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

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

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

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

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




Method Infoallhigh-res
multi-view
indooroutdoorbotani.boulde.bridgedoorexhibi.lectur.living.loungeobserv.old co.statueterrac.
sort bysort bysort bysort bysort bysort bysorted bysort bysort bysort bysort bysort bysort bysort bysort bysort by
DVP-MVS++99.08 298.89 299.64 399.17 10399.23 799.69 198.88 5197.32 3399.53 999.47 1097.81 399.94 498.47 2299.72 5499.74 37
FOURS199.82 198.66 2699.69 198.95 3597.46 2399.39 15
CS-MVS98.44 4298.49 2098.31 11299.08 11396.73 11999.67 398.47 17897.17 4698.94 4599.10 7895.73 4999.13 18798.71 799.49 9699.09 157
CS-MVS-test98.49 3798.50 1798.46 10199.20 10197.05 10599.64 498.50 17297.45 2598.88 5399.14 7295.25 7299.15 18498.83 599.56 8699.20 139
DROMVSNet98.21 6098.11 5398.49 9898.34 17697.26 9999.61 598.43 18696.78 6598.87 5498.84 11793.72 10699.01 20798.91 399.50 9599.19 143
RRT_MVS95.98 15895.78 15296.56 23496.48 30294.22 24099.57 697.92 27195.89 10393.95 25398.70 13389.27 18898.42 27497.23 9493.02 26797.04 239
mvsmamba96.57 13596.32 13297.32 17796.60 29396.43 13599.54 797.98 26496.49 7895.20 20698.64 14190.82 15898.55 25697.97 4593.65 25196.98 244
HPM-MVScopyleft98.36 4898.10 5499.13 5799.74 897.82 7799.53 898.80 9194.63 16898.61 7498.97 9795.13 7799.77 10597.65 7299.83 1199.79 13
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
test_low_dy_conf_00196.06 15495.86 14896.69 21896.39 30694.58 22599.47 998.26 21895.68 11395.23 20598.73 13088.90 20398.47 26796.43 13693.62 25397.02 241
MVSFormer97.57 8897.49 8097.84 14198.07 19995.76 17199.47 998.40 19094.98 15298.79 5898.83 11992.34 12098.41 28296.91 10799.59 7799.34 121
test_djsdf96.00 15795.69 16196.93 20295.72 33195.49 18199.47 998.40 19094.98 15294.58 22097.86 21889.16 19298.41 28296.91 10794.12 23896.88 260
HPM-MVS_fast98.38 4698.13 5199.12 6099.75 497.86 7399.44 1298.82 7494.46 17598.94 4599.20 5995.16 7699.74 11197.58 7799.85 599.77 23
nrg03096.28 14795.72 15597.96 13796.90 27898.15 6199.39 1398.31 20595.47 12494.42 23098.35 17492.09 13098.69 24197.50 8689.05 31597.04 239
APDe-MVS99.02 498.84 499.55 999.57 3598.96 1699.39 1398.93 3997.38 3099.41 1399.54 196.66 1799.84 5798.86 499.85 599.87 1
3Dnovator+94.38 697.43 9796.78 11299.38 2097.83 21498.52 3299.37 1598.71 11897.09 5392.99 28999.13 7389.36 18599.89 3996.97 10399.57 8199.71 50
FIs96.51 13796.12 13997.67 15897.13 26597.54 8799.36 1699.22 1595.89 10394.03 25198.35 17491.98 13398.44 27296.40 13892.76 27097.01 242
FC-MVSNet-test96.42 14096.05 14297.53 16796.95 27397.27 9599.36 1699.23 1395.83 10793.93 25498.37 17292.00 13298.32 29196.02 14992.72 27197.00 243
3Dnovator94.51 597.46 9296.93 10599.07 6397.78 21697.64 8299.35 1899.06 2397.02 5593.75 26499.16 6889.25 18999.92 2597.22 9599.75 4299.64 76
GeoE96.58 13496.07 14198.10 12898.35 17195.89 16799.34 1998.12 24093.12 23596.09 19198.87 11389.71 17998.97 20992.95 24598.08 16599.43 115
canonicalmvs97.67 7997.23 9298.98 6898.70 14798.38 4099.34 1998.39 19296.76 6797.67 13097.40 25792.26 12399.49 15398.28 3596.28 21499.08 161
CP-MVS98.57 2798.36 2799.19 4699.66 2897.86 7399.34 1998.87 5895.96 10198.60 7599.13 7396.05 3699.94 497.77 6299.86 199.77 23
EPP-MVSNet97.46 9297.28 9097.99 13498.64 15395.38 18599.33 2298.31 20593.61 21697.19 14599.07 8794.05 10199.23 17596.89 11198.43 15499.37 120
XVS98.70 1098.49 2099.34 2699.70 2498.35 4899.29 2398.88 5197.40 2798.46 7999.20 5995.90 4499.89 3997.85 5699.74 4599.78 16
X-MVStestdata94.06 27692.30 29699.34 2699.70 2498.35 4899.29 2398.88 5197.40 2798.46 7943.50 37695.90 4499.89 3997.85 5699.74 4599.78 16
tttt051796.07 15395.51 16797.78 14798.41 16894.84 20999.28 2594.33 36494.26 18097.64 13498.64 14184.05 29899.47 15995.34 17197.60 18299.03 164
mPP-MVS98.51 3698.26 4299.25 4299.75 498.04 6599.28 2598.81 8096.24 8898.35 8999.23 5295.46 5799.94 497.42 8899.81 1299.77 23
MSP-MVS98.74 998.55 1399.29 3499.75 498.23 5499.26 2798.88 5197.52 1799.41 1398.78 12496.00 3899.79 9697.79 6199.59 7799.85 4
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
v7n94.19 26593.43 27696.47 24595.90 32694.38 23399.26 2798.34 20191.99 27392.76 29497.13 27188.31 21598.52 26189.48 31487.70 33096.52 308
WR-MVS_H95.05 21394.46 21796.81 21196.86 28095.82 16999.24 2999.24 1193.87 19692.53 30296.84 30490.37 16898.24 30193.24 23587.93 32896.38 320
HFP-MVS98.63 1798.40 2399.32 3199.72 1398.29 5199.23 3098.96 3396.10 9698.94 4599.17 6396.06 3499.92 2597.62 7499.78 2799.75 32
region2R98.61 1898.38 2599.29 3499.74 898.16 6099.23 3098.93 3996.15 9198.94 4599.17 6395.91 4399.94 497.55 8299.79 2399.78 16
ACMMPR98.59 2198.36 2799.29 3499.74 898.15 6199.23 3098.95 3596.10 9698.93 5099.19 6295.70 5099.94 497.62 7499.79 2399.78 16
QAPM96.29 14595.40 16898.96 7097.85 21397.60 8599.23 3098.93 3989.76 32693.11 28699.02 9089.11 19499.93 1991.99 27299.62 7299.34 121
MP-MVScopyleft98.33 5498.01 5899.28 3899.75 498.18 5899.22 3498.79 9696.13 9397.92 11799.23 5294.54 9099.94 496.74 12699.78 2799.73 42
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
Vis-MVSNetpermissive97.42 9897.11 9698.34 11098.66 15196.23 14499.22 3499.00 2896.63 7398.04 10199.21 5588.05 22399.35 16696.01 15099.21 11599.45 113
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
CSCG97.85 7297.74 6898.20 12099.67 2795.16 19399.22 3499.32 793.04 23797.02 15498.92 10995.36 6499.91 3497.43 8799.64 6899.52 94
bld_raw_conf00595.91 16595.56 16596.99 19596.51 29995.46 18299.21 3797.42 30796.41 8494.10 24698.63 14386.59 25198.54 25897.56 8193.59 25696.96 247
OpenMVScopyleft93.04 1395.83 16995.00 19298.32 11197.18 26297.32 9399.21 3798.97 3189.96 32291.14 32399.05 8986.64 25099.92 2593.38 23099.47 9997.73 222
DTE-MVSNet93.98 27893.26 28196.14 26496.06 32194.39 23299.20 3998.86 6493.06 23691.78 31797.81 22685.87 26597.58 33690.53 29486.17 34596.46 317
Vis-MVSNet (Re-imp)96.87 12396.55 12497.83 14298.73 14295.46 18299.20 3998.30 21194.96 15496.60 17398.87 11390.05 17398.59 25293.67 22498.60 14399.46 111
ZNCC-MVS98.49 3798.20 4999.35 2599.73 1298.39 3999.19 4198.86 6495.77 10998.31 9299.10 7895.46 5799.93 1997.57 8099.81 1299.74 37
IS-MVSNet97.22 10796.88 10798.25 11798.85 13596.36 13999.19 4197.97 26695.39 12897.23 14498.99 9691.11 15498.93 21894.60 19398.59 14499.47 107
PEN-MVS94.42 25293.73 26396.49 24396.28 31294.84 20999.17 4399.00 2893.51 21892.23 31197.83 22486.10 26197.90 32592.55 25886.92 34096.74 276
PS-MVSNAJss96.43 13996.26 13596.92 20595.84 32995.08 19899.16 4498.50 17295.87 10693.84 26098.34 17894.51 9198.61 24996.88 11493.45 26097.06 238
dcpmvs_298.08 6198.59 1096.56 23499.57 3590.34 32099.15 4598.38 19596.82 6499.29 2099.49 795.78 4899.57 13998.94 299.86 199.77 23
APD-MVS_3200maxsize98.53 3598.33 3799.15 5699.50 4597.92 7299.15 4598.81 8096.24 8899.20 2699.37 2695.30 6899.80 8497.73 6499.67 6099.72 46
TSAR-MVS + MP.98.78 798.62 999.24 4399.69 2698.28 5399.14 4798.66 13696.84 6299.56 699.31 3996.34 2399.70 11998.32 3399.73 4799.73 42
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
anonymousdsp95.42 18994.91 19796.94 20195.10 34495.90 16699.14 4798.41 18893.75 20193.16 28297.46 25187.50 23798.41 28295.63 16694.03 24096.50 313
jajsoiax95.45 18795.03 19196.73 21495.42 34294.63 21899.14 4798.52 16495.74 11093.22 28098.36 17383.87 30398.65 24796.95 10694.04 23996.91 256
PS-CasMVS94.67 23593.99 24396.71 21596.68 29095.26 19199.13 5099.03 2693.68 21192.33 30997.95 21085.35 27598.10 30993.59 22688.16 32796.79 271
abl_698.30 5798.03 5799.13 5799.56 3797.76 8099.13 5098.82 7496.14 9299.26 2299.37 2693.33 10999.93 1996.96 10599.67 6099.69 57
bld_raw_dy_0_6495.74 17395.31 17997.03 19396.35 30995.76 17199.12 5297.37 31095.97 10094.70 21898.48 15885.80 26698.49 26396.55 13093.48 25796.84 267
CPTT-MVS97.72 7797.32 8998.92 7299.64 3097.10 10499.12 5298.81 8092.34 26198.09 9799.08 8693.01 11399.92 2596.06 14799.77 3099.75 32
SR-MVS-dyc-post98.54 3398.35 2999.13 5799.49 4997.86 7399.11 5498.80 9196.49 7899.17 3099.35 3295.34 6599.82 6897.72 6599.65 6499.71 50
RE-MVS-def98.34 3399.49 4997.86 7399.11 5498.80 9196.49 7899.17 3099.35 3295.29 6997.72 6599.65 6499.71 50
CP-MVSNet94.94 22294.30 22596.83 20996.72 28895.56 17799.11 5498.95 3593.89 19492.42 30897.90 21487.19 24198.12 30894.32 20388.21 32596.82 270
SteuartSystems-ACMMP98.90 698.75 699.36 2499.22 9898.43 3899.10 5798.87 5897.38 3099.35 1799.40 1797.78 599.87 4897.77 6299.85 599.78 16
Skip Steuart: Steuart Systems R&D Blog.
test117298.56 2998.35 2999.16 5399.53 3997.94 7199.09 5898.83 7296.52 7799.05 3899.34 3595.34 6599.82 6897.86 5599.64 6899.73 42
SR-MVS98.57 2798.35 2999.24 4399.53 3998.18 5899.09 5898.82 7496.58 7499.10 3599.32 3795.39 6199.82 6897.70 7099.63 7099.72 46
GST-MVS98.43 4398.12 5299.34 2699.72 1398.38 4099.09 5898.82 7495.71 11298.73 6499.06 8895.27 7099.93 1997.07 10099.63 7099.72 46
iter_conf_final96.42 14096.12 13997.34 17698.46 16596.55 13099.08 6198.06 25896.03 9895.63 19998.46 16287.72 23098.59 25297.84 5893.80 24796.87 262
K. test v392.55 30091.91 30294.48 31995.64 33389.24 33499.07 6294.88 35894.04 18586.78 35197.59 24377.64 34497.64 33492.08 26789.43 31096.57 298
test250694.44 25193.91 24896.04 26799.02 11888.99 34099.06 6379.47 38396.96 5898.36 8799.26 4777.21 34699.52 15196.78 12499.04 12199.59 87
test072699.72 1399.25 299.06 6398.88 5197.62 1299.56 699.50 597.42 9
v894.47 24993.77 25996.57 23396.36 30894.83 21199.05 6598.19 22591.92 27593.16 28296.97 29288.82 20698.48 26491.69 27987.79 32996.39 319
test111195.94 16295.78 15296.41 25198.99 12490.12 32299.04 6692.45 37296.99 5798.03 10299.27 4681.40 31599.48 15796.87 11799.04 12199.63 79
SF-MVS98.59 2198.32 3899.41 1999.54 3898.71 2299.04 6698.81 8095.12 14499.32 1899.39 1896.22 2499.84 5797.72 6599.73 4799.67 67
PHI-MVS98.34 5298.06 5599.18 5099.15 10998.12 6399.04 6699.09 2193.32 22698.83 5799.10 7896.54 2099.83 6097.70 7099.76 3699.59 87
ECVR-MVScopyleft95.95 16095.71 15896.65 22199.02 11890.86 30999.03 6991.80 37396.96 5898.10 9699.26 4781.31 31699.51 15296.90 11099.04 12199.59 87
test_part194.82 22593.82 25497.82 14498.84 13697.82 7799.03 6998.81 8092.31 26592.51 30497.89 21681.96 31198.67 24594.80 18888.24 32496.98 244
TranMVSNet+NR-MVSNet95.14 20894.48 21597.11 18996.45 30496.36 13999.03 6999.03 2695.04 15093.58 26797.93 21288.27 21698.03 31694.13 20986.90 34196.95 250
ACMMPcopyleft98.23 5897.95 6199.09 6299.74 897.62 8499.03 6999.41 695.98 9997.60 13799.36 3094.45 9599.93 1997.14 9798.85 13399.70 54
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
SED-MVS99.09 198.91 199.63 499.71 2199.24 599.02 7398.87 5897.65 1099.73 199.48 897.53 799.94 498.43 2699.81 1299.70 54
OPU-MVS99.37 2399.24 9699.05 1499.02 7399.16 6897.81 399.37 16597.24 9399.73 4799.70 54
EIA-MVS97.75 7597.58 7298.27 11498.38 16996.44 13499.01 7598.60 14695.88 10597.26 14397.53 24894.97 8199.33 16897.38 9099.20 11699.05 163
Anonymous2023121194.10 27293.26 28196.61 22799.11 11294.28 23599.01 7598.88 5186.43 34792.81 29297.57 24581.66 31498.68 24494.83 18589.02 31796.88 260
mvs_tets95.41 19195.00 19296.65 22195.58 33594.42 23099.00 7798.55 15895.73 11193.21 28198.38 17183.45 30798.63 24897.09 9994.00 24196.91 256
baseline97.64 8197.44 8498.25 11798.35 17196.20 14599.00 7798.32 20396.33 8798.03 10299.17 6391.35 14899.16 18198.10 3998.29 16099.39 118
v1094.29 25993.55 27196.51 24296.39 30694.80 21398.99 7998.19 22591.35 29393.02 28896.99 29088.09 22198.41 28290.50 29588.41 32396.33 323
PGM-MVS98.49 3798.23 4799.27 4199.72 1398.08 6498.99 7999.49 595.43 12699.03 3999.32 3795.56 5399.94 496.80 12299.77 3099.78 16
LPG-MVS_test95.62 18195.34 17496.47 24597.46 24093.54 25998.99 7998.54 16094.67 16594.36 23298.77 12685.39 27399.11 19195.71 16294.15 23696.76 274
#test#98.54 3398.27 4199.32 3199.72 1398.29 5198.98 8298.96 3395.65 11798.94 4599.17 6396.06 3499.92 2597.21 9699.78 2799.75 32
DVP-MVScopyleft99.03 398.83 599.63 499.72 1399.25 298.97 8398.58 15397.62 1299.45 1199.46 1397.42 999.94 498.47 2299.81 1299.69 57
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_SECOND99.71 199.72 1399.35 198.97 8398.88 5199.94 498.47 2299.81 1299.84 6
tfpnnormal93.66 28192.70 29096.55 23996.94 27495.94 16098.97 8399.19 1691.04 30591.38 32197.34 25884.94 28198.61 24985.45 34289.02 31795.11 348
V4294.78 22894.14 23396.70 21796.33 31195.22 19298.97 8398.09 25092.32 26394.31 23597.06 28288.39 21498.55 25692.90 24788.87 31996.34 321
SMA-MVScopyleft98.58 2498.25 4399.56 899.51 4399.04 1598.95 8798.80 9193.67 21399.37 1699.52 396.52 2199.89 3998.06 4199.81 1299.76 30
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
pm-mvs193.94 27993.06 28396.59 23096.49 30195.16 19398.95 8798.03 26192.32 26391.08 32497.84 22184.54 28998.41 28292.16 26586.13 34796.19 328
Anonymous2024052191.18 31090.44 31193.42 33093.70 35988.47 34798.94 8997.56 28988.46 33889.56 33895.08 34777.15 34896.97 34683.92 35089.55 30794.82 353
VPA-MVSNet95.75 17295.11 18897.69 15697.24 25497.27 9598.94 8999.23 1395.13 14395.51 20197.32 26085.73 26798.91 22097.33 9289.55 30796.89 259
LS3D97.16 11296.66 12198.68 8298.53 16197.19 10298.93 9198.90 4692.83 24695.99 19599.37 2692.12 12999.87 4893.67 22499.57 8198.97 170
ACMM93.85 995.69 17895.38 17296.61 22797.61 22793.84 24898.91 9298.44 18395.25 13894.28 23698.47 16086.04 26499.12 18995.50 16993.95 24396.87 262
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
MTAPA98.58 2498.29 4099.46 1599.76 298.64 2798.90 9398.74 10897.27 4098.02 10499.39 1894.81 8499.96 297.91 4999.79 2399.77 23
SD-MVS98.64 1598.68 798.53 9499.33 6998.36 4798.90 9398.85 6897.28 3699.72 399.39 1896.63 1997.60 33598.17 3699.85 599.64 76
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
TransMVSNet (Re)92.67 29991.51 30496.15 26396.58 29594.65 21698.90 9396.73 33990.86 30789.46 33997.86 21885.62 26998.09 31186.45 33481.12 35695.71 338
EPNet97.28 10596.87 10898.51 9594.98 34596.14 14898.90 9397.02 32698.28 195.99 19599.11 7691.36 14799.89 3996.98 10299.19 11799.50 100
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
MTMP98.89 9794.14 367
UA-Net97.96 6497.62 7098.98 6898.86 13397.47 8998.89 9799.08 2296.67 7198.72 6599.54 193.15 11299.81 7594.87 18398.83 13499.65 73
OurMVSNet-221017-094.21 26394.00 24194.85 30795.60 33489.22 33598.89 9797.43 30595.29 13592.18 31298.52 15682.86 30898.59 25293.46 22991.76 27996.74 276
thisisatest053096.01 15695.36 17397.97 13598.38 16995.52 18098.88 10094.19 36694.04 18597.64 13498.31 18183.82 30599.46 16095.29 17597.70 17998.93 174
iter_conf0596.13 15295.79 15197.15 18598.16 19495.99 15198.88 10097.98 26495.91 10295.58 20098.46 16285.53 27198.59 25297.88 5393.75 24896.86 265
UGNet96.78 12696.30 13398.19 12298.24 18395.89 16798.88 10098.93 3997.39 2996.81 16597.84 22182.60 30999.90 3796.53 13199.49 9698.79 181
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
Anonymous2024052995.10 21094.22 22797.75 15099.01 12094.26 23798.87 10398.83 7285.79 35396.64 17098.97 9778.73 33399.85 5496.27 14094.89 22799.12 154
thres100view90095.38 19294.70 20597.41 17198.98 12594.92 20798.87 10396.90 33295.38 12996.61 17296.88 30084.29 29199.56 14288.11 32396.29 21197.76 219
XXY-MVS95.20 20594.45 21997.46 16896.75 28696.56 12898.86 10598.65 14093.30 22893.27 27998.27 18684.85 28398.87 22794.82 18691.26 28796.96 247
VDDNet95.36 19594.53 21297.86 14098.10 19895.13 19698.85 10697.75 27990.46 31298.36 8799.39 1873.27 36199.64 13097.98 4496.58 20198.81 180
thres600view795.49 18494.77 20197.67 15898.98 12595.02 19998.85 10696.90 33295.38 12996.63 17196.90 29984.29 29199.59 13788.65 32296.33 20998.40 201
114514_t96.93 12096.27 13498.92 7299.50 4597.63 8398.85 10698.90 4684.80 35697.77 12299.11 7692.84 11499.66 12794.85 18499.77 3099.47 107
LFMVS95.86 16794.98 19498.47 10098.87 13296.32 14198.84 10996.02 34693.40 22398.62 7399.20 5974.99 35599.63 13397.72 6597.20 18899.46 111
testtj98.33 5497.95 6199.47 1499.49 4998.70 2398.83 11098.86 6495.48 12398.91 5299.17 6395.48 5699.93 1995.80 15799.53 9299.76 30
alignmvs97.56 8997.07 9999.01 6598.66 15198.37 4698.83 11098.06 25896.74 6898.00 11097.65 23790.80 16199.48 15798.37 3196.56 20299.19 143
DeepC-MVS95.98 397.88 7097.58 7298.77 7899.25 9096.93 11098.83 11098.75 10696.96 5896.89 16199.50 590.46 16799.87 4897.84 5899.76 3699.52 94
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
ACMMP_NAP98.61 1898.30 3999.55 999.62 3298.95 1798.82 11398.81 8095.80 10899.16 3299.47 1095.37 6399.92 2597.89 5299.75 4299.79 13
casdiffmvs97.63 8297.41 8598.28 11398.33 17896.14 14898.82 11398.32 20396.38 8597.95 11299.21 5591.23 15299.23 17598.12 3898.37 15599.48 105
GBi-Net94.49 24793.80 25696.56 23498.21 18695.00 20098.82 11398.18 22892.46 25494.09 24797.07 27981.16 31797.95 32192.08 26792.14 27496.72 279
test194.49 24793.80 25696.56 23498.21 18695.00 20098.82 11398.18 22892.46 25494.09 24797.07 27981.16 31797.95 32192.08 26792.14 27496.72 279
FMVSNet193.19 29392.07 29896.56 23497.54 23495.00 20098.82 11398.18 22890.38 31592.27 31097.07 27973.68 36097.95 32189.36 31691.30 28596.72 279
API-MVS97.41 9997.25 9197.91 13898.70 14796.80 11598.82 11398.69 12294.53 17098.11 9598.28 18394.50 9499.57 13994.12 21099.49 9697.37 232
ACMH92.88 1694.55 24293.95 24596.34 25797.63 22693.26 27298.81 11998.49 17793.43 22289.74 33598.53 15381.91 31299.08 19693.69 22193.30 26496.70 283
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
Effi-MVS+-dtu96.29 14596.56 12395.51 28697.89 21190.22 32198.80 12098.10 24596.57 7596.45 18496.66 31090.81 15998.91 22095.72 16097.99 16797.40 229
HQP_MVS96.14 15195.90 14796.85 20897.42 24594.60 22398.80 12098.56 15697.28 3695.34 20298.28 18387.09 24299.03 20296.07 14494.27 23096.92 251
plane_prior298.80 12097.28 36
APD-MVScopyleft98.35 5098.00 5999.42 1899.51 4398.72 2198.80 12098.82 7494.52 17299.23 2499.25 5095.54 5599.80 8496.52 13299.77 3099.74 37
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
UniMVSNet (Re)95.78 17195.19 18497.58 16496.99 27297.47 8998.79 12499.18 1795.60 11893.92 25597.04 28591.68 13898.48 26495.80 15787.66 33196.79 271
FMVSNet294.47 24993.61 26997.04 19298.21 18696.43 13598.79 12498.27 21492.46 25493.50 27397.09 27681.16 31798.00 31991.09 28491.93 27796.70 283
testgi93.06 29592.45 29494.88 30696.43 30589.90 32398.75 12697.54 29595.60 11891.63 32097.91 21374.46 35897.02 34586.10 33693.67 24997.72 223
LCM-MVSNet-Re95.22 20395.32 17794.91 30498.18 19187.85 35598.75 12695.66 35295.11 14588.96 34196.85 30390.26 17297.65 33395.65 16598.44 15299.22 138
SixPastTwentyTwo93.34 28792.86 28694.75 31195.67 33289.41 33398.75 12696.67 34393.89 19490.15 33398.25 18880.87 32198.27 30090.90 28990.64 29396.57 298
UniMVSNet_ETH3D94.24 26293.33 27896.97 19997.19 26193.38 26898.74 12998.57 15491.21 30293.81 26198.58 14972.85 36298.77 23895.05 18193.93 24498.77 183
MVS_Test97.28 10597.00 10298.13 12598.33 17895.97 15798.74 12998.07 25394.27 17998.44 8398.07 19992.48 11899.26 17196.43 13698.19 16199.16 149
UniMVSNet_NR-MVSNet95.71 17595.15 18597.40 17396.84 28196.97 10898.74 12999.24 1195.16 14293.88 25797.72 23291.68 13898.31 29395.81 15587.25 33696.92 251
NR-MVSNet94.98 21894.16 23197.44 16996.53 29797.22 10198.74 12998.95 3594.96 15489.25 34097.69 23389.32 18698.18 30394.59 19587.40 33496.92 251
ETV-MVS97.96 6497.81 6598.40 10798.42 16797.27 9598.73 13398.55 15896.84 6298.38 8697.44 25495.39 6199.35 16697.62 7498.89 12998.58 196
baseline195.84 16895.12 18798.01 13398.49 16495.98 15298.73 13397.03 32495.37 13196.22 18898.19 19289.96 17599.16 18194.60 19387.48 33298.90 176
MVSTER96.06 15495.72 15597.08 19198.23 18495.93 16398.73 13398.27 21494.86 15895.07 20798.09 19888.21 21798.54 25896.59 12893.46 25896.79 271
ACMP93.49 1095.34 19794.98 19496.43 25097.67 22393.48 26398.73 13398.44 18394.94 15792.53 30298.53 15384.50 29099.14 18695.48 17094.00 24196.66 289
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
HPM-MVS++copyleft98.58 2498.25 4399.55 999.50 4599.08 1198.72 13798.66 13697.51 1898.15 9398.83 11995.70 5099.92 2597.53 8499.67 6099.66 71
9.1498.06 5599.47 5298.71 13898.82 7494.36 17799.16 3299.29 4396.05 3699.81 7597.00 10199.71 56
VPNet94.99 21694.19 22997.40 17397.16 26396.57 12798.71 13898.97 3195.67 11594.84 21298.24 18980.36 32598.67 24596.46 13387.32 33596.96 247
MSLP-MVS++98.56 2998.57 1198.55 9099.26 8996.80 11598.71 13899.05 2597.28 3698.84 5599.28 4496.47 2299.40 16398.52 2099.70 5799.47 107
ACMH+92.99 1494.30 25893.77 25995.88 27797.81 21592.04 28998.71 13898.37 19693.99 19090.60 32998.47 16080.86 32299.05 19892.75 25192.40 27396.55 302
Anonymous20240521195.28 20094.49 21497.67 15899.00 12193.75 25298.70 14297.04 32390.66 30896.49 18198.80 12278.13 33899.83 6096.21 14395.36 22699.44 114
DP-MVS96.59 13295.93 14698.57 8899.34 6696.19 14798.70 14298.39 19289.45 33194.52 22299.35 3291.85 13599.85 5492.89 24998.88 13099.68 63
Fast-Effi-MVS+-dtu95.87 16695.85 14995.91 27497.74 22091.74 29598.69 14498.15 23695.56 12094.92 21097.68 23688.98 20098.79 23693.19 23797.78 17597.20 236
tfpn200view995.32 19994.62 20897.43 17098.94 12794.98 20398.68 14596.93 33095.33 13296.55 17696.53 31684.23 29499.56 14288.11 32396.29 21197.76 219
VDD-MVS95.82 17095.23 18297.61 16398.84 13693.98 24498.68 14597.40 30895.02 15197.95 11299.34 3574.37 35999.78 10098.64 896.80 19499.08 161
thres40095.38 19294.62 20897.65 16198.94 12794.98 20398.68 14596.93 33095.33 13296.55 17696.53 31684.23 29499.56 14288.11 32396.29 21198.40 201
ETH3D-3000-0.198.35 5098.00 5999.38 2099.47 5298.68 2598.67 14898.84 6994.66 16799.11 3499.25 5095.46 5799.81 7596.80 12299.73 4799.63 79
pmmvs691.77 30590.63 30995.17 29794.69 35291.24 30598.67 14897.92 27186.14 34989.62 33697.56 24775.79 35298.34 28990.75 29284.56 34995.94 334
v2v48294.69 23094.03 23796.65 22196.17 31694.79 21498.67 14898.08 25192.72 24794.00 25297.16 27087.69 23498.45 27092.91 24688.87 31996.72 279
DU-MVS95.42 18994.76 20297.40 17396.53 29796.97 10898.66 15198.99 3095.43 12693.88 25797.69 23388.57 20998.31 29395.81 15587.25 33696.92 251
MAR-MVS96.91 12196.40 12998.45 10298.69 14996.90 11298.66 15198.68 12592.40 26097.07 15197.96 20991.54 14499.75 10993.68 22298.92 12798.69 186
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
patch_mono-298.36 4898.87 396.82 21099.53 3990.68 31498.64 15399.29 897.88 599.19 2999.52 396.80 1599.97 199.11 199.86 199.82 10
h-mvs3396.17 15095.62 16497.81 14599.03 11794.45 22898.64 15398.75 10697.48 2098.67 6798.72 13289.76 17799.86 5397.95 4681.59 35599.11 155
VNet97.79 7497.40 8698.96 7098.88 13197.55 8698.63 15598.93 3996.74 6899.02 4098.84 11790.33 17099.83 6098.53 1496.66 19899.50 100
PVSNet_Blended_VisFu97.70 7897.46 8298.44 10399.27 8795.91 16598.63 15599.16 1894.48 17497.67 13098.88 11292.80 11599.91 3497.11 9899.12 11999.50 100
PAPM_NR97.46 9297.11 9698.50 9699.50 4596.41 13798.63 15598.60 14695.18 14197.06 15298.06 20094.26 9999.57 13993.80 22098.87 13299.52 94
Baseline_NR-MVSNet94.35 25593.81 25595.96 27296.20 31494.05 24398.61 15896.67 34391.44 28993.85 25997.60 24288.57 20998.14 30694.39 19986.93 33995.68 339
v114494.59 24093.92 24696.60 22996.21 31394.78 21598.59 15998.14 23891.86 27894.21 24197.02 28787.97 22498.41 28291.72 27889.57 30596.61 293
AllTest95.24 20294.65 20796.99 19599.25 9093.21 27498.59 15998.18 22891.36 29193.52 27098.77 12684.67 28699.72 11389.70 30997.87 17198.02 214
Fast-Effi-MVS+96.28 14795.70 16098.03 13298.29 18295.97 15798.58 16198.25 22091.74 27995.29 20497.23 26691.03 15799.15 18492.90 24797.96 16898.97 170
Anonymous2023120691.66 30691.10 30693.33 33394.02 35887.35 35798.58 16197.26 31690.48 31190.16 33296.31 32183.83 30496.53 35679.36 36289.90 30196.12 329
v14419294.39 25493.70 26596.48 24496.06 32194.35 23498.58 16198.16 23591.45 28894.33 23497.02 28787.50 23798.45 27091.08 28589.11 31496.63 291
v14894.29 25993.76 26195.91 27496.10 31992.93 27998.58 16197.97 26692.59 25293.47 27496.95 29688.53 21298.32 29192.56 25787.06 33896.49 314
COLMAP_ROBcopyleft93.27 1295.33 19894.87 19996.71 21599.29 8293.24 27398.58 16198.11 24389.92 32393.57 26899.10 7886.37 25799.79 9690.78 29198.10 16497.09 237
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
mvs-test196.60 13096.68 12096.37 25497.89 21191.81 29198.56 16698.10 24596.57 7596.52 18097.94 21190.81 15999.45 16195.72 16098.01 16697.86 218
FMVSNet394.97 21994.26 22697.11 18998.18 19196.62 12298.56 16698.26 21893.67 21394.09 24797.10 27284.25 29398.01 31792.08 26792.14 27496.70 283
zzz-MVS98.55 3198.25 4399.46 1599.76 298.64 2798.55 16898.74 10897.27 4098.02 10499.39 1894.81 8499.96 297.91 4999.79 2399.77 23
F-COLMAP97.09 11696.80 10997.97 13599.45 5994.95 20698.55 16898.62 14593.02 23896.17 19098.58 14994.01 10299.81 7593.95 21598.90 12899.14 152
v192192094.20 26493.47 27596.40 25395.98 32494.08 24298.52 17098.15 23691.33 29494.25 23897.20 26986.41 25698.42 27490.04 30389.39 31196.69 288
EU-MVSNet93.66 28194.14 23392.25 34295.96 32583.38 36598.52 17098.12 24094.69 16392.61 29998.13 19687.36 24096.39 35891.82 27590.00 30096.98 244
TAMVS97.02 11796.79 11197.70 15598.06 20195.31 19098.52 17098.31 20593.95 19297.05 15398.61 14493.49 10898.52 26195.33 17297.81 17399.29 132
LTVRE_ROB92.95 1594.60 23893.90 24996.68 22097.41 24894.42 23098.52 17098.59 14891.69 28291.21 32298.35 17484.87 28299.04 20191.06 28693.44 26196.60 294
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
TDRefinement91.06 31289.68 31795.21 29585.35 37491.49 30098.51 17497.07 32191.47 28788.83 34497.84 22177.31 34599.09 19592.79 25077.98 36295.04 350
v119294.32 25793.58 27096.53 24096.10 31994.45 22898.50 17598.17 23391.54 28694.19 24297.06 28286.95 24698.43 27390.14 29889.57 30596.70 283
test_040291.32 30890.27 31394.48 31996.60 29391.12 30698.50 17597.22 31786.10 35088.30 34696.98 29177.65 34397.99 32078.13 36692.94 26994.34 355
DeepC-MVS_fast96.70 198.55 3198.34 3399.18 5099.25 9098.04 6598.50 17598.78 9997.72 798.92 5199.28 4495.27 7099.82 6897.55 8299.77 3099.69 57
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
CNVR-MVS98.78 798.56 1299.45 1799.32 7298.87 1998.47 17898.81 8097.72 798.76 6199.16 6897.05 1399.78 10098.06 4199.66 6399.69 57
test_yl97.22 10796.78 11298.54 9298.73 14296.60 12598.45 17998.31 20594.70 16198.02 10498.42 16690.80 16199.70 11996.81 12096.79 19599.34 121
DCV-MVSNet97.22 10796.78 11298.54 9298.73 14296.60 12598.45 17998.31 20594.70 16198.02 10498.42 16690.80 16199.70 11996.81 12096.79 19599.34 121
NCCC98.61 1898.35 2999.38 2099.28 8698.61 2998.45 17998.76 10397.82 698.45 8298.93 10796.65 1899.83 6097.38 9099.41 10699.71 50
v124094.06 27693.29 28096.34 25796.03 32393.90 24698.44 18298.17 23391.18 30394.13 24597.01 28986.05 26298.42 27489.13 31989.50 30996.70 283
plane_prior94.60 22398.44 18296.74 6894.22 232
MP-MVS-pluss98.31 5697.92 6399.49 1299.72 1398.88 1898.43 18498.78 9994.10 18397.69 12999.42 1695.25 7299.92 2598.09 4099.80 1999.67 67
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
OPM-MVS95.69 17895.33 17696.76 21396.16 31894.63 21898.43 18498.39 19296.64 7295.02 20998.78 12485.15 27899.05 19895.21 17994.20 23396.60 294
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
DPE-MVScopyleft98.92 598.67 899.65 299.58 3499.20 998.42 18698.91 4597.58 1599.54 899.46 1397.10 1299.94 497.64 7399.84 1099.83 7
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
MCST-MVS98.65 1498.37 2699.48 1399.60 3398.87 1998.41 18798.68 12597.04 5498.52 7898.80 12296.78 1699.83 6097.93 4899.61 7399.74 37
Regformer-398.59 2198.50 1798.86 7699.43 6197.05 10598.40 18898.68 12597.43 2699.06 3799.31 3995.80 4799.77 10598.62 1099.76 3699.78 16
Regformer-498.64 1598.53 1498.99 6699.43 6197.37 9298.40 18898.79 9697.46 2399.09 3699.31 3995.86 4699.80 8498.64 899.76 3699.79 13
Regformer-198.66 1398.51 1699.12 6099.35 6497.81 7998.37 19098.76 10397.49 1999.20 2699.21 5596.08 3399.79 9698.42 2899.73 4799.75 32
Regformer-298.69 1298.52 1599.19 4699.35 6498.01 6798.37 19098.81 8097.48 2099.21 2599.21 5596.13 3199.80 8498.40 3099.73 4799.75 32
hse-mvs295.71 17595.30 18096.93 20298.50 16293.53 26198.36 19298.10 24597.48 2098.67 6797.99 20689.76 17799.02 20597.95 4680.91 35998.22 208
CANet98.05 6297.76 6798.90 7498.73 14297.27 9598.35 19398.78 9997.37 3297.72 12798.96 10391.53 14599.92 2598.79 699.65 6499.51 98
AUN-MVS94.53 24493.73 26396.92 20598.50 16293.52 26298.34 19498.10 24593.83 19995.94 19797.98 20885.59 27099.03 20294.35 20180.94 35898.22 208
ETH3D cwj APD-0.1697.96 6497.52 7799.29 3499.05 11498.52 3298.33 19598.68 12593.18 23198.68 6699.13 7394.62 8899.83 6096.45 13499.55 9099.52 94
test20.0390.89 31490.38 31292.43 33993.48 36088.14 35298.33 19597.56 28993.40 22387.96 34796.71 30980.69 32494.13 36979.15 36386.17 34595.01 352
DP-MVS Recon97.86 7197.46 8299.06 6499.53 3998.35 4898.33 19598.89 4892.62 25098.05 9998.94 10695.34 6599.65 12896.04 14899.42 10599.19 143
RPSCF94.87 22495.40 16893.26 33598.89 13082.06 36998.33 19598.06 25890.30 31796.56 17499.26 4787.09 24299.49 15393.82 21996.32 21098.24 207
TAPA-MVS93.98 795.35 19694.56 21197.74 15199.13 11094.83 21198.33 19598.64 14186.62 34596.29 18798.61 14494.00 10399.29 17080.00 36099.41 10699.09 157
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
IterMVS-LS95.46 18595.21 18396.22 26298.12 19693.72 25598.32 20098.13 23993.71 20694.26 23797.31 26192.24 12498.10 30994.63 19090.12 29896.84 267
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
mvs_anonymous96.70 12896.53 12697.18 18398.19 18993.78 24998.31 20198.19 22594.01 18894.47 22498.27 18692.08 13198.46 26997.39 8997.91 16999.31 127
WTY-MVS97.37 10296.92 10698.72 8098.86 13396.89 11498.31 20198.71 11895.26 13797.67 13098.56 15292.21 12699.78 10095.89 15296.85 19399.48 105
D2MVS95.18 20695.08 18995.48 28797.10 26792.07 28798.30 20399.13 2094.02 18792.90 29096.73 30789.48 18298.73 24094.48 19893.60 25595.65 340
EI-MVSNet-Vis-set98.47 4098.39 2498.69 8199.46 5596.49 13298.30 20398.69 12297.21 4398.84 5599.36 3095.41 6099.78 10098.62 1099.65 6499.80 12
DSMNet-mixed92.52 30192.58 29292.33 34094.15 35482.65 36798.30 20394.26 36589.08 33592.65 29895.73 33685.01 28095.76 36186.24 33597.76 17698.59 194
EI-MVSNet-UG-set98.41 4498.34 3398.61 8699.45 5996.32 14198.28 20698.68 12597.17 4698.74 6299.37 2695.25 7299.79 9698.57 1299.54 9199.73 42
OMC-MVS97.55 9097.34 8898.20 12099.33 6995.92 16498.28 20698.59 14895.52 12297.97 11199.10 7893.28 11199.49 15395.09 18098.88 13099.19 143
baseline295.11 20994.52 21396.87 20796.65 29293.56 25898.27 20894.10 36893.45 22192.02 31697.43 25587.45 23999.19 17993.88 21797.41 18697.87 217
PVSNet_BlendedMVS96.73 12796.60 12297.12 18899.25 9095.35 18898.26 20999.26 994.28 17897.94 11497.46 25192.74 11699.81 7596.88 11493.32 26396.20 327
BH-untuned95.95 16095.72 15596.65 22198.55 16092.26 28498.23 21097.79 27793.73 20494.62 21998.01 20488.97 20199.00 20893.04 24298.51 14898.68 187
sss97.39 10096.98 10498.61 8698.60 15796.61 12498.22 21198.93 3993.97 19198.01 10898.48 15891.98 13399.85 5496.45 13498.15 16299.39 118
xxxxxxxxxxxxxcwj98.70 1098.50 1799.30 3399.46 5598.38 4098.21 21298.52 16497.95 399.32 1899.39 1896.22 2499.84 5797.72 6599.73 4799.67 67
save fliter99.46 5598.38 4098.21 21298.71 11897.95 3
WR-MVS95.15 20794.46 21797.22 18096.67 29196.45 13398.21 21298.81 8094.15 18193.16 28297.69 23387.51 23598.30 29595.29 17588.62 32196.90 258
ETH3 D test640097.59 8697.01 10199.34 2699.40 6398.56 3098.20 21598.81 8091.63 28498.44 8398.85 11593.98 10499.82 6894.11 21199.69 5899.64 76
pmmvs593.65 28392.97 28595.68 28395.49 33892.37 28398.20 21597.28 31489.66 32892.58 30097.26 26382.14 31098.09 31193.18 23890.95 29196.58 296
thres20095.25 20194.57 21097.28 17898.81 13894.92 20798.20 21597.11 31995.24 14096.54 17896.22 32784.58 28899.53 14887.93 32796.50 20597.39 230
CDS-MVSNet96.99 11896.69 11897.90 13998.05 20295.98 15298.20 21598.33 20293.67 21396.95 15598.49 15793.54 10798.42 27495.24 17897.74 17799.31 127
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
131496.25 14995.73 15497.79 14697.13 26595.55 17998.19 21998.59 14893.47 22092.03 31597.82 22591.33 14999.49 15394.62 19298.44 15298.32 206
112197.37 10296.77 11699.16 5399.34 6697.99 7098.19 21998.68 12590.14 32098.01 10898.97 9794.80 8699.87 4893.36 23299.46 10299.61 82
MVS94.67 23593.54 27298.08 12996.88 27996.56 12898.19 21998.50 17278.05 36592.69 29798.02 20291.07 15699.63 13390.09 29998.36 15798.04 213
BH-RMVSNet95.92 16495.32 17797.69 15698.32 18094.64 21798.19 21997.45 30394.56 16996.03 19398.61 14485.02 27999.12 18990.68 29399.06 12099.30 130
1112_ss96.63 12996.00 14598.50 9698.56 15896.37 13898.18 22398.10 24592.92 24294.84 21298.43 16492.14 12899.58 13894.35 20196.51 20499.56 93
MVS_030492.81 29792.01 29995.23 29497.46 24091.33 30298.17 22498.81 8091.13 30493.80 26295.68 34166.08 36998.06 31490.79 29096.13 22096.32 324
EPNet_dtu95.21 20494.95 19695.99 26996.17 31690.45 31898.16 22597.27 31596.77 6693.14 28598.33 17990.34 16998.42 27485.57 34098.81 13699.09 157
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
HY-MVS93.96 896.82 12596.23 13798.57 8898.46 16597.00 10798.14 22698.21 22293.95 19296.72 16897.99 20691.58 14099.76 10794.51 19796.54 20398.95 173
PLCcopyleft95.07 497.20 11096.78 11298.44 10399.29 8296.31 14398.14 22698.76 10392.41 25996.39 18598.31 18194.92 8399.78 10094.06 21398.77 13799.23 137
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
EG-PatchMatch MVS91.13 31190.12 31494.17 32694.73 35189.00 33998.13 22897.81 27689.22 33485.32 35896.46 31867.71 36698.42 27487.89 32893.82 24695.08 349
EI-MVSNet95.96 15995.83 15096.36 25597.93 20893.70 25698.12 22998.27 21493.70 20895.07 20799.02 9092.23 12598.54 25894.68 18993.46 25896.84 267
CVMVSNet95.43 18896.04 14393.57 32997.93 20883.62 36498.12 22998.59 14895.68 11396.56 17499.02 9087.51 23597.51 33993.56 22897.44 18499.60 85
TSAR-MVS + GP.98.38 4698.24 4698.81 7799.22 9897.25 10098.11 23198.29 21397.19 4598.99 4499.02 9096.22 2499.67 12698.52 2098.56 14699.51 98
XVG-ACMP-BASELINE94.54 24394.14 23395.75 28296.55 29691.65 29798.11 23198.44 18394.96 15494.22 24097.90 21479.18 33299.11 19194.05 21493.85 24596.48 315
CNLPA97.45 9597.03 10098.73 7999.05 11497.44 9198.07 23398.53 16295.32 13496.80 16698.53 15393.32 11099.72 11394.31 20499.31 11399.02 165
diffmvs97.58 8797.40 8698.13 12598.32 18095.81 17098.06 23498.37 19696.20 9098.74 6298.89 11191.31 15099.25 17298.16 3798.52 14799.34 121
CHOSEN 1792x268897.12 11496.80 10998.08 12999.30 7994.56 22698.05 23599.71 193.57 21797.09 14898.91 11088.17 21899.89 3996.87 11799.56 8699.81 11
HQP-NCC97.20 25898.05 23596.43 8194.45 225
ACMP_Plane97.20 25898.05 23596.43 8194.45 225
HQP-MVS95.72 17495.40 16896.69 21897.20 25894.25 23898.05 23598.46 17996.43 8194.45 22597.73 23086.75 24898.96 21395.30 17394.18 23496.86 265
MIMVSNet189.67 32388.28 32793.82 32792.81 36491.08 30798.01 23997.45 30387.95 34087.90 34895.87 33367.63 36794.56 36878.73 36588.18 32695.83 336
AdaColmapbinary97.15 11396.70 11798.48 9999.16 10796.69 12198.01 23998.89 4894.44 17696.83 16298.68 13690.69 16499.76 10794.36 20099.29 11498.98 169
FMVSNet591.81 30490.92 30794.49 31897.21 25792.09 28698.00 24197.55 29489.31 33390.86 32695.61 34274.48 35795.32 36485.57 34089.70 30396.07 331
CANet_DTU96.96 11996.55 12498.21 11998.17 19396.07 15097.98 24298.21 22297.24 4297.13 14798.93 10786.88 24799.91 3495.00 18299.37 11098.66 190
MVP-Stereo94.28 26193.92 24695.35 29294.95 34692.60 28297.97 24397.65 28391.61 28590.68 32897.09 27686.32 25898.42 27489.70 30999.34 11195.02 351
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
KD-MVS_self_test90.38 31789.38 32093.40 33292.85 36388.94 34197.95 24497.94 26990.35 31690.25 33193.96 35579.82 32795.94 36084.62 34976.69 36495.33 343
MVS_111021_LR98.34 5298.23 4798.67 8399.27 8796.90 11297.95 24499.58 397.14 4998.44 8399.01 9495.03 8099.62 13597.91 4999.75 4299.50 100
TEST999.31 7498.50 3497.92 24698.73 11292.63 24997.74 12598.68 13696.20 2799.80 84
train_agg97.97 6397.52 7799.33 3099.31 7498.50 3497.92 24698.73 11292.98 23997.74 12598.68 13696.20 2799.80 8496.59 12899.57 8199.68 63
CDPH-MVS97.94 6897.49 8099.28 3899.47 5298.44 3697.91 24898.67 13392.57 25398.77 6098.85 11595.93 4299.72 11395.56 16799.69 5899.68 63
MVS_111021_HR98.47 4098.34 3398.88 7599.22 9897.32 9397.91 24899.58 397.20 4498.33 9099.00 9595.99 3999.64 13098.05 4399.76 3699.69 57
PatchMatch-RL96.59 13296.03 14498.27 11499.31 7496.51 13197.91 24899.06 2393.72 20596.92 15998.06 20088.50 21399.65 12891.77 27799.00 12598.66 190
OpenMVS_ROBcopyleft86.42 2089.00 32787.43 33293.69 32893.08 36289.42 33297.91 24896.89 33478.58 36485.86 35594.69 34969.48 36498.29 29877.13 36793.29 26593.36 364
test_899.29 8298.44 3697.89 25298.72 11492.98 23997.70 12898.66 13996.20 2799.80 84
ab-mvs96.42 14095.71 15898.55 9098.63 15496.75 11897.88 25398.74 10893.84 19796.54 17898.18 19385.34 27699.75 10995.93 15196.35 20899.15 150
jason97.32 10497.08 9898.06 13197.45 24495.59 17597.87 25497.91 27394.79 16098.55 7798.83 11991.12 15399.23 17597.58 7799.60 7499.34 121
jason: jason.
xiu_mvs_v1_base_debu97.60 8397.56 7497.72 15298.35 17195.98 15297.86 25598.51 16797.13 5099.01 4198.40 16891.56 14199.80 8498.53 1498.68 13897.37 232
xiu_mvs_v1_base97.60 8397.56 7497.72 15298.35 17195.98 15297.86 25598.51 16797.13 5099.01 4198.40 16891.56 14199.80 8498.53 1498.68 13897.37 232
xiu_mvs_v1_base_debi97.60 8397.56 7497.72 15298.35 17195.98 15297.86 25598.51 16797.13 5099.01 4198.40 16891.56 14199.80 8498.53 1498.68 13897.37 232
test_prior498.01 6797.86 255
agg_prior197.95 6797.51 7999.28 3899.30 7998.38 4097.81 25998.72 11493.16 23397.57 13898.66 13996.14 3099.81 7596.63 12799.56 8699.66 71
test_prior398.22 5997.90 6499.19 4699.31 7498.22 5597.80 26098.84 6996.12 9497.89 11998.69 13495.96 4099.70 11996.89 11199.60 7499.65 73
test_prior297.80 26096.12 9497.89 11998.69 13495.96 4096.89 11199.60 74
XVG-OURS-SEG-HR96.51 13796.34 13097.02 19498.77 14093.76 25097.79 26298.50 17295.45 12596.94 15699.09 8487.87 22899.55 14796.76 12595.83 22497.74 221
MS-PatchMatch93.84 28093.63 26894.46 32196.18 31589.45 33197.76 26398.27 21492.23 26792.13 31397.49 24979.50 32998.69 24189.75 30799.38 10995.25 344
DELS-MVS98.40 4598.20 4998.99 6699.00 12197.66 8197.75 26498.89 4897.71 998.33 9098.97 9794.97 8199.88 4798.42 2899.76 3699.42 117
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
MG-MVS97.81 7397.60 7198.44 10399.12 11195.97 15797.75 26498.78 9996.89 6198.46 7999.22 5493.90 10599.68 12594.81 18799.52 9499.67 67
Test_1112_low_res96.34 14495.66 16398.36 10998.56 15895.94 16097.71 26698.07 25392.10 27194.79 21697.29 26291.75 13799.56 14294.17 20896.50 20599.58 91
BH-w/o95.38 19295.08 18996.26 26198.34 17691.79 29297.70 26797.43 30592.87 24494.24 23997.22 26788.66 20798.84 23091.55 28197.70 17998.16 211
lupinMVS97.44 9697.22 9398.12 12798.07 19995.76 17197.68 26897.76 27894.50 17398.79 5898.61 14492.34 12099.30 16997.58 7799.59 7799.31 127
原ACMM297.67 269
LF4IMVS93.14 29492.79 28894.20 32495.88 32788.67 34497.66 27097.07 32193.81 20091.71 31897.65 23777.96 34098.81 23491.47 28291.92 27895.12 347
EGC-MVSNET75.22 33869.54 34192.28 34194.81 34989.58 32997.64 27196.50 3451.82 3815.57 38295.74 33468.21 36596.26 35973.80 37091.71 28090.99 366
新几何297.64 271
MDA-MVSNet-bldmvs89.97 32188.35 32694.83 30995.21 34391.34 30197.64 27197.51 29788.36 33971.17 37196.13 32979.22 33196.63 35583.65 35186.27 34496.52 308
pmmvs-eth3d90.36 31889.05 32394.32 32391.10 36892.12 28597.63 27496.95 32988.86 33684.91 35993.13 35878.32 33596.74 35088.70 32181.81 35494.09 359
TR-MVS94.94 22294.20 22897.17 18497.75 21794.14 24197.59 27597.02 32692.28 26695.75 19897.64 23983.88 30298.96 21389.77 30696.15 21998.40 201
无先验97.58 27698.72 11491.38 29099.87 4893.36 23299.60 85
旧先验297.57 27791.30 29698.67 6799.80 8495.70 164
CostFormer94.95 22094.73 20495.60 28597.28 25289.06 33797.53 27896.89 33489.66 32896.82 16496.72 30886.05 26298.95 21795.53 16896.13 22098.79 181
XVG-OURS96.55 13696.41 12896.99 19598.75 14193.76 25097.50 27998.52 16495.67 11596.83 16299.30 4288.95 20299.53 14895.88 15396.26 21597.69 224
xiu_mvs_v2_base97.66 8097.70 6997.56 16698.61 15695.46 18297.44 28098.46 17997.15 4898.65 7298.15 19494.33 9799.80 8497.84 5898.66 14297.41 228
tpm94.13 26993.80 25695.12 29896.50 30087.91 35497.44 28095.89 35192.62 25096.37 18696.30 32284.13 29798.30 29593.24 23591.66 28299.14 152
DeepPCF-MVS96.37 297.93 6998.48 2296.30 25999.00 12189.54 33097.43 28298.87 5898.16 299.26 2299.38 2596.12 3299.64 13098.30 3499.77 3099.72 46
test22299.23 9797.17 10397.40 28398.66 13688.68 33798.05 9998.96 10394.14 10099.53 9299.61 82
pmmvs494.69 23093.99 24396.81 21195.74 33095.94 16097.40 28397.67 28290.42 31493.37 27697.59 24389.08 19598.20 30292.97 24491.67 28196.30 325
test0.0.03 194.08 27493.51 27395.80 27995.53 33792.89 28097.38 28595.97 34895.11 14592.51 30496.66 31087.71 23196.94 34787.03 33193.67 24997.57 226
HyFIR lowres test96.90 12296.49 12798.14 12399.33 6995.56 17797.38 28599.65 292.34 26197.61 13698.20 19189.29 18799.10 19496.97 10397.60 18299.77 23
Effi-MVS+97.12 11496.69 11898.39 10898.19 18996.72 12097.37 28798.43 18693.71 20697.65 13398.02 20292.20 12799.25 17296.87 11797.79 17499.19 143
N_pmnet87.12 33187.77 33085.17 35195.46 33961.92 37897.37 28770.66 38485.83 35288.73 34596.04 33185.33 27797.76 33280.02 35990.48 29495.84 335
PAPR96.84 12496.24 13698.65 8498.72 14696.92 11197.36 28998.57 15493.33 22596.67 16997.57 24594.30 9899.56 14291.05 28898.59 14499.47 107
PMMVS96.60 13096.33 13197.41 17197.90 21093.93 24597.35 29098.41 18892.84 24597.76 12397.45 25391.10 15599.20 17896.26 14197.91 16999.11 155
PS-MVSNAJ97.73 7697.77 6697.62 16298.68 15095.58 17697.34 29198.51 16797.29 3598.66 7197.88 21794.51 9199.90 3797.87 5499.17 11897.39 230
SCA95.46 18595.13 18696.46 24897.67 22391.29 30497.33 29297.60 28794.68 16496.92 15997.10 27283.97 30098.89 22492.59 25598.32 15999.20 139
testdata197.32 29396.34 86
ET-MVSNet_ETH3D94.13 26992.98 28497.58 16498.22 18596.20 14597.31 29495.37 35394.53 17079.56 36597.63 24186.51 25297.53 33896.91 10790.74 29299.02 165
tpm294.19 26593.76 26195.46 28997.23 25589.04 33897.31 29496.85 33887.08 34496.21 18996.79 30683.75 30698.74 23992.43 26396.23 21798.59 194
PVSNet_Blended97.38 10197.12 9598.14 12399.25 9095.35 18897.28 29699.26 993.13 23497.94 11498.21 19092.74 11699.81 7596.88 11499.40 10899.27 134
CLD-MVS95.62 18195.34 17496.46 24897.52 23793.75 25297.27 29798.46 17995.53 12194.42 23098.00 20586.21 25998.97 20996.25 14294.37 22896.66 289
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
EPMVS94.99 21694.48 21596.52 24197.22 25691.75 29497.23 29891.66 37494.11 18297.28 14296.81 30585.70 26898.84 23093.04 24297.28 18798.97 170
miper_lstm_enhance94.33 25694.07 23695.11 29997.75 21790.97 30897.22 29998.03 26191.67 28392.76 29496.97 29290.03 17497.78 33192.51 26089.64 30496.56 300
YYNet190.70 31689.39 31994.62 31594.79 35090.65 31597.20 30097.46 30187.54 34272.54 36995.74 33486.51 25296.66 35486.00 33786.76 34396.54 303
MDA-MVSNet_test_wron90.71 31589.38 32094.68 31394.83 34890.78 31297.19 30197.46 30187.60 34172.41 37095.72 33886.51 25296.71 35385.92 33886.80 34296.56 300
IterMVS-SCA-FT94.11 27193.87 25194.85 30797.98 20790.56 31797.18 30298.11 24393.75 20192.58 30097.48 25083.97 30097.41 34092.48 26291.30 28596.58 296
IterMVS94.09 27393.85 25394.80 31097.99 20590.35 31997.18 30298.12 24093.68 21192.46 30797.34 25884.05 29897.41 34092.51 26091.33 28496.62 292
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
DPM-MVS97.55 9096.99 10399.23 4599.04 11698.55 3197.17 30498.35 19994.85 15997.93 11698.58 14995.07 7999.71 11892.60 25399.34 11199.43 115
c3_l94.79 22794.43 22195.89 27697.75 21793.12 27797.16 30598.03 26192.23 26793.46 27597.05 28491.39 14698.01 31793.58 22789.21 31396.53 305
new-patchmatchnet88.50 32887.45 33191.67 34490.31 37085.89 36197.16 30597.33 31189.47 33083.63 36192.77 35976.38 34995.06 36682.70 35377.29 36394.06 360
UnsupCasMVSNet_eth90.99 31389.92 31694.19 32594.08 35589.83 32497.13 30798.67 13393.69 20985.83 35696.19 32875.15 35496.74 35089.14 31879.41 36096.00 332
IB-MVS91.98 1793.27 28991.97 30097.19 18297.47 23993.41 26697.09 30895.99 34793.32 22692.47 30695.73 33678.06 33999.53 14894.59 19582.98 35098.62 193
Christian Sormann, Mattia Rossi, Andreas Kuhn and Friedrich Fraundorfer: IB-MVS: An Iterative Algorithm for Deep Multi-View Stereo based on Binary Decisions. BMVC 2021
cl____94.51 24694.01 24096.02 26897.58 22993.40 26797.05 30997.96 26891.73 28192.76 29497.08 27889.06 19698.13 30792.61 25290.29 29796.52 308
DIV-MVS_self_test94.52 24594.03 23795.99 26997.57 23393.38 26897.05 30997.94 26991.74 27992.81 29297.10 27289.12 19398.07 31392.60 25390.30 29696.53 305
miper_ehance_all_eth95.01 21494.69 20695.97 27197.70 22293.31 27097.02 31198.07 25392.23 26793.51 27296.96 29491.85 13598.15 30593.68 22291.16 28896.44 318
CMPMVSbinary66.06 2189.70 32289.67 31889.78 34693.19 36176.56 37197.00 31298.35 19980.97 36281.57 36397.75 22974.75 35698.61 24989.85 30593.63 25294.17 357
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
tpmrst95.63 18095.69 16195.44 29097.54 23488.54 34696.97 31397.56 28993.50 21997.52 14096.93 29889.49 18199.16 18195.25 17796.42 20798.64 192
dp94.15 26893.90 24994.90 30597.31 25186.82 36096.97 31397.19 31891.22 30196.02 19496.61 31585.51 27299.02 20590.00 30494.30 22998.85 177
cl2294.68 23294.19 22996.13 26598.11 19793.60 25796.94 31598.31 20592.43 25893.32 27896.87 30286.51 25298.28 29994.10 21291.16 28896.51 311
PM-MVS87.77 32986.55 33391.40 34591.03 36983.36 36696.92 31695.18 35691.28 29886.48 35493.42 35753.27 37396.74 35089.43 31581.97 35394.11 358
TinyColmap92.31 30291.53 30394.65 31496.92 27589.75 32596.92 31696.68 34290.45 31389.62 33697.85 22076.06 35198.81 23486.74 33292.51 27295.41 342
our_test_393.65 28393.30 27994.69 31295.45 34089.68 32896.91 31897.65 28391.97 27491.66 31996.88 30089.67 18097.93 32488.02 32691.49 28396.48 315
test-LLR95.10 21094.87 19995.80 27996.77 28389.70 32696.91 31895.21 35495.11 14594.83 21495.72 33887.71 23198.97 20993.06 24098.50 14998.72 184
TESTMET0.1,194.18 26793.69 26695.63 28496.92 27589.12 33696.91 31894.78 35993.17 23294.88 21196.45 31978.52 33498.92 21993.09 23998.50 14998.85 177
test-mter94.08 27493.51 27395.80 27996.77 28389.70 32696.91 31895.21 35492.89 24394.83 21495.72 33877.69 34198.97 20993.06 24098.50 14998.72 184
USDC93.33 28892.71 28995.21 29596.83 28290.83 31196.91 31897.50 29893.84 19790.72 32798.14 19577.69 34198.82 23389.51 31393.21 26695.97 333
MDTV_nov1_ep13_2view84.26 36396.89 32390.97 30697.90 11889.89 17693.91 21699.18 148
ppachtmachnet_test93.22 29192.63 29194.97 30395.45 34090.84 31096.88 32497.88 27490.60 30992.08 31497.26 26388.08 22297.86 33085.12 34490.33 29596.22 326
tpmvs94.60 23894.36 22495.33 29397.46 24088.60 34596.88 32497.68 28191.29 29793.80 26296.42 32088.58 20899.24 17491.06 28696.04 22298.17 210
MDTV_nov1_ep1395.40 16897.48 23888.34 34996.85 32697.29 31393.74 20397.48 14197.26 26389.18 19199.05 19891.92 27497.43 185
PatchmatchNetpermissive95.71 17595.52 16696.29 26097.58 22990.72 31396.84 32797.52 29694.06 18497.08 14996.96 29489.24 19098.90 22392.03 27198.37 15599.26 135
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
MSDG95.93 16395.30 18097.83 14298.90 12995.36 18696.83 32898.37 19691.32 29594.43 22998.73 13090.27 17199.60 13690.05 30298.82 13598.52 197
thisisatest051595.61 18394.89 19897.76 14998.15 19595.15 19596.77 32994.41 36292.95 24197.18 14697.43 25584.78 28499.45 16194.63 19097.73 17898.68 187
GA-MVS94.81 22694.03 23797.14 18697.15 26493.86 24796.76 33097.58 28894.00 18994.76 21797.04 28580.91 32098.48 26491.79 27696.25 21699.09 157
tpm cat193.36 28592.80 28795.07 30197.58 22987.97 35396.76 33097.86 27582.17 36193.53 26996.04 33186.13 26099.13 18789.24 31795.87 22398.10 212
eth_miper_zixun_eth94.68 23294.41 22295.47 28897.64 22591.71 29696.73 33298.07 25392.71 24893.64 26597.21 26890.54 16698.17 30493.38 23089.76 30296.54 303
test_post196.68 33330.43 38087.85 22998.69 24192.59 255
pmmvs386.67 33284.86 33592.11 34388.16 37187.19 35996.63 33494.75 36079.88 36387.22 35092.75 36066.56 36895.20 36581.24 35776.56 36593.96 361
miper_enhance_ethall95.10 21094.75 20396.12 26697.53 23693.73 25496.61 33598.08 25192.20 27093.89 25696.65 31292.44 11998.30 29594.21 20791.16 28896.34 321
testmvs21.48 34724.95 35011.09 36314.89 3856.47 38796.56 3369.87 3867.55 37917.93 37939.02 3779.43 3865.90 38216.56 38012.72 37920.91 377
test12320.95 34823.72 35112.64 36213.54 3868.19 38696.55 3376.13 3877.48 38016.74 38037.98 37812.97 3836.05 38116.69 3795.43 38023.68 376
CL-MVSNet_self_test90.11 31989.14 32293.02 33791.86 36688.23 35196.51 33898.07 25390.49 31090.49 33094.41 35084.75 28595.34 36380.79 35874.95 36695.50 341
GG-mvs-BLEND96.59 23096.34 31094.98 20396.51 33888.58 37893.10 28794.34 35480.34 32698.05 31589.53 31296.99 19196.74 276
new_pmnet90.06 32089.00 32493.22 33694.18 35388.32 35096.42 34096.89 33486.19 34885.67 35793.62 35677.18 34797.10 34481.61 35689.29 31294.23 356
PVSNet91.96 1896.35 14396.15 13896.96 20099.17 10392.05 28896.08 34198.68 12593.69 20997.75 12497.80 22788.86 20499.69 12494.26 20699.01 12499.15 150
ADS-MVSNet294.58 24194.40 22395.11 29998.00 20388.74 34396.04 34297.30 31290.15 31896.47 18296.64 31387.89 22697.56 33790.08 30097.06 18999.02 165
ADS-MVSNet95.00 21594.45 21996.63 22598.00 20391.91 29096.04 34297.74 28090.15 31896.47 18296.64 31387.89 22698.96 21390.08 30097.06 18999.02 165
PAPM94.95 22094.00 24197.78 14797.04 26995.65 17496.03 34498.25 22091.23 30094.19 24297.80 22791.27 15198.86 22982.61 35497.61 18198.84 179
cascas94.63 23793.86 25296.93 20296.91 27794.27 23696.00 34598.51 16785.55 35494.54 22196.23 32584.20 29698.87 22795.80 15796.98 19297.66 225
gg-mvs-nofinetune92.21 30390.58 31097.13 18796.75 28695.09 19795.85 34689.40 37785.43 35594.50 22381.98 37080.80 32398.40 28892.16 26598.33 15897.88 216
FPMVS77.62 33777.14 33779.05 35579.25 37860.97 37995.79 34795.94 34965.96 36967.93 37294.40 35137.73 37888.88 37468.83 37188.46 32287.29 368
CHOSEN 280x42097.18 11197.18 9497.20 18198.81 13893.27 27195.78 34899.15 1995.25 13896.79 16798.11 19792.29 12299.07 19798.56 1399.85 599.25 136
MIMVSNet93.26 29092.21 29796.41 25197.73 22193.13 27695.65 34997.03 32491.27 29994.04 25096.06 33075.33 35397.19 34386.56 33396.23 21798.92 175
KD-MVS_2432*160089.61 32487.96 32894.54 31694.06 35691.59 29895.59 35097.63 28589.87 32488.95 34294.38 35278.28 33696.82 34884.83 34568.05 37095.21 345
miper_refine_blended89.61 32487.96 32894.54 31694.06 35691.59 29895.59 35097.63 28589.87 32488.95 34294.38 35278.28 33696.82 34884.83 34568.05 37095.21 345
PCF-MVS93.45 1194.68 23293.43 27698.42 10698.62 15596.77 11795.48 35298.20 22484.63 35793.34 27798.32 18088.55 21199.81 7584.80 34798.96 12698.68 187
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
JIA-IIPM93.35 28692.49 29395.92 27396.48 30290.65 31595.01 35396.96 32885.93 35196.08 19287.33 36787.70 23398.78 23791.35 28395.58 22598.34 204
CR-MVSNet94.76 22994.15 23296.59 23097.00 27093.43 26494.96 35497.56 28992.46 25496.93 15796.24 32388.15 21997.88 32987.38 32996.65 19998.46 199
RPMNet92.81 29791.34 30597.24 17997.00 27093.43 26494.96 35498.80 9182.27 36096.93 15792.12 36386.98 24599.82 6876.32 36896.65 19998.46 199
UnsupCasMVSNet_bld87.17 33085.12 33493.31 33491.94 36588.77 34294.92 35698.30 21184.30 35882.30 36290.04 36463.96 37197.25 34285.85 33974.47 36893.93 362
PVSNet_088.72 1991.28 30990.03 31595.00 30297.99 20587.29 35894.84 35798.50 17292.06 27289.86 33495.19 34479.81 32899.39 16492.27 26469.79 36998.33 205
Patchmatch-test94.42 25293.68 26796.63 22597.60 22891.76 29394.83 35897.49 30089.45 33194.14 24497.10 27288.99 19798.83 23285.37 34398.13 16399.29 132
Patchmtry93.22 29192.35 29595.84 27896.77 28393.09 27894.66 35997.56 28987.37 34392.90 29096.24 32388.15 21997.90 32587.37 33090.10 29996.53 305
PatchT93.06 29591.97 30096.35 25696.69 28992.67 28194.48 36097.08 32086.62 34597.08 14992.23 36287.94 22597.90 32578.89 36496.69 19798.49 198
LCM-MVSNet78.70 33476.24 33986.08 34977.26 38071.99 37594.34 36196.72 34061.62 37176.53 36689.33 36533.91 38092.78 37181.85 35574.60 36793.46 363
PMMVS277.95 33675.44 34085.46 35082.54 37574.95 37394.23 36293.08 37072.80 36874.68 36787.38 36636.36 37991.56 37273.95 36963.94 37289.87 367
MVS-HIRNet89.46 32688.40 32592.64 33897.58 22982.15 36894.16 36393.05 37175.73 36790.90 32582.52 36979.42 33098.33 29083.53 35298.68 13897.43 227
Patchmatch-RL test91.49 30790.85 30893.41 33191.37 36784.40 36292.81 36495.93 35091.87 27787.25 34994.87 34888.99 19796.53 35692.54 25982.00 35299.30 130
ambc89.49 34786.66 37275.78 37292.66 36596.72 34086.55 35392.50 36146.01 37497.90 32590.32 29682.09 35194.80 354
EMVS64.07 34363.26 34666.53 36081.73 37758.81 38291.85 36684.75 38051.93 37559.09 37575.13 37443.32 37679.09 37842.03 37739.47 37561.69 374
E-PMN64.94 34264.25 34467.02 35982.28 37659.36 38191.83 36785.63 37952.69 37360.22 37477.28 37341.06 37780.12 37746.15 37641.14 37461.57 375
ANet_high69.08 33965.37 34380.22 35465.99 38271.96 37690.91 36890.09 37682.62 35949.93 37778.39 37229.36 38181.75 37562.49 37338.52 37686.95 370
tmp_tt68.90 34066.97 34274.68 35750.78 38459.95 38087.13 36983.47 38138.80 37762.21 37396.23 32564.70 37076.91 37988.91 32030.49 37787.19 369
MVEpermissive62.14 2263.28 34459.38 34774.99 35674.33 38165.47 37785.55 37080.50 38252.02 37451.10 37675.00 37510.91 38580.50 37651.60 37553.40 37378.99 371
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
PMVScopyleft61.03 2365.95 34163.57 34573.09 35857.90 38351.22 38485.05 37193.93 36954.45 37244.32 37883.57 36813.22 38289.15 37358.68 37481.00 35778.91 372
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
test_method79.03 33378.17 33681.63 35386.06 37354.40 38382.75 37296.89 33439.54 37680.98 36495.57 34358.37 37294.73 36784.74 34878.61 36195.75 337
Gipumacopyleft78.40 33576.75 33883.38 35295.54 33680.43 37079.42 37397.40 30864.67 37073.46 36880.82 37145.65 37593.14 37066.32 37287.43 33376.56 373
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
wuyk23d30.17 34530.18 34930.16 36178.61 37943.29 38566.79 37414.21 38517.31 37814.82 38111.93 38111.55 38441.43 38037.08 37819.30 3785.76 378
test_blank0.00 3510.00 3540.00 3640.00 3870.00 3880.00 3750.00 3880.00 3820.00 3830.00 3820.00 3870.00 3830.00 3810.00 3810.00 379
uanet_test0.00 3510.00 3540.00 3640.00 3870.00 3880.00 3750.00 3880.00 3820.00 3830.00 3820.00 3870.00 3830.00 3810.00 3810.00 379
DCPMVS0.00 3510.00 3540.00 3640.00 3870.00 3880.00 3750.00 3880.00 3820.00 3830.00 3820.00 3870.00 3830.00 3810.00 3810.00 379
cdsmvs_eth3d_5k23.98 34631.98 3480.00 3640.00 3870.00 3880.00 37598.59 1480.00 3820.00 38398.61 14490.60 1650.00 3830.00 3810.00 3810.00 379
pcd_1.5k_mvsjas7.88 35010.50 3530.00 3640.00 3870.00 3880.00 3750.00 3880.00 3820.00 3830.00 38294.51 910.00 3830.00 3810.00 3810.00 379
sosnet-low-res0.00 3510.00 3540.00 3640.00 3870.00 3880.00 3750.00 3880.00 3820.00 3830.00 3820.00 3870.00 3830.00 3810.00 3810.00 379
sosnet0.00 3510.00 3540.00 3640.00 3870.00 3880.00 3750.00 3880.00 3820.00 3830.00 3820.00 3870.00 3830.00 3810.00 3810.00 379
uncertanet0.00 3510.00 3540.00 3640.00 3870.00 3880.00 3750.00 3880.00 3820.00 3830.00 3820.00 3870.00 3830.00 3810.00 3810.00 379
Regformer0.00 3510.00 3540.00 3640.00 3870.00 3880.00 3750.00 3880.00 3820.00 3830.00 3820.00 3870.00 3830.00 3810.00 3810.00 379
ab-mvs-re8.20 34910.94 3520.00 3640.00 3870.00 3880.00 3750.00 3880.00 3820.00 38398.43 1640.00 3870.00 3830.00 3810.00 3810.00 379
uanet0.00 3510.00 3540.00 3640.00 3870.00 3880.00 3750.00 3880.00 3820.00 3830.00 3820.00 3870.00 3830.00 3810.00 3810.00 379
MSC_two_6792asdad99.62 699.17 10399.08 1198.63 14399.94 498.53 1499.80 1999.86 2
PC_three_145295.08 14999.60 599.16 6897.86 298.47 26797.52 8599.72 5499.74 37
No_MVS99.62 699.17 10399.08 1198.63 14399.94 498.53 1499.80 1999.86 2
test_one_060199.66 2899.25 298.86 6497.55 1699.20 2699.47 1097.57 6
eth-test20.00 387
eth-test0.00 387
ZD-MVS99.46 5598.70 2398.79 9693.21 23098.67 6798.97 9795.70 5099.83 6096.07 14499.58 80
IU-MVS99.71 2199.23 798.64 14195.28 13699.63 498.35 3299.81 1299.83 7
test_241102_TWO98.87 5897.65 1099.53 999.48 897.34 1199.94 498.43 2699.80 1999.83 7
test_241102_ONE99.71 2199.24 598.87 5897.62 1299.73 199.39 1897.53 799.74 111
test_0728_THIRD97.32 3399.45 1199.46 1397.88 199.94 498.47 2299.86 199.85 4
GSMVS99.20 139
test_part299.63 3199.18 1099.27 21
sam_mvs189.45 18399.20 139
sam_mvs88.99 197
MTGPAbinary98.74 108
test_post31.83 37988.83 20598.91 220
patchmatchnet-post95.10 34689.42 18498.89 224
gm-plane-assit95.88 32787.47 35689.74 32796.94 29799.19 17993.32 234
test9_res96.39 13999.57 8199.69 57
agg_prior295.87 15499.57 8199.68 63
agg_prior99.30 7998.38 4098.72 11497.57 13899.81 75
TestCases96.99 19599.25 9093.21 27498.18 22891.36 29193.52 27098.77 12684.67 28699.72 11389.70 30997.87 17198.02 214
test_prior99.19 4699.31 7498.22 5598.84 6999.70 11999.65 73
新几何199.16 5399.34 6698.01 6798.69 12290.06 32198.13 9498.95 10594.60 8999.89 3991.97 27399.47 9999.59 87
旧先验199.29 8297.48 8898.70 12199.09 8495.56 5399.47 9999.61 82
原ACMM198.65 8499.32 7296.62 12298.67 13393.27 22997.81 12198.97 9795.18 7599.83 6093.84 21899.46 10299.50 100
testdata299.89 3991.65 280
segment_acmp96.85 14
testdata98.26 11699.20 10195.36 18698.68 12591.89 27698.60 7599.10 7894.44 9699.82 6894.27 20599.44 10499.58 91
test1299.18 5099.16 10798.19 5798.53 16298.07 9895.13 7799.72 11399.56 8699.63 79
plane_prior797.42 24594.63 218
plane_prior697.35 25094.61 22187.09 242
plane_prior598.56 15699.03 20296.07 14494.27 23096.92 251
plane_prior498.28 183
plane_prior394.61 22197.02 5595.34 202
plane_prior197.37 249
n20.00 388
nn0.00 388
door-mid94.37 363
lessismore_v094.45 32294.93 34788.44 34891.03 37586.77 35297.64 23976.23 35098.42 27490.31 29785.64 34896.51 311
LGP-MVS_train96.47 24597.46 24093.54 25998.54 16094.67 16594.36 23298.77 12685.39 27399.11 19195.71 16294.15 23696.76 274
test1198.66 136
door94.64 361
HQP5-MVS94.25 238
BP-MVS95.30 173
HQP4-MVS94.45 22598.96 21396.87 262
HQP3-MVS98.46 17994.18 234
HQP2-MVS86.75 248
NP-MVS97.28 25294.51 22797.73 230
ACMMP++_ref92.97 268
ACMMP++93.61 254
Test By Simon94.64 87
ITE_SJBPF95.44 29097.42 24591.32 30397.50 29895.09 14893.59 26698.35 17481.70 31398.88 22689.71 30893.39 26296.12 329
DeepMVS_CXcopyleft86.78 34897.09 26872.30 37495.17 35775.92 36684.34 36095.19 34470.58 36395.35 36279.98 36189.04 31692.68 365