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 bysort bysorted bysort bysort bysort bysort bysort by
DeepPCF-MVS93.56 196.55 4297.84 992.68 21798.71 9778.11 33199.70 1797.71 7998.18 197.36 5899.76 190.37 4899.94 3799.27 1299.54 6199.99 1
CNVR-MVS98.46 198.38 198.72 899.80 496.19 1499.80 797.99 4497.05 399.41 299.59 292.89 24100.00 198.99 1799.90 799.96 10
SED-MVS98.18 298.10 498.41 1799.63 2195.24 2499.77 997.72 7594.17 2599.30 599.54 393.32 1899.98 1099.70 399.81 2399.99 1
test_241102_TWO97.72 7594.17 2599.23 799.54 393.14 2399.98 1099.70 399.82 1999.99 1
test072699.66 1595.20 2999.77 997.70 8093.95 3099.35 499.54 393.18 21
DPE-MVScopyleft98.11 698.00 698.44 1599.50 4795.39 2099.29 7197.72 7594.50 2198.64 2399.54 393.32 1899.97 2399.58 899.90 799.95 15
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
ETH3 D test640097.67 1197.33 1798.69 999.69 996.43 1199.63 2597.73 7391.05 9898.66 2299.53 790.59 4199.71 7799.32 1199.80 2799.91 22
DPM-MVS97.86 897.25 1899.68 198.25 10799.10 199.76 1297.78 6496.61 498.15 3499.53 793.62 16100.00 191.79 14599.80 2799.94 18
SMA-MVScopyleft97.24 1996.99 2498.00 3099.30 6594.20 5799.16 8097.65 9289.55 14499.22 999.52 990.34 4999.99 598.32 3699.83 1599.82 34
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
test_241102_ONE99.63 2195.24 2497.72 7594.16 2799.30 599.49 1093.32 1899.98 10
ETH3D-3000-0.197.29 1797.01 2398.12 2599.18 7494.97 3399.47 4497.52 12289.85 13198.79 1999.46 1190.41 4799.69 7998.78 1999.67 4299.70 61
DVP-MVScopyleft98.07 798.00 698.29 1899.66 1595.20 2999.72 1497.47 13393.95 3099.07 1099.46 1193.18 2199.97 2399.64 699.82 1999.69 64
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_THIRD93.01 5199.07 1099.46 1194.66 1299.97 2399.25 1499.82 1999.95 15
MSLP-MVS++97.50 1597.45 1397.63 4199.65 1993.21 7599.70 1798.13 3794.61 1997.78 5099.46 1189.85 5399.81 6697.97 4299.91 699.88 28
NCCC98.12 598.11 398.13 2399.76 694.46 5099.81 597.88 5096.54 598.84 1799.46 1192.55 2699.98 1098.25 3899.93 199.94 18
DVP-MVS++98.18 298.09 598.44 1599.61 2795.38 2199.55 3497.68 8493.01 5199.23 799.45 1695.12 799.98 1099.25 1499.92 399.97 7
test_one_060199.59 3194.89 3597.64 9393.14 5098.93 1599.45 1693.45 17
9.1496.87 2799.34 5899.50 4197.49 13089.41 14798.59 2599.43 1889.78 5499.69 7998.69 2199.62 51
xxxxxxxxxxxxxcwj97.51 1397.42 1497.78 3799.34 5893.85 6399.65 2395.45 28095.69 1198.70 2099.42 1990.42 4599.72 7598.47 2999.65 4499.77 48
SF-MVS97.22 2296.92 2598.12 2599.11 7894.88 3699.44 5297.45 13689.60 14098.70 2099.42 1990.42 4599.72 7598.47 2999.65 4499.77 48
ETH3D cwj APD-0.1696.94 3296.58 3798.01 2998.62 10094.73 4599.13 9297.38 14788.44 17798.53 2799.39 2189.66 5899.69 7998.43 3199.61 5599.61 76
DeepC-MVS_fast93.52 297.16 2496.84 2998.13 2399.61 2794.45 5198.85 11997.64 9396.51 795.88 9399.39 2187.35 9699.99 596.61 6599.69 4199.96 10
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
MCST-MVS98.18 297.95 898.86 599.85 396.60 999.70 1797.98 4597.18 295.96 9099.33 2392.62 25100.00 198.99 1799.93 199.98 6
testtj97.23 2197.05 2197.75 3899.75 793.34 7399.16 8097.74 6991.28 9598.40 2999.29 2489.95 5299.98 1098.20 3999.70 3999.94 18
HPM-MVS++copyleft97.72 1097.59 1098.14 2299.53 4594.76 4399.19 7597.75 6795.66 1398.21 3399.29 2491.10 3199.99 597.68 4699.87 999.68 65
SteuartSystems-ACMMP97.25 1897.34 1697.01 6597.38 13291.46 10999.75 1397.66 8794.14 2998.13 3599.26 2692.16 2799.66 8497.91 4499.64 4799.90 24
Skip Steuart: Steuart Systems R&D Blog.
MP-MVS-pluss95.80 6895.30 7297.29 5598.95 8892.66 8898.59 15397.14 16888.95 15993.12 13899.25 2785.62 12999.94 3796.56 6799.48 6399.28 103
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
CSCG94.87 8894.71 8395.36 14199.54 4086.49 22799.34 6898.15 3582.71 28490.15 18199.25 2789.48 5999.86 5694.97 10398.82 9799.72 58
zzz-MVS96.21 5495.96 5596.96 7399.29 6691.19 11598.69 13697.45 13692.58 6094.39 11999.24 2986.43 11899.99 596.22 7399.40 7299.71 59
MTAPA96.09 5695.80 6496.96 7399.29 6691.19 11597.23 24797.45 13692.58 6094.39 11999.24 2986.43 11899.99 596.22 7399.40 7299.71 59
CDPH-MVS96.56 4196.18 4697.70 3999.59 3193.92 6199.13 9297.44 14089.02 15697.90 4899.22 3188.90 6599.49 10894.63 11099.79 2999.68 65
API-MVS94.78 9194.18 9696.59 9699.21 7390.06 15198.80 12497.78 6483.59 26993.85 12999.21 3283.79 15299.97 2392.37 14199.00 8899.74 55
PHI-MVS96.65 3996.46 3997.21 5999.34 5891.77 10099.70 1798.05 4086.48 22698.05 4099.20 3389.33 6099.96 3098.38 3299.62 5199.90 24
OPU-MVS99.49 499.64 2098.51 499.77 999.19 3495.12 799.97 2399.90 199.92 399.99 1
MSP-MVS97.77 998.18 296.53 10199.54 4090.14 14499.41 5897.70 8095.46 1798.60 2499.19 3495.71 499.49 10898.15 4099.85 1399.95 15
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
test_899.55 3993.07 8099.37 6497.64 9390.18 12298.36 3299.19 3490.94 3399.64 90
TEST999.57 3793.17 7699.38 6197.66 8789.57 14298.39 3099.18 3790.88 3599.66 84
train_agg97.20 2397.08 2097.57 4599.57 3793.17 7699.38 6197.66 8790.18 12298.39 3099.18 3790.94 3399.66 8498.58 2699.85 1399.88 28
agg_prior197.12 2597.03 2297.38 5399.54 4092.66 8899.35 6697.64 9390.38 11697.98 4499.17 3990.84 3799.61 9398.57 2799.78 3199.87 31
MAR-MVS94.43 10394.09 9895.45 13899.10 8087.47 20598.39 17997.79 6388.37 18094.02 12699.17 3978.64 21399.91 4292.48 14098.85 9498.96 129
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
ZD-MVS99.67 1393.28 7497.61 10187.78 19797.41 5699.16 4190.15 5099.56 9798.35 3399.70 39
CP-MVS96.22 5396.15 5196.42 10699.67 1389.62 16299.70 1797.61 10190.07 12896.00 8799.16 4187.43 9099.92 4096.03 7999.72 3499.70 61
旧先验198.97 8592.90 8797.74 6999.15 4391.05 3299.33 7499.60 77
testdata95.26 14598.20 10987.28 21297.60 10385.21 24198.48 2899.15 4388.15 7798.72 15590.29 16199.45 6699.78 42
ACMMP_NAP96.59 4096.18 4697.81 3598.82 9493.55 6898.88 11897.59 10790.66 10797.98 4499.14 4586.59 112100.00 196.47 6999.46 6499.89 27
PS-MVSNAJ96.87 3496.40 4098.29 1897.35 13397.29 599.03 10197.11 17295.83 1098.97 1399.14 4582.48 17899.60 9598.60 2399.08 8498.00 185
DP-MVS Recon95.85 6695.15 7897.95 3199.87 294.38 5499.60 2897.48 13186.58 22394.42 11899.13 4787.36 9599.98 1093.64 12598.33 11199.48 89
PC_three_145294.60 2099.41 299.12 4895.50 699.96 3099.84 299.92 399.97 7
test117295.92 6396.07 5395.46 13799.42 5487.24 21798.51 16197.24 15690.29 11996.56 8299.12 4886.73 10899.36 12597.33 5199.42 7199.78 42
SR-MVS96.13 5596.16 5096.07 11899.42 5489.04 16998.59 15397.33 15290.44 11496.84 7299.12 4886.75 10699.41 12197.47 4899.44 6799.76 51
APDe-MVS97.53 1297.47 1197.70 3999.58 3393.63 6699.56 3397.52 12293.59 4498.01 4399.12 4890.80 3899.55 9899.26 1399.79 2999.93 21
PAPR96.35 4895.82 6097.94 3299.63 2194.19 5899.42 5797.55 11592.43 6593.82 13199.12 4887.30 9799.91 4294.02 11799.06 8599.74 55
xiu_mvs_v2_base96.66 3896.17 4898.11 2797.11 14396.96 699.01 10497.04 17995.51 1698.86 1699.11 5382.19 18499.36 12598.59 2598.14 11398.00 185
region2R96.30 5196.17 4896.70 9199.70 890.31 14099.46 4997.66 8790.55 11197.07 6399.07 5486.85 10499.97 2395.43 9299.74 3299.81 35
APD-MVScopyleft96.95 3096.72 3397.63 4199.51 4693.58 6799.16 8097.44 14090.08 12798.59 2599.07 5489.06 6299.42 11997.92 4399.66 4399.88 28
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
新几何197.40 5198.92 8992.51 9597.77 6685.52 23696.69 7899.06 5688.08 7999.89 4784.88 22299.62 5199.79 38
HFP-MVS96.42 4796.26 4596.90 7799.69 990.96 12799.47 4497.81 5990.54 11296.88 6699.05 5787.57 8699.96 3095.65 8599.72 3499.78 42
#test#96.48 4496.34 4396.90 7799.69 990.96 12799.53 3997.81 5990.94 10296.88 6699.05 5787.57 8699.96 3095.87 8199.72 3499.78 42
ACMMPR96.28 5296.14 5296.73 8899.68 1290.47 13899.47 4497.80 6190.54 11296.83 7499.03 5986.51 11699.95 3495.65 8599.72 3499.75 52
Regformer-196.97 2996.80 3197.47 4799.46 5293.11 7898.89 11697.94 4692.89 5796.90 6599.02 6089.78 5499.53 10197.06 5499.26 8099.75 52
Regformer-296.94 3296.78 3297.42 4999.46 5292.97 8598.89 11697.93 4792.86 5996.88 6699.02 6089.74 5699.53 10197.03 5599.26 8099.75 52
test22298.32 10691.21 11498.08 20797.58 10983.74 26595.87 9499.02 6086.74 10799.64 4799.81 35
SD-MVS97.51 1397.40 1597.81 3599.01 8493.79 6599.33 6997.38 14793.73 4198.83 1899.02 6090.87 3699.88 4898.69 2199.74 3299.77 48
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
112195.19 8294.45 8897.42 4998.88 9192.58 9396.22 28497.75 6785.50 23896.86 6999.01 6488.59 7099.90 4487.64 19499.60 5699.79 38
APD-MVS_3200maxsize95.64 7395.65 6995.62 13299.24 7087.80 19798.42 17197.22 15988.93 16196.64 8198.98 6585.49 13399.36 12596.68 6299.27 7999.70 61
SR-MVS-dyc-post95.75 7295.86 5995.41 14099.22 7187.26 21598.40 17697.21 16089.63 13896.67 7998.97 6686.73 10899.36 12596.62 6399.31 7699.60 77
RE-MVS-def95.70 6699.22 7187.26 21598.40 17697.21 16089.63 13896.67 7998.97 6685.24 13896.62 6399.31 7699.60 77
test_prior397.07 2797.09 1997.01 6599.58 3391.77 10099.57 3197.57 11291.43 9098.12 3798.97 6690.43 4399.49 10898.33 3499.81 2399.79 38
test_prior299.57 3191.43 9098.12 3798.97 6690.43 4398.33 3499.81 23
原ACMM196.18 11399.03 8390.08 14797.63 9888.98 15797.00 6498.97 6688.14 7899.71 7788.23 18799.62 5198.76 152
XVS96.47 4596.37 4196.77 8499.62 2590.66 13599.43 5597.58 10992.41 6996.86 6998.96 7187.37 9299.87 5195.65 8599.43 6899.78 42
CPTT-MVS94.60 10094.43 8995.09 14899.66 1586.85 22299.44 5297.47 13383.22 27494.34 12198.96 7182.50 17699.55 9894.81 10599.50 6298.88 138
Regformer-396.50 4396.36 4296.91 7699.34 5891.72 10398.71 13197.90 4992.48 6496.00 8798.95 7388.60 6899.52 10496.44 7098.83 9599.49 87
Regformer-496.45 4696.33 4496.81 8399.34 5891.44 11098.71 13197.88 5092.43 6595.97 8998.95 7388.42 7299.51 10596.40 7198.83 9599.49 87
MP-MVScopyleft96.00 5895.82 6096.54 10099.47 5190.13 14699.36 6597.41 14490.64 11095.49 10298.95 7385.51 13299.98 1096.00 8099.59 5899.52 83
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
PGM-MVS95.85 6695.65 6996.45 10499.50 4789.77 15898.22 19198.90 1289.19 15096.74 7698.95 7385.91 12799.92 4093.94 11899.46 6499.66 69
mPP-MVS95.90 6495.75 6596.38 10899.58 3389.41 16699.26 7297.41 14490.66 10794.82 11298.95 7386.15 12399.98 1095.24 9799.64 4799.74 55
ZNCC-MVS96.09 5695.81 6296.95 7599.42 5491.19 11599.55 3497.53 11989.72 13595.86 9598.94 7886.59 11299.97 2395.13 9899.56 5999.68 65
CANet97.00 2896.49 3898.55 1198.86 9396.10 1599.83 497.52 12295.90 997.21 6098.90 7982.66 17599.93 3998.71 2098.80 9899.63 73
PAPM_NR95.43 7495.05 8096.57 9999.42 5490.14 14498.58 15597.51 12590.65 10992.44 14698.90 7987.77 8499.90 4490.88 15499.32 7599.68 65
EI-MVSNet-Vis-set95.76 7195.63 7196.17 11599.14 7690.33 13998.49 16597.82 5691.92 7894.75 11398.88 8187.06 10099.48 11395.40 9397.17 13298.70 155
CNLPA93.64 12392.74 12896.36 10998.96 8790.01 15499.19 7595.89 25286.22 22989.40 18998.85 8280.66 19899.84 5988.57 18396.92 13499.24 107
xiu_mvs_v1_base_debu94.73 9393.98 10196.99 6895.19 20995.24 2498.62 14796.50 20692.99 5397.52 5298.83 8372.37 25499.15 13797.03 5596.74 13596.58 215
xiu_mvs_v1_base94.73 9393.98 10196.99 6895.19 20995.24 2498.62 14796.50 20692.99 5397.52 5298.83 8372.37 25499.15 13797.03 5596.74 13596.58 215
xiu_mvs_v1_base_debi94.73 9393.98 10196.99 6895.19 20995.24 2498.62 14796.50 20692.99 5397.52 5298.83 8372.37 25499.15 13797.03 5596.74 13596.58 215
cdsmvs_eth3d_5k22.52 34030.03 3430.00 3590.00 3820.00 3830.00 37097.17 1660.00 3770.00 37898.77 8674.35 2370.00 3780.00 3760.00 3760.00 374
EI-MVSNet-UG-set95.43 7495.29 7395.86 12699.07 8289.87 15598.43 17097.80 6191.78 8194.11 12498.77 8686.25 12299.48 11394.95 10496.45 13998.22 179
lupinMVS96.32 5095.94 5697.44 4895.05 22294.87 3799.86 296.50 20693.82 3998.04 4198.77 8685.52 13098.09 17596.98 5998.97 8999.37 94
LS3D90.19 19188.72 20194.59 16898.97 8586.33 23496.90 25996.60 19674.96 33584.06 23298.74 8975.78 22499.83 6174.93 30397.57 12197.62 194
MVS_111021_HR96.69 3796.69 3496.72 9098.58 10291.00 12699.14 8999.45 193.86 3695.15 10898.73 9088.48 7199.76 7297.23 5399.56 5999.40 93
OMC-MVS93.90 11493.62 11294.73 16398.63 9987.00 21998.04 21096.56 20192.19 7392.46 14598.73 9079.49 20599.14 14092.16 14394.34 16698.03 184
GST-MVS95.97 6095.66 6796.90 7799.49 5091.22 11399.45 5197.48 13189.69 13695.89 9298.72 9286.37 12099.95 3494.62 11199.22 8399.52 83
PAPM96.35 4895.94 5697.58 4394.10 24495.25 2398.93 11198.17 3294.26 2493.94 12798.72 9289.68 5797.88 18896.36 7299.29 7899.62 75
ACMMPcopyleft94.67 9794.30 9095.79 12899.25 6988.13 19198.41 17398.67 2090.38 11691.43 15898.72 9282.22 18399.95 3493.83 12295.76 15499.29 101
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
MG-MVS97.24 1996.83 3098.47 1499.79 595.71 1799.07 9699.06 994.45 2396.42 8398.70 9588.81 6699.74 7495.35 9499.86 1299.97 7
MVS_111021_LR95.78 6995.94 5695.28 14498.19 11187.69 19898.80 12499.26 793.39 4695.04 11098.69 9684.09 15099.76 7296.96 6099.06 8598.38 170
AdaColmapbinary93.82 11693.06 12196.10 11799.88 189.07 16898.33 18397.55 11586.81 21990.39 17898.65 9775.09 22799.98 1093.32 13197.53 12499.26 105
EIA-MVS95.11 8395.27 7494.64 16696.34 16886.51 22699.59 2996.62 19492.51 6294.08 12598.64 9886.05 12498.24 16995.07 10098.50 10899.18 112
TSAR-MVS + MP.97.44 1697.46 1297.39 5299.12 7793.49 7198.52 15897.50 12894.46 2298.99 1298.64 9891.58 2899.08 14398.49 2899.83 1599.60 77
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
TSAR-MVS + GP.96.95 3096.91 2697.07 6298.88 9191.62 10599.58 3096.54 20495.09 1896.84 7298.63 10091.16 2999.77 7199.04 1696.42 14099.81 35
alignmvs95.77 7095.00 8198.06 2897.35 13395.68 1899.71 1697.50 12891.50 8796.16 8698.61 10186.28 12199.00 14596.19 7591.74 19799.51 85
MVS93.92 11292.28 13698.83 695.69 19196.82 796.22 28498.17 3284.89 25084.34 22998.61 10179.32 20699.83 6193.88 12099.43 6899.86 32
abl_694.63 9994.48 8795.09 14898.61 10186.96 22098.06 20996.97 18589.31 14895.86 9598.56 10379.82 20099.64 9094.53 11398.65 10498.66 159
TAPA-MVS87.50 990.35 18689.05 19494.25 17998.48 10585.17 26298.42 17196.58 20082.44 29087.24 20698.53 10482.77 17198.84 14859.09 35697.88 11598.72 153
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
MVSFormer94.71 9694.08 9996.61 9595.05 22294.87 3797.77 22496.17 22886.84 21798.04 4198.52 10585.52 13095.99 28689.83 16498.97 8998.96 129
jason95.40 7794.86 8297.03 6492.91 27594.23 5699.70 1796.30 21793.56 4596.73 7798.52 10581.46 19397.91 18596.08 7898.47 10998.96 129
jason: jason.
1112_ss92.71 14291.55 15496.20 11295.56 19791.12 11998.48 16694.69 30988.29 18386.89 21198.50 10787.02 10198.66 15784.75 22389.77 21598.81 146
ab-mvs-re8.21 34410.94 3470.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 37898.50 1070.00 3820.00 3780.00 3760.00 3760.00 374
canonicalmvs95.02 8693.96 10498.20 2097.53 13095.92 1698.71 13196.19 22791.78 8195.86 9598.49 10979.53 20499.03 14496.12 7691.42 20399.66 69
HPM-MVScopyleft95.41 7695.22 7695.99 12199.29 6689.14 16799.17 7997.09 17687.28 21095.40 10398.48 11084.93 14199.38 12395.64 8999.65 4499.47 90
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
CANet_DTU94.31 10693.35 11597.20 6097.03 14794.71 4698.62 14795.54 27595.61 1497.21 6098.47 11171.88 25999.84 5988.38 18597.46 12697.04 209
HPM-MVS_fast94.89 8794.62 8495.70 13199.11 7888.44 18699.14 8997.11 17285.82 23395.69 9998.47 11183.46 15799.32 13193.16 13399.63 5099.35 95
WTY-MVS95.97 6095.11 7998.54 1297.62 12496.65 899.44 5298.74 1492.25 7295.21 10698.46 11386.56 11499.46 11595.00 10292.69 18099.50 86
CS-MVS95.86 6595.81 6295.98 12295.62 19591.26 11299.80 796.12 23192.15 7697.93 4798.45 11485.88 12897.55 21497.56 4798.80 9899.14 114
DROMVSNet95.09 8495.17 7794.84 15895.42 20288.17 18899.48 4295.92 24491.47 8897.34 5998.36 11582.77 17197.41 22297.24 5298.58 10598.94 134
DeepC-MVS91.02 494.56 10293.92 10796.46 10397.16 13990.76 13198.39 17997.11 17293.92 3288.66 19498.33 11678.14 21599.85 5895.02 10198.57 10698.78 150
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
LFMVS92.23 15590.84 16896.42 10698.24 10891.08 12398.24 19096.22 22483.39 27294.74 11498.31 11761.12 31998.85 14794.45 11492.82 17799.32 98
ETV-MVS96.00 5896.00 5496.00 12096.56 15991.05 12499.63 2596.61 19593.26 4997.39 5798.30 11886.62 11198.13 17298.07 4197.57 12198.82 145
CS-MVS-test95.20 8195.27 7494.98 15495.67 19388.17 18899.62 2795.84 25791.52 8697.42 5598.30 11885.07 13997.51 21595.81 8298.20 11299.26 105
ET-MVSNet_ETH3D92.56 14891.45 15695.88 12596.39 16694.13 5999.46 4996.97 18592.18 7466.94 35198.29 12094.65 1394.28 32994.34 11583.82 24799.24 107
DELS-MVS97.12 2596.60 3698.68 1098.03 11596.57 1099.84 397.84 5496.36 895.20 10798.24 12188.17 7699.83 6196.11 7799.60 5699.64 71
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
EPNet96.82 3596.68 3597.25 5898.65 9893.10 7999.48 4298.76 1396.54 597.84 4998.22 12287.49 8999.66 8495.35 9497.78 11999.00 125
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
114514_t94.06 10893.05 12297.06 6399.08 8192.26 9798.97 10897.01 18382.58 28692.57 14498.22 12280.68 19799.30 13289.34 17599.02 8799.63 73
PLCcopyleft91.07 394.23 10794.01 10094.87 15699.17 7587.49 20499.25 7396.55 20288.43 17891.26 16298.21 12485.92 12599.86 5689.77 16897.57 12197.24 202
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
VDD-MVS91.24 17390.18 17994.45 17297.08 14485.84 25098.40 17696.10 23286.99 21293.36 13598.16 12554.27 34099.20 13496.59 6690.63 21198.31 176
PMMVS93.62 12493.90 10892.79 21296.79 15381.40 30598.85 11996.81 18991.25 9696.82 7598.15 12677.02 22198.13 17293.15 13496.30 14498.83 144
XVG-OURS90.83 17990.49 17691.86 23095.23 20781.25 30995.79 29995.92 24488.96 15890.02 18398.03 12771.60 26399.35 12991.06 15187.78 22194.98 227
XVG-OURS-SEG-HR90.95 17790.66 17491.83 23195.18 21281.14 31295.92 29195.92 24488.40 17990.33 17997.85 12870.66 26999.38 12392.83 13888.83 21794.98 227
sss94.85 8993.94 10697.58 4396.43 16394.09 6098.93 11199.16 889.50 14595.27 10597.85 12881.50 19199.65 8892.79 13994.02 16898.99 126
diffmvs94.59 10194.19 9495.81 12795.54 19890.69 13398.70 13595.68 26691.61 8395.96 9097.81 13080.11 19998.06 17996.52 6895.76 15498.67 156
BH-RMVSNet91.25 17289.99 18095.03 15296.75 15488.55 18398.65 14294.95 30087.74 20087.74 20097.80 13168.27 28198.14 17180.53 26797.49 12598.41 167
F-COLMAP92.07 15891.75 15193.02 20798.16 11282.89 29198.79 12895.97 23686.54 22587.92 19997.80 13178.69 21299.65 8885.97 20995.93 15296.53 218
PVSNet_Blended95.94 6295.66 6796.75 8698.77 9591.61 10699.88 198.04 4193.64 4394.21 12297.76 13383.50 15599.87 5197.41 4997.75 12098.79 148
VDDNet90.08 19588.54 20894.69 16494.41 23987.68 19998.21 19396.40 21176.21 33193.33 13697.75 13454.93 33898.77 15094.71 10990.96 20697.61 195
test_yl95.27 7994.60 8597.28 5698.53 10392.98 8399.05 9998.70 1786.76 22094.65 11697.74 13587.78 8299.44 11695.57 9092.61 18199.44 91
DCV-MVSNet95.27 7994.60 8597.28 5698.53 10392.98 8399.05 9998.70 1786.76 22094.65 11697.74 13587.78 8299.44 11695.57 9092.61 18199.44 91
131493.44 12691.98 14597.84 3395.24 20694.38 5496.22 28497.92 4890.18 12282.28 25497.71 13777.63 21899.80 6891.94 14498.67 10399.34 97
baseline93.91 11393.30 11695.72 13095.10 21990.07 14897.48 23695.91 24991.03 9993.54 13397.68 13879.58 20298.02 18294.27 11695.14 15999.08 121
PVSNet87.13 1293.69 11992.83 12796.28 11197.99 11690.22 14399.38 6198.93 1191.42 9293.66 13297.68 13871.29 26699.64 9087.94 19197.20 12998.98 127
casdiffmvs93.98 11193.43 11495.61 13495.07 22189.86 15698.80 12495.84 25790.98 10092.74 14397.66 14079.71 20198.10 17494.72 10895.37 15898.87 140
Vis-MVSNet (Re-imp)93.26 13593.00 12594.06 18596.14 18086.71 22598.68 13896.70 19288.30 18289.71 18897.64 14185.43 13696.39 26388.06 19096.32 14299.08 121
3Dnovator+87.72 893.43 12791.84 14898.17 2195.73 19095.08 3298.92 11397.04 17991.42 9281.48 27297.60 14274.60 23199.79 6990.84 15598.97 8999.64 71
thisisatest051594.75 9294.19 9496.43 10596.13 18392.64 9299.47 4497.60 10387.55 20693.17 13797.59 14394.71 1198.42 16288.28 18693.20 17398.24 178
3Dnovator87.35 1193.17 13791.77 15097.37 5495.41 20393.07 8098.82 12297.85 5391.53 8582.56 24897.58 14471.97 25899.82 6491.01 15299.23 8299.22 110
CHOSEN 280x42096.80 3696.85 2896.66 9497.85 11894.42 5394.76 30798.36 2492.50 6395.62 10197.52 14597.92 197.38 22398.31 3798.80 9898.20 181
IS-MVSNet93.00 13992.51 13394.49 17096.14 18087.36 20998.31 18695.70 26488.58 16990.17 18097.50 14683.02 16797.22 22687.06 19796.07 15098.90 137
OpenMVScopyleft85.28 1490.75 18188.84 19896.48 10293.58 26193.51 7098.80 12497.41 14482.59 28578.62 30197.49 14768.00 28499.82 6484.52 22798.55 10796.11 223
PCF-MVS89.78 591.26 17089.63 18396.16 11695.44 20191.58 10895.29 30396.10 23285.07 24582.75 24497.45 14878.28 21499.78 7080.60 26695.65 15797.12 204
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
VNet95.08 8594.26 9197.55 4698.07 11493.88 6298.68 13898.73 1690.33 11897.16 6297.43 14979.19 20799.53 10196.91 6191.85 19599.24 107
QAPM91.41 16989.49 18697.17 6195.66 19493.42 7298.60 15197.51 12580.92 30881.39 27397.41 15072.89 25199.87 5182.33 25298.68 10298.21 180
thisisatest053094.00 11093.52 11395.43 13995.76 18990.02 15398.99 10697.60 10386.58 22391.74 15197.36 15194.78 1098.34 16486.37 20692.48 18497.94 187
test250694.80 9094.21 9396.58 9796.41 16492.18 9898.01 21198.96 1090.82 10593.46 13497.28 15285.92 12598.45 16189.82 16697.19 13099.12 117
ECVR-MVScopyleft92.29 15291.33 15795.15 14696.41 16487.84 19698.10 20494.84 30390.82 10591.42 16097.28 15265.61 30198.49 16090.33 16097.19 13099.12 117
DWT-MVSNet_test94.36 10493.95 10595.62 13296.99 14889.47 16496.62 27197.38 14790.96 10193.07 14097.27 15493.73 1598.09 17585.86 21493.65 17199.29 101
test111192.12 15691.19 16094.94 15596.15 17887.36 20998.12 20094.84 30390.85 10490.97 16697.26 15565.60 30298.37 16389.74 16997.14 13399.07 123
mvs-test191.57 16592.20 13989.70 28095.15 21374.34 34199.51 4095.40 28491.92 7891.02 16597.25 15674.27 23898.08 17889.45 17195.83 15396.67 212
DP-MVS88.75 21986.56 23595.34 14298.92 8987.45 20697.64 23293.52 33270.55 34681.49 27197.25 15674.43 23599.88 4871.14 32494.09 16798.67 156
TR-MVS90.77 18089.44 18794.76 16096.31 16988.02 19497.92 21595.96 23885.52 23688.22 19897.23 15866.80 29398.09 17584.58 22692.38 18598.17 182
Vis-MVSNetpermissive92.64 14491.85 14795.03 15295.12 21588.23 18798.48 16696.81 18991.61 8392.16 14997.22 15971.58 26498.00 18485.85 21597.81 11698.88 138
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
gm-plane-assit94.69 23488.14 19088.22 18597.20 16098.29 16790.79 156
tttt051793.30 13293.01 12494.17 18195.57 19686.47 22898.51 16197.60 10385.99 23190.55 17397.19 16194.80 998.31 16585.06 21991.86 19497.74 189
EPP-MVSNet93.75 11893.67 11194.01 18895.86 18685.70 25298.67 14097.66 8784.46 25591.36 16197.18 16291.16 2997.79 19492.93 13693.75 16998.53 162
Effi-MVS+93.87 11593.15 12096.02 11995.79 18790.76 13196.70 26995.78 25986.98 21495.71 9897.17 16379.58 20298.01 18394.57 11296.09 14899.31 99
CLD-MVS91.06 17490.71 17292.10 22794.05 24786.10 24199.55 3496.29 22094.16 2784.70 22597.17 16369.62 27397.82 19294.74 10786.08 23192.39 241
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
EI-MVSNet89.87 19889.38 18991.36 24194.32 24085.87 24897.61 23396.59 19785.10 24385.51 22097.10 16581.30 19596.56 25183.85 23983.03 25391.64 264
CVMVSNet90.30 18890.91 16688.46 30394.32 24073.58 34597.61 23397.59 10790.16 12588.43 19797.10 16576.83 22292.86 33882.64 24993.54 17298.93 135
UA-Net93.30 13292.62 13195.34 14296.27 17088.53 18595.88 29496.97 18590.90 10395.37 10497.07 16782.38 18199.10 14283.91 23794.86 16298.38 170
RPSCF85.33 27185.55 25084.67 32794.63 23662.28 36393.73 31793.76 32674.38 33885.23 22397.06 16864.09 30798.31 16580.98 26186.08 23193.41 235
EPNet_dtu92.28 15392.15 14192.70 21697.29 13584.84 26798.64 14497.82 5692.91 5693.02 14197.02 16985.48 13595.70 30172.25 32194.89 16197.55 196
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
BH-w/o92.32 15191.79 14993.91 19196.85 15086.18 23899.11 9495.74 26288.13 18784.81 22497.00 17077.26 22097.91 18589.16 18098.03 11497.64 191
thres20093.69 11992.59 13296.97 7297.76 11994.74 4499.35 6699.36 289.23 14991.21 16496.97 17183.42 15898.77 15085.08 21890.96 20697.39 198
baseline294.04 10993.80 11094.74 16293.07 27390.25 14198.12 20098.16 3489.86 13086.53 21596.95 17295.56 598.05 18091.44 14794.53 16395.93 224
MSDG88.29 22686.37 23794.04 18796.90 14986.15 24096.52 27394.36 31877.89 32679.22 29696.95 17269.72 27299.59 9673.20 31792.58 18396.37 221
tfpn200view993.43 12792.27 13796.90 7797.68 12294.84 3999.18 7799.36 288.45 17490.79 16896.90 17483.31 15998.75 15284.11 23390.69 20897.12 204
thres40093.39 12992.27 13796.73 8897.68 12294.84 3999.18 7799.36 288.45 17490.79 16896.90 17483.31 15998.75 15284.11 23390.69 20896.61 213
Anonymous20240521188.84 21387.03 22894.27 17798.14 11384.18 27598.44 16995.58 27376.79 33089.34 19096.88 17653.42 34399.54 10087.53 19687.12 22499.09 120
baseline192.61 14691.28 15896.58 9797.05 14694.63 4897.72 22896.20 22589.82 13288.56 19596.85 17786.85 10497.82 19288.42 18480.10 26897.30 200
GeoE90.60 18589.56 18493.72 19795.10 21985.43 25699.41 5894.94 30183.96 26387.21 20796.83 17874.37 23697.05 23380.50 26893.73 17098.67 156
thres100view90093.34 13192.15 14196.90 7797.62 12494.84 3999.06 9899.36 287.96 19290.47 17696.78 17983.29 16198.75 15284.11 23390.69 20897.12 204
thres600view793.18 13692.00 14496.75 8697.62 12494.92 3499.07 9699.36 287.96 19290.47 17696.78 17983.29 16198.71 15682.93 24790.47 21296.61 213
h-mvs3392.47 15091.95 14694.05 18697.13 14185.01 26598.36 18198.08 3893.85 3796.27 8496.73 18183.19 16499.43 11895.81 8268.09 33897.70 190
BH-untuned91.46 16890.84 16893.33 20296.51 16284.83 26898.84 12195.50 27786.44 22883.50 23596.70 18275.49 22697.77 19686.78 20497.81 11697.40 197
NP-MVS93.94 25186.22 23796.67 183
HQP-MVS91.50 16691.23 15992.29 22193.95 24886.39 23199.16 8096.37 21393.92 3287.57 20196.67 18373.34 24597.77 19693.82 12386.29 22692.72 236
HQP_MVS91.26 17090.95 16592.16 22593.84 25586.07 24399.02 10296.30 21793.38 4786.99 20896.52 18572.92 24997.75 20193.46 12886.17 22992.67 238
plane_prior496.52 185
CDS-MVSNet93.47 12593.04 12394.76 16094.75 23389.45 16598.82 12297.03 18187.91 19490.97 16696.48 18789.06 6296.36 26589.50 17092.81 17998.49 164
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
OPM-MVS89.76 19989.15 19391.57 23890.53 30485.58 25498.11 20395.93 24392.88 5886.05 21696.47 18867.06 29297.87 18989.29 17886.08 23191.26 285
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
GG-mvs-BLEND96.98 7196.53 16094.81 4287.20 34697.74 6993.91 12896.40 18996.56 296.94 23795.08 9998.95 9299.20 111
CHOSEN 1792x268894.35 10593.82 10995.95 12497.40 13188.74 18098.41 17398.27 2692.18 7491.43 15896.40 18978.88 20899.81 6693.59 12697.81 11699.30 100
tmp_tt53.66 33452.86 33656.05 35132.75 37941.97 37573.42 36576.12 37521.91 37239.68 36896.39 19142.59 35965.10 37178.00 28214.92 37261.08 365
PVSNet_Blended_VisFu94.67 9794.11 9796.34 11097.14 14091.10 12199.32 7097.43 14292.10 7791.53 15796.38 19283.29 16199.68 8293.42 13096.37 14198.25 177
test0.0.03 188.96 20988.61 20490.03 27391.09 29884.43 27298.97 10897.02 18290.21 12080.29 28296.31 19384.89 14291.93 35272.98 31885.70 23493.73 231
hse-mvs291.67 16491.51 15592.15 22696.22 17282.61 29797.74 22797.53 11993.85 3796.27 8496.15 19483.19 16497.44 22095.81 8266.86 34396.40 220
AUN-MVS90.17 19289.50 18592.19 22496.21 17382.67 29597.76 22697.53 11988.05 18991.67 15296.15 19483.10 16697.47 21788.11 18966.91 34296.43 219
LPG-MVS_test88.86 21288.47 20990.06 27093.35 26880.95 31498.22 19195.94 24187.73 20183.17 24096.11 19666.28 29797.77 19690.19 16285.19 23591.46 275
LGP-MVS_train90.06 27093.35 26880.95 31495.94 24187.73 20183.17 24096.11 19666.28 29797.77 19690.19 16285.19 23591.46 275
TAMVS92.62 14592.09 14394.20 18094.10 24487.68 19998.41 17396.97 18587.53 20789.74 18696.04 19884.77 14596.49 25788.97 18292.31 18798.42 166
Anonymous2024052987.66 23685.58 24993.92 19097.59 12785.01 26598.13 19897.13 17066.69 35888.47 19696.01 19955.09 33799.51 10587.00 19984.12 24397.23 203
COLMAP_ROBcopyleft82.69 1884.54 28082.82 28089.70 28096.72 15578.85 32395.89 29292.83 33871.55 34477.54 31095.89 20059.40 32399.14 14067.26 33688.26 21891.11 289
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
PatchMatch-RL91.47 16790.54 17594.26 17898.20 10986.36 23396.94 25797.14 16887.75 19988.98 19295.75 20171.80 26199.40 12280.92 26397.39 12797.02 210
Fast-Effi-MVS+91.72 16390.79 17194.49 17095.89 18587.40 20899.54 3895.70 26485.01 24889.28 19195.68 20277.75 21797.57 21383.22 24295.06 16098.51 163
ACMP87.39 1088.71 22088.24 21190.12 26993.91 25381.06 31398.50 16395.67 26789.43 14680.37 28095.55 20365.67 29997.83 19190.55 15884.51 23991.47 274
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
AllTest84.97 27483.12 27890.52 25996.82 15178.84 32495.89 29292.17 34477.96 32475.94 31595.50 20455.48 33399.18 13571.15 32287.14 22293.55 233
TestCases90.52 25996.82 15178.84 32492.17 34477.96 32475.94 31595.50 20455.48 33399.18 13571.15 32287.14 22293.55 233
ITE_SJBPF87.93 30592.26 28176.44 33593.47 33387.67 20479.95 28795.49 20656.50 33097.38 22375.24 30182.33 25989.98 319
testgi82.29 29681.00 29986.17 31887.24 34174.84 34097.39 23791.62 35288.63 16675.85 31895.42 20746.07 35791.55 35366.87 33979.94 26992.12 252
Fast-Effi-MVS+-dtu88.84 21388.59 20689.58 28493.44 26678.18 32998.65 14294.62 31188.46 17384.12 23195.37 20868.91 27596.52 25482.06 25591.70 19994.06 230
ACMM86.95 1388.77 21888.22 21290.43 26193.61 26081.34 30798.50 16395.92 24487.88 19583.85 23495.20 20967.20 29097.89 18786.90 20284.90 23792.06 255
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
RRT_MVS91.95 16091.09 16194.53 16996.71 15795.12 3198.64 14496.23 22389.04 15585.24 22295.06 21087.71 8596.43 26189.10 18182.06 26092.05 256
HyFIR lowres test93.68 12193.29 11794.87 15697.57 12888.04 19398.18 19598.47 2287.57 20591.24 16395.05 21185.49 13397.46 21893.22 13292.82 17799.10 119
VPNet88.30 22586.57 23493.49 19991.95 28691.35 11198.18 19597.20 16488.61 16784.52 22894.89 21262.21 31496.76 24489.34 17572.26 32592.36 243
TESTMET0.1,193.82 11693.26 11895.49 13695.21 20890.25 14199.15 8697.54 11889.18 15191.79 15094.87 21389.13 6197.63 20786.21 20796.29 14598.60 160
FIs90.70 18289.87 18193.18 20492.29 28091.12 11998.17 19798.25 2789.11 15383.44 23694.82 21482.26 18296.17 28087.76 19282.76 25592.25 246
HY-MVS88.56 795.29 7894.23 9298.48 1397.72 12096.41 1294.03 31598.74 1492.42 6895.65 10094.76 21586.52 11599.49 10895.29 9692.97 17699.53 82
FC-MVSNet-test90.22 19089.40 18892.67 21891.78 29089.86 15697.89 21698.22 2988.81 16482.96 24394.66 21681.90 18895.96 28885.89 21382.52 25892.20 250
nrg03090.23 18988.87 19794.32 17691.53 29393.54 6998.79 12895.89 25288.12 18884.55 22794.61 21778.80 21196.88 23892.35 14275.21 29292.53 240
cascas90.93 17889.33 19095.76 12995.69 19193.03 8298.99 10696.59 19780.49 31086.79 21494.45 21865.23 30498.60 15993.52 12792.18 19095.66 226
UniMVSNet_ETH3D85.65 26983.79 27591.21 24290.41 30680.75 31695.36 30295.78 25978.76 32081.83 26994.33 21949.86 35196.66 24684.30 22883.52 25096.22 222
XXY-MVS87.75 23386.02 24292.95 20990.46 30589.70 16097.71 23095.90 25084.02 26080.95 27494.05 22067.51 28897.10 23185.16 21778.41 27592.04 257
test-LLR93.11 13892.68 12994.40 17394.94 22787.27 21399.15 8697.25 15490.21 12091.57 15494.04 22184.89 14297.58 21085.94 21196.13 14698.36 173
test-mter93.27 13492.89 12694.40 17394.94 22787.27 21399.15 8697.25 15488.95 15991.57 15494.04 22188.03 8097.58 21085.94 21196.13 14698.36 173
MVS_Test93.67 12292.67 13096.69 9296.72 15592.66 8897.22 24896.03 23487.69 20395.12 10994.03 22381.55 19098.28 16889.17 17996.46 13899.14 114
ACMH+83.78 1584.21 28482.56 28989.15 29393.73 25979.16 32196.43 27494.28 31981.09 30574.00 32694.03 22354.58 33997.67 20476.10 29678.81 27390.63 305
MVSTER92.71 14292.32 13593.86 19297.29 13592.95 8699.01 10496.59 19790.09 12685.51 22094.00 22594.61 1496.56 25190.77 15783.03 25392.08 254
UniMVSNet_NR-MVSNet89.60 20188.55 20792.75 21592.17 28390.07 14898.74 13098.15 3588.37 18083.21 23893.98 22682.86 16995.93 29086.95 20072.47 32292.25 246
mvs_anonymous92.50 14991.65 15295.06 15096.60 15889.64 16197.06 25396.44 21086.64 22284.14 23093.93 22782.49 17796.17 28091.47 14696.08 14999.35 95
TranMVSNet+NR-MVSNet87.75 23386.31 23892.07 22890.81 30188.56 18298.33 18397.18 16587.76 19881.87 26693.90 22872.45 25395.43 30783.13 24571.30 33292.23 248
ab-mvs91.05 17589.17 19296.69 9295.96 18491.72 10392.62 32897.23 15885.61 23589.74 18693.89 22968.55 27899.42 11991.09 15087.84 22098.92 136
WR-MVS88.54 22287.22 22692.52 21991.93 28889.50 16398.56 15697.84 5486.99 21281.87 26693.81 23074.25 24095.92 29285.29 21674.43 30192.12 252
PS-MVSNAJss89.54 20389.05 19491.00 24788.77 32584.36 27397.39 23795.97 23688.47 17181.88 26593.80 23182.48 17896.50 25589.34 17583.34 25292.15 251
jajsoiax87.35 23986.51 23689.87 27487.75 33981.74 30297.03 25495.98 23588.47 17180.15 28493.80 23161.47 31696.36 26589.44 17384.47 24191.50 273
DU-MVS88.83 21587.51 21992.79 21291.46 29490.07 14898.71 13197.62 10088.87 16383.21 23893.68 23374.63 22995.93 29086.95 20072.47 32292.36 243
NR-MVSNet87.74 23586.00 24392.96 20891.46 29490.68 13496.65 27097.42 14388.02 19173.42 32993.68 23377.31 21995.83 29784.26 22971.82 32992.36 243
IB-MVS89.43 692.12 15690.83 17095.98 12295.40 20490.78 13099.81 598.06 3991.23 9785.63 21993.66 23590.63 4098.78 14991.22 14971.85 32898.36 173
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
mvs_tets87.09 24286.22 23989.71 27987.87 33581.39 30696.73 26895.90 25088.19 18679.99 28693.61 23659.96 32296.31 27389.40 17484.34 24291.43 277
UGNet91.91 16190.85 16795.10 14797.06 14588.69 18198.01 21198.24 2892.41 6992.39 14793.61 23660.52 32099.68 8288.14 18897.25 12896.92 211
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
ACMH83.09 1784.60 27882.61 28890.57 25793.18 27182.94 28896.27 27994.92 30281.01 30672.61 33793.61 23656.54 32997.79 19474.31 30881.07 26490.99 291
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
MS-PatchMatch86.75 24785.92 24489.22 29191.97 28582.47 29896.91 25896.14 23083.74 26577.73 30893.53 23958.19 32597.37 22576.75 29198.35 11087.84 338
RRT_test8_iter0591.04 17690.40 17892.95 20996.20 17689.75 15998.97 10896.38 21288.52 17082.00 26293.51 24090.69 3996.73 24590.43 15976.91 28692.38 242
Test_1112_low_res92.27 15490.97 16496.18 11395.53 19991.10 12198.47 16894.66 31088.28 18486.83 21393.50 24187.00 10298.65 15884.69 22489.74 21698.80 147
CMPMVSbinary58.40 2180.48 30480.11 30481.59 33985.10 35059.56 36594.14 31495.95 24068.54 35360.71 35993.31 24255.35 33697.87 18983.06 24684.85 23887.33 343
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
USDC84.74 27582.93 27990.16 26891.73 29183.54 28295.00 30593.30 33488.77 16573.19 33093.30 24353.62 34297.65 20675.88 29881.54 26389.30 327
OurMVSNet-221017-084.13 28783.59 27685.77 32187.81 33670.24 35594.89 30693.65 33086.08 23076.53 31193.28 24461.41 31796.14 28280.95 26277.69 28390.93 292
PVSNet_083.28 1687.31 24085.16 25493.74 19694.78 23284.59 27098.91 11498.69 1989.81 13378.59 30393.23 24561.95 31599.34 13094.75 10655.72 36097.30 200
EU-MVSNet84.19 28584.42 26983.52 33288.64 32867.37 36196.04 29095.76 26185.29 24078.44 30493.18 24670.67 26891.48 35475.79 29975.98 28891.70 263
pmmvs487.58 23886.17 24191.80 23389.58 31588.92 17597.25 24595.28 29082.54 28780.49 27993.17 24775.62 22596.05 28582.75 24878.90 27290.42 308
test_part188.43 22386.68 23393.67 19897.56 12992.40 9698.12 20096.55 20282.26 29280.31 28193.16 24874.59 23396.62 24885.00 22172.61 32091.99 258
bset_n11_16_dypcd89.07 20787.85 21492.76 21486.16 34890.66 13597.30 24195.62 26989.78 13483.94 23393.15 24974.85 22895.89 29591.34 14878.48 27491.74 262
GA-MVS90.10 19488.69 20294.33 17592.44 27987.97 19599.08 9596.26 22189.65 13786.92 21093.11 25068.09 28296.96 23582.54 25190.15 21398.05 183
CP-MVSNet86.54 25285.45 25289.79 27891.02 30082.78 29497.38 23997.56 11485.37 23979.53 29393.03 25171.86 26095.25 31279.92 26973.43 31591.34 281
LF4IMVS81.94 29981.17 29884.25 32987.23 34268.87 36093.35 32191.93 34983.35 27375.40 32093.00 25249.25 35496.65 24778.88 27778.11 27787.22 345
XVG-ACMP-BASELINE85.86 26284.95 25888.57 30089.90 31077.12 33494.30 31195.60 27287.40 20982.12 25792.99 25353.42 34397.66 20585.02 22083.83 24590.92 293
PS-CasMVS85.81 26484.58 26689.49 28890.77 30282.11 30097.20 24997.36 15084.83 25179.12 29892.84 25467.42 28995.16 31478.39 28173.25 31691.21 286
LTVRE_ROB81.71 1984.59 27982.72 28590.18 26792.89 27683.18 28693.15 32294.74 30678.99 31775.14 32292.69 25565.64 30097.63 20769.46 32981.82 26289.74 321
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
PEN-MVS85.21 27283.93 27489.07 29589.89 31181.31 30897.09 25297.24 15684.45 25678.66 30092.68 25668.44 28094.87 31975.98 29770.92 33391.04 290
PVSNet_BlendedMVS93.36 13093.20 11993.84 19398.77 9591.61 10699.47 4498.04 4191.44 8994.21 12292.63 25783.50 15599.87 5197.41 4983.37 25190.05 317
DTE-MVSNet84.14 28682.80 28188.14 30488.95 32479.87 32096.81 26296.24 22283.50 27077.60 30992.52 25867.89 28694.24 33072.64 32069.05 33690.32 310
miper_enhance_ethall90.33 18789.70 18292.22 22297.12 14288.93 17498.35 18295.96 23888.60 16883.14 24292.33 25987.38 9196.18 27986.49 20577.89 27891.55 272
SixPastTwentyTwo82.63 29581.58 29385.79 32088.12 33371.01 35495.17 30492.54 34084.33 25772.93 33592.08 26060.41 32195.61 30474.47 30774.15 30690.75 300
UniMVSNet (Re)89.50 20488.32 21093.03 20692.21 28290.96 12798.90 11598.39 2389.13 15283.22 23792.03 26181.69 18996.34 27186.79 20372.53 32191.81 261
pmmvs585.87 26184.40 27090.30 26688.53 32984.23 27498.60 15193.71 32881.53 30080.29 28292.02 26264.51 30695.52 30582.04 25678.34 27691.15 287
pm-mvs184.68 27782.78 28390.40 26289.58 31585.18 26197.31 24094.73 30781.93 29776.05 31492.01 26365.48 30396.11 28378.75 27969.14 33589.91 320
VPA-MVSNet89.10 20687.66 21893.45 20092.56 27791.02 12597.97 21498.32 2586.92 21686.03 21792.01 26368.84 27797.10 23190.92 15375.34 29192.23 248
MVP-Stereo86.61 25185.83 24588.93 29888.70 32783.85 28096.07 28994.41 31782.15 29475.64 31991.96 26567.65 28796.45 26077.20 28798.72 10186.51 349
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
test_djsdf88.26 22787.73 21689.84 27688.05 33482.21 29997.77 22496.17 22886.84 21782.41 25291.95 26672.07 25795.99 28689.83 16484.50 24091.32 282
cl2289.57 20288.79 20091.91 22997.94 11787.62 20197.98 21396.51 20585.03 24682.37 25391.79 26783.65 15396.50 25585.96 21077.89 27891.61 269
v2v48287.27 24185.76 24691.78 23789.59 31487.58 20298.56 15695.54 27584.53 25482.51 24991.78 26873.11 24896.47 25882.07 25474.14 30791.30 283
TinyColmap80.42 30577.94 30987.85 30692.09 28478.58 32693.74 31689.94 36074.99 33469.77 34191.78 26846.09 35697.58 21065.17 34477.89 27887.38 341
TransMVSNet (Re)81.97 29879.61 30689.08 29489.70 31384.01 27797.26 24491.85 35078.84 31873.07 33491.62 27067.17 29195.21 31367.50 33559.46 35588.02 337
FMVSNet388.81 21787.08 22793.99 18996.52 16194.59 4998.08 20796.20 22585.85 23282.12 25791.60 27174.05 24195.40 30979.04 27480.24 26591.99 258
eth_miper_zixun_eth87.76 23287.00 22990.06 27094.67 23582.65 29697.02 25695.37 28784.19 25881.86 26891.58 27281.47 19295.90 29483.24 24173.61 31091.61 269
miper_ehance_all_eth88.94 21088.12 21391.40 23995.32 20586.93 22197.85 22095.55 27484.19 25881.97 26391.50 27384.16 14995.91 29384.69 22477.89 27891.36 280
Effi-MVS+-dtu89.97 19790.68 17387.81 30795.15 21371.98 35197.87 21995.40 28491.92 7887.57 20191.44 27474.27 23896.84 23989.45 17193.10 17594.60 229
c3_l88.19 22887.23 22591.06 24594.97 22586.17 23997.72 22895.38 28683.43 27181.68 27091.37 27582.81 17095.72 30084.04 23673.70 30991.29 284
Baseline_NR-MVSNet85.83 26384.82 26188.87 29988.73 32683.34 28498.63 14691.66 35180.41 31382.44 25091.35 27674.63 22995.42 30884.13 23271.39 33187.84 338
DIV-MVS_self_test87.82 23086.81 23190.87 25294.87 23085.39 25897.81 22195.22 29882.92 28280.76 27691.31 27781.99 18595.81 29881.36 25975.04 29491.42 278
cl____87.82 23086.79 23290.89 25194.88 22985.43 25697.81 22195.24 29482.91 28380.71 27791.22 27881.97 18795.84 29681.34 26075.06 29391.40 279
IterMVS-LS88.34 22487.44 22091.04 24694.10 24485.85 24998.10 20495.48 27885.12 24282.03 26191.21 27981.35 19495.63 30383.86 23875.73 29091.63 265
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
FMVSNet286.90 24484.79 26293.24 20395.11 21692.54 9497.67 23195.86 25682.94 27980.55 27891.17 28062.89 31195.29 31177.23 28579.71 27191.90 260
TDRefinement78.01 31775.31 32086.10 31970.06 36973.84 34393.59 32091.58 35374.51 33773.08 33391.04 28149.63 35397.12 22874.88 30459.47 35487.33 343
ppachtmachnet_test83.63 29181.57 29489.80 27789.01 32285.09 26497.13 25194.50 31378.84 31876.14 31391.00 28269.78 27194.61 32663.40 34674.36 30289.71 323
tfpnnormal83.65 29081.35 29690.56 25891.37 29688.06 19297.29 24297.87 5278.51 32176.20 31290.91 28364.78 30596.47 25861.71 35173.50 31287.13 346
WR-MVS_H86.53 25385.49 25189.66 28391.04 29983.31 28597.53 23598.20 3184.95 24979.64 29090.90 28478.01 21695.33 31076.29 29572.81 31790.35 309
Anonymous2023121184.72 27682.65 28790.91 24997.71 12184.55 27197.28 24396.67 19366.88 35779.18 29790.87 28558.47 32496.60 24982.61 25074.20 30591.59 271
v114486.83 24685.31 25391.40 23989.75 31287.21 21898.31 18695.45 28083.22 27482.70 24690.78 28673.36 24496.36 26579.49 27174.69 29890.63 305
CostFormer92.89 14092.48 13494.12 18394.99 22485.89 24792.89 32497.00 18486.98 21495.00 11190.78 28690.05 5197.51 21592.92 13791.73 19898.96 129
v192192086.02 25984.44 26890.77 25489.32 32085.20 26098.10 20495.35 28982.19 29382.25 25590.71 28870.73 26796.30 27676.85 29074.49 30090.80 296
anonymousdsp86.69 24885.75 24789.53 28586.46 34582.94 28896.39 27595.71 26383.97 26279.63 29190.70 28968.85 27695.94 28986.01 20884.02 24489.72 322
tpmrst92.78 14192.16 14094.65 16596.27 17087.45 20691.83 33297.10 17589.10 15494.68 11590.69 29088.22 7597.73 20389.78 16791.80 19698.77 151
V4287.00 24385.68 24890.98 24889.91 30986.08 24298.32 18595.61 27183.67 26882.72 24590.67 29174.00 24296.53 25381.94 25774.28 30490.32 310
tpm291.77 16291.09 16193.82 19494.83 23185.56 25592.51 32997.16 16784.00 26193.83 13090.66 29287.54 8897.17 22787.73 19391.55 20198.72 153
EPMVS92.59 14791.59 15395.59 13597.22 13790.03 15291.78 33398.04 4190.42 11591.66 15390.65 29386.49 11797.46 21881.78 25896.31 14399.28 103
LCM-MVSNet-Re88.59 22188.61 20488.51 30295.53 19972.68 34996.85 26188.43 36588.45 17473.14 33190.63 29475.82 22394.38 32892.95 13595.71 15698.48 165
SCA90.64 18489.25 19194.83 15994.95 22688.83 17696.26 28197.21 16090.06 12990.03 18290.62 29566.61 29496.81 24183.16 24394.36 16598.84 141
Patchmatch-test86.25 25784.06 27292.82 21194.42 23882.88 29282.88 36194.23 32071.58 34379.39 29490.62 29589.00 6496.42 26263.03 34891.37 20499.16 113
v119286.32 25684.71 26391.17 24389.53 31786.40 23098.13 19895.44 28282.52 28882.42 25190.62 29571.58 26496.33 27277.23 28574.88 29590.79 297
v14419286.40 25484.89 25990.91 24989.48 31885.59 25398.21 19395.43 28382.45 28982.62 24790.58 29872.79 25296.36 26578.45 28074.04 30890.79 297
PatchmatchNetpermissive92.05 15991.04 16395.06 15096.17 17789.04 16991.26 33797.26 15389.56 14390.64 17290.56 29988.35 7497.11 22979.53 27096.07 15099.03 124
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
v124085.77 26684.11 27190.73 25589.26 32185.15 26397.88 21895.23 29781.89 29882.16 25690.55 30069.60 27496.31 27375.59 30074.87 29690.72 302
our_test_384.47 28282.80 28189.50 28689.01 32283.90 27997.03 25494.56 31281.33 30275.36 32190.52 30171.69 26294.54 32768.81 33176.84 28790.07 315
miper_lstm_enhance86.90 24486.20 24089.00 29694.53 23781.19 31096.74 26795.24 29482.33 29180.15 28490.51 30281.99 18594.68 32580.71 26573.58 31191.12 288
MDTV_nov1_ep1390.47 17796.14 18088.55 18391.34 33697.51 12589.58 14192.24 14890.50 30386.99 10397.61 20977.64 28492.34 186
IterMVS-SCA-FT85.73 26784.64 26589.00 29693.46 26582.90 29096.27 27994.70 30885.02 24778.62 30190.35 30466.61 29493.33 33479.38 27377.36 28590.76 299
D2MVS87.96 22987.39 22189.70 28091.84 28983.40 28398.31 18698.49 2188.04 19078.23 30790.26 30573.57 24396.79 24384.21 23083.53 24988.90 332
GBi-Net86.67 24984.96 25691.80 23395.11 21688.81 17796.77 26395.25 29182.94 27982.12 25790.25 30662.89 31194.97 31679.04 27480.24 26591.62 266
test186.67 24984.96 25691.80 23395.11 21688.81 17796.77 26395.25 29182.94 27982.12 25790.25 30662.89 31194.97 31679.04 27480.24 26591.62 266
FMVSNet183.94 28981.32 29791.80 23391.94 28788.81 17796.77 26395.25 29177.98 32278.25 30690.25 30650.37 35094.97 31673.27 31677.81 28291.62 266
v14886.38 25585.06 25590.37 26589.47 31984.10 27698.52 15895.48 27883.80 26480.93 27590.22 30974.60 23196.31 27380.92 26371.55 33090.69 303
lessismore_v085.08 32385.59 34969.28 35890.56 35867.68 34890.21 31054.21 34195.46 30673.88 31162.64 34990.50 307
dp90.16 19388.83 19994.14 18296.38 16786.42 22991.57 33497.06 17884.76 25288.81 19390.19 31184.29 14897.43 22175.05 30291.35 20598.56 161
IterMVS85.81 26484.67 26489.22 29193.51 26283.67 28196.32 27894.80 30585.09 24478.69 29990.17 31266.57 29693.17 33779.48 27277.42 28490.81 295
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
test_040278.81 31376.33 31786.26 31791.18 29778.44 32895.88 29491.34 35568.55 35270.51 34089.91 31352.65 34594.99 31547.14 36479.78 27085.34 355
v886.11 25884.45 26791.10 24489.99 30886.85 22297.24 24695.36 28881.99 29579.89 28889.86 31474.53 23496.39 26378.83 27872.32 32490.05 317
v1085.73 26784.01 27390.87 25290.03 30786.73 22497.20 24995.22 29881.25 30379.85 28989.75 31573.30 24796.28 27776.87 28972.64 31989.61 324
test20.0378.51 31677.48 31181.62 33883.07 35671.03 35396.11 28892.83 33881.66 29969.31 34289.68 31657.53 32687.29 36358.65 35768.47 33786.53 348
pmmvs679.90 30777.31 31287.67 30884.17 35378.13 33095.86 29693.68 32967.94 35572.67 33689.62 31750.98 34995.75 29974.80 30666.04 34489.14 330
tpm89.67 20088.95 19691.82 23292.54 27881.43 30492.95 32395.92 24487.81 19690.50 17589.44 31884.99 14095.65 30283.67 24082.71 25698.38 170
v7n84.42 28382.75 28489.43 28988.15 33281.86 30196.75 26695.67 26780.53 30978.38 30589.43 31969.89 27096.35 27073.83 31372.13 32690.07 315
K. test v381.04 30279.77 30584.83 32587.41 34070.23 35695.60 30193.93 32583.70 26767.51 34989.35 32055.76 33193.58 33376.67 29268.03 33990.67 304
tpmvs89.16 20587.76 21593.35 20197.19 13884.75 26990.58 34397.36 15081.99 29584.56 22689.31 32183.98 15198.17 17074.85 30590.00 21497.12 204
Anonymous2023120680.76 30379.42 30784.79 32684.78 35172.98 34696.53 27292.97 33679.56 31474.33 32388.83 32261.27 31892.15 34960.59 35375.92 28989.24 329
EG-PatchMatch MVS79.92 30677.59 31086.90 31487.06 34377.90 33396.20 28794.06 32374.61 33666.53 35388.76 32340.40 36496.20 27867.02 33783.66 24886.61 347
tpm cat188.89 21187.27 22493.76 19595.79 18785.32 25990.76 34197.09 17676.14 33285.72 21888.59 32482.92 16898.04 18176.96 28891.43 20297.90 188
DeepMVS_CXcopyleft76.08 34390.74 30351.65 37190.84 35786.47 22757.89 36087.98 32535.88 36692.60 34265.77 34265.06 34683.97 357
MDA-MVSNet-bldmvs77.82 31974.75 32387.03 31388.33 33078.52 32796.34 27792.85 33775.57 33348.87 36487.89 32657.32 32892.49 34660.79 35264.80 34790.08 314
UnsupCasMVSNet_eth78.90 31276.67 31685.58 32282.81 35874.94 33991.98 33196.31 21684.64 25365.84 35587.71 32751.33 34792.23 34872.89 31956.50 35989.56 325
MIMVSNet84.48 28181.83 29192.42 22091.73 29187.36 20985.52 35094.42 31681.40 30181.91 26487.58 32851.92 34692.81 34073.84 31288.15 21997.08 208
YYNet179.64 31077.04 31487.43 31187.80 33779.98 31996.23 28394.44 31473.83 34051.83 36187.53 32967.96 28592.07 35166.00 34167.75 34190.23 312
KD-MVS_2432*160082.98 29380.52 30190.38 26394.32 24088.98 17192.87 32595.87 25480.46 31173.79 32787.49 33082.76 17393.29 33570.56 32646.53 36588.87 333
miper_refine_blended82.98 29380.52 30190.38 26394.32 24088.98 17192.87 32595.87 25480.46 31173.79 32787.49 33082.76 17393.29 33570.56 32646.53 36588.87 333
MDA-MVSNet_test_wron79.65 30977.05 31387.45 31087.79 33880.13 31896.25 28294.44 31473.87 33951.80 36287.47 33268.04 28392.12 35066.02 34067.79 34090.09 313
ADS-MVSNet287.62 23786.88 23089.86 27596.21 17379.14 32287.15 34792.99 33583.01 27789.91 18487.27 33378.87 20992.80 34174.20 30992.27 18897.64 191
ADS-MVSNet88.99 20887.30 22394.07 18496.21 17387.56 20387.15 34796.78 19183.01 27789.91 18487.27 33378.87 20997.01 23474.20 30992.27 18897.64 191
DSMNet-mixed81.60 30181.43 29582.10 33684.36 35260.79 36493.63 31986.74 36779.00 31679.32 29587.15 33563.87 30989.78 35766.89 33891.92 19395.73 225
OpenMVS_ROBcopyleft73.86 2077.99 31875.06 32286.77 31583.81 35577.94 33296.38 27691.53 35467.54 35668.38 34487.13 33643.94 35896.08 28455.03 36081.83 26186.29 350
CR-MVSNet88.83 21587.38 22293.16 20593.47 26386.24 23584.97 35494.20 32188.92 16290.76 17086.88 33784.43 14694.82 32170.64 32592.17 19198.41 167
Patchmtry83.61 29281.64 29289.50 28693.36 26782.84 29384.10 35794.20 32169.47 35179.57 29286.88 33784.43 14694.78 32268.48 33374.30 30390.88 294
N_pmnet70.19 32769.87 32971.12 34688.24 33130.63 37995.85 29728.70 37970.18 34868.73 34386.55 33964.04 30893.81 33153.12 36273.46 31388.94 331
MVS_030484.13 28782.66 28688.52 30193.07 27380.15 31795.81 29898.21 3079.27 31586.85 21286.40 34041.33 36294.69 32476.36 29486.69 22590.73 301
MIMVSNet175.92 32273.30 32583.81 33181.29 36175.57 33792.26 33092.05 34773.09 34267.48 35086.18 34140.87 36387.64 36255.78 35970.68 33488.21 336
FMVSNet582.29 29680.54 30087.52 30993.79 25884.01 27793.73 31792.47 34176.92 32974.27 32486.15 34263.69 31089.24 35869.07 33074.79 29789.29 328
CL-MVSNet_self_test79.89 30878.34 30884.54 32881.56 36075.01 33896.88 26095.62 26981.10 30475.86 31785.81 34368.49 27990.26 35663.21 34756.51 35888.35 335
patchmatchnet-post84.86 34488.73 6796.81 241
Anonymous2024052178.63 31576.90 31583.82 33082.82 35772.86 34795.72 30093.57 33173.55 34172.17 33884.79 34549.69 35292.51 34565.29 34374.50 29986.09 351
test_method70.10 32868.66 33174.41 34486.30 34755.84 36894.47 30889.82 36135.18 36766.15 35484.75 34630.54 36777.96 36870.40 32860.33 35389.44 326
EGC-MVSNET60.70 33055.37 33476.72 34286.35 34671.08 35289.96 34484.44 3710.38 3761.50 37784.09 34737.30 36588.10 36140.85 36673.44 31470.97 364
KD-MVS_self_test77.47 32075.88 31982.24 33481.59 35968.93 35992.83 32794.02 32477.03 32873.14 33183.39 34855.44 33590.42 35567.95 33457.53 35787.38 341
PM-MVS74.88 32372.85 32680.98 34078.98 36564.75 36290.81 34085.77 36880.95 30768.23 34682.81 34929.08 36892.84 33976.54 29362.46 35085.36 354
pmmvs-eth3d78.71 31476.16 31886.38 31680.25 36381.19 31094.17 31392.13 34677.97 32366.90 35282.31 35055.76 33192.56 34473.63 31562.31 35185.38 353
Patchmatch-RL test81.90 30080.13 30387.23 31280.71 36270.12 35784.07 35888.19 36683.16 27670.57 33982.18 35187.18 9892.59 34382.28 25362.78 34898.98 127
new_pmnet76.02 32173.71 32482.95 33383.88 35472.85 34891.26 33792.26 34370.44 34762.60 35781.37 35247.64 35592.32 34761.85 35072.10 32783.68 358
FPMVS61.57 32960.32 33265.34 34860.14 37342.44 37491.02 33989.72 36244.15 36442.63 36680.93 35319.02 37080.59 36742.50 36572.76 31873.00 362
pmmvs372.86 32669.76 33082.17 33573.86 36774.19 34294.20 31289.01 36464.23 36167.72 34780.91 35441.48 36088.65 36062.40 34954.02 36283.68 358
ambc79.60 34172.76 36856.61 36776.20 36392.01 34868.25 34580.23 35523.34 36994.73 32373.78 31460.81 35287.48 340
new-patchmatchnet74.80 32472.40 32781.99 33778.36 36672.20 35094.44 30992.36 34277.06 32763.47 35679.98 35651.04 34888.85 35960.53 35454.35 36184.92 356
PatchT85.44 27083.19 27792.22 22293.13 27283.00 28783.80 36096.37 21370.62 34590.55 17379.63 35784.81 14494.87 31958.18 35891.59 20098.79 148
RPMNet85.07 27381.88 29094.64 16693.47 26386.24 23584.97 35497.21 16064.85 36090.76 17078.80 35880.95 19699.27 13353.76 36192.17 19198.41 167
UnsupCasMVSNet_bld73.85 32570.14 32884.99 32479.44 36475.73 33688.53 34595.24 29470.12 34961.94 35874.81 35941.41 36193.62 33268.65 33251.13 36485.62 352
LCM-MVSNet60.07 33156.37 33371.18 34554.81 37548.67 37282.17 36289.48 36337.95 36549.13 36369.12 36013.75 37681.76 36459.28 35551.63 36383.10 360
PMMVS258.97 33255.07 33570.69 34762.72 37055.37 36985.97 34980.52 37249.48 36345.94 36568.31 36115.73 37480.78 36649.79 36337.12 36775.91 361
JIA-IIPM85.97 26084.85 26089.33 29093.23 27073.68 34485.05 35397.13 17069.62 35091.56 15668.03 36288.03 8096.96 23577.89 28393.12 17497.34 199
testmvs18.81 34123.05 3446.10 3584.48 3802.29 38297.78 2233.00 3813.27 37418.60 37462.71 3631.53 3812.49 37714.26 3741.80 37413.50 372
gg-mvs-nofinetune90.00 19687.71 21796.89 8296.15 17894.69 4785.15 35297.74 6968.32 35492.97 14260.16 36496.10 396.84 23993.89 11998.87 9399.14 114
PMVScopyleft41.42 2345.67 33642.50 33955.17 35234.28 37832.37 37766.24 36678.71 37430.72 36822.04 37359.59 3654.59 37777.85 36927.49 36958.84 35655.29 366
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
MVS-HIRNet79.01 31175.13 32190.66 25693.82 25781.69 30385.16 35193.75 32754.54 36274.17 32559.15 36657.46 32796.58 25063.74 34594.38 16493.72 232
ANet_high50.71 33546.17 33864.33 34944.27 37752.30 37076.13 36478.73 37364.95 35927.37 37055.23 36714.61 37567.74 37036.01 36718.23 37072.95 363
Gipumacopyleft54.77 33352.22 33762.40 35086.50 34459.37 36650.20 36890.35 35936.52 36641.20 36749.49 36818.33 37281.29 36532.10 36865.34 34546.54 368
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
MVEpermissive44.00 2241.70 33737.64 34253.90 35349.46 37643.37 37365.09 36766.66 37626.19 37125.77 37248.53 3693.58 37963.35 37226.15 37027.28 36854.97 367
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
E-PMN41.02 33840.93 34041.29 35461.97 37133.83 37684.00 35965.17 37727.17 36927.56 36946.72 37017.63 37360.41 37319.32 37118.82 36929.61 369
test_post46.00 37187.37 9297.11 229
test12316.58 34319.47 3457.91 3573.59 3815.37 38194.32 3101.39 3822.49 37513.98 37544.60 3722.91 3802.65 37611.35 3750.57 37515.70 371
EMVS39.96 33939.88 34140.18 35559.57 37432.12 37884.79 35664.57 37826.27 37026.14 37144.18 37318.73 37159.29 37417.03 37217.67 37129.12 370
test_post190.74 34241.37 37485.38 13796.36 26583.16 243
X-MVStestdata90.69 18388.66 20396.77 8499.62 2590.66 13599.43 5597.58 10992.41 6996.86 6929.59 37587.37 9299.87 5195.65 8599.43 6899.78 42
wuyk23d16.71 34216.73 34616.65 35660.15 37225.22 38041.24 3695.17 3806.56 3735.48 3763.61 3763.64 37822.72 37515.20 3739.52 3731.99 373
test_blank0.00 3460.00 3490.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 3770.00 3820.00 3780.00 3760.00 3760.00 374
uanet_test0.00 3460.00 3490.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 3770.00 3820.00 3780.00 3760.00 3760.00 374
pcd_1.5k_mvsjas6.87 3459.16 3480.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 37782.48 1780.00 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
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
FOURS199.50 4788.94 17399.55 3497.47 13391.32 9498.12 37
MSC_two_6792asdad99.51 299.61 2798.60 297.69 8299.98 1099.55 999.83 1599.96 10
No_MVS99.51 299.61 2798.60 297.69 8299.98 1099.55 999.83 1599.96 10
eth-test20.00 382
eth-test0.00 382
IU-MVS99.63 2195.38 2197.73 7395.54 1599.54 199.69 599.81 2399.99 1
save fliter99.34 5893.85 6399.65 2397.63 9895.69 11
test_0728_SECOND98.77 799.66 1596.37 1399.72 1497.68 8499.98 1099.64 699.82 1999.96 10
GSMVS98.84 141
test_part299.54 4095.42 1998.13 35
sam_mvs188.39 7398.84 141
sam_mvs87.08 99
MTGPAbinary97.45 136
MTMP99.21 7491.09 356
test9_res98.60 2399.87 999.90 24
agg_prior297.84 4599.87 999.91 22
agg_prior99.54 4092.66 8897.64 9397.98 4499.61 93
test_prior492.00 9999.41 58
test_prior97.01 6599.58 3391.77 10097.57 11299.49 10899.79 38
旧先验298.67 14085.75 23498.96 1498.97 14693.84 121
新几何298.26 189
无先验98.52 15897.82 5687.20 21199.90 4487.64 19499.85 33
原ACMM298.69 136
testdata299.88 4884.16 231
segment_acmp90.56 42
testdata197.89 21692.43 65
test1297.83 3499.33 6494.45 5197.55 11597.56 5188.60 6899.50 10799.71 3899.55 81
plane_prior793.84 25585.73 251
plane_prior693.92 25286.02 24572.92 249
plane_prior596.30 21797.75 20193.46 12886.17 22992.67 238
plane_prior385.91 24693.65 4286.99 208
plane_prior299.02 10293.38 47
plane_prior193.90 254
plane_prior86.07 24399.14 8993.81 4086.26 228
n20.00 383
nn0.00 383
door-mid84.90 370
test1197.68 84
door85.30 369
HQP5-MVS86.39 231
HQP-NCC93.95 24899.16 8093.92 3287.57 201
ACMP_Plane93.95 24899.16 8093.92 3287.57 201
BP-MVS93.82 123
HQP4-MVS87.57 20197.77 19692.72 236
HQP3-MVS96.37 21386.29 226
HQP2-MVS73.34 245
MDTV_nov1_ep13_2view91.17 11891.38 33587.45 20893.08 13986.67 11087.02 19898.95 133
ACMMP++_ref82.64 257
ACMMP++83.83 245
Test By Simon83.62 154