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 bysorted bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort by
DVP-MVS++98.06 197.99 198.28 998.67 5895.39 1199.29 198.28 2994.78 3498.93 798.87 896.04 299.86 897.45 1699.58 2199.59 20
SED-MVS98.05 297.99 198.24 1099.42 795.30 1798.25 3698.27 3295.13 1999.19 298.89 695.54 599.85 1797.52 1299.66 1099.56 26
DVP-MVScopyleft97.91 397.81 498.22 1299.45 395.36 1398.21 4397.85 10894.92 2598.73 1198.87 895.08 899.84 2297.52 1299.67 699.48 40
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
DPE-MVScopyleft97.86 497.65 698.47 599.17 3295.78 797.21 14998.35 2195.16 1898.71 1398.80 1395.05 1099.89 396.70 3199.73 199.73 9
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
APDe-MVS97.82 597.73 598.08 1799.15 3394.82 2698.81 798.30 2594.76 3698.30 1898.90 593.77 1799.68 4897.93 499.69 399.75 5
CNVR-MVS97.68 697.44 1098.37 798.90 5095.86 697.27 14198.08 6695.81 797.87 2898.31 5094.26 1399.68 4897.02 2399.49 3699.57 23
SteuartSystems-ACMMP97.62 797.53 897.87 2398.39 7794.25 3798.43 2498.27 3295.34 1398.11 2098.56 2194.53 1299.71 4096.57 3599.62 1599.65 13
Skip Steuart: Steuart Systems R&D Blog.
MSP-MVS97.59 897.54 797.73 3599.40 1193.77 5398.53 1598.29 2795.55 998.56 1597.81 8993.90 1599.65 5296.62 3299.21 6699.77 1
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_fmvsm_n_192097.55 997.89 396.53 7398.41 7491.73 10198.01 5699.02 196.37 399.30 198.92 392.39 3599.79 3199.16 299.46 3998.08 155
TSAR-MVS + MP.97.42 1097.33 1297.69 3999.25 2794.24 3898.07 5297.85 10893.72 6598.57 1498.35 4193.69 1899.40 10097.06 2299.46 3999.44 44
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
SD-MVS97.41 1197.53 897.06 6198.57 6994.46 3097.92 6898.14 5694.82 3199.01 498.55 2394.18 1497.41 30996.94 2499.64 1399.32 56
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
SF-MVS97.39 1297.13 1398.17 1499.02 4295.28 1998.23 4098.27 3292.37 11998.27 1998.65 1993.33 2199.72 3996.49 3799.52 2899.51 34
SMA-MVScopyleft97.35 1397.03 1998.30 899.06 3895.42 1097.94 6698.18 4990.57 18098.85 1098.94 293.33 2199.83 2596.72 3099.68 499.63 15
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
HPM-MVS++copyleft97.34 1496.97 2198.47 599.08 3696.16 497.55 11297.97 9395.59 896.61 6297.89 8092.57 3299.84 2295.95 5699.51 3199.40 49
NCCC97.30 1597.03 1998.11 1698.77 5395.06 2497.34 13498.04 8195.96 597.09 4597.88 8293.18 2399.71 4095.84 6199.17 6999.56 26
ACMMP_NAP97.20 1696.86 2498.23 1199.09 3495.16 2297.60 10598.19 4792.82 10897.93 2698.74 1691.60 4999.86 896.26 4099.52 2899.67 11
XVS97.18 1796.96 2297.81 2799.38 1494.03 4798.59 1298.20 4494.85 2796.59 6498.29 5391.70 4699.80 2995.66 6599.40 4899.62 16
MCST-MVS97.18 1796.84 2698.20 1399.30 2495.35 1597.12 15698.07 7193.54 7396.08 8497.69 9693.86 1699.71 4096.50 3699.39 5099.55 29
HFP-MVS97.14 1996.92 2397.83 2599.42 794.12 4398.52 1698.32 2393.21 8697.18 4098.29 5392.08 4099.83 2595.63 7099.59 1799.54 30
MTAPA97.08 2096.78 3297.97 2199.37 1694.42 3297.24 14398.08 6695.07 2396.11 8298.59 2090.88 6599.90 296.18 4999.50 3399.58 22
region2R97.07 2196.84 2697.77 3299.46 293.79 5198.52 1698.24 3993.19 8997.14 4298.34 4491.59 5099.87 795.46 7799.59 1799.64 14
ACMMPR97.07 2196.84 2697.79 2999.44 693.88 4998.52 1698.31 2493.21 8697.15 4198.33 4791.35 5499.86 895.63 7099.59 1799.62 16
MVS_030497.04 2396.73 3497.96 2297.60 12994.36 3398.01 5694.09 33497.33 196.29 7698.79 1489.73 7899.86 899.36 199.42 4599.67 11
CP-MVS97.02 2496.81 3097.64 4299.33 2193.54 5698.80 898.28 2992.99 9796.45 7298.30 5291.90 4399.85 1795.61 7299.68 499.54 30
SR-MVS97.01 2596.86 2497.47 4599.09 3493.27 6597.98 5998.07 7193.75 6497.45 3298.48 3191.43 5299.59 6496.22 4399.27 5999.54 30
ZNCC-MVS96.96 2696.67 3797.85 2499.37 1694.12 4398.49 2098.18 4992.64 11496.39 7498.18 6091.61 4899.88 495.59 7599.55 2499.57 23
APD-MVScopyleft96.95 2796.60 3998.01 1899.03 4194.93 2597.72 8898.10 6491.50 14198.01 2398.32 4992.33 3699.58 6794.85 9099.51 3199.53 33
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
MSLP-MVS++96.94 2897.06 1596.59 7198.72 5591.86 10097.67 9398.49 1494.66 4197.24 3998.41 3792.31 3898.94 14996.61 3399.46 3998.96 88
DeepC-MVS_fast93.89 296.93 2996.64 3897.78 3098.64 6494.30 3497.41 12498.04 8194.81 3296.59 6498.37 3991.24 5699.64 5995.16 8399.52 2899.42 48
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
CS-MVS-test96.89 3097.04 1896.45 8498.29 8291.66 10799.03 497.85 10895.84 696.90 4997.97 7691.24 5698.75 16696.92 2599.33 5598.94 91
SR-MVS-dyc-post96.88 3196.80 3197.11 6099.02 4292.34 8597.98 5998.03 8393.52 7597.43 3598.51 2691.40 5399.56 7596.05 5199.26 6199.43 46
CS-MVS96.86 3297.06 1596.26 10098.16 9691.16 13499.09 397.87 10395.30 1497.06 4698.03 7091.72 4498.71 17297.10 2199.17 6998.90 96
mPP-MVS96.86 3296.60 3997.64 4299.40 1193.44 5898.50 1998.09 6593.27 8595.95 9098.33 4791.04 6199.88 495.20 8299.57 2399.60 19
GST-MVS96.85 3496.52 4397.82 2699.36 1894.14 4298.29 3198.13 5792.72 11196.70 5698.06 6791.35 5499.86 894.83 9199.28 5899.47 41
patch_mono-296.83 3597.44 1095.01 16299.05 3985.39 28796.98 16598.77 694.70 3897.99 2498.66 1793.61 1999.91 197.67 899.50 3399.72 10
APD-MVS_3200maxsize96.81 3696.71 3697.12 5999.01 4592.31 8797.98 5998.06 7493.11 9497.44 3398.55 2390.93 6399.55 7796.06 5099.25 6399.51 34
PGM-MVS96.81 3696.53 4297.65 4099.35 2093.53 5797.65 9698.98 292.22 12197.14 4298.44 3491.17 5999.85 1794.35 10399.46 3999.57 23
MP-MVScopyleft96.77 3896.45 4897.72 3699.39 1393.80 5098.41 2598.06 7493.37 8195.54 10598.34 4490.59 6999.88 494.83 9199.54 2699.49 38
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
PHI-MVS96.77 3896.46 4797.71 3898.40 7594.07 4598.21 4398.45 1789.86 19297.11 4498.01 7392.52 3399.69 4696.03 5499.53 2799.36 54
test_fmvsmvis_n_192096.70 4096.84 2696.31 9496.62 17691.73 10197.98 5998.30 2596.19 496.10 8398.95 189.42 7999.76 3398.90 399.08 7697.43 184
MP-MVS-pluss96.70 4096.27 5297.98 2099.23 3094.71 2796.96 16798.06 7490.67 17195.55 10398.78 1591.07 6099.86 896.58 3499.55 2499.38 52
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
TSAR-MVS + GP.96.69 4296.49 4497.27 5398.31 8193.39 5996.79 17996.72 22594.17 5397.44 3397.66 10092.76 2699.33 10596.86 2797.76 12199.08 77
HPM-MVScopyleft96.69 4296.45 4897.40 4799.36 1893.11 6898.87 698.06 7491.17 15696.40 7397.99 7490.99 6299.58 6795.61 7299.61 1699.49 38
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
MVS_111021_HR96.68 4496.58 4196.99 6298.46 7092.31 8796.20 23398.90 394.30 5195.86 9297.74 9492.33 3699.38 10396.04 5399.42 4599.28 59
DELS-MVS96.61 4596.38 5097.30 5097.79 11693.19 6695.96 24498.18 4995.23 1595.87 9197.65 10191.45 5199.70 4595.87 5799.44 4499.00 86
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
DeepPCF-MVS93.97 196.61 4597.09 1495.15 15398.09 9986.63 26796.00 24298.15 5495.43 1097.95 2598.56 2193.40 2099.36 10496.77 2899.48 3799.45 42
EI-MVSNet-Vis-set96.51 4796.47 4596.63 6898.24 8691.20 12996.89 17197.73 11794.74 3796.49 6898.49 2890.88 6599.58 6796.44 3898.32 10499.13 71
HPM-MVS_fast96.51 4796.27 5297.22 5599.32 2292.74 7598.74 998.06 7490.57 18096.77 5398.35 4190.21 7299.53 8194.80 9499.63 1499.38 52
EC-MVSNet96.42 4996.47 4596.26 10097.01 15691.52 11398.89 597.75 11494.42 4696.64 6197.68 9789.32 8098.60 18297.45 1699.11 7598.67 115
CANet96.39 5096.02 5597.50 4497.62 12693.38 6097.02 16097.96 9495.42 1194.86 11597.81 8987.38 11099.82 2796.88 2699.20 6799.29 57
dcpmvs_296.37 5197.05 1794.31 20198.96 4684.11 30597.56 10997.51 14493.92 5997.43 3598.52 2592.75 2799.32 10797.32 2099.50 3399.51 34
EI-MVSNet-UG-set96.34 5296.30 5196.47 8198.20 9190.93 14196.86 17397.72 11994.67 4096.16 8198.46 3290.43 7099.58 6796.23 4297.96 11598.90 96
train_agg96.30 5395.83 5997.72 3698.70 5694.19 3996.41 21298.02 8688.58 23496.03 8597.56 11192.73 2999.59 6495.04 8599.37 5499.39 50
ACMMPcopyleft96.27 5495.93 5697.28 5299.24 2892.62 7898.25 3698.81 492.99 9794.56 12198.39 3888.96 8599.85 1794.57 10297.63 12299.36 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
MVS_111021_LR96.24 5596.19 5496.39 8998.23 9091.35 12196.24 23198.79 593.99 5795.80 9497.65 10189.92 7699.24 11495.87 5799.20 6798.58 117
DeepC-MVS93.07 396.06 5695.66 6097.29 5197.96 10593.17 6797.30 13998.06 7493.92 5993.38 14898.66 1786.83 11699.73 3695.60 7499.22 6598.96 88
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
CSCG96.05 5795.91 5796.46 8399.24 2890.47 15698.30 3098.57 1389.01 21793.97 13597.57 10992.62 3199.76 3394.66 9799.27 5999.15 69
ETV-MVS96.02 5895.89 5896.40 8797.16 14292.44 8397.47 12197.77 11394.55 4396.48 6994.51 26391.23 5898.92 15195.65 6898.19 10897.82 167
canonicalmvs96.02 5895.45 6597.75 3497.59 13095.15 2398.28 3297.60 13394.52 4496.27 7896.12 19087.65 10399.18 12096.20 4894.82 18398.91 95
CDPH-MVS95.97 6095.38 6897.77 3298.93 4794.44 3196.35 22097.88 10186.98 27696.65 6097.89 8091.99 4299.47 9292.26 13999.46 3999.39 50
UA-Net95.95 6195.53 6297.20 5797.67 12192.98 7197.65 9698.13 5794.81 3296.61 6298.35 4188.87 8699.51 8690.36 17997.35 13299.11 75
VNet95.89 6295.45 6597.21 5698.07 10392.94 7297.50 11598.15 5493.87 6197.52 3197.61 10785.29 13699.53 8195.81 6295.27 17599.16 67
alignmvs95.87 6395.23 7297.78 3097.56 13395.19 2197.86 7197.17 18494.39 4896.47 7096.40 17785.89 12999.20 11796.21 4795.11 17998.95 90
casdiffmvs_mvgpermissive95.81 6495.57 6196.51 7796.87 16191.49 11497.50 11597.56 14093.99 5795.13 11297.92 7987.89 9998.78 16195.97 5597.33 13399.26 61
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
DPM-MVS95.69 6594.92 7898.01 1898.08 10295.71 995.27 27497.62 13290.43 18395.55 10397.07 13491.72 4499.50 8989.62 19498.94 8398.82 105
DP-MVS Recon95.68 6695.12 7697.37 4899.19 3194.19 3997.03 15898.08 6688.35 24195.09 11397.65 10189.97 7599.48 9192.08 14898.59 9498.44 134
casdiffmvspermissive95.64 6795.49 6396.08 10796.76 17390.45 15797.29 14097.44 16194.00 5695.46 10797.98 7587.52 10798.73 16895.64 6997.33 13399.08 77
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
MG-MVS95.61 6895.38 6896.31 9498.42 7390.53 15496.04 23997.48 14793.47 7795.67 10098.10 6389.17 8299.25 11391.27 16698.77 8899.13 71
baseline95.58 6995.42 6796.08 10796.78 16890.41 15997.16 15397.45 15793.69 6895.65 10197.85 8687.29 11198.68 17495.66 6597.25 13799.13 71
CPTT-MVS95.57 7095.19 7396.70 6599.27 2691.48 11598.33 2898.11 6287.79 25795.17 11198.03 7087.09 11499.61 6093.51 11999.42 4599.02 80
EIA-MVS95.53 7195.47 6495.71 12897.06 15189.63 17697.82 7797.87 10393.57 6993.92 13695.04 24090.61 6898.95 14894.62 9998.68 9198.54 119
3Dnovator+91.43 495.40 7294.48 9498.16 1596.90 16095.34 1698.48 2197.87 10394.65 4288.53 26998.02 7283.69 15799.71 4093.18 12698.96 8299.44 44
PS-MVSNAJ95.37 7395.33 7095.49 14197.35 13690.66 15295.31 27197.48 14793.85 6296.51 6795.70 21488.65 9099.65 5294.80 9498.27 10596.17 221
MVSFormer95.37 7395.16 7495.99 11496.34 19791.21 12798.22 4197.57 13791.42 14596.22 7997.32 11986.20 12697.92 26394.07 10799.05 7798.85 102
xiu_mvs_v2_base95.32 7595.29 7195.40 14697.22 13890.50 15595.44 26597.44 16193.70 6796.46 7196.18 18688.59 9399.53 8194.79 9697.81 11896.17 221
PVSNet_Blended_VisFu95.27 7694.91 7996.38 9098.20 9190.86 14397.27 14198.25 3790.21 18594.18 12997.27 12387.48 10899.73 3693.53 11897.77 12098.55 118
diffmvspermissive95.25 7795.13 7595.63 13196.43 19389.34 19295.99 24397.35 17392.83 10796.31 7597.37 11886.44 12198.67 17596.26 4097.19 13998.87 101
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
Vis-MVSNetpermissive95.23 7894.81 8096.51 7797.18 14191.58 11198.26 3598.12 5994.38 4994.90 11498.15 6282.28 19198.92 15191.45 16398.58 9599.01 83
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
EPP-MVSNet95.22 7995.04 7795.76 12197.49 13489.56 18098.67 1097.00 20390.69 16994.24 12797.62 10689.79 7798.81 15993.39 12496.49 15498.92 94
EPNet95.20 8094.56 8897.14 5892.80 33592.68 7797.85 7494.87 31996.64 292.46 16497.80 9186.23 12399.65 5293.72 11798.62 9399.10 76
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
3Dnovator91.36 595.19 8194.44 9697.44 4696.56 18393.36 6298.65 1198.36 1894.12 5489.25 25498.06 6782.20 19399.77 3293.41 12399.32 5699.18 66
OMC-MVS95.09 8294.70 8496.25 10398.46 7091.28 12396.43 21097.57 13792.04 13094.77 11797.96 7787.01 11599.09 13291.31 16596.77 14698.36 141
xiu_mvs_v1_base_debu95.01 8394.76 8195.75 12396.58 18091.71 10396.25 22897.35 17392.99 9796.70 5696.63 16482.67 18199.44 9696.22 4397.46 12596.11 226
xiu_mvs_v1_base95.01 8394.76 8195.75 12396.58 18091.71 10396.25 22897.35 17392.99 9796.70 5696.63 16482.67 18199.44 9696.22 4397.46 12596.11 226
xiu_mvs_v1_base_debi95.01 8394.76 8195.75 12396.58 18091.71 10396.25 22897.35 17392.99 9796.70 5696.63 16482.67 18199.44 9696.22 4397.46 12596.11 226
PAPM_NR95.01 8394.59 8696.26 10098.89 5190.68 15197.24 14397.73 11791.80 13592.93 16196.62 16789.13 8399.14 12589.21 20697.78 11998.97 87
lupinMVS94.99 8794.56 8896.29 9896.34 19791.21 12795.83 24996.27 25288.93 22296.22 7996.88 14586.20 12698.85 15695.27 8199.05 7798.82 105
Effi-MVS+94.93 8894.45 9596.36 9296.61 17791.47 11696.41 21297.41 16691.02 16194.50 12295.92 19887.53 10698.78 16193.89 11396.81 14598.84 104
IS-MVSNet94.90 8994.52 9296.05 11097.67 12190.56 15398.44 2396.22 25593.21 8693.99 13397.74 9485.55 13498.45 19489.98 18397.86 11699.14 70
MVS_Test94.89 9094.62 8595.68 12996.83 16589.55 18196.70 18897.17 18491.17 15695.60 10296.11 19387.87 10098.76 16593.01 13497.17 14098.72 110
PVSNet_Blended94.87 9194.56 8895.81 12098.27 8389.46 18795.47 26498.36 1888.84 22594.36 12496.09 19488.02 9699.58 6793.44 12198.18 10998.40 137
jason94.84 9294.39 9796.18 10595.52 23090.93 14196.09 23796.52 24189.28 20996.01 8897.32 11984.70 14398.77 16495.15 8498.91 8598.85 102
jason: jason.
API-MVS94.84 9294.49 9395.90 11697.90 11192.00 9797.80 7997.48 14789.19 21294.81 11696.71 15088.84 8799.17 12188.91 21398.76 8996.53 210
test_yl94.78 9494.23 9896.43 8597.74 11891.22 12596.85 17497.10 18991.23 15395.71 9796.93 14084.30 14999.31 10993.10 12795.12 17798.75 107
DCV-MVSNet94.78 9494.23 9896.43 8597.74 11891.22 12596.85 17497.10 18991.23 15395.71 9796.93 14084.30 14999.31 10993.10 12795.12 17798.75 107
WTY-MVS94.71 9694.02 10096.79 6497.71 12092.05 9596.59 20397.35 17390.61 17794.64 11996.93 14086.41 12299.39 10191.20 16894.71 18798.94 91
sss94.51 9793.80 10496.64 6697.07 14891.97 9896.32 22398.06 7488.94 22194.50 12296.78 14784.60 14499.27 11291.90 14996.02 15998.68 114
test_cas_vis1_n_192094.48 9894.55 9194.28 20396.78 16886.45 26997.63 10297.64 12993.32 8497.68 3098.36 4073.75 30399.08 13496.73 2999.05 7797.31 190
CANet_DTU94.37 9993.65 10896.55 7296.46 19192.13 9396.21 23296.67 23294.38 4993.53 14497.03 13779.34 24099.71 4090.76 17398.45 10197.82 167
AdaColmapbinary94.34 10093.68 10796.31 9498.59 6691.68 10696.59 20397.81 11289.87 19192.15 17397.06 13583.62 16099.54 7989.34 20098.07 11297.70 171
CNLPA94.28 10193.53 11396.52 7498.38 7892.55 8096.59 20396.88 21690.13 18891.91 17997.24 12585.21 13799.09 13287.64 23797.83 11797.92 159
MAR-MVS94.22 10293.46 11896.51 7798.00 10492.19 9297.67 9397.47 15088.13 24893.00 15695.84 20284.86 14299.51 8687.99 22498.17 11097.83 166
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
PAPR94.18 10393.42 12396.48 8097.64 12591.42 11995.55 26097.71 12388.99 21892.34 17095.82 20489.19 8199.11 12886.14 26397.38 13098.90 96
SDMVSNet94.17 10493.61 10995.86 11898.09 9991.37 12097.35 13398.20 4493.18 9091.79 18297.28 12179.13 24498.93 15094.61 10092.84 20797.28 191
test_vis1_n_192094.17 10494.58 8792.91 26597.42 13582.02 32597.83 7697.85 10894.68 3998.10 2198.49 2870.15 32399.32 10797.91 598.82 8697.40 185
h-mvs3394.15 10693.52 11596.04 11197.81 11590.22 16197.62 10497.58 13695.19 1696.74 5497.45 11483.67 15899.61 6095.85 5979.73 34598.29 144
CHOSEN 1792x268894.15 10693.51 11696.06 10998.27 8389.38 19095.18 27898.48 1685.60 29893.76 13997.11 13283.15 16899.61 6091.33 16498.72 9099.19 65
Vis-MVSNet (Re-imp)94.15 10693.88 10394.95 16897.61 12787.92 23798.10 4995.80 27192.22 12193.02 15597.45 11484.53 14697.91 26688.24 22197.97 11499.02 80
CDS-MVSNet94.14 10993.54 11295.93 11596.18 20491.46 11796.33 22297.04 19988.97 22093.56 14196.51 17187.55 10597.89 26789.80 18895.95 16198.44 134
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
PLCcopyleft91.00 694.11 11093.43 12196.13 10698.58 6891.15 13596.69 19097.39 16787.29 27191.37 19296.71 15088.39 9499.52 8587.33 24497.13 14197.73 169
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
FIs94.09 11193.70 10695.27 14995.70 22392.03 9698.10 4998.68 993.36 8390.39 21296.70 15287.63 10497.94 25992.25 14190.50 25295.84 234
PVSNet_BlendedMVS94.06 11293.92 10294.47 19298.27 8389.46 18796.73 18498.36 1890.17 18694.36 12495.24 23488.02 9699.58 6793.44 12190.72 24894.36 317
nrg03094.05 11393.31 12596.27 9995.22 25394.59 2898.34 2797.46 15292.93 10591.21 20296.64 15887.23 11398.22 21394.99 8885.80 29495.98 230
UGNet94.04 11493.28 12696.31 9496.85 16291.19 13097.88 7097.68 12494.40 4793.00 15696.18 18673.39 30599.61 6091.72 15598.46 10098.13 149
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
TAMVS94.01 11593.46 11895.64 13096.16 20690.45 15796.71 18796.89 21589.27 21093.46 14696.92 14387.29 11197.94 25988.70 21795.74 16698.53 120
114514_t93.95 11693.06 13196.63 6899.07 3791.61 10897.46 12397.96 9477.99 35893.00 15697.57 10986.14 12899.33 10589.22 20599.15 7198.94 91
FC-MVSNet-test93.94 11793.57 11095.04 15995.48 23291.45 11898.12 4898.71 793.37 8190.23 21596.70 15287.66 10297.85 26991.49 16190.39 25395.83 235
mvsany_test193.93 11893.98 10193.78 23194.94 26786.80 26094.62 28692.55 35188.77 23196.85 5098.49 2888.98 8498.08 23395.03 8695.62 17096.46 215
GeoE93.89 11993.28 12695.72 12796.96 15989.75 17498.24 3996.92 21289.47 20492.12 17597.21 12784.42 14798.39 20187.71 23196.50 15399.01 83
HY-MVS89.66 993.87 12092.95 13496.63 6897.10 14792.49 8295.64 25896.64 23389.05 21693.00 15695.79 20885.77 13299.45 9589.16 20994.35 18997.96 157
XVG-OURS-SEG-HR93.86 12193.55 11194.81 17697.06 15188.53 21895.28 27297.45 15791.68 13894.08 13297.68 9782.41 18998.90 15493.84 11592.47 21396.98 198
mvsmamba93.83 12293.46 11894.93 17194.88 27290.85 14498.55 1495.49 28794.24 5291.29 19996.97 13983.04 17298.14 22195.56 7691.17 23895.78 240
VDD-MVS93.82 12393.08 13096.02 11297.88 11289.96 17097.72 8895.85 26992.43 11795.86 9298.44 3468.42 33299.39 10196.31 3994.85 18198.71 112
mvs_anonymous93.82 12393.74 10594.06 21196.44 19285.41 28595.81 25097.05 19789.85 19490.09 22596.36 17987.44 10997.75 27993.97 10996.69 15099.02 80
HQP_MVS93.78 12593.43 12194.82 17496.21 20189.99 16697.74 8397.51 14494.85 2791.34 19396.64 15881.32 20798.60 18293.02 13292.23 21695.86 231
PS-MVSNAJss93.74 12693.51 11694.44 19393.91 30789.28 19797.75 8297.56 14092.50 11689.94 22996.54 17088.65 9098.18 21893.83 11690.90 24595.86 231
XVG-OURS93.72 12793.35 12494.80 17997.07 14888.61 21394.79 28397.46 15291.97 13393.99 13397.86 8581.74 20298.88 15592.64 13892.67 21296.92 202
HyFIR lowres test93.66 12892.92 13595.87 11798.24 8689.88 17194.58 28898.49 1485.06 30893.78 13895.78 20982.86 17798.67 17591.77 15495.71 16899.07 79
iter_conf_final93.60 12993.11 12995.04 15997.13 14591.30 12297.92 6895.65 28092.98 10291.60 18596.64 15879.28 24298.13 22295.34 8091.49 23095.70 248
LFMVS93.60 12992.63 14996.52 7498.13 9891.27 12497.94 6693.39 34490.57 18096.29 7698.31 5069.00 32899.16 12294.18 10695.87 16399.12 74
F-COLMAP93.58 13192.98 13395.37 14798.40 7588.98 20697.18 15197.29 17887.75 26090.49 20997.10 13385.21 13799.50 8986.70 25496.72 14997.63 173
ab-mvs93.57 13292.55 15496.64 6697.28 13791.96 9995.40 26697.45 15789.81 19693.22 15496.28 18279.62 23799.46 9390.74 17493.11 20498.50 124
LS3D93.57 13292.61 15296.47 8197.59 13091.61 10897.67 9397.72 11985.17 30690.29 21498.34 4484.60 14499.73 3683.85 29698.27 10598.06 156
FA-MVS(test-final)93.52 13492.92 13595.31 14896.77 17088.54 21794.82 28296.21 25789.61 19994.20 12895.25 23383.24 16599.14 12590.01 18296.16 15898.25 145
Fast-Effi-MVS+93.46 13592.75 14495.59 13496.77 17090.03 16396.81 17897.13 18688.19 24491.30 19694.27 27986.21 12598.63 17987.66 23696.46 15698.12 150
hse-mvs293.45 13692.99 13294.81 17697.02 15588.59 21496.69 19096.47 24495.19 1696.74 5496.16 18983.67 15898.48 19395.85 5979.13 34997.35 188
QAPM93.45 13692.27 16496.98 6396.77 17092.62 7898.39 2698.12 5984.50 31688.27 27697.77 9282.39 19099.81 2885.40 27698.81 8798.51 123
UniMVSNet_NR-MVSNet93.37 13892.67 14895.47 14495.34 24292.83 7397.17 15298.58 1292.98 10290.13 22095.80 20588.37 9597.85 26991.71 15683.93 32295.73 247
1112_ss93.37 13892.42 16196.21 10497.05 15390.99 13796.31 22496.72 22586.87 27989.83 23396.69 15486.51 12099.14 12588.12 22293.67 19898.50 124
UniMVSNet (Re)93.31 14092.55 15495.61 13395.39 23693.34 6397.39 12998.71 793.14 9390.10 22494.83 25087.71 10198.03 24491.67 15983.99 32195.46 258
OPM-MVS93.28 14192.76 14294.82 17494.63 28590.77 14896.65 19497.18 18293.72 6591.68 18497.26 12479.33 24198.63 17992.13 14592.28 21595.07 280
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
VPA-MVSNet93.24 14292.48 15995.51 13995.70 22392.39 8497.86 7198.66 1192.30 12092.09 17795.37 22880.49 22098.40 19793.95 11085.86 29395.75 245
test_fmvs193.21 14393.53 11392.25 28496.55 18581.20 33297.40 12896.96 20590.68 17096.80 5198.04 6969.25 32798.40 19797.58 1198.50 9697.16 195
MVSTER93.20 14492.81 14194.37 19796.56 18389.59 17997.06 15797.12 18791.24 15291.30 19695.96 19682.02 19698.05 24093.48 12090.55 25095.47 257
test111193.19 14592.82 14094.30 20297.58 13284.56 30098.21 4389.02 36893.53 7494.58 12098.21 5772.69 30699.05 14193.06 13098.48 9999.28 59
ECVR-MVScopyleft93.19 14592.73 14694.57 19097.66 12385.41 28598.21 4388.23 36993.43 7994.70 11898.21 5772.57 30799.07 13893.05 13198.49 9799.25 62
HQP-MVS93.19 14592.74 14594.54 19195.86 21689.33 19396.65 19497.39 16793.55 7090.14 21695.87 20080.95 21098.50 19092.13 14592.10 22195.78 240
iter_conf0593.18 14892.63 14994.83 17396.64 17590.69 15097.60 10595.53 28692.52 11591.58 18696.64 15876.35 28298.13 22295.43 7891.42 23395.68 250
CHOSEN 280x42093.12 14992.72 14794.34 19996.71 17487.27 24890.29 35797.72 11986.61 28391.34 19395.29 23084.29 15198.41 19693.25 12598.94 8397.35 188
sd_testset93.10 15092.45 16095.05 15898.09 9989.21 19996.89 17197.64 12993.18 9091.79 18297.28 12175.35 29198.65 17788.99 21192.84 20797.28 191
RRT_MVS93.10 15092.83 13993.93 22494.76 27788.04 23398.47 2296.55 24093.44 7890.01 22897.04 13680.64 21797.93 26294.33 10490.21 25595.83 235
Effi-MVS+-dtu93.08 15293.21 12892.68 27596.02 21483.25 31597.14 15596.72 22593.85 6291.20 20393.44 31183.08 17098.30 20891.69 15895.73 16796.50 212
test_djsdf93.07 15392.76 14294.00 21593.49 32188.70 21298.22 4197.57 13791.42 14590.08 22695.55 22282.85 17897.92 26394.07 10791.58 22895.40 263
VDDNet93.05 15492.07 16896.02 11296.84 16390.39 16098.08 5195.85 26986.22 29095.79 9598.46 3267.59 33599.19 11894.92 8994.85 18198.47 129
thisisatest053093.03 15592.21 16695.49 14197.07 14889.11 20497.49 12092.19 35390.16 18794.09 13196.41 17676.43 28199.05 14190.38 17895.68 16998.31 143
EI-MVSNet93.03 15592.88 13793.48 24595.77 22186.98 25796.44 20897.12 18790.66 17391.30 19697.64 10486.56 11898.05 24089.91 18590.55 25095.41 260
CLD-MVS92.98 15792.53 15694.32 20096.12 21089.20 20095.28 27297.47 15092.66 11289.90 23095.62 21880.58 21898.40 19792.73 13792.40 21495.38 265
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
tttt051792.96 15892.33 16394.87 17297.11 14687.16 25497.97 6592.09 35490.63 17593.88 13797.01 13876.50 27899.06 14090.29 18195.45 17298.38 139
ACMM89.79 892.96 15892.50 15894.35 19896.30 19988.71 21197.58 10797.36 17291.40 14790.53 20896.65 15779.77 23498.75 16691.24 16791.64 22695.59 252
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
LPG-MVS_test92.94 16092.56 15394.10 20996.16 20688.26 22597.65 9697.46 15291.29 14890.12 22297.16 12979.05 24698.73 16892.25 14191.89 22495.31 269
BH-untuned92.94 16092.62 15193.92 22597.22 13886.16 27796.40 21696.25 25490.06 18989.79 23496.17 18883.19 16698.35 20487.19 24797.27 13697.24 193
DU-MVS92.90 16292.04 16995.49 14194.95 26592.83 7397.16 15398.24 3993.02 9690.13 22095.71 21283.47 16197.85 26991.71 15683.93 32295.78 240
PatchMatch-RL92.90 16292.02 17195.56 13598.19 9390.80 14695.27 27497.18 18287.96 25091.86 18195.68 21580.44 22198.99 14684.01 29297.54 12496.89 203
PMMVS92.86 16492.34 16294.42 19594.92 26886.73 26394.53 29096.38 24884.78 31394.27 12695.12 23983.13 16998.40 19791.47 16296.49 15498.12 150
OpenMVScopyleft89.19 1292.86 16491.68 18396.40 8795.34 24292.73 7698.27 3398.12 5984.86 31185.78 31297.75 9378.89 25399.74 3587.50 24198.65 9296.73 207
Test_1112_low_res92.84 16691.84 17795.85 11997.04 15489.97 16995.53 26296.64 23385.38 30189.65 23995.18 23585.86 13099.10 12987.70 23293.58 20398.49 126
baseline192.82 16791.90 17595.55 13797.20 14090.77 14897.19 15094.58 32492.20 12392.36 16896.34 18084.16 15298.21 21489.20 20783.90 32597.68 172
131492.81 16892.03 17095.14 15495.33 24589.52 18496.04 23997.44 16187.72 26186.25 30995.33 22983.84 15598.79 16089.26 20397.05 14297.11 196
DP-MVS92.76 16991.51 19196.52 7498.77 5390.99 13797.38 13196.08 26182.38 33589.29 25197.87 8383.77 15699.69 4681.37 31796.69 15098.89 99
test_fmvs1_n92.73 17092.88 13792.29 28296.08 21381.05 33397.98 5997.08 19290.72 16896.79 5298.18 6063.07 35498.45 19497.62 1098.42 10297.36 186
BH-RMVSNet92.72 17191.97 17394.97 16697.16 14287.99 23596.15 23595.60 28190.62 17691.87 18097.15 13178.41 25998.57 18683.16 29897.60 12398.36 141
ACMP89.59 1092.62 17292.14 16794.05 21296.40 19488.20 22897.36 13297.25 18191.52 14088.30 27496.64 15878.46 25898.72 17191.86 15291.48 23195.23 276
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
LCM-MVSNet-Re92.50 17392.52 15792.44 27796.82 16781.89 32696.92 16993.71 34092.41 11884.30 32594.60 26185.08 13997.03 32291.51 16097.36 13198.40 137
TranMVSNet+NR-MVSNet92.50 17391.63 18495.14 15494.76 27792.07 9497.53 11398.11 6292.90 10689.56 24296.12 19083.16 16797.60 29289.30 20183.20 33195.75 245
thres600view792.49 17591.60 18595.18 15297.91 11089.47 18597.65 9694.66 32192.18 12793.33 14994.91 24578.06 26699.10 12981.61 31194.06 19596.98 198
thres100view90092.43 17691.58 18694.98 16597.92 10989.37 19197.71 9094.66 32192.20 12393.31 15094.90 24678.06 26699.08 13481.40 31494.08 19296.48 213
jajsoiax92.42 17791.89 17694.03 21493.33 32788.50 21997.73 8597.53 14292.00 13288.85 26196.50 17275.62 28998.11 22893.88 11491.56 22995.48 254
thres40092.42 17791.52 18995.12 15697.85 11389.29 19597.41 12494.88 31692.19 12593.27 15294.46 26878.17 26299.08 13481.40 31494.08 19296.98 198
tfpn200view992.38 17991.52 18994.95 16897.85 11389.29 19597.41 12494.88 31692.19 12593.27 15294.46 26878.17 26299.08 13481.40 31494.08 19296.48 213
test_vis1_n92.37 18092.26 16592.72 27294.75 27982.64 31798.02 5596.80 22291.18 15597.77 2997.93 7858.02 36198.29 20997.63 998.21 10797.23 194
bld_raw_dy_0_6492.37 18091.69 18294.39 19694.28 29989.73 17597.71 9093.65 34192.78 11090.46 21096.67 15675.88 28497.97 25192.92 13690.89 24695.48 254
WR-MVS92.34 18291.53 18894.77 18195.13 25890.83 14596.40 21697.98 9291.88 13489.29 25195.54 22382.50 18697.80 27489.79 18985.27 30295.69 249
NR-MVSNet92.34 18291.27 19995.53 13894.95 26593.05 6997.39 12998.07 7192.65 11384.46 32395.71 21285.00 14097.77 27889.71 19083.52 32895.78 240
mvs_tets92.31 18491.76 17893.94 22293.41 32488.29 22397.63 10297.53 14292.04 13088.76 26496.45 17474.62 29598.09 23293.91 11291.48 23195.45 259
TAPA-MVS90.10 792.30 18591.22 20295.56 13598.33 8089.60 17896.79 17997.65 12781.83 33991.52 18897.23 12687.94 9898.91 15371.31 36198.37 10398.17 148
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
thisisatest051592.29 18691.30 19795.25 15096.60 17888.90 20894.36 29792.32 35287.92 25193.43 14794.57 26277.28 27399.00 14589.42 19895.86 16497.86 163
Fast-Effi-MVS+-dtu92.29 18691.99 17293.21 25695.27 24985.52 28397.03 15896.63 23692.09 12889.11 25795.14 23780.33 22498.08 23387.54 24094.74 18696.03 229
IterMVS-LS92.29 18691.94 17493.34 25096.25 20086.97 25896.57 20697.05 19790.67 17189.50 24594.80 25286.59 11797.64 28789.91 18586.11 29295.40 263
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
PVSNet86.66 1892.24 18991.74 18193.73 23297.77 11783.69 31292.88 33896.72 22587.91 25293.00 15694.86 24878.51 25799.05 14186.53 25597.45 12998.47 129
VPNet92.23 19091.31 19694.99 16395.56 22890.96 13997.22 14897.86 10792.96 10490.96 20496.62 16775.06 29298.20 21591.90 14983.65 32795.80 238
thres20092.23 19091.39 19294.75 18397.61 12789.03 20596.60 20295.09 30692.08 12993.28 15194.00 29178.39 26099.04 14481.26 31894.18 19196.19 220
anonymousdsp92.16 19291.55 18793.97 21892.58 33989.55 18197.51 11497.42 16589.42 20688.40 27194.84 24980.66 21697.88 26891.87 15191.28 23694.48 312
XXY-MVS92.16 19291.23 20194.95 16894.75 27990.94 14097.47 12197.43 16489.14 21388.90 25896.43 17579.71 23598.24 21189.56 19587.68 27795.67 251
BH-w/o92.14 19491.75 17993.31 25196.99 15885.73 28095.67 25595.69 27688.73 23289.26 25394.82 25182.97 17598.07 23785.26 27896.32 15796.13 225
Anonymous20240521192.07 19590.83 21595.76 12198.19 9388.75 21097.58 10795.00 30986.00 29393.64 14097.45 11466.24 34699.53 8190.68 17692.71 21099.01 83
FE-MVS92.05 19691.05 20695.08 15796.83 16587.93 23693.91 31495.70 27486.30 28794.15 13094.97 24176.59 27799.21 11684.10 29096.86 14398.09 154
WR-MVS_H92.00 19791.35 19393.95 22095.09 26089.47 18598.04 5498.68 991.46 14388.34 27294.68 25785.86 13097.56 29485.77 27184.24 31994.82 297
Anonymous2024052991.98 19890.73 21995.73 12698.14 9789.40 18997.99 5897.72 11979.63 35293.54 14397.41 11769.94 32599.56 7591.04 17091.11 24098.22 146
PatchmatchNetpermissive91.91 19991.35 19393.59 24095.38 23784.11 30593.15 33395.39 28989.54 20192.10 17693.68 30382.82 17998.13 22284.81 28295.32 17498.52 121
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
CP-MVSNet91.89 20091.24 20093.82 22895.05 26188.57 21597.82 7798.19 4791.70 13788.21 27895.76 21081.96 19797.52 30087.86 22684.65 31195.37 266
SCA91.84 20191.18 20493.83 22795.59 22684.95 29694.72 28495.58 28390.82 16392.25 17193.69 30175.80 28698.10 22986.20 26195.98 16098.45 131
FMVSNet391.78 20290.69 22195.03 16196.53 18692.27 8997.02 16096.93 20889.79 19789.35 24894.65 25977.01 27497.47 30386.12 26488.82 26695.35 267
AUN-MVS91.76 20390.75 21894.81 17697.00 15788.57 21596.65 19496.49 24389.63 19892.15 17396.12 19078.66 25598.50 19090.83 17179.18 34897.36 186
X-MVStestdata91.71 20489.67 26397.81 2799.38 1494.03 4798.59 1298.20 4494.85 2796.59 6432.69 38191.70 4699.80 2995.66 6599.40 4899.62 16
MVS91.71 20490.44 22895.51 13995.20 25591.59 11096.04 23997.45 15773.44 36687.36 29495.60 21985.42 13599.10 12985.97 26897.46 12595.83 235
EPNet_dtu91.71 20491.28 19892.99 26293.76 31283.71 31196.69 19095.28 29693.15 9287.02 30195.95 19783.37 16497.38 31179.46 32996.84 14497.88 162
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
baseline291.63 20790.86 21193.94 22294.33 29586.32 27195.92 24691.64 35889.37 20786.94 30294.69 25681.62 20498.69 17388.64 21894.57 18896.81 205
test250691.60 20890.78 21694.04 21397.66 12383.81 30898.27 3375.53 38493.43 7995.23 10998.21 5767.21 33899.07 13893.01 13498.49 9799.25 62
miper_ehance_all_eth91.59 20991.13 20592.97 26395.55 22986.57 26894.47 29196.88 21687.77 25888.88 26094.01 29086.22 12497.54 29689.49 19686.93 28494.79 302
v2v48291.59 20990.85 21393.80 22993.87 30988.17 23096.94 16896.88 21689.54 20189.53 24394.90 24681.70 20398.02 24589.25 20485.04 30895.20 277
V4291.58 21190.87 21093.73 23294.05 30488.50 21997.32 13796.97 20488.80 23089.71 23594.33 27482.54 18598.05 24089.01 21085.07 30694.64 310
PCF-MVS89.48 1191.56 21289.95 25196.36 9296.60 17892.52 8192.51 34397.26 17979.41 35388.90 25896.56 16984.04 15499.55 7777.01 34397.30 13597.01 197
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
PS-CasMVS91.55 21390.84 21493.69 23694.96 26488.28 22497.84 7598.24 3991.46 14388.04 28295.80 20579.67 23697.48 30287.02 25184.54 31695.31 269
miper_enhance_ethall91.54 21491.01 20793.15 25795.35 24187.07 25693.97 30996.90 21386.79 28089.17 25593.43 31386.55 11997.64 28789.97 18486.93 28494.74 306
PAPM91.52 21590.30 23495.20 15195.30 24889.83 17293.38 32996.85 21986.26 28988.59 26795.80 20584.88 14198.15 22075.67 34795.93 16297.63 173
ET-MVSNet_ETH3D91.49 21690.11 24495.63 13196.40 19491.57 11295.34 26893.48 34390.60 17975.58 36295.49 22580.08 22896.79 33094.25 10589.76 25998.52 121
TR-MVS91.48 21790.59 22494.16 20796.40 19487.33 24695.67 25595.34 29587.68 26291.46 19095.52 22476.77 27698.35 20482.85 30293.61 20196.79 206
tpmrst91.44 21891.32 19591.79 29695.15 25679.20 35293.42 32895.37 29188.55 23793.49 14593.67 30482.49 18798.27 21090.41 17789.34 26397.90 160
test-LLR91.42 21991.19 20392.12 28694.59 28680.66 33594.29 30192.98 34691.11 15890.76 20692.37 32579.02 24898.07 23788.81 21496.74 14797.63 173
MSDG91.42 21990.24 23894.96 16797.15 14488.91 20793.69 32196.32 25085.72 29786.93 30396.47 17380.24 22598.98 14780.57 32095.05 18096.98 198
c3_l91.38 22190.89 20992.88 26795.58 22786.30 27294.68 28596.84 22088.17 24588.83 26394.23 28285.65 13397.47 30389.36 19984.63 31294.89 292
GA-MVS91.38 22190.31 23394.59 18594.65 28487.62 24494.34 29896.19 25890.73 16790.35 21393.83 29571.84 31097.96 25687.22 24693.61 20198.21 147
v114491.37 22390.60 22393.68 23793.89 30888.23 22796.84 17697.03 20188.37 24089.69 23794.39 27082.04 19597.98 24887.80 22885.37 29994.84 294
GBi-Net91.35 22490.27 23694.59 18596.51 18791.18 13197.50 11596.93 20888.82 22789.35 24894.51 26373.87 29997.29 31586.12 26488.82 26695.31 269
test191.35 22490.27 23694.59 18596.51 18791.18 13197.50 11596.93 20888.82 22789.35 24894.51 26373.87 29997.29 31586.12 26488.82 26695.31 269
UniMVSNet_ETH3D91.34 22690.22 24194.68 18494.86 27387.86 24097.23 14797.46 15287.99 24989.90 23096.92 14366.35 34498.23 21290.30 18090.99 24397.96 157
FMVSNet291.31 22790.08 24594.99 16396.51 18792.21 9097.41 12496.95 20688.82 22788.62 26694.75 25473.87 29997.42 30885.20 27988.55 27195.35 267
D2MVS91.30 22890.95 20892.35 27994.71 28285.52 28396.18 23498.21 4388.89 22386.60 30693.82 29779.92 23297.95 25889.29 20290.95 24493.56 330
v891.29 22990.53 22793.57 24294.15 30088.12 23297.34 13497.06 19688.99 21888.32 27394.26 28183.08 17098.01 24687.62 23883.92 32494.57 311
CVMVSNet91.23 23091.75 17989.67 32995.77 22174.69 36296.44 20894.88 31685.81 29592.18 17297.64 10479.07 24595.58 34988.06 22395.86 16498.74 109
cl2291.21 23190.56 22693.14 25896.09 21286.80 26094.41 29596.58 23987.80 25688.58 26893.99 29280.85 21597.62 29089.87 18786.93 28494.99 283
PEN-MVS91.20 23290.44 22893.48 24594.49 28987.91 23997.76 8198.18 4991.29 14887.78 28695.74 21180.35 22397.33 31385.46 27582.96 33295.19 278
Baseline_NR-MVSNet91.20 23290.62 22292.95 26493.83 31088.03 23497.01 16395.12 30588.42 23989.70 23695.13 23883.47 16197.44 30689.66 19383.24 33093.37 334
cascas91.20 23290.08 24594.58 18994.97 26389.16 20393.65 32397.59 13579.90 35189.40 24692.92 31775.36 29098.36 20392.14 14494.75 18596.23 217
CostFormer91.18 23590.70 22092.62 27694.84 27481.76 32794.09 30794.43 32684.15 31992.72 16393.77 29979.43 23998.20 21590.70 17592.18 21997.90 160
tt080591.09 23690.07 24894.16 20795.61 22588.31 22297.56 10996.51 24289.56 20089.17 25595.64 21767.08 34298.38 20291.07 16988.44 27295.80 238
v119291.07 23790.23 23993.58 24193.70 31387.82 24196.73 18497.07 19487.77 25889.58 24094.32 27680.90 21497.97 25186.52 25685.48 29794.95 284
v14419291.06 23890.28 23593.39 24893.66 31687.23 25196.83 17797.07 19487.43 26789.69 23794.28 27881.48 20598.00 24787.18 24884.92 31094.93 288
v1091.04 23990.23 23993.49 24494.12 30188.16 23197.32 13797.08 19288.26 24388.29 27594.22 28482.17 19497.97 25186.45 25884.12 32094.33 318
eth_miper_zixun_eth91.02 24090.59 22492.34 28195.33 24584.35 30194.10 30696.90 21388.56 23688.84 26294.33 27484.08 15397.60 29288.77 21684.37 31895.06 281
v14890.99 24190.38 23092.81 27093.83 31085.80 27996.78 18196.68 23089.45 20588.75 26593.93 29482.96 17697.82 27387.83 22783.25 32994.80 300
LTVRE_ROB88.41 1390.99 24189.92 25394.19 20596.18 20489.55 18196.31 22497.09 19187.88 25385.67 31395.91 19978.79 25498.57 18681.50 31289.98 25694.44 315
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
DIV-MVS_self_test90.97 24390.33 23192.88 26795.36 24086.19 27694.46 29396.63 23687.82 25488.18 27994.23 28282.99 17397.53 29887.72 22985.57 29694.93 288
cl____90.96 24490.32 23292.89 26695.37 23986.21 27594.46 29396.64 23387.82 25488.15 28094.18 28582.98 17497.54 29687.70 23285.59 29594.92 290
pmmvs490.93 24589.85 25594.17 20693.34 32690.79 14794.60 28796.02 26284.62 31487.45 29095.15 23681.88 20097.45 30587.70 23287.87 27694.27 322
XVG-ACMP-BASELINE90.93 24590.21 24293.09 25994.31 29785.89 27895.33 26997.26 17991.06 16089.38 24795.44 22768.61 33098.60 18289.46 19791.05 24194.79 302
v192192090.85 24790.03 25093.29 25293.55 31786.96 25996.74 18397.04 19987.36 26989.52 24494.34 27380.23 22697.97 25186.27 25985.21 30394.94 286
CR-MVSNet90.82 24889.77 25993.95 22094.45 29187.19 25290.23 35895.68 27886.89 27892.40 16592.36 32880.91 21297.05 32181.09 31993.95 19697.60 178
v7n90.76 24989.86 25493.45 24793.54 31887.60 24597.70 9297.37 17088.85 22487.65 28894.08 28981.08 20998.10 22984.68 28483.79 32694.66 309
RPSCF90.75 25090.86 21190.42 32296.84 16376.29 36095.61 25996.34 24983.89 32291.38 19197.87 8376.45 27998.78 16187.16 24992.23 21696.20 219
MVP-Stereo90.74 25190.08 24592.71 27393.19 32988.20 22895.86 24896.27 25286.07 29284.86 32194.76 25377.84 26997.75 27983.88 29598.01 11392.17 351
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
pm-mvs190.72 25289.65 26593.96 21994.29 29889.63 17697.79 8096.82 22189.07 21486.12 31195.48 22678.61 25697.78 27686.97 25281.67 33794.46 313
v124090.70 25389.85 25593.23 25493.51 32086.80 26096.61 20097.02 20287.16 27489.58 24094.31 27779.55 23897.98 24885.52 27485.44 29894.90 291
EPMVS90.70 25389.81 25793.37 24994.73 28184.21 30393.67 32288.02 37089.50 20392.38 16793.49 30977.82 27097.78 27686.03 26792.68 21198.11 153
Anonymous2023121190.63 25589.42 26894.27 20498.24 8689.19 20298.05 5397.89 9979.95 35088.25 27794.96 24272.56 30898.13 22289.70 19185.14 30495.49 253
DTE-MVSNet90.56 25689.75 26193.01 26193.95 30587.25 24997.64 10097.65 12790.74 16687.12 29795.68 21579.97 23197.00 32583.33 29781.66 33894.78 304
ACMH87.59 1690.53 25789.42 26893.87 22696.21 20187.92 23797.24 14396.94 20788.45 23883.91 33396.27 18371.92 30998.62 18184.43 28789.43 26295.05 282
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
OurMVSNet-221017-090.51 25890.19 24391.44 30593.41 32481.25 33096.98 16596.28 25191.68 13886.55 30796.30 18174.20 29897.98 24888.96 21287.40 28295.09 279
miper_lstm_enhance90.50 25990.06 24991.83 29395.33 24583.74 30993.86 31596.70 22987.56 26587.79 28593.81 29883.45 16396.92 32787.39 24284.62 31394.82 297
COLMAP_ROBcopyleft87.81 1590.40 26089.28 27193.79 23097.95 10687.13 25596.92 16995.89 26882.83 33386.88 30597.18 12873.77 30299.29 11178.44 33493.62 20094.95 284
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
IterMVS-SCA-FT90.31 26189.81 25791.82 29495.52 23084.20 30494.30 30096.15 25990.61 17787.39 29394.27 27975.80 28696.44 33387.34 24386.88 28894.82 297
MS-PatchMatch90.27 26289.77 25991.78 29794.33 29584.72 29995.55 26096.73 22486.17 29186.36 30895.28 23271.28 31497.80 27484.09 29198.14 11192.81 340
tpm90.25 26389.74 26291.76 29993.92 30679.73 34893.98 30893.54 34288.28 24291.99 17893.25 31477.51 27297.44 30687.30 24587.94 27598.12 150
AllTest90.23 26488.98 27593.98 21697.94 10786.64 26496.51 20795.54 28485.38 30185.49 31596.77 14870.28 32099.15 12380.02 32492.87 20596.15 223
dmvs_re90.21 26589.50 26792.35 27995.47 23485.15 29195.70 25494.37 32990.94 16288.42 27093.57 30774.63 29495.67 34682.80 30389.57 26196.22 218
ACMH+87.92 1490.20 26689.18 27393.25 25396.48 19086.45 26996.99 16496.68 23088.83 22684.79 32296.22 18570.16 32298.53 18884.42 28888.04 27494.77 305
test-mter90.19 26789.54 26692.12 28694.59 28680.66 33594.29 30192.98 34687.68 26290.76 20692.37 32567.67 33498.07 23788.81 21496.74 14797.63 173
IterMVS90.15 26889.67 26391.61 30195.48 23283.72 31094.33 29996.12 26089.99 19087.31 29694.15 28775.78 28896.27 33686.97 25286.89 28794.83 295
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
TESTMET0.1,190.06 26989.42 26891.97 28994.41 29380.62 33794.29 30191.97 35687.28 27290.44 21192.47 32468.79 32997.67 28488.50 22096.60 15297.61 177
tpm289.96 27089.21 27292.23 28594.91 27081.25 33093.78 31794.42 32780.62 34891.56 18793.44 31176.44 28097.94 25985.60 27392.08 22397.49 182
IB-MVS87.33 1789.91 27188.28 28494.79 18095.26 25287.70 24395.12 28093.95 33889.35 20887.03 30092.49 32370.74 31899.19 11889.18 20881.37 33997.49 182
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
ADS-MVSNet89.89 27288.68 27993.53 24395.86 21684.89 29790.93 35395.07 30783.23 33191.28 20091.81 33579.01 25097.85 26979.52 32691.39 23497.84 164
FMVSNet189.88 27388.31 28394.59 18595.41 23591.18 13197.50 11596.93 20886.62 28287.41 29294.51 26365.94 34897.29 31583.04 30087.43 28095.31 269
pmmvs589.86 27488.87 27792.82 26992.86 33386.23 27496.26 22795.39 28984.24 31887.12 29794.51 26374.27 29797.36 31287.61 23987.57 27894.86 293
tpmvs89.83 27589.15 27491.89 29194.92 26880.30 34293.11 33495.46 28886.28 28888.08 28192.65 31980.44 22198.52 18981.47 31389.92 25796.84 204
test_fmvs289.77 27689.93 25289.31 33293.68 31576.37 35997.64 10095.90 26689.84 19591.49 18996.26 18458.77 36097.10 31994.65 9891.13 23994.46 313
tfpnnormal89.70 27788.40 28293.60 23995.15 25690.10 16297.56 10998.16 5387.28 27286.16 31094.63 26077.57 27198.05 24074.48 34984.59 31492.65 343
ADS-MVSNet289.45 27888.59 28092.03 28895.86 21682.26 32390.93 35394.32 33283.23 33191.28 20091.81 33579.01 25095.99 33879.52 32691.39 23497.84 164
Patchmatch-test89.42 27987.99 28693.70 23595.27 24985.11 29288.98 36494.37 32981.11 34287.10 29993.69 30182.28 19197.50 30174.37 35194.76 18498.48 128
test0.0.03 189.37 28088.70 27891.41 30692.47 34185.63 28195.22 27792.70 34991.11 15886.91 30493.65 30579.02 24893.19 36678.00 33689.18 26495.41 260
SixPastTwentyTwo89.15 28188.54 28190.98 31293.49 32180.28 34396.70 18894.70 32090.78 16484.15 32895.57 22071.78 31197.71 28284.63 28585.07 30694.94 286
RPMNet88.98 28287.05 29694.77 18194.45 29187.19 25290.23 35898.03 8377.87 36092.40 16587.55 36380.17 22799.51 8668.84 36693.95 19697.60 178
TransMVSNet (Re)88.94 28387.56 28993.08 26094.35 29488.45 22197.73 8595.23 30087.47 26684.26 32695.29 23079.86 23397.33 31379.44 33074.44 36093.45 333
USDC88.94 28387.83 28892.27 28394.66 28384.96 29593.86 31595.90 26687.34 27083.40 33595.56 22167.43 33698.19 21782.64 30789.67 26093.66 329
dp88.90 28588.26 28590.81 31594.58 28876.62 35892.85 33994.93 31385.12 30790.07 22793.07 31575.81 28598.12 22780.53 32187.42 28197.71 170
PatchT88.87 28687.42 29093.22 25594.08 30385.10 29389.51 36294.64 32381.92 33892.36 16888.15 35980.05 22997.01 32472.43 35793.65 19997.54 181
our_test_388.78 28787.98 28791.20 31092.45 34282.53 31993.61 32595.69 27685.77 29684.88 32093.71 30079.99 23096.78 33179.47 32886.24 28994.28 321
EU-MVSNet88.72 28888.90 27688.20 33693.15 33074.21 36396.63 19994.22 33385.18 30587.32 29595.97 19576.16 28394.98 35485.27 27786.17 29095.41 260
Patchmtry88.64 28987.25 29292.78 27194.09 30286.64 26489.82 36195.68 27880.81 34687.63 28992.36 32880.91 21297.03 32278.86 33285.12 30594.67 308
MIMVSNet88.50 29086.76 29893.72 23494.84 27487.77 24291.39 34894.05 33586.41 28687.99 28392.59 32263.27 35395.82 34377.44 33792.84 20797.57 180
tpm cat188.36 29187.21 29491.81 29595.13 25880.55 33892.58 34295.70 27474.97 36387.45 29091.96 33378.01 26898.17 21980.39 32288.74 26996.72 208
ppachtmachnet_test88.35 29287.29 29191.53 30292.45 34283.57 31393.75 31895.97 26384.28 31785.32 31894.18 28579.00 25296.93 32675.71 34684.99 30994.10 323
JIA-IIPM88.26 29387.04 29791.91 29093.52 31981.42 32989.38 36394.38 32880.84 34590.93 20580.74 37079.22 24397.92 26382.76 30491.62 22796.38 216
testgi87.97 29487.21 29490.24 32492.86 33380.76 33496.67 19394.97 31191.74 13685.52 31495.83 20362.66 35694.47 35876.25 34488.36 27395.48 254
LF4IMVS87.94 29587.25 29289.98 32692.38 34480.05 34694.38 29695.25 29987.59 26484.34 32494.74 25564.31 35197.66 28684.83 28187.45 27992.23 348
gg-mvs-nofinetune87.82 29685.61 30594.44 19394.46 29089.27 19891.21 35284.61 37880.88 34489.89 23274.98 37271.50 31297.53 29885.75 27297.21 13896.51 211
pmmvs687.81 29786.19 30192.69 27491.32 34986.30 27297.34 13496.41 24780.59 34984.05 33294.37 27267.37 33797.67 28484.75 28379.51 34794.09 325
K. test v387.64 29886.75 29990.32 32393.02 33279.48 35096.61 20092.08 35590.66 17380.25 35194.09 28867.21 33896.65 33285.96 26980.83 34194.83 295
Patchmatch-RL test87.38 29986.24 30090.81 31588.74 36578.40 35688.12 36893.17 34587.11 27582.17 34289.29 35381.95 19895.60 34888.64 21877.02 35398.41 136
FMVSNet587.29 30085.79 30491.78 29794.80 27687.28 24795.49 26395.28 29684.09 32083.85 33491.82 33462.95 35594.17 36078.48 33385.34 30193.91 327
Anonymous2023120687.09 30186.14 30289.93 32791.22 35080.35 34096.11 23695.35 29283.57 32884.16 32793.02 31673.54 30495.61 34772.16 35886.14 29193.84 328
EG-PatchMatch MVS87.02 30285.44 30691.76 29992.67 33785.00 29496.08 23896.45 24583.41 33079.52 35393.49 30957.10 36397.72 28179.34 33190.87 24792.56 344
TinyColmap86.82 30385.35 30991.21 30994.91 27082.99 31693.94 31194.02 33783.58 32781.56 34394.68 25762.34 35798.13 22275.78 34587.35 28392.52 345
TDRefinement86.53 30484.76 31591.85 29282.23 37584.25 30296.38 21895.35 29284.97 31084.09 33094.94 24365.76 34998.34 20784.60 28674.52 35992.97 337
test_040286.46 30584.79 31491.45 30495.02 26285.55 28296.29 22694.89 31580.90 34382.21 34193.97 29368.21 33397.29 31562.98 37088.68 27091.51 355
Anonymous2024052186.42 30685.44 30689.34 33190.33 35479.79 34796.73 18495.92 26483.71 32683.25 33691.36 33963.92 35296.01 33778.39 33585.36 30092.22 349
DSMNet-mixed86.34 30786.12 30387.00 34289.88 35870.43 36794.93 28190.08 36677.97 35985.42 31792.78 31874.44 29693.96 36174.43 35095.14 17696.62 209
CL-MVSNet_self_test86.31 30885.15 31089.80 32888.83 36481.74 32893.93 31296.22 25586.67 28185.03 31990.80 34278.09 26594.50 35674.92 34871.86 36593.15 336
pmmvs-eth3d86.22 30984.45 31691.53 30288.34 36687.25 24994.47 29195.01 30883.47 32979.51 35489.61 35169.75 32695.71 34483.13 29976.73 35691.64 352
test_vis1_rt86.16 31085.06 31189.46 33093.47 32380.46 33996.41 21286.61 37585.22 30479.15 35588.64 35452.41 36797.06 32093.08 12990.57 24990.87 360
test20.0386.14 31185.40 30888.35 33490.12 35580.06 34595.90 24795.20 30188.59 23381.29 34493.62 30671.43 31392.65 36771.26 36281.17 34092.34 347
UnsupCasMVSNet_eth85.99 31284.45 31690.62 31989.97 35782.40 32293.62 32497.37 17089.86 19278.59 35792.37 32565.25 35095.35 35382.27 30970.75 36694.10 323
KD-MVS_self_test85.95 31384.95 31288.96 33389.55 36179.11 35395.13 27996.42 24685.91 29484.07 33190.48 34370.03 32494.82 35580.04 32372.94 36392.94 338
YYNet185.87 31484.23 31890.78 31892.38 34482.46 32193.17 33195.14 30482.12 33767.69 36692.36 32878.16 26495.50 35177.31 33979.73 34594.39 316
MDA-MVSNet_test_wron85.87 31484.23 31890.80 31792.38 34482.57 31893.17 33195.15 30382.15 33667.65 36792.33 33178.20 26195.51 35077.33 33879.74 34494.31 320
CMPMVSbinary62.92 2185.62 31684.92 31387.74 33889.14 36273.12 36694.17 30496.80 22273.98 36473.65 36594.93 24466.36 34397.61 29183.95 29491.28 23692.48 346
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
PVSNet_082.17 1985.46 31783.64 32090.92 31395.27 24979.49 34990.55 35695.60 28183.76 32583.00 33989.95 34871.09 31597.97 25182.75 30560.79 37695.31 269
MDA-MVSNet-bldmvs85.00 31882.95 32391.17 31193.13 33183.33 31494.56 28995.00 30984.57 31565.13 37192.65 31970.45 31995.85 34173.57 35477.49 35294.33 318
MIMVSNet184.93 31983.05 32190.56 32089.56 36084.84 29895.40 26695.35 29283.91 32180.38 34992.21 33257.23 36293.34 36570.69 36482.75 33593.50 331
KD-MVS_2432*160084.81 32082.64 32491.31 30791.07 35185.34 28991.22 35095.75 27285.56 29983.09 33790.21 34667.21 33895.89 33977.18 34162.48 37492.69 341
miper_refine_blended84.81 32082.64 32491.31 30791.07 35185.34 28991.22 35095.75 27285.56 29983.09 33790.21 34667.21 33895.89 33977.18 34162.48 37492.69 341
OpenMVS_ROBcopyleft81.14 2084.42 32282.28 32890.83 31490.06 35684.05 30795.73 25394.04 33673.89 36580.17 35291.53 33859.15 35997.64 28766.92 36889.05 26590.80 361
mvsany_test383.59 32382.44 32787.03 34183.80 37173.82 36493.70 31990.92 36486.42 28582.51 34090.26 34546.76 37095.71 34490.82 17276.76 35591.57 354
PM-MVS83.48 32481.86 33088.31 33587.83 36877.59 35793.43 32791.75 35786.91 27780.63 34789.91 34944.42 37195.84 34285.17 28076.73 35691.50 356
test_fmvs383.21 32583.02 32283.78 34786.77 37068.34 37296.76 18294.91 31486.49 28484.14 32989.48 35236.04 37591.73 36991.86 15280.77 34291.26 359
new-patchmatchnet83.18 32681.87 32987.11 34086.88 36975.99 36193.70 31995.18 30285.02 30977.30 36088.40 35665.99 34793.88 36274.19 35370.18 36791.47 357
new_pmnet82.89 32781.12 33288.18 33789.63 35980.18 34491.77 34792.57 35076.79 36275.56 36388.23 35861.22 35894.48 35771.43 36082.92 33389.87 364
MVS-HIRNet82.47 32881.21 33186.26 34495.38 23769.21 37088.96 36589.49 36766.28 36980.79 34674.08 37468.48 33197.39 31071.93 35995.47 17192.18 350
UnsupCasMVSNet_bld82.13 32979.46 33490.14 32588.00 36782.47 32090.89 35596.62 23878.94 35575.61 36184.40 36856.63 36496.31 33577.30 34066.77 37291.63 353
dmvs_testset81.38 33082.60 32677.73 35391.74 34851.49 38393.03 33684.21 37989.07 21478.28 35891.25 34076.97 27588.53 37456.57 37582.24 33693.16 335
test_f80.57 33179.62 33383.41 34883.38 37367.80 37493.57 32693.72 33980.80 34777.91 35987.63 36233.40 37692.08 36887.14 25079.04 35090.34 363
pmmvs379.97 33277.50 33787.39 33982.80 37479.38 35192.70 34190.75 36570.69 36778.66 35687.47 36451.34 36893.40 36473.39 35569.65 36889.38 365
APD_test179.31 33377.70 33684.14 34689.11 36369.07 37192.36 34691.50 35969.07 36873.87 36492.63 32139.93 37394.32 35970.54 36580.25 34389.02 366
N_pmnet78.73 33478.71 33578.79 35292.80 33546.50 38694.14 30543.71 38978.61 35680.83 34591.66 33774.94 29396.36 33467.24 36784.45 31793.50 331
test_vis3_rt72.73 33570.55 33879.27 35180.02 37668.13 37393.92 31374.30 38676.90 36158.99 37573.58 37520.29 38495.37 35284.16 28972.80 36474.31 374
LCM-MVSNet72.55 33669.39 34082.03 34970.81 38565.42 37790.12 36094.36 33155.02 37565.88 36981.72 36924.16 38389.96 37074.32 35268.10 37190.71 362
FPMVS71.27 33769.85 33975.50 35774.64 38059.03 38191.30 34991.50 35958.80 37257.92 37688.28 35729.98 37985.53 37753.43 37682.84 33481.95 370
PMMVS270.19 33866.92 34180.01 35076.35 37965.67 37686.22 36987.58 37264.83 37162.38 37280.29 37126.78 38188.49 37563.79 36954.07 37785.88 367
testf169.31 33966.76 34276.94 35578.61 37761.93 37988.27 36686.11 37655.62 37359.69 37385.31 36620.19 38589.32 37157.62 37269.44 36979.58 371
APD_test269.31 33966.76 34276.94 35578.61 37761.93 37988.27 36686.11 37655.62 37359.69 37385.31 36620.19 38589.32 37157.62 37269.44 36979.58 371
EGC-MVSNET68.77 34163.01 34686.07 34592.49 34082.24 32493.96 31090.96 3630.71 3862.62 38790.89 34153.66 36593.46 36357.25 37484.55 31582.51 369
Gipumacopyleft67.86 34265.41 34475.18 35892.66 33873.45 36566.50 37794.52 32553.33 37657.80 37766.07 37730.81 37789.20 37348.15 37878.88 35162.90 377
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
test_method66.11 34364.89 34569.79 36072.62 38335.23 39065.19 37892.83 34820.35 38165.20 37088.08 36043.14 37282.70 37873.12 35663.46 37391.45 358
ANet_high63.94 34459.58 34777.02 35461.24 38766.06 37585.66 37187.93 37178.53 35742.94 37971.04 37625.42 38280.71 37952.60 37730.83 38084.28 368
PMVScopyleft53.92 2258.58 34555.40 34868.12 36151.00 38848.64 38478.86 37487.10 37446.77 37735.84 38374.28 3738.76 38786.34 37642.07 37973.91 36169.38 375
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
E-PMN53.28 34652.56 35055.43 36374.43 38147.13 38583.63 37376.30 38342.23 37842.59 38062.22 37928.57 38074.40 38131.53 38131.51 37944.78 378
MVEpermissive50.73 2353.25 34748.81 35266.58 36265.34 38657.50 38272.49 37670.94 38740.15 38039.28 38263.51 3786.89 38973.48 38338.29 38042.38 37868.76 376
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
EMVS52.08 34851.31 35154.39 36472.62 38345.39 38783.84 37275.51 38541.13 37940.77 38159.65 38030.08 37873.60 38228.31 38229.90 38144.18 379
tmp_tt51.94 34953.82 34946.29 36533.73 38945.30 38878.32 37567.24 38818.02 38250.93 37887.05 36552.99 36653.11 38470.76 36325.29 38240.46 380
wuyk23d25.11 35024.57 35426.74 36673.98 38239.89 38957.88 3799.80 39012.27 38310.39 3846.97 3867.03 38836.44 38525.43 38317.39 3833.89 383
cdsmvs_eth3d_5k23.24 35130.99 3530.00 3690.00 3920.00 3930.00 38097.63 1310.00 3870.00 38896.88 14584.38 1480.00 3880.00 3860.00 3860.00 384
testmvs13.36 35216.33 3554.48 3685.04 3902.26 39293.18 3303.28 3912.70 3848.24 38521.66 3822.29 3912.19 3867.58 3842.96 3849.00 382
test12313.04 35315.66 3565.18 3674.51 3913.45 39192.50 3441.81 3922.50 3857.58 38620.15 3833.67 3902.18 3877.13 3851.07 3859.90 381
ab-mvs-re8.06 35410.74 3570.00 3690.00 3920.00 3930.00 3800.00 3930.00 3870.00 38896.69 1540.00 3920.00 3880.00 3860.00 3860.00 384
pcd_1.5k_mvsjas7.39 3559.85 3580.00 3690.00 3920.00 3930.00 3800.00 3930.00 3870.00 3880.00 38788.65 900.00 3880.00 3860.00 3860.00 384
test_blank0.00 3560.00 3590.00 3690.00 3920.00 3930.00 3800.00 3930.00 3870.00 3880.00 3870.00 3920.00 3880.00 3860.00 3860.00 384
uanet_test0.00 3560.00 3590.00 3690.00 3920.00 3930.00 3800.00 3930.00 3870.00 3880.00 3870.00 3920.00 3880.00 3860.00 3860.00 384
DCPMVS0.00 3560.00 3590.00 3690.00 3920.00 3930.00 3800.00 3930.00 3870.00 3880.00 3870.00 3920.00 3880.00 3860.00 3860.00 384
sosnet-low-res0.00 3560.00 3590.00 3690.00 3920.00 3930.00 3800.00 3930.00 3870.00 3880.00 3870.00 3920.00 3880.00 3860.00 3860.00 384
sosnet0.00 3560.00 3590.00 3690.00 3920.00 3930.00 3800.00 3930.00 3870.00 3880.00 3870.00 3920.00 3880.00 3860.00 3860.00 384
uncertanet0.00 3560.00 3590.00 3690.00 3920.00 3930.00 3800.00 3930.00 3870.00 3880.00 3870.00 3920.00 3880.00 3860.00 3860.00 384
Regformer0.00 3560.00 3590.00 3690.00 3920.00 3930.00 3800.00 3930.00 3870.00 3880.00 3870.00 3920.00 3880.00 3860.00 3860.00 384
uanet0.00 3560.00 3590.00 3690.00 3920.00 3930.00 3800.00 3930.00 3870.00 3880.00 3870.00 3920.00 3880.00 3860.00 3860.00 384
FOURS199.55 193.34 6399.29 198.35 2194.98 2498.49 16
MSC_two_6792asdad98.86 198.67 5896.94 197.93 9799.86 897.68 699.67 699.77 1
PC_three_145290.77 16598.89 998.28 5596.24 198.35 20495.76 6399.58 2199.59 20
No_MVS98.86 198.67 5896.94 197.93 9799.86 897.68 699.67 699.77 1
test_one_060199.32 2295.20 2098.25 3795.13 1998.48 1798.87 895.16 7
eth-test20.00 392
eth-test0.00 392
ZD-MVS99.05 3994.59 2898.08 6689.22 21197.03 4798.10 6392.52 3399.65 5294.58 10199.31 57
RE-MVS-def96.72 3599.02 4292.34 8597.98 5998.03 8393.52 7597.43 3598.51 2690.71 6796.05 5199.26 6199.43 46
IU-MVS99.42 795.39 1197.94 9690.40 18498.94 697.41 1999.66 1099.74 7
OPU-MVS98.55 398.82 5296.86 398.25 3698.26 5696.04 299.24 11495.36 7999.59 1799.56 26
test_241102_TWO98.27 3295.13 1998.93 798.89 694.99 1199.85 1797.52 1299.65 1299.74 7
test_241102_ONE99.42 795.30 1798.27 3295.09 2299.19 298.81 1295.54 599.65 52
9.1496.75 3398.93 4797.73 8598.23 4291.28 15197.88 2798.44 3493.00 2499.65 5295.76 6399.47 38
save fliter98.91 4994.28 3597.02 16098.02 8695.35 12
test_0728_THIRD94.78 3498.73 1198.87 895.87 499.84 2297.45 1699.72 299.77 1
test_0728_SECOND98.51 499.45 395.93 598.21 4398.28 2999.86 897.52 1299.67 699.75 5
test072699.45 395.36 1398.31 2998.29 2794.92 2598.99 598.92 395.08 8
GSMVS98.45 131
test_part299.28 2595.74 898.10 21
sam_mvs182.76 18098.45 131
sam_mvs81.94 199
ambc86.56 34383.60 37270.00 36985.69 37094.97 31180.60 34888.45 35537.42 37496.84 32982.69 30675.44 35892.86 339
MTGPAbinary98.08 66
test_post192.81 34016.58 38580.53 21997.68 28386.20 261
test_post17.58 38481.76 20198.08 233
patchmatchnet-post90.45 34482.65 18498.10 229
GG-mvs-BLEND93.62 23893.69 31489.20 20092.39 34583.33 38087.98 28489.84 35071.00 31696.87 32882.08 31095.40 17394.80 300
MTMP97.86 7182.03 381
gm-plane-assit93.22 32878.89 35584.82 31293.52 30898.64 17887.72 229
test9_res94.81 9399.38 5199.45 42
TEST998.70 5694.19 3996.41 21298.02 8688.17 24596.03 8597.56 11192.74 2899.59 64
test_898.67 5894.06 4696.37 21998.01 8988.58 23495.98 8997.55 11392.73 2999.58 67
agg_prior293.94 11199.38 5199.50 37
agg_prior98.67 5893.79 5198.00 9095.68 9999.57 74
TestCases93.98 21697.94 10786.64 26495.54 28485.38 30185.49 31596.77 14870.28 32099.15 12380.02 32492.87 20596.15 223
test_prior493.66 5496.42 211
test_prior296.35 22092.80 10996.03 8597.59 10892.01 4195.01 8799.38 51
test_prior97.23 5498.67 5892.99 7098.00 9099.41 9999.29 57
旧先验295.94 24581.66 34097.34 3898.82 15892.26 139
新几何295.79 251
新几何197.32 4998.60 6593.59 5597.75 11481.58 34195.75 9697.85 8690.04 7499.67 5086.50 25799.13 7398.69 113
旧先验198.38 7893.38 6097.75 11498.09 6592.30 3999.01 8099.16 67
无先验95.79 25197.87 10383.87 32499.65 5287.68 23598.89 99
原ACMM295.67 255
原ACMM196.38 9098.59 6691.09 13697.89 9987.41 26895.22 11097.68 9790.25 7199.54 7987.95 22599.12 7498.49 126
test22298.24 8692.21 9095.33 26997.60 13379.22 35495.25 10897.84 8888.80 8899.15 7198.72 110
testdata299.67 5085.96 269
segment_acmp92.89 25
testdata95.46 14598.18 9588.90 20897.66 12582.73 33497.03 4798.07 6690.06 7398.85 15689.67 19298.98 8198.64 116
testdata195.26 27693.10 95
test1297.65 4098.46 7094.26 3697.66 12595.52 10690.89 6499.46 9399.25 6399.22 64
plane_prior796.21 20189.98 168
plane_prior696.10 21190.00 16481.32 207
plane_prior597.51 14498.60 18293.02 13292.23 21695.86 231
plane_prior496.64 158
plane_prior390.00 16494.46 4591.34 193
plane_prior297.74 8394.85 27
plane_prior196.14 209
plane_prior89.99 16697.24 14394.06 5592.16 220
n20.00 393
nn0.00 393
door-mid91.06 362
lessismore_v090.45 32191.96 34779.09 35487.19 37380.32 35094.39 27066.31 34597.55 29584.00 29376.84 35494.70 307
LGP-MVS_train94.10 20996.16 20688.26 22597.46 15291.29 14890.12 22297.16 12979.05 24698.73 16892.25 14191.89 22495.31 269
test1197.88 101
door91.13 361
HQP5-MVS89.33 193
HQP-NCC95.86 21696.65 19493.55 7090.14 216
ACMP_Plane95.86 21696.65 19493.55 7090.14 216
BP-MVS92.13 145
HQP4-MVS90.14 21698.50 19095.78 240
HQP3-MVS97.39 16792.10 221
HQP2-MVS80.95 210
NP-MVS95.99 21589.81 17395.87 200
MDTV_nov1_ep13_2view70.35 36893.10 33583.88 32393.55 14282.47 18886.25 26098.38 139
MDTV_nov1_ep1390.76 21795.22 25380.33 34193.03 33695.28 29688.14 24792.84 16293.83 29581.34 20698.08 23382.86 30194.34 190
ACMMP++_ref90.30 254
ACMMP++91.02 242
Test By Simon88.73 89
ITE_SJBPF92.43 27895.34 24285.37 28895.92 26491.47 14287.75 28796.39 17871.00 31697.96 25682.36 30889.86 25893.97 326
DeepMVS_CXcopyleft74.68 35990.84 35364.34 37881.61 38265.34 37067.47 36888.01 36148.60 36980.13 38062.33 37173.68 36279.58 371