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

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

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

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

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




Method Infoallhigh-res
multi-view
indooroutdoorbotani.boulde.bridgedoorexhibi.lectur.living.loungeobserv.old co.statueterrac.
sort bysort bysort bysort bysort bysort bysort bysort bysort bysorted bysort bysort bysort bysort bysort bysort by
LCM-MVSNet99.86 199.86 199.87 199.99 199.77 199.77 199.80 199.97 199.97 199.95 199.74 199.98 199.56 1100.00 199.85 3
PS-MVSNAJss98.53 1998.63 1998.21 8099.68 994.82 13198.10 5099.21 1696.91 8899.75 299.45 995.82 10999.92 598.80 499.96 499.89 1
UniMVSNet_ETH3D99.12 399.28 398.65 4399.77 396.34 6799.18 599.20 1899.67 299.73 399.65 499.15 399.86 2297.22 4899.92 1499.77 8
mvs_tets98.90 598.94 698.75 3399.69 896.48 6398.54 2099.22 1596.23 11599.71 499.48 798.77 699.93 398.89 399.95 599.84 5
wuyk23d93.25 27895.20 19587.40 35496.07 32595.38 10697.04 11494.97 31895.33 16199.70 598.11 12398.14 1391.94 37277.76 36599.68 6474.89 372
Anonymous2023121198.55 1798.76 1397.94 9998.79 11494.37 14998.84 1099.15 2699.37 399.67 699.43 1195.61 12199.72 9098.12 1699.86 2599.73 15
jajsoiax98.77 998.79 1298.74 3599.66 1096.48 6398.45 2799.12 3095.83 14299.67 699.37 1298.25 1099.92 598.77 599.94 899.82 6
ANet_high98.31 2898.94 696.41 20699.33 4589.64 25197.92 6099.56 799.27 699.66 899.50 697.67 2599.83 3297.55 3799.98 299.77 8
pmmvs699.07 499.24 498.56 4999.81 296.38 6598.87 999.30 1299.01 1699.63 999.66 399.27 299.68 12897.75 3099.89 2299.62 26
LTVRE_ROB96.88 199.18 299.34 298.72 3899.71 796.99 4699.69 299.57 699.02 1599.62 1099.36 1498.53 799.52 18498.58 1299.95 599.66 22
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
OurMVSNet-221017-098.61 1698.61 2398.63 4599.77 396.35 6699.17 699.05 4598.05 4399.61 1199.52 593.72 18299.88 1998.72 999.88 2399.65 24
TransMVSNet (Re)98.38 2598.67 1797.51 13199.51 2493.39 18698.20 4598.87 8998.23 3699.48 1299.27 1998.47 899.55 17596.52 7099.53 10599.60 27
LCM-MVSNet-Re97.33 10697.33 9997.32 15498.13 19893.79 17296.99 11799.65 496.74 9399.47 1398.93 4796.91 6399.84 2990.11 28599.06 21998.32 254
SixPastTwentyTwo97.49 9497.57 8397.26 15899.56 1792.33 20598.28 3796.97 28298.30 3499.45 1499.35 1688.43 26999.89 1798.01 2099.76 4499.54 40
v7n98.73 1198.99 597.95 9899.64 1194.20 15798.67 1399.14 2899.08 1099.42 1599.23 2196.53 8499.91 1399.27 299.93 1099.73 15
NR-MVSNet97.96 4797.86 5298.26 7298.73 12095.54 9698.14 4898.73 13197.79 4899.42 1597.83 15994.40 16599.78 4795.91 9899.76 4499.46 66
MIMVSNet198.51 2098.45 2698.67 4199.72 696.71 5298.76 1198.89 8198.49 2899.38 1799.14 3395.44 13099.84 2996.47 7399.80 3699.47 64
ACMH93.61 998.44 2298.76 1397.51 13199.43 3493.54 18298.23 4099.05 4597.40 7599.37 1899.08 3798.79 599.47 19797.74 3199.71 5899.50 47
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
anonymousdsp98.72 1498.63 1998.99 1399.62 1397.29 3998.65 1699.19 2095.62 15099.35 1999.37 1297.38 3399.90 1498.59 1199.91 1799.77 8
test_djsdf98.73 1198.74 1698.69 4099.63 1296.30 6998.67 1399.02 5496.50 10399.32 2099.44 1097.43 3199.92 598.73 799.95 599.86 2
test_part196.77 13996.53 14997.47 13998.04 20292.92 19697.93 5898.85 9698.83 2199.30 2199.07 3879.25 32099.79 4397.59 3599.93 1099.69 20
PEN-MVS98.75 1098.85 1098.44 5699.58 1595.67 9198.45 2799.15 2699.33 599.30 2199.00 4197.27 3899.92 597.64 3499.92 1499.75 13
DTE-MVSNet98.79 898.86 898.59 4799.55 1996.12 7498.48 2699.10 3399.36 499.29 2399.06 3997.27 3899.93 397.71 3299.91 1799.70 18
pm-mvs198.47 2198.67 1797.86 10599.52 2394.58 14198.28 3799.00 6297.57 6399.27 2499.22 2298.32 999.50 18997.09 5699.75 4899.50 47
ACMH+93.58 1098.23 3298.31 2997.98 9799.39 3995.22 11997.55 8399.20 1898.21 3799.25 2598.51 7698.21 1199.40 22194.79 16599.72 5599.32 103
Anonymous2024052997.96 4798.04 3997.71 11598.69 12994.28 15497.86 6398.31 19698.79 2299.23 2698.86 5395.76 11699.61 16095.49 12199.36 16299.23 129
PS-CasMVS98.73 1198.85 1098.39 6099.55 1995.47 10398.49 2499.13 2999.22 899.22 2798.96 4597.35 3499.92 597.79 2899.93 1099.79 7
SD-MVS97.37 10397.70 6496.35 20798.14 19595.13 12396.54 13698.92 7895.94 13399.19 2898.08 12597.74 2295.06 37095.24 14099.54 10298.87 200
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
WR-MVS_H98.65 1598.62 2198.75 3399.51 2496.61 5798.55 1999.17 2199.05 1399.17 2998.79 5595.47 12899.89 1797.95 2199.91 1799.75 13
dcpmvs_297.12 11597.99 4294.51 28799.11 8484.00 33897.75 7099.65 497.38 7699.14 3098.42 8295.16 13899.96 295.52 12099.78 4199.58 29
tfpnnormal97.72 7797.97 4396.94 17399.26 5092.23 20897.83 6598.45 17398.25 3599.13 3198.66 6596.65 7699.69 12193.92 20499.62 7398.91 190
SED-MVS97.94 5397.90 4798.07 8999.22 5995.35 10996.79 12498.83 10896.11 12199.08 3298.24 10797.87 2099.72 9095.44 12899.51 11599.14 145
test_241102_ONE99.22 5995.35 10998.83 10896.04 12699.08 3298.13 11997.87 2099.33 242
VPA-MVSNet98.27 2998.46 2497.70 11799.06 9093.80 17197.76 6999.00 6298.40 3099.07 3498.98 4396.89 6499.75 6997.19 5399.79 3899.55 39
nrg03098.54 1898.62 2198.32 6599.22 5995.66 9297.90 6199.08 3998.31 3399.02 3598.74 5997.68 2499.61 16097.77 2999.85 2899.70 18
CP-MVSNet98.42 2398.46 2498.30 6999.46 3095.22 11998.27 3998.84 10199.05 1399.01 3698.65 6795.37 13199.90 1497.57 3699.91 1799.77 8
FMVSNet197.95 5198.08 3597.56 12699.14 8293.67 17698.23 4098.66 15197.41 7499.00 3799.19 2495.47 12899.73 8595.83 10399.76 4499.30 109
TDRefinement98.90 598.86 899.02 999.54 2198.06 899.34 499.44 1098.85 2099.00 3799.20 2397.42 3299.59 16297.21 5099.76 4499.40 86
K. test v396.44 15996.28 16096.95 17299.41 3791.53 22597.65 7690.31 36098.89 1998.93 3999.36 1484.57 29899.92 597.81 2699.56 9399.39 88
FC-MVSNet-test98.16 3398.37 2797.56 12699.49 2893.10 19298.35 3099.21 1698.43 2998.89 4098.83 5494.30 16799.81 3697.87 2499.91 1799.77 8
FOURS199.59 1498.20 499.03 799.25 1498.96 1898.87 41
KD-MVS_self_test97.86 6698.07 3697.25 15999.22 5992.81 19897.55 8398.94 7697.10 8498.85 4298.88 5195.03 14399.67 13397.39 4599.65 6899.26 122
TranMVSNet+NR-MVSNet98.33 2698.30 3198.43 5799.07 8995.87 8296.73 13199.05 4598.67 2498.84 4398.45 8097.58 2899.88 1996.45 7499.86 2599.54 40
new-patchmatchnet95.67 18796.58 14392.94 32197.48 26880.21 35692.96 30498.19 21194.83 18298.82 4498.79 5593.31 18999.51 18895.83 10399.04 22099.12 153
EG-PatchMatch MVS97.69 7997.79 5797.40 14999.06 9093.52 18395.96 16998.97 7294.55 19398.82 4498.76 5897.31 3699.29 25397.20 5299.44 13799.38 90
DPE-MVScopyleft97.64 8297.35 9898.50 5298.85 10996.18 7195.21 21798.99 6595.84 14198.78 4698.08 12596.84 7099.81 3693.98 20299.57 9099.52 44
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
COLMAP_ROBcopyleft94.48 698.25 3198.11 3498.64 4499.21 6697.35 3797.96 5699.16 2298.34 3298.78 4698.52 7597.32 3599.45 20494.08 19599.67 6599.13 148
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
lessismore_v097.05 16899.36 4292.12 21384.07 37298.77 4898.98 4385.36 29299.74 7997.34 4699.37 15999.30 109
v897.60 8698.06 3896.23 21398.71 12589.44 25597.43 9398.82 11697.29 8098.74 4999.10 3593.86 17799.68 12898.61 1099.94 899.56 37
DP-MVS97.87 6497.89 5097.81 10898.62 13794.82 13197.13 10998.79 11898.98 1798.74 4998.49 7795.80 11599.49 19195.04 15599.44 13799.11 157
v1097.55 8997.97 4396.31 21098.60 14089.64 25197.44 9199.02 5496.60 9798.72 5199.16 3093.48 18699.72 9098.76 699.92 1499.58 29
test072699.24 5495.51 9896.89 12098.89 8195.92 13498.64 5298.31 9297.06 50
DVP-MVS++97.96 4797.90 4798.12 8697.75 24695.40 10499.03 798.89 8196.62 9598.62 5398.30 9696.97 5699.75 6995.70 10699.25 19099.21 131
test_241102_TWO98.83 10896.11 12198.62 5398.24 10796.92 6299.72 9095.44 12899.49 12399.49 55
FIs97.93 5698.07 3697.48 13899.38 4092.95 19598.03 5599.11 3198.04 4498.62 5398.66 6593.75 18199.78 4797.23 4799.84 2999.73 15
abl_698.42 2398.19 3299.09 399.16 7198.10 697.73 7499.11 3197.76 5298.62 5398.27 10597.88 1999.80 4295.67 11099.50 11999.38 90
DeepC-MVS95.41 497.82 7097.70 6498.16 8198.78 11695.72 8696.23 15399.02 5493.92 21498.62 5398.99 4297.69 2399.62 15496.18 8299.87 2499.15 142
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
APDe-MVS98.14 3498.03 4098.47 5598.72 12296.04 7798.07 5299.10 3395.96 13198.59 5898.69 6396.94 5899.81 3696.64 6499.58 8799.57 34
XXY-MVS97.54 9097.70 6497.07 16799.46 3092.21 20997.22 10399.00 6294.93 18098.58 5998.92 4897.31 3699.41 21994.44 17899.43 14599.59 28
test_040297.84 6797.97 4397.47 13999.19 6994.07 16096.71 13298.73 13198.66 2598.56 6098.41 8396.84 7099.69 12194.82 16399.81 3398.64 223
PM-MVS97.36 10597.10 11498.14 8598.91 10596.77 5196.20 15498.63 15793.82 21598.54 6198.33 9093.98 17599.05 28695.99 9399.45 13698.61 228
DeepPCF-MVS94.58 596.90 12896.43 15598.31 6797.48 26897.23 4292.56 31398.60 15992.84 24998.54 6197.40 19896.64 7898.78 31294.40 18299.41 15498.93 185
MSP-MVS97.45 9796.92 12799.03 899.26 5097.70 1997.66 7598.89 8195.65 14898.51 6396.46 26592.15 21799.81 3695.14 14998.58 26699.58 29
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
VDD-MVS97.37 10397.25 10497.74 11398.69 12994.50 14597.04 11495.61 31198.59 2698.51 6398.72 6092.54 21099.58 16496.02 9099.49 12399.12 153
FMVSNet296.72 14396.67 14096.87 17897.96 21291.88 21997.15 10698.06 23095.59 15298.50 6598.62 6889.51 26099.65 14194.99 15999.60 8399.07 164
test111194.53 24194.81 21693.72 30199.06 9081.94 35098.31 3483.87 37396.37 10898.49 6699.17 2981.49 30999.73 8596.64 6499.86 2599.49 55
SMA-MVScopyleft97.48 9597.11 11398.60 4698.83 11096.67 5496.74 12798.73 13191.61 26598.48 6798.36 8796.53 8499.68 12895.17 14499.54 10299.45 71
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
EU-MVSNet94.25 24994.47 23593.60 30498.14 19582.60 34597.24 10292.72 34085.08 33398.48 6798.94 4682.59 30698.76 31597.47 4299.53 10599.44 81
RPSCF97.87 6497.51 8798.95 1799.15 7498.43 397.56 8299.06 4396.19 11898.48 6798.70 6294.72 15199.24 26194.37 18399.33 17799.17 138
v124096.74 14097.02 12195.91 22998.18 18888.52 27095.39 20198.88 8793.15 23898.46 7098.40 8692.80 20099.71 10498.45 1399.49 12399.49 55
VPNet97.26 11097.49 9096.59 19399.47 2990.58 24096.27 14898.53 16697.77 4998.46 7098.41 8394.59 15899.68 12894.61 17199.29 18599.52 44
IterMVS-LS96.92 12697.29 10195.79 23398.51 15088.13 28095.10 22098.66 15196.99 8598.46 7098.68 6492.55 20899.74 7996.91 6299.79 3899.50 47
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
ambc96.56 19798.23 18291.68 22497.88 6298.13 22098.42 7398.56 7294.22 17099.04 28794.05 19999.35 16798.95 179
DVP-MVScopyleft97.78 7397.65 7198.16 8199.24 5495.51 9896.74 12798.23 20295.92 13498.40 7498.28 10197.06 5099.71 10495.48 12499.52 11099.26 122
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_THIRD96.62 9598.40 7498.28 10197.10 4599.71 10495.70 10699.62 7399.58 29
VDDNet96.98 12396.84 13097.41 14899.40 3893.26 18897.94 5795.31 31799.26 798.39 7699.18 2787.85 27899.62 15495.13 15199.09 21399.35 100
PC_three_145287.24 31098.37 7797.44 19597.00 5496.78 36792.01 23599.25 19099.21 131
Anonymous20240521196.34 16295.98 17497.43 14698.25 17993.85 16996.74 12794.41 32497.72 5698.37 7798.03 13587.15 28299.53 18094.06 19699.07 21698.92 189
Baseline_NR-MVSNet97.72 7797.79 5797.50 13499.56 1793.29 18795.44 19598.86 9298.20 3898.37 7799.24 2094.69 15299.55 17595.98 9499.79 3899.65 24
IU-MVS99.22 5995.40 10498.14 21885.77 32598.36 8095.23 14199.51 11599.49 55
IterMVS-SCA-FT95.86 18296.19 16394.85 27197.68 25385.53 31892.42 31697.63 25996.99 8598.36 8098.54 7487.94 27399.75 6997.07 5899.08 21499.27 121
ACMM93.33 1198.05 4297.79 5798.85 2599.15 7497.55 2796.68 13398.83 10895.21 16598.36 8098.13 11998.13 1499.62 15496.04 8899.54 10299.39 88
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
Anonymous2024052197.07 11797.51 8795.76 23499.35 4388.18 27797.78 6698.40 18397.11 8398.34 8399.04 4089.58 25699.79 4398.09 1899.93 1099.30 109
Regformer-497.53 9297.47 9397.71 11597.35 27893.91 16595.26 21298.14 21897.97 4598.34 8397.89 15295.49 12599.71 10497.41 4399.42 14899.51 46
LPG-MVS_test97.94 5397.67 6898.74 3599.15 7497.02 4497.09 11199.02 5495.15 16998.34 8398.23 10997.91 1799.70 11394.41 18099.73 5299.50 47
LGP-MVS_train98.74 3599.15 7497.02 4499.02 5495.15 16998.34 8398.23 10997.91 1799.70 11394.41 18099.73 5299.50 47
casdiffmvs97.50 9397.81 5696.56 19798.51 15091.04 23195.83 17799.09 3897.23 8198.33 8798.30 9697.03 5299.37 23296.58 6899.38 15899.28 117
Patchmatch-RL test94.66 23494.49 23395.19 25798.54 14788.91 26392.57 31298.74 12991.46 26898.32 8897.75 16877.31 33398.81 31096.06 8599.61 7997.85 292
XVG-OURS97.12 11596.74 13698.26 7298.99 9897.45 3493.82 28199.05 4595.19 16798.32 8897.70 17495.22 13798.41 34294.27 18898.13 28198.93 185
UniMVSNet_NR-MVSNet97.83 6897.65 7198.37 6198.72 12295.78 8495.66 18599.02 5498.11 4098.31 9097.69 17694.65 15699.85 2697.02 5999.71 5899.48 61
DU-MVS97.79 7297.60 8098.36 6298.73 12095.78 8495.65 18898.87 8997.57 6398.31 9097.83 15994.69 15299.85 2697.02 5999.71 5899.46 66
EI-MVSNet-UG-set97.32 10797.40 9497.09 16697.34 28292.01 21795.33 20697.65 25597.74 5398.30 9298.14 11895.04 14299.69 12197.55 3799.52 11099.58 29
EI-MVSNet-Vis-set97.32 10797.39 9597.11 16497.36 27792.08 21595.34 20597.65 25597.74 5398.29 9398.11 12395.05 14099.68 12897.50 3999.50 11999.56 37
test20.0396.58 15396.61 14196.48 20198.49 15491.72 22395.68 18497.69 25096.81 9198.27 9497.92 15094.18 17198.71 31990.78 26699.66 6799.00 173
RRT_MVS94.90 21994.07 24897.39 15093.18 36493.21 19095.26 21297.49 26393.94 21398.25 9597.85 15772.96 35599.84 2997.90 2299.78 4199.14 145
APD-MVS_3200maxsize98.13 3797.90 4798.79 3198.79 11497.31 3897.55 8398.92 7897.72 5698.25 9598.13 11997.10 4599.75 6995.44 12899.24 19399.32 103
v14896.58 15396.97 12295.42 25098.63 13687.57 29195.09 22297.90 23695.91 13698.24 9797.96 14293.42 18799.39 22696.04 8899.52 11099.29 116
ECVR-MVScopyleft94.37 24794.48 23494.05 29898.95 10083.10 34298.31 3482.48 37496.20 11698.23 9899.16 3081.18 31299.66 13995.95 9599.83 3199.38 90
UniMVSNet (Re)97.83 6897.65 7198.35 6498.80 11395.86 8395.92 17399.04 5197.51 6898.22 9997.81 16394.68 15499.78 4797.14 5599.75 4899.41 85
SR-MVS-dyc-post98.14 3497.84 5399.02 998.81 11198.05 997.55 8398.86 9297.77 4998.20 10098.07 12796.60 8199.76 6295.49 12199.20 19599.26 122
RE-MVS-def97.88 5198.81 11198.05 997.55 8398.86 9297.77 4998.20 10098.07 12796.94 5895.49 12199.20 19599.26 122
WR-MVS96.90 12896.81 13297.16 16198.56 14592.20 21194.33 25598.12 22197.34 7798.20 10097.33 20992.81 19999.75 6994.79 16599.81 3399.54 40
v192192096.72 14396.96 12495.99 22298.21 18388.79 26795.42 19798.79 11893.22 23298.19 10398.26 10692.68 20399.70 11398.34 1599.55 9999.49 55
Regformer-397.25 11197.29 10197.11 16497.35 27892.32 20695.26 21297.62 26097.67 6198.17 10497.89 15295.05 14099.56 17197.16 5499.42 14899.46 66
TSAR-MVS + MP.97.42 9997.23 10798.00 9699.38 4095.00 12697.63 7898.20 20693.00 24298.16 10598.06 13295.89 10499.72 9095.67 11099.10 21299.28 117
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
TinyColmap96.00 17796.34 15894.96 26597.90 21887.91 28394.13 26998.49 17094.41 19598.16 10597.76 16596.29 9898.68 32490.52 27899.42 14898.30 258
test117298.08 3997.76 6199.05 698.78 11698.07 797.41 9598.85 9697.57 6398.15 10797.96 14296.60 8199.76 6295.30 13699.18 19999.33 102
XVG-OURS-SEG-HR97.38 10297.07 11798.30 6999.01 9797.41 3694.66 24599.02 5495.20 16698.15 10797.52 18898.83 498.43 34194.87 16196.41 33399.07 164
IS-MVSNet96.93 12596.68 13997.70 11799.25 5394.00 16398.57 1796.74 29198.36 3198.14 10997.98 14188.23 27199.71 10493.10 22499.72 5599.38 90
CSCG97.40 10197.30 10097.69 11998.95 10094.83 13097.28 9998.99 6596.35 11198.13 11095.95 29395.99 10299.66 13994.36 18699.73 5298.59 229
MP-MVS-pluss97.69 7997.36 9798.70 3999.50 2796.84 4995.38 20298.99 6592.45 25498.11 11198.31 9297.25 4199.77 5796.60 6699.62 7399.48 61
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
v119296.83 13497.06 11896.15 21898.28 17489.29 25795.36 20398.77 12393.73 21798.11 11198.34 8993.02 19799.67 13398.35 1499.58 8799.50 47
Regformer-297.41 10097.24 10697.93 10097.21 28994.72 13494.85 23898.27 19797.74 5398.11 11197.50 19095.58 12399.69 12196.57 6999.31 18199.37 97
OPM-MVS97.54 9097.25 10498.41 5899.11 8496.61 5795.24 21598.46 17294.58 19298.10 11498.07 12797.09 4799.39 22695.16 14699.44 13799.21 131
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
v14419296.69 14696.90 12996.03 22198.25 17988.92 26295.49 19398.77 12393.05 24098.09 11598.29 10092.51 21299.70 11398.11 1799.56 9399.47 64
N_pmnet95.18 20894.23 24298.06 9197.85 22096.55 6192.49 31491.63 34889.34 28998.09 11597.41 19790.33 24599.06 28591.58 24799.31 18198.56 231
test_part299.03 9696.07 7698.08 117
SteuartSystems-ACMMP98.02 4497.76 6198.79 3199.43 3497.21 4397.15 10698.90 8096.58 9998.08 11797.87 15697.02 5399.76 6295.25 13999.59 8599.40 86
Skip Steuart: Steuart Systems R&D Blog.
SR-MVS98.00 4697.66 6999.01 1198.77 11897.93 1197.38 9698.83 10897.32 7898.06 11997.85 15796.65 7699.77 5795.00 15899.11 21099.32 103
XVG-ACMP-BASELINE97.58 8897.28 10398.49 5399.16 7196.90 4896.39 14198.98 6895.05 17498.06 11998.02 13695.86 10599.56 17194.37 18399.64 7099.00 173
IterMVS95.42 19995.83 17994.20 29597.52 26683.78 34092.41 31797.47 26695.49 15698.06 11998.49 7787.94 27399.58 16496.02 9099.02 22199.23 129
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
TSAR-MVS + GP.96.47 15896.12 16697.49 13797.74 24995.23 11694.15 26696.90 28493.26 23098.04 12296.70 25294.41 16498.89 30394.77 16899.14 20298.37 247
test_one_060199.05 9495.50 10198.87 8997.21 8298.03 12398.30 9696.93 60
Regformer-197.27 10997.16 11197.61 12497.21 28993.86 16894.85 23898.04 23297.62 6298.03 12397.50 19095.34 13299.63 14696.52 7099.31 18199.35 100
testgi96.07 17296.50 15394.80 27499.26 5087.69 29095.96 16998.58 16295.08 17298.02 12596.25 27697.92 1697.60 36188.68 30798.74 25199.11 157
V4297.04 11897.16 11196.68 19098.59 14291.05 23096.33 14698.36 18894.60 18997.99 12698.30 9693.32 18899.62 15497.40 4499.53 10599.38 90
GBi-Net96.99 12096.80 13397.56 12697.96 21293.67 17698.23 4098.66 15195.59 15297.99 12699.19 2489.51 26099.73 8594.60 17299.44 13799.30 109
test196.99 12096.80 13397.56 12697.96 21293.67 17698.23 4098.66 15195.59 15297.99 12699.19 2489.51 26099.73 8594.60 17299.44 13799.30 109
FMVSNet395.26 20694.94 20696.22 21596.53 30890.06 24495.99 16697.66 25394.11 20897.99 12697.91 15180.22 31899.63 14694.60 17299.44 13798.96 178
pmmvs-eth3d96.49 15696.18 16497.42 14798.25 17994.29 15194.77 24298.07 22989.81 28697.97 13098.33 9093.11 19299.08 28395.46 12799.84 2998.89 194
v114496.84 13197.08 11696.13 21998.42 16489.28 25895.41 19998.67 14994.21 20397.97 13098.31 9293.06 19399.65 14198.06 1999.62 7399.45 71
ACMP92.54 1397.47 9697.10 11498.55 5099.04 9596.70 5396.24 15298.89 8193.71 21897.97 13097.75 16897.44 3099.63 14693.22 22199.70 6199.32 103
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
EI-MVSNet96.63 15096.93 12595.74 23597.26 28788.13 28095.29 21097.65 25596.99 8597.94 13398.19 11492.55 20899.58 16496.91 6299.56 9399.50 47
MVSTER94.21 25293.93 25595.05 26295.83 33086.46 30895.18 21897.65 25592.41 25597.94 13398.00 14072.39 35699.58 16496.36 7799.56 9399.12 153
ACMMPcopyleft98.05 4297.75 6398.93 2199.23 5697.60 2398.09 5198.96 7395.75 14697.91 13598.06 13296.89 6499.76 6295.32 13599.57 9099.43 82
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
zzz-MVS98.01 4597.66 6999.06 499.44 3297.90 1295.66 18598.73 13197.69 5997.90 13697.96 14295.81 11399.82 3396.13 8399.61 7999.45 71
MTAPA98.14 3497.84 5399.06 499.44 3297.90 1297.25 10098.73 13197.69 5997.90 13697.96 14295.81 11399.82 3396.13 8399.61 7999.45 71
LFMVS95.32 20394.88 21196.62 19198.03 20391.47 22797.65 7690.72 35799.11 997.89 13898.31 9279.20 32199.48 19493.91 20599.12 20998.93 185
ACMMP_NAP97.89 6297.63 7698.67 4199.35 4396.84 4996.36 14498.79 11895.07 17397.88 13998.35 8897.24 4299.72 9096.05 8799.58 8799.45 71
VNet96.84 13196.83 13196.88 17798.06 20192.02 21696.35 14597.57 26297.70 5897.88 13997.80 16492.40 21499.54 17894.73 17098.96 22599.08 162
HPM-MVS_fast98.32 2798.13 3398.88 2499.54 2197.48 3298.35 3099.03 5295.88 13797.88 13998.22 11298.15 1299.74 7996.50 7299.62 7399.42 83
UA-Net98.88 798.76 1399.22 299.11 8497.89 1499.47 399.32 1199.08 1097.87 14299.67 296.47 8999.92 597.88 2399.98 299.85 3
baseline97.44 9897.78 6096.43 20398.52 14990.75 23896.84 12199.03 5296.51 10297.86 14398.02 13696.67 7599.36 23497.09 5699.47 12999.19 135
v2v48296.78 13897.06 11895.95 22698.57 14488.77 26895.36 20398.26 19995.18 16897.85 14498.23 10992.58 20799.63 14697.80 2799.69 6299.45 71
xxxxxxxxxxxxxcwj97.24 11297.03 12097.89 10298.48 15694.71 13594.53 25099.07 4295.02 17697.83 14597.88 15496.44 9199.72 9094.59 17599.39 15699.25 126
SF-MVS97.60 8697.39 9598.22 7798.93 10395.69 8897.05 11399.10 3395.32 16297.83 14597.88 15496.44 9199.72 9094.59 17599.39 15699.25 126
Vis-MVSNetpermissive98.27 2998.34 2898.07 8999.33 4595.21 12198.04 5399.46 997.32 7897.82 14799.11 3496.75 7399.86 2297.84 2599.36 16299.15 142
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
AllTest97.20 11496.92 12798.06 9199.08 8796.16 7297.14 10899.16 2294.35 19897.78 14898.07 12795.84 10699.12 27691.41 24999.42 14898.91 190
TestCases98.06 9199.08 8796.16 7299.16 2294.35 19897.78 14898.07 12795.84 10699.12 27691.41 24999.42 14898.91 190
GeoE97.75 7597.70 6497.89 10298.88 10794.53 14297.10 11098.98 6895.75 14697.62 15097.59 18297.61 2799.77 5796.34 7899.44 13799.36 98
MDA-MVSNet-bldmvs95.69 18595.67 18495.74 23598.48 15688.76 26992.84 30597.25 26996.00 12997.59 15197.95 14691.38 23399.46 20093.16 22396.35 33498.99 176
PGM-MVS97.88 6397.52 8698.96 1699.20 6797.62 2297.09 11199.06 4395.45 15797.55 15297.94 14797.11 4499.78 4794.77 16899.46 13299.48 61
GST-MVS97.82 7097.49 9098.81 2999.23 5697.25 4097.16 10598.79 11895.96 13197.53 15397.40 19896.93 6099.77 5795.04 15599.35 16799.42 83
YYNet194.73 22694.84 21394.41 29097.47 27285.09 32790.29 34895.85 30692.52 25197.53 15397.76 16591.97 22399.18 26793.31 21896.86 32398.95 179
bset_n11_16_dypcd94.53 24193.95 25496.25 21297.56 26389.85 24888.52 36191.32 35094.90 18197.51 15596.38 27182.34 30799.78 4797.22 4899.80 3699.12 153
TAMVS95.49 19394.94 20697.16 16198.31 17093.41 18595.07 22596.82 28791.09 27497.51 15597.82 16289.96 25299.42 21088.42 31099.44 13798.64 223
LS3D97.77 7497.50 8998.57 4896.24 31597.58 2598.45 2798.85 9698.58 2797.51 15597.94 14795.74 11799.63 14695.19 14298.97 22498.51 235
HFP-MVS97.94 5397.64 7498.83 2699.15 7497.50 3097.59 8098.84 10196.05 12497.49 15897.54 18597.07 4899.70 11395.61 11699.46 13299.30 109
#test#97.62 8497.22 10898.83 2699.15 7497.50 3096.81 12398.84 10194.25 20297.49 15897.54 18597.07 4899.70 11394.37 18399.46 13299.30 109
Patchmtry95.03 21694.59 22996.33 20894.83 34790.82 23596.38 14397.20 27196.59 9897.49 15898.57 7077.67 32899.38 22992.95 22799.62 7398.80 206
MDA-MVSNet_test_wron94.73 22694.83 21594.42 28997.48 26885.15 32590.28 34995.87 30592.52 25197.48 16197.76 16591.92 22799.17 27193.32 21796.80 32698.94 181
UnsupCasMVSNet_eth95.91 17995.73 18396.44 20298.48 15691.52 22695.31 20898.45 17395.76 14497.48 16197.54 18589.53 25998.69 32194.43 17994.61 35299.13 148
tttt051793.31 27692.56 28395.57 24198.71 12587.86 28497.44 9187.17 36895.79 14397.47 16396.84 24164.12 36999.81 3696.20 8199.32 17999.02 172
ACMMPR97.95 5197.62 7898.94 1899.20 6797.56 2697.59 8098.83 10896.05 12497.46 16497.63 17996.77 7299.76 6295.61 11699.46 13299.49 55
RRT_test8_iter0592.46 28892.52 28492.29 33295.33 34277.43 36495.73 17998.55 16594.41 19597.46 16497.72 17357.44 37499.74 7996.92 6199.14 20299.69 20
APD-MVScopyleft97.00 11996.53 14998.41 5898.55 14696.31 6896.32 14798.77 12392.96 24797.44 16697.58 18495.84 10699.74 7991.96 23699.35 16799.19 135
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
HPM-MVScopyleft98.11 3897.83 5598.92 2299.42 3697.46 3398.57 1799.05 4595.43 15997.41 16797.50 19097.98 1599.79 4395.58 11999.57 9099.50 47
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
c3_l95.20 20795.32 19394.83 27396.19 31986.43 31091.83 32698.35 19293.47 22397.36 16897.26 21488.69 26699.28 25595.41 13499.36 16298.78 209
EPP-MVSNet96.84 13196.58 14397.65 12199.18 7093.78 17398.68 1296.34 29597.91 4797.30 16998.06 13288.46 26899.85 2693.85 20699.40 15599.32 103
DeepC-MVS_fast94.34 796.74 14096.51 15297.44 14597.69 25294.15 15896.02 16498.43 17693.17 23797.30 16997.38 20495.48 12799.28 25593.74 20999.34 17098.88 198
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
region2R97.92 5797.59 8198.92 2299.22 5997.55 2797.60 7998.84 10196.00 12997.22 17197.62 18096.87 6899.76 6295.48 12499.43 14599.46 66
ITE_SJBPF97.85 10698.64 13296.66 5598.51 16995.63 14997.22 17197.30 21295.52 12498.55 33590.97 25998.90 23398.34 253
h-mvs3396.29 16395.63 18698.26 7298.50 15396.11 7596.90 11997.09 27796.58 9997.21 17398.19 11484.14 29999.78 4795.89 9996.17 33798.89 194
hse-mvs295.77 18495.09 20097.79 10997.84 22495.51 9895.66 18595.43 31696.58 9997.21 17396.16 28084.14 29999.54 17895.89 9996.92 32098.32 254
9.1496.69 13898.53 14896.02 16498.98 6893.23 23197.18 17597.46 19396.47 8999.62 15492.99 22599.32 179
OMC-MVS96.48 15796.00 17297.91 10198.30 17196.01 8094.86 23798.60 15991.88 26297.18 17597.21 21796.11 10099.04 28790.49 28199.34 17098.69 220
our_test_394.20 25494.58 23093.07 31596.16 32181.20 35390.42 34796.84 28590.72 27797.14 17797.13 22090.47 24399.11 27994.04 20098.25 27798.91 190
MS-PatchMatch94.83 22294.91 21094.57 28496.81 30487.10 30194.23 26197.34 26888.74 29797.14 17797.11 22391.94 22598.23 35292.99 22597.92 28898.37 247
eth_miper_zixun_eth94.89 22094.93 20894.75 27695.99 32686.12 31391.35 33298.49 17093.40 22497.12 17997.25 21586.87 28599.35 23795.08 15498.82 24498.78 209
3Dnovator96.53 297.61 8597.64 7497.50 13497.74 24993.65 18098.49 2498.88 8796.86 9097.11 18098.55 7395.82 10999.73 8595.94 9699.42 14899.13 148
cl____94.73 22694.64 22395.01 26395.85 32987.00 30291.33 33398.08 22593.34 22797.10 18197.33 20984.01 30299.30 24995.14 14999.56 9398.71 219
DIV-MVS_self_test94.73 22694.64 22395.01 26395.86 32887.00 30291.33 33398.08 22593.34 22797.10 18197.34 20884.02 30199.31 24695.15 14899.55 9998.72 217
PMMVS293.66 26894.07 24892.45 32997.57 26180.67 35586.46 36496.00 30193.99 21197.10 18197.38 20489.90 25397.82 35888.76 30499.47 12998.86 201
mPP-MVS97.91 6097.53 8599.04 799.22 5997.87 1597.74 7298.78 12296.04 12697.10 18197.73 17196.53 8499.78 4795.16 14699.50 11999.46 66
BH-untuned94.69 23194.75 21994.52 28697.95 21587.53 29294.07 27197.01 28093.99 21197.10 18195.65 30092.65 20598.95 30087.60 32096.74 32797.09 314
test250689.86 32089.16 32591.97 33498.95 10076.83 36798.54 2061.07 38196.20 11697.07 18699.16 3055.19 38099.69 12196.43 7599.83 3199.38 90
miper_ehance_all_eth94.69 23194.70 22094.64 27895.77 33286.22 31291.32 33598.24 20191.67 26497.05 18796.65 25588.39 27099.22 26594.88 16098.34 27398.49 237
ETH3D-3000-0.196.89 13096.46 15498.16 8198.62 13795.69 8895.96 16998.98 6893.36 22697.04 18897.31 21194.93 14899.63 14692.60 22899.34 17099.17 138
miper_lstm_enhance94.81 22494.80 21794.85 27196.16 32186.45 30991.14 33998.20 20693.49 22297.03 18997.37 20684.97 29599.26 25895.28 13799.56 9398.83 203
UnsupCasMVSNet_bld94.72 23094.26 24196.08 22098.62 13790.54 24393.38 29698.05 23190.30 28197.02 19096.80 24689.54 25799.16 27288.44 30996.18 33698.56 231
ppachtmachnet_test94.49 24394.84 21393.46 30796.16 32182.10 34790.59 34597.48 26590.53 27997.01 19197.59 18291.01 23699.36 23493.97 20399.18 19998.94 181
D2MVS95.18 20895.17 19795.21 25697.76 24487.76 28994.15 26697.94 23489.77 28796.99 19297.68 17787.45 28099.14 27495.03 15799.81 3398.74 214
ab-mvs96.59 15196.59 14296.60 19298.64 13292.21 20998.35 3097.67 25194.45 19496.99 19298.79 5594.96 14799.49 19190.39 28299.07 21698.08 273
Anonymous2023120695.27 20595.06 20395.88 23098.72 12289.37 25695.70 18197.85 23988.00 30596.98 19497.62 18091.95 22499.34 23989.21 29899.53 10598.94 181
PVSNet_Blended_VisFu95.95 17895.80 18096.42 20499.28 4990.62 23995.31 20899.08 3988.40 30096.97 19598.17 11792.11 21999.78 4793.64 21399.21 19498.86 201
mvs_anonymous95.36 20196.07 17093.21 31396.29 31381.56 35194.60 24797.66 25393.30 22996.95 19698.91 4993.03 19699.38 22996.60 6697.30 31798.69 220
ZNCC-MVS97.92 5797.62 7898.83 2699.32 4797.24 4197.45 9098.84 10195.76 14496.93 19797.43 19697.26 4099.79 4396.06 8599.53 10599.45 71
3Dnovator+96.13 397.73 7697.59 8198.15 8498.11 20095.60 9498.04 5398.70 14198.13 3996.93 19798.45 8095.30 13599.62 15495.64 11498.96 22599.24 128
USDC94.56 23994.57 23294.55 28597.78 24286.43 31092.75 30898.65 15685.96 32196.91 19997.93 14990.82 23998.74 31690.71 27199.59 8598.47 238
CP-MVS97.92 5797.56 8498.99 1398.99 9897.82 1697.93 5898.96 7396.11 12196.89 20097.45 19496.85 6999.78 4795.19 14299.63 7299.38 90
OpenMVS_ROBcopyleft91.80 1493.64 26993.05 26895.42 25097.31 28691.21 22995.08 22496.68 29381.56 34996.88 20196.41 26790.44 24499.25 26085.39 33997.67 30295.80 346
testtj96.69 14696.13 16598.36 6298.46 16196.02 7996.44 13998.70 14194.26 20196.79 20297.13 22094.07 17399.75 6990.53 27798.80 24599.31 108
test_yl94.40 24494.00 25195.59 23996.95 29889.52 25394.75 24395.55 31396.18 11996.79 20296.14 28381.09 31399.18 26790.75 26797.77 29298.07 275
DCV-MVSNet94.40 24494.00 25195.59 23996.95 29889.52 25394.75 24395.55 31396.18 11996.79 20296.14 28381.09 31399.18 26790.75 26797.77 29298.07 275
Gipumacopyleft98.07 4198.31 2997.36 15299.76 596.28 7098.51 2399.10 3398.76 2396.79 20299.34 1796.61 7998.82 30896.38 7699.50 11996.98 318
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
alignmvs96.01 17695.52 19097.50 13497.77 24394.71 13596.07 16096.84 28597.48 6996.78 20694.28 33085.50 29199.40 22196.22 8098.73 25498.40 243
CL-MVSNet_self_test95.04 21494.79 21895.82 23297.51 26789.79 24991.14 33996.82 28793.05 24096.72 20796.40 26990.82 23999.16 27291.95 23798.66 25898.50 236
MSLP-MVS++96.42 16196.71 13795.57 24197.82 22790.56 24295.71 18098.84 10194.72 18596.71 20897.39 20294.91 14998.10 35695.28 13799.02 22198.05 282
canonicalmvs97.23 11397.21 10997.30 15597.65 25794.39 14797.84 6499.05 4597.42 7196.68 20993.85 33397.63 2699.33 24296.29 7998.47 27098.18 270
ZD-MVS98.43 16395.94 8198.56 16490.72 27796.66 21097.07 22695.02 14499.74 7991.08 25698.93 231
diffmvs96.04 17496.23 16195.46 24997.35 27888.03 28293.42 29399.08 3994.09 20996.66 21096.93 23693.85 17899.29 25396.01 9298.67 25699.06 166
patch_mono-296.59 15196.93 12595.55 24498.88 10787.12 30094.47 25299.30 1294.12 20796.65 21298.41 8394.98 14699.87 2195.81 10599.78 4199.66 22
MVP-Stereo95.69 18595.28 19496.92 17498.15 19493.03 19395.64 19098.20 20690.39 28096.63 21397.73 17191.63 23199.10 28191.84 24297.31 31698.63 225
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
Vis-MVSNet (Re-imp)95.11 21194.85 21295.87 23199.12 8389.17 25997.54 8894.92 31996.50 10396.58 21497.27 21383.64 30399.48 19488.42 31099.67 6598.97 177
MVS_111021_HR96.73 14296.54 14897.27 15698.35 16993.66 17993.42 29398.36 18894.74 18496.58 21496.76 24996.54 8398.99 29394.87 16199.27 18899.15 142
thisisatest053092.71 28591.76 29395.56 24398.42 16488.23 27596.03 16387.35 36794.04 21096.56 21695.47 30664.03 37099.77 5794.78 16799.11 21098.68 222
MVS_111021_LR96.82 13596.55 14697.62 12398.27 17695.34 11193.81 28398.33 19394.59 19196.56 21696.63 25696.61 7998.73 31794.80 16499.34 17098.78 209
DELS-MVS96.17 16996.23 16195.99 22297.55 26590.04 24592.38 31898.52 16794.13 20696.55 21897.06 22794.99 14599.58 16495.62 11599.28 18698.37 247
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
baseline193.14 28092.64 28194.62 28097.34 28287.20 29996.67 13493.02 33594.71 18696.51 21995.83 29681.64 30898.60 33190.00 28888.06 36798.07 275
Patchmatch-test93.60 27093.25 26694.63 27996.14 32487.47 29396.04 16294.50 32393.57 22096.47 22096.97 23376.50 33698.61 32990.67 27398.41 27297.81 296
HyFIR lowres test93.72 26592.65 28096.91 17698.93 10391.81 22291.23 33798.52 16782.69 34596.46 22196.52 26380.38 31799.90 1490.36 28398.79 24699.03 170
QAPM95.88 18195.57 18996.80 18297.90 21891.84 22198.18 4798.73 13188.41 29996.42 22298.13 11994.73 15099.75 6988.72 30598.94 22998.81 205
BH-RMVSNet94.56 23994.44 23894.91 26697.57 26187.44 29493.78 28496.26 29693.69 21996.41 22396.50 26492.10 22099.00 29185.96 33297.71 29898.31 256
CNVR-MVS96.92 12696.55 14698.03 9598.00 21095.54 9694.87 23698.17 21294.60 18996.38 22497.05 22895.67 11999.36 23495.12 15299.08 21499.19 135
thres600view792.03 29791.43 29593.82 29998.19 18584.61 33296.27 14890.39 35896.81 9196.37 22593.11 33673.44 35399.49 19180.32 35897.95 28797.36 310
thres100view90091.76 30191.26 30093.26 31098.21 18384.50 33396.39 14190.39 35896.87 8996.33 22693.08 34073.44 35399.42 21078.85 36297.74 29595.85 344
XVS97.96 4797.63 7698.94 1899.15 7497.66 2097.77 6798.83 10897.42 7196.32 22797.64 17896.49 8799.72 9095.66 11299.37 15999.45 71
X-MVStestdata92.86 28290.83 30798.94 1899.15 7497.66 2097.77 6798.83 10897.42 7196.32 22736.50 37496.49 8799.72 9095.66 11299.37 15999.45 71
MSDG95.33 20295.13 19895.94 22897.40 27691.85 22091.02 34298.37 18795.30 16396.31 22995.99 28894.51 16298.38 34589.59 29397.65 30497.60 304
CDS-MVSNet94.88 22194.12 24797.14 16397.64 25893.57 18193.96 27797.06 27990.05 28496.30 23096.55 25986.10 28799.47 19790.10 28699.31 18198.40 243
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
CVMVSNet92.33 29292.79 27590.95 34097.26 28775.84 37095.29 21092.33 34381.86 34796.27 23198.19 11481.44 31098.46 34094.23 19098.29 27698.55 233
FMVSNet593.39 27492.35 28596.50 19995.83 33090.81 23797.31 9798.27 19792.74 25096.27 23198.28 10162.23 37199.67 13390.86 26299.36 16299.03 170
TAPA-MVS93.32 1294.93 21894.23 24297.04 16998.18 18894.51 14395.22 21698.73 13181.22 35296.25 23395.95 29393.80 18098.98 29589.89 28998.87 23797.62 302
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
CHOSEN 1792x268894.10 25693.41 26396.18 21799.16 7190.04 24592.15 32098.68 14679.90 35796.22 23497.83 15987.92 27799.42 21089.18 29999.65 6899.08 162
MCST-MVS96.24 16595.80 18097.56 12698.75 11994.13 15994.66 24598.17 21290.17 28396.21 23596.10 28695.14 13999.43 20994.13 19498.85 24199.13 148
PHI-MVS96.96 12496.53 14998.25 7597.48 26896.50 6296.76 12698.85 9693.52 22196.19 23696.85 24095.94 10399.42 21093.79 20899.43 14598.83 203
HQP_MVS96.66 14996.33 15997.68 12098.70 12794.29 15196.50 13798.75 12796.36 10996.16 23796.77 24791.91 22899.46 20092.59 23099.20 19599.28 117
plane_prior394.51 14395.29 16496.16 237
miper_enhance_ethall93.14 28092.78 27794.20 29593.65 36185.29 32289.97 35197.85 23985.05 33496.15 23994.56 32285.74 28999.14 27493.74 20998.34 27398.17 271
MVS_Test96.27 16496.79 13594.73 27796.94 30086.63 30796.18 15598.33 19394.94 17896.07 24098.28 10195.25 13699.26 25897.21 5097.90 29098.30 258
CS-MVS-test97.69 7997.49 9098.31 6798.48 15696.61 5797.21 10499.53 898.10 4196.05 24195.33 30895.49 12599.86 2297.49 4099.74 5098.45 241
CS-MVS98.08 3998.01 4198.29 7198.46 16196.58 6098.53 2299.69 298.07 4296.04 24297.18 21896.88 6699.86 2297.48 4199.74 5098.43 242
PCF-MVS89.43 1892.12 29690.64 31096.57 19697.80 23293.48 18489.88 35598.45 17374.46 36996.04 24295.68 29990.71 24199.31 24673.73 36899.01 22396.91 322
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
ETH3D cwj APD-0.1696.23 16695.61 18898.09 8897.91 21695.65 9394.94 23398.74 12991.31 27196.02 24497.08 22594.05 17499.69 12191.51 24898.94 22998.93 185
CPTT-MVS96.69 14696.08 16998.49 5398.89 10696.64 5697.25 10098.77 12392.89 24896.01 24597.13 22092.23 21699.67 13392.24 23399.34 17099.17 138
DROMVSNet97.90 6197.94 4697.79 10998.66 13195.14 12298.31 3499.66 397.57 6395.95 24697.01 23296.99 5599.82 3397.66 3399.64 7098.39 245
PMVScopyleft89.60 1796.71 14596.97 12295.95 22699.51 2497.81 1797.42 9497.49 26397.93 4695.95 24698.58 6996.88 6696.91 36489.59 29399.36 16293.12 364
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
xiu_mvs_v1_base_debu95.62 18895.96 17594.60 28198.01 20688.42 27193.99 27498.21 20392.98 24395.91 24894.53 32396.39 9399.72 9095.43 13198.19 27895.64 348
xiu_mvs_v1_base95.62 18895.96 17594.60 28198.01 20688.42 27193.99 27498.21 20392.98 24395.91 24894.53 32396.39 9399.72 9095.43 13198.19 27895.64 348
xiu_mvs_v1_base_debi95.62 18895.96 17594.60 28198.01 20688.42 27193.99 27498.21 20392.98 24395.91 24894.53 32396.39 9399.72 9095.43 13198.19 27895.64 348
tfpn200view991.55 30391.00 30293.21 31398.02 20484.35 33595.70 18190.79 35596.26 11395.90 25192.13 35373.62 35099.42 21078.85 36297.74 29595.85 344
thres40091.68 30291.00 30293.71 30298.02 20484.35 33595.70 18190.79 35596.26 11395.90 25192.13 35373.62 35099.42 21078.85 36297.74 29597.36 310
cl2293.25 27892.84 27494.46 28894.30 35386.00 31491.09 34196.64 29490.74 27695.79 25396.31 27478.24 32598.77 31394.15 19398.34 27398.62 226
API-MVS95.09 21395.01 20595.31 25396.61 30694.02 16296.83 12297.18 27395.60 15195.79 25394.33 32894.54 16198.37 34785.70 33498.52 26793.52 361
DP-MVS Recon95.55 19195.13 19896.80 18298.51 15093.99 16494.60 24798.69 14490.20 28295.78 25596.21 27992.73 20298.98 29590.58 27698.86 23997.42 309
CLD-MVS95.47 19695.07 20196.69 18998.27 17692.53 20291.36 33198.67 14991.22 27395.78 25594.12 33195.65 12098.98 29590.81 26499.72 5598.57 230
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
旧先验293.35 29777.95 36595.77 25798.67 32590.74 270
pmmvs494.82 22394.19 24596.70 18897.42 27592.75 20092.09 32396.76 28986.80 31695.73 25897.22 21689.28 26398.89 30393.28 21999.14 20298.46 240
LF4IMVS96.07 17295.63 18697.36 15298.19 18595.55 9595.44 19598.82 11692.29 25695.70 25996.55 25992.63 20698.69 32191.75 24599.33 17797.85 292
testdata95.70 23898.16 19290.58 24097.72 24880.38 35595.62 26097.02 23092.06 22298.98 29589.06 30298.52 26797.54 305
MP-MVScopyleft97.64 8297.18 11099.00 1299.32 4797.77 1897.49 8998.73 13196.27 11295.59 26197.75 16896.30 9799.78 4793.70 21299.48 12799.45 71
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
ETV-MVS96.13 17195.90 17896.82 18197.76 24493.89 16695.40 20098.95 7595.87 13895.58 26291.00 36496.36 9699.72 9093.36 21698.83 24396.85 325
thres20091.00 30990.42 31392.77 32397.47 27283.98 33994.01 27391.18 35395.12 17195.44 26391.21 36273.93 34699.31 24677.76 36597.63 30595.01 354
CDPH-MVS95.45 19894.65 22297.84 10798.28 17494.96 12793.73 28598.33 19385.03 33595.44 26396.60 25795.31 13499.44 20790.01 28799.13 20699.11 157
NCCC96.52 15595.99 17398.10 8797.81 22895.68 9095.00 23198.20 20695.39 16095.40 26596.36 27293.81 17999.45 20493.55 21598.42 27199.17 138
jason94.39 24694.04 25095.41 25298.29 17287.85 28692.74 31096.75 29085.38 33295.29 26696.15 28188.21 27299.65 14194.24 18999.34 17098.74 214
jason: jason.
new_pmnet92.34 29191.69 29494.32 29296.23 31789.16 26092.27 31992.88 33784.39 34295.29 26696.35 27385.66 29096.74 36884.53 34697.56 30697.05 316
pmmvs594.63 23694.34 24095.50 24697.63 25988.34 27494.02 27297.13 27587.15 31295.22 26897.15 21987.50 27999.27 25793.99 20199.26 18998.88 198
Effi-MVS+-dtu96.81 13696.09 16898.99 1396.90 30298.69 296.42 14098.09 22395.86 13995.15 26995.54 30494.26 16899.81 3694.06 19698.51 26998.47 238
KD-MVS_2432*160088.93 32687.74 33192.49 32688.04 37781.99 34889.63 35795.62 30991.35 26995.06 27093.11 33656.58 37698.63 32785.19 34095.07 34796.85 325
miper_refine_blended88.93 32687.74 33192.49 32688.04 37781.99 34889.63 35795.62 30991.35 26995.06 27093.11 33656.58 37698.63 32785.19 34095.07 34796.85 325
HPM-MVS++copyleft96.99 12096.38 15698.81 2998.64 13297.59 2495.97 16898.20 20695.51 15595.06 27096.53 26194.10 17299.70 11394.29 18799.15 20199.13 148
MIMVSNet93.42 27392.86 27295.10 26098.17 19088.19 27698.13 4993.69 32792.07 25795.04 27398.21 11380.95 31599.03 29081.42 35698.06 28498.07 275
TR-MVS92.54 28792.20 28793.57 30596.49 30986.66 30693.51 29194.73 32089.96 28594.95 27493.87 33290.24 25098.61 32981.18 35794.88 34995.45 352
PatchMatch-RL94.61 23793.81 25797.02 17198.19 18595.72 8693.66 28697.23 27088.17 30394.94 27595.62 30291.43 23298.57 33287.36 32597.68 30196.76 331
MG-MVS94.08 25894.00 25194.32 29297.09 29485.89 31593.19 30295.96 30392.52 25194.93 27697.51 18989.54 25798.77 31387.52 32397.71 29898.31 256
新几何197.25 15998.29 17294.70 13897.73 24777.98 36394.83 27796.67 25492.08 22199.45 20488.17 31498.65 26097.61 303
Fast-Effi-MVS+-dtu96.44 15996.12 16697.39 15097.18 29194.39 14795.46 19498.73 13196.03 12894.72 27894.92 31796.28 9999.69 12193.81 20797.98 28698.09 272
test0.0.03 190.11 31489.21 32192.83 32293.89 35986.87 30591.74 32788.74 36592.02 25894.71 27991.14 36373.92 34794.48 37183.75 35292.94 35797.16 313
ETH3 D test640094.77 22593.87 25697.47 13998.12 19993.73 17494.56 24998.70 14185.45 33094.70 28095.93 29591.77 23099.63 14686.45 33099.14 20299.05 168
test22298.17 19093.24 18992.74 31097.61 26175.17 36894.65 28196.69 25390.96 23898.66 25897.66 301
SCA93.38 27593.52 26192.96 32096.24 31581.40 35293.24 30094.00 32691.58 26794.57 28296.97 23387.94 27399.42 21089.47 29597.66 30398.06 279
CNLPA95.04 21494.47 23596.75 18597.81 22895.25 11594.12 27097.89 23794.41 19594.57 28295.69 29890.30 24898.35 34886.72 32998.76 24996.64 334
112194.26 24893.26 26597.27 15698.26 17894.73 13395.86 17497.71 24977.96 36494.53 28496.71 25191.93 22699.40 22187.71 31698.64 26197.69 300
PVSNet_BlendedMVS95.02 21794.93 20895.27 25497.79 23887.40 29594.14 26898.68 14688.94 29494.51 28598.01 13893.04 19499.30 24989.77 29199.49 12399.11 157
PVSNet_Blended93.96 26093.65 25994.91 26697.79 23887.40 29591.43 33098.68 14684.50 34094.51 28594.48 32693.04 19499.30 24989.77 29198.61 26398.02 285
MVSFormer96.14 17096.36 15795.49 24797.68 25387.81 28798.67 1399.02 5496.50 10394.48 28796.15 28186.90 28399.92 598.73 799.13 20698.74 214
lupinMVS93.77 26393.28 26495.24 25597.68 25387.81 28792.12 32196.05 29984.52 33994.48 28795.06 31386.90 28399.63 14693.62 21499.13 20698.27 262
OpenMVScopyleft94.22 895.48 19595.20 19596.32 20997.16 29291.96 21897.74 7298.84 10187.26 30994.36 28998.01 13893.95 17699.67 13390.70 27298.75 25097.35 312
PatchT93.75 26493.57 26094.29 29495.05 34587.32 29796.05 16192.98 33697.54 6794.25 29098.72 6075.79 34199.24 26195.92 9795.81 33996.32 340
BH-w/o92.14 29591.94 28992.73 32497.13 29385.30 32192.46 31595.64 30889.33 29094.21 29192.74 34689.60 25598.24 35181.68 35594.66 35194.66 356
xiu_mvs_v2_base94.22 25094.63 22592.99 31997.32 28584.84 33092.12 32197.84 24191.96 26094.17 29293.43 33496.07 10199.71 10491.27 25297.48 31094.42 357
PS-MVSNAJ94.10 25694.47 23593.00 31897.35 27884.88 32991.86 32597.84 24191.96 26094.17 29292.50 35095.82 10999.71 10491.27 25297.48 31094.40 358
CR-MVSNet93.29 27792.79 27594.78 27595.44 33988.15 27896.18 15597.20 27184.94 33794.10 29498.57 7077.67 32899.39 22695.17 14495.81 33996.81 329
RPMNet94.68 23394.60 22794.90 26895.44 33988.15 27896.18 15598.86 9297.43 7094.10 29498.49 7779.40 31999.76 6295.69 10895.81 33996.81 329
WTY-MVS93.55 27193.00 27095.19 25797.81 22887.86 28493.89 27996.00 30189.02 29294.07 29695.44 30786.27 28699.33 24287.69 31896.82 32498.39 245
GA-MVS92.83 28392.15 28894.87 27096.97 29787.27 29890.03 35096.12 29891.83 26394.05 29794.57 32176.01 34098.97 29992.46 23297.34 31598.36 252
test_prior395.91 17995.39 19297.46 14297.79 23894.26 15593.33 29898.42 17994.21 20394.02 29896.25 27693.64 18399.34 23991.90 23898.96 22598.79 207
test_prior293.33 29894.21 20394.02 29896.25 27693.64 18391.90 23898.96 225
MDTV_nov1_ep13_2view57.28 38094.89 23580.59 35494.02 29878.66 32485.50 33897.82 294
AdaColmapbinary95.11 21194.62 22696.58 19497.33 28494.45 14694.92 23498.08 22593.15 23893.98 30195.53 30594.34 16699.10 28185.69 33598.61 26396.20 342
pmmvs390.00 31688.90 32693.32 30894.20 35785.34 32091.25 33692.56 34278.59 36193.82 30295.17 31067.36 36798.69 32189.08 30198.03 28595.92 343
TEST997.84 22495.23 11693.62 28798.39 18486.81 31593.78 30395.99 28894.68 15499.52 184
train_agg95.46 19794.66 22197.88 10497.84 22495.23 11693.62 28798.39 18487.04 31393.78 30395.99 28894.58 15999.52 18491.76 24498.90 23398.89 194
EIA-MVS96.04 17495.77 18296.85 17997.80 23292.98 19496.12 15899.16 2294.65 18793.77 30591.69 35895.68 11899.67 13394.18 19198.85 24197.91 290
sss94.22 25093.72 25895.74 23597.71 25189.95 24793.84 28096.98 28188.38 30193.75 30695.74 29787.94 27398.89 30391.02 25898.10 28298.37 247
test_897.81 22895.07 12593.54 29098.38 18687.04 31393.71 30795.96 29294.58 15999.52 184
E-PMN89.52 32389.78 31788.73 34993.14 36677.61 36383.26 36892.02 34494.82 18393.71 30793.11 33675.31 34296.81 36585.81 33396.81 32591.77 367
thisisatest051590.43 31289.18 32494.17 29797.07 29585.44 31989.75 35687.58 36688.28 30293.69 30991.72 35765.27 36899.58 16490.59 27598.67 25697.50 307
mvs-test196.20 16795.50 19198.32 6596.90 30298.16 595.07 22598.09 22395.86 13993.63 31094.32 32994.26 16899.71 10494.06 19697.27 31897.07 315
UGNet96.81 13696.56 14597.58 12596.64 30593.84 17097.75 7097.12 27696.47 10693.62 31198.88 5193.22 19199.53 18095.61 11699.69 6299.36 98
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
PatchmatchNetpermissive91.98 29891.87 29092.30 33194.60 35079.71 35795.12 21993.59 33189.52 28893.61 31297.02 23077.94 32699.18 26790.84 26394.57 35498.01 286
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
CMPMVSbinary73.10 2392.74 28491.39 29696.77 18493.57 36394.67 13994.21 26397.67 25180.36 35693.61 31296.60 25782.85 30597.35 36284.86 34498.78 24798.29 261
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
test1297.46 14297.61 26094.07 16097.78 24593.57 31493.31 18999.42 21098.78 24798.89 194
tpm91.08 30890.85 30691.75 33595.33 34278.09 36095.03 23091.27 35288.75 29693.53 31597.40 19871.24 35899.30 24991.25 25493.87 35597.87 291
agg_prior195.39 20094.60 22797.75 11297.80 23294.96 12793.39 29598.36 18887.20 31193.49 31695.97 29194.65 15699.53 18091.69 24698.86 23998.77 212
agg_prior97.80 23294.96 12798.36 18893.49 31699.53 180
原ACMM196.58 19498.16 19292.12 21398.15 21785.90 32393.49 31696.43 26692.47 21399.38 22987.66 31998.62 26298.23 265
MDTV_nov1_ep1391.28 29894.31 35273.51 37494.80 24093.16 33486.75 31793.45 31997.40 19876.37 33798.55 33588.85 30396.43 332
114514_t93.96 26093.22 26796.19 21699.06 9090.97 23395.99 16698.94 7673.88 37093.43 32096.93 23692.38 21599.37 23289.09 30099.28 18698.25 264
Fast-Effi-MVS+95.49 19395.07 20196.75 18597.67 25692.82 19794.22 26298.60 15991.61 26593.42 32192.90 34396.73 7499.70 11392.60 22897.89 29197.74 297
PAPM_NR94.61 23794.17 24695.96 22498.36 16891.23 22895.93 17297.95 23392.98 24393.42 32194.43 32790.53 24298.38 34587.60 32096.29 33598.27 262
Effi-MVS+96.19 16896.01 17196.71 18797.43 27492.19 21296.12 15899.10 3395.45 15793.33 32394.71 32097.23 4399.56 17193.21 22297.54 30798.37 247
F-COLMAP95.30 20494.38 23998.05 9498.64 13296.04 7795.61 19198.66 15189.00 29393.22 32496.40 26992.90 19899.35 23787.45 32497.53 30898.77 212
EPMVS89.26 32488.55 32891.39 33792.36 37279.11 35895.65 18879.86 37588.60 29893.12 32596.53 26170.73 36298.10 35690.75 26789.32 36696.98 318
DPM-MVS93.68 26792.77 27896.42 20497.91 21692.54 20191.17 33897.47 26684.99 33693.08 32694.74 31989.90 25399.00 29187.54 32298.09 28397.72 298
1112_ss94.12 25593.42 26296.23 21398.59 14290.85 23494.24 26098.85 9685.49 32792.97 32794.94 31586.01 28899.64 14491.78 24397.92 28898.20 268
HQP4-MVS92.87 32899.23 26399.06 166
HQP-NCC97.85 22094.26 25693.18 23492.86 329
ACMP_Plane97.85 22094.26 25693.18 23492.86 329
HQP-MVS95.17 21094.58 23096.92 17497.85 22092.47 20394.26 25698.43 17693.18 23492.86 32995.08 31190.33 24599.23 26390.51 27998.74 25199.05 168
ADS-MVSNet291.47 30490.51 31294.36 29195.51 33785.63 31695.05 22895.70 30783.46 34392.69 33296.84 24179.15 32299.41 21985.66 33690.52 36298.04 283
ADS-MVSNet90.95 31090.26 31493.04 31695.51 33782.37 34695.05 22893.41 33283.46 34392.69 33296.84 24179.15 32298.70 32085.66 33690.52 36298.04 283
Test_1112_low_res93.53 27292.86 27295.54 24598.60 14088.86 26592.75 30898.69 14482.66 34692.65 33496.92 23884.75 29699.56 17190.94 26097.76 29498.19 269
AUN-MVS93.95 26292.69 27997.74 11397.80 23295.38 10695.57 19295.46 31591.26 27292.64 33596.10 28674.67 34499.55 17593.72 21196.97 31998.30 258
EMVS89.06 32589.22 32088.61 35093.00 36877.34 36582.91 36990.92 35494.64 18892.63 33691.81 35676.30 33897.02 36383.83 35096.90 32291.48 368
CANet95.86 18295.65 18596.49 20096.41 31190.82 23594.36 25498.41 18194.94 17892.62 33796.73 25092.68 20399.71 10495.12 15299.60 8398.94 181
DSMNet-mixed92.19 29491.83 29193.25 31196.18 32083.68 34196.27 14893.68 32976.97 36792.54 33899.18 2789.20 26598.55 33583.88 34998.60 26597.51 306
PVSNet86.72 1991.10 30790.97 30491.49 33697.56 26378.04 36187.17 36394.60 32284.65 33892.34 33992.20 35287.37 28198.47 33985.17 34297.69 30097.96 287
tpmrst90.31 31390.61 31189.41 34794.06 35872.37 37695.06 22793.69 32788.01 30492.32 34096.86 23977.45 33098.82 30891.04 25787.01 36997.04 317
cascas91.89 29991.35 29793.51 30694.27 35485.60 31788.86 36098.61 15879.32 35992.16 34191.44 36089.22 26498.12 35590.80 26597.47 31296.82 328
MAR-MVS94.21 25293.03 26997.76 11196.94 30097.44 3596.97 11897.15 27487.89 30792.00 34292.73 34792.14 21899.12 27683.92 34897.51 30996.73 332
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
tpmvs90.79 31190.87 30590.57 34392.75 37176.30 36895.79 17893.64 33091.04 27591.91 34396.26 27577.19 33498.86 30789.38 29789.85 36596.56 337
PMMVS92.39 28991.08 30196.30 21193.12 36792.81 19890.58 34695.96 30379.17 36091.85 34492.27 35190.29 24998.66 32689.85 29096.68 32997.43 308
PLCcopyleft91.02 1694.05 25992.90 27197.51 13198.00 21095.12 12494.25 25998.25 20086.17 31991.48 34595.25 30991.01 23699.19 26685.02 34396.69 32898.22 266
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
dp88.08 33288.05 33088.16 35392.85 36968.81 37894.17 26492.88 33785.47 32891.38 34696.14 28368.87 36598.81 31086.88 32783.80 37296.87 323
PAPR92.22 29391.27 29995.07 26195.73 33488.81 26691.97 32497.87 23885.80 32490.91 34792.73 34791.16 23498.33 34979.48 35995.76 34398.08 273
131492.38 29092.30 28692.64 32595.42 34185.15 32595.86 17496.97 28285.40 33190.62 34893.06 34191.12 23597.80 35986.74 32895.49 34694.97 355
MVS90.02 31589.20 32292.47 32894.71 34886.90 30495.86 17496.74 29164.72 37290.62 34892.77 34592.54 21098.39 34479.30 36095.56 34592.12 365
CostFormer89.75 32189.25 31991.26 33994.69 34978.00 36295.32 20791.98 34581.50 35090.55 35096.96 23571.06 36098.89 30388.59 30892.63 35996.87 323
HY-MVS91.43 1592.58 28691.81 29294.90 26896.49 30988.87 26497.31 9794.62 32185.92 32290.50 35196.84 24185.05 29399.40 22183.77 35195.78 34296.43 339
FPMVS89.92 31988.63 32793.82 29998.37 16796.94 4791.58 32893.34 33388.00 30590.32 35297.10 22470.87 36191.13 37371.91 37196.16 33893.39 363
JIA-IIPM91.79 30090.69 30995.11 25993.80 36090.98 23294.16 26591.78 34796.38 10790.30 35399.30 1872.02 35798.90 30188.28 31290.17 36495.45 352
CANet_DTU94.65 23594.21 24495.96 22495.90 32789.68 25093.92 27897.83 24393.19 23390.12 35495.64 30188.52 26799.57 17093.27 22099.47 12998.62 226
test-LLR89.97 31889.90 31690.16 34494.24 35574.98 37189.89 35289.06 36392.02 25889.97 35590.77 36573.92 34798.57 33291.88 24097.36 31396.92 320
test-mter87.92 33487.17 33590.16 34494.24 35574.98 37189.89 35289.06 36386.44 31889.97 35590.77 36554.96 38198.57 33291.88 24097.36 31396.92 320
tpm288.47 32987.69 33390.79 34194.98 34677.34 36595.09 22291.83 34677.51 36689.40 35796.41 26767.83 36698.73 31783.58 35392.60 36096.29 341
tpm cat188.01 33387.33 33490.05 34694.48 35176.28 36994.47 25294.35 32573.84 37189.26 35895.61 30373.64 34998.30 35084.13 34786.20 37095.57 351
MVS_030495.50 19295.05 20496.84 18096.28 31493.12 19197.00 11696.16 29795.03 17589.22 35997.70 17490.16 25199.48 19494.51 17799.34 17097.93 289
TESTMET0.1,187.20 33786.57 33989.07 34893.62 36272.84 37589.89 35287.01 36985.46 32989.12 36090.20 36756.00 37997.72 36090.91 26196.92 32096.64 334
MVS-HIRNet88.40 33090.20 31582.99 35597.01 29660.04 37993.11 30385.61 37184.45 34188.72 36199.09 3684.72 29798.23 35282.52 35496.59 33190.69 370
IB-MVS85.98 2088.63 32886.95 33793.68 30395.12 34484.82 33190.85 34390.17 36287.55 30888.48 36291.34 36158.01 37399.59 16287.24 32693.80 35696.63 336
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
DWT-MVSNet_test87.92 33486.77 33891.39 33793.18 36478.62 35995.10 22091.42 34985.58 32688.00 36388.73 36960.60 37298.90 30190.60 27487.70 36896.65 333
PVSNet_081.89 2184.49 33983.21 34288.34 35195.76 33374.97 37383.49 36792.70 34178.47 36287.94 36486.90 37183.38 30496.63 36973.44 36966.86 37593.40 362
EPNet93.72 26592.62 28297.03 17087.61 37992.25 20796.27 14891.28 35196.74 9387.65 36597.39 20285.00 29499.64 14492.14 23499.48 12799.20 134
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CHOSEN 280x42089.98 31789.19 32392.37 33095.60 33681.13 35486.22 36597.09 27781.44 35187.44 36693.15 33573.99 34599.47 19788.69 30699.07 21696.52 338
baseline289.65 32288.44 32993.25 31195.62 33582.71 34393.82 28185.94 37088.89 29587.35 36792.54 34971.23 35999.33 24286.01 33194.60 35397.72 298
gg-mvs-nofinetune88.28 33186.96 33692.23 33392.84 37084.44 33498.19 4674.60 37799.08 1087.01 36899.47 856.93 37598.23 35278.91 36195.61 34494.01 359
ET-MVSNet_ETH3D91.12 30689.67 31895.47 24896.41 31189.15 26191.54 32990.23 36189.07 29186.78 36992.84 34469.39 36499.44 20794.16 19296.61 33097.82 294
PAPM87.64 33685.84 34193.04 31696.54 30784.99 32888.42 36295.57 31279.52 35883.82 37093.05 34280.57 31698.41 34262.29 37492.79 35895.71 347
GG-mvs-BLEND90.60 34291.00 37484.21 33798.23 4072.63 38082.76 37184.11 37256.14 37896.79 36672.20 37092.09 36190.78 369
MVEpermissive73.61 2286.48 33885.92 34088.18 35296.23 31785.28 32381.78 37075.79 37686.01 32082.53 37291.88 35592.74 20187.47 37571.42 37294.86 35091.78 366
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
EPNet_dtu91.39 30590.75 30893.31 30990.48 37682.61 34494.80 24092.88 33793.39 22581.74 37394.90 31881.36 31199.11 27988.28 31298.87 23798.21 267
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
DeepMVS_CXcopyleft77.17 35690.94 37585.28 32374.08 37952.51 37380.87 37488.03 37075.25 34370.63 37659.23 37584.94 37175.62 371
tmp_tt57.23 34262.50 34541.44 35834.77 38149.21 38183.93 36660.22 38215.31 37471.11 37579.37 37370.09 36344.86 37764.76 37382.93 37330.25 373
test_method66.88 34166.13 34469.11 35762.68 38025.73 38249.76 37196.04 30014.32 37564.27 37691.69 35873.45 35288.05 37476.06 36766.94 37493.54 360
EGC-MVSNET83.08 34077.93 34398.53 5199.57 1697.55 2798.33 3398.57 1634.71 37610.38 37798.90 5095.60 12299.50 18995.69 10899.61 7998.55 233
testmvs12.33 34515.23 3483.64 3605.77 3832.23 38488.99 3593.62 3832.30 3785.29 37813.09 3754.52 3831.95 3785.16 3778.32 3776.75 375
test12312.59 34415.49 3473.87 3596.07 3822.55 38390.75 3442.59 3842.52 3775.20 37913.02 3764.96 3821.85 3795.20 3769.09 3767.23 374
test_blank0.00 3480.00 3510.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.00 3790.00 3840.00 3800.00 3780.00 3780.00 376
uanet_test0.00 3480.00 3510.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.00 3790.00 3840.00 3800.00 3780.00 3780.00 376
DCPMVS0.00 3480.00 3510.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.00 3790.00 3840.00 3800.00 3780.00 3780.00 376
cdsmvs_eth3d_5k24.22 34332.30 3460.00 3610.00 3840.00 3850.00 37298.10 2220.00 3790.00 38095.06 31397.54 290.00 3800.00 3780.00 3780.00 376
pcd_1.5k_mvsjas7.98 34610.65 3490.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.00 37995.82 1090.00 3800.00 3780.00 3780.00 376
sosnet-low-res0.00 3480.00 3510.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.00 3790.00 3840.00 3800.00 3780.00 3780.00 376
sosnet0.00 3480.00 3510.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.00 3790.00 3840.00 3800.00 3780.00 3780.00 376
uncertanet0.00 3480.00 3510.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.00 3790.00 3840.00 3800.00 3780.00 3780.00 376
Regformer0.00 3480.00 3510.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.00 3790.00 3840.00 3800.00 3780.00 3780.00 376
ab-mvs-re7.91 34710.55 3500.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 38094.94 3150.00 3840.00 3800.00 3780.00 3780.00 376
uanet0.00 3480.00 3510.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.00 3790.00 3840.00 3800.00 3780.00 3780.00 376
MSC_two_6792asdad98.22 7797.75 24695.34 11198.16 21599.75 6995.87 10199.51 11599.57 34
No_MVS98.22 7797.75 24695.34 11198.16 21599.75 6995.87 10199.51 11599.57 34
eth-test20.00 384
eth-test0.00 384
OPU-MVS97.64 12298.01 20695.27 11496.79 12497.35 20796.97 5698.51 33891.21 25599.25 19099.14 145
save fliter98.48 15694.71 13594.53 25098.41 18195.02 176
test_0728_SECOND98.25 7599.23 5695.49 10296.74 12798.89 8199.75 6995.48 12499.52 11099.53 43
GSMVS98.06 279
sam_mvs177.80 32798.06 279
sam_mvs77.38 331
MTGPAbinary98.73 131
test_post194.98 23210.37 37876.21 33999.04 28789.47 295
test_post10.87 37776.83 33599.07 284
patchmatchnet-post96.84 24177.36 33299.42 210
MTMP96.55 13574.60 377
gm-plane-assit91.79 37371.40 37781.67 34890.11 36898.99 29384.86 344
test9_res91.29 25198.89 23699.00 173
agg_prior290.34 28498.90 23399.10 161
test_prior495.38 10693.61 289
test_prior97.46 14297.79 23894.26 15598.42 17999.34 23998.79 207
新几何293.43 292
旧先验197.80 23293.87 16797.75 24697.04 22993.57 18598.68 25598.72 217
无先验93.20 30197.91 23580.78 35399.40 22187.71 31697.94 288
原ACMM292.82 306
testdata299.46 20087.84 315
segment_acmp95.34 132
testdata192.77 30793.78 216
plane_prior798.70 12794.67 139
plane_prior698.38 16694.37 14991.91 228
plane_prior598.75 12799.46 20092.59 23099.20 19599.28 117
plane_prior496.77 247
plane_prior296.50 13796.36 109
plane_prior198.49 154
plane_prior94.29 15195.42 19794.31 20098.93 231
n20.00 385
nn0.00 385
door-mid98.17 212
test1198.08 225
door97.81 244
HQP5-MVS92.47 203
BP-MVS90.51 279
HQP3-MVS98.43 17698.74 251
HQP2-MVS90.33 245
NP-MVS98.14 19593.72 17595.08 311
ACMMP++_ref99.52 110
ACMMP++99.55 99
Test By Simon94.51 162