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 bysorted bysort bysort bysort bysort bysort bysort bysort bysort bysort by
DVP-MVS++90.23 191.01 187.89 2494.34 2971.25 6395.06 194.23 578.38 3592.78 495.74 682.45 397.49 389.42 496.68 294.95 7
FOURS195.00 1072.39 4295.06 193.84 1874.49 11991.30 15
CP-MVS87.11 3586.92 3787.68 3794.20 3673.86 893.98 392.82 6476.62 7383.68 8594.46 2767.93 9095.95 5684.20 4994.39 6093.23 89
APDe-MVS89.15 689.63 687.73 3094.49 2071.69 5893.83 493.96 1675.70 9291.06 1696.03 176.84 1597.03 1589.09 695.65 3294.47 31
SteuartSystems-ACMMP88.72 1088.86 1088.32 892.14 8072.96 2693.73 593.67 2380.19 1488.10 2794.80 1673.76 4197.11 1387.51 1895.82 2494.90 10
Skip Steuart: Steuart Systems R&D Blog.
test072695.27 571.25 6393.60 694.11 877.33 5092.81 395.79 380.98 9
SED-MVS90.08 290.85 287.77 2695.30 270.98 7093.57 794.06 1277.24 5293.10 195.72 882.99 197.44 589.07 996.63 494.88 11
OPU-MVS89.06 394.62 1575.42 493.57 794.02 4782.45 396.87 1983.77 5496.48 894.88 11
DVP-MVScopyleft89.60 390.35 387.33 4595.27 571.25 6393.49 992.73 6577.33 5092.12 995.78 480.98 997.40 789.08 796.41 1293.33 86
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_SECOND87.71 3495.34 171.43 6293.49 994.23 597.49 389.08 796.41 1294.21 42
3Dnovator+77.84 485.48 6284.47 7688.51 691.08 9373.49 1793.18 1193.78 2180.79 1076.66 19193.37 6060.40 19096.75 2577.20 11793.73 6995.29 3
HFP-MVS87.58 2387.47 2587.94 1794.58 1673.54 1593.04 1293.24 3776.78 6884.91 5894.44 3070.78 6496.61 3284.53 4194.89 4693.66 68
ACMMPR87.44 2687.23 3188.08 1394.64 1373.59 1293.04 1293.20 3976.78 6884.66 6794.52 2368.81 8696.65 2984.53 4194.90 4594.00 52
ZNCC-MVS87.94 1887.85 2088.20 1194.39 2673.33 2093.03 1493.81 2076.81 6685.24 5294.32 3571.76 5696.93 1885.53 2995.79 2594.32 38
region2R87.42 2887.20 3288.09 1294.63 1473.55 1393.03 1493.12 4276.73 7184.45 7194.52 2369.09 8296.70 2684.37 4494.83 5194.03 49
MSP-MVS89.51 489.91 588.30 994.28 3273.46 1892.90 1694.11 880.27 1291.35 1494.16 4178.35 1396.77 2389.59 394.22 6594.67 24
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
CS-MVS86.69 4186.95 3685.90 7590.76 10267.57 14692.83 1793.30 3679.67 1984.57 7092.27 8371.47 5995.02 9684.24 4893.46 7095.13 4
XVS87.18 3486.91 3888.00 1594.42 2273.33 2092.78 1892.99 4979.14 2383.67 8694.17 4067.45 9596.60 3483.06 6294.50 5794.07 47
X-MVStestdata80.37 14777.83 18488.00 1594.42 2273.33 2092.78 1892.99 4979.14 2383.67 8612.47 37467.45 9596.60 3483.06 6294.50 5794.07 47
mPP-MVS86.67 4386.32 4787.72 3294.41 2473.55 1392.74 2092.22 8776.87 6582.81 9894.25 3866.44 10496.24 4282.88 6694.28 6393.38 83
ACMMPcopyleft85.89 5685.39 6287.38 4493.59 5172.63 3492.74 2093.18 4176.78 6880.73 12293.82 5364.33 12596.29 4082.67 7290.69 10293.23 89
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
MP-MVScopyleft87.71 2187.64 2387.93 2094.36 2873.88 792.71 2292.65 7077.57 4383.84 8394.40 3472.24 5296.28 4185.65 2895.30 4093.62 76
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
SF-MVS88.46 1188.74 1187.64 3892.78 6971.95 5392.40 2394.74 275.71 9089.16 1995.10 1375.65 2296.19 4587.07 2196.01 1794.79 18
SMA-MVScopyleft89.08 789.23 788.61 594.25 3373.73 1092.40 2393.63 2474.77 11292.29 795.97 274.28 3697.24 1188.58 1396.91 194.87 13
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
GST-MVS87.42 2887.26 2987.89 2494.12 3972.97 2592.39 2593.43 3276.89 6484.68 6493.99 5070.67 6796.82 2184.18 5095.01 4293.90 57
HPM-MVS++copyleft89.02 889.15 888.63 495.01 976.03 192.38 2692.85 6080.26 1387.78 3094.27 3675.89 2096.81 2287.45 1996.44 993.05 97
SR-MVS86.73 3986.67 4186.91 5294.11 4072.11 5192.37 2792.56 7374.50 11886.84 3794.65 2067.31 9795.77 6084.80 3792.85 7592.84 106
CS-MVS-test86.29 5086.48 4485.71 7791.02 9567.21 15592.36 2893.78 2178.97 3083.51 8991.20 10970.65 6895.15 8881.96 7794.89 4694.77 21
#test#87.33 3187.13 3387.94 1794.58 1673.54 1592.34 2993.24 3775.23 10084.91 5894.44 3070.78 6496.61 3283.75 5594.89 4693.66 68
DROMVSNet86.01 5386.38 4584.91 9789.31 14466.27 17092.32 3093.63 2479.37 2284.17 7891.88 9169.04 8595.43 7483.93 5393.77 6893.01 100
EPP-MVSNet83.40 8683.02 8684.57 10690.13 11364.47 20892.32 3090.73 13874.45 12279.35 13691.10 11269.05 8495.12 8972.78 15987.22 14494.13 44
PHI-MVS86.43 4686.17 5287.24 4690.88 9970.96 7292.27 3294.07 1172.45 15785.22 5391.90 9069.47 7896.42 3883.28 6095.94 2094.35 36
testtj87.78 2087.78 2187.77 2694.55 1872.47 3992.23 3393.49 2974.75 11388.33 2594.43 3273.27 4497.02 1684.18 5094.84 4993.82 62
HPM-MVScopyleft87.11 3586.98 3587.50 4193.88 4372.16 4992.19 3493.33 3576.07 8583.81 8493.95 5169.77 7696.01 5285.15 3194.66 5394.32 38
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
MTMP92.18 3532.83 379
HPM-MVS_fast85.35 6684.95 7186.57 6193.69 4870.58 8492.15 3691.62 11473.89 13482.67 10094.09 4462.60 14795.54 6880.93 8492.93 7393.57 78
CPTT-MVS83.73 7883.33 8284.92 9693.28 5570.86 7792.09 3790.38 14668.75 23179.57 13392.83 7460.60 18693.04 18780.92 8591.56 9390.86 168
APD-MVS_3200maxsize85.97 5485.88 5686.22 6792.69 7269.53 10291.93 3892.99 4973.54 14385.94 4294.51 2665.80 11495.61 6383.04 6492.51 8093.53 81
SR-MVS-dyc-post85.77 5785.61 5986.23 6693.06 6270.63 8291.88 3992.27 8373.53 14485.69 4794.45 2865.00 12295.56 6582.75 6791.87 8892.50 115
RE-MVS-def85.48 6093.06 6270.63 8291.88 3992.27 8373.53 14485.69 4794.45 2863.87 12982.75 6791.87 8892.50 115
APD-MVScopyleft87.44 2687.52 2487.19 4794.24 3472.39 4291.86 4192.83 6173.01 15488.58 2394.52 2373.36 4296.49 3784.26 4695.01 4292.70 108
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
SD-MVS88.06 1488.50 1386.71 5792.60 7672.71 3091.81 4293.19 4077.87 3890.32 1794.00 4874.83 2893.78 14987.63 1794.27 6493.65 73
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
test117286.20 5286.22 4986.12 7093.95 4269.89 9591.79 4392.28 8275.07 10486.40 4094.58 2265.00 12295.56 6584.34 4592.60 7892.90 104
DPE-MVScopyleft89.48 589.98 488.01 1494.80 1172.69 3291.59 4494.10 1075.90 8892.29 795.66 1081.67 697.38 987.44 2096.34 1593.95 54
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
QAPM80.88 12779.50 14385.03 9088.01 19168.97 11391.59 4492.00 9766.63 25375.15 22992.16 8557.70 20395.45 7263.52 23488.76 12590.66 174
IS-MVSNet83.15 8982.81 8984.18 12289.94 12263.30 23391.59 4488.46 21079.04 2779.49 13492.16 8565.10 11994.28 12267.71 20291.86 9094.95 7
9.1488.26 1592.84 6891.52 4794.75 173.93 13388.57 2494.67 1975.57 2495.79 5986.77 2395.76 28
ETH3D-3000-0.188.09 1388.29 1487.50 4192.76 7071.89 5691.43 4894.70 374.47 12088.86 2294.61 2175.23 2595.84 5886.62 2695.92 2194.78 20
TSAR-MVS + MP.88.02 1788.11 1687.72 3293.68 4972.13 5091.41 4992.35 8074.62 11788.90 2193.85 5275.75 2196.00 5387.80 1594.63 5495.04 5
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
mvsmamba81.69 11380.74 11984.56 10787.45 21066.72 16391.26 5085.89 25474.66 11578.23 15790.56 12554.33 22894.91 10080.73 8983.54 19092.04 134
DeepC-MVS_fast79.65 386.91 3886.62 4287.76 2993.52 5272.37 4491.26 5093.04 4376.62 7384.22 7693.36 6171.44 6096.76 2480.82 8695.33 3894.16 43
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
HQP_MVS83.64 8183.14 8385.14 8790.08 11568.71 12191.25 5292.44 7579.12 2578.92 14191.00 11860.42 18895.38 7978.71 10286.32 15791.33 151
plane_prior291.25 5279.12 25
NCCC88.06 1488.01 1888.24 1094.41 2473.62 1191.22 5492.83 6181.50 685.79 4693.47 5973.02 4797.00 1784.90 3394.94 4494.10 45
API-MVS81.99 10781.23 11184.26 12090.94 9770.18 9291.10 5589.32 17671.51 17578.66 14688.28 18665.26 11795.10 9364.74 23091.23 9887.51 270
RRT_MVS80.35 14879.22 15383.74 14287.63 20465.46 18891.08 5688.92 19773.82 13576.44 19790.03 13749.05 28794.25 12876.84 12179.20 24391.51 145
EPNet83.72 7982.92 8886.14 6984.22 26069.48 10391.05 5785.27 25981.30 776.83 18691.65 9566.09 10995.56 6576.00 13093.85 6793.38 83
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
test_part182.78 9682.08 10084.89 9890.66 10366.97 16090.96 5892.93 5777.19 5580.53 12490.04 13663.44 13295.39 7876.04 12976.90 26092.31 122
ACMMP_NAP88.05 1688.08 1787.94 1793.70 4773.05 2390.86 5993.59 2676.27 8288.14 2695.09 1571.06 6296.67 2887.67 1696.37 1494.09 46
CSCG86.41 4886.19 5187.07 5092.91 6572.48 3890.81 6093.56 2773.95 13183.16 9291.07 11475.94 1995.19 8679.94 9594.38 6193.55 79
abl_685.23 6784.95 7186.07 7192.23 7970.48 8590.80 6192.08 9273.51 14685.26 5194.16 4162.75 14695.92 5782.46 7491.30 9791.81 139
MSLP-MVS++85.43 6485.76 5884.45 11291.93 8370.24 8690.71 6292.86 5977.46 4984.22 7692.81 7667.16 9992.94 18980.36 9194.35 6290.16 191
3Dnovator76.31 583.38 8782.31 9686.59 6087.94 19272.94 2990.64 6392.14 9177.21 5475.47 21592.83 7458.56 19794.72 11173.24 15592.71 7792.13 130
ETH3 D test640087.50 2587.44 2687.70 3593.71 4671.75 5790.62 6494.05 1570.80 18587.59 3393.51 5677.57 1496.63 3183.31 5795.77 2694.72 23
OpenMVScopyleft72.83 1079.77 15878.33 17384.09 12585.17 24469.91 9390.57 6590.97 13366.70 24972.17 26291.91 8954.70 22593.96 13761.81 25290.95 10088.41 255
CNVR-MVS88.93 989.13 988.33 794.77 1273.82 990.51 6693.00 4780.90 988.06 2894.06 4676.43 1796.84 2088.48 1495.99 1994.34 37
MVSFormer82.85 9582.05 10185.24 8587.35 21170.21 8790.50 6790.38 14668.55 23481.32 11389.47 15261.68 16293.46 16678.98 10090.26 10892.05 132
test_djsdf80.30 14979.32 14983.27 15583.98 26565.37 19290.50 6790.38 14668.55 23476.19 20388.70 17256.44 21593.46 16678.98 10080.14 23290.97 165
xxxxxxxxxxxxxcwj87.88 1987.92 1987.77 2693.80 4472.35 4590.47 6989.69 16874.31 12389.16 1995.10 1375.65 2296.19 4587.07 2196.01 1794.79 18
save fliter93.80 4472.35 4590.47 6991.17 12974.31 123
nrg03083.88 7683.53 7984.96 9386.77 22669.28 10890.46 7192.67 6774.79 11182.95 9391.33 10672.70 4893.09 18380.79 8879.28 24192.50 115
canonicalmvs85.91 5585.87 5786.04 7289.84 12469.44 10790.45 7293.00 4776.70 7288.01 2991.23 10773.28 4393.91 14481.50 8088.80 12494.77 21
plane_prior68.71 12190.38 7377.62 4186.16 160
DeepC-MVS79.81 287.08 3786.88 3987.69 3691.16 9272.32 4790.31 7493.94 1777.12 5882.82 9794.23 3972.13 5497.09 1484.83 3695.37 3593.65 73
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
Vis-MVSNetpermissive83.46 8482.80 9085.43 8190.25 11168.74 11990.30 7590.13 15676.33 8180.87 12192.89 7261.00 17994.20 12972.45 16290.97 9993.35 85
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
zzz-MVS87.53 2487.41 2787.90 2194.18 3774.25 590.23 7692.02 9479.45 2085.88 4394.80 1668.07 8896.21 4386.69 2495.34 3693.23 89
PGM-MVS86.68 4286.27 4887.90 2194.22 3573.38 1990.22 7793.04 4375.53 9483.86 8294.42 3367.87 9296.64 3082.70 7194.57 5693.66 68
LPG-MVS_test82.08 10481.27 11084.50 10989.23 14868.76 11790.22 7791.94 10175.37 9876.64 19291.51 10054.29 22994.91 10078.44 10483.78 18389.83 212
Anonymous2023121178.97 18177.69 19182.81 17890.54 10664.29 21290.11 7991.51 11865.01 27176.16 20788.13 19550.56 26893.03 18869.68 18577.56 25491.11 158
ETH3D cwj APD-0.1687.31 3287.27 2887.44 4391.60 8872.45 4190.02 8094.37 471.76 16687.28 3494.27 3675.18 2696.08 4985.16 3095.77 2693.80 65
ACMM73.20 880.78 13779.84 13583.58 14589.31 14468.37 12989.99 8191.60 11570.28 19677.25 17789.66 14553.37 23793.53 16274.24 14382.85 19988.85 243
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
ACMP74.13 681.51 12080.57 12284.36 11589.42 13468.69 12489.97 8291.50 12174.46 12175.04 23390.41 12853.82 23494.54 11577.56 11382.91 19889.86 211
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
iter_conf_final80.63 13979.35 14884.46 11189.36 13867.70 14389.85 8384.49 26973.19 15078.30 15588.94 16645.98 30594.56 11379.59 9784.48 17691.11 158
LFMVS81.82 11081.23 11183.57 14691.89 8463.43 23189.84 8481.85 30577.04 6183.21 9093.10 6552.26 24593.43 16871.98 16389.95 11493.85 59
MCST-MVS87.37 3087.25 3087.73 3094.53 1972.46 4089.82 8593.82 1973.07 15284.86 6392.89 7276.22 1896.33 3984.89 3595.13 4194.40 34
MAR-MVS81.84 10980.70 12085.27 8491.32 9171.53 6089.82 8590.92 13469.77 20578.50 14986.21 24562.36 15394.52 11765.36 22492.05 8689.77 215
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
MP-MVS-pluss87.67 2287.72 2287.54 3993.64 5072.04 5289.80 8793.50 2875.17 10386.34 4195.29 1270.86 6396.00 5388.78 1296.04 1694.58 27
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
UA-Net85.08 7184.96 7085.45 8092.07 8168.07 13689.78 8890.86 13782.48 284.60 6993.20 6369.35 7995.22 8571.39 16890.88 10193.07 96
alignmvs85.48 6285.32 6485.96 7489.51 13169.47 10489.74 8992.47 7476.17 8387.73 3291.46 10370.32 7093.78 14981.51 7988.95 12194.63 26
VDDNet81.52 11880.67 12184.05 12990.44 10864.13 21589.73 9085.91 25371.11 18083.18 9193.48 5750.54 26993.49 16373.40 15288.25 13294.54 30
CANet86.45 4586.10 5487.51 4090.09 11470.94 7489.70 9192.59 7281.78 481.32 11391.43 10470.34 6997.23 1284.26 4693.36 7194.37 35
114514_t80.68 13879.51 14284.20 12194.09 4167.27 15389.64 9291.11 13158.75 32974.08 24390.72 12258.10 19995.04 9569.70 18489.42 11990.30 187
DeepPCF-MVS80.84 188.10 1288.56 1286.73 5692.24 7869.03 10989.57 9393.39 3477.53 4789.79 1894.12 4378.98 1296.58 3685.66 2795.72 2994.58 27
UGNet80.83 13179.59 14184.54 10888.04 18968.09 13589.42 9488.16 21276.95 6276.22 20289.46 15449.30 28393.94 14068.48 19790.31 10691.60 142
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
AdaColmapbinary80.58 14379.42 14484.06 12793.09 6168.91 11489.36 9588.97 19469.27 21475.70 21289.69 14457.20 21195.77 6063.06 23988.41 13187.50 271
mvs-test180.88 12779.40 14585.29 8385.13 24769.75 9889.28 9688.10 21474.99 10676.44 19786.72 22557.27 20994.26 12773.53 14883.18 19591.87 136
PS-MVSNAJss82.07 10581.31 10984.34 11786.51 22967.27 15389.27 9791.51 11871.75 16779.37 13590.22 13263.15 14094.27 12377.69 11282.36 20691.49 148
jajsoiax79.29 17277.96 17983.27 15584.68 25466.57 16689.25 9890.16 15569.20 21875.46 21789.49 15145.75 31093.13 18176.84 12180.80 22290.11 195
mvs_tets79.13 17677.77 18783.22 15984.70 25366.37 16889.17 9990.19 15469.38 21275.40 22089.46 15444.17 31593.15 17976.78 12380.70 22490.14 192
HQP-NCC89.33 13989.17 9976.41 7577.23 179
ACMP_Plane89.33 13989.17 9976.41 7577.23 179
HQP-MVS82.61 9982.02 10284.37 11489.33 13966.98 15889.17 9992.19 8976.41 7577.23 17990.23 13160.17 19195.11 9077.47 11485.99 16391.03 162
LS3D76.95 22574.82 23783.37 15290.45 10767.36 15289.15 10386.94 23961.87 30569.52 29090.61 12451.71 25794.53 11646.38 34486.71 15288.21 257
OPM-MVS83.50 8382.95 8785.14 8788.79 16570.95 7389.13 10491.52 11777.55 4680.96 12091.75 9360.71 18294.50 11879.67 9686.51 15589.97 207
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
TSAR-MVS + GP.85.71 5985.33 6386.84 5391.34 9072.50 3789.07 10587.28 23376.41 7585.80 4590.22 13274.15 3995.37 8281.82 7891.88 8792.65 112
test_prior472.60 3589.01 106
GeoE81.71 11281.01 11683.80 14189.51 13164.45 20988.97 10788.73 20571.27 17878.63 14789.76 14366.32 10693.20 17569.89 18286.02 16293.74 66
Anonymous2024052980.19 15278.89 16084.10 12490.60 10464.75 20288.95 10890.90 13565.97 26180.59 12391.17 11149.97 27493.73 15569.16 19082.70 20393.81 63
VDD-MVS83.01 9482.36 9584.96 9391.02 9566.40 16788.91 10988.11 21377.57 4384.39 7493.29 6252.19 24693.91 14477.05 11988.70 12694.57 29
Effi-MVS+83.62 8283.08 8485.24 8588.38 18067.45 14888.89 11089.15 18575.50 9582.27 10188.28 18669.61 7794.45 11977.81 11187.84 13493.84 61
ACMH+68.96 1476.01 23974.01 24682.03 19588.60 17265.31 19388.86 11187.55 22770.25 19767.75 30187.47 20741.27 33293.19 17758.37 28175.94 27687.60 267
test_prior386.73 3986.86 4086.33 6392.61 7469.59 10088.85 11292.97 5475.41 9684.91 5893.54 5474.28 3695.48 7083.31 5795.86 2293.91 55
test_prior288.85 11275.41 9684.91 5893.54 5474.28 3683.31 5795.86 22
iter_conf0580.00 15678.70 16283.91 13987.84 19565.83 17888.84 11484.92 26471.61 17278.70 14388.94 16643.88 31794.56 11379.28 9884.28 17991.33 151
DP-MVS Recon83.11 9282.09 9986.15 6894.44 2170.92 7688.79 11592.20 8870.53 19279.17 13791.03 11764.12 12796.03 5068.39 19990.14 11091.50 147
Effi-MVS+-dtu80.03 15478.57 16684.42 11385.13 24768.74 11988.77 11688.10 21474.99 10674.97 23483.49 28957.27 20993.36 16973.53 14880.88 22091.18 156
TEST993.26 5672.96 2688.75 11791.89 10368.44 23685.00 5693.10 6574.36 3595.41 76
train_agg86.43 4686.20 5087.13 4993.26 5672.96 2688.75 11791.89 10368.69 23285.00 5693.10 6574.43 3295.41 7684.97 3295.71 3093.02 99
ETV-MVS84.90 7484.67 7485.59 7989.39 13668.66 12588.74 11992.64 7179.97 1784.10 7985.71 25369.32 8095.38 7980.82 8691.37 9592.72 107
PVSNet_Blended_VisFu82.62 9881.83 10684.96 9390.80 10169.76 9788.74 11991.70 11369.39 21178.96 13988.46 18165.47 11694.87 10674.42 14088.57 12790.24 189
test_893.13 5872.57 3688.68 12191.84 10768.69 23284.87 6293.10 6574.43 3295.16 87
ACMH67.68 1675.89 24073.93 24781.77 20088.71 16966.61 16588.62 12289.01 19169.81 20366.78 31386.70 23041.95 33191.51 23555.64 30078.14 25087.17 279
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
agg_prior186.22 5186.09 5586.62 5992.85 6671.94 5488.59 12391.78 11068.96 22784.41 7293.18 6474.94 2794.93 9884.75 3895.33 3893.01 100
CDPH-MVS85.76 5885.29 6687.17 4893.49 5371.08 6888.58 12492.42 7868.32 23784.61 6893.48 5772.32 5196.15 4879.00 9995.43 3494.28 40
DP-MVS76.78 22774.57 23983.42 14993.29 5469.46 10688.55 12583.70 28163.98 28570.20 27888.89 16954.01 23394.80 10846.66 34181.88 21186.01 303
Regformer-186.41 4886.33 4686.64 5889.33 13970.93 7588.43 12691.39 12382.14 386.65 3890.09 13474.39 3495.01 9783.97 5290.63 10393.97 53
Regformer-286.63 4486.53 4386.95 5189.33 13971.24 6788.43 12692.05 9382.50 186.88 3690.09 13474.45 3195.61 6384.38 4390.63 10394.01 51
WR-MVS_H78.51 19078.49 16778.56 26488.02 19056.38 31788.43 12692.67 6777.14 5773.89 24487.55 20466.25 10789.24 27558.92 27573.55 30790.06 201
F-COLMAP76.38 23574.33 24482.50 18889.28 14666.95 16288.41 12989.03 18964.05 28366.83 31288.61 17646.78 29992.89 19057.48 28878.55 24487.67 265
GBi-Net78.40 19177.40 19681.40 20887.60 20563.01 23988.39 13089.28 17771.63 16975.34 22287.28 20954.80 22191.11 24362.72 24079.57 23590.09 197
test178.40 19177.40 19681.40 20887.60 20563.01 23988.39 13089.28 17771.63 16975.34 22287.28 20954.80 22191.11 24362.72 24079.57 23590.09 197
FMVSNet177.44 21576.12 22281.40 20886.81 22563.01 23988.39 13089.28 17770.49 19374.39 24087.28 20949.06 28691.11 24360.91 25978.52 24590.09 197
tttt051779.40 16977.91 18183.90 14088.10 18763.84 21988.37 13384.05 27771.45 17676.78 18889.12 16249.93 27794.89 10470.18 17883.18 19592.96 103
v7n78.97 18177.58 19483.14 16283.45 27465.51 18588.32 13491.21 12773.69 13872.41 25986.32 24457.93 20093.81 14869.18 18975.65 27990.11 195
COLMAP_ROBcopyleft66.92 1773.01 26870.41 27980.81 22587.13 22065.63 18388.30 13584.19 27662.96 29363.80 33687.69 20038.04 34592.56 19846.66 34174.91 29484.24 322
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
Regformer-385.23 6785.07 6885.70 7888.95 15769.01 11188.29 13689.91 16280.95 885.01 5490.01 13872.45 5094.19 13082.50 7387.57 13693.90 57
Regformer-485.68 6085.45 6186.35 6288.95 15769.67 9988.29 13691.29 12581.73 585.36 5090.01 13872.62 4995.35 8383.28 6087.57 13694.03 49
FIs82.07 10582.42 9281.04 22088.80 16458.34 28688.26 13893.49 2976.93 6378.47 15191.04 11569.92 7492.34 20869.87 18384.97 16992.44 119
EIA-MVS83.31 8882.80 9084.82 10089.59 12765.59 18488.21 13992.68 6674.66 11578.96 13986.42 24169.06 8395.26 8475.54 13590.09 11193.62 76
PLCcopyleft70.83 1178.05 20276.37 22083.08 16591.88 8567.80 14088.19 14089.46 17364.33 27969.87 28788.38 18353.66 23593.58 15758.86 27682.73 20187.86 262
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
MG-MVS83.41 8583.45 8083.28 15492.74 7162.28 24988.17 14189.50 17275.22 10181.49 11292.74 8066.75 10095.11 9072.85 15891.58 9292.45 118
TAPA-MVS73.13 979.15 17577.94 18082.79 18189.59 12762.99 24288.16 14291.51 11865.77 26277.14 18391.09 11360.91 18093.21 17350.26 32487.05 14692.17 129
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
h-mvs3383.15 8982.19 9786.02 7390.56 10570.85 7888.15 14389.16 18476.02 8684.67 6591.39 10561.54 16595.50 6982.71 6975.48 28391.72 141
bld_raw_dy_0_6477.29 22075.98 22381.22 21485.04 25065.47 18788.14 14477.56 33569.20 21873.77 24589.40 16042.24 32888.85 28576.78 12381.64 21389.33 225
PS-CasMVS78.01 20478.09 17777.77 27687.71 20154.39 33288.02 14591.22 12677.50 4873.26 24988.64 17560.73 18188.41 29061.88 25073.88 30490.53 180
OMC-MVS82.69 9781.97 10484.85 9988.75 16767.42 14987.98 14690.87 13674.92 10879.72 13291.65 9562.19 15793.96 13775.26 13786.42 15693.16 94
v879.97 15779.02 15882.80 17984.09 26264.50 20787.96 14790.29 15374.13 13075.24 22786.81 22262.88 14593.89 14674.39 14175.40 28790.00 203
FC-MVSNet-test81.52 11882.02 10280.03 24088.42 17955.97 32287.95 14893.42 3377.10 5977.38 17490.98 12069.96 7391.79 22668.46 19884.50 17492.33 120
CP-MVSNet78.22 19578.34 17277.84 27487.83 19654.54 33087.94 14991.17 12977.65 4073.48 24788.49 18062.24 15688.43 28962.19 24674.07 30090.55 179
PAPM_NR83.02 9382.41 9384.82 10092.47 7766.37 16887.93 15091.80 10873.82 13577.32 17690.66 12367.90 9194.90 10370.37 17689.48 11893.19 93
PEN-MVS77.73 20977.69 19177.84 27487.07 22153.91 33587.91 15191.18 12877.56 4573.14 25188.82 17161.23 17489.17 27659.95 26572.37 31590.43 183
ECVR-MVScopyleft79.61 16079.26 15180.67 22890.08 11554.69 32887.89 15277.44 33874.88 10980.27 12692.79 7748.96 28992.45 20168.55 19692.50 8194.86 14
v1079.74 15978.67 16382.97 17284.06 26364.95 19887.88 15390.62 14073.11 15175.11 23086.56 23761.46 16894.05 13673.68 14675.55 28189.90 209
test250677.30 21976.49 21679.74 24690.08 11552.02 34487.86 15463.10 37174.88 10980.16 12992.79 7738.29 34492.35 20768.74 19592.50 8194.86 14
casdiffmvs85.11 7085.14 6785.01 9187.20 21865.77 18287.75 15592.83 6177.84 3984.36 7592.38 8272.15 5393.93 14381.27 8290.48 10595.33 2
TranMVSNet+NR-MVSNet80.84 12980.31 12882.42 18987.85 19462.33 24787.74 15691.33 12480.55 1177.99 16489.86 14065.23 11892.62 19567.05 21275.24 29292.30 123
EI-MVSNet-Vis-set84.19 7583.81 7885.31 8288.18 18467.85 13987.66 15789.73 16780.05 1682.95 9389.59 14970.74 6694.82 10780.66 9084.72 17293.28 88
UniMVSNet (Re)81.60 11781.11 11383.09 16488.38 18064.41 21087.60 15893.02 4678.42 3478.56 14888.16 19069.78 7593.26 17269.58 18676.49 26791.60 142
CNLPA78.08 20076.79 20981.97 19790.40 10971.07 6987.59 15984.55 26866.03 26072.38 26089.64 14657.56 20586.04 30859.61 26883.35 19288.79 246
DTE-MVSNet76.99 22376.80 20877.54 28186.24 23153.06 34387.52 16090.66 13977.08 6072.50 25788.67 17460.48 18789.52 27057.33 29170.74 32690.05 202
无先验87.48 16188.98 19260.00 31794.12 13367.28 20788.97 238
FMVSNet278.20 19777.21 19981.20 21587.60 20562.89 24387.47 16289.02 19071.63 16975.29 22687.28 20954.80 22191.10 24662.38 24479.38 23989.61 219
EI-MVSNet-UG-set83.81 7783.38 8185.09 8987.87 19367.53 14787.44 16389.66 16979.74 1882.23 10289.41 15870.24 7194.74 11079.95 9483.92 18292.99 102
thisisatest053079.40 16977.76 18884.31 11887.69 20365.10 19787.36 16484.26 27570.04 19977.42 17388.26 18849.94 27594.79 10970.20 17784.70 17393.03 98
CANet_DTU80.61 14079.87 13482.83 17685.60 23963.17 23887.36 16488.65 20676.37 7975.88 20988.44 18253.51 23693.07 18473.30 15389.74 11692.25 125
test111179.43 16779.18 15580.15 23889.99 12053.31 34187.33 16677.05 34175.04 10580.23 12892.77 7948.97 28892.33 20968.87 19392.40 8394.81 17
baseline84.93 7284.98 6984.80 10287.30 21665.39 19187.30 16792.88 5877.62 4184.04 8192.26 8471.81 5593.96 13781.31 8190.30 10795.03 6
UniMVSNet_ETH3D79.10 17778.24 17581.70 20186.85 22360.24 27487.28 16888.79 19974.25 12676.84 18590.53 12749.48 28091.56 23267.98 20082.15 20793.29 87
anonymousdsp78.60 18877.15 20082.98 17180.51 32667.08 15687.24 16989.53 17165.66 26475.16 22887.19 21552.52 24092.25 21177.17 11879.34 24089.61 219
UniMVSNet_NR-MVSNet81.88 10881.54 10882.92 17388.46 17763.46 22987.13 17092.37 7980.19 1478.38 15289.14 16171.66 5893.05 18570.05 17976.46 26892.25 125
DPM-MVS84.93 7284.29 7786.84 5390.20 11273.04 2487.12 17193.04 4369.80 20482.85 9691.22 10873.06 4696.02 5176.72 12594.63 5491.46 150
v114480.03 15479.03 15783.01 16983.78 26864.51 20587.11 17290.57 14271.96 16578.08 16386.20 24661.41 16993.94 14074.93 13877.23 25590.60 177
v2v48280.23 15079.29 15083.05 16783.62 27064.14 21487.04 17389.97 15973.61 14078.18 16087.22 21361.10 17793.82 14776.11 12776.78 26591.18 156
DU-MVS81.12 12580.52 12482.90 17487.80 19763.46 22987.02 17491.87 10579.01 2878.38 15289.07 16365.02 12093.05 18570.05 17976.46 26892.20 127
v14419279.47 16578.37 17182.78 18283.35 27563.96 21786.96 17590.36 14969.99 20077.50 17185.67 25560.66 18493.77 15174.27 14276.58 26690.62 175
Fast-Effi-MVS+-dtu78.02 20376.49 21682.62 18683.16 28366.96 16186.94 17687.45 23172.45 15771.49 26984.17 27854.79 22491.58 23167.61 20380.31 22989.30 226
v119279.59 16278.43 17083.07 16683.55 27264.52 20486.93 17790.58 14170.83 18477.78 16785.90 24959.15 19493.94 14073.96 14577.19 25790.76 170
EPNet_dtu75.46 24574.86 23677.23 28682.57 29754.60 32986.89 17883.09 29471.64 16866.25 32085.86 25155.99 21688.04 29454.92 30286.55 15489.05 233
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
原ACMM286.86 179
VPA-MVSNet80.60 14180.55 12380.76 22688.07 18860.80 26686.86 17991.58 11675.67 9380.24 12789.45 15663.34 13490.25 26070.51 17579.22 24291.23 155
v192192079.22 17378.03 17882.80 17983.30 27763.94 21886.80 18190.33 15069.91 20277.48 17285.53 25858.44 19893.75 15373.60 14776.85 26390.71 173
IterMVS-LS80.06 15379.38 14682.11 19385.89 23463.20 23686.79 18289.34 17574.19 12775.45 21886.72 22566.62 10192.39 20472.58 16076.86 26290.75 171
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
TransMVSNet (Re)75.39 24874.56 24077.86 27385.50 24157.10 30586.78 18386.09 25272.17 16371.53 26887.34 20863.01 14489.31 27456.84 29561.83 34987.17 279
Baseline_NR-MVSNet78.15 19978.33 17377.61 27985.79 23556.21 32086.78 18385.76 25573.60 14177.93 16587.57 20365.02 12088.99 27967.14 21175.33 28987.63 266
PAPR81.66 11680.89 11883.99 13590.27 11064.00 21686.76 18591.77 11268.84 23077.13 18489.50 15067.63 9394.88 10567.55 20488.52 12993.09 95
Vis-MVSNet (Re-imp)78.36 19378.45 16878.07 27288.64 17151.78 34786.70 18679.63 32674.14 12975.11 23090.83 12161.29 17389.75 26658.10 28491.60 9192.69 110
pmmvs674.69 25173.39 25278.61 26381.38 31557.48 30186.64 18787.95 21964.99 27270.18 27986.61 23350.43 27089.52 27062.12 24870.18 32888.83 244
v124078.99 18077.78 18682.64 18583.21 27963.54 22686.62 18890.30 15269.74 20877.33 17585.68 25457.04 21293.76 15273.13 15676.92 25990.62 175
MTAPA87.23 3387.00 3487.90 2194.18 3774.25 586.58 18992.02 9479.45 2085.88 4394.80 1668.07 8896.21 4386.69 2495.34 3693.23 89
旧先验286.56 19058.10 33287.04 3588.98 28074.07 144
FMVSNet377.88 20776.85 20780.97 22286.84 22462.36 24686.52 19188.77 20071.13 17975.34 22286.66 23254.07 23291.10 24662.72 24079.57 23589.45 222
dcpmvs_285.63 6186.15 5384.06 12791.71 8664.94 19986.47 19291.87 10573.63 13986.60 3993.02 7076.57 1691.87 22583.36 5692.15 8495.35 1
pm-mvs177.25 22176.68 21478.93 25984.22 26058.62 28486.41 19388.36 21171.37 17773.31 24888.01 19661.22 17589.15 27764.24 23273.01 31289.03 234
EI-MVSNet80.52 14479.98 13282.12 19284.28 25863.19 23786.41 19388.95 19574.18 12878.69 14487.54 20566.62 10192.43 20272.57 16180.57 22690.74 172
CVMVSNet72.99 26972.58 25974.25 31184.28 25850.85 35386.41 19383.45 28844.56 35973.23 25087.54 20549.38 28185.70 31065.90 22078.44 24786.19 298
NR-MVSNet80.23 15079.38 14682.78 18287.80 19763.34 23286.31 19691.09 13279.01 2872.17 26289.07 16367.20 9892.81 19466.08 21975.65 27992.20 127
v14878.72 18577.80 18581.47 20682.73 29361.96 25386.30 19788.08 21673.26 14976.18 20485.47 26062.46 15192.36 20671.92 16473.82 30590.09 197
新几何286.29 198
test_yl81.17 12380.47 12583.24 15789.13 15263.62 22286.21 19989.95 16072.43 16081.78 10989.61 14757.50 20693.58 15770.75 17186.90 14892.52 113
DCV-MVSNet81.17 12380.47 12583.24 15789.13 15263.62 22286.21 19989.95 16072.43 16081.78 10989.61 14757.50 20693.58 15770.75 17186.90 14892.52 113
PVSNet_BlendedMVS80.60 14180.02 13182.36 19188.85 15965.40 18986.16 20192.00 9769.34 21378.11 16186.09 24866.02 11194.27 12371.52 16582.06 20887.39 272
MVS_Test83.15 8983.06 8583.41 15186.86 22263.21 23586.11 20292.00 9774.31 12382.87 9589.44 15770.03 7293.21 17377.39 11688.50 13093.81 63
BH-untuned79.47 16578.60 16582.05 19489.19 15065.91 17686.07 20388.52 20972.18 16275.42 21987.69 20061.15 17693.54 16160.38 26286.83 15086.70 291
MVS_111021_HR85.14 6984.75 7386.32 6591.65 8772.70 3185.98 20490.33 15076.11 8482.08 10391.61 9871.36 6194.17 13281.02 8392.58 7992.08 131
jason81.39 12180.29 12984.70 10486.63 22869.90 9485.95 20586.77 24163.24 28881.07 11989.47 15261.08 17892.15 21478.33 10790.07 11392.05 132
jason: jason.
test_040272.79 27170.44 27879.84 24488.13 18565.99 17485.93 20684.29 27365.57 26567.40 30685.49 25946.92 29892.61 19635.88 36274.38 29980.94 346
OurMVSNet-221017-074.26 25472.42 26179.80 24583.76 26959.59 27985.92 20786.64 24266.39 25566.96 30987.58 20239.46 33891.60 23065.76 22269.27 33088.22 256
hse-mvs281.72 11180.94 11784.07 12688.72 16867.68 14485.87 20887.26 23476.02 8684.67 6588.22 18961.54 16593.48 16482.71 6973.44 30991.06 160
EG-PatchMatch MVS74.04 25771.82 26580.71 22784.92 25167.42 14985.86 20988.08 21666.04 25964.22 33283.85 28235.10 35392.56 19857.44 28980.83 22182.16 340
AUN-MVS79.21 17477.60 19384.05 12988.71 16967.61 14585.84 21087.26 23469.08 22277.23 17988.14 19453.20 23993.47 16575.50 13673.45 30891.06 160
thres100view90076.50 23075.55 22779.33 25489.52 13056.99 30685.83 21183.23 29173.94 13276.32 20087.12 21751.89 25491.95 22048.33 33283.75 18589.07 228
CLD-MVS82.31 10181.65 10784.29 11988.47 17667.73 14285.81 21292.35 8075.78 8978.33 15486.58 23664.01 12894.35 12076.05 12887.48 14190.79 169
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
SixPastTwentyTwo73.37 26271.26 27279.70 24785.08 24957.89 29485.57 21383.56 28471.03 18265.66 32285.88 25042.10 32992.57 19759.11 27363.34 34788.65 250
xiu_mvs_v1_base_debu80.80 13479.72 13884.03 13287.35 21170.19 8985.56 21488.77 20069.06 22381.83 10588.16 19050.91 26392.85 19178.29 10887.56 13889.06 230
xiu_mvs_v1_base80.80 13479.72 13884.03 13287.35 21170.19 8985.56 21488.77 20069.06 22381.83 10588.16 19050.91 26392.85 19178.29 10887.56 13889.06 230
xiu_mvs_v1_base_debi80.80 13479.72 13884.03 13287.35 21170.19 8985.56 21488.77 20069.06 22381.83 10588.16 19050.91 26392.85 19178.29 10887.56 13889.06 230
V4279.38 17178.24 17582.83 17681.10 32065.50 18685.55 21789.82 16371.57 17478.21 15886.12 24760.66 18493.18 17875.64 13275.46 28589.81 214
lupinMVS81.39 12180.27 13084.76 10387.35 21170.21 8785.55 21786.41 24562.85 29581.32 11388.61 17661.68 16292.24 21278.41 10690.26 10891.83 137
Fast-Effi-MVS+80.81 13279.92 13383.47 14788.85 15964.51 20585.53 21989.39 17470.79 18678.49 15085.06 26967.54 9493.58 15767.03 21386.58 15392.32 121
thres600view776.50 23075.44 22879.68 24889.40 13557.16 30385.53 21983.23 29173.79 13776.26 20187.09 21851.89 25491.89 22348.05 33783.72 18890.00 203
DELS-MVS85.41 6585.30 6585.77 7688.49 17567.93 13885.52 22193.44 3178.70 3183.63 8889.03 16574.57 2995.71 6280.26 9394.04 6693.66 68
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
tfpn200view976.42 23375.37 23279.55 25389.13 15257.65 29885.17 22283.60 28273.41 14776.45 19486.39 24252.12 24791.95 22048.33 33283.75 18589.07 228
thres40076.50 23075.37 23279.86 24389.13 15257.65 29885.17 22283.60 28273.41 14776.45 19486.39 24252.12 24791.95 22048.33 33283.75 18590.00 203
MVS_111021_LR82.61 9982.11 9884.11 12388.82 16271.58 5985.15 22486.16 25074.69 11480.47 12591.04 11562.29 15490.55 25780.33 9290.08 11290.20 190
baseline176.98 22476.75 21277.66 27788.13 18555.66 32585.12 22581.89 30373.04 15376.79 18788.90 16862.43 15287.78 29763.30 23871.18 32489.55 221
WR-MVS79.49 16479.22 15380.27 23688.79 16558.35 28585.06 22688.61 20878.56 3277.65 16988.34 18463.81 13190.66 25664.98 22877.22 25691.80 140
ET-MVSNet_ETH3D78.63 18776.63 21584.64 10586.73 22769.47 10485.01 22784.61 26769.54 20966.51 31886.59 23450.16 27291.75 22776.26 12684.24 18092.69 110
OpenMVS_ROBcopyleft64.09 1970.56 28668.19 29177.65 27880.26 32759.41 28185.01 22782.96 29658.76 32865.43 32482.33 30137.63 34791.23 24245.34 34976.03 27582.32 338
BH-RMVSNet79.61 16078.44 16983.14 16289.38 13765.93 17584.95 22987.15 23673.56 14278.19 15989.79 14256.67 21493.36 16959.53 26986.74 15190.13 193
BH-w/o78.21 19677.33 19880.84 22488.81 16365.13 19684.87 23087.85 22369.75 20674.52 23984.74 27361.34 17193.11 18258.24 28385.84 16584.27 321
TDRefinement67.49 30564.34 31476.92 28873.47 36361.07 26284.86 23182.98 29559.77 31958.30 35285.13 26726.06 36387.89 29547.92 33860.59 35381.81 342
Anonymous20240521178.25 19477.01 20281.99 19691.03 9460.67 26884.77 23283.90 27970.65 19180.00 13091.20 10941.08 33491.43 23665.21 22585.26 16793.85 59
TAMVS78.89 18377.51 19583.03 16887.80 19767.79 14184.72 23385.05 26267.63 24076.75 18987.70 19962.25 15590.82 25258.53 28087.13 14590.49 181
131476.53 22975.30 23480.21 23783.93 26662.32 24884.66 23488.81 19860.23 31570.16 28184.07 28055.30 21990.73 25567.37 20683.21 19487.59 269
112180.84 12979.77 13684.05 12993.11 6070.78 7984.66 23485.42 25857.37 33881.76 11192.02 8763.41 13394.12 13367.28 20792.93 7387.26 277
MVS78.19 19876.99 20481.78 19985.66 23766.99 15784.66 23490.47 14455.08 34872.02 26485.27 26363.83 13094.11 13566.10 21889.80 11584.24 322
tfpnnormal74.39 25273.16 25578.08 27186.10 23358.05 28984.65 23787.53 22870.32 19571.22 27185.63 25654.97 22089.86 26443.03 35375.02 29386.32 295
TR-MVS77.44 21576.18 22181.20 21588.24 18363.24 23484.61 23886.40 24667.55 24277.81 16686.48 24054.10 23193.15 17957.75 28782.72 20287.20 278
AllTest70.96 28268.09 29479.58 25185.15 24563.62 22284.58 23979.83 32462.31 30160.32 34686.73 22332.02 35888.96 28250.28 32271.57 32286.15 299
EU-MVSNet68.53 30267.61 30271.31 32878.51 34447.01 36284.47 24084.27 27442.27 36066.44 31984.79 27240.44 33683.76 32358.76 27868.54 33583.17 331
VNet82.21 10282.41 9381.62 20290.82 10060.93 26384.47 24089.78 16476.36 8084.07 8091.88 9164.71 12490.26 25970.68 17388.89 12293.66 68
xiu_mvs_v2_base81.69 11381.05 11483.60 14489.15 15168.03 13784.46 24290.02 15870.67 18981.30 11686.53 23963.17 13994.19 13075.60 13488.54 12888.57 252
VPNet78.69 18678.66 16478.76 26188.31 18255.72 32484.45 24386.63 24376.79 6778.26 15690.55 12659.30 19389.70 26866.63 21477.05 25890.88 167
PVSNet_Blended80.98 12680.34 12782.90 17488.85 15965.40 18984.43 24492.00 9767.62 24178.11 16185.05 27066.02 11194.27 12371.52 16589.50 11789.01 235
MVP-Stereo76.12 23774.46 24381.13 21885.37 24269.79 9684.42 24587.95 21965.03 27067.46 30485.33 26253.28 23891.73 22958.01 28583.27 19381.85 341
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
CDS-MVSNet79.07 17877.70 19083.17 16187.60 20568.23 13384.40 24686.20 24967.49 24376.36 19986.54 23861.54 16590.79 25361.86 25187.33 14290.49 181
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
K. test v371.19 28068.51 28879.21 25783.04 28657.78 29784.35 24776.91 34272.90 15662.99 33982.86 29539.27 33991.09 24861.65 25352.66 36188.75 247
PS-MVSNAJ81.69 11381.02 11583.70 14389.51 13168.21 13484.28 24890.09 15770.79 18681.26 11785.62 25763.15 14094.29 12175.62 13388.87 12388.59 251
patch_mono-283.65 8084.54 7580.99 22190.06 11965.83 17884.21 24988.74 20471.60 17385.01 5492.44 8174.51 3083.50 32682.15 7692.15 8493.64 75
test22291.50 8968.26 13284.16 25083.20 29354.63 34979.74 13191.63 9758.97 19591.42 9486.77 289
testdata184.14 25175.71 90
MVS_030472.48 27270.89 27577.24 28582.20 30359.68 27784.11 25283.49 28667.10 24566.87 31180.59 31835.00 35487.40 29959.07 27479.58 23484.63 319
c3_l78.75 18477.91 18181.26 21282.89 29061.56 25884.09 25389.13 18769.97 20175.56 21384.29 27766.36 10592.09 21673.47 15175.48 28390.12 194
MVSTER79.01 17977.88 18382.38 19083.07 28464.80 20184.08 25488.95 19569.01 22678.69 14487.17 21654.70 22592.43 20274.69 13980.57 22689.89 210
ab-mvs79.51 16378.97 15981.14 21788.46 17760.91 26483.84 25589.24 18170.36 19479.03 13888.87 17063.23 13890.21 26165.12 22682.57 20492.28 124
PAPM77.68 21276.40 21981.51 20587.29 21761.85 25483.78 25689.59 17064.74 27371.23 27088.70 17262.59 14893.66 15652.66 31187.03 14789.01 235
diffmvs82.10 10381.88 10582.76 18483.00 28763.78 22183.68 25789.76 16572.94 15582.02 10489.85 14165.96 11390.79 25382.38 7587.30 14393.71 67
miper_ehance_all_eth78.59 18977.76 18881.08 21982.66 29561.56 25883.65 25889.15 18568.87 22975.55 21483.79 28566.49 10392.03 21773.25 15476.39 27089.64 218
1112_ss77.40 21776.43 21880.32 23589.11 15660.41 27383.65 25887.72 22562.13 30373.05 25286.72 22562.58 14989.97 26362.11 24980.80 22290.59 178
PCF-MVS73.52 780.38 14678.84 16185.01 9187.71 20168.99 11283.65 25891.46 12263.00 29277.77 16890.28 12966.10 10895.09 9461.40 25588.22 13390.94 166
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
XVG-ACMP-BASELINE76.11 23874.27 24581.62 20283.20 28064.67 20383.60 26189.75 16669.75 20671.85 26587.09 21832.78 35792.11 21569.99 18180.43 22888.09 258
cl2278.07 20177.01 20281.23 21382.37 30261.83 25583.55 26287.98 21868.96 22775.06 23283.87 28161.40 17091.88 22473.53 14876.39 27089.98 206
XVG-OURS-SEG-HR80.81 13279.76 13783.96 13785.60 23968.78 11683.54 26390.50 14370.66 19076.71 19091.66 9460.69 18391.26 24076.94 12081.58 21491.83 137
IB-MVS68.01 1575.85 24173.36 25383.31 15384.76 25266.03 17283.38 26485.06 26170.21 19869.40 29181.05 31245.76 30994.66 11265.10 22775.49 28289.25 227
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
HY-MVS69.67 1277.95 20577.15 20080.36 23387.57 20960.21 27583.37 26587.78 22466.11 25775.37 22187.06 22063.27 13690.48 25861.38 25682.43 20590.40 185
Anonymous2024052168.80 29967.22 30573.55 31474.33 35854.11 33383.18 26685.61 25658.15 33161.68 34280.94 31530.71 36181.27 33757.00 29473.34 31185.28 310
eth_miper_zixun_eth77.92 20676.69 21381.61 20483.00 28761.98 25283.15 26789.20 18369.52 21074.86 23684.35 27661.76 16192.56 19871.50 16772.89 31390.28 188
cl____77.72 21076.76 21080.58 22982.49 29960.48 27183.09 26887.87 22169.22 21674.38 24185.22 26562.10 15891.53 23371.09 16975.41 28689.73 217
DIV-MVS_self_test77.72 21076.76 21080.58 22982.48 30060.48 27183.09 26887.86 22269.22 21674.38 24185.24 26462.10 15891.53 23371.09 16975.40 28789.74 216
thres20075.55 24474.47 24278.82 26087.78 20057.85 29583.07 27083.51 28572.44 15975.84 21084.42 27552.08 24991.75 22747.41 33983.64 18986.86 287
XVG-OURS80.41 14579.23 15283.97 13685.64 23869.02 11083.03 27190.39 14571.09 18177.63 17091.49 10254.62 22791.35 23875.71 13183.47 19191.54 144
miper_enhance_ethall77.87 20876.86 20680.92 22381.65 30961.38 26082.68 27288.98 19265.52 26675.47 21582.30 30265.76 11592.00 21972.95 15776.39 27089.39 223
mvs_anonymous79.42 16879.11 15680.34 23484.45 25757.97 29282.59 27387.62 22667.40 24476.17 20688.56 17968.47 8789.59 26970.65 17486.05 16193.47 82
baseline275.70 24273.83 25081.30 21183.26 27861.79 25682.57 27480.65 31466.81 24666.88 31083.42 29057.86 20292.19 21363.47 23579.57 23589.91 208
cascas76.72 22874.64 23882.99 17085.78 23665.88 17782.33 27589.21 18260.85 31172.74 25481.02 31347.28 29693.75 15367.48 20585.02 16889.34 224
RPSCF73.23 26671.46 26778.54 26582.50 29859.85 27682.18 27682.84 29758.96 32671.15 27289.41 15845.48 31284.77 31858.82 27771.83 32091.02 164
thisisatest051577.33 21875.38 23183.18 16085.27 24363.80 22082.11 27783.27 29065.06 26975.91 20883.84 28349.54 27994.27 12367.24 20986.19 15991.48 149
pmmvs-eth3d70.50 28767.83 29878.52 26677.37 34866.18 17181.82 27881.51 30758.90 32763.90 33580.42 32042.69 32386.28 30758.56 27965.30 34383.11 333
MS-PatchMatch73.83 25972.67 25877.30 28483.87 26766.02 17381.82 27884.66 26661.37 30968.61 29782.82 29647.29 29588.21 29159.27 27084.32 17877.68 355
pmmvs571.55 27870.20 28175.61 29777.83 34556.39 31681.74 28080.89 31057.76 33467.46 30484.49 27449.26 28485.32 31457.08 29375.29 29085.11 314
Test_1112_low_res76.40 23475.44 22879.27 25589.28 14658.09 28881.69 28187.07 23759.53 32272.48 25886.67 23161.30 17289.33 27360.81 26180.15 23190.41 184
IterMVS74.29 25372.94 25778.35 26881.53 31263.49 22881.58 28282.49 29968.06 23969.99 28483.69 28751.66 25885.54 31165.85 22171.64 32186.01 303
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
IterMVS-SCA-FT75.43 24673.87 24980.11 23982.69 29464.85 20081.57 28383.47 28769.16 22070.49 27584.15 27951.95 25288.15 29269.23 18872.14 31887.34 274
pmmvs474.03 25871.91 26480.39 23281.96 30668.32 13081.45 28482.14 30159.32 32369.87 28785.13 26752.40 24388.13 29360.21 26474.74 29684.73 318
GA-MVS76.87 22675.17 23581.97 19782.75 29262.58 24481.44 28586.35 24872.16 16474.74 23782.89 29446.20 30492.02 21868.85 19481.09 21891.30 154
CostFormer75.24 24973.90 24879.27 25582.65 29658.27 28780.80 28682.73 29861.57 30675.33 22583.13 29255.52 21791.07 24964.98 22878.34 24988.45 253
MIMVSNet168.58 30166.78 30873.98 31380.07 33051.82 34680.77 28784.37 27064.40 27759.75 34982.16 30536.47 34983.63 32542.73 35470.33 32786.48 294
CL-MVSNet_self_test72.37 27571.46 26775.09 30379.49 33953.53 33780.76 28885.01 26369.12 22170.51 27482.05 30657.92 20184.13 32152.27 31266.00 34187.60 267
MSDG73.36 26470.99 27380.49 23184.51 25665.80 18080.71 28986.13 25165.70 26365.46 32383.74 28644.60 31390.91 25151.13 31776.89 26184.74 317
tpm273.26 26571.46 26778.63 26283.34 27656.71 31180.65 29080.40 31956.63 34273.55 24682.02 30751.80 25691.24 24156.35 29878.42 24887.95 259
XXY-MVS75.41 24775.56 22674.96 30483.59 27157.82 29680.59 29183.87 28066.54 25474.93 23588.31 18563.24 13780.09 34162.16 24776.85 26386.97 285
EGC-MVSNET52.07 33247.05 33667.14 34183.51 27360.71 26780.50 29267.75 3640.07 3770.43 37875.85 34924.26 36581.54 33528.82 36562.25 34859.16 365
HyFIR lowres test77.53 21475.40 23083.94 13889.59 12766.62 16480.36 29388.64 20756.29 34476.45 19485.17 26657.64 20493.28 17161.34 25783.10 19791.91 135
D2MVS74.82 25073.21 25479.64 25079.81 33362.56 24580.34 29487.35 23264.37 27868.86 29482.66 29846.37 30190.10 26267.91 20181.24 21786.25 296
TinyColmap67.30 30864.81 31274.76 30781.92 30756.68 31280.29 29581.49 30860.33 31356.27 35883.22 29124.77 36487.66 29845.52 34769.47 32979.95 350
LCM-MVSNet-Re77.05 22276.94 20577.36 28287.20 21851.60 34880.06 29680.46 31875.20 10267.69 30286.72 22562.48 15088.98 28063.44 23689.25 12091.51 145
FMVSNet569.50 29467.96 29574.15 31282.97 28955.35 32680.01 29782.12 30262.56 29963.02 33781.53 30936.92 34881.92 33348.42 33174.06 30185.17 313
SCA74.22 25572.33 26279.91 24284.05 26462.17 25079.96 29879.29 32866.30 25672.38 26080.13 32251.95 25288.60 28759.25 27177.67 25388.96 239
tpmrst72.39 27372.13 26373.18 31980.54 32549.91 35679.91 29979.08 32963.11 29071.69 26779.95 32455.32 21882.77 33165.66 22373.89 30386.87 286
PatchmatchNetpermissive73.12 26771.33 27078.49 26783.18 28160.85 26579.63 30078.57 33064.13 28071.73 26679.81 32751.20 26185.97 30957.40 29076.36 27388.66 249
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
PatchMatch-RL72.38 27470.90 27476.80 29088.60 17267.38 15179.53 30176.17 34462.75 29769.36 29282.00 30845.51 31184.89 31753.62 30780.58 22578.12 354
CMPMVSbinary51.72 2170.19 29068.16 29276.28 29273.15 36557.55 30079.47 30283.92 27848.02 35856.48 35784.81 27143.13 32086.42 30662.67 24381.81 21284.89 315
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
GG-mvs-BLEND75.38 30181.59 31155.80 32379.32 30369.63 35967.19 30773.67 35343.24 31988.90 28450.41 31984.50 17481.45 343
LTVRE_ROB69.57 1376.25 23674.54 24181.41 20788.60 17264.38 21179.24 30489.12 18870.76 18869.79 28987.86 19749.09 28593.20 17556.21 29980.16 23086.65 292
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
tpm72.37 27571.71 26674.35 31082.19 30452.00 34579.22 30577.29 33964.56 27572.95 25383.68 28851.35 25983.26 32958.33 28275.80 27787.81 263
ppachtmachnet_test70.04 29167.34 30478.14 27079.80 33461.13 26179.19 30680.59 31559.16 32565.27 32579.29 32846.75 30087.29 30049.33 32866.72 33786.00 305
USDC70.33 28868.37 28976.21 29380.60 32456.23 31979.19 30686.49 24460.89 31061.29 34385.47 26031.78 36089.47 27253.37 30876.21 27482.94 337
PM-MVS66.41 31364.14 31573.20 31873.92 36056.45 31478.97 30864.96 36963.88 28764.72 32980.24 32119.84 36983.44 32766.24 21564.52 34579.71 351
tpmvs71.09 28169.29 28476.49 29182.04 30556.04 32178.92 30981.37 30964.05 28367.18 30878.28 33649.74 27889.77 26549.67 32772.37 31583.67 327
test_post178.90 3105.43 37648.81 29185.44 31359.25 271
CHOSEN 1792x268877.63 21375.69 22483.44 14889.98 12168.58 12778.70 31187.50 22956.38 34375.80 21186.84 22158.67 19691.40 23761.58 25485.75 16690.34 186
test-LLR72.94 27072.43 26074.48 30881.35 31658.04 29078.38 31277.46 33666.66 25069.95 28579.00 33148.06 29279.24 34266.13 21684.83 17086.15 299
TESTMET0.1,169.89 29369.00 28672.55 32079.27 34256.85 30778.38 31274.71 35057.64 33568.09 29977.19 34337.75 34676.70 35363.92 23384.09 18184.10 325
test-mter71.41 27970.39 28074.48 30881.35 31658.04 29078.38 31277.46 33660.32 31469.95 28579.00 33136.08 35179.24 34266.13 21684.83 17086.15 299
Anonymous2023120668.60 30067.80 29971.02 32980.23 32850.75 35478.30 31580.47 31756.79 34166.11 32182.63 29946.35 30278.95 34443.62 35275.70 27883.36 330
tpm cat170.57 28568.31 29077.35 28382.41 30157.95 29378.08 31680.22 32252.04 35468.54 29877.66 34152.00 25187.84 29651.77 31372.07 31986.25 296
our_test_369.14 29667.00 30675.57 29879.80 33458.80 28277.96 31777.81 33359.55 32162.90 34078.25 33747.43 29483.97 32251.71 31467.58 33683.93 326
KD-MVS_self_test68.81 29867.59 30372.46 32174.29 35945.45 36377.93 31887.00 23863.12 28963.99 33478.99 33342.32 32584.77 31856.55 29764.09 34687.16 281
WTY-MVS75.65 24375.68 22575.57 29886.40 23056.82 30877.92 31982.40 30065.10 26876.18 20487.72 19863.13 14380.90 33860.31 26381.96 20989.00 237
test20.0367.45 30666.95 30768.94 33575.48 35544.84 36577.50 32077.67 33466.66 25063.01 33883.80 28447.02 29778.40 34642.53 35568.86 33483.58 328
EPMVS69.02 29768.16 29271.59 32379.61 33749.80 35877.40 32166.93 36562.82 29670.01 28279.05 32945.79 30877.86 35056.58 29675.26 29187.13 282
gg-mvs-nofinetune69.95 29267.96 29575.94 29483.07 28454.51 33177.23 32270.29 35763.11 29070.32 27762.33 36043.62 31888.69 28653.88 30687.76 13584.62 320
MDTV_nov1_ep1369.97 28283.18 28153.48 33877.10 32380.18 32360.45 31269.33 29380.44 31948.89 29086.90 30251.60 31578.51 246
LF4IMVS64.02 32262.19 32569.50 33470.90 36753.29 34276.13 32477.18 34052.65 35358.59 35080.98 31423.55 36676.52 35453.06 31066.66 33878.68 353
sss73.60 26073.64 25173.51 31582.80 29155.01 32776.12 32581.69 30662.47 30074.68 23885.85 25257.32 20878.11 34860.86 26080.93 21987.39 272
testgi66.67 31166.53 30967.08 34275.62 35441.69 36975.93 32676.50 34366.11 25765.20 32886.59 23435.72 35274.71 36143.71 35173.38 31084.84 316
CR-MVSNet73.37 26271.27 27179.67 24981.32 31865.19 19475.92 32780.30 32059.92 31872.73 25581.19 31052.50 24186.69 30359.84 26677.71 25187.11 283
RPMNet73.51 26170.49 27782.58 18781.32 31865.19 19475.92 32792.27 8357.60 33672.73 25576.45 34652.30 24495.43 7448.14 33677.71 25187.11 283
MIMVSNet70.69 28469.30 28374.88 30584.52 25556.35 31875.87 32979.42 32764.59 27467.76 30082.41 30041.10 33381.54 33546.64 34381.34 21586.75 290
test0.0.03 168.00 30467.69 30168.90 33677.55 34647.43 36075.70 33072.95 35466.66 25066.56 31482.29 30348.06 29275.87 35744.97 35074.51 29883.41 329
PMMVS69.34 29568.67 28771.35 32775.67 35362.03 25175.17 33173.46 35250.00 35768.68 29579.05 32952.07 25078.13 34761.16 25882.77 20073.90 358
UnsupCasMVSNet_eth67.33 30765.99 31071.37 32573.48 36251.47 35075.16 33285.19 26065.20 26760.78 34580.93 31742.35 32477.20 35257.12 29253.69 36085.44 308
MDTV_nov1_ep13_2view37.79 37175.16 33255.10 34766.53 31549.34 28253.98 30587.94 260
pmmvs357.79 32754.26 33168.37 33964.02 37156.72 31075.12 33465.17 36740.20 36252.93 36169.86 35820.36 36875.48 35945.45 34855.25 35972.90 359
dp66.80 30965.43 31170.90 33079.74 33648.82 35975.12 33474.77 34859.61 32064.08 33377.23 34242.89 32180.72 33948.86 33066.58 33983.16 332
Patchmtry70.74 28369.16 28575.49 30080.72 32254.07 33474.94 33680.30 32058.34 33070.01 28281.19 31052.50 24186.54 30453.37 30871.09 32585.87 306
PVSNet64.34 1872.08 27770.87 27675.69 29686.21 23256.44 31574.37 33780.73 31362.06 30470.17 28082.23 30442.86 32283.31 32854.77 30384.45 17787.32 275
MDA-MVSNet-bldmvs66.68 31063.66 31875.75 29579.28 34160.56 27073.92 33878.35 33164.43 27650.13 36379.87 32644.02 31683.67 32446.10 34556.86 35683.03 335
UnsupCasMVSNet_bld63.70 32361.53 32770.21 33273.69 36151.39 35172.82 33981.89 30355.63 34657.81 35371.80 35638.67 34178.61 34549.26 32952.21 36280.63 347
PatchT68.46 30367.85 29770.29 33180.70 32343.93 36672.47 34074.88 34760.15 31670.55 27376.57 34549.94 27581.59 33450.58 31874.83 29585.34 309
miper_lstm_enhance74.11 25673.11 25677.13 28780.11 32959.62 27872.23 34186.92 24066.76 24870.40 27682.92 29356.93 21382.92 33069.06 19172.63 31488.87 242
MVS-HIRNet59.14 32657.67 32963.57 34481.65 30943.50 36771.73 34265.06 36839.59 36451.43 36257.73 36438.34 34382.58 33239.53 35973.95 30264.62 363
Patchmatch-RL test70.24 28967.78 30077.61 27977.43 34759.57 28071.16 34370.33 35662.94 29468.65 29672.77 35450.62 26785.49 31269.58 18666.58 33987.77 264
test1236.12 3468.11 3490.14 3600.06 3840.09 38471.05 3440.03 3850.04 3790.25 3801.30 3790.05 3830.03 3800.21 3780.01 3780.29 375
ANet_high50.57 33446.10 33763.99 34348.67 37739.13 37070.99 34580.85 31161.39 30831.18 36857.70 36517.02 37173.65 36531.22 36415.89 37479.18 352
KD-MVS_2432*160066.22 31563.89 31673.21 31675.47 35653.42 33970.76 34684.35 27164.10 28166.52 31678.52 33434.55 35584.98 31550.40 32050.33 36481.23 344
miper_refine_blended66.22 31563.89 31673.21 31675.47 35653.42 33970.76 34684.35 27164.10 28166.52 31678.52 33434.55 35584.98 31550.40 32050.33 36481.23 344
testmvs6.04 3478.02 3500.10 3610.08 3830.03 38569.74 3480.04 3840.05 3780.31 3791.68 3780.02 3840.04 3790.24 3770.02 3770.25 376
N_pmnet52.79 33153.26 33251.40 35178.99 3437.68 38269.52 3493.89 38251.63 35657.01 35574.98 35140.83 33565.96 36937.78 36164.67 34480.56 349
FPMVS53.68 33051.64 33359.81 34765.08 37051.03 35269.48 35069.58 36041.46 36140.67 36572.32 35516.46 37270.00 36724.24 36965.42 34258.40 366
DSMNet-mixed57.77 32856.90 33060.38 34667.70 36935.61 37269.18 35153.97 37432.30 36957.49 35479.88 32540.39 33768.57 36838.78 36072.37 31576.97 356
new-patchmatchnet61.73 32461.73 32661.70 34572.74 36624.50 37969.16 35278.03 33261.40 30756.72 35675.53 35038.42 34276.48 35545.95 34657.67 35584.13 324
YYNet165.03 31862.91 32271.38 32475.85 35256.60 31369.12 35374.66 35157.28 33954.12 35977.87 33945.85 30774.48 36249.95 32561.52 35183.05 334
MDA-MVSNet_test_wron65.03 31862.92 32171.37 32575.93 35156.73 30969.09 35474.73 34957.28 33954.03 36077.89 33845.88 30674.39 36349.89 32661.55 35082.99 336
PVSNet_057.27 2061.67 32559.27 32868.85 33779.61 33757.44 30268.01 35573.44 35355.93 34558.54 35170.41 35744.58 31477.55 35147.01 34035.91 36771.55 360
ADS-MVSNet266.20 31763.33 31974.82 30679.92 33158.75 28367.55 35675.19 34653.37 35165.25 32675.86 34742.32 32580.53 34041.57 35668.91 33285.18 311
ADS-MVSNet64.36 32162.88 32368.78 33879.92 33147.17 36167.55 35671.18 35553.37 35165.25 32675.86 34742.32 32573.99 36441.57 35668.91 33285.18 311
LCM-MVSNet54.25 32949.68 33567.97 34053.73 37445.28 36466.85 35880.78 31235.96 36639.45 36662.23 3628.70 37878.06 34948.24 33551.20 36380.57 348
JIA-IIPM66.32 31462.82 32476.82 28977.09 34961.72 25765.34 35975.38 34558.04 33364.51 33062.32 36142.05 33086.51 30551.45 31669.22 33182.21 339
PMVScopyleft37.38 2244.16 33640.28 33955.82 34840.82 37942.54 36865.12 36063.99 37034.43 36724.48 37057.12 3663.92 38076.17 35617.10 37255.52 35848.75 367
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
new_pmnet50.91 33350.29 33452.78 35068.58 36834.94 37463.71 36156.63 37339.73 36344.95 36465.47 35921.93 36758.48 37034.98 36356.62 35764.92 362
Patchmatch-test64.82 32063.24 32069.57 33379.42 34049.82 35763.49 36269.05 36251.98 35559.95 34880.13 32250.91 26370.98 36640.66 35873.57 30687.90 261
ambc75.24 30273.16 36450.51 35563.05 36387.47 23064.28 33177.81 34017.80 37089.73 26757.88 28660.64 35285.49 307
CHOSEN 280x42066.51 31264.71 31371.90 32281.45 31363.52 22757.98 36468.95 36353.57 35062.59 34176.70 34446.22 30375.29 36055.25 30179.68 23376.88 357
E-PMN31.77 33830.64 34135.15 35552.87 37527.67 37657.09 36547.86 37624.64 37016.40 37533.05 37111.23 37554.90 37214.46 37418.15 37222.87 371
EMVS30.81 34029.65 34234.27 35650.96 37625.95 37856.58 36646.80 37724.01 37115.53 37630.68 37212.47 37454.43 37312.81 37517.05 37322.43 372
PMMVS240.82 33738.86 34046.69 35253.84 37316.45 38048.61 36749.92 37537.49 36531.67 36760.97 3638.14 37956.42 37128.42 36630.72 36967.19 361
wuyk23d16.82 34415.94 34719.46 35858.74 37231.45 37539.22 3683.74 3836.84 3746.04 3772.70 3771.27 38224.29 37710.54 37614.40 3762.63 374
tmp_tt18.61 34321.40 34610.23 3594.82 38210.11 38134.70 36930.74 3801.48 37623.91 37226.07 37328.42 36213.41 37827.12 36715.35 3757.17 373
Gipumacopyleft45.18 33541.86 33855.16 34977.03 35051.52 34932.50 37080.52 31632.46 36827.12 36935.02 3709.52 37775.50 35822.31 37060.21 35438.45 369
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
MVEpermissive26.22 2330.37 34125.89 34543.81 35344.55 37835.46 37328.87 37139.07 37818.20 37218.58 37440.18 3692.68 38147.37 37517.07 37323.78 37148.60 368
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
test_method31.52 33929.28 34338.23 35427.03 3816.50 38320.94 37262.21 3724.05 37522.35 37352.50 36713.33 37347.58 37427.04 36834.04 36860.62 364
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_5k19.96 34226.61 3440.00 3620.00 3850.00 3860.00 37389.26 1800.00 3800.00 38188.61 17661.62 1640.00 3810.00 3790.00 3790.00 377
pcd_1.5k_mvsjas5.26 3487.02 3510.00 3620.00 3850.00 3860.00 3730.00 3860.00 3800.00 3810.00 38063.15 1400.00 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-re7.23 3459.64 3480.00 3620.00 3850.00 3860.00 3730.00 3860.00 3800.00 38186.72 2250.00 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
MSC_two_6792asdad89.16 194.34 2975.53 292.99 4997.53 189.67 196.44 994.41 32
PC_three_145268.21 23892.02 1294.00 4882.09 595.98 5584.58 4096.68 294.95 7
No_MVS89.16 194.34 2975.53 292.99 4997.53 189.67 196.44 994.41 32
test_one_060195.07 771.46 6194.14 778.27 3792.05 1195.74 680.83 11
eth-test20.00 385
eth-test0.00 385
ZD-MVS94.38 2772.22 4892.67 6770.98 18387.75 3194.07 4574.01 4096.70 2684.66 3994.84 49
IU-MVS95.30 271.25 6392.95 5666.81 24692.39 688.94 1196.63 494.85 16
test_241102_TWO94.06 1277.24 5292.78 495.72 881.26 897.44 589.07 996.58 694.26 41
test_241102_ONE95.30 270.98 7094.06 1277.17 5693.10 195.39 1182.99 197.27 10
test_0728_THIRD78.38 3592.12 995.78 481.46 797.40 789.42 496.57 794.67 24
GSMVS88.96 239
test_part295.06 872.65 3391.80 13
sam_mvs151.32 26088.96 239
sam_mvs50.01 273
MTGPAbinary92.02 94
test_post5.46 37550.36 27184.24 320
patchmatchnet-post74.00 35251.12 26288.60 287
gm-plane-assit81.40 31453.83 33662.72 29880.94 31592.39 20463.40 237
test9_res84.90 3395.70 3192.87 105
agg_prior282.91 6595.45 3392.70 108
agg_prior92.85 6671.94 5491.78 11084.41 7294.93 98
TestCases79.58 25185.15 24563.62 22279.83 32462.31 30160.32 34686.73 22332.02 35888.96 28250.28 32271.57 32286.15 299
test_prior86.33 6392.61 7469.59 10092.97 5495.48 7093.91 55
新几何183.42 14993.13 5870.71 8085.48 25757.43 33781.80 10891.98 8863.28 13592.27 21064.60 23192.99 7287.27 276
旧先验191.96 8265.79 18186.37 24793.08 6969.31 8192.74 7688.74 248
原ACMM184.35 11693.01 6468.79 11592.44 7563.96 28681.09 11891.57 9966.06 11095.45 7267.19 21094.82 5288.81 245
testdata291.01 25062.37 245
segment_acmp73.08 45
testdata79.97 24190.90 9864.21 21384.71 26559.27 32485.40 4992.91 7162.02 16089.08 27868.95 19291.37 9586.63 293
test1286.80 5592.63 7370.70 8191.79 10982.71 9971.67 5796.16 4794.50 5793.54 80
plane_prior790.08 11568.51 128
plane_prior689.84 12468.70 12360.42 188
plane_prior592.44 7595.38 7978.71 10286.32 15791.33 151
plane_prior491.00 118
plane_prior368.60 12678.44 3378.92 141
plane_prior189.90 123
n20.00 386
nn0.00 386
door-mid69.98 358
lessismore_v078.97 25881.01 32157.15 30465.99 36661.16 34482.82 29639.12 34091.34 23959.67 26746.92 36688.43 254
LGP-MVS_train84.50 10989.23 14868.76 11791.94 10175.37 9876.64 19291.51 10054.29 22994.91 10078.44 10483.78 18389.83 212
test1192.23 86
door69.44 361
HQP5-MVS66.98 158
BP-MVS77.47 114
HQP4-MVS77.24 17895.11 9091.03 162
HQP3-MVS92.19 8985.99 163
HQP2-MVS60.17 191
NP-MVS89.62 12668.32 13090.24 130
ACMMP++_ref81.95 210
ACMMP++81.25 216
Test By Simon64.33 125
ITE_SJBPF78.22 26981.77 30860.57 26983.30 28969.25 21567.54 30387.20 21436.33 35087.28 30154.34 30474.62 29786.80 288
DeepMVS_CXcopyleft27.40 35740.17 38026.90 37724.59 38117.44 37323.95 37148.61 3689.77 37626.48 37618.06 37124.47 37028.83 370