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

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

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

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

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




Method Infoallhigh-res
multi-view
indooroutdoorbotani.boulde.bridgedoorexhibi.lectur.living.loungeobserv.old co.statueterrac.
sort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysorted bysort bysort by
LTVRE_ROB86.10 193.04 393.44 291.82 2393.73 6685.72 3396.79 195.51 888.86 1495.63 896.99 884.81 7093.16 13991.10 197.53 7396.58 29
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
MP-MVS-pluss90.81 2991.08 3689.99 5195.97 1479.88 7488.13 9494.51 2175.79 14292.94 4494.96 4488.36 2995.01 6790.70 298.40 2095.09 62
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
ACMMP_NAP90.65 3191.07 3889.42 6095.93 1679.54 7989.95 5993.68 5677.65 11891.97 6594.89 4688.38 2895.45 4989.27 397.87 5293.27 128
ZNCC-MVS91.26 2391.34 2991.01 3595.73 2183.05 5492.18 2894.22 2780.14 8991.29 7693.97 9087.93 4095.87 1888.65 497.96 4794.12 95
zzz-MVS91.27 2291.26 3391.29 2996.59 486.29 1988.94 8191.81 11984.07 4092.00 6394.40 6886.63 5495.28 5788.59 598.31 2492.30 169
MTAPA91.52 1691.60 2091.29 2996.59 486.29 1992.02 3091.81 11984.07 4092.00 6394.40 6886.63 5495.28 5788.59 598.31 2492.30 169
HPM-MVScopyleft92.13 992.20 1191.91 1795.58 2684.67 4393.51 894.85 1682.88 5791.77 6893.94 9790.55 1395.73 3088.50 798.23 2995.33 53
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
MSP-MVS89.08 6588.16 7791.83 2195.76 1886.14 2492.75 1793.90 4678.43 11289.16 12092.25 14372.03 21596.36 288.21 890.93 25492.98 139
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
HPM-MVS_fast92.50 592.54 692.37 695.93 1685.81 3292.99 1394.23 2685.21 3492.51 5495.13 4190.65 1095.34 5488.06 998.15 3595.95 40
SMA-MVScopyleft90.31 3890.48 4989.83 5295.31 3179.52 8090.98 4293.24 7675.37 14992.84 4895.28 3685.58 6696.09 787.92 1097.76 5693.88 103
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
HFP-MVS91.30 2191.39 2591.02 3395.43 2984.66 4492.58 2293.29 7381.99 6691.47 7193.96 9388.35 3095.56 3787.74 1197.74 5892.85 143
ACMMPR91.49 1791.35 2891.92 1695.74 2085.88 2992.58 2293.25 7581.99 6691.40 7394.17 8187.51 4495.87 1887.74 1197.76 5693.99 98
anonymousdsp89.73 5388.88 7092.27 989.82 17586.67 1790.51 4890.20 16769.87 21995.06 1196.14 2184.28 7593.07 14487.68 1396.34 11297.09 19
TSAR-MVS + MP.88.14 7587.82 8089.09 6795.72 2276.74 11592.49 2591.19 13667.85 24086.63 16694.84 4879.58 13695.96 1387.62 1494.50 17994.56 76
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
SteuartSystems-ACMMP91.16 2691.36 2690.55 4293.91 6180.97 6891.49 3893.48 6382.82 5892.60 5393.97 9088.19 3396.29 487.61 1598.20 3294.39 85
Skip Steuart: Steuart Systems R&D Blog.
region2R91.44 2091.30 3291.87 1995.75 1985.90 2892.63 2193.30 7281.91 6890.88 8494.21 7787.75 4195.87 1887.60 1697.71 6093.83 105
APDe-MVS91.22 2491.92 1389.14 6592.97 8378.04 9292.84 1694.14 3583.33 5193.90 2595.73 2688.77 2696.41 187.60 1697.98 4492.98 139
abl_693.02 493.16 492.60 494.73 4488.99 793.26 1294.19 3089.11 1294.43 1695.27 3791.86 395.09 6487.54 1898.02 4093.71 113
MSC_two_6792asdad88.81 7091.55 13277.99 9391.01 14096.05 887.45 1998.17 3392.40 164
No_MVS88.81 7091.55 13277.99 9391.01 14096.05 887.45 1998.17 3392.40 164
DVP-MVS++90.07 4291.09 3587.00 9991.55 13272.64 14296.19 294.10 3885.33 3293.49 3894.64 5781.12 12095.88 1687.41 2195.94 13092.48 160
test_0728_THIRD85.33 3293.75 3194.65 5487.44 4595.78 2787.41 2198.21 3092.98 139
XVS91.54 1591.36 2692.08 1095.64 2486.25 2192.64 1993.33 6785.07 3589.99 9794.03 8786.57 5695.80 2487.35 2397.62 6494.20 90
X-MVStestdata85.04 12282.70 16692.08 1095.64 2486.25 2192.64 1993.33 6785.07 3589.99 9716.05 37286.57 5695.80 2487.35 2397.62 6494.20 90
ACMMPcopyleft91.91 1291.87 1792.03 1395.53 2785.91 2793.35 1194.16 3182.52 6192.39 5794.14 8389.15 2395.62 3487.35 2398.24 2894.56 76
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
CP-MVS91.67 1491.58 2191.96 1495.29 3287.62 1293.38 993.36 6583.16 5391.06 7994.00 8988.26 3295.71 3187.28 2698.39 2192.55 157
mPP-MVS91.69 1391.47 2492.37 696.04 1388.48 1092.72 1892.60 9983.09 5491.54 7094.25 7687.67 4395.51 4487.21 2798.11 3693.12 134
SR-MVS-dyc-post92.41 692.41 792.39 594.13 5588.95 892.87 1494.16 3188.75 1693.79 2994.43 6488.83 2495.51 4487.16 2897.60 6692.73 148
RE-MVS-def92.61 594.13 5588.95 892.87 1494.16 3188.75 1693.79 2994.43 6490.64 1187.16 2897.60 6692.73 148
test117292.40 792.41 792.37 694.68 4589.04 691.98 3193.62 5790.14 1193.63 3694.16 8288.83 2495.51 4487.11 3097.54 7292.54 158
GST-MVS90.96 2891.01 3990.82 3895.45 2882.73 5791.75 3693.74 5280.98 7991.38 7493.80 10087.20 4895.80 2487.10 3197.69 6193.93 101
SR-MVS92.23 892.34 991.91 1794.89 3987.85 1192.51 2493.87 4988.20 2193.24 4194.02 8890.15 1795.67 3386.82 3297.34 7992.19 177
APD-MVS_3200maxsize92.05 1092.24 1091.48 2493.02 8185.17 3692.47 2695.05 1587.65 2493.21 4294.39 7090.09 1895.08 6586.67 3397.60 6694.18 92
DVP-MVScopyleft90.06 4391.32 3086.29 11394.16 5372.56 14690.54 4691.01 14083.61 4793.75 3194.65 5489.76 1995.78 2786.42 3497.97 4590.55 220
Zhenlong Yuan, Jinguo Luo, Fei Shen, Zhaoxin Li, Cong Liu, Tianlu Mao, Zhaoqi Wang: DVP-MVS: Synergize Depth-Edge and Visibility Prior for Multi-View Stereo. AAAI2025
test_0728_SECOND86.79 10394.25 4972.45 15090.54 4694.10 3895.88 1686.42 3497.97 4592.02 181
PGM-MVS91.20 2590.95 4291.93 1595.67 2385.85 3090.00 5693.90 4680.32 8691.74 6994.41 6788.17 3495.98 1186.37 3697.99 4293.96 100
MP-MVScopyleft91.14 2790.91 4391.83 2196.18 1186.88 1692.20 2793.03 8582.59 6088.52 13194.37 7186.74 5395.41 5186.32 3798.21 3093.19 132
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
MVSFormer82.23 17681.57 18584.19 15985.54 25469.26 18191.98 3190.08 17071.54 19976.23 30185.07 28458.69 28394.27 8786.26 3888.77 27989.03 247
test_djsdf89.62 5489.01 6691.45 2592.36 9882.98 5591.98 3190.08 17071.54 19994.28 2196.54 1381.57 11494.27 8786.26 3896.49 10697.09 19
v7n90.13 4090.96 4187.65 9391.95 11371.06 16789.99 5893.05 8286.53 2894.29 1996.27 1782.69 9194.08 10086.25 4097.63 6397.82 8
SD-MVS88.96 6789.88 5386.22 11691.63 12577.07 11189.82 6293.77 5178.90 10592.88 4592.29 14186.11 6290.22 22586.24 4197.24 8291.36 200
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
HPM-MVS++copyleft88.93 6888.45 7590.38 4594.92 3785.85 3089.70 6391.27 13378.20 11486.69 16592.28 14280.36 13095.06 6686.17 4296.49 10690.22 225
TDRefinement93.52 293.39 393.88 195.94 1590.26 395.70 496.46 290.58 892.86 4796.29 1688.16 3594.17 9686.07 4398.48 1897.22 17
SED-MVS90.46 3791.64 1986.93 10094.18 5072.65 14090.47 5093.69 5483.77 4494.11 2394.27 7290.28 1595.84 2286.03 4497.92 4892.29 171
test_241102_TWO93.71 5383.77 4493.49 3894.27 7289.27 2295.84 2286.03 4497.82 5392.04 180
UA-Net91.49 1791.53 2291.39 2694.98 3682.95 5693.52 792.79 9488.22 2088.53 13097.64 283.45 8494.55 8486.02 4698.60 1396.67 26
IU-MVS94.18 5072.64 14290.82 14556.98 31589.67 10885.78 4797.92 4893.28 127
xxxxxxxxxxxxxcwj89.04 6689.13 6488.79 7293.75 6477.44 10386.31 12595.27 1270.80 20792.28 5893.80 10086.89 5194.64 7885.52 4897.51 7494.30 88
SF-MVS90.27 3990.80 4588.68 7692.86 8777.09 11091.19 4195.74 581.38 7492.28 5893.80 10086.89 5194.64 7885.52 4897.51 7494.30 88
LPG-MVS_test91.47 1991.68 1890.82 3894.75 4281.69 6190.00 5694.27 2382.35 6393.67 3494.82 4991.18 595.52 4285.36 5098.73 795.23 58
LGP-MVS_train90.82 3894.75 4281.69 6194.27 2382.35 6393.67 3494.82 4991.18 595.52 4285.36 5098.73 795.23 58
LCM-MVSNet95.70 196.40 193.61 298.67 185.39 3495.54 597.36 196.97 199.04 199.05 196.61 195.92 1485.07 5299.27 199.54 1
OurMVSNet-221017-090.01 4689.74 5590.83 3793.16 7980.37 7191.91 3493.11 7981.10 7795.32 1097.24 572.94 20394.85 7285.07 5297.78 5597.26 15
ACMM79.39 990.65 3190.99 4089.63 5695.03 3583.53 4989.62 6893.35 6679.20 10193.83 2893.60 10790.81 892.96 14685.02 5498.45 1992.41 163
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
#test#90.49 3690.31 5191.02 3395.43 2984.66 4490.65 4493.29 7377.00 12691.47 7193.96 9388.35 3095.56 3784.88 5597.74 5892.85 143
3Dnovator+83.92 289.97 4989.66 5690.92 3691.27 14181.66 6491.25 3994.13 3688.89 1388.83 12594.26 7577.55 15295.86 2184.88 5595.87 13495.24 57
OPM-MVS89.80 5189.97 5289.27 6294.76 4179.86 7586.76 11792.78 9578.78 10792.51 5493.64 10688.13 3693.84 11084.83 5797.55 6994.10 96
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
CNVR-MVS87.81 8387.68 8288.21 8692.87 8577.30 10885.25 13891.23 13477.31 12387.07 15591.47 16282.94 8994.71 7584.67 5896.27 11692.62 155
XVG-OURS-SEG-HR89.59 5589.37 6190.28 4794.47 4685.95 2686.84 11393.91 4580.07 9086.75 16293.26 11093.64 290.93 20384.60 5990.75 25993.97 99
DPE-MVScopyleft90.53 3591.08 3688.88 6893.38 7378.65 8889.15 7894.05 4084.68 3893.90 2594.11 8588.13 3696.30 384.51 6097.81 5491.70 192
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
RRT_MVS83.25 16381.08 19189.74 5380.55 31479.32 8186.41 12486.69 22672.33 19087.00 15791.08 17144.98 34595.55 4084.47 6196.24 11894.36 86
mvs_tets89.78 5289.27 6391.30 2893.51 6984.79 4189.89 6190.63 15070.00 21894.55 1596.67 1187.94 3993.59 12184.27 6295.97 12795.52 48
DeepC-MVS82.31 489.15 6389.08 6589.37 6193.64 6879.07 8388.54 9094.20 2873.53 16789.71 10694.82 4985.09 6795.77 2984.17 6398.03 3993.26 129
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
jajsoiax89.41 5888.81 7291.19 3293.38 7384.72 4289.70 6390.29 16469.27 22294.39 1796.38 1586.02 6493.52 12583.96 6495.92 13295.34 52
v1086.54 9587.10 9084.84 14288.16 20463.28 22986.64 12092.20 10775.42 14892.81 5094.50 6074.05 18894.06 10183.88 6596.28 11497.17 18
XVG-OURS89.18 6288.83 7190.23 4894.28 4886.11 2585.91 12893.60 6080.16 8889.13 12193.44 10883.82 7990.98 20183.86 6695.30 15493.60 120
Regformer-486.41 9785.71 11588.52 7784.27 27077.57 10184.07 15688.00 20582.82 5889.84 10385.48 27282.06 10392.77 15283.83 6791.04 24895.22 60
9.1489.29 6291.84 12188.80 8595.32 1175.14 15191.07 7892.89 12187.27 4693.78 11283.69 6897.55 69
Regformer-286.74 9386.08 10788.73 7384.18 27479.20 8283.52 17589.33 18483.33 5189.92 10185.07 28483.23 8793.16 13983.39 6992.72 22193.83 105
ETH3D-3000-0.188.85 6988.96 6988.52 7791.94 11577.27 10988.71 8795.26 1376.08 13390.66 8792.69 12884.48 7393.83 11183.38 7097.48 7694.47 80
ACMH76.49 1489.34 6091.14 3483.96 16492.50 9570.36 17289.55 6993.84 5081.89 6994.70 1395.44 3490.69 988.31 26183.33 7198.30 2693.20 131
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
v886.22 10286.83 9784.36 15387.82 20962.35 24486.42 12391.33 13176.78 12892.73 5194.48 6273.41 19793.72 11483.10 7295.41 14797.01 21
PS-MVSNAJss88.31 7387.90 7989.56 5993.31 7577.96 9587.94 9791.97 11370.73 20994.19 2296.67 1176.94 16194.57 8283.07 7396.28 11496.15 32
CPTT-MVS89.39 5988.98 6890.63 4195.09 3486.95 1592.09 2992.30 10579.74 9287.50 14792.38 13681.42 11693.28 13483.07 7397.24 8291.67 193
SixPastTwentyTwo87.20 8787.45 8686.45 10992.52 9469.19 18487.84 9988.05 20381.66 7194.64 1496.53 1465.94 24394.75 7483.02 7596.83 9495.41 50
ACMP79.16 1090.54 3490.60 4890.35 4694.36 4780.98 6789.16 7794.05 4079.03 10492.87 4693.74 10490.60 1295.21 6182.87 7698.76 494.87 65
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
v124084.30 13984.51 14083.65 17187.65 21461.26 25382.85 19691.54 12467.94 23890.68 8690.65 18971.71 21793.64 11682.84 7794.78 17296.07 35
XVG-ACMP-BASELINE89.98 4789.84 5490.41 4494.91 3884.50 4689.49 7393.98 4279.68 9392.09 6193.89 9883.80 8093.10 14382.67 7898.04 3793.64 118
DROMVSNet88.01 7788.32 7687.09 9889.28 18172.03 15690.31 5296.31 380.88 8085.12 19389.67 20884.47 7495.46 4882.56 7996.26 11793.77 111
CS-MVS88.03 7687.67 8389.10 6689.60 17677.89 9690.49 4994.78 1879.37 9984.25 21689.32 21283.84 7894.49 8582.47 8094.93 16794.93 64
v119284.57 13184.69 13584.21 15787.75 21162.88 23483.02 19291.43 12769.08 22589.98 9990.89 18072.70 20793.62 12082.41 8194.97 16696.13 33
Regformer-186.00 10585.50 11987.49 9484.18 27476.90 11383.52 17587.94 20782.18 6589.19 11985.07 28482.28 9991.89 17782.40 8292.72 22193.69 114
v192192084.23 14384.37 14483.79 16787.64 21561.71 24882.91 19591.20 13567.94 23890.06 9490.34 19472.04 21493.59 12182.32 8394.91 16896.07 35
APD-MVScopyleft89.54 5689.63 5789.26 6392.57 9281.34 6690.19 5493.08 8180.87 8191.13 7793.19 11186.22 6195.97 1282.23 8497.18 8490.45 222
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
EI-MVSNet-Vis-set85.12 11984.53 13986.88 10184.01 27772.76 13983.91 16485.18 24680.44 8388.75 12685.49 27180.08 13291.92 17582.02 8590.85 25795.97 38
ZD-MVS92.22 10580.48 7091.85 11671.22 20490.38 8992.98 11686.06 6396.11 681.99 8696.75 97
Regformer-385.06 12184.67 13686.22 11684.27 27073.43 13484.07 15685.26 24480.77 8288.62 12985.48 27280.56 12890.39 22181.99 8691.04 24894.85 69
EI-MVSNet-UG-set85.04 12284.44 14186.85 10283.87 28072.52 14883.82 16685.15 24780.27 8788.75 12685.45 27579.95 13491.90 17681.92 8890.80 25896.13 33
v14419284.24 14284.41 14283.71 17087.59 21661.57 24982.95 19491.03 13967.82 24189.80 10490.49 19273.28 20093.51 12681.88 8994.89 17096.04 37
v114484.54 13484.72 13384.00 16287.67 21362.55 24082.97 19390.93 14370.32 21489.80 10490.99 17573.50 19493.48 12781.69 9094.65 17795.97 38
ETH3D cwj APD-0.1687.83 8287.62 8488.47 7991.21 14278.20 9087.26 10694.54 2072.05 19588.89 12292.31 14083.86 7794.24 9081.59 9196.87 9192.97 142
testtj89.51 5789.48 6089.59 5892.26 10280.80 6990.14 5593.54 6183.37 5090.57 8892.55 13384.99 6896.15 581.26 9296.61 10191.83 188
train_agg85.98 10785.28 12288.07 8892.34 9979.70 7783.94 16190.32 15865.79 25684.49 20590.97 17681.93 10793.63 11781.21 9396.54 10490.88 209
NCCC87.36 8586.87 9688.83 6992.32 10178.84 8686.58 12191.09 13878.77 10884.85 19990.89 18080.85 12395.29 5581.14 9495.32 15192.34 167
agg_prior185.72 11085.20 12487.28 9791.58 12977.69 9983.69 17190.30 16166.29 25284.32 20991.07 17382.13 10193.18 13781.02 9596.36 11190.98 205
v2v48284.09 14584.24 14683.62 17287.13 22461.40 25082.71 19989.71 17672.19 19489.55 11491.41 16370.70 22293.20 13681.02 9593.76 19496.25 31
WR-MVS_H89.91 5091.31 3185.71 12996.32 1062.39 24289.54 7193.31 7090.21 1095.57 995.66 2981.42 11695.90 1580.94 9798.80 398.84 5
LS3D90.60 3390.34 5091.38 2789.03 18684.23 4793.58 694.68 1990.65 790.33 9193.95 9684.50 7295.37 5380.87 9895.50 14694.53 79
test9_res80.83 9996.45 10890.57 218
HQP_MVS87.75 8487.43 8788.70 7593.45 7076.42 11989.45 7493.61 5879.44 9786.55 16792.95 11974.84 17895.22 5980.78 10095.83 13594.46 81
plane_prior593.61 5895.22 5980.78 10095.83 13594.46 81
PHI-MVS86.38 9885.81 11288.08 8788.44 19877.34 10689.35 7693.05 8273.15 17884.76 20087.70 23878.87 14094.18 9480.67 10296.29 11392.73 148
K. test v385.14 11884.73 13186.37 11091.13 14769.63 17785.45 13676.68 30284.06 4292.44 5696.99 862.03 26294.65 7780.58 10393.24 20694.83 71
Vis-MVSNetpermissive86.86 9086.58 9987.72 9192.09 10977.43 10587.35 10492.09 10978.87 10684.27 21494.05 8678.35 14493.65 11580.54 10491.58 24292.08 179
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
test_part187.15 8887.82 8085.15 13888.88 19063.04 23287.98 9594.85 1682.52 6193.61 3795.73 2667.51 23495.71 3180.48 10598.83 296.69 25
V4283.47 16083.37 15783.75 16983.16 28663.33 22881.31 22890.23 16669.51 22190.91 8390.81 18374.16 18692.29 16580.06 10690.22 26595.62 46
MVS_Test82.47 17383.22 15880.22 23382.62 29157.75 29182.54 20591.96 11471.16 20582.89 23392.52 13577.41 15390.50 21880.04 10787.84 29292.40 164
COLMAP_ROBcopyleft83.01 391.97 1191.95 1292.04 1293.68 6786.15 2393.37 1095.10 1490.28 992.11 6095.03 4389.75 2194.93 6979.95 10898.27 2795.04 63
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
test_040288.65 7089.58 5985.88 12592.55 9372.22 15484.01 15989.44 18288.63 1894.38 1895.77 2586.38 6093.59 12179.84 10995.21 15591.82 189
EGC-MVSNET74.79 26769.99 30189.19 6494.89 3987.00 1491.89 3586.28 2301.09 3732.23 37595.98 2381.87 11189.48 24279.76 11095.96 12891.10 202
nrg03087.85 8188.49 7485.91 12390.07 17169.73 17587.86 9894.20 2874.04 16192.70 5294.66 5385.88 6591.50 18479.72 11197.32 8096.50 30
agg_prior279.68 11296.16 12090.22 225
DeepPCF-MVS81.24 587.28 8686.21 10590.49 4391.48 13684.90 3983.41 18092.38 10470.25 21589.35 11890.68 18782.85 9094.57 8279.55 11395.95 12992.00 182
test_prior386.31 9986.31 10286.32 11190.59 16071.99 15783.37 18192.85 9175.43 14684.58 20391.57 15881.92 10994.17 9679.54 11496.97 8892.80 145
test_prior283.37 18175.43 14684.58 20391.57 15881.92 10979.54 11496.97 88
lessismore_v085.95 12291.10 14870.99 16870.91 34191.79 6794.42 6661.76 26392.93 14879.52 11693.03 21293.93 101
PS-CasMVS90.06 4391.92 1384.47 15096.56 758.83 28489.04 7992.74 9691.40 596.12 496.06 2287.23 4795.57 3679.42 11798.74 699.00 2
tttt051781.07 19179.58 21285.52 13288.99 18866.45 20487.03 11175.51 31073.76 16588.32 13790.20 19837.96 36194.16 9979.36 11895.13 15895.93 41
DTE-MVSNet89.98 4791.91 1584.21 15796.51 857.84 28988.93 8292.84 9391.92 396.16 396.23 1886.95 5095.99 1079.05 11998.57 1598.80 6
CP-MVSNet89.27 6190.91 4384.37 15196.34 958.61 28688.66 8992.06 11090.78 695.67 795.17 4081.80 11295.54 4179.00 12098.69 1098.95 4
ambc82.98 18490.55 16264.86 21488.20 9289.15 18689.40 11793.96 9371.67 21891.38 19278.83 12196.55 10392.71 151
PEN-MVS90.03 4591.88 1684.48 14996.57 658.88 28188.95 8093.19 7791.62 496.01 696.16 2087.02 4995.60 3578.69 12298.72 998.97 3
bset_n11_16_dypcd79.19 21777.97 22982.86 19085.81 25166.85 20175.02 31079.31 28766.07 25383.50 22683.37 30555.04 30692.10 17078.63 12394.99 16589.63 232
baseline85.20 11785.93 10983.02 18386.30 24262.37 24384.55 14893.96 4374.48 15887.12 15192.03 14682.30 9791.94 17478.39 12494.21 18594.74 72
DeepC-MVS_fast80.27 886.23 10185.65 11787.96 9091.30 13976.92 11287.19 10791.99 11270.56 21084.96 19590.69 18680.01 13395.14 6278.37 12595.78 13991.82 189
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
ACMH+77.89 1190.73 3091.50 2388.44 8193.00 8276.26 12189.65 6795.55 787.72 2393.89 2794.94 4591.62 493.44 12978.35 12698.76 495.61 47
MCST-MVS84.36 13683.93 15185.63 13091.59 12671.58 16483.52 17592.13 10861.82 28383.96 21889.75 20779.93 13593.46 12878.33 12794.34 18391.87 187
3Dnovator80.37 784.80 12784.71 13485.06 14086.36 24074.71 12788.77 8690.00 17275.65 14484.96 19593.17 11274.06 18791.19 19578.28 12891.09 24689.29 241
h-mvs3384.25 14182.76 16588.72 7491.82 12382.60 5884.00 16084.98 25371.27 20186.70 16390.55 19163.04 25893.92 10678.26 12994.20 18689.63 232
hse-mvs283.47 16081.81 18088.47 7991.03 14982.27 5982.61 20083.69 25971.27 20186.70 16386.05 26463.04 25892.41 15978.26 12993.62 20190.71 213
CS-MVS-test85.00 12485.28 12284.17 16087.84 20866.12 20687.30 10595.67 677.63 12080.02 27485.85 26881.34 11895.41 5178.18 13193.71 19790.99 204
c3_l81.64 18581.59 18481.79 21080.86 30759.15 27878.61 26890.18 16868.36 23187.20 14987.11 25069.39 22491.62 18278.16 13294.43 18294.60 75
IterMVS-LS84.73 12884.98 12783.96 16487.35 21963.66 22483.25 18589.88 17476.06 13489.62 11092.37 13973.40 19992.52 15778.16 13294.77 17495.69 43
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
EI-MVSNet82.61 17082.42 17383.20 18083.25 28463.66 22483.50 17885.07 24876.06 13486.55 16785.10 28173.41 19790.25 22278.15 13490.67 26195.68 44
GeoE85.45 11485.81 11284.37 15190.08 16967.07 19785.86 13191.39 13072.33 19087.59 14590.25 19784.85 6992.37 16178.00 13591.94 23693.66 115
diffmvs80.40 20480.48 19980.17 23479.02 32960.04 26777.54 28290.28 16566.65 25082.40 23887.33 24673.50 19487.35 26977.98 13689.62 27093.13 133
OMC-MVS88.19 7487.52 8590.19 4991.94 11581.68 6387.49 10393.17 7876.02 13688.64 12891.22 16684.24 7693.37 13277.97 13797.03 8795.52 48
casdiffmvs85.21 11685.85 11183.31 17886.17 24762.77 23683.03 19193.93 4474.69 15588.21 13892.68 12982.29 9891.89 17777.87 13893.75 19695.27 56
DP-MVS88.60 7189.01 6687.36 9691.30 13977.50 10287.55 10192.97 8887.95 2289.62 11092.87 12284.56 7193.89 10777.65 13996.62 10090.70 214
RRT_test8_iter0578.08 23177.52 23279.75 23980.84 30852.54 32780.61 23888.96 18867.77 24284.62 20289.29 21333.89 36692.10 17077.59 14094.15 18794.62 73
PMVScopyleft80.48 690.08 4190.66 4788.34 8496.71 392.97 190.31 5289.57 18088.51 1990.11 9395.12 4290.98 788.92 25177.55 14197.07 8683.13 316
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
MSLP-MVS++85.00 12486.03 10881.90 20491.84 12171.56 16586.75 11893.02 8675.95 13987.12 15189.39 21077.98 14689.40 24777.46 14294.78 17284.75 293
IterMVS-SCA-FT80.64 19979.41 21384.34 15483.93 27869.66 17676.28 29981.09 27772.43 18586.47 17390.19 19960.46 26893.15 14177.45 14386.39 30490.22 225
CDPH-MVS86.17 10485.54 11888.05 8992.25 10375.45 12483.85 16592.01 11165.91 25586.19 17491.75 15683.77 8194.98 6877.43 14496.71 9893.73 112
BP-MVS77.30 145
HQP-MVS84.61 13084.06 14886.27 11491.19 14370.66 16984.77 14292.68 9773.30 17380.55 26790.17 20172.10 21194.61 8077.30 14594.47 18093.56 122
MVS_111021_LR84.28 14083.76 15385.83 12789.23 18383.07 5380.99 23483.56 26172.71 18386.07 17889.07 21981.75 11386.19 28777.11 14793.36 20288.24 253
CANet83.79 15382.85 16486.63 10586.17 24772.21 15583.76 16991.43 12777.24 12474.39 31787.45 24375.36 17395.42 5077.03 14892.83 21792.25 175
Anonymous2023121188.40 7289.62 5884.73 14590.46 16365.27 21188.86 8393.02 8687.15 2593.05 4397.10 682.28 9992.02 17376.70 14997.99 4296.88 23
MVS_111021_HR84.63 12984.34 14585.49 13490.18 16875.86 12379.23 26087.13 21773.35 17085.56 18889.34 21183.60 8390.50 21876.64 15094.05 19090.09 230
RPSCF88.00 7886.93 9591.22 3190.08 16989.30 589.68 6591.11 13779.26 10089.68 10794.81 5282.44 9487.74 26576.54 15188.74 28196.61 28
DIV-MVS_self_test80.43 20280.23 20281.02 22079.99 31759.25 27577.07 28887.02 22267.38 24386.19 17489.22 21463.09 25690.16 22776.32 15295.80 13793.66 115
cl____80.42 20380.23 20281.02 22079.99 31759.25 27577.07 28887.02 22267.37 24486.18 17689.21 21563.08 25790.16 22776.31 15395.80 13793.65 117
AUN-MVS81.18 19078.78 21888.39 8290.93 15182.14 6082.51 20683.67 26064.69 27080.29 27085.91 26751.07 31592.38 16076.29 15493.63 20090.65 217
Gipumacopyleft84.44 13586.33 10178.78 25184.20 27373.57 13389.55 6990.44 15484.24 3984.38 20794.89 4676.35 17080.40 32576.14 15596.80 9682.36 324
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
miper_ehance_all_eth80.34 20680.04 20981.24 21679.82 31958.95 28077.66 27989.66 17765.75 25985.99 18285.11 28068.29 23191.42 18976.03 15692.03 23293.33 125
alignmvs83.94 15183.98 15083.80 16687.80 21067.88 19384.54 15091.42 12973.27 17688.41 13487.96 23372.33 21090.83 20876.02 15794.11 18892.69 152
ETH3 D test640085.09 12084.87 12985.75 12890.80 15569.34 17985.90 12993.31 7065.43 26286.11 17789.95 20380.92 12294.86 7175.90 15895.57 14493.05 136
PC_three_145258.96 30190.06 9491.33 16480.66 12693.03 14575.78 15995.94 13092.48 160
canonicalmvs85.50 11286.14 10683.58 17387.97 20567.13 19687.55 10194.32 2273.44 16988.47 13287.54 24186.45 5891.06 20075.76 16093.76 19492.54 158
CSCG86.26 10086.47 10085.60 13190.87 15374.26 13087.98 9591.85 11680.35 8589.54 11688.01 23279.09 13892.13 16775.51 16195.06 16290.41 223
thisisatest053079.07 21877.33 23684.26 15687.13 22464.58 21683.66 17375.95 30568.86 22885.22 19287.36 24538.10 35993.57 12475.47 16294.28 18494.62 73
TSAR-MVS + GP.83.95 15082.69 16787.72 9189.27 18281.45 6583.72 17081.58 27574.73 15485.66 18586.06 26372.56 20992.69 15475.44 16395.21 15589.01 249
cl2278.97 21978.21 22781.24 21677.74 33359.01 27977.46 28587.13 21765.79 25684.32 20985.10 28158.96 28290.88 20775.36 16492.03 23293.84 104
eth_miper_zixun_eth80.84 19580.22 20482.71 19281.41 29960.98 25977.81 27790.14 16967.31 24586.95 15987.24 24764.26 24892.31 16375.23 16591.61 24094.85 69
v14882.31 17482.48 17281.81 20985.59 25359.66 27181.47 22686.02 23472.85 18188.05 13990.65 18970.73 22190.91 20575.15 16691.79 23794.87 65
FC-MVSNet-test85.93 10887.05 9282.58 19592.25 10356.44 30085.75 13293.09 8077.33 12291.94 6694.65 5474.78 18093.41 13175.11 16798.58 1497.88 7
UniMVSNet (Re)86.87 8986.98 9486.55 10793.11 8068.48 18883.80 16892.87 9080.37 8489.61 11291.81 15477.72 14994.18 9475.00 16898.53 1696.99 22
OPU-MVS88.27 8591.89 11777.83 9790.47 5091.22 16681.12 12094.68 7674.48 16995.35 14992.29 171
DELS-MVS81.44 18781.25 18782.03 20284.27 27062.87 23576.47 29792.49 10170.97 20681.64 25483.83 29775.03 17592.70 15374.29 17092.22 23090.51 221
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
Effi-MVS+83.90 15284.01 14983.57 17487.22 22265.61 21086.55 12292.40 10278.64 11081.34 25884.18 29583.65 8292.93 14874.22 17187.87 29192.17 178
UniMVSNet_NR-MVSNet86.84 9187.06 9186.17 12092.86 8767.02 19882.55 20491.56 12383.08 5590.92 8191.82 15378.25 14593.99 10274.16 17298.35 2297.49 13
DU-MVS86.80 9286.99 9386.21 11893.24 7767.02 19883.16 18992.21 10681.73 7090.92 8191.97 14777.20 15593.99 10274.16 17298.35 2297.61 10
LF4IMVS82.75 16981.93 17985.19 13682.08 29280.15 7385.53 13588.76 19168.01 23585.58 18787.75 23771.80 21686.85 27674.02 17493.87 19388.58 252
FIs85.35 11586.27 10382.60 19491.86 11857.31 29385.10 14093.05 8275.83 14191.02 8093.97 9073.57 19392.91 15073.97 17598.02 4097.58 12
IS-MVSNet86.66 9486.82 9886.17 12092.05 11166.87 20091.21 4088.64 19386.30 3089.60 11392.59 13069.22 22694.91 7073.89 17697.89 5196.72 24
EU-MVSNet75.12 26174.43 26377.18 27683.11 28859.48 27385.71 13482.43 26839.76 36785.64 18688.76 22244.71 34787.88 26473.86 17785.88 30884.16 299
ETV-MVS84.31 13883.91 15285.52 13288.58 19470.40 17184.50 15293.37 6478.76 10984.07 21778.72 34280.39 12995.13 6373.82 17892.98 21491.04 203
Anonymous2024052180.18 21181.25 18776.95 27883.15 28760.84 26182.46 20785.99 23568.76 22986.78 16093.73 10559.13 28077.44 33273.71 17997.55 6992.56 156
MVSTER77.09 24175.70 25281.25 21475.27 35361.08 25577.49 28485.07 24860.78 29386.55 16788.68 22443.14 35190.25 22273.69 18090.67 26192.42 162
ITE_SJBPF90.11 5090.72 15784.97 3890.30 16181.56 7290.02 9691.20 16882.40 9590.81 20973.58 18194.66 17694.56 76
RPMNet78.88 22078.28 22680.68 22779.58 32062.64 23882.58 20294.16 3174.80 15375.72 30792.59 13048.69 32195.56 3773.48 18282.91 33183.85 303
EG-PatchMatch MVS84.08 14684.11 14783.98 16392.22 10572.61 14582.20 21887.02 22272.63 18488.86 12391.02 17478.52 14191.11 19873.41 18391.09 24688.21 254
miper_lstm_enhance76.45 25176.10 24877.51 27476.72 34160.97 26064.69 34985.04 25063.98 27283.20 22988.22 22956.67 29578.79 33073.22 18493.12 20992.78 147
xiu_mvs_v1_base_debu80.84 19580.14 20682.93 18688.31 19971.73 16079.53 25187.17 21465.43 26279.59 27682.73 31376.94 16190.14 23073.22 18488.33 28386.90 272
xiu_mvs_v1_base80.84 19580.14 20682.93 18688.31 19971.73 16079.53 25187.17 21465.43 26279.59 27682.73 31376.94 16190.14 23073.22 18488.33 28386.90 272
xiu_mvs_v1_base_debi80.84 19580.14 20682.93 18688.31 19971.73 16079.53 25187.17 21465.43 26279.59 27682.73 31376.94 16190.14 23073.22 18488.33 28386.90 272
TranMVSNet+NR-MVSNet87.86 8088.76 7385.18 13794.02 5864.13 22184.38 15391.29 13284.88 3792.06 6293.84 9986.45 5893.73 11373.22 18498.66 1197.69 9
TAPA-MVS77.73 1285.71 11184.83 13088.37 8388.78 19279.72 7687.15 10993.50 6269.17 22385.80 18489.56 20980.76 12492.13 16773.21 18995.51 14593.25 130
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
miper_enhance_ethall77.83 23376.93 24080.51 22876.15 34658.01 28875.47 30788.82 18958.05 30783.59 22380.69 32764.41 24791.20 19473.16 19092.03 23292.33 168
旧先验281.73 22156.88 31686.54 17284.90 30072.81 191
114514_t83.10 16782.54 17184.77 14492.90 8469.10 18686.65 11990.62 15154.66 32481.46 25590.81 18376.98 16094.38 8672.62 19296.18 11990.82 211
UniMVSNet_ETH3D89.12 6490.72 4684.31 15597.00 264.33 22089.67 6688.38 19788.84 1594.29 1997.57 390.48 1491.26 19372.57 19397.65 6297.34 14
NR-MVSNet86.00 10586.22 10485.34 13593.24 7764.56 21782.21 21690.46 15380.99 7888.42 13391.97 14777.56 15193.85 10872.46 19498.65 1297.61 10
Baseline_NR-MVSNet84.00 14985.90 11078.29 26291.47 13753.44 31982.29 21287.00 22579.06 10389.55 11495.72 2877.20 15586.14 28872.30 19598.51 1795.28 55
Effi-MVS+-dtu85.82 10983.38 15693.14 387.13 22491.15 287.70 10088.42 19574.57 15683.56 22485.65 26978.49 14294.21 9272.04 19692.88 21694.05 97
mvs-test184.55 13282.12 17591.84 2087.13 22489.54 485.05 14188.42 19574.57 15680.60 26482.98 30678.49 14293.98 10472.04 19689.77 26892.00 182
PM-MVS80.20 21079.00 21683.78 16888.17 20386.66 1881.31 22866.81 35569.64 22088.33 13690.19 19964.58 24683.63 31171.99 19890.03 26681.06 342
EIA-MVS82.19 17781.23 18985.10 13987.95 20669.17 18583.22 18893.33 6770.42 21178.58 28579.77 33977.29 15494.20 9371.51 19988.96 27791.93 186
DPM-MVS80.10 21379.18 21582.88 18990.71 15869.74 17478.87 26490.84 14460.29 29775.64 30985.92 26667.28 23593.11 14271.24 20091.79 23785.77 283
OpenMVScopyleft76.72 1381.98 18282.00 17881.93 20384.42 26668.22 19088.50 9189.48 18166.92 24781.80 25191.86 14972.59 20890.16 22771.19 20191.25 24587.40 266
AllTest87.97 7987.40 8889.68 5491.59 12683.40 5089.50 7295.44 979.47 9588.00 14093.03 11482.66 9291.47 18570.81 20296.14 12194.16 93
TestCases89.68 5491.59 12683.40 5095.44 979.47 9588.00 14093.03 11482.66 9291.47 18570.81 20296.14 12194.16 93
ET-MVSNet_ETH3D75.28 25872.77 27882.81 19183.03 28968.11 19177.09 28776.51 30360.67 29577.60 29480.52 33138.04 36091.15 19770.78 20490.68 26089.17 242
EPP-MVSNet85.47 11385.04 12686.77 10491.52 13569.37 17891.63 3787.98 20681.51 7387.05 15691.83 15266.18 24295.29 5570.75 20596.89 9095.64 45
jason77.42 23875.75 25182.43 20087.10 22869.27 18077.99 27481.94 27251.47 34377.84 29085.07 28460.32 27089.00 24970.74 20689.27 27489.03 247
jason: jason.
MG-MVS80.32 20780.94 19378.47 25888.18 20252.62 32682.29 21285.01 25272.01 19779.24 28192.54 13469.36 22593.36 13370.65 20789.19 27589.45 235
QAPM82.59 17182.59 17082.58 19586.44 23566.69 20289.94 6090.36 15767.97 23784.94 19792.58 13272.71 20692.18 16670.63 20887.73 29388.85 250
CVMVSNet72.62 28371.41 29276.28 28883.25 28460.34 26583.50 17879.02 29137.77 36876.33 29985.10 28149.60 32087.41 26870.54 20977.54 35381.08 340
pmmvs686.52 9688.06 7881.90 20492.22 10562.28 24584.66 14689.15 18683.54 4989.85 10297.32 488.08 3886.80 27770.43 21097.30 8196.62 27
D2MVS76.84 24475.67 25380.34 23180.48 31562.16 24773.50 32084.80 25657.61 31182.24 24087.54 24151.31 31487.65 26670.40 21193.19 20891.23 201
PAPM_NR83.23 16483.19 16083.33 17790.90 15265.98 20788.19 9390.78 14678.13 11680.87 26287.92 23673.49 19692.42 15870.07 21288.40 28291.60 195
lupinMVS76.37 25274.46 26282.09 20185.54 25469.26 18176.79 29080.77 28050.68 34976.23 30182.82 31158.69 28388.94 25069.85 21388.77 27988.07 255
PVSNet_Blended_VisFu81.55 18680.49 19884.70 14791.58 12973.24 13784.21 15491.67 12262.86 27680.94 26087.16 24867.27 23692.87 15169.82 21488.94 27887.99 258
Patchmatch-RL test74.48 26973.68 26876.89 28184.83 26066.54 20372.29 32669.16 34857.70 30986.76 16186.33 25845.79 33582.59 31469.63 21590.65 26381.54 333
EPNet80.37 20578.41 22586.23 11576.75 34073.28 13587.18 10877.45 29776.24 13268.14 34088.93 22165.41 24593.85 10869.47 21696.12 12391.55 197
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CLD-MVS83.18 16582.64 16884.79 14389.05 18567.82 19477.93 27592.52 10068.33 23285.07 19481.54 32382.06 10392.96 14669.35 21797.91 5093.57 121
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
原ACMM184.60 14892.81 9074.01 13191.50 12562.59 27782.73 23590.67 18876.53 16894.25 8969.24 21895.69 14285.55 284
VDD-MVS84.23 14384.58 13883.20 18091.17 14665.16 21383.25 18584.97 25479.79 9187.18 15094.27 7274.77 18190.89 20669.24 21896.54 10493.55 124
CANet_DTU77.81 23577.05 23880.09 23581.37 30059.90 26983.26 18488.29 19969.16 22467.83 34383.72 29860.93 26589.47 24369.22 22089.70 26990.88 209
Anonymous2024052986.20 10387.13 8983.42 17690.19 16764.55 21884.55 14890.71 14785.85 3189.94 10095.24 3982.13 10190.40 22069.19 22196.40 11095.31 54
FMVSNet184.55 13285.45 12081.85 20690.27 16661.05 25686.83 11488.27 20078.57 11189.66 10995.64 3075.43 17290.68 21369.09 22295.33 15093.82 107
UGNet82.78 16881.64 18286.21 11886.20 24676.24 12286.86 11285.68 23877.07 12573.76 32092.82 12369.64 22391.82 18069.04 22393.69 19890.56 219
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
ANet_high83.17 16685.68 11675.65 29281.24 30145.26 36079.94 24692.91 8983.83 4391.33 7596.88 1080.25 13185.92 29068.89 22495.89 13395.76 42
Fast-Effi-MVS+-dtu82.54 17281.41 18685.90 12485.60 25276.53 11883.07 19089.62 17973.02 18079.11 28283.51 30080.74 12590.24 22468.76 22589.29 27290.94 207
pm-mvs183.69 15484.95 12879.91 23690.04 17359.66 27182.43 20887.44 21075.52 14587.85 14295.26 3881.25 11985.65 29468.74 22696.04 12494.42 84
CR-MVSNet74.00 27373.04 27676.85 28279.58 32062.64 23882.58 20276.90 29950.50 35075.72 30792.38 13648.07 32384.07 30768.72 22782.91 33183.85 303
KD-MVS_self_test81.93 18383.14 16178.30 26184.75 26152.75 32380.37 24189.42 18370.24 21690.26 9293.39 10974.55 18586.77 27868.61 22896.64 9995.38 51
IterMVS76.91 24376.34 24678.64 25480.91 30564.03 22276.30 29879.03 29064.88 26983.11 23089.16 21659.90 27484.46 30468.61 22885.15 31487.42 265
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
testdata79.54 24492.87 8572.34 15180.14 28459.91 29985.47 19091.75 15667.96 23385.24 29668.57 23092.18 23181.06 342
mvs_anonymous78.13 23078.76 21976.23 29079.24 32650.31 34478.69 26684.82 25561.60 28783.09 23292.82 12373.89 19087.01 27168.33 23186.41 30391.37 199
WR-MVS83.56 15784.40 14381.06 21993.43 7254.88 31178.67 26785.02 25181.24 7590.74 8591.56 16072.85 20491.08 19968.00 23298.04 3797.23 16
TransMVSNet (Re)84.02 14885.74 11478.85 25091.00 15055.20 31082.29 21287.26 21379.65 9488.38 13595.52 3383.00 8886.88 27567.97 23396.60 10294.45 83
无先验82.81 19785.62 23958.09 30691.41 19067.95 23484.48 294
112180.86 19479.81 21184.02 16193.93 6078.70 8781.64 22380.18 28355.43 32183.67 22191.15 16971.29 21991.41 19067.95 23493.06 21181.96 328
Fast-Effi-MVS+81.04 19280.57 19582.46 19987.50 21763.22 23078.37 27189.63 17868.01 23581.87 24782.08 31882.31 9692.65 15567.10 23688.30 28791.51 198
FMVSNet281.31 18881.61 18380.41 23086.38 23758.75 28583.93 16386.58 22872.43 18587.65 14492.98 11663.78 25290.22 22566.86 23793.92 19292.27 173
GA-MVS75.83 25574.61 25979.48 24581.87 29459.25 27573.42 32182.88 26468.68 23079.75 27581.80 32050.62 31789.46 24466.85 23885.64 30989.72 231
CNLPA83.55 15883.10 16284.90 14189.34 18083.87 4884.54 15088.77 19079.09 10283.54 22588.66 22574.87 17781.73 31966.84 23992.29 22689.11 243
tfpnnormal81.79 18482.95 16378.31 26088.93 18955.40 30680.83 23782.85 26576.81 12785.90 18394.14 8374.58 18486.51 28266.82 24095.68 14393.01 138
VPA-MVSNet83.47 16084.73 13179.69 24190.29 16557.52 29281.30 23088.69 19276.29 13087.58 14694.44 6380.60 12787.20 27066.60 24196.82 9594.34 87
VDDNet84.35 13785.39 12181.25 21495.13 3359.32 27485.42 13781.11 27686.41 2987.41 14896.21 1973.61 19290.61 21666.33 24296.85 9293.81 110
DP-MVS Recon84.05 14783.22 15886.52 10891.73 12475.27 12583.23 18792.40 10272.04 19682.04 24488.33 22877.91 14893.95 10566.17 24395.12 16090.34 224
GBi-Net82.02 18082.07 17681.85 20686.38 23761.05 25686.83 11488.27 20072.43 18586.00 17995.64 3063.78 25290.68 21365.95 24493.34 20393.82 107
test182.02 18082.07 17681.85 20686.38 23761.05 25686.83 11488.27 20072.43 18586.00 17995.64 3063.78 25290.68 21365.95 24493.34 20393.82 107
FMVSNet378.80 22278.55 22279.57 24382.89 29056.89 29881.76 22085.77 23769.04 22686.00 17990.44 19351.75 31390.09 23365.95 24493.34 20391.72 191
新几何182.95 18593.96 5978.56 8980.24 28255.45 32083.93 21991.08 17171.19 22088.33 26065.84 24793.07 21081.95 329
F-COLMAP84.97 12683.42 15589.63 5692.39 9783.40 5088.83 8491.92 11573.19 17780.18 27389.15 21777.04 15993.28 13465.82 24892.28 22792.21 176
ppachtmachnet_test74.73 26874.00 26676.90 28080.71 31156.89 29871.53 32978.42 29258.24 30579.32 28082.92 31057.91 28984.26 30665.60 24991.36 24489.56 234
API-MVS82.28 17582.61 16981.30 21386.29 24369.79 17388.71 8787.67 20978.42 11382.15 24384.15 29677.98 14691.59 18365.39 25092.75 21882.51 323
test111178.53 22678.85 21777.56 27392.22 10547.49 35382.61 20069.24 34772.43 18585.28 19194.20 7851.91 31190.07 23465.36 25196.45 10895.11 61
thisisatest051573.00 28170.52 29580.46 22981.45 29859.90 26973.16 32474.31 31757.86 30876.08 30477.78 34537.60 36292.12 16965.00 25291.45 24389.35 238
cascas76.29 25374.81 25880.72 22684.47 26362.94 23373.89 31887.34 21155.94 31875.16 31476.53 35363.97 25091.16 19665.00 25290.97 25388.06 256
test250674.12 27273.39 27276.28 28891.85 11944.20 36384.06 15848.20 37572.30 19281.90 24694.20 7827.22 37689.77 23964.81 25496.02 12594.87 65
MDA-MVSNet-bldmvs77.47 23776.90 24179.16 24879.03 32864.59 21566.58 34675.67 30873.15 17888.86 12388.99 22066.94 23781.23 32164.71 25588.22 28891.64 194
OpenMVS_ROBcopyleft70.19 1777.77 23677.46 23378.71 25384.39 26761.15 25481.18 23282.52 26662.45 28083.34 22787.37 24466.20 24188.66 25764.69 25685.02 31586.32 276
PS-MVSNAJ77.04 24276.53 24478.56 25587.09 22961.40 25075.26 30887.13 21761.25 28874.38 31877.22 35076.94 16190.94 20264.63 25784.83 32083.35 311
xiu_mvs_v2_base77.19 24076.75 24278.52 25687.01 23061.30 25275.55 30687.12 22061.24 28974.45 31678.79 34177.20 15590.93 20364.62 25884.80 32183.32 312
PatchT70.52 29772.76 27963.79 33979.38 32433.53 37377.63 28065.37 35773.61 16671.77 32892.79 12644.38 34875.65 33964.53 25985.37 31182.18 326
LFMVS80.15 21280.56 19678.89 24989.19 18455.93 30285.22 13973.78 32282.96 5684.28 21392.72 12757.38 29290.07 23463.80 26095.75 14090.68 215
ECVR-MVScopyleft78.44 22778.63 22177.88 26991.85 11948.95 34783.68 17269.91 34572.30 19284.26 21594.20 7851.89 31289.82 23863.58 26196.02 12594.87 65
131473.22 27872.56 28375.20 29480.41 31657.84 28981.64 22385.36 24151.68 34273.10 32376.65 35261.45 26485.19 29763.54 26279.21 34782.59 319
testdata286.43 28463.52 263
Patchmtry76.56 24977.46 23373.83 30179.37 32546.60 35782.41 20976.90 29973.81 16485.56 18892.38 13648.07 32383.98 30863.36 26495.31 15390.92 208
MSDG80.06 21479.99 21080.25 23283.91 27968.04 19277.51 28389.19 18577.65 11881.94 24583.45 30276.37 16986.31 28563.31 26586.59 30186.41 275
BH-RMVSNet80.53 20080.22 20481.49 21287.19 22366.21 20577.79 27886.23 23174.21 16083.69 22088.50 22673.25 20190.75 21063.18 26687.90 29087.52 264
test_yl78.71 22478.51 22379.32 24684.32 26858.84 28278.38 26985.33 24275.99 13782.49 23686.57 25458.01 28690.02 23662.74 26792.73 21989.10 244
DCV-MVSNet78.71 22478.51 22379.32 24684.32 26858.84 28278.38 26985.33 24275.99 13782.49 23686.57 25458.01 28690.02 23662.74 26792.73 21989.10 244
TinyColmap81.25 18982.34 17477.99 26785.33 25660.68 26382.32 21188.33 19871.26 20386.97 15892.22 14577.10 15886.98 27462.37 26995.17 15786.31 277
Anonymous20240521180.51 20181.19 19078.49 25788.48 19657.26 29476.63 29382.49 26781.21 7684.30 21292.24 14467.99 23286.24 28662.22 27095.13 15891.98 185
our_test_371.85 28971.59 28972.62 30880.71 31153.78 31669.72 33671.71 33958.80 30278.03 28780.51 33256.61 29678.84 32962.20 27186.04 30785.23 287
pmmvs-eth3d78.42 22877.04 23982.57 19787.44 21874.41 12980.86 23679.67 28655.68 31984.69 20190.31 19660.91 26685.42 29562.20 27191.59 24187.88 261
CMPMVSbinary59.41 2075.12 26173.57 26979.77 23775.84 34867.22 19581.21 23182.18 26950.78 34776.50 29787.66 23955.20 30482.99 31362.17 27390.64 26489.09 246
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
MIMVSNet183.63 15684.59 13780.74 22494.06 5762.77 23682.72 19884.53 25777.57 12190.34 9095.92 2476.88 16785.83 29261.88 27497.42 7793.62 119
BH-untuned80.96 19380.99 19280.84 22388.55 19568.23 18980.33 24288.46 19472.79 18286.55 16786.76 25374.72 18291.77 18161.79 27588.99 27682.52 322
AdaColmapbinary83.66 15583.69 15483.57 17490.05 17272.26 15386.29 12790.00 17278.19 11581.65 25387.16 24883.40 8594.24 9061.69 27694.76 17584.21 298
VPNet80.25 20881.68 18175.94 29192.46 9647.98 35176.70 29281.67 27473.45 16884.87 19892.82 12374.66 18386.51 28261.66 27796.85 9293.33 125
DWT-MVSNet_test66.43 31764.37 32372.63 30774.86 35650.86 34176.52 29572.74 32954.06 32765.50 35068.30 36432.13 36984.84 30161.63 27873.59 35882.19 325
MAR-MVS80.24 20978.74 22084.73 14586.87 23478.18 9185.75 13287.81 20865.67 26177.84 29078.50 34373.79 19190.53 21761.59 27990.87 25685.49 286
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
PLCcopyleft73.85 1682.09 17980.31 20087.45 9590.86 15480.29 7285.88 13090.65 14968.17 23476.32 30086.33 25873.12 20292.61 15661.40 28090.02 26789.44 236
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
test-LLR67.21 31266.74 31668.63 32576.45 34455.21 30867.89 34067.14 35262.43 28165.08 35372.39 35843.41 34969.37 34861.00 28184.89 31881.31 335
test-mter65.00 32263.79 32568.63 32576.45 34455.21 30867.89 34067.14 35250.98 34665.08 35372.39 35828.27 37469.37 34861.00 28184.89 31881.31 335
PatchmatchNetpermissive69.71 30568.83 30672.33 31177.66 33553.60 31779.29 25669.99 34457.66 31072.53 32582.93 30946.45 32780.08 32760.91 28372.09 36083.31 313
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
MVS_030478.17 22977.23 23780.99 22284.13 27669.07 18781.39 22780.81 27976.28 13167.53 34589.11 21862.87 26086.77 27860.90 28492.01 23587.13 269
PVSNet_BlendedMVS78.80 22277.84 23081.65 21184.43 26463.41 22679.49 25490.44 15461.70 28675.43 31087.07 25169.11 22791.44 18760.68 28592.24 22890.11 229
PVSNet_Blended76.49 25075.40 25479.76 23884.43 26463.41 22675.14 30990.44 15457.36 31375.43 31078.30 34469.11 22791.44 18760.68 28587.70 29484.42 296
VNet79.31 21680.27 20176.44 28587.92 20753.95 31575.58 30584.35 25874.39 15982.23 24190.72 18572.84 20584.39 30560.38 28793.98 19190.97 206
LCM-MVSNet-Re83.48 15985.06 12578.75 25285.94 25055.75 30580.05 24494.27 2376.47 12996.09 594.54 5983.31 8689.75 24159.95 28894.89 17090.75 212
YYNet170.06 30170.44 29668.90 32273.76 35953.42 32058.99 36067.20 35158.42 30487.10 15385.39 27759.82 27567.32 35559.79 28983.50 32785.96 279
MDA-MVSNet_test_wron70.05 30270.44 29668.88 32373.84 35853.47 31858.93 36167.28 35058.43 30387.09 15485.40 27659.80 27667.25 35659.66 29083.54 32685.92 281
PAPR78.84 22178.10 22881.07 21885.17 25760.22 26682.21 21690.57 15262.51 27875.32 31284.61 29174.99 17692.30 16459.48 29188.04 28990.68 215
IB-MVS62.13 1971.64 29168.97 30579.66 24280.80 31062.26 24673.94 31776.90 29963.27 27468.63 33976.79 35133.83 36791.84 17959.28 29287.26 29684.88 291
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
PCF-MVS74.62 1582.15 17880.92 19485.84 12689.43 17872.30 15280.53 23991.82 11857.36 31387.81 14389.92 20577.67 15093.63 11758.69 29395.08 16191.58 196
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
1112_ss74.82 26673.74 26778.04 26689.57 17760.04 26776.49 29687.09 22154.31 32573.66 32179.80 33760.25 27186.76 28058.37 29484.15 32487.32 267
tpmvs70.16 29969.56 30371.96 31274.71 35748.13 34979.63 24975.45 31165.02 26870.26 33481.88 31945.34 34185.68 29358.34 29575.39 35682.08 327
UnsupCasMVSNet_eth71.63 29272.30 28569.62 31976.47 34352.70 32570.03 33580.97 27859.18 30079.36 27988.21 23060.50 26769.12 35158.33 29677.62 35287.04 270
tpmrst66.28 31966.69 31765.05 33772.82 36539.33 36878.20 27270.69 34253.16 33267.88 34280.36 33348.18 32274.75 34158.13 29770.79 36281.08 340
test_post178.85 2653.13 37345.19 34380.13 32658.11 298
SCA73.32 27672.57 28275.58 29381.62 29655.86 30378.89 26371.37 34061.73 28474.93 31583.42 30360.46 26887.01 27158.11 29882.63 33583.88 300
pmmvs474.92 26472.98 27780.73 22584.95 25871.71 16376.23 30077.59 29652.83 33377.73 29386.38 25656.35 29884.97 29957.72 30087.05 29885.51 285
Vis-MVSNet (Re-imp)77.82 23477.79 23177.92 26888.82 19151.29 33783.28 18371.97 33574.04 16182.23 24189.78 20657.38 29289.41 24657.22 30195.41 14793.05 136
ab-mvs79.67 21580.56 19676.99 27788.48 19656.93 29684.70 14586.06 23368.95 22780.78 26393.08 11375.30 17484.62 30356.78 30290.90 25589.43 237
baseline173.26 27773.54 27072.43 31084.92 25947.79 35279.89 24774.00 31865.93 25478.81 28486.28 26156.36 29781.63 32056.63 30379.04 34887.87 262
Test_1112_low_res73.90 27473.08 27576.35 28690.35 16455.95 30173.40 32286.17 23250.70 34873.14 32285.94 26558.31 28585.90 29156.51 30483.22 32887.20 268
TESTMET0.1,161.29 32960.32 33464.19 33872.06 36651.30 33667.89 34062.09 36045.27 35960.65 36269.01 36127.93 37564.74 36456.31 30581.65 33876.53 349
XXY-MVS74.44 27176.19 24769.21 32184.61 26252.43 32871.70 32877.18 29860.73 29480.60 26490.96 17875.44 17169.35 35056.13 30688.33 28385.86 282
MDTV_nov1_ep1368.29 31078.03 33243.87 36474.12 31672.22 33352.17 33767.02 34685.54 27045.36 34080.85 32355.73 30784.42 323
E-PMN61.59 32861.62 33061.49 34466.81 37255.40 30653.77 36360.34 36566.80 24958.90 36665.50 36540.48 35666.12 36155.72 30886.25 30562.95 363
MVS73.21 27972.59 28175.06 29680.97 30460.81 26281.64 22385.92 23646.03 35871.68 32977.54 34668.47 23089.77 23955.70 30985.39 31074.60 353
TR-MVS76.77 24675.79 25079.72 24086.10 24965.79 20977.14 28683.02 26365.20 26781.40 25682.10 31766.30 24090.73 21255.57 31085.27 31282.65 318
EPMVS62.47 32462.63 32862.01 34170.63 36938.74 36974.76 31252.86 37253.91 32867.71 34480.01 33539.40 35766.60 35955.54 31168.81 36780.68 344
MS-PatchMatch70.93 29570.22 29873.06 30581.85 29562.50 24173.82 31977.90 29452.44 33675.92 30581.27 32455.67 30181.75 31855.37 31277.70 35174.94 352
CL-MVSNet_self_test76.81 24577.38 23575.12 29586.90 23251.34 33573.20 32380.63 28168.30 23381.80 25188.40 22766.92 23880.90 32255.35 31394.90 16993.12 134
new-patchmatchnet70.10 30073.37 27360.29 34781.23 30216.95 37759.54 35774.62 31362.93 27580.97 25987.93 23562.83 26171.90 34555.24 31495.01 16492.00 182
CostFormer69.98 30368.68 30873.87 30077.14 33750.72 34279.26 25774.51 31551.94 34170.97 33384.75 28945.16 34487.49 26755.16 31579.23 34683.40 310
thres600view775.97 25475.35 25677.85 27187.01 23051.84 33380.45 24073.26 32675.20 15083.10 23186.31 26045.54 33689.05 24855.03 31692.24 22892.66 153
EMVS61.10 33160.81 33261.99 34265.96 37355.86 30353.10 36458.97 36767.06 24656.89 36963.33 36640.98 35467.03 35754.79 31786.18 30663.08 362
USDC76.63 24776.73 24376.34 28783.46 28257.20 29580.02 24588.04 20452.14 33983.65 22291.25 16563.24 25586.65 28154.66 31894.11 18885.17 288
CDS-MVSNet77.32 23975.40 25483.06 18289.00 18772.48 14977.90 27682.17 27060.81 29278.94 28383.49 30159.30 27888.76 25654.64 31992.37 22587.93 260
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
gm-plane-assit75.42 35244.97 36252.17 33772.36 36087.90 26354.10 320
PatchMatch-RL74.48 26973.22 27478.27 26387.70 21285.26 3575.92 30270.09 34364.34 27176.09 30381.25 32565.87 24478.07 33153.86 32183.82 32571.48 356
EPNet_dtu72.87 28271.33 29377.49 27577.72 33460.55 26482.35 21075.79 30666.49 25158.39 36881.06 32653.68 30885.98 28953.55 32292.97 21585.95 280
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
JIA-IIPM69.41 30666.64 31877.70 27273.19 36171.24 16675.67 30365.56 35670.42 21165.18 35292.97 11833.64 36883.06 31253.52 32369.61 36678.79 347
baseline269.77 30466.89 31478.41 25979.51 32258.09 28776.23 30069.57 34657.50 31264.82 35677.45 34846.02 33088.44 25853.08 32477.83 35088.70 251
KD-MVS_2432*160066.87 31465.81 31970.04 31567.50 37047.49 35362.56 35379.16 28861.21 29077.98 28880.61 32825.29 37882.48 31553.02 32584.92 31680.16 345
miper_refine_blended66.87 31465.81 31970.04 31567.50 37047.49 35362.56 35379.16 28861.21 29077.98 28880.61 32825.29 37882.48 31553.02 32584.92 31680.16 345
BH-w/o76.57 24876.07 24978.10 26586.88 23365.92 20877.63 28086.33 22965.69 26080.89 26179.95 33668.97 22990.74 21153.01 32785.25 31377.62 348
pmmvs570.73 29670.07 29972.72 30677.03 33952.73 32474.14 31575.65 30950.36 35172.17 32785.37 27855.42 30380.67 32452.86 32887.59 29584.77 292
tpm67.95 31068.08 31167.55 32978.74 33143.53 36575.60 30467.10 35454.92 32372.23 32688.10 23142.87 35275.97 33752.21 32980.95 34283.15 315
MVP-Stereo75.81 25673.51 27182.71 19289.35 17973.62 13280.06 24385.20 24560.30 29673.96 31987.94 23457.89 29089.45 24552.02 33074.87 35785.06 290
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
thres100view90075.45 25775.05 25776.66 28487.27 22051.88 33281.07 23373.26 32675.68 14383.25 22886.37 25745.54 33688.80 25251.98 33190.99 25089.31 239
tfpn200view974.86 26574.23 26476.74 28386.24 24452.12 32979.24 25873.87 32073.34 17181.82 24984.60 29246.02 33088.80 25251.98 33190.99 25089.31 239
thres40075.14 25974.23 26477.86 27086.24 24452.12 32979.24 25873.87 32073.34 17181.82 24984.60 29246.02 33088.80 25251.98 33190.99 25092.66 153
HyFIR lowres test75.12 26172.66 28082.50 19891.44 13865.19 21272.47 32587.31 21246.79 35580.29 27084.30 29452.70 31092.10 17051.88 33486.73 30090.22 225
TAMVS78.08 23176.36 24583.23 17990.62 15972.87 13879.08 26180.01 28561.72 28581.35 25786.92 25263.96 25188.78 25550.61 33593.01 21388.04 257
sss66.92 31367.26 31365.90 33377.23 33651.10 34064.79 34871.72 33852.12 34070.13 33580.18 33457.96 28865.36 36350.21 33681.01 34181.25 337
FPMVS72.29 28772.00 28673.14 30488.63 19385.00 3774.65 31467.39 34971.94 19877.80 29287.66 23950.48 31875.83 33849.95 33779.51 34358.58 367
tpm cat166.76 31665.21 32271.42 31377.09 33850.62 34378.01 27373.68 32444.89 36068.64 33879.00 34045.51 33882.42 31749.91 33870.15 36381.23 339
CHOSEN 1792x268872.45 28470.56 29478.13 26490.02 17463.08 23168.72 33883.16 26242.99 36475.92 30585.46 27457.22 29485.18 29849.87 33981.67 33686.14 278
HY-MVS64.64 1873.03 28072.47 28474.71 29783.36 28354.19 31382.14 21981.96 27156.76 31769.57 33786.21 26260.03 27284.83 30249.58 34082.65 33385.11 289
MDTV_nov1_ep13_2view27.60 37670.76 33146.47 35761.27 36045.20 34249.18 34183.75 305
PMMVS61.65 32760.38 33365.47 33665.40 37469.26 18163.97 35161.73 36336.80 36960.11 36368.43 36259.42 27766.35 36048.97 34278.57 34960.81 364
WTY-MVS67.91 31168.35 30966.58 33280.82 30948.12 35065.96 34772.60 33053.67 32971.20 33181.68 32258.97 28169.06 35248.57 34381.67 33682.55 320
UnsupCasMVSNet_bld69.21 30769.68 30267.82 32879.42 32351.15 33867.82 34375.79 30654.15 32677.47 29585.36 27959.26 27970.64 34748.46 34479.35 34581.66 331
tpm268.45 30966.83 31573.30 30378.93 33048.50 34879.76 24871.76 33747.50 35469.92 33683.60 29942.07 35388.40 25948.44 34579.51 34383.01 317
Patchmatch-test65.91 32067.38 31261.48 34575.51 35043.21 36668.84 33763.79 35962.48 27972.80 32483.42 30344.89 34659.52 36748.27 34686.45 30281.70 330
FMVSNet572.10 28871.69 28873.32 30281.57 29753.02 32276.77 29178.37 29363.31 27376.37 29891.85 15036.68 36378.98 32847.87 34792.45 22487.95 259
dp60.70 33360.29 33561.92 34372.04 36738.67 37070.83 33064.08 35851.28 34460.75 36177.28 34936.59 36471.58 34647.41 34862.34 36975.52 351
N_pmnet70.20 29868.80 30774.38 29980.91 30584.81 4059.12 35976.45 30455.06 32275.31 31382.36 31655.74 30054.82 36847.02 34987.24 29783.52 307
thres20072.34 28671.55 29174.70 29883.48 28151.60 33475.02 31073.71 32370.14 21778.56 28680.57 33046.20 32888.20 26246.99 35089.29 27284.32 297
test20.0373.75 27574.59 26171.22 31481.11 30351.12 33970.15 33472.10 33470.42 21180.28 27291.50 16164.21 24974.72 34246.96 35194.58 17887.82 263
pmmvs362.47 32460.02 33669.80 31871.58 36864.00 22370.52 33258.44 36839.77 36666.05 34775.84 35427.10 37772.28 34346.15 35284.77 32273.11 354
testgi72.36 28574.61 25965.59 33480.56 31342.82 36768.29 33973.35 32566.87 24881.84 24889.93 20472.08 21366.92 35846.05 35392.54 22387.01 271
PVSNet58.17 2166.41 31865.63 32168.75 32481.96 29349.88 34662.19 35572.51 33251.03 34568.04 34175.34 35650.84 31674.77 34045.82 35482.96 32981.60 332
gg-mvs-nofinetune68.96 30869.11 30468.52 32776.12 34745.32 35983.59 17455.88 37086.68 2664.62 35797.01 730.36 37183.97 30944.78 35582.94 33076.26 350
Anonymous2023120671.38 29371.88 28769.88 31786.31 24154.37 31270.39 33374.62 31352.57 33576.73 29688.76 22259.94 27372.06 34444.35 35693.23 20783.23 314
CHOSEN 280x42059.08 33456.52 33966.76 33176.51 34264.39 21949.62 36559.00 36643.86 36255.66 37068.41 36335.55 36568.21 35443.25 35776.78 35567.69 361
ADS-MVSNet265.87 32163.64 32672.55 30973.16 36256.92 29767.10 34474.81 31249.74 35266.04 34882.97 30746.71 32577.26 33342.29 35869.96 36483.46 308
ADS-MVSNet61.90 32662.19 32961.03 34673.16 36236.42 37167.10 34461.75 36249.74 35266.04 34882.97 30746.71 32563.21 36542.29 35869.96 36483.46 308
DSMNet-mixed60.98 33261.61 33159.09 34972.88 36445.05 36174.70 31346.61 37626.20 37065.34 35190.32 19555.46 30263.12 36641.72 36081.30 34069.09 360
MIMVSNet71.09 29471.59 28969.57 32087.23 22150.07 34578.91 26271.83 33660.20 29871.26 33091.76 15555.08 30576.09 33641.06 36187.02 29982.54 321
test0.0.03 164.66 32364.36 32465.57 33575.03 35546.89 35664.69 34961.58 36462.43 28171.18 33277.54 34643.41 34968.47 35340.75 36282.65 33381.35 334
PAPM71.77 29070.06 30076.92 27986.39 23653.97 31476.62 29486.62 22753.44 33063.97 35884.73 29057.79 29192.34 16239.65 36381.33 33984.45 295
MVS-HIRNet61.16 33062.92 32755.87 35079.09 32735.34 37271.83 32757.98 36946.56 35659.05 36591.14 17049.95 31976.43 33538.74 36471.92 36155.84 368
GG-mvs-BLEND67.16 33073.36 36046.54 35884.15 15555.04 37158.64 36761.95 36829.93 37283.87 31038.71 36576.92 35471.07 357
new_pmnet55.69 33657.66 33849.76 35275.47 35130.59 37459.56 35651.45 37343.62 36362.49 35975.48 35540.96 35549.15 37137.39 36672.52 35969.55 359
PVSNet_051.08 2256.10 33554.97 34059.48 34875.12 35453.28 32155.16 36261.89 36144.30 36159.16 36462.48 36754.22 30765.91 36235.40 36747.01 37059.25 366
wuyk23d75.13 26079.30 21462.63 34075.56 34975.18 12680.89 23573.10 32875.06 15294.76 1295.32 3587.73 4252.85 36934.16 36897.11 8559.85 365
MVEpermissive40.22 2351.82 33850.47 34155.87 35062.66 37651.91 33131.61 36839.28 37740.65 36550.76 37174.98 35756.24 29944.67 37233.94 36964.11 36871.04 358
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
PMMVS255.64 33759.27 33744.74 35364.30 37512.32 37840.60 36649.79 37453.19 33165.06 35584.81 28853.60 30949.76 37032.68 37089.41 27172.15 355
test_method30.46 33929.60 34233.06 35417.99 3783.84 38013.62 36973.92 3192.79 37218.29 37453.41 36928.53 37343.25 37322.56 37135.27 37252.11 369
tmp_tt20.25 34124.50 3447.49 3564.47 3798.70 37934.17 36725.16 3791.00 37432.43 37318.49 37139.37 3589.21 37521.64 37243.75 3714.57 371
DeepMVS_CXcopyleft24.13 35532.95 37729.49 37521.63 38012.07 37137.95 37245.07 37030.84 37019.21 37417.94 37333.06 37323.69 370
test1236.27 3448.08 3470.84 3571.11 3810.57 38162.90 3520.82 3810.54 3751.07 3772.75 3761.26 3800.30 3761.04 3741.26 3751.66 372
testmvs5.91 3457.65 3480.72 3581.20 3800.37 38259.14 3580.67 3820.49 3761.11 3762.76 3750.94 3810.24 3771.02 3751.47 3741.55 373
test_blank0.00 3460.00 3490.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 3770.00 3820.00 3780.00 3760.00 3760.00 374
uanet_test0.00 3460.00 3490.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 3770.00 3820.00 3780.00 3760.00 3760.00 374
cdsmvs_eth3d_5k20.81 34027.75 3430.00 3590.00 3820.00 3830.00 37085.44 2400.00 3770.00 37882.82 31181.46 1150.00 3780.00 3760.00 3760.00 374
pcd_1.5k_mvsjas6.41 3438.55 3460.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 37776.94 1610.00 3780.00 3760.00 3760.00 374
sosnet-low-res0.00 3460.00 3490.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 3770.00 3820.00 3780.00 3760.00 3760.00 374
sosnet0.00 3460.00 3490.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 3770.00 3820.00 3780.00 3760.00 3760.00 374
uncertanet0.00 3460.00 3490.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 3770.00 3820.00 3780.00 3760.00 3760.00 374
Regformer0.00 3460.00 3490.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 3770.00 3820.00 3780.00 3760.00 3760.00 374
ab-mvs-re6.65 3428.87 3450.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 37879.80 3370.00 3820.00 3780.00 3760.00 3760.00 374
uanet0.00 3460.00 3490.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 3770.00 3820.00 3780.00 3760.00 3760.00 374
FOURS196.08 1287.41 1396.19 295.83 492.95 296.57 2
test_one_060193.85 6373.27 13694.11 3786.57 2793.47 4094.64 5788.42 27
eth-test20.00 382
eth-test0.00 382
test_241102_ONE94.18 5072.65 14093.69 5483.62 4694.11 2393.78 10390.28 1595.50 47
save fliter93.75 6477.44 10386.31 12589.72 17570.80 207
test072694.16 5372.56 14690.63 4593.90 4683.61 4793.75 3194.49 6189.76 19
GSMVS83.88 300
test_part293.86 6277.77 9892.84 48
sam_mvs146.11 32983.88 300
sam_mvs45.92 334
MTGPAbinary91.81 119
test_post3.10 37445.43 33977.22 334
patchmatchnet-post81.71 32145.93 33387.01 271
MTMP90.66 4333.14 378
TEST992.34 9979.70 7783.94 16190.32 15865.41 26684.49 20590.97 17682.03 10593.63 117
test_892.09 10978.87 8583.82 16690.31 16065.79 25684.36 20890.96 17881.93 10793.44 129
agg_prior91.58 12977.69 9990.30 16184.32 20993.18 137
test_prior478.97 8484.59 147
test_prior86.32 11190.59 16071.99 15792.85 9194.17 9692.80 145
新几何281.72 222
旧先验191.97 11271.77 15981.78 27391.84 15173.92 18993.65 19983.61 306
原ACMM282.26 215
test22293.31 7576.54 11679.38 25577.79 29552.59 33482.36 23990.84 18266.83 23991.69 23981.25 337
segment_acmp81.94 106
testdata179.62 25073.95 163
test1286.57 10690.74 15672.63 14490.69 14882.76 23479.20 13794.80 7395.32 15192.27 173
plane_prior793.45 7077.31 107
plane_prior692.61 9176.54 11674.84 178
plane_prior492.95 119
plane_prior376.85 11477.79 11786.55 167
plane_prior289.45 7479.44 97
plane_prior192.83 89
plane_prior76.42 11987.15 10975.94 14095.03 163
n20.00 383
nn0.00 383
door-mid74.45 316
test1191.46 126
door72.57 331
HQP5-MVS70.66 169
HQP-NCC91.19 14384.77 14273.30 17380.55 267
ACMP_Plane91.19 14384.77 14273.30 17380.55 267
HQP4-MVS80.56 26694.61 8093.56 122
HQP3-MVS92.68 9794.47 180
HQP2-MVS72.10 211
NP-MVS91.95 11374.55 12890.17 201
ACMMP++_ref95.74 141
ACMMP++97.35 78
Test By Simon79.09 138