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 bysorted bysort bysort bysort bysort bysort bysort by
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 12
test_241102_ONE95.30 270.98 7094.06 1277.17 5693.10 195.39 1182.99 197.27 10
test072695.27 571.25 6393.60 694.11 877.33 5092.81 395.79 380.98 9
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 8
test_241102_TWO94.06 1277.24 5292.78 495.72 881.26 897.44 589.07 996.58 694.26 41
IU-MVS95.30 271.25 6392.95 5666.81 24492.39 688.94 1196.63 494.85 17
SMA-MVScopyleft89.08 789.23 788.61 594.25 3373.73 1092.40 2393.63 2374.77 11292.29 795.97 274.28 3697.24 1188.58 1396.91 194.87 14
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
DPE-MVScopyleft89.48 589.98 488.01 1494.80 1172.69 3291.59 4394.10 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
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_THIRD78.38 3592.12 995.78 481.46 797.40 789.42 496.57 794.67 24
test_one_060195.07 771.46 6194.14 778.27 3792.05 1195.74 680.83 11
PC_three_145268.21 23692.02 1294.00 4882.09 595.98 5584.58 4096.68 294.95 8
test_part295.06 872.65 3391.80 13
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 6494.67 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
FOURS195.00 1072.39 4295.06 193.84 1874.49 11891.30 15
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
SD-MVS88.06 1488.50 1386.71 5792.60 7672.71 3091.81 4193.19 4077.87 3890.32 1794.00 4874.83 2893.78 14587.63 1794.27 6393.65 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
DeepPCF-MVS80.84 188.10 1288.56 1286.73 5692.24 7869.03 11089.57 9093.39 3477.53 4789.79 1894.12 4378.98 1296.58 3685.66 2795.72 2994.58 27
xxxxxxxxxxxxxcwj87.88 1987.92 1987.77 2693.80 4472.35 4590.47 6789.69 16974.31 12289.16 1995.10 1375.65 2296.19 4587.07 2196.01 1794.79 19
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 19
TSAR-MVS + MP.88.02 1788.11 1687.72 3293.68 4972.13 5091.41 4892.35 8074.62 11688.90 2193.85 5275.75 2196.00 5387.80 1594.63 5395.04 6
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
ETH3D-3000-0.188.09 1388.29 1487.50 4192.76 7071.89 5691.43 4794.70 374.47 11988.86 2294.61 2175.23 2595.84 5886.62 2695.92 2194.78 21
APD-MVScopyleft87.44 2687.52 2487.19 4794.24 3472.39 4291.86 4092.83 6173.01 15188.58 2394.52 2373.36 4296.49 3784.26 4795.01 4292.70 108
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
9.1488.26 1592.84 6891.52 4694.75 173.93 13288.57 2494.67 1975.57 2495.79 5986.77 2395.76 28
testtj87.78 2087.78 2187.77 2694.55 1872.47 3992.23 3293.49 2974.75 11388.33 2594.43 3273.27 4497.02 1684.18 5194.84 4893.82 62
ACMMP_NAP88.05 1688.08 1787.94 1793.70 4773.05 2390.86 5793.59 2576.27 8288.14 2695.09 1571.06 6296.67 2887.67 1696.37 1494.09 46
SteuartSystems-ACMMP88.72 1088.86 1088.32 892.14 8072.96 2693.73 593.67 2280.19 1488.10 2794.80 1673.76 4197.11 1387.51 1895.82 2494.90 11
Skip Steuart: Steuart Systems R&D Blog.
CNVR-MVS88.93 989.13 988.33 794.77 1273.82 990.51 6493.00 4780.90 988.06 2894.06 4676.43 1796.84 2088.48 1495.99 1994.34 37
canonicalmvs85.91 5585.87 5786.04 7289.84 12469.44 10890.45 7093.00 4776.70 7288.01 2991.23 10773.28 4393.91 14081.50 8088.80 12494.77 22
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
ZD-MVS94.38 2772.22 4892.67 6770.98 18187.75 3194.07 4574.01 4096.70 2684.66 3994.84 48
alignmvs85.48 6285.32 6485.96 7489.51 13169.47 10589.74 8692.47 7476.17 8387.73 3291.46 10370.32 7093.78 14581.51 7988.95 12194.63 26
ETH3 D test640087.50 2587.44 2687.70 3593.71 4671.75 5790.62 6294.05 1570.80 18387.59 3393.51 5677.57 1496.63 3183.31 5895.77 2694.72 23
ETH3D cwj APD-0.1687.31 3287.27 2887.44 4391.60 8872.45 4190.02 7894.37 471.76 16587.28 3494.27 3675.18 2696.08 4985.16 3095.77 2693.80 65
旧先验286.56 18658.10 33187.04 3588.98 28074.07 142
Regformer-286.63 4386.53 4386.95 5189.33 13871.24 6788.43 12392.05 9382.50 186.88 3690.09 13274.45 3195.61 6384.38 4390.63 10394.01 51
SR-MVS86.73 3986.67 4186.91 5294.11 4072.11 5192.37 2792.56 7374.50 11786.84 3794.65 2067.31 9795.77 6084.80 3792.85 7592.84 106
Regformer-186.41 4886.33 4686.64 5889.33 13870.93 7588.43 12391.39 12382.14 386.65 3890.09 13274.39 3495.01 9683.97 5390.63 10393.97 53
dcpmvs_285.63 6186.15 5384.06 12691.71 8664.94 19686.47 18991.87 10573.63 13786.60 3993.02 7076.57 1691.87 22483.36 5792.15 8495.35 1
test117286.20 5286.22 4986.12 7093.95 4269.89 9691.79 4292.28 8275.07 10486.40 4094.58 2265.00 12295.56 6584.34 4592.60 7892.90 104
MP-MVS-pluss87.67 2287.72 2287.54 3993.64 5072.04 5289.80 8493.50 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
APD-MVS_3200maxsize85.97 5485.88 5686.22 6792.69 7269.53 10391.93 3792.99 4973.54 14185.94 4294.51 2665.80 11495.61 6383.04 6592.51 8093.53 81
zzz-MVS87.53 2487.41 2787.90 2194.18 3774.25 590.23 7492.02 9479.45 2185.88 4394.80 1668.07 8896.21 4386.69 2495.34 3693.23 89
MTAPA87.23 3387.00 3487.90 2194.18 3774.25 586.58 18592.02 9479.45 2185.88 4394.80 1668.07 8896.21 4386.69 2495.34 3693.23 89
TSAR-MVS + GP.85.71 5985.33 6386.84 5391.34 9072.50 3789.07 10287.28 23476.41 7585.80 4590.22 13074.15 3995.37 8281.82 7891.88 8792.65 112
NCCC88.06 1488.01 1888.24 1094.41 2473.62 1191.22 5292.83 6181.50 685.79 4693.47 5973.02 4797.00 1784.90 3394.94 4494.10 45
SR-MVS-dyc-post85.77 5785.61 5986.23 6693.06 6270.63 8291.88 3892.27 8373.53 14285.69 4794.45 2865.00 12295.56 6582.75 6891.87 8892.50 115
RE-MVS-def85.48 6093.06 6270.63 8291.88 3892.27 8373.53 14285.69 4794.45 2863.87 12982.75 6891.87 8892.50 115
testdata79.97 23990.90 9764.21 21084.71 26459.27 32385.40 4992.91 7162.02 16089.08 27868.95 19091.37 9586.63 292
Regformer-485.68 6085.45 6186.35 6288.95 15669.67 10088.29 13391.29 12581.73 585.36 5090.01 13572.62 4995.35 8383.28 6187.57 13694.03 49
abl_685.23 6784.95 7186.07 7192.23 7970.48 8690.80 5992.08 9273.51 14485.26 5194.16 4162.75 14695.92 5782.46 7591.30 9791.81 138
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
PHI-MVS86.43 4686.17 5287.24 4690.88 9870.96 7292.27 3194.07 1172.45 15485.22 5391.90 9069.47 7896.42 3883.28 6195.94 2094.35 36
patch_mono-283.65 8084.54 7580.99 21990.06 11965.83 17884.21 24688.74 20571.60 17185.01 5492.44 8174.51 3083.50 32582.15 7792.15 8493.64 75
Regformer-385.23 6785.07 6885.70 7688.95 15669.01 11288.29 13389.91 16380.95 885.01 5490.01 13572.45 5094.19 12682.50 7487.57 13693.90 57
TEST993.26 5672.96 2688.75 11391.89 10368.44 23485.00 5693.10 6574.36 3595.41 76
train_agg86.43 4686.20 5087.13 4993.26 5672.96 2688.75 11391.89 10368.69 23085.00 5693.10 6574.43 3295.41 7684.97 3295.71 3093.02 99
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
#test#87.33 3187.13 3387.94 1794.58 1673.54 1592.34 2893.24 3775.23 10084.91 5894.44 3070.78 6496.61 3283.75 5694.89 4693.66 68
test_prior386.73 3986.86 4086.33 6392.61 7469.59 10188.85 10992.97 5475.41 9684.91 5893.54 5474.28 3695.48 7083.31 5895.86 2293.91 55
test_prior288.85 10975.41 9684.91 5893.54 5474.28 3683.31 5895.86 22
test_893.13 5872.57 3688.68 11891.84 10768.69 23084.87 6293.10 6574.43 3295.16 87
MCST-MVS87.37 3087.25 3087.73 3094.53 1972.46 4089.82 8293.82 1973.07 14984.86 6392.89 7276.22 1896.33 3984.89 3595.13 4194.40 34
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 5195.01 4293.90 57
h-mvs3383.15 8982.19 9786.02 7390.56 10570.85 7888.15 14089.16 18576.02 8684.67 6591.39 10561.54 16595.50 6982.71 7075.48 28191.72 140
hse-mvs281.72 11180.94 11784.07 12588.72 16767.68 14485.87 20587.26 23576.02 8684.67 6588.22 18561.54 16593.48 16182.71 7073.44 30891.06 157
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
CDPH-MVS85.76 5885.29 6687.17 4893.49 5371.08 6888.58 12192.42 7868.32 23584.61 6893.48 5772.32 5196.15 4879.00 9695.43 3494.28 40
UA-Net85.08 7184.96 7085.45 8092.07 8168.07 13789.78 8590.86 13882.48 284.60 6993.20 6369.35 7995.22 8571.39 16690.88 10193.07 96
CS-MVS-test86.26 5086.48 4485.60 7790.84 9966.60 16391.16 5393.56 2679.82 1884.57 7089.89 13770.67 6795.04 9484.30 4693.48 6995.16 4
CS-MVS86.61 4486.96 3685.56 7990.78 10266.54 16592.84 1793.30 3679.67 2084.55 7192.25 8471.46 5995.00 9784.25 4993.48 6995.15 5
region2R87.42 2887.20 3288.09 1294.63 1473.55 1393.03 1493.12 4276.73 7184.45 7294.52 2369.09 8296.70 2684.37 4494.83 5094.03 49
agg_prior186.22 5186.09 5586.62 5992.85 6671.94 5488.59 12091.78 11068.96 22584.41 7393.18 6474.94 2794.93 9884.75 3895.33 3893.01 100
agg_prior92.85 6671.94 5491.78 11084.41 7394.93 98
VDD-MVS83.01 9482.36 9584.96 9391.02 9566.40 16688.91 10688.11 21477.57 4384.39 7593.29 6252.19 24593.91 14077.05 11888.70 12694.57 29
casdiffmvs85.11 7085.14 6785.01 9187.20 21465.77 18187.75 15192.83 6177.84 3984.36 7692.38 8272.15 5393.93 13981.27 8290.48 10595.33 2
MSLP-MVS++85.43 6485.76 5884.45 11091.93 8370.24 8790.71 6092.86 5977.46 4984.22 7792.81 7667.16 9992.94 18680.36 9094.35 6190.16 189
DeepC-MVS_fast79.65 386.91 3886.62 4287.76 2993.52 5272.37 4491.26 4993.04 4376.62 7384.22 7793.36 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
DROMVSNet86.01 5386.38 4584.91 9789.31 14366.27 16992.32 2993.63 2379.37 2384.17 7991.88 9169.04 8595.43 7483.93 5493.77 6793.01 100
ETV-MVS84.90 7484.67 7485.59 7889.39 13668.66 12688.74 11592.64 7179.97 1784.10 8085.71 25069.32 8095.38 7980.82 8691.37 9592.72 107
VNet82.21 10282.41 9381.62 20090.82 10060.93 26084.47 23789.78 16576.36 8084.07 8191.88 9164.71 12490.26 25870.68 17188.89 12293.66 68
baseline84.93 7284.98 6984.80 10287.30 21265.39 18887.30 16392.88 5877.62 4184.04 8292.26 8371.81 5593.96 13381.31 8190.30 10795.03 7
PGM-MVS86.68 4186.27 4887.90 2194.22 3573.38 1990.22 7593.04 4375.53 9483.86 8394.42 3367.87 9296.64 3082.70 7294.57 5593.66 68
MP-MVScopyleft87.71 2187.64 2387.93 2094.36 2873.88 792.71 2292.65 7077.57 4383.84 8494.40 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.
HPM-MVScopyleft87.11 3586.98 3587.50 4193.88 4372.16 4992.19 3393.33 3576.07 8583.81 8593.95 5169.77 7696.01 5285.15 3194.66 5294.32 38
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
CP-MVS87.11 3586.92 3787.68 3794.20 3673.86 893.98 392.82 6476.62 7383.68 8694.46 2767.93 9095.95 5684.20 5094.39 5993.23 89
XVS87.18 3486.91 3888.00 1594.42 2273.33 2092.78 1892.99 4979.14 2483.67 8794.17 4067.45 9596.60 3483.06 6394.50 5694.07 47
X-MVStestdata80.37 14577.83 18188.00 1594.42 2273.33 2092.78 1892.99 4979.14 2483.67 8712.47 37367.45 9596.60 3483.06 6394.50 5694.07 47
DELS-MVS85.41 6585.30 6585.77 7588.49 17467.93 13985.52 21893.44 3178.70 3183.63 8989.03 16374.57 2995.71 6280.26 9294.04 6593.66 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
LFMVS81.82 11081.23 11183.57 14391.89 8463.43 22889.84 8181.85 30577.04 6183.21 9093.10 6552.26 24493.43 16571.98 16189.95 11493.85 59
VDDNet81.52 11780.67 12084.05 12890.44 10864.13 21289.73 8785.91 25471.11 17883.18 9193.48 5750.54 26893.49 16073.40 15088.25 13294.54 30
CSCG86.41 4886.19 5187.07 5092.91 6572.48 3890.81 5893.56 2673.95 13083.16 9291.07 11375.94 1995.19 8679.94 9494.38 6093.55 79
nrg03083.88 7683.53 7984.96 9386.77 22269.28 10990.46 6992.67 6774.79 11182.95 9391.33 10672.70 4893.09 18080.79 8879.28 23892.50 115
EI-MVSNet-Vis-set84.19 7583.81 7885.31 8288.18 18367.85 14087.66 15389.73 16880.05 1682.95 9389.59 14770.74 6694.82 10680.66 8984.72 17293.28 88
MVS_Test83.15 8983.06 8583.41 14886.86 21863.21 23286.11 19992.00 9774.31 12282.87 9589.44 15570.03 7293.21 17077.39 11588.50 13093.81 63
DPM-MVS84.93 7284.29 7786.84 5390.20 11273.04 2487.12 16793.04 4369.80 20382.85 9691.22 10873.06 4696.02 5176.72 12394.63 5391.46 148
DeepC-MVS79.81 287.08 3786.88 3987.69 3691.16 9272.32 4790.31 7293.94 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
mPP-MVS86.67 4286.32 4787.72 3294.41 2473.55 1392.74 2092.22 8776.87 6582.81 9894.25 3866.44 10496.24 4282.88 6794.28 6293.38 83
test1286.80 5592.63 7370.70 8191.79 10982.71 9971.67 5796.16 4794.50 5693.54 80
HPM-MVS_fast85.35 6684.95 7186.57 6193.69 4870.58 8592.15 3591.62 11473.89 13382.67 10094.09 4462.60 14795.54 6880.93 8492.93 7393.57 78
Effi-MVS+83.62 8283.08 8485.24 8588.38 17967.45 14788.89 10789.15 18675.50 9582.27 10188.28 18269.61 7794.45 11677.81 11087.84 13493.84 61
EI-MVSNet-UG-set83.81 7783.38 8185.09 8987.87 19267.53 14687.44 15989.66 17079.74 1982.23 10289.41 15670.24 7194.74 10979.95 9383.92 18092.99 102
MVS_111021_HR85.14 6984.75 7386.32 6591.65 8772.70 3185.98 20190.33 15176.11 8482.08 10391.61 9871.36 6194.17 12881.02 8392.58 7992.08 131
diffmvs82.10 10381.88 10582.76 18183.00 28463.78 21883.68 25489.76 16672.94 15282.02 10489.85 13965.96 11390.79 25282.38 7687.30 14393.71 67
xiu_mvs_v1_base_debu80.80 13379.72 13784.03 13187.35 20770.19 9085.56 21188.77 20069.06 22181.83 10588.16 18650.91 26292.85 18878.29 10787.56 13889.06 227
xiu_mvs_v1_base80.80 13379.72 13784.03 13187.35 20770.19 9085.56 21188.77 20069.06 22181.83 10588.16 18650.91 26292.85 18878.29 10787.56 13889.06 227
xiu_mvs_v1_base_debi80.80 13379.72 13784.03 13187.35 20770.19 9085.56 21188.77 20069.06 22181.83 10588.16 18650.91 26292.85 18878.29 10787.56 13889.06 227
新几何183.42 14693.13 5870.71 8085.48 25757.43 33681.80 10891.98 8863.28 13592.27 20764.60 22992.99 7287.27 275
test_yl81.17 12280.47 12483.24 15489.13 15163.62 21986.21 19689.95 16172.43 15781.78 10989.61 14557.50 20693.58 15470.75 16986.90 14892.52 113
DCV-MVSNet81.17 12280.47 12483.24 15489.13 15163.62 21986.21 19689.95 16172.43 15781.78 10989.61 14557.50 20693.58 15470.75 16986.90 14892.52 113
112180.84 12879.77 13584.05 12893.11 6070.78 7984.66 23185.42 25857.37 33781.76 11192.02 8763.41 13394.12 12967.28 20592.93 7387.26 276
MG-MVS83.41 8583.45 8083.28 15192.74 7162.28 24688.17 13889.50 17375.22 10181.49 11292.74 8066.75 10095.11 8972.85 15691.58 9292.45 118
CANet86.45 4586.10 5487.51 4090.09 11470.94 7489.70 8892.59 7281.78 481.32 11391.43 10470.34 6997.23 1284.26 4793.36 7194.37 35
MVSFormer82.85 9582.05 10185.24 8587.35 20770.21 8890.50 6590.38 14768.55 23281.32 11389.47 15061.68 16293.46 16378.98 9790.26 10892.05 132
lupinMVS81.39 12080.27 12984.76 10387.35 20770.21 8885.55 21486.41 24662.85 29481.32 11388.61 17261.68 16292.24 21078.41 10590.26 10891.83 136
xiu_mvs_v2_base81.69 11381.05 11483.60 14189.15 15068.03 13884.46 23990.02 15970.67 18781.30 11686.53 23663.17 13994.19 12675.60 13288.54 12888.57 249
PS-MVSNAJ81.69 11381.02 11583.70 14089.51 13168.21 13584.28 24590.09 15870.79 18481.26 11785.62 25463.15 14094.29 11875.62 13188.87 12388.59 248
原ACMM184.35 11593.01 6468.79 11692.44 7563.96 28581.09 11891.57 9966.06 11095.45 7267.19 20894.82 5188.81 242
jason81.39 12080.29 12884.70 10486.63 22469.90 9585.95 20286.77 24263.24 28781.07 11989.47 15061.08 17892.15 21378.33 10690.07 11392.05 132
jason: jason.
OPM-MVS83.50 8382.95 8785.14 8788.79 16470.95 7389.13 10191.52 11777.55 4680.96 12091.75 9360.71 18294.50 11579.67 9586.51 15589.97 205
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
Vis-MVSNetpermissive83.46 8482.80 9085.43 8190.25 11168.74 12090.30 7390.13 15776.33 8180.87 12192.89 7261.00 17994.20 12572.45 16090.97 9993.35 85
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
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 7390.69 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
Anonymous2024052980.19 14978.89 15784.10 12390.60 10464.75 19988.95 10590.90 13665.97 25980.59 12391.17 11049.97 27393.73 15169.16 18882.70 20093.81 63
test_part182.78 9682.08 10084.89 9890.66 10366.97 15890.96 5692.93 5777.19 5580.53 12490.04 13463.44 13295.39 7876.04 12776.90 25892.31 122
MVS_111021_LR82.61 9982.11 9884.11 12288.82 16171.58 5985.15 22186.16 25174.69 11480.47 12591.04 11462.29 15490.55 25680.33 9190.08 11290.20 188
ECVR-MVScopyleft79.61 15779.26 14980.67 22690.08 11554.69 32787.89 14877.44 33774.88 10980.27 12692.79 7748.96 28792.45 19868.55 19492.50 8194.86 15
VPA-MVSNet80.60 13980.55 12280.76 22488.07 18760.80 26386.86 17591.58 11675.67 9380.24 12789.45 15463.34 13490.25 25970.51 17379.22 23991.23 153
test111179.43 16479.18 15280.15 23689.99 12053.31 34087.33 16277.05 34075.04 10580.23 12892.77 7948.97 28692.33 20668.87 19192.40 8394.81 18
test250677.30 21776.49 21479.74 24490.08 11552.02 34387.86 15063.10 37074.88 10980.16 12992.79 7738.29 34392.35 20468.74 19392.50 8194.86 15
Anonymous20240521178.25 19277.01 20081.99 19491.03 9460.67 26584.77 22983.90 27770.65 18980.00 13091.20 10941.08 33391.43 23565.21 22385.26 16793.85 59
test22291.50 8968.26 13384.16 24783.20 29154.63 34879.74 13191.63 9758.97 19591.42 9486.77 288
OMC-MVS82.69 9781.97 10484.85 9988.75 16667.42 14887.98 14290.87 13774.92 10879.72 13291.65 9562.19 15793.96 13375.26 13586.42 15693.16 94
CPTT-MVS83.73 7883.33 8284.92 9693.28 5570.86 7792.09 3690.38 14768.75 22979.57 13392.83 7460.60 18693.04 18480.92 8591.56 9390.86 165
IS-MVSNet83.15 8982.81 8984.18 12189.94 12263.30 23091.59 4388.46 21179.04 2879.49 13492.16 8565.10 11994.28 11967.71 20091.86 9094.95 8
PS-MVSNAJss82.07 10581.31 10984.34 11686.51 22567.27 15289.27 9491.51 11871.75 16679.37 13590.22 13063.15 14094.27 12077.69 11182.36 20391.49 146
EPP-MVSNet83.40 8683.02 8684.57 10690.13 11364.47 20592.32 2990.73 13974.45 12179.35 13691.10 11169.05 8495.12 8872.78 15787.22 14494.13 44
DP-MVS Recon83.11 9282.09 9986.15 6894.44 2170.92 7688.79 11192.20 8870.53 19079.17 13791.03 11664.12 12796.03 5068.39 19790.14 11091.50 145
ab-mvs79.51 16078.97 15681.14 21588.46 17660.91 26183.84 25289.24 18270.36 19279.03 13888.87 16663.23 13890.21 26065.12 22482.57 20192.28 124
EIA-MVS83.31 8882.80 9084.82 10089.59 12765.59 18388.21 13692.68 6674.66 11578.96 13986.42 23869.06 8395.26 8475.54 13390.09 11193.62 76
PVSNet_Blended_VisFu82.62 9881.83 10684.96 9390.80 10169.76 9888.74 11591.70 11369.39 21078.96 13988.46 17765.47 11694.87 10574.42 13888.57 12790.24 187
HQP_MVS83.64 8183.14 8385.14 8790.08 11568.71 12291.25 5092.44 7579.12 2678.92 14191.00 11760.42 18895.38 7978.71 9986.32 15791.33 150
plane_prior368.60 12778.44 3378.92 141
RRT_MVS79.88 15478.38 16784.38 11285.42 23970.60 8488.71 11788.75 20472.30 15978.83 14389.14 15844.44 31492.18 21278.50 10279.33 23790.35 183
EI-MVSNet80.52 14279.98 13182.12 18984.28 25563.19 23486.41 19088.95 19674.18 12778.69 14487.54 20166.62 10192.43 19972.57 15980.57 22290.74 169
MVSTER79.01 17677.88 18082.38 18783.07 28164.80 19884.08 25188.95 19669.01 22478.69 14487.17 21354.70 22592.43 19974.69 13780.57 22289.89 208
API-MVS81.99 10781.23 11184.26 11990.94 9670.18 9391.10 5489.32 17771.51 17378.66 14688.28 18265.26 11795.10 9264.74 22891.23 9887.51 269
GeoE81.71 11281.01 11683.80 13989.51 13164.45 20688.97 10488.73 20671.27 17678.63 14789.76 14166.32 10693.20 17269.89 18086.02 16293.74 66
UniMVSNet (Re)81.60 11681.11 11383.09 16188.38 17964.41 20787.60 15493.02 4678.42 3478.56 14888.16 18669.78 7593.26 16969.58 18476.49 26591.60 141
MAR-MVS81.84 10980.70 11985.27 8491.32 9171.53 6089.82 8290.92 13569.77 20478.50 14986.21 24262.36 15394.52 11465.36 22292.05 8689.77 213
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
Fast-Effi-MVS+80.81 13179.92 13283.47 14488.85 15864.51 20285.53 21689.39 17570.79 18478.49 15085.06 26667.54 9493.58 15467.03 21186.58 15392.32 121
FIs82.07 10582.42 9281.04 21888.80 16358.34 28588.26 13593.49 2976.93 6378.47 15191.04 11469.92 7492.34 20569.87 18184.97 16992.44 119
UniMVSNet_NR-MVSNet81.88 10881.54 10882.92 17088.46 17663.46 22687.13 16692.37 7980.19 1478.38 15289.14 15871.66 5893.05 18270.05 17776.46 26692.25 125
DU-MVS81.12 12480.52 12382.90 17187.80 19563.46 22687.02 17091.87 10579.01 2978.38 15289.07 16165.02 12093.05 18270.05 17776.46 26692.20 127
CLD-MVS82.31 10181.65 10784.29 11888.47 17567.73 14385.81 20992.35 8075.78 8978.33 15486.58 23364.01 12894.35 11776.05 12687.48 14190.79 166
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
VPNet78.69 18378.66 16078.76 26088.31 18155.72 32384.45 24086.63 24476.79 6778.26 15590.55 12459.30 19389.70 26866.63 21277.05 25690.88 164
V4279.38 16878.24 17282.83 17381.10 31965.50 18585.55 21489.82 16471.57 17278.21 15686.12 24460.66 18493.18 17575.64 13075.46 28389.81 212
BH-RMVSNet79.61 15778.44 16583.14 15989.38 13765.93 17584.95 22687.15 23773.56 14078.19 15789.79 14056.67 21493.36 16659.53 26886.74 15190.13 191
v2v48280.23 14779.29 14883.05 16483.62 26764.14 21187.04 16989.97 16073.61 13878.18 15887.22 21061.10 17793.82 14376.11 12576.78 26391.18 154
PVSNet_BlendedMVS80.60 13980.02 13082.36 18888.85 15865.40 18686.16 19892.00 9769.34 21278.11 15986.09 24566.02 11194.27 12071.52 16382.06 20587.39 271
PVSNet_Blended80.98 12580.34 12682.90 17188.85 15865.40 18684.43 24192.00 9767.62 23978.11 15985.05 26766.02 11194.27 12071.52 16389.50 11789.01 232
v114480.03 15179.03 15483.01 16683.78 26564.51 20287.11 16890.57 14371.96 16478.08 16186.20 24361.41 16993.94 13674.93 13677.23 25390.60 174
TranMVSNet+NR-MVSNet80.84 12880.31 12782.42 18687.85 19362.33 24487.74 15291.33 12480.55 1177.99 16289.86 13865.23 11892.62 19267.05 21075.24 29192.30 123
Baseline_NR-MVSNet78.15 19778.33 17077.61 27885.79 23256.21 31986.78 17985.76 25573.60 13977.93 16387.57 19965.02 12088.99 27967.14 20975.33 28787.63 265
TR-MVS77.44 21376.18 21981.20 21388.24 18263.24 23184.61 23586.40 24767.55 24077.81 16486.48 23754.10 23093.15 17657.75 28682.72 19987.20 277
v119279.59 15978.43 16683.07 16383.55 26964.52 20186.93 17390.58 14270.83 18277.78 16585.90 24659.15 19493.94 13673.96 14377.19 25590.76 167
PCF-MVS73.52 780.38 14478.84 15885.01 9187.71 19968.99 11383.65 25591.46 12263.00 29177.77 16690.28 12766.10 10895.09 9361.40 25488.22 13390.94 163
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
WR-MVS79.49 16179.22 15180.27 23488.79 16458.35 28485.06 22388.61 20978.56 3277.65 16788.34 18063.81 13190.66 25564.98 22677.22 25491.80 139
XVG-OURS80.41 14379.23 15083.97 13585.64 23569.02 11183.03 26890.39 14671.09 17977.63 16891.49 10254.62 22791.35 23775.71 12983.47 18891.54 143
v14419279.47 16278.37 16882.78 17983.35 27263.96 21486.96 17190.36 15069.99 19877.50 16985.67 25260.66 18493.77 14774.27 14076.58 26490.62 172
v192192079.22 17078.03 17582.80 17683.30 27463.94 21586.80 17790.33 15169.91 20177.48 17085.53 25558.44 19893.75 14973.60 14576.85 26190.71 170
thisisatest053079.40 16677.76 18584.31 11787.69 20165.10 19487.36 16084.26 27370.04 19777.42 17188.26 18449.94 27494.79 10870.20 17584.70 17393.03 98
FC-MVSNet-test81.52 11782.02 10280.03 23888.42 17855.97 32187.95 14493.42 3377.10 5977.38 17290.98 11969.96 7391.79 22568.46 19684.50 17492.33 120
v124078.99 17777.78 18382.64 18283.21 27663.54 22386.62 18490.30 15369.74 20777.33 17385.68 25157.04 21293.76 14873.13 15476.92 25790.62 172
PAPM_NR83.02 9382.41 9384.82 10092.47 7766.37 16787.93 14691.80 10873.82 13477.32 17490.66 12267.90 9194.90 10270.37 17489.48 11893.19 93
ACMM73.20 880.78 13679.84 13483.58 14289.31 14368.37 13089.99 7991.60 11570.28 19477.25 17589.66 14353.37 23693.53 15974.24 14182.85 19688.85 240
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
HQP4-MVS77.24 17695.11 8991.03 159
AUN-MVS79.21 17177.60 19084.05 12888.71 16867.61 14585.84 20787.26 23569.08 22077.23 17788.14 19053.20 23893.47 16275.50 13473.45 30791.06 157
HQP-NCC89.33 13889.17 9676.41 7577.23 177
ACMP_Plane89.33 13889.17 9676.41 7577.23 177
HQP-MVS82.61 9982.02 10284.37 11389.33 13866.98 15689.17 9692.19 8976.41 7577.23 17790.23 12960.17 19195.11 8977.47 11385.99 16391.03 159
TAPA-MVS73.13 979.15 17277.94 17782.79 17889.59 12762.99 23988.16 13991.51 11865.77 26077.14 18191.09 11260.91 18093.21 17050.26 32387.05 14692.17 129
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
PAPR81.66 11580.89 11883.99 13490.27 11064.00 21386.76 18191.77 11268.84 22877.13 18289.50 14867.63 9394.88 10467.55 20288.52 12993.09 95
UniMVSNet_ETH3D79.10 17478.24 17281.70 19986.85 21960.24 27187.28 16488.79 19974.25 12576.84 18390.53 12549.48 27991.56 23167.98 19882.15 20493.29 87
EPNet83.72 7982.92 8886.14 6984.22 25769.48 10491.05 5585.27 25981.30 776.83 18491.65 9566.09 10995.56 6576.00 12893.85 6693.38 83
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
baseline176.98 22276.75 21077.66 27688.13 18455.66 32485.12 22281.89 30373.04 15076.79 18588.90 16462.43 15287.78 29663.30 23671.18 32389.55 219
tttt051779.40 16677.91 17883.90 13888.10 18663.84 21688.37 13084.05 27571.45 17476.78 18689.12 16049.93 27694.89 10370.18 17683.18 19292.96 103
TAMVS78.89 18077.51 19283.03 16587.80 19567.79 14284.72 23085.05 26267.63 23876.75 18787.70 19562.25 15590.82 25158.53 27987.13 14590.49 178
XVG-OURS-SEG-HR80.81 13179.76 13683.96 13685.60 23668.78 11783.54 26090.50 14470.66 18876.71 18891.66 9460.69 18391.26 23976.94 12081.58 21091.83 136
3Dnovator+77.84 485.48 6284.47 7688.51 691.08 9373.49 1793.18 1193.78 2180.79 1076.66 18993.37 6060.40 19096.75 2577.20 11693.73 6895.29 3
LPG-MVS_test82.08 10481.27 11084.50 10889.23 14768.76 11890.22 7591.94 10175.37 9876.64 19091.51 10054.29 22894.91 10078.44 10383.78 18189.83 210
LGP-MVS_train84.50 10889.23 14768.76 11891.94 10175.37 9876.64 19091.51 10054.29 22894.91 10078.44 10383.78 18189.83 210
tfpn200view976.42 23175.37 23079.55 25189.13 15157.65 29785.17 21983.60 28073.41 14576.45 19286.39 23952.12 24691.95 21948.33 33183.75 18389.07 225
thres40076.50 22875.37 23079.86 24189.13 15157.65 29785.17 21983.60 28073.41 14576.45 19286.39 23952.12 24691.95 21948.33 33183.75 18390.00 201
HyFIR lowres test77.53 21275.40 22883.94 13789.59 12766.62 16180.36 29288.64 20856.29 34376.45 19285.17 26357.64 20493.28 16861.34 25683.10 19491.91 134
mvs-test180.88 12679.40 14485.29 8385.13 24569.75 9989.28 9388.10 21574.99 10676.44 19586.72 22257.27 20994.26 12473.53 14683.18 19291.87 135
CDS-MVSNet79.07 17577.70 18783.17 15887.60 20268.23 13484.40 24386.20 25067.49 24176.36 19686.54 23561.54 16590.79 25261.86 25087.33 14290.49 178
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
thres100view90076.50 22875.55 22479.33 25289.52 13056.99 30585.83 20883.23 28973.94 13176.32 19787.12 21451.89 25391.95 21948.33 33183.75 18389.07 225
thres600view776.50 22875.44 22679.68 24689.40 13557.16 30285.53 21683.23 28973.79 13576.26 19887.09 21551.89 25391.89 22248.05 33683.72 18690.00 201
UGNet80.83 13079.59 14084.54 10788.04 18868.09 13689.42 9188.16 21376.95 6276.22 19989.46 15249.30 28293.94 13668.48 19590.31 10691.60 141
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
test_djsdf80.30 14679.32 14783.27 15283.98 26265.37 18990.50 6590.38 14768.55 23276.19 20088.70 16856.44 21593.46 16378.98 9780.14 22890.97 162
v14878.72 18277.80 18281.47 20482.73 29161.96 25086.30 19488.08 21773.26 14776.18 20185.47 25762.46 15192.36 20371.92 16273.82 30490.09 195
WTY-MVS75.65 24175.68 22275.57 29786.40 22656.82 30777.92 31882.40 29965.10 26776.18 20187.72 19463.13 14380.90 33760.31 26281.96 20689.00 234
mvs_anonymous79.42 16579.11 15380.34 23284.45 25457.97 29182.59 27087.62 22767.40 24276.17 20388.56 17568.47 8789.59 26970.65 17286.05 16193.47 82
Anonymous2023121178.97 17877.69 18882.81 17590.54 10664.29 20990.11 7791.51 11865.01 27076.16 20488.13 19150.56 26793.03 18569.68 18377.56 25191.11 156
bset_n11_16_dypcd77.12 21975.47 22582.06 19181.12 31865.99 17381.37 28483.20 29169.94 20076.09 20583.38 28847.75 29292.26 20878.51 10177.91 24787.95 257
thisisatest051577.33 21675.38 22983.18 15785.27 24163.80 21782.11 27583.27 28865.06 26875.91 20683.84 28049.54 27894.27 12067.24 20786.19 15991.48 147
RRT_test8_iter0578.38 19077.40 19381.34 20986.00 23058.86 28086.55 18791.26 12672.13 16375.91 20687.42 20444.97 31193.73 15177.02 11975.30 28891.45 149
CANet_DTU80.61 13879.87 13382.83 17385.60 23663.17 23587.36 16088.65 20776.37 7975.88 20888.44 17853.51 23593.07 18173.30 15189.74 11692.25 125
thres20075.55 24274.47 24078.82 25987.78 19857.85 29483.07 26783.51 28372.44 15675.84 20984.42 27252.08 24891.75 22647.41 33883.64 18786.86 286
CHOSEN 1792x268877.63 21175.69 22183.44 14589.98 12168.58 12878.70 31087.50 23056.38 34275.80 21086.84 21858.67 19691.40 23661.58 25385.75 16690.34 184
AdaColmapbinary80.58 14179.42 14384.06 12693.09 6168.91 11589.36 9288.97 19569.27 21375.70 21189.69 14257.20 21195.77 6063.06 23888.41 13187.50 270
c3_l78.75 18177.91 17881.26 21182.89 28861.56 25584.09 25089.13 18869.97 19975.56 21284.29 27466.36 10592.09 21573.47 14975.48 28190.12 192
miper_ehance_all_eth78.59 18677.76 18581.08 21782.66 29361.56 25583.65 25589.15 18668.87 22775.55 21383.79 28266.49 10392.03 21673.25 15276.39 26889.64 216
miper_enhance_ethall77.87 20676.86 20480.92 22181.65 30761.38 25782.68 26988.98 19365.52 26475.47 21482.30 30065.76 11592.00 21872.95 15576.39 26889.39 221
3Dnovator76.31 583.38 8782.31 9686.59 6087.94 19172.94 2990.64 6192.14 9177.21 5475.47 21492.83 7458.56 19794.72 11073.24 15392.71 7792.13 130
jajsoiax79.29 16977.96 17683.27 15284.68 25166.57 16489.25 9590.16 15669.20 21775.46 21689.49 14945.75 30893.13 17876.84 12180.80 21890.11 193
IterMVS-LS80.06 15079.38 14582.11 19085.89 23163.20 23386.79 17889.34 17674.19 12675.45 21786.72 22266.62 10192.39 20172.58 15876.86 26090.75 168
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
BH-untuned79.47 16278.60 16182.05 19289.19 14965.91 17686.07 20088.52 21072.18 16075.42 21887.69 19661.15 17693.54 15860.38 26186.83 15086.70 290
mvs_tets79.13 17377.77 18483.22 15684.70 25066.37 16789.17 9690.19 15569.38 21175.40 21989.46 15244.17 31693.15 17676.78 12280.70 22090.14 190
HY-MVS69.67 1277.95 20377.15 19880.36 23187.57 20660.21 27283.37 26287.78 22566.11 25575.37 22087.06 21763.27 13690.48 25761.38 25582.43 20290.40 182
GBi-Net78.40 18877.40 19381.40 20687.60 20263.01 23688.39 12789.28 17871.63 16875.34 22187.28 20654.80 22191.11 24262.72 23979.57 23190.09 195
test178.40 18877.40 19381.40 20687.60 20263.01 23688.39 12789.28 17871.63 16875.34 22187.28 20654.80 22191.11 24262.72 23979.57 23190.09 195
FMVSNet377.88 20576.85 20580.97 22086.84 22062.36 24386.52 18888.77 20071.13 17775.34 22186.66 22954.07 23191.10 24562.72 23979.57 23189.45 220
CostFormer75.24 24773.90 24679.27 25382.65 29458.27 28680.80 28582.73 29761.57 30575.33 22483.13 29055.52 21791.07 24864.98 22678.34 24588.45 251
FMVSNet278.20 19577.21 19781.20 21387.60 20262.89 24087.47 15889.02 19171.63 16875.29 22587.28 20654.80 22191.10 24562.38 24379.38 23589.61 217
v879.97 15379.02 15582.80 17684.09 25964.50 20487.96 14390.29 15474.13 12975.24 22686.81 21962.88 14593.89 14274.39 13975.40 28590.00 201
anonymousdsp78.60 18577.15 19882.98 16880.51 32567.08 15487.24 16589.53 17265.66 26275.16 22787.19 21252.52 23992.25 20977.17 11779.34 23689.61 217
QAPM80.88 12679.50 14285.03 9088.01 19068.97 11491.59 4392.00 9766.63 25175.15 22892.16 8557.70 20395.45 7263.52 23288.76 12590.66 171
v1079.74 15678.67 15982.97 16984.06 26064.95 19587.88 14990.62 14173.11 14875.11 22986.56 23461.46 16894.05 13273.68 14475.55 27989.90 207
Vis-MVSNet (Re-imp)78.36 19178.45 16478.07 27188.64 17051.78 34686.70 18279.63 32674.14 12875.11 22990.83 12061.29 17389.75 26658.10 28391.60 9192.69 110
cl2278.07 19977.01 20081.23 21282.37 30061.83 25283.55 25987.98 21968.96 22575.06 23183.87 27861.40 17091.88 22373.53 14676.39 26889.98 204
ACMP74.13 681.51 11980.57 12184.36 11489.42 13468.69 12589.97 8091.50 12174.46 12075.04 23290.41 12653.82 23394.54 11277.56 11282.91 19589.86 209
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
Effi-MVS+-dtu80.03 15178.57 16284.42 11185.13 24568.74 12088.77 11288.10 21574.99 10674.97 23383.49 28657.27 20993.36 16673.53 14680.88 21691.18 154
XXY-MVS75.41 24575.56 22374.96 30383.59 26857.82 29580.59 29083.87 27866.54 25274.93 23488.31 18163.24 13780.09 34062.16 24676.85 26186.97 284
eth_miper_zixun_eth77.92 20476.69 21181.61 20283.00 28461.98 24983.15 26489.20 18469.52 20974.86 23584.35 27361.76 16192.56 19571.50 16572.89 31290.28 186
GA-MVS76.87 22475.17 23381.97 19582.75 29062.58 24181.44 28386.35 24972.16 16274.74 23682.89 29246.20 30392.02 21768.85 19281.09 21491.30 152
sss73.60 25973.64 24973.51 31482.80 28955.01 32676.12 32481.69 30662.47 29974.68 23785.85 24957.32 20878.11 34760.86 25980.93 21587.39 271
BH-w/o78.21 19477.33 19680.84 22288.81 16265.13 19384.87 22787.85 22469.75 20574.52 23884.74 27061.34 17193.11 17958.24 28285.84 16584.27 320
FMVSNet177.44 21376.12 22081.40 20686.81 22163.01 23688.39 12789.28 17870.49 19174.39 23987.28 20649.06 28591.11 24260.91 25878.52 24190.09 195
cl____77.72 20876.76 20880.58 22782.49 29760.48 26883.09 26587.87 22269.22 21574.38 24085.22 26262.10 15891.53 23271.09 16775.41 28489.73 215
DIV-MVS_self_test77.72 20876.76 20880.58 22782.48 29860.48 26883.09 26587.86 22369.22 21574.38 24085.24 26162.10 15891.53 23271.09 16775.40 28589.74 214
114514_t80.68 13779.51 14184.20 12094.09 4167.27 15289.64 8991.11 13258.75 32874.08 24290.72 12158.10 19995.04 9469.70 18289.42 11990.30 185
WR-MVS_H78.51 18778.49 16378.56 26388.02 18956.38 31688.43 12392.67 6777.14 5773.89 24387.55 20066.25 10789.24 27558.92 27473.55 30690.06 199
tpm273.26 26471.46 26678.63 26183.34 27356.71 31080.65 28980.40 31956.63 34173.55 24482.02 30551.80 25591.24 24056.35 29778.42 24487.95 257
CP-MVSNet78.22 19378.34 16977.84 27387.83 19454.54 32987.94 14591.17 13077.65 4073.48 24588.49 17662.24 15688.43 28862.19 24574.07 29990.55 176
pm-mvs177.25 21876.68 21278.93 25884.22 25758.62 28386.41 19088.36 21271.37 17573.31 24688.01 19261.22 17589.15 27764.24 23073.01 31189.03 231
PS-CasMVS78.01 20278.09 17477.77 27587.71 19954.39 33188.02 14191.22 12777.50 4873.26 24788.64 17160.73 18188.41 28961.88 24973.88 30390.53 177
CVMVSNet72.99 26872.58 25774.25 31084.28 25550.85 35286.41 19083.45 28644.56 35873.23 24887.54 20149.38 28085.70 30965.90 21878.44 24386.19 297
PEN-MVS77.73 20777.69 18877.84 27387.07 21753.91 33487.91 14791.18 12977.56 4573.14 24988.82 16761.23 17489.17 27659.95 26472.37 31490.43 180
1112_ss77.40 21576.43 21680.32 23389.11 15560.41 27083.65 25587.72 22662.13 30273.05 25086.72 22262.58 14989.97 26362.11 24880.80 21890.59 175
tpm72.37 27471.71 26574.35 30982.19 30252.00 34479.22 30477.29 33864.56 27472.95 25183.68 28551.35 25883.26 32858.33 28175.80 27587.81 262
cascas76.72 22674.64 23682.99 16785.78 23365.88 17782.33 27389.21 18360.85 31072.74 25281.02 31147.28 29593.75 14967.48 20385.02 16889.34 222
CR-MVSNet73.37 26171.27 27079.67 24781.32 31665.19 19175.92 32680.30 32059.92 31772.73 25381.19 30852.50 24086.69 30259.84 26577.71 24887.11 282
RPMNet73.51 26070.49 27682.58 18481.32 31665.19 19175.92 32692.27 8357.60 33572.73 25376.45 34552.30 24395.43 7448.14 33577.71 24887.11 282
DTE-MVSNet76.99 22176.80 20677.54 28086.24 22753.06 34287.52 15690.66 14077.08 6072.50 25588.67 17060.48 18789.52 27057.33 29070.74 32590.05 200
Test_1112_low_res76.40 23275.44 22679.27 25389.28 14558.09 28781.69 27987.07 23859.53 32172.48 25686.67 22861.30 17289.33 27360.81 26080.15 22790.41 181
v7n78.97 17877.58 19183.14 15983.45 27165.51 18488.32 13191.21 12873.69 13672.41 25786.32 24157.93 20093.81 14469.18 18775.65 27790.11 193
SCA74.22 25372.33 26079.91 24084.05 26162.17 24779.96 29779.29 32866.30 25472.38 25880.13 32051.95 25188.60 28659.25 27077.67 25088.96 236
CNLPA78.08 19876.79 20781.97 19590.40 10971.07 6987.59 15584.55 26766.03 25872.38 25889.64 14457.56 20586.04 30759.61 26783.35 18988.79 243
NR-MVSNet80.23 14779.38 14582.78 17987.80 19563.34 22986.31 19391.09 13379.01 2972.17 26089.07 16167.20 9892.81 19166.08 21775.65 27792.20 127
OpenMVScopyleft72.83 1079.77 15578.33 17084.09 12485.17 24269.91 9490.57 6390.97 13466.70 24772.17 26091.91 8954.70 22593.96 13361.81 25190.95 10088.41 253
MVS78.19 19676.99 20281.78 19785.66 23466.99 15584.66 23190.47 14555.08 34772.02 26285.27 26063.83 13094.11 13166.10 21689.80 11584.24 321
XVG-ACMP-BASELINE76.11 23674.27 24381.62 20083.20 27764.67 20083.60 25889.75 16769.75 20571.85 26387.09 21532.78 35692.11 21469.99 17980.43 22488.09 256
PatchmatchNetpermissive73.12 26671.33 26978.49 26683.18 27860.85 26279.63 29978.57 33064.13 27971.73 26479.81 32551.20 26085.97 30857.40 28976.36 27188.66 246
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
tpmrst72.39 27272.13 26173.18 31880.54 32449.91 35579.91 29879.08 32963.11 28971.69 26579.95 32255.32 21882.77 33065.66 22173.89 30286.87 285
TransMVSNet (Re)75.39 24674.56 23877.86 27285.50 23857.10 30486.78 17986.09 25372.17 16171.53 26687.34 20563.01 14489.31 27456.84 29461.83 34887.17 278
Fast-Effi-MVS+-dtu78.02 20176.49 21482.62 18383.16 28066.96 15986.94 17287.45 23272.45 15471.49 26784.17 27554.79 22491.58 23067.61 20180.31 22589.30 223
PAPM77.68 21076.40 21781.51 20387.29 21361.85 25183.78 25389.59 17164.74 27271.23 26888.70 16862.59 14893.66 15352.66 31087.03 14789.01 232
tfpnnormal74.39 25073.16 25378.08 27086.10 22958.05 28884.65 23487.53 22970.32 19371.22 26985.63 25354.97 22089.86 26443.03 35275.02 29286.32 294
RPSCF73.23 26571.46 26678.54 26482.50 29659.85 27382.18 27482.84 29658.96 32571.15 27089.41 15645.48 31084.77 31758.82 27671.83 31991.02 161
DWT-MVSNet_test73.70 25871.86 26379.21 25582.91 28758.94 27982.34 27282.17 30065.21 26571.05 27178.31 33444.21 31590.17 26163.29 23777.28 25288.53 250
PatchT68.46 30267.85 29670.29 33080.70 32243.93 36572.47 33974.88 34660.15 31570.55 27276.57 34449.94 27481.59 33350.58 31774.83 29485.34 308
CL-MVSNet_self_test72.37 27471.46 26675.09 30279.49 33853.53 33680.76 28785.01 26369.12 21970.51 27382.05 30457.92 20184.13 32052.27 31166.00 34087.60 266
IterMVS-SCA-FT75.43 24473.87 24780.11 23782.69 29264.85 19781.57 28183.47 28569.16 21870.49 27484.15 27651.95 25188.15 29169.23 18672.14 31787.34 273
miper_lstm_enhance74.11 25473.11 25477.13 28680.11 32859.62 27572.23 34086.92 24166.76 24670.40 27582.92 29156.93 21382.92 32969.06 18972.63 31388.87 239
gg-mvs-nofinetune69.95 29167.96 29475.94 29383.07 28154.51 33077.23 32170.29 35663.11 28970.32 27662.33 35943.62 31888.69 28553.88 30587.76 13584.62 319
DP-MVS76.78 22574.57 23783.42 14693.29 5469.46 10788.55 12283.70 27963.98 28470.20 27788.89 16554.01 23294.80 10746.66 34081.88 20886.01 302
pmmvs674.69 24973.39 25078.61 26281.38 31357.48 30086.64 18387.95 22064.99 27170.18 27886.61 23050.43 26989.52 27062.12 24770.18 32788.83 241
PVSNet64.34 1872.08 27670.87 27575.69 29586.21 22856.44 31474.37 33680.73 31362.06 30370.17 27982.23 30242.86 32283.31 32754.77 30284.45 17687.32 274
131476.53 22775.30 23280.21 23583.93 26362.32 24584.66 23188.81 19860.23 31470.16 28084.07 27755.30 21990.73 25467.37 20483.21 19187.59 268
Patchmtry70.74 28269.16 28475.49 29980.72 32154.07 33374.94 33580.30 32058.34 32970.01 28181.19 30852.50 24086.54 30353.37 30771.09 32485.87 305
EPMVS69.02 29668.16 29171.59 32279.61 33649.80 35777.40 32066.93 36462.82 29570.01 28179.05 32745.79 30677.86 34956.58 29575.26 29087.13 281
IterMVS74.29 25172.94 25578.35 26781.53 31063.49 22581.58 28082.49 29868.06 23769.99 28383.69 28451.66 25785.54 31065.85 21971.64 32086.01 302
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
test-LLR72.94 26972.43 25874.48 30781.35 31458.04 28978.38 31177.46 33566.66 24869.95 28479.00 32948.06 29079.24 34166.13 21484.83 17086.15 298
test-mter71.41 27870.39 27974.48 30781.35 31458.04 28978.38 31177.46 33560.32 31369.95 28479.00 32936.08 35079.24 34166.13 21484.83 17086.15 298
pmmvs474.03 25671.91 26280.39 23081.96 30468.32 13181.45 28282.14 30159.32 32269.87 28685.13 26452.40 24288.13 29260.21 26374.74 29584.73 317
PLCcopyleft70.83 1178.05 20076.37 21883.08 16291.88 8567.80 14188.19 13789.46 17464.33 27869.87 28688.38 17953.66 23493.58 15458.86 27582.73 19887.86 261
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
LTVRE_ROB69.57 1376.25 23474.54 23981.41 20588.60 17164.38 20879.24 30389.12 18970.76 18669.79 28887.86 19349.09 28493.20 17256.21 29880.16 22686.65 291
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
LS3D76.95 22374.82 23583.37 14990.45 10767.36 15189.15 10086.94 24061.87 30469.52 28990.61 12351.71 25694.53 11346.38 34386.71 15288.21 255
IB-MVS68.01 1575.85 23973.36 25183.31 15084.76 24966.03 17183.38 26185.06 26170.21 19669.40 29081.05 31045.76 30794.66 11165.10 22575.49 28089.25 224
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
PatchMatch-RL72.38 27370.90 27376.80 28988.60 17167.38 15079.53 30076.17 34362.75 29669.36 29182.00 30645.51 30984.89 31653.62 30680.58 22178.12 353
MDTV_nov1_ep1369.97 28183.18 27853.48 33777.10 32280.18 32360.45 31169.33 29280.44 31748.89 28886.90 30151.60 31478.51 242
D2MVS74.82 24873.21 25279.64 24879.81 33262.56 24280.34 29387.35 23364.37 27768.86 29382.66 29646.37 30090.10 26267.91 19981.24 21386.25 295
PMMVS69.34 29468.67 28671.35 32675.67 35262.03 24875.17 33073.46 35150.00 35668.68 29479.05 32752.07 24978.13 34661.16 25782.77 19773.90 357
Patchmatch-RL test70.24 28867.78 29977.61 27877.43 34659.57 27771.16 34270.33 35562.94 29368.65 29572.77 35350.62 26685.49 31169.58 18466.58 33887.77 263
MS-PatchMatch73.83 25772.67 25677.30 28383.87 26466.02 17281.82 27684.66 26561.37 30868.61 29682.82 29447.29 29488.21 29059.27 26984.32 17777.68 354
tpm cat170.57 28468.31 28977.35 28282.41 29957.95 29278.08 31580.22 32252.04 35368.54 29777.66 34052.00 25087.84 29551.77 31272.07 31886.25 295
TESTMET0.1,169.89 29269.00 28572.55 31979.27 34156.85 30678.38 31174.71 34957.64 33468.09 29877.19 34237.75 34576.70 35263.92 23184.09 17984.10 324
MIMVSNet70.69 28369.30 28274.88 30484.52 25256.35 31775.87 32879.42 32764.59 27367.76 29982.41 29841.10 33281.54 33446.64 34281.34 21186.75 289
ACMH+68.96 1476.01 23774.01 24482.03 19388.60 17165.31 19088.86 10887.55 22870.25 19567.75 30087.47 20341.27 33193.19 17458.37 28075.94 27487.60 266
LCM-MVSNet-Re77.05 22076.94 20377.36 28187.20 21451.60 34780.06 29580.46 31875.20 10267.69 30186.72 22262.48 15088.98 28063.44 23489.25 12091.51 144
ITE_SJBPF78.22 26881.77 30660.57 26683.30 28769.25 21467.54 30287.20 21136.33 34987.28 30054.34 30374.62 29686.80 287
pmmvs571.55 27770.20 28075.61 29677.83 34456.39 31581.74 27880.89 31057.76 33367.46 30384.49 27149.26 28385.32 31357.08 29275.29 28985.11 313
MVP-Stereo76.12 23574.46 24181.13 21685.37 24069.79 9784.42 24287.95 22065.03 26967.46 30385.33 25953.28 23791.73 22858.01 28483.27 19081.85 340
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
test_040272.79 27070.44 27779.84 24288.13 18465.99 17385.93 20384.29 27165.57 26367.40 30585.49 25646.92 29792.61 19335.88 36174.38 29880.94 345
GG-mvs-BLEND75.38 30081.59 30955.80 32279.32 30269.63 35867.19 30673.67 35243.24 31988.90 28450.41 31884.50 17481.45 342
tpmvs71.09 28069.29 28376.49 29082.04 30356.04 32078.92 30881.37 30964.05 28267.18 30778.28 33549.74 27789.77 26549.67 32672.37 31483.67 326
OurMVSNet-221017-074.26 25272.42 25979.80 24383.76 26659.59 27685.92 20486.64 24366.39 25366.96 30887.58 19839.46 33791.60 22965.76 22069.27 32988.22 254
baseline275.70 24073.83 24881.30 21083.26 27561.79 25382.57 27180.65 31466.81 24466.88 30983.42 28757.86 20292.19 21163.47 23379.57 23189.91 206
MVS_030472.48 27170.89 27477.24 28482.20 30159.68 27484.11 24983.49 28467.10 24366.87 31080.59 31635.00 35387.40 29859.07 27379.58 23084.63 318
F-COLMAP76.38 23374.33 24282.50 18589.28 14566.95 16088.41 12689.03 19064.05 28266.83 31188.61 17246.78 29892.89 18757.48 28778.55 24087.67 264
ACMH67.68 1675.89 23873.93 24581.77 19888.71 16866.61 16288.62 11989.01 19269.81 20266.78 31286.70 22741.95 33091.51 23455.64 29978.14 24687.17 278
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
test0.0.03 168.00 30367.69 30068.90 33577.55 34547.43 35975.70 32972.95 35366.66 24866.56 31382.29 30148.06 29075.87 35644.97 34974.51 29783.41 328
MDTV_nov1_ep13_2view37.79 37075.16 33155.10 34666.53 31449.34 28153.98 30487.94 259
KD-MVS_2432*160066.22 31463.89 31573.21 31575.47 35553.42 33870.76 34584.35 26964.10 28066.52 31578.52 33234.55 35484.98 31450.40 31950.33 36381.23 343
miper_refine_blended66.22 31463.89 31573.21 31575.47 35553.42 33870.76 34584.35 26964.10 28066.52 31578.52 33234.55 35484.98 31450.40 31950.33 36381.23 343
ET-MVSNet_ETH3D78.63 18476.63 21384.64 10586.73 22369.47 10585.01 22484.61 26669.54 20866.51 31786.59 23150.16 27191.75 22676.26 12484.24 17892.69 110
EU-MVSNet68.53 30167.61 30171.31 32778.51 34347.01 36184.47 23784.27 27242.27 35966.44 31884.79 26940.44 33583.76 32258.76 27768.54 33483.17 330
EPNet_dtu75.46 24374.86 23477.23 28582.57 29554.60 32886.89 17483.09 29371.64 16766.25 31985.86 24855.99 21688.04 29354.92 30186.55 15489.05 230
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
Anonymous2023120668.60 29967.80 29871.02 32880.23 32750.75 35378.30 31480.47 31756.79 34066.11 32082.63 29746.35 30178.95 34343.62 35175.70 27683.36 329
SixPastTwentyTwo73.37 26171.26 27179.70 24585.08 24757.89 29385.57 21083.56 28271.03 18065.66 32185.88 24742.10 32892.57 19459.11 27263.34 34688.65 247
MSDG73.36 26370.99 27280.49 22984.51 25365.80 17980.71 28886.13 25265.70 26165.46 32283.74 28344.60 31290.91 25051.13 31676.89 25984.74 316
OpenMVS_ROBcopyleft64.09 1970.56 28568.19 29077.65 27780.26 32659.41 27885.01 22482.96 29558.76 32765.43 32382.33 29937.63 34691.23 24145.34 34876.03 27382.32 337
ppachtmachnet_test70.04 29067.34 30378.14 26979.80 33361.13 25879.19 30580.59 31559.16 32465.27 32479.29 32646.75 29987.29 29949.33 32766.72 33686.00 304
ADS-MVSNet266.20 31663.33 31874.82 30579.92 33058.75 28267.55 35575.19 34553.37 35065.25 32575.86 34642.32 32580.53 33941.57 35568.91 33185.18 310
ADS-MVSNet64.36 32062.88 32268.78 33779.92 33047.17 36067.55 35571.18 35453.37 35065.25 32575.86 34642.32 32573.99 36341.57 35568.91 33185.18 310
testgi66.67 31066.53 30867.08 34175.62 35341.69 36875.93 32576.50 34266.11 25565.20 32786.59 23135.72 35174.71 36043.71 35073.38 30984.84 315
PM-MVS66.41 31264.14 31473.20 31773.92 35956.45 31378.97 30764.96 36863.88 28664.72 32880.24 31919.84 36883.44 32666.24 21364.52 34479.71 350
JIA-IIPM66.32 31362.82 32376.82 28877.09 34861.72 25465.34 35875.38 34458.04 33264.51 32962.32 36042.05 32986.51 30451.45 31569.22 33082.21 338
ambc75.24 30173.16 36350.51 35463.05 36287.47 23164.28 33077.81 33917.80 36989.73 26757.88 28560.64 35185.49 306
EG-PatchMatch MVS74.04 25571.82 26480.71 22584.92 24867.42 14885.86 20688.08 21766.04 25764.22 33183.85 27935.10 35292.56 19557.44 28880.83 21782.16 339
dp66.80 30865.43 31070.90 32979.74 33548.82 35875.12 33374.77 34759.61 31964.08 33277.23 34142.89 32180.72 33848.86 32966.58 33883.16 331
KD-MVS_self_test68.81 29767.59 30272.46 32074.29 35845.45 36277.93 31787.00 23963.12 28863.99 33378.99 33142.32 32584.77 31756.55 29664.09 34587.16 280
pmmvs-eth3d70.50 28667.83 29778.52 26577.37 34766.18 17081.82 27681.51 30758.90 32663.90 33480.42 31842.69 32386.28 30658.56 27865.30 34283.11 332
COLMAP_ROBcopyleft66.92 1773.01 26770.41 27880.81 22387.13 21665.63 18288.30 13284.19 27462.96 29263.80 33587.69 19638.04 34492.56 19546.66 34074.91 29384.24 321
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
FMVSNet569.50 29367.96 29474.15 31182.97 28655.35 32580.01 29682.12 30262.56 29863.02 33681.53 30736.92 34781.92 33248.42 33074.06 30085.17 312
test20.0367.45 30566.95 30668.94 33475.48 35444.84 36477.50 31977.67 33466.66 24863.01 33783.80 28147.02 29678.40 34542.53 35468.86 33383.58 327
K. test v371.19 27968.51 28779.21 25583.04 28357.78 29684.35 24476.91 34172.90 15362.99 33882.86 29339.27 33891.09 24761.65 25252.66 36088.75 244
our_test_369.14 29567.00 30575.57 29779.80 33358.80 28177.96 31677.81 33359.55 32062.90 33978.25 33647.43 29383.97 32151.71 31367.58 33583.93 325
CHOSEN 280x42066.51 31164.71 31271.90 32181.45 31163.52 22457.98 36368.95 36253.57 34962.59 34076.70 34346.22 30275.29 35955.25 30079.68 22976.88 356
Anonymous2024052168.80 29867.22 30473.55 31374.33 35754.11 33283.18 26385.61 25658.15 33061.68 34180.94 31330.71 36081.27 33657.00 29373.34 31085.28 309
USDC70.33 28768.37 28876.21 29280.60 32356.23 31879.19 30586.49 24560.89 30961.29 34285.47 25731.78 35989.47 27253.37 30776.21 27282.94 336
lessismore_v078.97 25781.01 32057.15 30365.99 36561.16 34382.82 29439.12 33991.34 23859.67 26646.92 36588.43 252
UnsupCasMVSNet_eth67.33 30665.99 30971.37 32473.48 36151.47 34975.16 33185.19 26065.20 26660.78 34480.93 31542.35 32477.20 35157.12 29153.69 35985.44 307
AllTest70.96 28168.09 29379.58 24985.15 24363.62 21984.58 23679.83 32462.31 30060.32 34586.73 22032.02 35788.96 28250.28 32171.57 32186.15 298
TestCases79.58 24985.15 24363.62 21979.83 32462.31 30060.32 34586.73 22032.02 35788.96 28250.28 32171.57 32186.15 298
Patchmatch-test64.82 31963.24 31969.57 33279.42 33949.82 35663.49 36169.05 36151.98 35459.95 34780.13 32050.91 26270.98 36540.66 35773.57 30587.90 260
MIMVSNet168.58 30066.78 30773.98 31280.07 32951.82 34580.77 28684.37 26864.40 27659.75 34882.16 30336.47 34883.63 32442.73 35370.33 32686.48 293
LF4IMVS64.02 32162.19 32469.50 33370.90 36653.29 34176.13 32377.18 33952.65 35258.59 34980.98 31223.55 36576.52 35353.06 30966.66 33778.68 352
PVSNet_057.27 2061.67 32459.27 32768.85 33679.61 33657.44 30168.01 35473.44 35255.93 34458.54 35070.41 35644.58 31377.55 35047.01 33935.91 36671.55 359
TDRefinement67.49 30464.34 31376.92 28773.47 36261.07 25984.86 22882.98 29459.77 31858.30 35185.13 26426.06 36287.89 29447.92 33760.59 35281.81 341
UnsupCasMVSNet_bld63.70 32261.53 32670.21 33173.69 36051.39 35072.82 33881.89 30355.63 34557.81 35271.80 35538.67 34078.61 34449.26 32852.21 36180.63 346
DSMNet-mixed57.77 32756.90 32960.38 34567.70 36835.61 37169.18 35053.97 37332.30 36857.49 35379.88 32340.39 33668.57 36738.78 35972.37 31476.97 355
N_pmnet52.79 33053.26 33151.40 35078.99 3427.68 38169.52 3483.89 38151.63 35557.01 35474.98 35040.83 33465.96 36837.78 36064.67 34380.56 348
new-patchmatchnet61.73 32361.73 32561.70 34472.74 36524.50 37869.16 35178.03 33261.40 30656.72 35575.53 34938.42 34176.48 35445.95 34557.67 35484.13 323
CMPMVSbinary51.72 2170.19 28968.16 29176.28 29173.15 36457.55 29979.47 30183.92 27648.02 35756.48 35684.81 26843.13 32086.42 30562.67 24281.81 20984.89 314
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
TinyColmap67.30 30764.81 31174.76 30681.92 30556.68 31180.29 29481.49 30860.33 31256.27 35783.22 28924.77 36387.66 29745.52 34669.47 32879.95 349
YYNet165.03 31762.91 32171.38 32375.85 35156.60 31269.12 35274.66 35057.28 33854.12 35877.87 33845.85 30574.48 36149.95 32461.52 35083.05 333
MDA-MVSNet_test_wron65.03 31762.92 32071.37 32475.93 35056.73 30869.09 35374.73 34857.28 33854.03 35977.89 33745.88 30474.39 36249.89 32561.55 34982.99 335
pmmvs357.79 32654.26 33068.37 33864.02 37056.72 30975.12 33365.17 36640.20 36152.93 36069.86 35720.36 36775.48 35845.45 34755.25 35872.90 358
MVS-HIRNet59.14 32557.67 32863.57 34381.65 30743.50 36671.73 34165.06 36739.59 36351.43 36157.73 36338.34 34282.58 33139.53 35873.95 30164.62 362
MDA-MVSNet-bldmvs66.68 30963.66 31775.75 29479.28 34060.56 26773.92 33778.35 33164.43 27550.13 36279.87 32444.02 31783.67 32346.10 34456.86 35583.03 334
new_pmnet50.91 33250.29 33352.78 34968.58 36734.94 37363.71 36056.63 37239.73 36244.95 36365.47 35821.93 36658.48 36934.98 36256.62 35664.92 361
FPMVS53.68 32951.64 33259.81 34665.08 36951.03 35169.48 34969.58 35941.46 36040.67 36472.32 35416.46 37170.00 36624.24 36865.42 34158.40 365
LCM-MVSNet54.25 32849.68 33467.97 33953.73 37345.28 36366.85 35780.78 31235.96 36539.45 36562.23 3618.70 37778.06 34848.24 33451.20 36280.57 347
PMMVS240.82 33638.86 33946.69 35153.84 37216.45 37948.61 36649.92 37437.49 36431.67 36660.97 3628.14 37856.42 37028.42 36530.72 36867.19 360
ANet_high50.57 33346.10 33663.99 34248.67 37639.13 36970.99 34480.85 31161.39 30731.18 36757.70 36417.02 37073.65 36431.22 36315.89 37379.18 351
Gipumacopyleft45.18 33441.86 33755.16 34877.03 34951.52 34832.50 36980.52 31632.46 36727.12 36835.02 3699.52 37675.50 35722.31 36960.21 35338.45 368
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
PMVScopyleft37.38 2244.16 33540.28 33855.82 34740.82 37842.54 36765.12 35963.99 36934.43 36624.48 36957.12 3653.92 37976.17 35517.10 37155.52 35748.75 366
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
DeepMVS_CXcopyleft27.40 35640.17 37926.90 37624.59 38017.44 37223.95 37048.61 3679.77 37526.48 37518.06 37024.47 36928.83 369
tmp_tt18.61 34221.40 34510.23 3584.82 38110.11 38034.70 36830.74 3791.48 37523.91 37126.07 37228.42 36113.41 37727.12 36615.35 3747.17 372
test_method31.52 33829.28 34238.23 35327.03 3806.50 38220.94 37162.21 3714.05 37422.35 37252.50 36613.33 37247.58 37327.04 36734.04 36760.62 363
MVEpermissive26.22 2330.37 34025.89 34443.81 35244.55 37735.46 37228.87 37039.07 37718.20 37118.58 37340.18 3682.68 38047.37 37417.07 37223.78 37048.60 367
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
E-PMN31.77 33730.64 34035.15 35452.87 37427.67 37557.09 36447.86 37524.64 36916.40 37433.05 37011.23 37454.90 37114.46 37318.15 37122.87 370
EMVS30.81 33929.65 34134.27 35550.96 37525.95 37756.58 36546.80 37624.01 37015.53 37530.68 37112.47 37354.43 37212.81 37417.05 37222.43 371
wuyk23d16.82 34315.94 34619.46 35758.74 37131.45 37439.22 3673.74 3826.84 3736.04 3762.70 3761.27 38124.29 37610.54 37514.40 3752.63 373
EGC-MVSNET52.07 33147.05 33567.14 34083.51 27060.71 26480.50 29167.75 3630.07 3760.43 37775.85 34824.26 36481.54 33428.82 36462.25 34759.16 364
testmvs6.04 3468.02 3490.10 3600.08 3820.03 38469.74 3470.04 3830.05 3770.31 3781.68 3770.02 3830.04 3780.24 3760.02 3760.25 375
test1236.12 3458.11 3480.14 3590.06 3830.09 38371.05 3430.03 3840.04 3780.25 3791.30 3780.05 3820.03 3790.21 3770.01 3770.29 374
test_blank0.00 3480.00 3510.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.00 3790.00 3840.00 3800.00 3780.00 3780.00 376
uanet_test0.00 3480.00 3510.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.00 3790.00 3840.00 3800.00 3780.00 3780.00 376
DCPMVS0.00 3480.00 3510.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.00 3790.00 3840.00 3800.00 3780.00 3780.00 376
cdsmvs_eth3d_5k19.96 34126.61 3430.00 3610.00 3840.00 3850.00 37289.26 1810.00 3790.00 38088.61 17261.62 1640.00 3800.00 3780.00 3780.00 376
pcd_1.5k_mvsjas5.26 3477.02 3500.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.00 37963.15 1400.00 3800.00 3780.00 3780.00 376
sosnet-low-res0.00 3480.00 3510.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.00 3790.00 3840.00 3800.00 3780.00 3780.00 376
sosnet0.00 3480.00 3510.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.00 3790.00 3840.00 3800.00 3780.00 3780.00 376
uncertanet0.00 3480.00 3510.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.00 3790.00 3840.00 3800.00 3780.00 3780.00 376
Regformer0.00 3480.00 3510.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.00 3790.00 3840.00 3800.00 3780.00 3780.00 376
ab-mvs-re7.23 3449.64 3470.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 38086.72 2220.00 3840.00 3800.00 3780.00 3780.00 376
uanet0.00 3480.00 3510.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.00 3790.00 3840.00 3800.00 3780.00 3780.00 376
MSC_two_6792asdad89.16 194.34 2975.53 292.99 4997.53 189.67 196.44 994.41 32
No_MVS89.16 194.34 2975.53 292.99 4997.53 189.67 196.44 994.41 32
eth-test20.00 384
eth-test0.00 384
OPU-MVS89.06 394.62 1575.42 493.57 794.02 4782.45 396.87 1983.77 5596.48 894.88 12
save fliter93.80 4472.35 4590.47 6791.17 13074.31 122
test_0728_SECOND87.71 3495.34 171.43 6293.49 994.23 597.49 389.08 796.41 1294.21 42
GSMVS88.96 236
sam_mvs151.32 25988.96 236
sam_mvs50.01 272
MTGPAbinary92.02 94
test_post178.90 3095.43 37548.81 28985.44 31259.25 270
test_post5.46 37450.36 27084.24 319
patchmatchnet-post74.00 35151.12 26188.60 286
MTMP92.18 3432.83 378
gm-plane-assit81.40 31253.83 33562.72 29780.94 31392.39 20163.40 235
test9_res84.90 3395.70 3192.87 105
agg_prior282.91 6695.45 3392.70 108
test_prior472.60 3589.01 103
test_prior86.33 6392.61 7469.59 10192.97 5495.48 7093.91 55
新几何286.29 195
旧先验191.96 8265.79 18086.37 24893.08 6969.31 8192.74 7688.74 245
无先验87.48 15788.98 19360.00 31694.12 12967.28 20588.97 235
原ACMM286.86 175
testdata291.01 24962.37 244
segment_acmp73.08 45
testdata184.14 24875.71 90
plane_prior790.08 11568.51 129
plane_prior689.84 12468.70 12460.42 188
plane_prior592.44 7595.38 7978.71 9986.32 15791.33 150
plane_prior491.00 117
plane_prior291.25 5079.12 26
plane_prior189.90 123
plane_prior68.71 12290.38 7177.62 4186.16 160
n20.00 385
nn0.00 385
door-mid69.98 357
test1192.23 86
door69.44 360
HQP5-MVS66.98 156
BP-MVS77.47 113
HQP3-MVS92.19 8985.99 163
HQP2-MVS60.17 191
NP-MVS89.62 12668.32 13190.24 128
ACMMP++_ref81.95 207
ACMMP++81.25 212
Test By Simon64.33 125