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++95.98 196.36 194.82 2897.78 5186.00 4798.29 197.49 590.75 1797.62 598.06 692.59 299.61 395.64 699.02 1298.86 10
SED-MVS95.91 296.28 294.80 3098.77 585.99 4997.13 1497.44 1490.31 2697.71 198.07 492.31 499.58 895.66 499.13 398.84 13
DVP-MVScopyleft95.67 396.02 394.64 3698.78 385.93 5297.09 1696.73 7690.27 2997.04 1098.05 891.47 899.55 1495.62 899.08 798.45 34
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-MVScopyleft95.57 495.67 495.25 998.36 2587.28 1595.56 8297.51 489.13 5897.14 897.91 1191.64 799.62 194.61 1499.17 298.86 10
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
APDe-MVS95.46 595.64 594.91 1998.26 2886.29 4397.46 697.40 1989.03 6196.20 1698.10 289.39 1699.34 3295.88 399.03 1199.10 4
MSP-MVS95.42 695.56 694.98 1798.49 1786.52 3396.91 2597.47 1091.73 896.10 1796.69 5389.90 1299.30 3894.70 1298.04 6399.13 2
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
CNVR-MVS95.40 795.37 795.50 798.11 3688.51 795.29 9296.96 5092.09 495.32 2297.08 3689.49 1599.33 3595.10 1198.85 1998.66 19
SMA-MVScopyleft95.20 895.07 1095.59 598.14 3588.48 896.26 4597.28 2985.90 13897.67 398.10 288.41 2099.56 1094.66 1399.19 198.71 18
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
SteuartSystems-ACMMP95.20 895.32 994.85 2396.99 7286.33 3997.33 797.30 2791.38 1095.39 2197.46 1788.98 1999.40 2894.12 1898.89 1898.82 15
Skip Steuart: Steuart Systems R&D Blog.
HPM-MVS++copyleft95.14 1094.91 1295.83 498.25 2989.65 495.92 6396.96 5091.75 794.02 3596.83 4888.12 2499.55 1493.41 2998.94 1698.28 48
SF-MVS94.97 1194.90 1395.20 1097.84 4787.76 996.65 3497.48 987.76 10195.71 1997.70 1388.28 2399.35 3193.89 2298.78 2598.48 28
SD-MVS94.96 1295.33 893.88 5497.25 6986.69 2596.19 4897.11 4190.42 2596.95 1297.27 2589.53 1496.91 23494.38 1698.85 1998.03 68
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
TSAR-MVS + MP.94.85 1394.94 1194.58 3998.25 2986.33 3996.11 5396.62 8588.14 8996.10 1796.96 4289.09 1898.94 7394.48 1598.68 3598.48 28
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
NCCC94.81 1494.69 1595.17 1297.83 4887.46 1495.66 7696.93 5492.34 293.94 3696.58 6387.74 2799.44 2792.83 3798.40 5098.62 20
ACMMP_NAP94.74 1594.56 1695.28 898.02 4187.70 1095.68 7497.34 2188.28 8295.30 2397.67 1485.90 4399.54 1893.91 2198.95 1598.60 21
HFP-MVS94.52 1694.40 1994.86 2298.61 1086.81 2296.94 2097.34 2188.63 7193.65 4097.21 2986.10 4199.49 2492.35 4898.77 2798.30 45
ZNCC-MVS94.47 1794.28 2395.03 1498.52 1586.96 1796.85 2897.32 2588.24 8393.15 5097.04 3986.17 4099.62 192.40 4698.81 2298.52 24
XVS94.45 1894.32 2094.85 2398.54 1386.60 3196.93 2297.19 3390.66 2292.85 5797.16 3485.02 5499.49 2491.99 6198.56 4698.47 31
MCST-MVS94.45 1894.20 2895.19 1198.46 1987.50 1395.00 11297.12 3987.13 11192.51 7096.30 7089.24 1799.34 3293.46 2698.62 4298.73 16
region2R94.43 2094.27 2594.92 1898.65 886.67 2796.92 2497.23 3288.60 7393.58 4297.27 2585.22 5099.54 1892.21 5198.74 2998.56 23
ACMMPR94.43 2094.28 2394.91 1998.63 986.69 2596.94 2097.32 2588.63 7193.53 4597.26 2785.04 5399.54 1892.35 4898.78 2598.50 25
MTAPA94.42 2294.22 2695.00 1698.42 2186.95 1894.36 15796.97 4891.07 1193.14 5197.56 1584.30 6299.56 1093.43 2798.75 2898.47 31
CP-MVS94.34 2394.21 2794.74 3498.39 2386.64 2997.60 497.24 3088.53 7592.73 6497.23 2885.20 5199.32 3692.15 5498.83 2198.25 53
MP-MVScopyleft94.25 2494.07 3294.77 3298.47 1886.31 4196.71 3196.98 4789.04 6091.98 7997.19 3185.43 4899.56 1092.06 6098.79 2398.44 35
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
APD-MVScopyleft94.24 2594.07 3294.75 3398.06 3986.90 2095.88 6496.94 5385.68 14495.05 2597.18 3287.31 3399.07 5191.90 6798.61 4498.28 48
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
SR-MVS94.23 2694.17 3094.43 4498.21 3285.78 5996.40 3996.90 5788.20 8794.33 2997.40 2084.75 5999.03 5693.35 3097.99 6498.48 28
GST-MVS94.21 2793.97 3594.90 2198.41 2286.82 2196.54 3697.19 3388.24 8393.26 4796.83 4885.48 4799.59 791.43 7398.40 5098.30 45
MP-MVS-pluss94.21 2794.00 3494.85 2398.17 3386.65 2894.82 12397.17 3786.26 13092.83 5997.87 1285.57 4699.56 1094.37 1798.92 1798.34 40
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
DeepPCF-MVS89.96 194.20 2994.77 1492.49 10196.52 8780.00 20494.00 18197.08 4290.05 3395.65 2097.29 2489.66 1398.97 7093.95 2098.71 3098.50 25
CS-MVS94.12 3094.44 1893.17 6896.55 8483.08 11597.63 396.95 5291.71 993.50 4696.21 7385.61 4498.24 12393.64 2498.17 5698.19 56
DeepC-MVS_fast89.43 294.04 3193.79 3894.80 3097.48 6186.78 2395.65 7896.89 5889.40 5092.81 6096.97 4185.37 4999.24 4190.87 8398.69 3398.38 39
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
CS-MVS-test94.02 3294.29 2293.24 6596.69 7883.24 10897.49 596.92 5592.14 392.90 5595.77 9485.02 5498.33 11893.03 3498.62 4298.13 60
HPM-MVScopyleft94.02 3293.88 3694.43 4498.39 2385.78 5997.25 1097.07 4386.90 11992.62 6796.80 5284.85 5899.17 4592.43 4498.65 4098.33 41
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
mPP-MVS93.99 3493.78 3994.63 3798.50 1685.90 5696.87 2696.91 5688.70 6991.83 8897.17 3383.96 6699.55 1491.44 7298.64 4198.43 36
PGM-MVS93.96 3593.72 4194.68 3598.43 2086.22 4495.30 9097.78 187.45 10793.26 4797.33 2384.62 6099.51 2290.75 8598.57 4598.32 44
PHI-MVS93.89 3693.65 4494.62 3896.84 7586.43 3696.69 3297.49 585.15 15893.56 4496.28 7185.60 4599.31 3792.45 4398.79 2398.12 62
SR-MVS-dyc-post93.82 3793.82 3793.82 5697.92 4384.57 7396.28 4396.76 7287.46 10593.75 3897.43 1884.24 6399.01 6192.73 3897.80 7097.88 75
APD-MVS_3200maxsize93.78 3893.77 4093.80 5897.92 4384.19 8596.30 4196.87 6086.96 11593.92 3797.47 1683.88 6798.96 7292.71 4197.87 6898.26 52
patch_mono-293.74 3994.32 2092.01 11797.54 5778.37 24293.40 20497.19 3388.02 9194.99 2697.21 2988.35 2198.44 10994.07 1998.09 6199.23 1
MSLP-MVS++93.72 4094.08 3192.65 9397.31 6583.43 10395.79 6897.33 2390.03 3493.58 4296.96 4284.87 5797.76 16192.19 5398.66 3896.76 119
TSAR-MVS + GP.93.66 4193.41 4594.41 4696.59 8286.78 2394.40 15093.93 23589.77 4294.21 3095.59 10187.35 3298.61 9592.72 4096.15 9897.83 79
CANet93.54 4293.20 4994.55 4095.65 11785.73 6194.94 11596.69 8191.89 690.69 10495.88 8881.99 9099.54 1893.14 3397.95 6698.39 37
dcpmvs_293.49 4394.19 2991.38 15197.69 5476.78 27494.25 16096.29 10188.33 7994.46 2796.88 4588.07 2598.64 9193.62 2598.09 6198.73 16
MVS_111021_HR93.45 4493.31 4693.84 5596.99 7284.84 6893.24 21697.24 3088.76 6891.60 9395.85 8986.07 4298.66 8991.91 6598.16 5798.03 68
train_agg93.44 4593.08 5094.52 4197.53 5886.49 3494.07 17396.78 6981.86 22892.77 6196.20 7487.63 2999.12 4992.14 5598.69 3397.94 71
DROMVSNet93.44 4593.71 4292.63 9495.21 13182.43 13697.27 996.71 7990.57 2492.88 5695.80 9283.16 7198.16 12993.68 2398.14 5897.31 96
DELS-MVS93.43 4793.25 4793.97 5195.42 12485.04 6793.06 22397.13 3890.74 1991.84 8695.09 11786.32 3999.21 4391.22 7498.45 4897.65 84
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
HPM-MVS_fast93.40 4893.22 4893.94 5398.36 2584.83 6997.15 1396.80 6885.77 14192.47 7197.13 3582.38 7999.07 5190.51 9098.40 5097.92 74
DeepC-MVS88.79 393.31 4992.99 5294.26 4996.07 10285.83 5794.89 11896.99 4689.02 6389.56 11897.37 2282.51 7899.38 2992.20 5298.30 5397.57 89
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
canonicalmvs93.27 5092.75 5694.85 2395.70 11687.66 1196.33 4096.41 9590.00 3594.09 3394.60 13882.33 8198.62 9492.40 4692.86 15998.27 50
ACMMPcopyleft93.24 5192.88 5494.30 4898.09 3885.33 6596.86 2797.45 1388.33 7990.15 11397.03 4081.44 9399.51 2290.85 8495.74 10198.04 67
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
CSCG93.23 5293.05 5193.76 5998.04 4084.07 8796.22 4797.37 2084.15 17490.05 11495.66 9887.77 2699.15 4889.91 9398.27 5498.07 64
alignmvs93.08 5392.50 6094.81 2995.62 11987.61 1295.99 5996.07 11989.77 4294.12 3294.87 12380.56 9998.66 8992.42 4593.10 15598.15 59
EI-MVSNet-Vis-set93.01 5492.92 5393.29 6395.01 13883.51 10294.48 14295.77 14190.87 1392.52 6996.67 5584.50 6199.00 6591.99 6194.44 13097.36 95
casdiffmvs_mvgpermissive92.96 5592.83 5593.35 6294.59 16183.40 10595.00 11296.34 9990.30 2892.05 7796.05 8283.43 6998.15 13092.07 5795.67 10298.49 27
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
UA-Net92.83 5692.54 5993.68 6096.10 10084.71 7195.66 7696.39 9691.92 593.22 4996.49 6683.16 7198.87 7784.47 15995.47 10797.45 94
CDPH-MVS92.83 5692.30 6294.44 4297.79 4986.11 4694.06 17596.66 8280.09 25592.77 6196.63 6086.62 3699.04 5587.40 12198.66 3898.17 58
ETV-MVS92.74 5892.66 5792.97 7895.20 13284.04 8995.07 10896.51 9190.73 2092.96 5491.19 25784.06 6498.34 11691.72 6996.54 9296.54 128
EI-MVSNet-UG-set92.74 5892.62 5893.12 7094.86 14983.20 11094.40 15095.74 14490.71 2192.05 7796.60 6284.00 6598.99 6791.55 7093.63 14097.17 103
DPM-MVS92.58 6091.74 6895.08 1396.19 9589.31 592.66 23396.56 9083.44 19291.68 9295.04 11886.60 3898.99 6785.60 14597.92 6796.93 115
casdiffmvspermissive92.51 6192.43 6192.74 8894.41 17381.98 14694.54 14096.23 10889.57 4691.96 8196.17 7882.58 7798.01 14890.95 8195.45 10998.23 54
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
MVS_111021_LR92.47 6292.29 6392.98 7795.99 10684.43 8293.08 22196.09 11788.20 8791.12 10095.72 9781.33 9597.76 16191.74 6897.37 7796.75 120
3Dnovator+87.14 492.42 6391.37 7195.55 695.63 11888.73 697.07 1896.77 7190.84 1484.02 24296.62 6175.95 15099.34 3287.77 11597.68 7398.59 22
baseline92.39 6492.29 6392.69 9294.46 17081.77 15194.14 16696.27 10389.22 5491.88 8496.00 8382.35 8097.99 15091.05 7695.27 11498.30 45
VNet92.24 6591.91 6693.24 6596.59 8283.43 10394.84 12296.44 9389.19 5694.08 3495.90 8777.85 13498.17 12888.90 10393.38 14998.13 60
CPTT-MVS91.99 6691.80 6792.55 9898.24 3181.98 14696.76 3096.49 9281.89 22790.24 10996.44 6878.59 12398.61 9589.68 9497.85 6997.06 107
EIA-MVS91.95 6791.94 6591.98 12195.16 13380.01 20395.36 8596.73 7688.44 7689.34 12292.16 22383.82 6898.45 10889.35 9797.06 8097.48 92
DP-MVS Recon91.95 6791.28 7393.96 5298.33 2785.92 5494.66 13496.66 8282.69 20990.03 11595.82 9182.30 8299.03 5684.57 15796.48 9596.91 116
EPNet91.79 6991.02 7994.10 5090.10 31185.25 6696.03 5892.05 28292.83 187.39 15795.78 9379.39 11499.01 6188.13 11197.48 7598.05 66
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
MG-MVS91.77 7091.70 6992.00 12097.08 7180.03 20293.60 19895.18 18287.85 9990.89 10296.47 6782.06 8898.36 11385.07 14997.04 8197.62 85
Vis-MVSNetpermissive91.75 7191.23 7493.29 6395.32 12683.78 9496.14 5195.98 12589.89 3690.45 10696.58 6375.09 16298.31 12184.75 15596.90 8497.78 82
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
3Dnovator86.66 591.73 7290.82 8394.44 4294.59 16186.37 3897.18 1297.02 4589.20 5584.31 23896.66 5673.74 18699.17 4586.74 13197.96 6597.79 81
EPP-MVSNet91.70 7391.56 7092.13 11695.88 10980.50 18797.33 795.25 17886.15 13489.76 11795.60 10083.42 7098.32 12087.37 12393.25 15297.56 90
MVSFormer91.68 7491.30 7292.80 8493.86 19483.88 9295.96 6195.90 13284.66 16991.76 8994.91 12177.92 13197.30 20589.64 9597.11 7897.24 99
Effi-MVS+91.59 7591.11 7693.01 7694.35 17783.39 10694.60 13695.10 18687.10 11290.57 10593.10 19581.43 9498.07 14489.29 9994.48 12897.59 88
IS-MVSNet91.43 7691.09 7892.46 10295.87 11181.38 16396.95 1993.69 24689.72 4489.50 12095.98 8478.57 12497.77 16083.02 17796.50 9498.22 55
PVSNet_Blended_VisFu91.38 7790.91 8192.80 8496.39 9083.17 11194.87 12096.66 8283.29 19689.27 12394.46 14280.29 10199.17 4587.57 11995.37 11096.05 146
diffmvspermissive91.37 7891.23 7491.77 13693.09 21680.27 19092.36 24295.52 16187.03 11491.40 9794.93 12080.08 10397.44 18992.13 5694.56 12597.61 86
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
MVS_Test91.31 7991.11 7691.93 12594.37 17480.14 19593.46 20395.80 13986.46 12691.35 9893.77 17482.21 8498.09 14187.57 11994.95 11797.55 91
OMC-MVS91.23 8090.62 8593.08 7296.27 9384.07 8793.52 20095.93 12886.95 11689.51 11996.13 8078.50 12598.35 11585.84 14392.90 15896.83 118
PAPM_NR91.22 8190.78 8492.52 10097.60 5681.46 16094.37 15696.24 10786.39 12887.41 15494.80 12982.06 8898.48 10282.80 18395.37 11097.61 86
PS-MVSNAJ91.18 8290.92 8091.96 12395.26 12982.60 13592.09 25395.70 14686.27 12991.84 8692.46 21379.70 10998.99 6789.08 10195.86 10094.29 217
xiu_mvs_v2_base91.13 8390.89 8291.86 13094.97 14182.42 13792.24 24795.64 15386.11 13791.74 9193.14 19379.67 11298.89 7689.06 10295.46 10894.28 218
nrg03091.08 8490.39 8693.17 6893.07 21786.91 1996.41 3796.26 10488.30 8188.37 13794.85 12682.19 8597.64 17291.09 7582.95 27094.96 181
lupinMVS90.92 8590.21 8993.03 7593.86 19483.88 9292.81 23093.86 23979.84 25891.76 8994.29 14877.92 13198.04 14690.48 9197.11 7897.17 103
h-mvs3390.80 8690.15 9292.75 8796.01 10482.66 13295.43 8495.53 16089.80 3893.08 5295.64 9975.77 15199.00 6592.07 5778.05 32596.60 124
jason90.80 8690.10 9392.90 8193.04 21983.53 10193.08 22194.15 22880.22 25291.41 9694.91 12176.87 13897.93 15590.28 9296.90 8497.24 99
jason: jason.
VDD-MVS90.74 8889.92 10093.20 6796.27 9383.02 11795.73 7193.86 23988.42 7892.53 6896.84 4762.09 29798.64 9190.95 8192.62 16297.93 73
PVSNet_Blended90.73 8990.32 8891.98 12196.12 9781.25 16592.55 23796.83 6482.04 22189.10 12592.56 21181.04 9798.85 8186.72 13395.91 9995.84 153
test_yl90.69 9090.02 9892.71 8995.72 11482.41 13994.11 16895.12 18485.63 14691.49 9494.70 13274.75 16698.42 11186.13 13892.53 16397.31 96
DCV-MVSNet90.69 9090.02 9892.71 8995.72 11482.41 13994.11 16895.12 18485.63 14691.49 9494.70 13274.75 16698.42 11186.13 13892.53 16397.31 96
API-MVS90.66 9290.07 9492.45 10396.36 9184.57 7396.06 5795.22 18182.39 21289.13 12494.27 15180.32 10098.46 10580.16 23096.71 8994.33 214
xiu_mvs_v1_base_debu90.64 9390.05 9592.40 10493.97 19184.46 7993.32 20695.46 16385.17 15592.25 7294.03 15670.59 22198.57 9890.97 7894.67 12094.18 219
xiu_mvs_v1_base90.64 9390.05 9592.40 10493.97 19184.46 7993.32 20695.46 16385.17 15592.25 7294.03 15670.59 22198.57 9890.97 7894.67 12094.18 219
xiu_mvs_v1_base_debi90.64 9390.05 9592.40 10493.97 19184.46 7993.32 20695.46 16385.17 15592.25 7294.03 15670.59 22198.57 9890.97 7894.67 12094.18 219
HQP_MVS90.60 9690.19 9091.82 13394.70 15782.73 12895.85 6596.22 10990.81 1586.91 16694.86 12474.23 17498.12 13188.15 10989.99 18694.63 193
FIs90.51 9790.35 8790.99 17293.99 19080.98 17395.73 7197.54 389.15 5786.72 17194.68 13481.83 9297.24 21385.18 14888.31 22094.76 191
MAR-MVS90.30 9889.37 11093.07 7496.61 8184.48 7895.68 7495.67 14882.36 21487.85 14592.85 20076.63 14498.80 8580.01 23196.68 9095.91 149
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
FC-MVSNet-test90.27 9990.18 9190.53 18393.71 20079.85 20995.77 6997.59 289.31 5286.27 18094.67 13581.93 9197.01 22884.26 16188.09 22494.71 192
CANet_DTU90.26 10089.41 10992.81 8393.46 20883.01 11893.48 20194.47 21589.43 4987.76 14994.23 15270.54 22599.03 5684.97 15096.39 9696.38 131
OPM-MVS90.12 10189.56 10491.82 13393.14 21483.90 9194.16 16595.74 14488.96 6487.86 14495.43 10572.48 20297.91 15688.10 11390.18 18593.65 253
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
LFMVS90.08 10289.13 11692.95 7996.71 7782.32 14196.08 5489.91 33186.79 12092.15 7696.81 5062.60 29598.34 11687.18 12593.90 13698.19 56
GeoE90.05 10389.43 10891.90 12995.16 13380.37 18995.80 6794.65 21283.90 17987.55 15394.75 13178.18 12997.62 17481.28 21093.63 14097.71 83
PAPR90.02 10489.27 11592.29 11295.78 11280.95 17592.68 23296.22 10981.91 22586.66 17293.75 17682.23 8398.44 10979.40 24194.79 11897.48 92
PVSNet_BlendedMVS89.98 10589.70 10290.82 17696.12 9781.25 16593.92 18696.83 6483.49 19189.10 12592.26 22181.04 9798.85 8186.72 13387.86 22892.35 298
PS-MVSNAJss89.97 10689.62 10391.02 16991.90 24980.85 17895.26 9595.98 12586.26 13086.21 18194.29 14879.70 10997.65 16988.87 10488.10 22294.57 198
mvsmamba89.96 10789.50 10591.33 15492.90 22681.82 14996.68 3392.37 27089.03 6187.00 16294.85 12673.05 19497.65 16991.03 7788.63 21194.51 203
XVG-OURS-SEG-HR89.95 10889.45 10691.47 14894.00 18981.21 16891.87 25696.06 12185.78 14088.55 13395.73 9674.67 17097.27 20988.71 10589.64 19595.91 149
UGNet89.95 10888.95 12092.95 7994.51 16783.31 10795.70 7395.23 17989.37 5187.58 15193.94 16464.00 28698.78 8683.92 16696.31 9796.74 121
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
UniMVSNet_NR-MVSNet89.92 11089.29 11391.81 13593.39 20983.72 9594.43 14897.12 3989.80 3886.46 17493.32 18483.16 7197.23 21484.92 15181.02 29994.49 208
AdaColmapbinary89.89 11189.07 11792.37 10797.41 6283.03 11694.42 14995.92 12982.81 20786.34 17994.65 13673.89 18299.02 5980.69 22195.51 10595.05 176
hse-mvs289.88 11289.34 11191.51 14594.83 15181.12 17093.94 18493.91 23889.80 3893.08 5293.60 17875.77 15197.66 16892.07 5777.07 33295.74 158
UniMVSNet (Re)89.80 11389.07 11792.01 11793.60 20484.52 7694.78 12697.47 1089.26 5386.44 17792.32 21882.10 8697.39 20184.81 15480.84 30394.12 223
HQP-MVS89.80 11389.28 11491.34 15394.17 18081.56 15494.39 15296.04 12288.81 6585.43 20593.97 16373.83 18497.96 15287.11 12889.77 19394.50 206
FA-MVS(test-final)89.66 11588.91 12291.93 12594.57 16480.27 19091.36 26794.74 20984.87 16389.82 11692.61 21074.72 16998.47 10483.97 16593.53 14397.04 109
VPA-MVSNet89.62 11688.96 11991.60 14193.86 19482.89 12395.46 8397.33 2387.91 9488.43 13693.31 18574.17 17797.40 19887.32 12482.86 27594.52 201
WTY-MVS89.60 11788.92 12191.67 13995.47 12381.15 16992.38 24194.78 20783.11 19989.06 12794.32 14678.67 12296.61 24881.57 20790.89 17997.24 99
Vis-MVSNet (Re-imp)89.59 11889.44 10790.03 21095.74 11375.85 28695.61 8090.80 31787.66 10487.83 14695.40 10676.79 14096.46 26178.37 24696.73 8897.80 80
VDDNet89.56 11988.49 13692.76 8695.07 13782.09 14396.30 4193.19 25381.05 24791.88 8496.86 4661.16 30898.33 11888.43 10892.49 16597.84 78
114514_t89.51 12088.50 13492.54 9998.11 3681.99 14595.16 10396.36 9870.19 34785.81 18695.25 11076.70 14298.63 9382.07 19596.86 8797.00 112
QAPM89.51 12088.15 14593.59 6194.92 14584.58 7296.82 2996.70 8078.43 28083.41 25796.19 7773.18 19399.30 3877.11 26296.54 9296.89 117
CLD-MVS89.47 12288.90 12391.18 15994.22 17982.07 14492.13 25196.09 11787.90 9585.37 21192.45 21474.38 17297.56 17787.15 12690.43 18193.93 232
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
LPG-MVS_test89.45 12388.90 12391.12 16194.47 16881.49 15895.30 9096.14 11486.73 12285.45 20295.16 11469.89 23198.10 13387.70 11789.23 20293.77 246
CDS-MVSNet89.45 12388.51 13392.29 11293.62 20383.61 10093.01 22494.68 21181.95 22387.82 14793.24 18978.69 12196.99 22980.34 22793.23 15396.28 134
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
iter_conf_final89.42 12588.69 12791.60 14195.12 13682.93 12195.75 7092.14 27987.32 10987.12 16194.07 15467.09 26197.55 17890.61 8789.01 20694.32 215
Fast-Effi-MVS+89.41 12688.64 12891.71 13894.74 15380.81 17993.54 19995.10 18683.11 19986.82 17090.67 27479.74 10897.75 16480.51 22593.55 14296.57 126
ab-mvs89.41 12688.35 13892.60 9595.15 13582.65 13392.20 24995.60 15583.97 17888.55 13393.70 17774.16 17898.21 12782.46 18889.37 19896.94 114
XVG-OURS89.40 12888.70 12691.52 14494.06 18381.46 16091.27 26996.07 11986.14 13588.89 12995.77 9468.73 25197.26 21187.39 12289.96 18895.83 154
test_vis1_n_192089.39 12989.84 10188.04 26892.97 22372.64 31694.71 13196.03 12486.18 13391.94 8396.56 6561.63 30095.74 29393.42 2895.11 11695.74 158
mvs_anonymous89.37 13089.32 11289.51 23393.47 20774.22 29991.65 26394.83 20382.91 20585.45 20293.79 17281.23 9696.36 26786.47 13594.09 13397.94 71
DU-MVS89.34 13188.50 13491.85 13293.04 21983.72 9594.47 14596.59 8789.50 4786.46 17493.29 18777.25 13697.23 21484.92 15181.02 29994.59 196
TAMVS89.21 13288.29 14291.96 12393.71 20082.62 13493.30 21094.19 22682.22 21687.78 14893.94 16478.83 11896.95 23177.70 25592.98 15796.32 132
ACMM84.12 989.14 13388.48 13791.12 16194.65 16081.22 16795.31 8896.12 11685.31 15485.92 18594.34 14470.19 22998.06 14585.65 14488.86 20994.08 227
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
test111189.10 13488.64 12890.48 18995.53 12274.97 29296.08 5484.89 35388.13 9090.16 11296.65 5763.29 29198.10 13386.14 13696.90 8498.39 37
EI-MVSNet89.10 13488.86 12589.80 22291.84 25178.30 24493.70 19595.01 18985.73 14287.15 15995.28 10879.87 10697.21 21683.81 16887.36 23493.88 235
ECVR-MVScopyleft89.09 13688.53 13290.77 17895.62 11975.89 28596.16 4984.22 35587.89 9790.20 11096.65 5763.19 29398.10 13385.90 14196.94 8298.33 41
RRT_MVS89.09 13688.62 13190.49 18792.85 22779.65 21396.41 3794.41 21888.22 8585.50 19894.77 13069.36 23997.31 20489.33 9886.73 24194.51 203
CNLPA89.07 13887.98 14992.34 10896.87 7484.78 7094.08 17293.24 25181.41 23884.46 22895.13 11675.57 15896.62 24577.21 26093.84 13895.61 163
PLCcopyleft84.53 789.06 13988.03 14892.15 11597.27 6882.69 13194.29 15895.44 16879.71 26084.01 24394.18 15376.68 14398.75 8777.28 25993.41 14895.02 177
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
test_djsdf89.03 14088.64 12890.21 20090.74 29679.28 22595.96 6195.90 13284.66 16985.33 21392.94 19974.02 18097.30 20589.64 9588.53 21394.05 229
HY-MVS83.01 1289.03 14087.94 15192.29 11294.86 14982.77 12492.08 25494.49 21481.52 23786.93 16492.79 20678.32 12898.23 12479.93 23290.55 18095.88 151
ACMP84.23 889.01 14288.35 13890.99 17294.73 15481.27 16495.07 10895.89 13486.48 12583.67 25094.30 14769.33 24097.99 15087.10 13088.55 21293.72 250
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
sss88.93 14388.26 14490.94 17594.05 18480.78 18091.71 26095.38 17281.55 23688.63 13293.91 16875.04 16395.47 30482.47 18791.61 17096.57 126
iter_conf0588.85 14488.08 14791.17 16094.27 17881.64 15395.18 10092.15 27886.23 13287.28 15894.07 15463.89 28997.55 17890.63 8689.00 20794.32 215
TranMVSNet+NR-MVSNet88.84 14587.95 15091.49 14692.68 23183.01 11894.92 11796.31 10089.88 3785.53 19593.85 17176.63 14496.96 23081.91 19979.87 31694.50 206
CHOSEN 1792x268888.84 14587.69 15492.30 11196.14 9681.42 16290.01 29395.86 13674.52 31987.41 15493.94 16475.46 15998.36 11380.36 22695.53 10497.12 106
MVSTER88.84 14588.29 14290.51 18692.95 22480.44 18893.73 19295.01 18984.66 16987.15 15993.12 19472.79 19897.21 21687.86 11487.36 23493.87 236
OpenMVScopyleft83.78 1188.74 14887.29 16493.08 7292.70 23085.39 6496.57 3596.43 9478.74 27580.85 28696.07 8169.64 23599.01 6178.01 25396.65 9194.83 188
thisisatest053088.67 14987.61 15691.86 13094.87 14880.07 19894.63 13589.90 33284.00 17788.46 13593.78 17366.88 26598.46 10583.30 17392.65 16197.06 107
Effi-MVS+-dtu88.65 15088.35 13889.54 23093.33 21076.39 28094.47 14594.36 22087.70 10285.43 20589.56 29673.45 18997.26 21185.57 14691.28 17294.97 178
tttt051788.61 15187.78 15391.11 16494.96 14277.81 25795.35 8689.69 33585.09 16088.05 14294.59 13966.93 26398.48 10283.27 17492.13 16897.03 110
BH-untuned88.60 15288.13 14690.01 21395.24 13078.50 23893.29 21194.15 22884.75 16784.46 22893.40 18175.76 15397.40 19877.59 25694.52 12794.12 223
NR-MVSNet88.58 15387.47 16091.93 12593.04 21984.16 8694.77 12796.25 10689.05 5980.04 30093.29 18779.02 11797.05 22681.71 20680.05 31394.59 196
1112_ss88.42 15487.33 16391.72 13794.92 14580.98 17392.97 22694.54 21378.16 28683.82 24693.88 16978.78 12097.91 15679.45 23789.41 19796.26 135
WR-MVS88.38 15587.67 15590.52 18593.30 21180.18 19393.26 21395.96 12788.57 7485.47 20192.81 20476.12 14696.91 23481.24 21182.29 27994.47 211
BH-RMVSNet88.37 15687.48 15991.02 16995.28 12779.45 21792.89 22893.07 25585.45 15186.91 16694.84 12870.35 22697.76 16173.97 29094.59 12495.85 152
IterMVS-LS88.36 15787.91 15289.70 22693.80 19778.29 24593.73 19295.08 18885.73 14284.75 22091.90 23779.88 10596.92 23383.83 16782.51 27693.89 233
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
X-MVStestdata88.31 15886.13 20494.85 2398.54 1386.60 3196.93 2297.19 3390.66 2292.85 5723.41 37485.02 5499.49 2491.99 6198.56 4698.47 31
LCM-MVSNet-Re88.30 15988.32 14188.27 26094.71 15672.41 32193.15 21790.98 31287.77 10079.25 30891.96 23578.35 12795.75 29283.04 17695.62 10396.65 123
jajsoiax88.24 16087.50 15890.48 18990.89 29080.14 19595.31 8895.65 15284.97 16284.24 23994.02 15965.31 28097.42 19188.56 10688.52 21493.89 233
VPNet88.20 16187.47 16090.39 19493.56 20579.46 21694.04 17695.54 15988.67 7086.96 16394.58 14069.33 24097.15 21884.05 16480.53 30894.56 199
TAPA-MVS84.62 688.16 16287.01 17291.62 14096.64 8080.65 18294.39 15296.21 11276.38 29986.19 18295.44 10379.75 10798.08 14362.75 34795.29 11296.13 139
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
baseline188.10 16387.28 16590.57 18194.96 14280.07 19894.27 15991.29 30586.74 12187.41 15494.00 16176.77 14196.20 27280.77 21979.31 32195.44 165
Anonymous2024052988.09 16486.59 18892.58 9796.53 8681.92 14895.99 5995.84 13774.11 32389.06 12795.21 11361.44 30398.81 8483.67 17187.47 23197.01 111
HyFIR lowres test88.09 16486.81 17691.93 12596.00 10580.63 18390.01 29395.79 14073.42 32987.68 15092.10 22973.86 18397.96 15280.75 22091.70 16997.19 102
mvs_tets88.06 16687.28 16590.38 19690.94 28679.88 20795.22 9795.66 15085.10 15984.21 24093.94 16463.53 29097.40 19888.50 10788.40 21893.87 236
F-COLMAP87.95 16786.80 17791.40 15096.35 9280.88 17794.73 12995.45 16679.65 26182.04 27494.61 13771.13 21298.50 10176.24 27191.05 17794.80 190
LS3D87.89 16886.32 19892.59 9696.07 10282.92 12295.23 9694.92 19675.66 30682.89 26495.98 8472.48 20299.21 4368.43 32195.23 11595.64 162
anonymousdsp87.84 16987.09 16890.12 20689.13 32380.54 18694.67 13395.55 15782.05 21983.82 24692.12 22671.47 21097.15 21887.15 12687.80 23092.67 287
v2v48287.84 16987.06 16990.17 20290.99 28279.23 22894.00 18195.13 18384.87 16385.53 19592.07 23274.45 17197.45 18784.71 15681.75 28793.85 239
WR-MVS_H87.80 17187.37 16289.10 24193.23 21278.12 24895.61 8097.30 2787.90 9583.72 24892.01 23479.65 11396.01 28076.36 26880.54 30793.16 272
AUN-MVS87.78 17286.54 19091.48 14794.82 15281.05 17193.91 18893.93 23583.00 20286.93 16493.53 17969.50 23797.67 16686.14 13677.12 33195.73 160
PCF-MVS84.11 1087.74 17386.08 20892.70 9194.02 18584.43 8289.27 30395.87 13573.62 32884.43 23094.33 14578.48 12698.86 7970.27 30794.45 12994.81 189
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
Anonymous20240521187.68 17486.13 20492.31 11096.66 7980.74 18194.87 12091.49 30080.47 25189.46 12195.44 10354.72 33598.23 12482.19 19389.89 19097.97 70
V4287.68 17486.86 17490.15 20490.58 30280.14 19594.24 16295.28 17783.66 18585.67 18991.33 25274.73 16897.41 19684.43 16081.83 28592.89 282
thres600view787.65 17686.67 18390.59 18096.08 10178.72 23194.88 11991.58 29687.06 11388.08 14092.30 21968.91 24898.10 13370.05 31491.10 17394.96 181
XXY-MVS87.65 17686.85 17590.03 21092.14 24180.60 18593.76 19195.23 17982.94 20484.60 22394.02 15974.27 17395.49 30381.04 21383.68 26394.01 231
Test_1112_low_res87.65 17686.51 19191.08 16594.94 14479.28 22591.77 25894.30 22276.04 30483.51 25592.37 21677.86 13397.73 16578.69 24589.13 20496.22 136
thres100view90087.63 17986.71 18190.38 19696.12 9778.55 23595.03 11191.58 29687.15 11088.06 14192.29 22068.91 24898.10 13370.13 31191.10 17394.48 209
CP-MVSNet87.63 17987.26 16788.74 25093.12 21576.59 27795.29 9296.58 8888.43 7783.49 25692.98 19875.28 16095.83 28878.97 24381.15 29593.79 241
thres40087.62 18186.64 18490.57 18195.99 10678.64 23394.58 13791.98 28686.94 11788.09 13891.77 23969.18 24598.10 13370.13 31191.10 17394.96 181
v114487.61 18286.79 17890.06 20991.01 28179.34 22193.95 18395.42 17183.36 19585.66 19091.31 25574.98 16497.42 19183.37 17282.06 28193.42 262
bld_raw_dy_0_6487.60 18386.73 17990.21 20091.72 25580.26 19295.09 10788.61 34085.68 14485.55 19294.38 14363.93 28896.66 24287.73 11687.84 22993.72 250
tfpn200view987.58 18486.64 18490.41 19395.99 10678.64 23394.58 13791.98 28686.94 11788.09 13891.77 23969.18 24598.10 13370.13 31191.10 17394.48 209
BH-w/o87.57 18587.05 17089.12 24094.90 14777.90 25392.41 23993.51 24882.89 20683.70 24991.34 25175.75 15497.07 22475.49 27693.49 14592.39 296
UniMVSNet_ETH3D87.53 18686.37 19591.00 17192.44 23478.96 23094.74 12895.61 15484.07 17685.36 21294.52 14159.78 31697.34 20382.93 17887.88 22796.71 122
ET-MVSNet_ETH3D87.51 18785.91 21692.32 10993.70 20283.93 9092.33 24490.94 31384.16 17372.09 34692.52 21269.90 23095.85 28789.20 10088.36 21997.17 103
131487.51 18786.57 18990.34 19892.42 23579.74 21192.63 23495.35 17678.35 28180.14 29791.62 24674.05 17997.15 21881.05 21293.53 14394.12 223
v887.50 18986.71 18189.89 21691.37 26879.40 21894.50 14195.38 17284.81 16683.60 25391.33 25276.05 14797.42 19182.84 18180.51 31092.84 284
Fast-Effi-MVS+-dtu87.44 19086.72 18089.63 22892.04 24577.68 26294.03 17793.94 23485.81 13982.42 26891.32 25470.33 22797.06 22580.33 22890.23 18494.14 222
MVS87.44 19086.10 20791.44 14992.61 23283.62 9992.63 23495.66 15067.26 35181.47 27892.15 22477.95 13098.22 12679.71 23495.48 10692.47 293
FE-MVS87.40 19286.02 21091.57 14394.56 16579.69 21290.27 28393.72 24580.57 25088.80 13091.62 24665.32 27998.59 9774.97 28494.33 13296.44 129
FMVSNet387.40 19286.11 20691.30 15593.79 19983.64 9894.20 16494.81 20583.89 18084.37 23191.87 23868.45 25496.56 25378.23 25085.36 24893.70 252
test_fmvs187.34 19487.56 15786.68 30090.59 30171.80 32594.01 17994.04 23378.30 28291.97 8095.22 11156.28 32893.71 32792.89 3694.71 11994.52 201
thisisatest051587.33 19585.99 21191.37 15293.49 20679.55 21490.63 27989.56 33880.17 25387.56 15290.86 26867.07 26298.28 12281.50 20893.02 15696.29 133
PS-CasMVS87.32 19686.88 17388.63 25392.99 22276.33 28295.33 8796.61 8688.22 8583.30 26193.07 19673.03 19695.79 29178.36 24781.00 30193.75 248
GBi-Net87.26 19785.98 21291.08 16594.01 18683.10 11295.14 10494.94 19283.57 18784.37 23191.64 24266.59 27096.34 26878.23 25085.36 24893.79 241
test187.26 19785.98 21291.08 16594.01 18683.10 11295.14 10494.94 19283.57 18784.37 23191.64 24266.59 27096.34 26878.23 25085.36 24893.79 241
v119287.25 19986.33 19790.00 21490.76 29579.04 22993.80 18995.48 16282.57 21085.48 20091.18 25973.38 19297.42 19182.30 19182.06 28193.53 256
v1087.25 19986.38 19489.85 21791.19 27479.50 21594.48 14295.45 16683.79 18383.62 25291.19 25775.13 16197.42 19181.94 19880.60 30592.63 289
DP-MVS87.25 19985.36 23192.90 8197.65 5583.24 10894.81 12492.00 28474.99 31481.92 27695.00 11972.66 19999.05 5366.92 33292.33 16696.40 130
miper_ehance_all_eth87.22 20286.62 18789.02 24492.13 24277.40 26790.91 27594.81 20581.28 24184.32 23690.08 28579.26 11596.62 24583.81 16882.94 27193.04 277
test250687.21 20386.28 20090.02 21295.62 11973.64 30496.25 4671.38 37487.89 9790.45 10696.65 5755.29 33398.09 14186.03 14096.94 8298.33 41
thres20087.21 20386.24 20290.12 20695.36 12578.53 23693.26 21392.10 28086.42 12788.00 14391.11 26369.24 24498.00 14969.58 31591.04 17893.83 240
v14419287.19 20586.35 19689.74 22390.64 29978.24 24693.92 18695.43 16981.93 22485.51 19791.05 26574.21 17697.45 18782.86 18081.56 28993.53 256
FMVSNet287.19 20585.82 21891.30 15594.01 18683.67 9794.79 12594.94 19283.57 18783.88 24592.05 23366.59 27096.51 25677.56 25785.01 25193.73 249
c3_l87.14 20786.50 19289.04 24392.20 23977.26 26891.22 27194.70 21082.01 22284.34 23590.43 27878.81 11996.61 24883.70 17081.09 29693.25 267
Baseline_NR-MVSNet87.07 20886.63 18688.40 25691.44 26377.87 25594.23 16392.57 26784.12 17585.74 18892.08 23077.25 13696.04 27782.29 19279.94 31491.30 316
v14887.04 20986.32 19889.21 23790.94 28677.26 26893.71 19494.43 21684.84 16584.36 23490.80 27176.04 14897.05 22682.12 19479.60 31893.31 264
test_fmvs1_n87.03 21087.04 17186.97 29289.74 31971.86 32394.55 13994.43 21678.47 27891.95 8295.50 10251.16 34593.81 32593.02 3594.56 12595.26 171
v192192086.97 21186.06 20989.69 22790.53 30578.11 24993.80 18995.43 16981.90 22685.33 21391.05 26572.66 19997.41 19682.05 19681.80 28693.53 256
tt080586.92 21285.74 22490.48 18992.22 23879.98 20595.63 7994.88 19983.83 18284.74 22192.80 20557.61 32497.67 16685.48 14784.42 25593.79 241
miper_enhance_ethall86.90 21386.18 20389.06 24291.66 26077.58 26490.22 28994.82 20479.16 26784.48 22789.10 29979.19 11696.66 24284.06 16382.94 27192.94 280
v7n86.81 21485.76 22289.95 21590.72 29779.25 22795.07 10895.92 12984.45 17282.29 26990.86 26872.60 20197.53 18179.42 24080.52 30993.08 276
PEN-MVS86.80 21586.27 20188.40 25692.32 23775.71 28895.18 10096.38 9787.97 9282.82 26593.15 19273.39 19195.92 28376.15 27279.03 32393.59 254
cl2286.78 21685.98 21289.18 23992.34 23677.62 26390.84 27694.13 23081.33 24083.97 24490.15 28373.96 18196.60 25084.19 16282.94 27193.33 263
v124086.78 21685.85 21789.56 22990.45 30677.79 25893.61 19795.37 17481.65 23285.43 20591.15 26171.50 20997.43 19081.47 20982.05 28393.47 260
TR-MVS86.78 21685.76 22289.82 21994.37 17478.41 24092.47 23892.83 26081.11 24686.36 17892.40 21568.73 25197.48 18473.75 29389.85 19293.57 255
PatchMatch-RL86.77 21985.54 22590.47 19295.88 10982.71 13090.54 28092.31 27379.82 25984.32 23691.57 25068.77 25096.39 26473.16 29593.48 14792.32 299
PAPM86.68 22085.39 22990.53 18393.05 21879.33 22489.79 29694.77 20878.82 27281.95 27593.24 18976.81 13997.30 20566.94 33093.16 15494.95 184
pm-mvs186.61 22185.54 22589.82 21991.44 26380.18 19395.28 9494.85 20183.84 18181.66 27792.62 20972.45 20496.48 25879.67 23578.06 32492.82 285
GA-MVS86.61 22185.27 23390.66 17991.33 27178.71 23290.40 28293.81 24285.34 15385.12 21589.57 29561.25 30597.11 22280.99 21689.59 19696.15 137
Anonymous2023121186.59 22385.13 23590.98 17496.52 8781.50 15696.14 5196.16 11373.78 32683.65 25192.15 22463.26 29297.37 20282.82 18281.74 28894.06 228
test_vis1_n86.56 22486.49 19386.78 29988.51 32872.69 31394.68 13293.78 24379.55 26290.70 10395.31 10748.75 35093.28 33393.15 3293.99 13494.38 213
DIV-MVS_self_test86.53 22585.78 21988.75 24892.02 24776.45 27990.74 27794.30 22281.83 23083.34 25990.82 27075.75 15496.57 25181.73 20581.52 29193.24 268
cl____86.52 22685.78 21988.75 24892.03 24676.46 27890.74 27794.30 22281.83 23083.34 25990.78 27275.74 15696.57 25181.74 20481.54 29093.22 269
eth_miper_zixun_eth86.50 22785.77 22188.68 25191.94 24875.81 28790.47 28194.89 19782.05 21984.05 24190.46 27775.96 14996.77 23882.76 18479.36 32093.46 261
baseline286.50 22785.39 22989.84 21891.12 27876.70 27591.88 25588.58 34182.35 21579.95 30190.95 26773.42 19097.63 17380.27 22989.95 18995.19 173
EPNet_dtu86.49 22985.94 21588.14 26590.24 30972.82 31194.11 16892.20 27686.66 12479.42 30792.36 21773.52 18795.81 29071.26 30193.66 13995.80 156
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
cascas86.43 23084.98 23890.80 17792.10 24480.92 17690.24 28795.91 13173.10 33283.57 25488.39 31065.15 28197.46 18684.90 15391.43 17194.03 230
SCA86.32 23185.18 23489.73 22592.15 24076.60 27691.12 27291.69 29383.53 19085.50 19888.81 30366.79 26696.48 25876.65 26590.35 18396.12 140
LTVRE_ROB82.13 1386.26 23284.90 24190.34 19894.44 17281.50 15692.31 24694.89 19783.03 20179.63 30592.67 20769.69 23497.79 15971.20 30286.26 24491.72 308
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
DTE-MVSNet86.11 23385.48 22787.98 26991.65 26174.92 29394.93 11695.75 14387.36 10882.26 27093.04 19772.85 19795.82 28974.04 28977.46 32993.20 270
XVG-ACMP-BASELINE86.00 23484.84 24389.45 23491.20 27378.00 25091.70 26195.55 15785.05 16182.97 26392.25 22254.49 33697.48 18482.93 17887.45 23392.89 282
MVP-Stereo85.97 23584.86 24289.32 23590.92 28882.19 14292.11 25294.19 22678.76 27478.77 31191.63 24568.38 25596.56 25375.01 28393.95 13589.20 341
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
D2MVS85.90 23685.09 23688.35 25890.79 29377.42 26691.83 25795.70 14680.77 24980.08 29990.02 28666.74 26896.37 26581.88 20087.97 22691.26 317
test-LLR85.87 23785.41 22887.25 28590.95 28471.67 32789.55 29789.88 33383.41 19384.54 22587.95 31767.25 25895.11 30981.82 20193.37 15094.97 178
FMVSNet185.85 23884.11 25291.08 16592.81 22883.10 11295.14 10494.94 19281.64 23382.68 26691.64 24259.01 32096.34 26875.37 27883.78 26093.79 241
PatchmatchNetpermissive85.85 23884.70 24589.29 23691.76 25475.54 28988.49 31591.30 30481.63 23485.05 21688.70 30771.71 20696.24 27174.61 28789.05 20596.08 143
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
CostFormer85.77 24084.94 24088.26 26191.16 27772.58 31989.47 30191.04 31176.26 30286.45 17689.97 28870.74 21996.86 23782.35 19087.07 23995.34 170
PMMVS85.71 24184.96 23987.95 27088.90 32677.09 27088.68 31390.06 32772.32 33886.47 17390.76 27372.15 20594.40 31581.78 20393.49 14592.36 297
PVSNet78.82 1885.55 24284.65 24688.23 26394.72 15571.93 32287.12 33092.75 26378.80 27384.95 21890.53 27664.43 28596.71 24174.74 28593.86 13796.06 145
IterMVS-SCA-FT85.45 24384.53 24988.18 26491.71 25776.87 27390.19 29092.65 26685.40 15281.44 27990.54 27566.79 26695.00 31281.04 21381.05 29792.66 288
pmmvs485.43 24483.86 25790.16 20390.02 31482.97 12090.27 28392.67 26575.93 30580.73 28791.74 24171.05 21395.73 29478.85 24483.46 26791.78 307
mvsany_test185.42 24585.30 23285.77 31087.95 33975.41 29187.61 32780.97 36376.82 29688.68 13195.83 9077.44 13590.82 35185.90 14186.51 24291.08 325
ACMH80.38 1785.36 24683.68 25990.39 19494.45 17180.63 18394.73 12994.85 20182.09 21877.24 31992.65 20860.01 31497.58 17572.25 29984.87 25292.96 279
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
OurMVSNet-221017-085.35 24784.64 24787.49 27990.77 29472.59 31894.01 17994.40 21984.72 16879.62 30693.17 19161.91 29996.72 23981.99 19781.16 29393.16 272
CR-MVSNet85.35 24783.76 25890.12 20690.58 30279.34 22185.24 34291.96 28878.27 28385.55 19287.87 32071.03 21495.61 29573.96 29189.36 19995.40 167
tpmrst85.35 24784.99 23786.43 30290.88 29167.88 34888.71 31291.43 30280.13 25486.08 18488.80 30573.05 19496.02 27982.48 18683.40 26995.40 167
miper_lstm_enhance85.27 25084.59 24887.31 28291.28 27274.63 29487.69 32494.09 23281.20 24581.36 28189.85 29174.97 16594.30 31881.03 21579.84 31793.01 278
IB-MVS80.51 1585.24 25183.26 26391.19 15892.13 24279.86 20891.75 25991.29 30583.28 19780.66 28988.49 30961.28 30498.46 10580.99 21679.46 31995.25 172
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
CHOSEN 280x42085.15 25283.99 25588.65 25292.47 23378.40 24179.68 36292.76 26274.90 31681.41 28089.59 29469.85 23395.51 30079.92 23395.29 11292.03 303
RPSCF85.07 25384.27 25087.48 28092.91 22570.62 33791.69 26292.46 26876.20 30382.67 26795.22 11163.94 28797.29 20877.51 25885.80 24694.53 200
MS-PatchMatch85.05 25484.16 25187.73 27391.42 26678.51 23791.25 27093.53 24777.50 28980.15 29691.58 24861.99 29895.51 30075.69 27594.35 13189.16 342
ACMH+81.04 1485.05 25483.46 26289.82 21994.66 15979.37 21994.44 14794.12 23182.19 21778.04 31492.82 20358.23 32297.54 18073.77 29282.90 27492.54 290
IterMVS84.88 25683.98 25687.60 27591.44 26376.03 28490.18 29192.41 26983.24 19881.06 28590.42 27966.60 26994.28 31979.46 23680.98 30292.48 292
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
MSDG84.86 25783.09 26590.14 20593.80 19780.05 20089.18 30693.09 25478.89 27078.19 31291.91 23665.86 27897.27 20968.47 32088.45 21693.11 274
tpm84.73 25884.02 25486.87 29790.33 30768.90 34489.06 30889.94 33080.85 24885.75 18789.86 29068.54 25395.97 28177.76 25484.05 25995.75 157
tfpnnormal84.72 25983.23 26489.20 23892.79 22980.05 20094.48 14295.81 13882.38 21381.08 28491.21 25669.01 24796.95 23161.69 34980.59 30690.58 331
CVMVSNet84.69 26084.79 24484.37 32191.84 25164.92 35793.70 19591.47 30166.19 35386.16 18395.28 10867.18 26093.33 33280.89 21890.42 18294.88 186
test-mter84.54 26183.64 26087.25 28590.95 28471.67 32789.55 29789.88 33379.17 26684.54 22587.95 31755.56 33095.11 30981.82 20193.37 15094.97 178
TransMVSNet (Re)84.43 26283.06 26688.54 25491.72 25578.44 23995.18 10092.82 26182.73 20879.67 30492.12 22673.49 18895.96 28271.10 30668.73 35391.21 319
pmmvs584.21 26382.84 27088.34 25988.95 32576.94 27292.41 23991.91 29075.63 30780.28 29491.18 25964.59 28495.57 29677.09 26383.47 26692.53 291
tpm284.08 26482.94 26787.48 28091.39 26771.27 32989.23 30590.37 32171.95 34084.64 22289.33 29767.30 25796.55 25575.17 28087.09 23894.63 193
test_fmvs283.98 26584.03 25383.83 32687.16 34167.53 35193.93 18592.89 25877.62 28886.89 16993.53 17947.18 35592.02 34490.54 8886.51 24291.93 305
COLMAP_ROBcopyleft80.39 1683.96 26682.04 27389.74 22395.28 12779.75 21094.25 16092.28 27475.17 31278.02 31593.77 17458.60 32197.84 15865.06 34085.92 24591.63 310
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
RPMNet83.95 26781.53 27791.21 15790.58 30279.34 22185.24 34296.76 7271.44 34285.55 19282.97 35070.87 21798.91 7561.01 35189.36 19995.40 167
SixPastTwentyTwo83.91 26882.90 26886.92 29490.99 28270.67 33693.48 20191.99 28585.54 14977.62 31892.11 22860.59 31096.87 23676.05 27377.75 32693.20 270
EPMVS83.90 26982.70 27187.51 27790.23 31072.67 31488.62 31481.96 36181.37 23985.01 21788.34 31166.31 27394.45 31475.30 27987.12 23795.43 166
TESTMET0.1,183.74 27082.85 26986.42 30389.96 31571.21 33189.55 29787.88 34377.41 29083.37 25887.31 32556.71 32693.65 32980.62 22392.85 16094.40 212
MVS_030483.46 27181.92 27488.10 26690.63 30077.49 26593.26 21393.75 24480.04 25680.44 29387.24 32747.94 35295.55 29775.79 27488.16 22191.26 317
pmmvs683.42 27281.60 27688.87 24688.01 33777.87 25594.96 11494.24 22574.67 31878.80 31091.09 26460.17 31396.49 25777.06 26475.40 33792.23 301
AllTest83.42 27281.39 27889.52 23195.01 13877.79 25893.12 21890.89 31577.41 29076.12 32793.34 18254.08 33897.51 18268.31 32284.27 25793.26 265
tpmvs83.35 27482.07 27287.20 28991.07 28071.00 33488.31 31891.70 29278.91 26980.49 29287.18 32869.30 24397.08 22368.12 32583.56 26593.51 259
USDC82.76 27581.26 28087.26 28491.17 27574.55 29589.27 30393.39 25078.26 28475.30 33292.08 23054.43 33796.63 24471.64 30085.79 24790.61 328
Patchmtry82.71 27680.93 28288.06 26790.05 31376.37 28184.74 34791.96 28872.28 33981.32 28287.87 32071.03 21495.50 30268.97 31780.15 31292.32 299
PatchT82.68 27781.27 27986.89 29690.09 31270.94 33584.06 34990.15 32474.91 31585.63 19183.57 34669.37 23894.87 31365.19 33788.50 21594.84 187
MIMVSNet82.59 27880.53 28388.76 24791.51 26278.32 24386.57 33390.13 32579.32 26380.70 28888.69 30852.98 34293.07 33766.03 33588.86 20994.90 185
test0.0.03 182.41 27981.69 27584.59 31988.23 33472.89 31090.24 28787.83 34483.41 19379.86 30289.78 29267.25 25888.99 35965.18 33883.42 26891.90 306
EG-PatchMatch MVS82.37 28080.34 28688.46 25590.27 30879.35 22092.80 23194.33 22177.14 29473.26 34390.18 28247.47 35496.72 23970.25 30887.32 23689.30 339
tpm cat181.96 28180.27 28787.01 29191.09 27971.02 33387.38 32891.53 29966.25 35280.17 29586.35 33468.22 25696.15 27569.16 31682.29 27993.86 238
our_test_381.93 28280.46 28586.33 30488.46 33173.48 30688.46 31691.11 30776.46 29776.69 32388.25 31366.89 26494.36 31668.75 31879.08 32291.14 321
ppachtmachnet_test81.84 28380.07 29187.15 29088.46 33174.43 29889.04 30992.16 27775.33 31077.75 31688.99 30066.20 27495.37 30565.12 33977.60 32791.65 309
gg-mvs-nofinetune81.77 28479.37 29788.99 24590.85 29277.73 26186.29 33479.63 36674.88 31783.19 26269.05 36460.34 31196.11 27675.46 27794.64 12393.11 274
CL-MVSNet_self_test81.74 28580.53 28385.36 31385.96 34772.45 32090.25 28593.07 25581.24 24379.85 30387.29 32670.93 21692.52 34066.95 32969.23 34991.11 323
Patchmatch-RL test81.67 28679.96 29286.81 29885.42 35271.23 33082.17 35687.50 34778.47 27877.19 32082.50 35170.81 21893.48 33082.66 18572.89 34195.71 161
ADS-MVSNet281.66 28779.71 29587.50 27891.35 26974.19 30083.33 35288.48 34272.90 33482.24 27185.77 33864.98 28293.20 33564.57 34183.74 26195.12 174
K. test v381.59 28880.15 29085.91 30989.89 31769.42 34392.57 23687.71 34585.56 14873.44 34289.71 29355.58 32995.52 29977.17 26169.76 34792.78 286
ADS-MVSNet81.56 28979.78 29386.90 29591.35 26971.82 32483.33 35289.16 33972.90 33482.24 27185.77 33864.98 28293.76 32664.57 34183.74 26195.12 174
FMVSNet581.52 29079.60 29687.27 28391.17 27577.95 25191.49 26592.26 27576.87 29576.16 32687.91 31951.67 34392.34 34167.74 32681.16 29391.52 311
dp81.47 29180.23 28885.17 31689.92 31665.49 35586.74 33190.10 32676.30 30181.10 28387.12 32962.81 29495.92 28368.13 32479.88 31594.09 226
Patchmatch-test81.37 29279.30 29887.58 27690.92 28874.16 30180.99 35887.68 34670.52 34676.63 32488.81 30371.21 21192.76 33960.01 35586.93 24095.83 154
EU-MVSNet81.32 29380.95 28182.42 33288.50 33063.67 35893.32 20691.33 30364.02 35680.57 29192.83 20261.21 30792.27 34276.34 26980.38 31191.32 315
test_040281.30 29479.17 30287.67 27493.19 21378.17 24792.98 22591.71 29175.25 31176.02 32990.31 28059.23 31896.37 26550.22 36383.63 26488.47 348
JIA-IIPM81.04 29578.98 30587.25 28588.64 32773.48 30681.75 35789.61 33773.19 33182.05 27373.71 36166.07 27795.87 28671.18 30484.60 25492.41 295
Anonymous2023120681.03 29679.77 29484.82 31887.85 34070.26 33991.42 26692.08 28173.67 32777.75 31689.25 29862.43 29693.08 33661.50 35082.00 28491.12 322
pmmvs-eth3d80.97 29778.72 30687.74 27284.99 35479.97 20690.11 29291.65 29475.36 30973.51 34186.03 33559.45 31793.96 32475.17 28072.21 34289.29 340
testgi80.94 29880.20 28983.18 32787.96 33866.29 35291.28 26890.70 31983.70 18478.12 31392.84 20151.37 34490.82 35163.34 34482.46 27792.43 294
CMPMVSbinary59.16 2180.52 29979.20 30184.48 32083.98 35567.63 35089.95 29593.84 24164.79 35566.81 35691.14 26257.93 32395.17 30776.25 27088.10 22290.65 327
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
Anonymous2024052180.44 30079.21 30084.11 32485.75 35067.89 34792.86 22993.23 25275.61 30875.59 33187.47 32450.03 34694.33 31771.14 30581.21 29290.12 333
LF4IMVS80.37 30179.07 30484.27 32386.64 34369.87 34289.39 30291.05 31076.38 29974.97 33490.00 28747.85 35394.25 32074.55 28880.82 30488.69 346
KD-MVS_self_test80.20 30279.24 29983.07 32885.64 35165.29 35691.01 27493.93 23578.71 27676.32 32586.40 33359.20 31992.93 33872.59 29769.35 34891.00 326
UnsupCasMVSNet_eth80.07 30378.27 30785.46 31285.24 35372.63 31788.45 31794.87 20082.99 20371.64 34988.07 31656.34 32791.75 34773.48 29463.36 36092.01 304
test20.0379.95 30479.08 30382.55 33085.79 34967.74 34991.09 27391.08 30881.23 24474.48 33889.96 28961.63 30090.15 35360.08 35376.38 33389.76 334
TDRefinement79.81 30577.34 30987.22 28879.24 36475.48 29093.12 21892.03 28376.45 29875.01 33391.58 24849.19 34996.44 26270.22 31069.18 35089.75 335
TinyColmap79.76 30677.69 30885.97 30691.71 25773.12 30889.55 29790.36 32275.03 31372.03 34790.19 28146.22 35696.19 27463.11 34581.03 29888.59 347
OpenMVS_ROBcopyleft74.94 1979.51 30777.03 31486.93 29387.00 34276.23 28392.33 24490.74 31868.93 34974.52 33788.23 31449.58 34896.62 24557.64 35784.29 25687.94 350
MIMVSNet179.38 30877.28 31085.69 31186.35 34473.67 30391.61 26492.75 26378.11 28772.64 34588.12 31548.16 35191.97 34660.32 35277.49 32891.43 314
YYNet179.22 30977.20 31185.28 31588.20 33672.66 31585.87 33690.05 32974.33 32162.70 35887.61 32266.09 27692.03 34366.94 33072.97 34091.15 320
MDA-MVSNet_test_wron79.21 31077.19 31285.29 31488.22 33572.77 31285.87 33690.06 32774.34 32062.62 35987.56 32366.14 27591.99 34566.90 33373.01 33991.10 324
MDA-MVSNet-bldmvs78.85 31176.31 31686.46 30189.76 31873.88 30288.79 31190.42 32079.16 26759.18 36088.33 31260.20 31294.04 32162.00 34868.96 35191.48 313
KD-MVS_2432*160078.50 31276.02 31985.93 30786.22 34574.47 29684.80 34592.33 27179.29 26476.98 32185.92 33653.81 34093.97 32267.39 32757.42 36589.36 337
miper_refine_blended78.50 31276.02 31985.93 30786.22 34574.47 29684.80 34592.33 27179.29 26476.98 32185.92 33653.81 34093.97 32267.39 32757.42 36589.36 337
PM-MVS78.11 31476.12 31884.09 32583.54 35770.08 34088.97 31085.27 35279.93 25774.73 33686.43 33234.70 36393.48 33079.43 23972.06 34388.72 345
test_vis1_rt77.96 31576.46 31582.48 33185.89 34871.74 32690.25 28578.89 36771.03 34571.30 35081.35 35342.49 35991.05 35084.55 15882.37 27884.65 353
test_fmvs377.67 31677.16 31379.22 33679.52 36361.14 36292.34 24391.64 29573.98 32478.86 30986.59 33027.38 36787.03 36188.12 11275.97 33589.50 336
PVSNet_073.20 2077.22 31774.83 32284.37 32190.70 29871.10 33283.09 35489.67 33672.81 33673.93 34083.13 34860.79 30993.70 32868.54 31950.84 36888.30 349
DSMNet-mixed76.94 31876.29 31778.89 33783.10 35856.11 37287.78 32279.77 36560.65 35975.64 33088.71 30661.56 30288.34 36060.07 35489.29 20192.21 302
new-patchmatchnet76.41 31975.17 32180.13 33482.65 36059.61 36487.66 32591.08 30878.23 28569.85 35283.22 34754.76 33491.63 34964.14 34364.89 35889.16 342
UnsupCasMVSNet_bld76.23 32073.27 32385.09 31783.79 35672.92 30985.65 33993.47 24971.52 34168.84 35479.08 35649.77 34793.21 33466.81 33460.52 36289.13 344
mvsany_test374.95 32173.26 32480.02 33574.61 36663.16 36085.53 34078.42 36874.16 32274.89 33586.46 33136.02 36289.09 35882.39 18966.91 35487.82 351
MVS-HIRNet73.70 32272.20 32578.18 34091.81 25356.42 37182.94 35582.58 35955.24 36168.88 35366.48 36555.32 33295.13 30858.12 35688.42 21783.01 356
new_pmnet72.15 32370.13 32778.20 33982.95 35965.68 35383.91 35082.40 36062.94 35864.47 35779.82 35542.85 35886.26 36357.41 35874.44 33882.65 358
test_f71.95 32470.87 32675.21 34374.21 36859.37 36585.07 34485.82 34965.25 35470.42 35183.13 34823.62 36882.93 36878.32 24871.94 34483.33 355
pmmvs371.81 32568.71 32881.11 33375.86 36570.42 33886.74 33183.66 35658.95 36068.64 35580.89 35436.93 36189.52 35663.10 34663.59 35983.39 354
APD_test169.04 32666.26 33077.36 34280.51 36162.79 36185.46 34183.51 35754.11 36359.14 36184.79 34223.40 37089.61 35555.22 35970.24 34679.68 361
N_pmnet68.89 32768.44 32970.23 34789.07 32428.79 38188.06 31919.50 38269.47 34871.86 34884.93 34061.24 30691.75 34754.70 36077.15 33090.15 332
LCM-MVSNet66.00 32862.16 33377.51 34164.51 37658.29 36683.87 35190.90 31448.17 36554.69 36273.31 36216.83 37686.75 36265.47 33661.67 36187.48 352
test_vis3_rt65.12 32962.60 33172.69 34571.44 36960.71 36387.17 32965.55 37563.80 35753.22 36365.65 36714.54 37789.44 35776.65 26565.38 35667.91 366
FPMVS64.63 33062.55 33270.88 34670.80 37056.71 36784.42 34884.42 35451.78 36449.57 36481.61 35223.49 36981.48 36940.61 37076.25 33474.46 362
EGC-MVSNET61.97 33156.37 33578.77 33889.63 32173.50 30589.12 30782.79 3580.21 3791.24 38084.80 34139.48 36090.04 35444.13 36575.94 33672.79 363
PMMVS259.60 33256.40 33469.21 35068.83 37346.58 37673.02 36777.48 37155.07 36249.21 36572.95 36317.43 37580.04 37049.32 36444.33 37080.99 360
testf159.54 33356.11 33669.85 34869.28 37156.61 36980.37 36076.55 37242.58 36845.68 36775.61 35711.26 37884.18 36543.20 36760.44 36368.75 364
APD_test259.54 33356.11 33669.85 34869.28 37156.61 36980.37 36076.55 37242.58 36845.68 36775.61 35711.26 37884.18 36543.20 36760.44 36368.75 364
ANet_high58.88 33554.22 33972.86 34456.50 37956.67 36880.75 35986.00 34873.09 33337.39 37164.63 36822.17 37179.49 37143.51 36623.96 37382.43 359
Gipumacopyleft57.99 33654.91 33867.24 35188.51 32865.59 35452.21 37090.33 32343.58 36742.84 37051.18 37120.29 37385.07 36434.77 37170.45 34551.05 370
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
PMVScopyleft47.18 2252.22 33748.46 34163.48 35245.72 38146.20 37773.41 36678.31 36941.03 37030.06 37365.68 3666.05 38083.43 36730.04 37265.86 35560.80 367
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
test_method50.52 33848.47 34056.66 35452.26 38018.98 38341.51 37281.40 36210.10 37444.59 36975.01 36028.51 36568.16 37253.54 36149.31 36982.83 357
MVEpermissive39.65 2343.39 33938.59 34557.77 35356.52 37848.77 37555.38 36958.64 37929.33 37328.96 37452.65 3704.68 38164.62 37528.11 37333.07 37159.93 368
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
E-PMN43.23 34042.29 34246.03 35665.58 37537.41 37873.51 36564.62 37633.99 37128.47 37547.87 37219.90 37467.91 37322.23 37424.45 37232.77 371
EMVS42.07 34141.12 34344.92 35763.45 37735.56 38073.65 36463.48 37733.05 37226.88 37645.45 37321.27 37267.14 37419.80 37523.02 37432.06 372
tmp_tt35.64 34239.24 34424.84 35814.87 38223.90 38262.71 36851.51 3816.58 37636.66 37262.08 36944.37 35730.34 37852.40 36222.00 37520.27 373
cdsmvs_eth3d_5k22.14 34329.52 3460.00 3620.00 3850.00 3860.00 37395.76 1420.00 3800.00 38194.29 14875.66 1570.00 3810.00 3790.00 3790.00 377
wuyk23d21.27 34420.48 34723.63 35968.59 37436.41 37949.57 3716.85 3839.37 3757.89 3774.46 3794.03 38231.37 37717.47 37616.07 3763.12 374
testmvs8.92 34511.52 3481.12 3611.06 3830.46 38586.02 3350.65 3840.62 3772.74 3789.52 3770.31 3840.45 3802.38 3770.39 3772.46 376
test1238.76 34611.22 3491.39 3600.85 3840.97 38485.76 3380.35 3850.54 3782.45 3798.14 3780.60 3830.48 3792.16 3780.17 3782.71 375
ab-mvs-re7.82 34710.43 3500.00 3620.00 3850.00 3860.00 3730.00 3860.00 3800.00 38193.88 1690.00 3850.00 3810.00 3790.00 3790.00 377
pcd_1.5k_mvsjas6.64 3488.86 3510.00 3620.00 3850.00 3860.00 3730.00 3860.00 3800.00 3810.00 38079.70 1090.00 3810.00 3790.00 3790.00 377
test_blank0.00 3490.00 3520.00 3620.00 3850.00 3860.00 3730.00 3860.00 3800.00 3810.00 3800.00 3850.00 3810.00 3790.00 3790.00 377
uanet_test0.00 3490.00 3520.00 3620.00 3850.00 3860.00 3730.00 3860.00 3800.00 3810.00 3800.00 3850.00 3810.00 3790.00 3790.00 377
DCPMVS0.00 3490.00 3520.00 3620.00 3850.00 3860.00 3730.00 3860.00 3800.00 3810.00 3800.00 3850.00 3810.00 3790.00 3790.00 377
sosnet-low-res0.00 3490.00 3520.00 3620.00 3850.00 3860.00 3730.00 3860.00 3800.00 3810.00 3800.00 3850.00 3810.00 3790.00 3790.00 377
sosnet0.00 3490.00 3520.00 3620.00 3850.00 3860.00 3730.00 3860.00 3800.00 3810.00 3800.00 3850.00 3810.00 3790.00 3790.00 377
uncertanet0.00 3490.00 3520.00 3620.00 3850.00 3860.00 3730.00 3860.00 3800.00 3810.00 3800.00 3850.00 3810.00 3790.00 3790.00 377
Regformer0.00 3490.00 3520.00 3620.00 3850.00 3860.00 3730.00 3860.00 3800.00 3810.00 3800.00 3850.00 3810.00 3790.00 3790.00 377
uanet0.00 3490.00 3520.00 3620.00 3850.00 3860.00 3730.00 3860.00 3800.00 3810.00 3800.00 3850.00 3810.00 3790.00 3790.00 377
FOURS198.86 185.54 6398.29 197.49 589.79 4196.29 15
MSC_two_6792asdad96.52 197.78 5190.86 196.85 6199.61 396.03 199.06 999.07 5
PC_three_145282.47 21197.09 997.07 3892.72 198.04 14692.70 4299.02 1298.86 10
No_MVS96.52 197.78 5190.86 196.85 6199.61 396.03 199.06 999.07 5
test_one_060198.58 1185.83 5797.44 1491.05 1296.78 1398.06 691.45 11
eth-test20.00 385
eth-test0.00 385
ZD-MVS98.15 3486.62 3097.07 4383.63 18694.19 3196.91 4487.57 3199.26 4091.99 6198.44 49
RE-MVS-def93.68 4397.92 4384.57 7396.28 4396.76 7287.46 10593.75 3897.43 1882.94 7492.73 3897.80 7097.88 75
IU-MVS98.77 586.00 4796.84 6381.26 24297.26 795.50 1099.13 399.03 7
OPU-MVS96.21 398.00 4290.85 397.13 1497.08 3692.59 298.94 7392.25 5098.99 1498.84 13
test_241102_TWO97.44 1490.31 2697.62 598.07 491.46 1099.58 895.66 499.12 698.98 9
test_241102_ONE98.77 585.99 4997.44 1490.26 3197.71 197.96 1092.31 499.38 29
9.1494.47 1797.79 4996.08 5497.44 1486.13 13695.10 2497.40 2088.34 2299.22 4293.25 3198.70 32
save fliter97.85 4685.63 6295.21 9896.82 6689.44 48
test_0728_THIRD90.75 1797.04 1098.05 892.09 699.55 1495.64 699.13 399.13 2
test_0728_SECOND95.01 1598.79 286.43 3697.09 1697.49 599.61 395.62 899.08 798.99 8
test072698.78 385.93 5297.19 1197.47 1090.27 2997.64 498.13 191.47 8
GSMVS96.12 140
test_part298.55 1287.22 1696.40 14
sam_mvs171.70 20796.12 140
sam_mvs70.60 220
ambc83.06 32979.99 36263.51 35977.47 36392.86 25974.34 33984.45 34328.74 36495.06 31173.06 29668.89 35290.61 328
MTGPAbinary96.97 48
test_post188.00 3209.81 37669.31 24295.53 29876.65 265
test_post10.29 37570.57 22495.91 285
patchmatchnet-post83.76 34571.53 20896.48 258
GG-mvs-BLEND87.94 27189.73 32077.91 25287.80 32178.23 37080.58 29083.86 34459.88 31595.33 30671.20 30292.22 16790.60 330
MTMP96.16 4960.64 378
gm-plane-assit89.60 32268.00 34677.28 29388.99 30097.57 17679.44 238
test9_res91.91 6598.71 3098.07 64
TEST997.53 5886.49 3494.07 17396.78 6981.61 23592.77 6196.20 7487.71 2899.12 49
test_897.49 6086.30 4294.02 17896.76 7281.86 22892.70 6596.20 7487.63 2999.02 59
agg_prior290.54 8898.68 3598.27 50
agg_prior97.38 6385.92 5496.72 7892.16 7598.97 70
TestCases89.52 23195.01 13877.79 25890.89 31577.41 29076.12 32793.34 18254.08 33897.51 18268.31 32284.27 25793.26 265
test_prior485.96 5194.11 168
test_prior294.12 16787.67 10392.63 6696.39 6986.62 3691.50 7198.67 37
test_prior93.82 5697.29 6784.49 7796.88 5998.87 7798.11 63
旧先验293.36 20571.25 34394.37 2897.13 22186.74 131
新几何293.11 220
新几何193.10 7197.30 6684.35 8495.56 15671.09 34491.26 9996.24 7282.87 7598.86 7979.19 24298.10 6096.07 144
旧先验196.79 7681.81 15095.67 14896.81 5086.69 3597.66 7496.97 113
无先验93.28 21296.26 10473.95 32599.05 5380.56 22496.59 125
原ACMM292.94 227
原ACMM192.01 11797.34 6481.05 17196.81 6778.89 27090.45 10695.92 8682.65 7698.84 8380.68 22298.26 5596.14 138
test22296.55 8481.70 15292.22 24895.01 18968.36 35090.20 11096.14 7980.26 10297.80 7096.05 146
testdata298.75 8778.30 249
segment_acmp87.16 34
testdata90.49 18796.40 8977.89 25495.37 17472.51 33793.63 4196.69 5382.08 8797.65 16983.08 17597.39 7695.94 148
testdata192.15 25087.94 93
test1294.34 4797.13 7086.15 4596.29 10191.04 10185.08 5299.01 6198.13 5997.86 77
plane_prior794.70 15782.74 127
plane_prior694.52 16682.75 12574.23 174
plane_prior596.22 10998.12 13188.15 10989.99 18694.63 193
plane_prior494.86 124
plane_prior382.75 12590.26 3186.91 166
plane_prior295.85 6590.81 15
plane_prior194.59 161
plane_prior82.73 12895.21 9889.66 4589.88 191
n20.00 386
nn0.00 386
door-mid85.49 350
lessismore_v086.04 30588.46 33168.78 34580.59 36473.01 34490.11 28455.39 33196.43 26375.06 28265.06 35792.90 281
LGP-MVS_train91.12 16194.47 16881.49 15896.14 11486.73 12285.45 20295.16 11469.89 23198.10 13387.70 11789.23 20293.77 246
test1196.57 89
door85.33 351
HQP5-MVS81.56 154
HQP-NCC94.17 18094.39 15288.81 6585.43 205
ACMP_Plane94.17 18094.39 15288.81 6585.43 205
BP-MVS87.11 128
HQP4-MVS85.43 20597.96 15294.51 203
HQP3-MVS96.04 12289.77 193
HQP2-MVS73.83 184
NP-MVS94.37 17482.42 13793.98 162
MDTV_nov1_ep13_2view55.91 37387.62 32673.32 33084.59 22470.33 22774.65 28695.50 164
MDTV_nov1_ep1383.56 26191.69 25969.93 34187.75 32391.54 29878.60 27784.86 21988.90 30269.54 23696.03 27870.25 30888.93 208
ACMMP++_ref87.47 231
ACMMP++88.01 225
Test By Simon80.02 104
ITE_SJBPF88.24 26291.88 25077.05 27192.92 25785.54 14980.13 29893.30 18657.29 32596.20 27272.46 29884.71 25391.49 312
DeepMVS_CXcopyleft56.31 35574.23 36751.81 37456.67 38044.85 36648.54 36675.16 35927.87 36658.74 37640.92 36952.22 36758.39 369