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 7899.68 994.82 12998.10 4999.21 1496.91 8599.75 299.45 995.82 10899.92 498.80 499.96 499.89 1
UniMVSNet_ETH3D99.12 399.28 398.65 4399.77 396.34 6599.18 599.20 1699.67 299.73 399.65 499.15 399.86 2097.22 4699.92 1499.77 8
mvs_tets98.90 598.94 698.75 3399.69 896.48 6198.54 2099.22 1396.23 11299.71 499.48 798.77 699.93 298.89 399.95 599.84 5
wuyk23d93.25 27695.20 19387.40 35296.07 32395.38 10497.04 11294.97 31695.33 15999.70 598.11 12198.14 1391.94 37077.76 36399.68 6074.89 370
Anonymous2023121198.55 1798.76 1397.94 9798.79 11294.37 14798.84 1099.15 2499.37 399.67 699.43 1195.61 12099.72 8698.12 1699.86 2599.73 15
jajsoiax98.77 998.79 1298.74 3599.66 1096.48 6198.45 2699.12 2895.83 13999.67 699.37 1298.25 1099.92 498.77 599.94 899.82 6
ANet_high98.31 2898.94 696.41 20599.33 4589.64 25197.92 5999.56 599.27 699.66 899.50 697.67 2599.83 2897.55 3799.98 299.77 8
pmmvs699.07 499.24 498.56 4999.81 296.38 6398.87 999.30 1199.01 1699.63 999.66 399.27 299.68 12597.75 3099.89 2299.62 25
LTVRE_ROB96.88 199.18 299.34 298.72 3899.71 796.99 4699.69 299.57 499.02 1599.62 1099.36 1498.53 799.52 18298.58 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 6499.17 699.05 4398.05 4199.61 1199.52 593.72 18099.88 1898.72 999.88 2399.65 23
TransMVSNet (Re)98.38 2598.67 1797.51 12999.51 2493.39 18498.20 4498.87 8798.23 3699.48 1299.27 1998.47 899.55 17396.52 6899.53 10199.60 26
LCM-MVSNet-Re97.33 10497.33 9697.32 15298.13 19493.79 17096.99 11599.65 396.74 9099.47 1398.93 4796.91 6399.84 2590.11 28399.06 21798.32 250
SixPastTwentyTwo97.49 9297.57 8197.26 15699.56 1792.33 20498.28 3696.97 28098.30 3499.45 1499.35 1688.43 26799.89 1698.01 2099.76 4299.54 38
v7n98.73 1198.99 597.95 9699.64 1194.20 15598.67 1399.14 2699.08 1099.42 1599.23 2196.53 8399.91 1299.27 299.93 1099.73 15
NR-MVSNet97.96 4697.86 5098.26 7098.73 11895.54 9498.14 4798.73 12997.79 4699.42 1597.83 15794.40 16399.78 4395.91 9799.76 4299.46 64
MIMVSNet198.51 2098.45 2698.67 4199.72 696.71 5298.76 1198.89 7998.49 2899.38 1799.14 3395.44 12999.84 2596.47 7199.80 3699.47 62
ACMH93.61 998.44 2298.76 1397.51 12999.43 3493.54 18098.23 3999.05 4397.40 7399.37 1899.08 3798.79 599.47 19597.74 3199.71 5499.50 45
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 1895.62 14799.35 1999.37 1297.38 3399.90 1398.59 1199.91 1799.77 8
test_djsdf98.73 1198.74 1698.69 4099.63 1296.30 6798.67 1399.02 5296.50 10099.32 2099.44 1097.43 3199.92 498.73 799.95 599.86 2
test_part196.77 13696.53 14697.47 13798.04 19892.92 19597.93 5798.85 9498.83 2199.30 2199.07 3879.25 31899.79 3997.59 3599.93 1099.69 20
PEN-MVS98.75 1098.85 1098.44 5699.58 1595.67 8998.45 2699.15 2499.33 599.30 2199.00 4197.27 3899.92 497.64 3499.92 1499.75 13
DTE-MVSNet98.79 898.86 898.59 4799.55 1996.12 7298.48 2599.10 3199.36 499.29 2399.06 3997.27 3899.93 297.71 3299.91 1799.70 18
pm-mvs198.47 2198.67 1797.86 10399.52 2394.58 13998.28 3699.00 6097.57 6199.27 2499.22 2298.32 999.50 18797.09 5499.75 4699.50 45
ACMH+93.58 1098.23 3298.31 2997.98 9599.39 3995.22 11797.55 8199.20 1698.21 3799.25 2598.51 7698.21 1199.40 21994.79 16399.72 5199.32 101
Anonymous2024052997.96 4698.04 3997.71 11398.69 12794.28 15297.86 6298.31 19498.79 2299.23 2698.86 5395.76 11599.61 15895.49 11899.36 15999.23 127
PS-CasMVS98.73 1198.85 1098.39 6099.55 1995.47 10198.49 2399.13 2799.22 899.22 2798.96 4597.35 3499.92 497.79 2899.93 1099.79 7
SD-MVS97.37 10197.70 6296.35 20698.14 19195.13 12196.54 13498.92 7695.94 13099.19 2898.08 12397.74 2295.06 36895.24 13899.54 9898.87 198
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 1999.05 1399.17 2998.79 5595.47 12799.89 1697.95 2199.91 1799.75 13
tfpnnormal97.72 7697.97 4196.94 17199.26 5092.23 20797.83 6498.45 17198.25 3599.13 3098.66 6596.65 7599.69 11793.92 20299.62 6998.91 188
SED-MVS97.94 5297.90 4598.07 8799.22 5995.35 10796.79 12298.83 10696.11 11899.08 3198.24 10597.87 2099.72 8695.44 12599.51 11199.14 143
test_241102_ONE99.22 5995.35 10798.83 10696.04 12399.08 3198.13 11797.87 2099.33 240
VPA-MVSNet98.27 2998.46 2497.70 11599.06 8993.80 16997.76 6899.00 6098.40 3099.07 3398.98 4396.89 6499.75 6597.19 5199.79 3899.55 37
nrg03098.54 1898.62 2198.32 6599.22 5995.66 9097.90 6099.08 3798.31 3399.02 3498.74 5997.68 2499.61 15897.77 2999.85 2899.70 18
CP-MVSNet98.42 2398.46 2498.30 6899.46 3095.22 11798.27 3898.84 9999.05 1399.01 3598.65 6795.37 13099.90 1397.57 3699.91 1799.77 8
FMVSNet197.95 5098.08 3597.56 12499.14 8293.67 17498.23 3998.66 14997.41 7299.00 3699.19 2495.47 12799.73 8195.83 10299.76 4299.30 107
TDRefinement98.90 598.86 899.02 999.54 2198.06 899.34 499.44 898.85 2099.00 3699.20 2397.42 3299.59 16097.21 4899.76 4299.40 84
K. test v396.44 15696.28 15796.95 17099.41 3791.53 22497.65 7490.31 35898.89 1998.93 3899.36 1484.57 29699.92 497.81 2699.56 8999.39 86
FC-MVSNet-test98.16 3398.37 2797.56 12499.49 2893.10 19198.35 2999.21 1498.43 2998.89 3998.83 5494.30 16599.81 3297.87 2499.91 1799.77 8
FOURS199.59 1498.20 499.03 799.25 1298.96 1898.87 40
KD-MVS_self_test97.86 6598.07 3697.25 15799.22 5992.81 19797.55 8198.94 7497.10 8198.85 4198.88 5195.03 14199.67 13097.39 4399.65 6499.26 120
TranMVSNet+NR-MVSNet98.33 2698.30 3198.43 5799.07 8895.87 8096.73 12999.05 4398.67 2498.84 4298.45 8097.58 2899.88 1896.45 7299.86 2599.54 38
new-patchmatchnet95.67 18596.58 14092.94 31997.48 26580.21 35492.96 30298.19 20994.83 18098.82 4398.79 5593.31 18799.51 18695.83 10299.04 21899.12 151
EG-PatchMatch MVS97.69 7897.79 5597.40 14799.06 8993.52 18195.96 16798.97 7094.55 19198.82 4398.76 5897.31 3699.29 25197.20 5099.44 13399.38 88
DPE-MVScopyleft97.64 8097.35 9598.50 5298.85 10796.18 6995.21 21698.99 6395.84 13898.78 4598.08 12396.84 6999.81 3293.98 20099.57 8699.52 42
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 5599.16 2098.34 3298.78 4598.52 7597.32 3599.45 20294.08 19399.67 6199.13 146
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
lessismore_v097.05 16699.36 4292.12 21284.07 37098.77 4798.98 4385.36 29099.74 7597.34 4499.37 15699.30 107
v897.60 8498.06 3896.23 21298.71 12389.44 25597.43 9198.82 11497.29 7798.74 4899.10 3593.86 17599.68 12598.61 1099.94 899.56 35
DP-MVS97.87 6397.89 4897.81 10698.62 13594.82 12997.13 10798.79 11698.98 1798.74 4898.49 7795.80 11499.49 18995.04 15399.44 13399.11 155
v1097.55 8797.97 4196.31 20998.60 13889.64 25197.44 8999.02 5296.60 9498.72 5099.16 3093.48 18499.72 8698.76 699.92 1499.58 28
test072699.24 5495.51 9696.89 11898.89 7995.92 13198.64 5198.31 9097.06 50
DVP-MVS++97.96 4697.90 4598.12 8497.75 24395.40 10299.03 798.89 7996.62 9298.62 5298.30 9496.97 5699.75 6595.70 10499.25 18799.21 129
test_241102_TWO98.83 10696.11 11898.62 5298.24 10596.92 6299.72 8695.44 12599.49 11999.49 53
FIs97.93 5598.07 3697.48 13699.38 4092.95 19498.03 5499.11 2998.04 4298.62 5298.66 6593.75 17999.78 4397.23 4599.84 2999.73 15
abl_698.42 2398.19 3299.09 399.16 7198.10 697.73 7299.11 2997.76 5098.62 5298.27 10397.88 1999.80 3895.67 10899.50 11599.38 88
DeepC-MVS95.41 497.82 6997.70 6298.16 7998.78 11495.72 8496.23 15199.02 5293.92 21198.62 5298.99 4297.69 2399.62 15196.18 8099.87 2499.15 140
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 12096.04 7598.07 5199.10 3195.96 12898.59 5798.69 6396.94 5899.81 3296.64 6299.58 8399.57 32
XXY-MVS97.54 8897.70 6297.07 16599.46 3092.21 20897.22 10199.00 6094.93 17898.58 5898.92 4897.31 3699.41 21794.44 17699.43 14199.59 27
test_040297.84 6697.97 4197.47 13799.19 6994.07 15896.71 13098.73 12998.66 2598.56 5998.41 8296.84 6999.69 11794.82 16199.81 3398.64 221
PM-MVS97.36 10397.10 11198.14 8398.91 10496.77 5196.20 15298.63 15593.82 21398.54 6098.33 8893.98 17399.05 28495.99 9299.45 13298.61 226
DeepPCF-MVS94.58 596.90 12596.43 15298.31 6797.48 26597.23 4292.56 31198.60 15792.84 24798.54 6097.40 19696.64 7798.78 31094.40 18099.41 15098.93 183
MSP-MVS97.45 9596.92 12399.03 899.26 5097.70 1997.66 7398.89 7995.65 14598.51 6296.46 26292.15 21599.81 3295.14 14798.58 26499.58 28
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 10197.25 10197.74 11198.69 12794.50 14397.04 11295.61 30998.59 2698.51 6298.72 6092.54 20899.58 16296.02 8999.49 11999.12 151
FMVSNet296.72 14096.67 13696.87 17697.96 20891.88 21897.15 10498.06 22895.59 15098.50 6498.62 6889.51 25899.65 13894.99 15799.60 7999.07 162
test111194.53 23994.81 21493.72 29999.06 8981.94 34898.31 3383.87 37196.37 10598.49 6599.17 2981.49 30799.73 8196.64 6299.86 2599.49 53
SMA-MVScopyleft97.48 9397.11 11098.60 4698.83 10896.67 5496.74 12598.73 12991.61 26398.48 6698.36 8596.53 8399.68 12595.17 14299.54 9899.45 69
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 24794.47 23393.60 30298.14 19182.60 34397.24 10092.72 33885.08 33198.48 6698.94 4682.59 30498.76 31397.47 4099.53 10199.44 79
RPSCF97.87 6397.51 8598.95 1799.15 7498.43 397.56 8099.06 4196.19 11598.48 6698.70 6294.72 14999.24 25994.37 18199.33 17499.17 136
v124096.74 13797.02 11895.91 22898.18 18488.52 27095.39 20098.88 8593.15 23698.46 6998.40 8492.80 19899.71 10098.45 1399.49 11999.49 53
VPNet97.26 10897.49 8896.59 19299.47 2990.58 23996.27 14698.53 16497.77 4798.46 6998.41 8294.59 15699.68 12594.61 16999.29 18299.52 42
IterMVS-LS96.92 12397.29 9895.79 23298.51 14888.13 28095.10 21998.66 14996.99 8298.46 6998.68 6492.55 20699.74 7596.91 6099.79 3899.50 45
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
ambc96.56 19698.23 17891.68 22397.88 6198.13 21898.42 7298.56 7294.22 16899.04 28594.05 19799.35 16498.95 177
DVP-MVScopyleft97.78 7297.65 6998.16 7999.24 5495.51 9696.74 12598.23 20095.92 13198.40 7398.28 9997.06 5099.71 10095.48 12199.52 10699.26 120
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 9298.40 7398.28 9997.10 4599.71 10095.70 10499.62 6999.58 28
VDDNet96.98 12096.84 12697.41 14699.40 3893.26 18697.94 5695.31 31599.26 798.39 7599.18 2787.85 27699.62 15195.13 14999.09 21199.35 98
PC_three_145287.24 30898.37 7697.44 19397.00 5496.78 36592.01 23399.25 18799.21 129
Anonymous20240521196.34 15995.98 17297.43 14498.25 17593.85 16796.74 12594.41 32297.72 5498.37 7698.03 13387.15 28099.53 17894.06 19499.07 21498.92 187
Baseline_NR-MVSNet97.72 7697.79 5597.50 13299.56 1793.29 18595.44 19498.86 9098.20 3898.37 7699.24 2094.69 15099.55 17395.98 9399.79 3899.65 23
IU-MVS99.22 5995.40 10298.14 21685.77 32398.36 7995.23 13999.51 11199.49 53
IterMVS-SCA-FT95.86 18096.19 16194.85 27097.68 25085.53 31792.42 31497.63 25796.99 8298.36 7998.54 7487.94 27199.75 6597.07 5699.08 21299.27 119
ACMM93.33 1198.05 4197.79 5598.85 2599.15 7497.55 2796.68 13198.83 10695.21 16398.36 7998.13 11798.13 1499.62 15196.04 8799.54 9899.39 86
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
Anonymous2024052197.07 11497.51 8595.76 23399.35 4388.18 27797.78 6598.40 18197.11 8098.34 8299.04 4089.58 25499.79 3998.09 1899.93 1099.30 107
Regformer-497.53 9097.47 9097.71 11397.35 27593.91 16395.26 21198.14 21697.97 4398.34 8297.89 15095.49 12499.71 10097.41 4199.42 14499.51 44
LPG-MVS_test97.94 5297.67 6698.74 3599.15 7497.02 4497.09 10999.02 5295.15 16798.34 8298.23 10797.91 1799.70 10994.41 17899.73 4899.50 45
LGP-MVS_train98.74 3599.15 7497.02 4499.02 5295.15 16798.34 8298.23 10797.91 1799.70 10994.41 17899.73 4899.50 45
casdiffmvs97.50 9197.81 5496.56 19698.51 14891.04 23095.83 17699.09 3697.23 7898.33 8698.30 9497.03 5299.37 23096.58 6699.38 15599.28 115
Patchmatch-RL test94.66 23294.49 23195.19 25698.54 14588.91 26392.57 31098.74 12791.46 26698.32 8797.75 16677.31 33198.81 30896.06 8499.61 7597.85 288
XVG-OURS97.12 11396.74 13298.26 7098.99 9797.45 3493.82 27999.05 4395.19 16598.32 8797.70 17295.22 13698.41 34094.27 18698.13 27998.93 183
UniMVSNet_NR-MVSNet97.83 6797.65 6998.37 6198.72 12095.78 8295.66 18499.02 5298.11 4098.31 8997.69 17494.65 15499.85 2297.02 5799.71 5499.48 59
DU-MVS97.79 7197.60 7898.36 6298.73 11895.78 8295.65 18798.87 8797.57 6198.31 8997.83 15794.69 15099.85 2297.02 5799.71 5499.46 64
EI-MVSNet-UG-set97.32 10597.40 9197.09 16497.34 27992.01 21695.33 20597.65 25397.74 5198.30 9198.14 11695.04 14099.69 11797.55 3799.52 10699.58 28
EI-MVSNet-Vis-set97.32 10597.39 9297.11 16297.36 27492.08 21495.34 20497.65 25397.74 5198.29 9298.11 12195.05 13899.68 12597.50 3999.50 11599.56 35
test20.0396.58 15096.61 13796.48 20098.49 15291.72 22295.68 18397.69 24896.81 8898.27 9397.92 14894.18 16998.71 31790.78 26499.66 6399.00 171
RRT_MVS94.90 21794.07 24697.39 14893.18 36293.21 18895.26 21197.49 26193.94 21098.25 9497.85 15572.96 35399.84 2597.90 2299.78 4199.14 143
APD-MVS_3200maxsize98.13 3797.90 4598.79 3198.79 11297.31 3897.55 8198.92 7697.72 5498.25 9498.13 11797.10 4599.75 6595.44 12599.24 19099.32 101
v14896.58 15096.97 11995.42 24898.63 13487.57 29195.09 22197.90 23495.91 13398.24 9697.96 14093.42 18599.39 22496.04 8799.52 10699.29 114
ECVR-MVScopyleft94.37 24594.48 23294.05 29698.95 9983.10 34098.31 3382.48 37296.20 11398.23 9799.16 3081.18 31099.66 13695.95 9499.83 3199.38 88
UniMVSNet (Re)97.83 6797.65 6998.35 6498.80 11195.86 8195.92 17199.04 4997.51 6698.22 9897.81 16194.68 15299.78 4397.14 5399.75 4699.41 83
SR-MVS-dyc-post98.14 3497.84 5199.02 998.81 10998.05 997.55 8198.86 9097.77 4798.20 9998.07 12596.60 8099.76 5895.49 11899.20 19299.26 120
RE-MVS-def97.88 4998.81 10998.05 997.55 8198.86 9097.77 4798.20 9998.07 12596.94 5895.49 11899.20 19299.26 120
WR-MVS96.90 12596.81 12897.16 15998.56 14392.20 21094.33 25398.12 21997.34 7498.20 9997.33 20792.81 19799.75 6594.79 16399.81 3399.54 38
v192192096.72 14096.96 12195.99 22198.21 17988.79 26795.42 19698.79 11693.22 23098.19 10298.26 10492.68 20199.70 10998.34 1599.55 9599.49 53
Regformer-397.25 10997.29 9897.11 16297.35 27592.32 20595.26 21197.62 25897.67 5998.17 10397.89 15095.05 13899.56 16997.16 5299.42 14499.46 64
TSAR-MVS + MP.97.42 9797.23 10498.00 9499.38 4095.00 12497.63 7698.20 20493.00 24098.16 10498.06 13095.89 10399.72 8695.67 10899.10 21099.28 115
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
TinyColmap96.00 17496.34 15594.96 26497.90 21487.91 28394.13 26798.49 16894.41 19398.16 10497.76 16396.29 9798.68 32290.52 27699.42 14498.30 254
test117298.08 3997.76 5999.05 698.78 11498.07 797.41 9398.85 9497.57 6198.15 10697.96 14096.60 8099.76 5895.30 13499.18 19799.33 100
XVG-OURS-SEG-HR97.38 10097.07 11498.30 6899.01 9697.41 3694.66 24499.02 5295.20 16498.15 10697.52 18698.83 498.43 33994.87 15996.41 33199.07 162
IS-MVSNet96.93 12296.68 13597.70 11599.25 5394.00 16198.57 1796.74 28998.36 3198.14 10897.98 13988.23 26999.71 10093.10 22299.72 5199.38 88
CSCG97.40 9997.30 9797.69 11798.95 9994.83 12897.28 9798.99 6396.35 10898.13 10995.95 29095.99 10199.66 13694.36 18499.73 4898.59 227
MP-MVS-pluss97.69 7897.36 9498.70 3999.50 2796.84 4995.38 20198.99 6392.45 25298.11 11098.31 9097.25 4199.77 5396.60 6499.62 6999.48 59
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
v119296.83 13197.06 11596.15 21798.28 17089.29 25795.36 20298.77 12193.73 21598.11 11098.34 8793.02 19599.67 13098.35 1499.58 8399.50 45
Regformer-297.41 9897.24 10397.93 9897.21 28794.72 13294.85 23798.27 19597.74 5198.11 11097.50 18895.58 12299.69 11796.57 6799.31 17899.37 95
OPM-MVS97.54 8897.25 10198.41 5899.11 8496.61 5795.24 21498.46 17094.58 19098.10 11398.07 12597.09 4799.39 22495.16 14499.44 13399.21 129
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
v14419296.69 14396.90 12596.03 22098.25 17588.92 26295.49 19298.77 12193.05 23898.09 11498.29 9892.51 21099.70 10998.11 1799.56 8999.47 62
N_pmnet95.18 20694.23 24098.06 8997.85 21796.55 5992.49 31291.63 34689.34 28798.09 11497.41 19590.33 24399.06 28391.58 24599.31 17898.56 229
test_part299.03 9596.07 7498.08 116
SteuartSystems-ACMMP98.02 4397.76 5998.79 3199.43 3497.21 4397.15 10498.90 7896.58 9698.08 11697.87 15497.02 5399.76 5895.25 13799.59 8199.40 84
Skip Steuart: Steuart Systems R&D Blog.
SR-MVS98.00 4597.66 6799.01 1198.77 11697.93 1197.38 9498.83 10697.32 7598.06 11897.85 15596.65 7599.77 5395.00 15699.11 20899.32 101
XVG-ACMP-BASELINE97.58 8697.28 10098.49 5399.16 7196.90 4896.39 13998.98 6695.05 17298.06 11898.02 13495.86 10499.56 16994.37 18199.64 6699.00 171
IterMVS95.42 19795.83 17794.20 29397.52 26383.78 33892.41 31597.47 26495.49 15498.06 11898.49 7787.94 27199.58 16296.02 8999.02 21999.23 127
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
TSAR-MVS + GP.96.47 15596.12 16497.49 13597.74 24695.23 11494.15 26496.90 28293.26 22898.04 12196.70 24994.41 16298.89 30194.77 16699.14 20098.37 243
test_one_060199.05 9395.50 9998.87 8797.21 7998.03 12298.30 9496.93 60
Regformer-197.27 10797.16 10897.61 12297.21 28793.86 16694.85 23798.04 23097.62 6098.03 12297.50 18895.34 13199.63 14396.52 6899.31 17899.35 98
testgi96.07 16996.50 15094.80 27399.26 5087.69 29095.96 16798.58 16095.08 17098.02 12496.25 27397.92 1697.60 35988.68 30598.74 24999.11 155
V4297.04 11597.16 10896.68 18998.59 14091.05 22996.33 14498.36 18694.60 18797.99 12598.30 9493.32 18699.62 15197.40 4299.53 10199.38 88
GBi-Net96.99 11796.80 12997.56 12497.96 20893.67 17498.23 3998.66 14995.59 15097.99 12599.19 2489.51 25899.73 8194.60 17099.44 13399.30 107
test196.99 11796.80 12997.56 12497.96 20893.67 17498.23 3998.66 14995.59 15097.99 12599.19 2489.51 25899.73 8194.60 17099.44 13399.30 107
FMVSNet395.26 20494.94 20496.22 21496.53 30690.06 24395.99 16497.66 25194.11 20597.99 12597.91 14980.22 31699.63 14394.60 17099.44 13398.96 176
pmmvs-eth3d96.49 15396.18 16297.42 14598.25 17594.29 14994.77 24198.07 22789.81 28497.97 12998.33 8893.11 19099.08 28195.46 12499.84 2998.89 192
v114496.84 12897.08 11396.13 21898.42 16089.28 25895.41 19898.67 14794.21 20197.97 12998.31 9093.06 19199.65 13898.06 1999.62 6999.45 69
ACMP92.54 1397.47 9497.10 11198.55 5099.04 9496.70 5396.24 15098.89 7993.71 21697.97 12997.75 16697.44 3099.63 14393.22 21999.70 5799.32 101
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
EI-MVSNet96.63 14796.93 12295.74 23497.26 28488.13 28095.29 20997.65 25396.99 8297.94 13298.19 11292.55 20699.58 16296.91 6099.56 8999.50 45
MVSTER94.21 25093.93 25395.05 26195.83 32886.46 30795.18 21797.65 25392.41 25397.94 13298.00 13872.39 35499.58 16296.36 7599.56 8999.12 151
ACMMPcopyleft98.05 4197.75 6198.93 2199.23 5697.60 2398.09 5098.96 7195.75 14397.91 13498.06 13096.89 6499.76 5895.32 13399.57 8699.43 80
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 4497.66 6799.06 499.44 3297.90 1295.66 18498.73 12997.69 5797.90 13597.96 14095.81 11299.82 2996.13 8199.61 7599.45 69
MTAPA98.14 3497.84 5199.06 499.44 3297.90 1297.25 9898.73 12997.69 5797.90 13597.96 14095.81 11299.82 2996.13 8199.61 7599.45 69
LFMVS95.32 20194.88 20996.62 19098.03 19991.47 22697.65 7490.72 35599.11 997.89 13798.31 9079.20 31999.48 19293.91 20399.12 20798.93 183
ACMMP_NAP97.89 6197.63 7498.67 4199.35 4396.84 4996.36 14298.79 11695.07 17197.88 13898.35 8697.24 4299.72 8696.05 8699.58 8399.45 69
VNet96.84 12896.83 12796.88 17598.06 19792.02 21596.35 14397.57 26097.70 5697.88 13897.80 16292.40 21299.54 17694.73 16898.96 22399.08 160
HPM-MVS_fast98.32 2798.13 3398.88 2499.54 2197.48 3298.35 2999.03 5095.88 13497.88 13898.22 11098.15 1299.74 7596.50 7099.62 6999.42 81
UA-Net98.88 798.76 1399.22 299.11 8497.89 1499.47 399.32 1099.08 1097.87 14199.67 296.47 8899.92 497.88 2399.98 299.85 3
baseline97.44 9697.78 5896.43 20298.52 14790.75 23796.84 11999.03 5096.51 9997.86 14298.02 13496.67 7499.36 23297.09 5499.47 12599.19 133
v2v48296.78 13597.06 11595.95 22598.57 14288.77 26895.36 20298.26 19795.18 16697.85 14398.23 10792.58 20599.63 14397.80 2799.69 5899.45 69
xxxxxxxxxxxxxcwj97.24 11097.03 11797.89 10098.48 15494.71 13394.53 24999.07 4095.02 17497.83 14497.88 15296.44 9099.72 8694.59 17399.39 15399.25 124
SF-MVS97.60 8497.39 9298.22 7598.93 10295.69 8697.05 11199.10 3195.32 16097.83 14497.88 15296.44 9099.72 8694.59 17399.39 15399.25 124
Vis-MVSNetpermissive98.27 2998.34 2898.07 8799.33 4595.21 11998.04 5299.46 797.32 7597.82 14699.11 3496.75 7299.86 2097.84 2599.36 15999.15 140
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
AllTest97.20 11296.92 12398.06 8999.08 8696.16 7097.14 10699.16 2094.35 19697.78 14798.07 12595.84 10599.12 27491.41 24799.42 14498.91 188
TestCases98.06 8999.08 8696.16 7099.16 2094.35 19697.78 14798.07 12595.84 10599.12 27491.41 24799.42 14498.91 188
GeoE97.75 7497.70 6297.89 10098.88 10694.53 14097.10 10898.98 6695.75 14397.62 14997.59 18097.61 2799.77 5396.34 7699.44 13399.36 96
MDA-MVSNet-bldmvs95.69 18395.67 18295.74 23498.48 15488.76 26992.84 30397.25 26796.00 12697.59 15097.95 14491.38 23199.46 19893.16 22196.35 33298.99 174
PGM-MVS97.88 6297.52 8498.96 1699.20 6797.62 2297.09 10999.06 4195.45 15597.55 15197.94 14597.11 4499.78 4394.77 16699.46 12899.48 59
GST-MVS97.82 6997.49 8898.81 2999.23 5697.25 4097.16 10398.79 11695.96 12897.53 15297.40 19696.93 6099.77 5395.04 15399.35 16499.42 81
YYNet194.73 22494.84 21194.41 28897.47 26985.09 32690.29 34695.85 30492.52 24997.53 15297.76 16391.97 22199.18 26593.31 21696.86 32198.95 177
bset_n11_16_dypcd94.53 23993.95 25296.25 21197.56 26089.85 24888.52 35991.32 34894.90 17997.51 15496.38 26882.34 30599.78 4397.22 4699.80 3699.12 151
TAMVS95.49 19194.94 20497.16 15998.31 16693.41 18395.07 22496.82 28591.09 27297.51 15497.82 16089.96 25099.42 20888.42 30899.44 13398.64 221
LS3D97.77 7397.50 8798.57 4896.24 31397.58 2598.45 2698.85 9498.58 2797.51 15497.94 14595.74 11699.63 14395.19 14098.97 22298.51 233
HFP-MVS97.94 5297.64 7298.83 2699.15 7497.50 3097.59 7898.84 9996.05 12197.49 15797.54 18397.07 4899.70 10995.61 11499.46 12899.30 107
#test#97.62 8297.22 10598.83 2699.15 7497.50 3096.81 12198.84 9994.25 20097.49 15797.54 18397.07 4899.70 10994.37 18199.46 12899.30 107
Patchmtry95.03 21494.59 22796.33 20794.83 34590.82 23496.38 14197.20 26996.59 9597.49 15798.57 7077.67 32699.38 22792.95 22599.62 6998.80 204
MDA-MVSNet_test_wron94.73 22494.83 21394.42 28797.48 26585.15 32490.28 34795.87 30392.52 24997.48 16097.76 16391.92 22599.17 26993.32 21596.80 32498.94 179
UnsupCasMVSNet_eth95.91 17795.73 18196.44 20198.48 15491.52 22595.31 20798.45 17195.76 14197.48 16097.54 18389.53 25798.69 31994.43 17794.61 35099.13 146
tttt051793.31 27492.56 28195.57 24098.71 12387.86 28497.44 8987.17 36695.79 14097.47 16296.84 23864.12 36799.81 3296.20 7999.32 17699.02 170
ACMMPR97.95 5097.62 7698.94 1899.20 6797.56 2697.59 7898.83 10696.05 12197.46 16397.63 17796.77 7199.76 5895.61 11499.46 12899.49 53
RRT_test8_iter0592.46 28692.52 28292.29 33095.33 34077.43 36295.73 17898.55 16394.41 19397.46 16397.72 17157.44 37299.74 7596.92 5999.14 20099.69 20
APD-MVScopyleft97.00 11696.53 14698.41 5898.55 14496.31 6696.32 14598.77 12192.96 24597.44 16597.58 18295.84 10599.74 7591.96 23499.35 16499.19 133
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
HPM-MVScopyleft98.11 3897.83 5398.92 2299.42 3697.46 3398.57 1799.05 4395.43 15797.41 16697.50 18897.98 1599.79 3995.58 11799.57 8699.50 45
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
c3_l95.20 20595.32 19194.83 27296.19 31786.43 30991.83 32498.35 19093.47 22197.36 16797.26 21288.69 26499.28 25395.41 13199.36 15998.78 207
EPP-MVSNet96.84 12896.58 14097.65 11999.18 7093.78 17198.68 1296.34 29397.91 4597.30 16898.06 13088.46 26699.85 2293.85 20499.40 15199.32 101
DeepC-MVS_fast94.34 796.74 13796.51 14997.44 14397.69 24994.15 15696.02 16298.43 17493.17 23597.30 16897.38 20295.48 12699.28 25393.74 20799.34 16798.88 196
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
region2R97.92 5697.59 7998.92 2299.22 5997.55 2797.60 7798.84 9996.00 12697.22 17097.62 17896.87 6799.76 5895.48 12199.43 14199.46 64
ITE_SJBPF97.85 10498.64 13096.66 5598.51 16795.63 14697.22 17097.30 21095.52 12398.55 33390.97 25798.90 23198.34 249
h-mvs3396.29 16095.63 18498.26 7098.50 15196.11 7396.90 11797.09 27596.58 9697.21 17298.19 11284.14 29799.78 4395.89 9896.17 33598.89 192
hse-mvs295.77 18295.09 19897.79 10797.84 22195.51 9695.66 18495.43 31496.58 9697.21 17296.16 27784.14 29799.54 17695.89 9896.92 31898.32 250
9.1496.69 13498.53 14696.02 16298.98 6693.23 22997.18 17497.46 19196.47 8899.62 15192.99 22399.32 176
OMC-MVS96.48 15496.00 17097.91 9998.30 16796.01 7894.86 23698.60 15791.88 26097.18 17497.21 21596.11 9999.04 28590.49 27999.34 16798.69 218
our_test_394.20 25294.58 22893.07 31396.16 31981.20 35190.42 34596.84 28390.72 27597.14 17697.13 21790.47 24199.11 27794.04 19898.25 27598.91 188
MS-PatchMatch94.83 22094.91 20894.57 28396.81 30287.10 30094.23 25997.34 26688.74 29597.14 17697.11 22091.94 22398.23 35092.99 22397.92 28698.37 243
eth_miper_zixun_eth94.89 21894.93 20694.75 27595.99 32486.12 31291.35 33098.49 16893.40 22297.12 17897.25 21386.87 28399.35 23595.08 15298.82 24298.78 207
3Dnovator96.53 297.61 8397.64 7297.50 13297.74 24693.65 17898.49 2398.88 8596.86 8797.11 17998.55 7395.82 10899.73 8195.94 9599.42 14499.13 146
cl____94.73 22494.64 22195.01 26295.85 32787.00 30191.33 33198.08 22393.34 22597.10 18097.33 20784.01 30099.30 24795.14 14799.56 8998.71 217
DIV-MVS_self_test94.73 22494.64 22195.01 26295.86 32687.00 30191.33 33198.08 22393.34 22597.10 18097.34 20684.02 29999.31 24495.15 14699.55 9598.72 215
PMMVS293.66 26694.07 24692.45 32797.57 25880.67 35386.46 36296.00 29993.99 20897.10 18097.38 20289.90 25197.82 35688.76 30299.47 12598.86 199
mPP-MVS97.91 5997.53 8399.04 799.22 5997.87 1597.74 7098.78 12096.04 12397.10 18097.73 16996.53 8399.78 4395.16 14499.50 11599.46 64
BH-untuned94.69 22994.75 21794.52 28597.95 21187.53 29294.07 26997.01 27893.99 20897.10 18095.65 29792.65 20398.95 29887.60 31896.74 32597.09 311
test250689.86 31889.16 32391.97 33298.95 9976.83 36598.54 2061.07 37996.20 11397.07 18599.16 3055.19 37899.69 11796.43 7399.83 3199.38 88
miper_ehance_all_eth94.69 22994.70 21894.64 27795.77 33086.22 31191.32 33398.24 19991.67 26297.05 18696.65 25288.39 26899.22 26394.88 15898.34 27198.49 235
ETH3D-3000-0.196.89 12796.46 15198.16 7998.62 13595.69 8695.96 16798.98 6693.36 22497.04 18797.31 20994.93 14599.63 14392.60 22699.34 16799.17 136
miper_lstm_enhance94.81 22294.80 21594.85 27096.16 31986.45 30891.14 33798.20 20493.49 22097.03 18897.37 20484.97 29399.26 25695.28 13599.56 8998.83 201
UnsupCasMVSNet_bld94.72 22894.26 23996.08 21998.62 13590.54 24293.38 29498.05 22990.30 27997.02 18996.80 24389.54 25599.16 27088.44 30796.18 33498.56 229
ppachtmachnet_test94.49 24194.84 21193.46 30596.16 31982.10 34590.59 34397.48 26390.53 27797.01 19097.59 18091.01 23499.36 23293.97 20199.18 19798.94 179
D2MVS95.18 20695.17 19595.21 25497.76 24187.76 28994.15 26497.94 23289.77 28596.99 19197.68 17587.45 27899.14 27295.03 15599.81 3398.74 212
ab-mvs96.59 14996.59 13896.60 19198.64 13092.21 20898.35 2997.67 24994.45 19296.99 19198.79 5594.96 14499.49 18990.39 28099.07 21498.08 269
Anonymous2023120695.27 20395.06 20195.88 22998.72 12089.37 25695.70 18097.85 23788.00 30396.98 19397.62 17891.95 22299.34 23789.21 29699.53 10198.94 179
PVSNet_Blended_VisFu95.95 17695.80 17896.42 20399.28 4990.62 23895.31 20799.08 3788.40 29896.97 19498.17 11592.11 21799.78 4393.64 21199.21 19198.86 199
mvs_anonymous95.36 19996.07 16893.21 31196.29 31181.56 34994.60 24697.66 25193.30 22796.95 19598.91 4993.03 19499.38 22796.60 6497.30 31598.69 218
ZNCC-MVS97.92 5697.62 7698.83 2699.32 4797.24 4197.45 8898.84 9995.76 14196.93 19697.43 19497.26 4099.79 3996.06 8499.53 10199.45 69
3Dnovator+96.13 397.73 7597.59 7998.15 8298.11 19695.60 9298.04 5298.70 13998.13 3996.93 19698.45 8095.30 13499.62 15195.64 11298.96 22399.24 126
USDC94.56 23794.57 23094.55 28497.78 23986.43 30992.75 30698.65 15485.96 31996.91 19897.93 14790.82 23798.74 31490.71 26999.59 8198.47 236
CP-MVS97.92 5697.56 8298.99 1398.99 9797.82 1697.93 5798.96 7196.11 11896.89 19997.45 19296.85 6899.78 4395.19 14099.63 6899.38 88
OpenMVS_ROBcopyleft91.80 1493.64 26793.05 26695.42 24897.31 28391.21 22895.08 22396.68 29181.56 34796.88 20096.41 26490.44 24299.25 25885.39 33797.67 30095.80 344
testtj96.69 14396.13 16398.36 6298.46 15896.02 7796.44 13798.70 13994.26 19996.79 20197.13 21794.07 17199.75 6590.53 27598.80 24399.31 106
test_yl94.40 24294.00 24995.59 23896.95 29689.52 25394.75 24295.55 31196.18 11696.79 20196.14 28081.09 31199.18 26590.75 26597.77 29098.07 271
DCV-MVSNet94.40 24294.00 24995.59 23896.95 29689.52 25394.75 24295.55 31196.18 11696.79 20196.14 28081.09 31199.18 26590.75 26597.77 29098.07 271
Gipumacopyleft98.07 4098.31 2997.36 15099.76 596.28 6898.51 2299.10 3198.76 2396.79 20199.34 1796.61 7898.82 30696.38 7499.50 11596.98 315
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
alignmvs96.01 17395.52 18897.50 13297.77 24094.71 13396.07 15896.84 28397.48 6796.78 20594.28 32885.50 28999.40 21996.22 7898.73 25298.40 239
CL-MVSNet_self_test95.04 21294.79 21695.82 23197.51 26489.79 24991.14 33796.82 28593.05 23896.72 20696.40 26690.82 23799.16 27091.95 23598.66 25698.50 234
MSLP-MVS++96.42 15896.71 13395.57 24097.82 22490.56 24195.71 17998.84 9994.72 18396.71 20797.39 20094.91 14698.10 35495.28 13599.02 21998.05 278
canonicalmvs97.23 11197.21 10697.30 15397.65 25494.39 14597.84 6399.05 4397.42 6996.68 20893.85 33197.63 2699.33 24096.29 7798.47 26898.18 266
ZD-MVS98.43 15995.94 7998.56 16290.72 27596.66 20997.07 22395.02 14299.74 7591.08 25498.93 229
diffmvs96.04 17196.23 15995.46 24797.35 27588.03 28293.42 29199.08 3794.09 20696.66 20996.93 23393.85 17699.29 25196.01 9198.67 25499.06 164
MVP-Stereo95.69 18395.28 19296.92 17298.15 19093.03 19295.64 18998.20 20490.39 27896.63 21197.73 16991.63 22999.10 27991.84 24097.31 31498.63 223
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
Vis-MVSNet (Re-imp)95.11 20994.85 21095.87 23099.12 8389.17 25997.54 8694.92 31796.50 10096.58 21297.27 21183.64 30199.48 19288.42 30899.67 6198.97 175
MVS_111021_HR96.73 13996.54 14597.27 15498.35 16593.66 17793.42 29198.36 18694.74 18296.58 21296.76 24696.54 8298.99 29194.87 15999.27 18599.15 140
thisisatest053092.71 28391.76 29195.56 24298.42 16088.23 27596.03 16187.35 36594.04 20796.56 21495.47 30364.03 36899.77 5394.78 16599.11 20898.68 220
MVS_111021_LR96.82 13296.55 14397.62 12198.27 17295.34 10993.81 28198.33 19194.59 18996.56 21496.63 25396.61 7898.73 31594.80 16299.34 16798.78 207
DELS-MVS96.17 16696.23 15995.99 22197.55 26290.04 24492.38 31698.52 16594.13 20496.55 21697.06 22494.99 14399.58 16295.62 11399.28 18398.37 243
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 27892.64 27994.62 27997.34 27987.20 29996.67 13293.02 33394.71 18496.51 21795.83 29381.64 30698.60 32990.00 28688.06 36598.07 271
Patchmatch-test93.60 26893.25 26494.63 27896.14 32287.47 29396.04 16094.50 32193.57 21896.47 21896.97 23076.50 33498.61 32790.67 27198.41 27097.81 292
HyFIR lowres test93.72 26392.65 27896.91 17498.93 10291.81 22191.23 33598.52 16582.69 34396.46 21996.52 26080.38 31599.90 1390.36 28198.79 24499.03 168
QAPM95.88 17995.57 18796.80 18097.90 21491.84 22098.18 4698.73 12988.41 29796.42 22098.13 11794.73 14899.75 6588.72 30398.94 22798.81 203
BH-RMVSNet94.56 23794.44 23694.91 26597.57 25887.44 29493.78 28296.26 29493.69 21796.41 22196.50 26192.10 21899.00 28985.96 33097.71 29698.31 252
CNVR-MVS96.92 12396.55 14398.03 9398.00 20695.54 9494.87 23598.17 21094.60 18796.38 22297.05 22595.67 11899.36 23295.12 15099.08 21299.19 133
thres600view792.03 29591.43 29393.82 29798.19 18184.61 33196.27 14690.39 35696.81 8896.37 22393.11 33473.44 35199.49 18980.32 35697.95 28597.36 306
thres100view90091.76 29991.26 29893.26 30898.21 17984.50 33296.39 13990.39 35696.87 8696.33 22493.08 33873.44 35199.42 20878.85 36097.74 29395.85 342
XVS97.96 4697.63 7498.94 1899.15 7497.66 2097.77 6698.83 10697.42 6996.32 22597.64 17696.49 8699.72 8695.66 11099.37 15699.45 69
X-MVStestdata92.86 28090.83 30598.94 1899.15 7497.66 2097.77 6698.83 10697.42 6996.32 22536.50 37296.49 8699.72 8695.66 11099.37 15699.45 69
MSDG95.33 20095.13 19695.94 22797.40 27391.85 21991.02 34098.37 18595.30 16196.31 22795.99 28594.51 16098.38 34389.59 29197.65 30297.60 300
CDS-MVSNet94.88 21994.12 24597.14 16197.64 25593.57 17993.96 27597.06 27790.05 28296.30 22896.55 25686.10 28599.47 19590.10 28499.31 17898.40 239
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
CVMVSNet92.33 29092.79 27390.95 33897.26 28475.84 36895.29 20992.33 34181.86 34596.27 22998.19 11281.44 30898.46 33894.23 18898.29 27498.55 231
FMVSNet593.39 27292.35 28396.50 19895.83 32890.81 23697.31 9598.27 19592.74 24896.27 22998.28 9962.23 36999.67 13090.86 26099.36 15999.03 168
TAPA-MVS93.32 1294.93 21694.23 24097.04 16798.18 18494.51 14195.22 21598.73 12981.22 35096.25 23195.95 29093.80 17898.98 29389.89 28798.87 23597.62 298
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
CHOSEN 1792x268894.10 25493.41 26196.18 21699.16 7190.04 24492.15 31898.68 14479.90 35596.22 23297.83 15787.92 27599.42 20889.18 29799.65 6499.08 160
MCST-MVS96.24 16295.80 17897.56 12498.75 11794.13 15794.66 24498.17 21090.17 28196.21 23396.10 28395.14 13799.43 20794.13 19298.85 23999.13 146
PHI-MVS96.96 12196.53 14698.25 7397.48 26596.50 6096.76 12498.85 9493.52 21996.19 23496.85 23795.94 10299.42 20893.79 20699.43 14198.83 201
HQP_MVS96.66 14696.33 15697.68 11898.70 12594.29 14996.50 13598.75 12596.36 10696.16 23596.77 24491.91 22699.46 19892.59 22899.20 19299.28 115
plane_prior394.51 14195.29 16296.16 235
miper_enhance_ethall93.14 27892.78 27594.20 29393.65 35985.29 32189.97 34997.85 23785.05 33296.15 23794.56 32085.74 28799.14 27293.74 20798.34 27198.17 267
MVS_Test96.27 16196.79 13194.73 27696.94 29886.63 30696.18 15398.33 19194.94 17696.07 23898.28 9995.25 13599.26 25697.21 4897.90 28898.30 254
PCF-MVS89.43 1892.12 29490.64 30896.57 19597.80 22993.48 18289.88 35398.45 17174.46 36796.04 23995.68 29690.71 23999.31 24473.73 36699.01 22196.91 319
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
ETH3D cwj APD-0.1696.23 16395.61 18698.09 8697.91 21295.65 9194.94 23298.74 12791.31 26996.02 24097.08 22294.05 17299.69 11791.51 24698.94 22798.93 183
CPTT-MVS96.69 14396.08 16798.49 5398.89 10596.64 5697.25 9898.77 12192.89 24696.01 24197.13 21792.23 21499.67 13092.24 23199.34 16799.17 136
DROMVSNet97.90 6097.94 4497.79 10798.66 12995.14 12098.31 3399.66 297.57 6195.95 24297.01 22996.99 5599.82 2997.66 3399.64 6698.39 241
PMVScopyleft89.60 1796.71 14296.97 11995.95 22599.51 2497.81 1797.42 9297.49 26197.93 4495.95 24298.58 6996.88 6696.91 36289.59 29199.36 15993.12 362
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
xiu_mvs_v1_base_debu95.62 18695.96 17394.60 28098.01 20288.42 27193.99 27298.21 20192.98 24195.91 24494.53 32196.39 9299.72 8695.43 12898.19 27695.64 346
xiu_mvs_v1_base95.62 18695.96 17394.60 28098.01 20288.42 27193.99 27298.21 20192.98 24195.91 24494.53 32196.39 9299.72 8695.43 12898.19 27695.64 346
xiu_mvs_v1_base_debi95.62 18695.96 17394.60 28098.01 20288.42 27193.99 27298.21 20192.98 24195.91 24494.53 32196.39 9299.72 8695.43 12898.19 27695.64 346
tfpn200view991.55 30191.00 30093.21 31198.02 20084.35 33495.70 18090.79 35396.26 11095.90 24792.13 35173.62 34899.42 20878.85 36097.74 29395.85 342
thres40091.68 30091.00 30093.71 30098.02 20084.35 33495.70 18090.79 35396.26 11095.90 24792.13 35173.62 34899.42 20878.85 36097.74 29397.36 306
cl2293.25 27692.84 27294.46 28694.30 35186.00 31391.09 33996.64 29290.74 27495.79 24996.31 27178.24 32398.77 31194.15 19198.34 27198.62 224
API-MVS95.09 21195.01 20395.31 25196.61 30494.02 16096.83 12097.18 27195.60 14995.79 24994.33 32694.54 15998.37 34585.70 33298.52 26593.52 359
DP-MVS Recon95.55 18995.13 19696.80 18098.51 14893.99 16294.60 24698.69 14290.20 28095.78 25196.21 27692.73 20098.98 29390.58 27498.86 23797.42 305
CLD-MVS95.47 19495.07 19996.69 18798.27 17292.53 20191.36 32998.67 14791.22 27195.78 25194.12 32995.65 11998.98 29390.81 26299.72 5198.57 228
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 29577.95 36395.77 25398.67 32390.74 268
pmmvs494.82 22194.19 24396.70 18697.42 27292.75 19992.09 32196.76 28786.80 31495.73 25497.22 21489.28 26198.89 30193.28 21799.14 20098.46 238
LF4IMVS96.07 16995.63 18497.36 15098.19 18195.55 9395.44 19498.82 11492.29 25495.70 25596.55 25692.63 20498.69 31991.75 24399.33 17497.85 288
testdata95.70 23798.16 18890.58 23997.72 24680.38 35395.62 25697.02 22792.06 22098.98 29389.06 30098.52 26597.54 301
MP-MVScopyleft97.64 8097.18 10799.00 1299.32 4797.77 1897.49 8798.73 12996.27 10995.59 25797.75 16696.30 9699.78 4393.70 21099.48 12399.45 69
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
ETV-MVS96.13 16895.90 17696.82 17997.76 24193.89 16495.40 19998.95 7395.87 13595.58 25891.00 36296.36 9599.72 8693.36 21498.83 24196.85 322
thres20091.00 30790.42 31192.77 32197.47 26983.98 33794.01 27191.18 35195.12 16995.44 25991.21 36073.93 34499.31 24477.76 36397.63 30395.01 352
CDPH-MVS95.45 19694.65 22097.84 10598.28 17094.96 12593.73 28398.33 19185.03 33395.44 25996.60 25495.31 13399.44 20590.01 28599.13 20499.11 155
NCCC96.52 15295.99 17198.10 8597.81 22595.68 8895.00 23098.20 20495.39 15895.40 26196.36 26993.81 17799.45 20293.55 21398.42 26999.17 136
jason94.39 24494.04 24895.41 25098.29 16887.85 28692.74 30896.75 28885.38 33095.29 26296.15 27888.21 27099.65 13894.24 18799.34 16798.74 212
jason: jason.
new_pmnet92.34 28991.69 29294.32 29096.23 31589.16 26092.27 31792.88 33584.39 34095.29 26296.35 27085.66 28896.74 36684.53 34497.56 30497.05 313
pmmvs594.63 23494.34 23895.50 24497.63 25688.34 27494.02 27097.13 27387.15 31095.22 26497.15 21687.50 27799.27 25593.99 19999.26 18698.88 196
Effi-MVS+-dtu96.81 13396.09 16698.99 1396.90 30098.69 296.42 13898.09 22195.86 13695.15 26595.54 30194.26 16699.81 3294.06 19498.51 26798.47 236
KD-MVS_2432*160088.93 32487.74 32992.49 32488.04 37581.99 34689.63 35595.62 30791.35 26795.06 26693.11 33456.58 37498.63 32585.19 33895.07 34596.85 322
miper_refine_blended88.93 32487.74 32992.49 32488.04 37581.99 34689.63 35595.62 30791.35 26795.06 26693.11 33456.58 37498.63 32585.19 33895.07 34596.85 322
HPM-MVS++copyleft96.99 11796.38 15398.81 2998.64 13097.59 2495.97 16698.20 20495.51 15395.06 26696.53 25894.10 17099.70 10994.29 18599.15 19999.13 146
MIMVSNet93.42 27192.86 27095.10 25998.17 18688.19 27698.13 4893.69 32592.07 25595.04 26998.21 11180.95 31399.03 28881.42 35498.06 28298.07 271
TR-MVS92.54 28592.20 28593.57 30396.49 30786.66 30593.51 28994.73 31889.96 28394.95 27093.87 33090.24 24898.61 32781.18 35594.88 34795.45 350
PatchMatch-RL94.61 23593.81 25597.02 16998.19 18195.72 8493.66 28497.23 26888.17 30194.94 27195.62 29991.43 23098.57 33087.36 32397.68 29996.76 328
MG-MVS94.08 25694.00 24994.32 29097.09 29285.89 31493.19 30095.96 30192.52 24994.93 27297.51 18789.54 25598.77 31187.52 32197.71 29698.31 252
新几何197.25 15798.29 16894.70 13697.73 24577.98 36194.83 27396.67 25192.08 21999.45 20288.17 31298.65 25897.61 299
Fast-Effi-MVS+-dtu96.44 15696.12 16497.39 14897.18 28994.39 14595.46 19398.73 12996.03 12594.72 27494.92 31596.28 9899.69 11793.81 20597.98 28498.09 268
test0.0.03 190.11 31289.21 31992.83 32093.89 35786.87 30491.74 32588.74 36392.02 25694.71 27591.14 36173.92 34594.48 36983.75 35092.94 35597.16 310
ETH3 D test640094.77 22393.87 25497.47 13798.12 19593.73 17294.56 24898.70 13985.45 32894.70 27695.93 29291.77 22899.63 14386.45 32899.14 20099.05 166
test22298.17 18693.24 18792.74 30897.61 25975.17 36694.65 27796.69 25090.96 23698.66 25697.66 297
SCA93.38 27393.52 25992.96 31896.24 31381.40 35093.24 29894.00 32491.58 26594.57 27896.97 23087.94 27199.42 20889.47 29397.66 30198.06 275
CNLPA95.04 21294.47 23396.75 18397.81 22595.25 11394.12 26897.89 23594.41 19394.57 27895.69 29590.30 24698.35 34686.72 32798.76 24796.64 331
112194.26 24693.26 26397.27 15498.26 17494.73 13195.86 17297.71 24777.96 36294.53 28096.71 24891.93 22499.40 21987.71 31498.64 25997.69 296
PVSNet_BlendedMVS95.02 21594.93 20695.27 25297.79 23587.40 29594.14 26698.68 14488.94 29294.51 28198.01 13693.04 19299.30 24789.77 28999.49 11999.11 155
PVSNet_Blended93.96 25893.65 25794.91 26597.79 23587.40 29591.43 32898.68 14484.50 33894.51 28194.48 32493.04 19299.30 24789.77 28998.61 26198.02 281
MVSFormer96.14 16796.36 15495.49 24597.68 25087.81 28798.67 1399.02 5296.50 10094.48 28396.15 27886.90 28199.92 498.73 799.13 20498.74 212
lupinMVS93.77 26193.28 26295.24 25397.68 25087.81 28792.12 31996.05 29784.52 33794.48 28395.06 31186.90 28199.63 14393.62 21299.13 20498.27 258
OpenMVScopyleft94.22 895.48 19395.20 19396.32 20897.16 29091.96 21797.74 7098.84 9987.26 30794.36 28598.01 13693.95 17499.67 13090.70 27098.75 24897.35 308
CS-MVS95.98 17596.24 15895.20 25597.26 28489.88 24795.84 17599.39 993.89 21294.28 28695.15 30894.81 14799.62 15196.11 8399.40 15196.10 340
PatchT93.75 26293.57 25894.29 29295.05 34387.32 29796.05 15992.98 33497.54 6594.25 28798.72 6075.79 33999.24 25995.92 9695.81 33796.32 337
BH-w/o92.14 29391.94 28792.73 32297.13 29185.30 32092.46 31395.64 30689.33 28894.21 28892.74 34489.60 25398.24 34981.68 35394.66 34994.66 354
xiu_mvs_v2_base94.22 24894.63 22392.99 31797.32 28284.84 32992.12 31997.84 23991.96 25894.17 28993.43 33296.07 10099.71 10091.27 25097.48 30894.42 355
PS-MVSNAJ94.10 25494.47 23393.00 31697.35 27584.88 32891.86 32397.84 23991.96 25894.17 28992.50 34895.82 10899.71 10091.27 25097.48 30894.40 356
CR-MVSNet93.29 27592.79 27394.78 27495.44 33788.15 27896.18 15397.20 26984.94 33594.10 29198.57 7077.67 32699.39 22495.17 14295.81 33796.81 326
RPMNet94.68 23194.60 22594.90 26795.44 33788.15 27896.18 15398.86 9097.43 6894.10 29198.49 7779.40 31799.76 5895.69 10695.81 33796.81 326
WTY-MVS93.55 26993.00 26895.19 25697.81 22587.86 28493.89 27796.00 29989.02 29094.07 29395.44 30486.27 28499.33 24087.69 31696.82 32298.39 241
GA-MVS92.83 28192.15 28694.87 26996.97 29587.27 29890.03 34896.12 29691.83 26194.05 29494.57 31976.01 33898.97 29792.46 23097.34 31398.36 248
test_prior395.91 17795.39 19097.46 14097.79 23594.26 15393.33 29698.42 17794.21 20194.02 29596.25 27393.64 18199.34 23791.90 23698.96 22398.79 205
test_prior293.33 29694.21 20194.02 29596.25 27393.64 18191.90 23698.96 223
MDTV_nov1_ep13_2view57.28 37894.89 23480.59 35294.02 29578.66 32285.50 33697.82 290
AdaColmapbinary95.11 20994.62 22496.58 19397.33 28194.45 14494.92 23398.08 22393.15 23693.98 29895.53 30294.34 16499.10 27985.69 33398.61 26196.20 339
pmmvs390.00 31488.90 32493.32 30694.20 35585.34 31991.25 33492.56 34078.59 35993.82 29995.17 30767.36 36598.69 31989.08 29998.03 28395.92 341
TEST997.84 22195.23 11493.62 28598.39 18286.81 31393.78 30095.99 28594.68 15299.52 182
train_agg95.46 19594.66 21997.88 10297.84 22195.23 11493.62 28598.39 18287.04 31193.78 30095.99 28594.58 15799.52 18291.76 24298.90 23198.89 192
EIA-MVS96.04 17195.77 18096.85 17797.80 22992.98 19396.12 15699.16 2094.65 18593.77 30291.69 35695.68 11799.67 13094.18 18998.85 23997.91 286
sss94.22 24893.72 25695.74 23497.71 24889.95 24693.84 27896.98 27988.38 29993.75 30395.74 29487.94 27198.89 30191.02 25698.10 28098.37 243
CS-MVS-test96.62 14896.59 13896.69 18797.88 21693.16 18997.21 10299.53 695.61 14893.72 30495.33 30595.49 12499.69 11795.37 13299.19 19697.22 309
test_897.81 22595.07 12393.54 28898.38 18487.04 31193.71 30595.96 28994.58 15799.52 182
E-PMN89.52 32189.78 31588.73 34793.14 36477.61 36183.26 36692.02 34294.82 18193.71 30593.11 33475.31 34096.81 36385.81 33196.81 32391.77 365
thisisatest051590.43 31089.18 32294.17 29597.07 29385.44 31889.75 35487.58 36488.28 30093.69 30791.72 35565.27 36699.58 16290.59 27398.67 25497.50 303
mvs-test196.20 16495.50 18998.32 6596.90 30098.16 595.07 22498.09 22195.86 13693.63 30894.32 32794.26 16699.71 10094.06 19497.27 31697.07 312
UGNet96.81 13396.56 14297.58 12396.64 30393.84 16897.75 6997.12 27496.47 10393.62 30998.88 5193.22 18999.53 17895.61 11499.69 5899.36 96
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 29691.87 28892.30 32994.60 34879.71 35595.12 21893.59 32989.52 28693.61 31097.02 22777.94 32499.18 26590.84 26194.57 35298.01 282
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
CMPMVSbinary73.10 2392.74 28291.39 29496.77 18293.57 36194.67 13794.21 26197.67 24980.36 35493.61 31096.60 25482.85 30397.35 36084.86 34298.78 24598.29 257
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
test1297.46 14097.61 25794.07 15897.78 24393.57 31293.31 18799.42 20898.78 24598.89 192
tpm91.08 30690.85 30491.75 33395.33 34078.09 35895.03 22991.27 35088.75 29493.53 31397.40 19671.24 35699.30 24791.25 25293.87 35397.87 287
agg_prior195.39 19894.60 22597.75 11097.80 22994.96 12593.39 29398.36 18687.20 30993.49 31495.97 28894.65 15499.53 17891.69 24498.86 23798.77 210
agg_prior97.80 22994.96 12598.36 18693.49 31499.53 178
原ACMM196.58 19398.16 18892.12 21298.15 21585.90 32193.49 31496.43 26392.47 21199.38 22787.66 31798.62 26098.23 261
MDTV_nov1_ep1391.28 29694.31 35073.51 37294.80 23993.16 33286.75 31593.45 31797.40 19676.37 33598.55 33388.85 30196.43 330
114514_t93.96 25893.22 26596.19 21599.06 8990.97 23295.99 16498.94 7473.88 36893.43 31896.93 23392.38 21399.37 23089.09 29899.28 18398.25 260
Fast-Effi-MVS+95.49 19195.07 19996.75 18397.67 25392.82 19694.22 26098.60 15791.61 26393.42 31992.90 34196.73 7399.70 10992.60 22697.89 28997.74 293
PAPM_NR94.61 23594.17 24495.96 22398.36 16491.23 22795.93 17097.95 23192.98 24193.42 31994.43 32590.53 24098.38 34387.60 31896.29 33398.27 258
Effi-MVS+96.19 16596.01 16996.71 18597.43 27192.19 21196.12 15699.10 3195.45 15593.33 32194.71 31897.23 4399.56 16993.21 22097.54 30598.37 243
F-COLMAP95.30 20294.38 23798.05 9298.64 13096.04 7595.61 19098.66 14989.00 29193.22 32296.40 26692.90 19699.35 23587.45 32297.53 30698.77 210
EPMVS89.26 32288.55 32691.39 33592.36 37079.11 35695.65 18779.86 37388.60 29693.12 32396.53 25870.73 36098.10 35490.75 26589.32 36496.98 315
DPM-MVS93.68 26592.77 27696.42 20397.91 21292.54 20091.17 33697.47 26484.99 33493.08 32494.74 31789.90 25199.00 28987.54 32098.09 28197.72 294
1112_ss94.12 25393.42 26096.23 21298.59 14090.85 23394.24 25898.85 9485.49 32592.97 32594.94 31386.01 28699.64 14191.78 24197.92 28698.20 264
HQP4-MVS92.87 32699.23 26199.06 164
HQP-NCC97.85 21794.26 25493.18 23292.86 327
ACMP_Plane97.85 21794.26 25493.18 23292.86 327
HQP-MVS95.17 20894.58 22896.92 17297.85 21792.47 20294.26 25498.43 17493.18 23292.86 32795.08 30990.33 24399.23 26190.51 27798.74 24999.05 166
ADS-MVSNet291.47 30290.51 31094.36 28995.51 33585.63 31595.05 22795.70 30583.46 34192.69 33096.84 23879.15 32099.41 21785.66 33490.52 36098.04 279
ADS-MVSNet90.95 30890.26 31293.04 31495.51 33582.37 34495.05 22793.41 33083.46 34192.69 33096.84 23879.15 32098.70 31885.66 33490.52 36098.04 279
Test_1112_low_res93.53 27092.86 27095.54 24398.60 13888.86 26592.75 30698.69 14282.66 34492.65 33296.92 23584.75 29499.56 16990.94 25897.76 29298.19 265
AUN-MVS93.95 26092.69 27797.74 11197.80 22995.38 10495.57 19195.46 31391.26 27092.64 33396.10 28374.67 34299.55 17393.72 20996.97 31798.30 254
EMVS89.06 32389.22 31888.61 34893.00 36677.34 36382.91 36790.92 35294.64 18692.63 33491.81 35476.30 33697.02 36183.83 34896.90 32091.48 366
CANet95.86 18095.65 18396.49 19996.41 30990.82 23494.36 25298.41 17994.94 17692.62 33596.73 24792.68 20199.71 10095.12 15099.60 7998.94 179
DSMNet-mixed92.19 29291.83 28993.25 30996.18 31883.68 33996.27 14693.68 32776.97 36592.54 33699.18 2789.20 26398.55 33383.88 34798.60 26397.51 302
PVSNet86.72 1991.10 30590.97 30291.49 33497.56 26078.04 35987.17 36194.60 32084.65 33692.34 33792.20 35087.37 27998.47 33785.17 34097.69 29897.96 283
tpmrst90.31 31190.61 30989.41 34594.06 35672.37 37495.06 22693.69 32588.01 30292.32 33896.86 23677.45 32898.82 30691.04 25587.01 36797.04 314
cascas91.89 29791.35 29593.51 30494.27 35285.60 31688.86 35898.61 15679.32 35792.16 33991.44 35889.22 26298.12 35390.80 26397.47 31096.82 325
MAR-MVS94.21 25093.03 26797.76 10996.94 29897.44 3596.97 11697.15 27287.89 30592.00 34092.73 34592.14 21699.12 27483.92 34697.51 30796.73 329
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 30990.87 30390.57 34192.75 36976.30 36695.79 17793.64 32891.04 27391.91 34196.26 27277.19 33298.86 30589.38 29589.85 36396.56 334
PMMVS92.39 28791.08 29996.30 21093.12 36592.81 19790.58 34495.96 30179.17 35891.85 34292.27 34990.29 24798.66 32489.85 28896.68 32797.43 304
PLCcopyleft91.02 1694.05 25792.90 26997.51 12998.00 20695.12 12294.25 25798.25 19886.17 31791.48 34395.25 30691.01 23499.19 26485.02 34196.69 32698.22 262
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
dp88.08 33088.05 32888.16 35192.85 36768.81 37694.17 26292.88 33585.47 32691.38 34496.14 28068.87 36398.81 30886.88 32583.80 37096.87 320
PAPR92.22 29191.27 29795.07 26095.73 33288.81 26691.97 32297.87 23685.80 32290.91 34592.73 34591.16 23298.33 34779.48 35795.76 34198.08 269
131492.38 28892.30 28492.64 32395.42 33985.15 32495.86 17296.97 28085.40 32990.62 34693.06 33991.12 23397.80 35786.74 32695.49 34494.97 353
MVS90.02 31389.20 32092.47 32694.71 34686.90 30395.86 17296.74 28964.72 37090.62 34692.77 34392.54 20898.39 34279.30 35895.56 34392.12 363
CostFormer89.75 31989.25 31791.26 33794.69 34778.00 36095.32 20691.98 34381.50 34890.55 34896.96 23271.06 35898.89 30188.59 30692.63 35796.87 320
HY-MVS91.43 1592.58 28491.81 29094.90 26796.49 30788.87 26497.31 9594.62 31985.92 32090.50 34996.84 23885.05 29199.40 21983.77 34995.78 34096.43 336
FPMVS89.92 31788.63 32593.82 29798.37 16396.94 4791.58 32693.34 33188.00 30390.32 35097.10 22170.87 35991.13 37171.91 36996.16 33693.39 361
JIA-IIPM91.79 29890.69 30795.11 25893.80 35890.98 23194.16 26391.78 34596.38 10490.30 35199.30 1872.02 35598.90 29988.28 31090.17 36295.45 350
CANet_DTU94.65 23394.21 24295.96 22395.90 32589.68 25093.92 27697.83 24193.19 23190.12 35295.64 29888.52 26599.57 16893.27 21899.47 12598.62 224
test-LLR89.97 31689.90 31490.16 34294.24 35374.98 36989.89 35089.06 36192.02 25689.97 35390.77 36373.92 34598.57 33091.88 23897.36 31196.92 317
test-mter87.92 33287.17 33390.16 34294.24 35374.98 36989.89 35089.06 36186.44 31689.97 35390.77 36354.96 37998.57 33091.88 23897.36 31196.92 317
tpm288.47 32787.69 33190.79 33994.98 34477.34 36395.09 22191.83 34477.51 36489.40 35596.41 26467.83 36498.73 31583.58 35192.60 35896.29 338
tpm cat188.01 33187.33 33290.05 34494.48 34976.28 36794.47 25194.35 32373.84 36989.26 35695.61 30073.64 34798.30 34884.13 34586.20 36895.57 349
MVS_030495.50 19095.05 20296.84 17896.28 31293.12 19097.00 11496.16 29595.03 17389.22 35797.70 17290.16 24999.48 19294.51 17599.34 16797.93 285
TESTMET0.1,187.20 33586.57 33789.07 34693.62 36072.84 37389.89 35087.01 36785.46 32789.12 35890.20 36556.00 37797.72 35890.91 25996.92 31896.64 331
MVS-HIRNet88.40 32890.20 31382.99 35397.01 29460.04 37793.11 30185.61 36984.45 33988.72 35999.09 3684.72 29598.23 35082.52 35296.59 32990.69 368
IB-MVS85.98 2088.63 32686.95 33593.68 30195.12 34284.82 33090.85 34190.17 36087.55 30688.48 36091.34 35958.01 37199.59 16087.24 32493.80 35496.63 333
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 33286.77 33691.39 33593.18 36278.62 35795.10 21991.42 34785.58 32488.00 36188.73 36760.60 37098.90 29990.60 27287.70 36696.65 330
PVSNet_081.89 2184.49 33783.21 34088.34 34995.76 33174.97 37183.49 36592.70 33978.47 36087.94 36286.90 36983.38 30296.63 36773.44 36766.86 37393.40 360
EPNet93.72 26392.62 28097.03 16887.61 37792.25 20696.27 14691.28 34996.74 9087.65 36397.39 20085.00 29299.64 14192.14 23299.48 12399.20 132
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CHOSEN 280x42089.98 31589.19 32192.37 32895.60 33481.13 35286.22 36397.09 27581.44 34987.44 36493.15 33373.99 34399.47 19588.69 30499.07 21496.52 335
baseline289.65 32088.44 32793.25 30995.62 33382.71 34193.82 27985.94 36888.89 29387.35 36592.54 34771.23 35799.33 24086.01 32994.60 35197.72 294
gg-mvs-nofinetune88.28 32986.96 33492.23 33192.84 36884.44 33398.19 4574.60 37599.08 1087.01 36699.47 856.93 37398.23 35078.91 35995.61 34294.01 357
ET-MVSNet_ETH3D91.12 30489.67 31695.47 24696.41 30989.15 26191.54 32790.23 35989.07 28986.78 36792.84 34269.39 36299.44 20594.16 19096.61 32897.82 290
PAPM87.64 33485.84 33993.04 31496.54 30584.99 32788.42 36095.57 31079.52 35683.82 36893.05 34080.57 31498.41 34062.29 37292.79 35695.71 345
GG-mvs-BLEND90.60 34091.00 37284.21 33698.23 3972.63 37882.76 36984.11 37056.14 37696.79 36472.20 36892.09 35990.78 367
MVEpermissive73.61 2286.48 33685.92 33888.18 35096.23 31585.28 32281.78 36875.79 37486.01 31882.53 37091.88 35392.74 19987.47 37371.42 37094.86 34891.78 364
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
EPNet_dtu91.39 30390.75 30693.31 30790.48 37482.61 34294.80 23992.88 33593.39 22381.74 37194.90 31681.36 30999.11 27788.28 31098.87 23598.21 263
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
DeepMVS_CXcopyleft77.17 35490.94 37385.28 32274.08 37752.51 37180.87 37288.03 36875.25 34170.63 37459.23 37384.94 36975.62 369
tmp_tt57.23 34062.50 34341.44 35634.77 37949.21 37983.93 36460.22 38015.31 37271.11 37379.37 37170.09 36144.86 37564.76 37182.93 37130.25 371
test_method66.88 33966.13 34269.11 35562.68 37825.73 38049.76 36996.04 29814.32 37364.27 37491.69 35673.45 35088.05 37276.06 36566.94 37293.54 358
EGC-MVSNET83.08 33877.93 34198.53 5199.57 1697.55 2798.33 3298.57 1614.71 37410.38 37598.90 5095.60 12199.50 18795.69 10699.61 7598.55 231
testmvs12.33 34315.23 3463.64 3585.77 3812.23 38288.99 3573.62 3812.30 3765.29 37613.09 3734.52 3811.95 3765.16 3758.32 3756.75 373
test12312.59 34215.49 3453.87 3576.07 3802.55 38190.75 3422.59 3822.52 3755.20 37713.02 3744.96 3801.85 3775.20 3749.09 3747.23 372
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
cdsmvs_eth3d_5k24.22 34132.30 3440.00 3590.00 3820.00 3830.00 37098.10 2200.00 3770.00 37895.06 31197.54 290.00 3780.00 3760.00 3760.00 374
pcd_1.5k_mvsjas7.98 34410.65 3470.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 37795.82 1080.00 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
ab-mvs-re7.91 34510.55 3480.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 37894.94 3130.00 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
MSC_two_6792asdad98.22 7597.75 24395.34 10998.16 21399.75 6595.87 10099.51 11199.57 32
No_MVS98.22 7597.75 24395.34 10998.16 21399.75 6595.87 10099.51 11199.57 32
eth-test20.00 382
eth-test0.00 382
OPU-MVS97.64 12098.01 20295.27 11296.79 12297.35 20596.97 5698.51 33691.21 25399.25 18799.14 143
save fliter98.48 15494.71 13394.53 24998.41 17995.02 174
test_0728_SECOND98.25 7399.23 5695.49 10096.74 12598.89 7999.75 6595.48 12199.52 10699.53 41
GSMVS98.06 275
sam_mvs177.80 32598.06 275
sam_mvs77.38 329
MTGPAbinary98.73 129
test_post194.98 23110.37 37676.21 33799.04 28589.47 293
test_post10.87 37576.83 33399.07 282
patchmatchnet-post96.84 23877.36 33099.42 208
MTMP96.55 13374.60 375
gm-plane-assit91.79 37171.40 37581.67 34690.11 36698.99 29184.86 342
test9_res91.29 24998.89 23499.00 171
agg_prior290.34 28298.90 23199.10 159
test_prior495.38 10493.61 287
test_prior97.46 14097.79 23594.26 15398.42 17799.34 23798.79 205
新几何293.43 290
旧先验197.80 22993.87 16597.75 24497.04 22693.57 18398.68 25398.72 215
无先验93.20 29997.91 23380.78 35199.40 21987.71 31497.94 284
原ACMM292.82 304
testdata299.46 19887.84 313
segment_acmp95.34 131
testdata192.77 30593.78 214
plane_prior798.70 12594.67 137
plane_prior698.38 16294.37 14791.91 226
plane_prior598.75 12599.46 19892.59 22899.20 19299.28 115
plane_prior496.77 244
plane_prior296.50 13596.36 106
plane_prior198.49 152
plane_prior94.29 14995.42 19694.31 19898.93 229
n20.00 383
nn0.00 383
door-mid98.17 210
test1198.08 223
door97.81 242
HQP5-MVS92.47 202
BP-MVS90.51 277
HQP3-MVS98.43 17498.74 249
HQP2-MVS90.33 243
NP-MVS98.14 19193.72 17395.08 309
ACMMP++_ref99.52 106
ACMMP++99.55 95
Test By Simon94.51 160