34391.14 349
VDDNet94.03 12594.27 11993.31 17098.87 2082.36 21595.51 7891.78 30497.19 1296.32 8698.60 1884.24 23098.75 15687.09 21398.83 13098.81 79
Anonymous20240521192.58 16892.50 16692.83 18696.55 16683.22 20492.43 17791.64 30594.10 5195.59 12496.64 12481.88 25497.50 26885.12 23998.52 16097.77 179
HY-MVS82.50 1886.81 29285.93 29389.47 28293.63 28977.93 28194.02 13291.58 30675.68 31683.64 34493.64 25977.40 28397.42 27471.70 34592.07 34293.05 333
door91.26 307
PatchMatch-RL89.18 24488.02 26292.64 19295.90 21892.87 4788.67 29791.06 30880.34 28390.03 28091.67 30583.34 23494.42 34276.35 32194.84 30490.64 352
ADS-MVSNet284.01 30782.20 31589.41 28489.04 35376.37 30587.57 30490.98 30972.71 33584.46 33892.45 28868.08 31896.48 30570.58 35283.97 36195.38 282
KD-MVS_2432*160082.17 31880.75 32586.42 32282.04 37570.09 34781.75 35690.80 31082.56 26890.37 27289.30 33642.90 37796.11 31674.47 32992.55 33793.06 331
miper_refine_blended82.17 31880.75 32586.42 32282.04 37570.09 34781.75 35690.80 31082.56 26890.37 27289.30 33642.90 37796.11 31674.47 32992.55 33793.06 331
wuyk23d87.83 26990.79 20678.96 35090.46 33988.63 10992.72 16390.67 31291.65 11398.68 1197.64 5796.06 1677.53 37159.84 36699.41 5270.73 369
our_test_387.55 27687.59 26787.44 31591.76 32170.48 34483.83 34990.55 31379.79 28792.06 24792.17 29578.63 27595.63 32384.77 24594.73 30696.22 251
test_method50.44 33948.94 34254.93 35439.68 37812.38 38028.59 36990.09 3146.82 37241.10 37478.41 36754.41 36470.69 37350.12 37151.26 37381.72 367
EU-MVSNet87.39 28086.71 28389.44 28393.40 29176.11 30694.93 10090.00 31557.17 36895.71 12097.37 7264.77 33897.68 26292.67 8594.37 31394.52 302
CHOSEN 280x42080.04 33377.97 33886.23 32590.13 34174.53 31972.87 36489.59 31666.38 35776.29 36785.32 35956.96 36095.36 33169.49 35594.72 30788.79 357
MDA-MVSNet_test_wron88.16 26588.23 25687.93 30992.22 31173.71 32580.71 35988.84 31782.52 27094.88 15995.14 20482.70 24393.61 35083.28 25793.80 32196.46 242
YYNet188.17 26488.24 25587.93 30992.21 31273.62 32680.75 35888.77 31882.51 27194.99 15495.11 20682.70 24393.70 34983.33 25693.83 32096.48 241
PVSNet76.22 2082.89 31382.37 31384.48 33693.96 28364.38 36878.60 36188.61 31971.50 33984.43 34086.36 35574.27 30094.60 33969.87 35493.69 32394.46 303
MIMVSNet87.13 28886.54 28688.89 29396.05 20676.11 30694.39 12088.51 32081.37 27888.27 31296.75 11572.38 30795.52 32565.71 36295.47 29095.03 289
tpmvs84.22 30683.97 30584.94 33287.09 36465.18 36391.21 22888.35 32182.87 26785.21 33290.96 31565.24 33696.75 29779.60 29885.25 36092.90 335
EPNet_dtu85.63 29784.37 30189.40 28586.30 36774.33 32291.64 21988.26 32284.84 24972.96 37089.85 32571.27 31297.69 26176.60 31997.62 23696.18 253
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
tpm cat180.61 33179.46 33384.07 33988.78 35565.06 36689.26 28388.23 32362.27 36581.90 35789.66 33362.70 34995.29 33471.72 34480.60 36891.86 346
baseline187.62 27587.31 27088.54 29994.71 26574.27 32393.10 15488.20 32486.20 22392.18 24493.04 27373.21 30495.52 32579.32 29985.82 35995.83 267
CVMVSNet85.16 30084.72 29886.48 32092.12 31570.19 34592.32 18588.17 32556.15 36990.64 26895.85 16767.97 32096.69 29988.78 18190.52 35092.56 339
SCA87.43 27987.21 27388.10 30792.01 31871.98 33889.43 27788.11 32682.26 27488.71 30592.83 27878.65 27397.59 26479.61 29693.30 32694.75 296
tpmrst82.85 31482.93 31282.64 34387.65 35858.99 37390.14 25887.90 32775.54 31883.93 34291.63 30666.79 32795.36 33181.21 27981.54 36793.57 327
Vis-MVSNet (Re-imp)90.42 21490.16 21891.20 23997.66 11177.32 29194.33 12287.66 32891.20 12392.99 21895.13 20575.40 29898.28 20977.86 30799.19 8597.99 155
bset_n11_16_dypcd89.99 23389.15 23692.53 19994.75 25981.34 22784.19 34687.56 32985.13 24293.77 19092.46 28772.82 30599.01 11292.46 9099.21 8297.23 214
MDTV_nov1_ep1383.88 30689.42 35061.52 37188.74 29487.41 33073.99 32784.96 33694.01 24965.25 33595.53 32478.02 30693.16 328
PatchmatchNetpermissive85.22 29984.64 29986.98 31889.51 34969.83 35090.52 24487.34 33178.87 30187.22 32492.74 28266.91 32496.53 30281.77 27286.88 35894.58 300
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
N_pmnet88.90 25287.25 27293.83 15494.40 27493.81 3684.73 33987.09 33279.36 29593.26 20892.43 29179.29 26991.68 35977.50 31397.22 24896.00 259
EPNet89.80 23888.25 25494.45 13283.91 37386.18 16793.87 13787.07 33391.16 12580.64 36194.72 22578.83 27198.89 12885.17 23598.89 11898.28 129
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
Patchmatch-test86.10 29586.01 29286.38 32490.63 33574.22 32489.57 27486.69 33485.73 23389.81 28692.83 27865.24 33691.04 36177.82 31095.78 28393.88 318
K. test v393.37 13793.27 14893.66 15798.05 8182.62 21394.35 12186.62 33596.05 2897.51 4098.85 1276.59 29499.65 393.21 6798.20 20098.73 90
CostFormer83.09 31182.21 31485.73 32689.27 35167.01 35490.35 25086.47 33670.42 34583.52 34693.23 27161.18 35396.85 29477.21 31588.26 35693.34 329
thres20085.85 29685.18 29787.88 31194.44 27272.52 33589.08 28786.21 33788.57 18391.44 25488.40 34364.22 33998.00 23468.35 35695.88 28293.12 330
ET-MVSNet_ETH3D86.15 29484.27 30391.79 21993.04 29981.28 22887.17 31486.14 33879.57 29183.65 34388.66 34057.10 35998.18 22087.74 20295.40 29295.90 265
PatchT87.51 27788.17 25885.55 32790.64 33466.91 35592.02 19886.09 33992.20 8789.05 29797.16 8964.15 34096.37 31089.21 17392.98 33393.37 328
DWT-MVSNet_test80.74 32979.18 33485.43 32987.51 36166.87 35689.87 26886.01 34074.20 32680.86 36080.62 36648.84 37096.68 30181.54 27483.14 36592.75 337
tfpn200view987.05 28986.52 28788.67 29795.77 22372.94 33191.89 20686.00 34190.84 13092.61 22889.80 32763.93 34198.28 20971.27 34896.54 26894.79 294
thres40087.20 28586.52 28789.24 29095.77 22372.94 33191.89 20686.00 34190.84 13092.61 22889.80 32763.93 34198.28 20971.27 34896.54 26896.51 237
IB-MVS77.21 1983.11 31081.05 32189.29 28791.15 32975.85 30985.66 33386.00 34179.70 28982.02 35686.61 35248.26 37198.39 20077.84 30892.22 34093.63 323
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
PMMVS83.00 31281.11 32088.66 29883.81 37486.44 15982.24 35585.65 34461.75 36682.07 35485.64 35879.75 26691.59 36075.99 32393.09 33087.94 359
tpm84.38 30584.08 30485.30 33190.47 33863.43 37089.34 28085.63 34577.24 31287.62 31995.03 21261.00 35597.30 28079.26 30091.09 34995.16 285
LFMVS91.33 19791.16 19991.82 21896.27 18879.36 26095.01 9785.61 34696.04 2994.82 16097.06 9472.03 31098.46 19984.96 24398.70 14497.65 188
FPMVS84.50 30483.28 30888.16 30696.32 18494.49 1685.76 33285.47 34783.09 26385.20 33394.26 23863.79 34386.58 36863.72 36491.88 34583.40 363
tpm281.46 32280.35 32984.80 33389.90 34365.14 36490.44 24685.36 34865.82 36082.05 35592.44 29057.94 35896.69 29970.71 35188.49 35592.56 339
thres100view90087.35 28186.89 27988.72 29696.14 19973.09 33093.00 15685.31 34992.13 8993.26 20890.96 31563.42 34498.28 20971.27 34896.54 26894.79 294
thres600view787.66 27387.10 27789.36 28696.05 20673.17 32892.72 16385.31 34991.89 9693.29 20590.97 31463.42 34498.39 20073.23 33696.99 25896.51 237
dp79.28 33478.62 33681.24 34685.97 36856.45 37486.91 31885.26 35172.97 33381.45 35989.17 33956.01 36395.45 32973.19 33776.68 36991.82 347
PMMVS281.31 32383.44 30774.92 35290.52 33746.49 37769.19 36685.23 35284.30 25487.95 31694.71 22676.95 29084.36 37064.07 36398.09 21093.89 317
ADS-MVSNet82.25 31681.55 31784.34 33789.04 35365.30 36287.57 30485.13 35372.71 33584.46 33892.45 28868.08 31892.33 35770.58 35283.97 36195.38 282
test-LLR83.58 30883.17 30984.79 33489.68 34666.86 35783.08 35184.52 35483.07 26482.85 34984.78 36062.86 34793.49 35182.85 26094.86 30294.03 312
test-mter81.21 32580.01 33284.79 33489.68 34666.86 35783.08 35184.52 35473.85 32882.85 34984.78 36043.66 37693.49 35182.85 26094.86 30294.03 312
JIA-IIPM85.08 30183.04 31091.19 24087.56 35986.14 16889.40 27984.44 35688.98 17282.20 35397.95 4356.82 36196.15 31476.55 32083.45 36391.30 348
thisisatest053088.69 25787.52 26892.20 20696.33 18379.36 26092.81 16184.01 35786.44 21993.67 19492.68 28453.62 36799.25 7789.65 16298.45 16698.00 152
tttt051789.81 23788.90 24392.55 19897.00 14279.73 25495.03 9683.65 35889.88 15295.30 13794.79 22453.64 36699.39 4891.99 9998.79 13698.54 111
thisisatest051584.72 30382.99 31189.90 27792.96 30175.33 31484.36 34483.42 35977.37 31088.27 31286.65 35153.94 36598.72 16182.56 26497.40 24395.67 275
PVSNet_070.34 2174.58 33772.96 34079.47 34990.63 33566.24 36173.26 36283.40 36063.67 36478.02 36578.35 36872.53 30689.59 36556.68 36860.05 37282.57 366
pmmvs380.83 32878.96 33586.45 32187.23 36377.48 28984.87 33882.31 36163.83 36385.03 33489.50 33449.66 36993.10 35373.12 33895.10 29988.78 358
E-PMN80.72 33080.86 32480.29 34885.11 37068.77 35272.96 36381.97 36287.76 19883.25 34883.01 36462.22 35089.17 36677.15 31694.31 31582.93 364
test0.0.03 182.48 31581.47 31985.48 32889.70 34573.57 32784.73 33981.64 36383.07 26488.13 31486.61 35262.86 34789.10 36766.24 36190.29 35193.77 320
baseline283.38 30981.54 31888.90 29291.38 32772.84 33388.78 29281.22 36478.97 29979.82 36387.56 34661.73 35297.80 25174.30 33190.05 35296.05 258
EMVS80.35 33280.28 33080.54 34784.73 37269.07 35172.54 36580.73 36587.80 19781.66 35881.73 36562.89 34689.84 36475.79 32594.65 30982.71 365
TESTMET0.1,179.09 33578.04 33782.25 34487.52 36064.03 36983.08 35180.62 36670.28 34680.16 36283.22 36344.13 37590.56 36279.95 29093.36 32492.15 342
lessismore_v093.87 15398.05 8183.77 19980.32 36797.13 5297.91 4677.49 28299.11 9592.62 8698.08 21198.74 88
new_pmnet81.22 32481.01 32381.86 34590.92 33370.15 34684.03 34780.25 36870.83 34385.97 33089.78 33067.93 32184.65 36967.44 35891.90 34490.78 351
test111190.39 21690.61 21089.74 27998.04 8471.50 34095.59 7279.72 36989.41 16095.94 10998.14 3370.79 31398.81 14488.52 18799.32 6298.90 69
ECVR-MVScopyleft90.12 22690.16 21890.00 27697.81 9772.68 33495.76 6778.54 37089.04 17095.36 13498.10 3570.51 31498.64 17787.10 21299.18 8798.67 95
MVS-HIRNet78.83 33680.60 32773.51 35393.07 29747.37 37687.10 31578.00 37168.94 35077.53 36697.26 8271.45 31194.62 33863.28 36588.74 35478.55 368
DSMNet-mixed82.21 31781.56 31684.16 33889.57 34870.00 34990.65 24177.66 37254.99 37083.30 34797.57 5977.89 28190.50 36366.86 36095.54 28891.97 343
EPMVS81.17 32680.37 32883.58 34085.58 36965.08 36590.31 25271.34 37377.31 31185.80 33191.30 30959.38 35692.70 35679.99 28982.34 36692.96 334
gg-mvs-nofinetune82.10 32081.02 32285.34 33087.46 36271.04 34194.74 10567.56 37496.44 2279.43 36498.99 645.24 37396.15 31467.18 35992.17 34188.85 356
GG-mvs-BLEND83.24 34285.06 37171.03 34294.99 9965.55 37574.09 36975.51 36944.57 37494.46 34159.57 36787.54 35784.24 362
MVEpermissive59.87 2373.86 33872.65 34177.47 35187.00 36674.35 32161.37 36860.93 37667.27 35569.69 37186.49 35481.24 26072.33 37256.45 36983.45 36385.74 361
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
test250685.42 29884.57 30087.96 30897.81 9766.53 36096.14 5156.35 37789.04 17093.55 19898.10 3542.88 37998.68 17188.09 19599.18 8798.67 95
MTMP94.82 10254.62 378
DeepMVS_CXcopyleft53.83 35570.38 37764.56 36748.52 37933.01 37165.50 37274.21 37056.19 36246.64 37438.45 37370.07 37050.30 370
tmp_tt37.97 34044.33 34318.88 35611.80 37921.54 37963.51 36745.66 3804.23 37351.34 37350.48 37159.08 35722.11 37544.50 37268.35 37113.00 371
testmvs9.02 34311.42 3461.81 3582.77 3811.13 38279.44 3601.90 3811.18 3762.65 3776.80 3731.95 3810.87 3772.62 3753.45 3753.44 373
test1239.49 34212.01 3451.91 3572.87 3801.30 38182.38 3541.34 3821.36 3752.84 3766.56 3742.45 3800.97 3762.73 3745.56 3743.47 372
test_blank0.00 3460.00 3490.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 3770.00 3820.00 3780.00 3760.00 3760.00 374
uanet_test0.00 3460.00 3490.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 3770.00 3820.00 3780.00 3760.00 3760.00 374
pcd_1.5k_mvsjas7.56 34410.09 3470.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 37790.77 1450.00 3780.00 3760.00 3760.00 374
sosnet-low-res0.00 3460.00 3490.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 3770.00 3820.00 3780.00 3760.00 3760.00 374
sosnet0.00 3460.00 3490.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 3770.00 3820.00 3780.00 3760.00 3760.00 374
uncertanet0.00 3460.00 3490.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 3770.00 3820.00 3780.00 3760.00 3760.00 374
Regformer0.00 3460.00 3490.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 3770.00 3820.00 3780.00 3760.00 3760.00 374
n20.00 383
nn0.00 383
ab-mvs-re7.56 34410.08 3480.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 37890.69 3200.00 3820.00 3780.00 3760.00 3760.00 374
uanet0.00 3460.00 3490.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 3770.00 3820.00 3780.00 3760.00 3760.00 374
PC_three_145275.31 32195.87 11395.75 17692.93 9396.34 31387.18 21198.68 14698.04 147
eth-test20.00 382
eth-test0.00 382
OPU-MVS95.15 9996.84 15189.43 9495.21 8695.66 18093.12 8798.06 22786.28 22898.61 15197.95 160
test_0728_THIRD93.26 6897.40 4697.35 7894.69 5599.34 6293.88 3499.42 4798.89 70
GSMVS94.75 296
test_part298.21 7189.41 9596.72 71
sam_mvs166.64 32894.75 296
sam_mvs66.41 329
test_post190.21 2545.85 37665.36 33496.00 31979.61 296
test_post6.07 37565.74 33395.84 321
patchmatchnet-post91.71 30466.22 33197.59 264
gm-plane-assit87.08 36559.33 37271.22 34083.58 36297.20 28373.95 332
test9_res88.16 19398.40 16997.83 173
agg_prior287.06 21498.36 18097.98 156
test_prior489.91 8490.74 238
test_prior290.21 25489.33 16490.77 26494.81 22090.41 15588.21 18998.55 155
旧先验290.00 26368.65 35192.71 22696.52 30385.15 237
新几何290.02 262
原ACMM289.34 280
testdata298.03 22980.24 287
segment_acmp92.14 111
testdata188.96 28988.44 185
plane_prior797.71 10588.68 108
plane_prior697.21 13488.23 11986.93 205
plane_prior495.59 182
plane_prior388.43 11790.35 14593.31 203
plane_prior294.56 11491.74 109
plane_prior197.38 126
plane_prior88.12 12193.01 15588.98 17298.06 212
HQP5-MVS84.89 183
HQP-NCC96.36 17891.37 22387.16 21088.81 300
ACMP_Plane96.36 17891.37 22387.16 21088.81 300
BP-MVS86.55 222
HQP4-MVS88.81 30098.61 17998.15 138
HQP2-MVS84.76 227
NP-MVS96.82 15287.10 14093.40 266
MDTV_nov1_ep13_2view42.48 37888.45 29967.22 35683.56 34566.80 32572.86 33994.06 311
ACMMP++_ref98.82 131
ACMMP++99.25 76
Test By Simon90.61 151