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

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

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

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

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




Method Infoallhigh-res
multi-view
indooroutdoorbotani.boulde.bridgedoorexhibi.lectur.living.loungeobserv.old co.statueterrac.
sort bysort bysort bysorted bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort by
MSC_two_6792asdad96.52 197.78 5190.86 196.85 6199.61 396.03 199.06 999.07 5
No_MVS96.52 197.78 5190.86 196.85 6199.61 396.03 199.06 999.07 5
OPU-MVS96.21 398.00 4290.85 397.13 1497.08 3692.59 298.94 7392.25 5098.99 1498.84 13
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
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
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
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
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
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
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
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
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
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
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
test_0728_SECOND95.01 1598.79 286.43 3697.09 1697.49 599.61 395.62 899.08 798.99 8
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
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
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
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
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
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
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
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
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
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
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
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.
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
test1294.34 4797.13 7086.15 4596.29 10191.04 10185.08 5299.01 6198.13 5997.86 77
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
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
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
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
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
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
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
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
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
test_prior93.82 5697.29 6784.49 7796.88 5998.87 7798.11 63
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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.
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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).
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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.
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
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
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
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
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
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
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
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.
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.
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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.
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
lessismore_v086.04 30588.46 33168.78 34580.59 36473.01 34490.11 28455.39 33196.43 26375.06 28265.06 35792.90 281
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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_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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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)
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)
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
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
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
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
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
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
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
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
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
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
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
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
PC_three_145282.47 21197.09 997.07 3892.72 198.04 14692.70 4299.02 1298.86 10
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
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
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
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
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
test_prior485.96 5194.11 168
test_prior294.12 16787.67 10392.63 6696.39 6986.62 3691.50 7198.67 37
旧先验293.36 20571.25 34394.37 2897.13 22186.74 131
新几何293.11 220
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
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
testdata192.15 25087.94 93
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
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