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

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

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

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

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




Method Infoallhigh-res
multi-view
indooroutdoorbotani.boulde.bridgedoorexhibi.lectur.living.loungeobserv.old co.statueterrac.
sort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysorted bysort bysort bysort bysort bysort by
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 25
SMA-MVScopyleft89.08 789.23 788.61 594.25 3373.73 1092.40 2293.63 2374.77 10992.29 795.97 274.28 3497.24 1188.58 1396.91 194.87 11
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
test072695.27 571.25 6393.60 694.11 877.33 4992.81 395.79 380.98 9
DVP-MVScopyleft89.60 390.35 387.33 4595.27 571.25 6393.49 992.73 6577.33 4992.12 995.78 480.98 997.40 789.08 796.41 1293.33 79
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 3392.12 995.78 481.46 797.40 789.42 496.57 794.67 18
DVP-MVS++.90.23 191.01 187.89 2494.34 2971.25 6395.06 194.23 578.38 3392.78 495.74 682.45 397.49 389.42 496.68 294.95 5
test_one_060195.07 771.46 6194.14 778.27 3592.05 1195.74 680.83 11
SED-MVS90.08 290.85 287.77 2695.30 270.98 7093.57 794.06 1277.24 5193.10 195.72 882.99 197.44 589.07 996.63 494.88 9
test_241102_TWO94.06 1277.24 5192.78 495.72 881.26 897.44 589.07 996.58 694.26 35
DPE-MVScopyleft89.48 589.98 488.01 1494.80 1172.69 3291.59 4294.10 1075.90 8892.29 795.66 1081.67 697.38 987.44 2096.34 1593.95 48
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
test_241102_ONE95.30 270.98 7094.06 1277.17 5593.10 195.39 1182.99 197.27 10
MP-MVS-pluss87.67 2287.72 2287.54 3993.64 5072.04 5289.80 8393.50 2875.17 10386.34 4095.29 1270.86 6096.00 5388.78 1296.04 1694.58 21
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
xxxxxxxxxxxxxcwj87.88 1987.92 1987.77 2693.80 4472.35 4590.47 6689.69 16874.31 11989.16 1995.10 1375.65 2196.19 4587.07 2196.01 1794.79 13
SF-MVS88.46 1188.74 1187.64 3892.78 6971.95 5392.40 2294.74 275.71 9089.16 1995.10 1375.65 2196.19 4587.07 2196.01 1794.79 13
ACMMP_NAP88.05 1688.08 1787.94 1793.70 4773.05 2390.86 5693.59 2576.27 8188.14 2695.09 1571.06 5996.67 2887.67 1696.37 1494.09 40
zzz-MVS87.53 2487.41 2787.90 2194.18 3774.25 590.23 7392.02 9479.45 1985.88 4294.80 1668.07 8696.21 4386.69 2495.34 3693.23 82
MTAPA87.23 3387.00 3487.90 2194.18 3774.25 586.58 18292.02 9479.45 1985.88 4294.80 1668.07 8696.21 4386.69 2495.34 3693.23 82
SteuartSystems-ACMMP88.72 1088.86 1088.32 892.14 8072.96 2693.73 593.67 2280.19 1488.10 2794.80 1673.76 3997.11 1387.51 1895.82 2494.90 8
Skip Steuart: Steuart Systems R&D Blog.
9.1488.26 1592.84 6891.52 4594.75 173.93 12988.57 2494.67 1975.57 2395.79 5986.77 2395.76 28
SR-MVS86.73 3986.67 4086.91 5294.11 4072.11 5192.37 2692.56 7374.50 11486.84 3794.65 2067.31 9595.77 6084.80 3792.85 7492.84 99
ETH3D-3000-0.188.09 1388.29 1487.50 4192.76 7071.89 5691.43 4694.70 374.47 11688.86 2294.61 2175.23 2495.84 5886.62 2695.92 2194.78 15
test117286.20 5086.22 4786.12 7093.95 4269.89 9691.79 4192.28 8275.07 10486.40 3994.58 2265.00 12095.56 6684.34 4592.60 7792.90 97
region2R87.42 2887.20 3288.09 1294.63 1473.55 1393.03 1493.12 4276.73 7084.45 6894.52 2369.09 8096.70 2684.37 4494.83 5094.03 43
ACMMPR87.44 2687.23 3188.08 1394.64 1373.59 1293.04 1293.20 3976.78 6784.66 6594.52 2368.81 8496.65 2984.53 4194.90 4594.00 46
APD-MVScopyleft87.44 2687.52 2487.19 4794.24 3472.39 4291.86 3992.83 6173.01 14788.58 2394.52 2373.36 4096.49 3784.26 4695.01 4292.70 101
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
APD-MVS_3200maxsize85.97 5285.88 5386.22 6792.69 7269.53 10391.93 3692.99 4973.54 13785.94 4194.51 2665.80 11295.61 6383.04 6292.51 7993.53 74
CP-MVS87.11 3586.92 3687.68 3794.20 3673.86 893.98 392.82 6476.62 7283.68 8294.46 2767.93 8895.95 5684.20 4894.39 5993.23 82
SR-MVS-dyc-post85.77 5585.61 5686.23 6693.06 6270.63 8291.88 3792.27 8373.53 13885.69 4694.45 2865.00 12095.56 6682.75 6591.87 8392.50 108
RE-MVS-def85.48 5793.06 6270.63 8291.88 3792.27 8373.53 13885.69 4694.45 2863.87 12782.75 6591.87 8392.50 108
HFP-MVS87.58 2387.47 2587.94 1794.58 1673.54 1593.04 1293.24 3776.78 6784.91 5694.44 3070.78 6196.61 3284.53 4194.89 4693.66 62
#test#87.33 3187.13 3387.94 1794.58 1673.54 1592.34 2793.24 3775.23 10084.91 5694.44 3070.78 6196.61 3283.75 5494.89 4693.66 62
testtj87.78 2087.78 2187.77 2694.55 1872.47 3992.23 3193.49 3074.75 11088.33 2594.43 3273.27 4297.02 1684.18 4994.84 4893.82 56
PGM-MVS86.68 4186.27 4687.90 2194.22 3573.38 1990.22 7493.04 4375.53 9483.86 7994.42 3367.87 9096.64 3082.70 6994.57 5593.66 62
MP-MVScopyleft87.71 2187.64 2387.93 2094.36 2873.88 792.71 2192.65 7077.57 4283.84 8094.40 3472.24 5096.28 4185.65 2895.30 4093.62 69
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
ZNCC-MVS87.94 1887.85 2088.20 1194.39 2673.33 2093.03 1493.81 2076.81 6585.24 5194.32 3571.76 5496.93 1885.53 2995.79 2594.32 32
ETH3D cwj APD-0.1687.31 3287.27 2887.44 4391.60 8772.45 4190.02 7794.37 471.76 16187.28 3494.27 3675.18 2596.08 4985.16 3095.77 2693.80 59
HPM-MVS++copyleft89.02 889.15 888.63 495.01 976.03 192.38 2592.85 6080.26 1387.78 3094.27 3675.89 1996.81 2287.45 1996.44 993.05 90
mPP-MVS86.67 4286.32 4587.72 3294.41 2473.55 1392.74 1992.22 8776.87 6482.81 9594.25 3866.44 10296.24 4282.88 6494.28 6293.38 76
DeepC-MVS79.81 287.08 3786.88 3887.69 3691.16 9172.32 4790.31 7193.94 1777.12 5782.82 9494.23 3972.13 5297.09 1484.83 3695.37 3593.65 67
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
XVS87.18 3486.91 3788.00 1594.42 2273.33 2092.78 1792.99 4979.14 2283.67 8394.17 4067.45 9396.60 3483.06 6094.50 5694.07 41
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 18
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
abl_685.23 6484.95 7086.07 7192.23 7970.48 8690.80 5892.08 9273.51 14085.26 5094.16 4162.75 14495.92 5782.46 7291.30 9291.81 132
DeepPCF-MVS80.84 188.10 1288.56 1286.73 5692.24 7869.03 11089.57 8993.39 3577.53 4689.79 1894.12 4378.98 1296.58 3685.66 2795.72 2994.58 21
HPM-MVS_fast85.35 6384.95 7086.57 6193.69 4870.58 8592.15 3491.62 11373.89 13082.67 9794.09 4462.60 14595.54 6980.93 8192.93 7293.57 71
ZD-MVS94.38 2772.22 4892.67 6770.98 17687.75 3194.07 4574.01 3896.70 2684.66 3994.84 48
CNVR-MVS88.93 989.13 988.33 794.77 1273.82 990.51 6393.00 4780.90 988.06 2894.06 4676.43 1696.84 2088.48 1495.99 1994.34 31
OPU-MVS89.06 394.62 1575.42 493.57 794.02 4782.45 396.87 1983.77 5396.48 894.88 9
PC_three_145268.21 23192.02 1294.00 4882.09 595.98 5584.58 4096.68 294.95 5
SD-MVS88.06 1488.50 1386.71 5792.60 7672.71 3091.81 4093.19 4077.87 3690.32 1794.00 4874.83 2793.78 14587.63 1794.27 6393.65 67
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
GST-MVS87.42 2887.26 2987.89 2494.12 3972.97 2592.39 2493.43 3376.89 6384.68 6293.99 5070.67 6496.82 2184.18 4995.01 4293.90 51
HPM-MVScopyleft87.11 3586.98 3587.50 4193.88 4372.16 4992.19 3293.33 3676.07 8483.81 8193.95 5169.77 7496.01 5285.15 3194.66 5294.32 32
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
TSAR-MVS + MP.88.02 1788.11 1687.72 3293.68 4972.13 5091.41 4792.35 8074.62 11388.90 2193.85 5275.75 2096.00 5387.80 1594.63 5395.04 3
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
ACMMPcopyleft85.89 5485.39 5987.38 4493.59 5172.63 3492.74 1993.18 4176.78 6780.73 12093.82 5364.33 12396.29 4082.67 7090.69 9793.23 82
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
test_prior386.73 3986.86 3986.33 6392.61 7469.59 10188.85 10892.97 5475.41 9684.91 5693.54 5474.28 3495.48 7183.31 5595.86 2293.91 49
test_prior288.85 10875.41 9684.91 5693.54 5474.28 3483.31 5595.86 22
ETH3 D test640087.50 2587.44 2687.70 3593.71 4671.75 5790.62 6194.05 1570.80 17887.59 3393.51 5677.57 1496.63 3183.31 5595.77 2694.72 17
VDDNet81.52 11580.67 11884.05 12690.44 10564.13 20989.73 8685.91 25271.11 17383.18 8793.48 5750.54 26693.49 16073.40 14888.25 12794.54 24
CDPH-MVS85.76 5685.29 6387.17 4893.49 5371.08 6888.58 12192.42 7868.32 23084.61 6693.48 5772.32 4996.15 4879.00 9495.43 3494.28 34
NCCC88.06 1488.01 1888.24 1094.41 2473.62 1191.22 5192.83 6181.50 685.79 4593.47 5973.02 4597.00 1784.90 3394.94 4494.10 39
3Dnovator+77.84 485.48 5984.47 7488.51 691.08 9273.49 1793.18 1193.78 2180.79 1076.66 18493.37 6060.40 18896.75 2577.20 11493.73 6895.29 2
DeepC-MVS_fast79.65 386.91 3886.62 4187.76 2993.52 5272.37 4491.26 4893.04 4376.62 7284.22 7393.36 6171.44 5796.76 2480.82 8395.33 3894.16 37
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
VDD-MVS83.01 9282.36 9384.96 9191.02 9466.40 16488.91 10588.11 21277.57 4284.39 7193.29 6252.19 24393.91 14077.05 11688.70 12194.57 23
UA-Net85.08 6884.96 6985.45 7892.07 8168.07 13789.78 8490.86 13782.48 284.60 6793.20 6369.35 7795.22 8771.39 16490.88 9693.07 89
agg_prior186.22 4986.09 5286.62 5992.85 6671.94 5488.59 12091.78 10968.96 22084.41 6993.18 6474.94 2694.93 9884.75 3895.33 3893.01 93
TEST993.26 5672.96 2688.75 11391.89 10368.44 22985.00 5493.10 6574.36 3395.41 77
train_agg86.43 4586.20 4887.13 4993.26 5672.96 2688.75 11391.89 10368.69 22585.00 5493.10 6574.43 3095.41 7784.97 3295.71 3093.02 92
test_893.13 5872.57 3688.68 11891.84 10668.69 22584.87 6093.10 6574.43 3095.16 89
LFMVS81.82 10881.23 10983.57 14191.89 8463.43 22589.84 8081.85 30377.04 6083.21 8693.10 6552.26 24293.43 16571.98 15989.95 10993.85 53
旧先验191.96 8265.79 17786.37 24693.08 6969.31 7992.74 7588.74 240
testdata79.97 23590.90 9664.21 20784.71 26259.27 31885.40 4892.91 7062.02 15889.08 27468.95 18891.37 9086.63 287
MCST-MVS87.37 3087.25 3087.73 3094.53 1972.46 4089.82 8193.82 1973.07 14584.86 6192.89 7176.22 1796.33 3984.89 3595.13 4194.40 28
Vis-MVSNetpermissive83.46 8282.80 8885.43 7990.25 10868.74 12090.30 7290.13 15676.33 8080.87 11992.89 7161.00 17794.20 12572.45 15890.97 9493.35 78
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
CPTT-MVS83.73 7783.33 8084.92 9493.28 5570.86 7792.09 3590.38 14668.75 22479.57 12892.83 7360.60 18493.04 18480.92 8291.56 8890.86 160
3Dnovator76.31 583.38 8582.31 9486.59 6087.94 18572.94 2990.64 6092.14 9177.21 5375.47 20992.83 7358.56 19594.72 11073.24 15192.71 7692.13 123
MSLP-MVS++85.43 6185.76 5584.45 10991.93 8370.24 8790.71 5992.86 5977.46 4884.22 7392.81 7567.16 9792.94 18680.36 8894.35 6190.16 184
MG-MVS83.41 8383.45 7883.28 14992.74 7162.28 24488.17 13889.50 17275.22 10181.49 11092.74 7666.75 9895.11 9172.85 15491.58 8792.45 111
casdiffmvs85.11 6785.14 6585.01 8987.20 20965.77 17887.75 14992.83 6177.84 3784.36 7292.38 7772.15 5193.93 13981.27 7990.48 10095.33 1
baseline84.93 7084.98 6784.80 10087.30 20765.39 18687.30 16092.88 5877.62 4084.04 7892.26 7871.81 5393.96 13381.31 7890.30 10295.03 4
QAPM80.88 12479.50 14085.03 8888.01 18468.97 11491.59 4292.00 9766.63 24675.15 22392.16 7957.70 20195.45 7363.52 22788.76 12090.66 166
IS-MVSNet83.15 8782.81 8784.18 12089.94 11563.30 22791.59 4288.46 20979.04 2679.49 12992.16 7965.10 11794.28 11967.71 19591.86 8594.95 5
112180.84 12679.77 13384.05 12693.11 6070.78 7984.66 22785.42 25657.37 33281.76 10992.02 8163.41 13194.12 12967.28 20092.93 7287.26 271
新几何183.42 14493.13 5870.71 8085.48 25557.43 33181.80 10591.98 8263.28 13392.27 20464.60 22492.99 7187.27 270
OpenMVScopyleft72.83 1079.77 15378.33 16684.09 12385.17 23769.91 9490.57 6290.97 13366.70 24272.17 25591.91 8354.70 22393.96 13361.81 24690.95 9588.41 248
PHI-MVS86.43 4586.17 5087.24 4690.88 9770.96 7292.27 3094.07 1172.45 15085.22 5291.90 8469.47 7696.42 3883.28 5895.94 2094.35 30
VNet82.21 10082.41 9181.62 19990.82 9860.93 25884.47 23389.78 16476.36 7984.07 7791.88 8564.71 12290.26 25470.68 16988.89 11793.66 62
DROMVSNet86.01 5186.38 4384.91 9589.31 13666.27 16792.32 2893.63 2379.37 2184.17 7591.88 8569.04 8395.43 7583.93 5293.77 6793.01 93
OPM-MVS83.50 8182.95 8585.14 8588.79 15870.95 7389.13 10091.52 11677.55 4580.96 11891.75 8760.71 18094.50 11579.67 9386.51 15089.97 200
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
XVG-OURS-SEG-HR80.81 12979.76 13483.96 13485.60 23168.78 11783.54 25590.50 14370.66 18376.71 18391.66 8860.69 18191.26 23576.94 11881.58 20591.83 130
EPNet83.72 7882.92 8686.14 6984.22 25269.48 10491.05 5485.27 25781.30 776.83 17991.65 8966.09 10795.56 6676.00 12693.85 6693.38 76
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
OMC-MVS82.69 9581.97 10284.85 9788.75 16067.42 14887.98 14290.87 13674.92 10779.72 12791.65 8962.19 15593.96 13375.26 13386.42 15193.16 87
test22291.50 8868.26 13384.16 24283.20 28954.63 34379.74 12691.63 9158.97 19391.42 8986.77 283
MVS_111021_HR85.14 6684.75 7286.32 6591.65 8672.70 3185.98 19790.33 15076.11 8382.08 10091.61 9271.36 5894.17 12881.02 8092.58 7892.08 124
原ACMM184.35 11493.01 6468.79 11692.44 7563.96 28081.09 11691.57 9366.06 10895.45 7367.19 20394.82 5188.81 237
LPG-MVS_test82.08 10281.27 10884.50 10689.23 14168.76 11890.22 7491.94 10175.37 9876.64 18591.51 9454.29 22694.91 10078.44 10183.78 17689.83 205
LGP-MVS_train84.50 10689.23 14168.76 11891.94 10175.37 9876.64 18591.51 9454.29 22694.91 10078.44 10183.78 17689.83 205
XVG-OURS80.41 14179.23 14783.97 13385.64 23069.02 11183.03 26390.39 14571.09 17477.63 16391.49 9654.62 22591.35 23375.71 12783.47 18391.54 137
alignmvs85.48 5985.32 6185.96 7489.51 12469.47 10589.74 8592.47 7476.17 8287.73 3291.46 9770.32 6793.78 14581.51 7688.95 11694.63 20
CANet86.45 4486.10 5187.51 4090.09 11170.94 7489.70 8792.59 7281.78 481.32 11191.43 9870.34 6697.23 1284.26 4693.36 7094.37 29
hse-mvs383.15 8782.19 9586.02 7390.56 10270.85 7888.15 14089.16 18476.02 8584.67 6391.39 9961.54 16395.50 7082.71 6775.48 27691.72 134
nrg03083.88 7583.53 7784.96 9186.77 21769.28 10990.46 6892.67 6774.79 10882.95 9091.33 10072.70 4693.09 18080.79 8579.28 23392.50 108
canonicalmvs85.91 5385.87 5486.04 7289.84 11769.44 10890.45 6993.00 4776.70 7188.01 2991.23 10173.28 4193.91 14081.50 7788.80 11994.77 16
DPM-MVS84.93 7084.29 7586.84 5390.20 10973.04 2487.12 16493.04 4369.80 19882.85 9391.22 10273.06 4496.02 5176.72 12194.63 5391.46 142
Anonymous20240521178.25 18877.01 19681.99 19391.03 9360.67 26284.77 22583.90 27570.65 18480.00 12591.20 10341.08 32991.43 23165.21 21885.26 16293.85 53
Anonymous2024052980.19 14778.89 15384.10 12290.60 10164.75 19688.95 10490.90 13565.97 25480.59 12191.17 10449.97 27193.73 15169.16 18682.70 19593.81 57
EPP-MVSNet83.40 8483.02 8484.57 10490.13 11064.47 20292.32 2890.73 13874.45 11879.35 13191.10 10569.05 8295.12 9072.78 15587.22 13994.13 38
TAPA-MVS73.13 979.15 16877.94 17382.79 17789.59 12062.99 23788.16 13991.51 11765.77 25577.14 17691.09 10660.91 17893.21 17050.26 31887.05 14192.17 122
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
CSCG86.41 4786.19 4987.07 5092.91 6572.48 3890.81 5793.56 2673.95 12783.16 8891.07 10775.94 1895.19 8879.94 9294.38 6093.55 72
FIs82.07 10382.42 9081.04 21788.80 15758.34 28288.26 13593.49 3076.93 6278.47 14691.04 10869.92 7292.34 20369.87 17984.97 16492.44 112
MVS_111021_LR82.61 9782.11 9684.11 12188.82 15571.58 5985.15 21786.16 24974.69 11180.47 12391.04 10862.29 15290.55 25280.33 8990.08 10790.20 183
DP-MVS Recon83.11 9082.09 9786.15 6894.44 2170.92 7688.79 11192.20 8870.53 18579.17 13291.03 11064.12 12596.03 5068.39 19290.14 10591.50 139
HQP_MVS83.64 7983.14 8185.14 8590.08 11268.71 12291.25 4992.44 7579.12 2478.92 13691.00 11160.42 18695.38 8078.71 9786.32 15291.33 144
plane_prior491.00 111
FC-MVSNet-test81.52 11582.02 10080.03 23488.42 17255.97 31887.95 14493.42 3477.10 5877.38 16790.98 11369.96 7191.79 22168.46 19184.50 16992.33 113
Vis-MVSNet (Re-imp)78.36 18778.45 16078.07 26688.64 16451.78 34086.70 17979.63 32474.14 12575.11 22490.83 11461.29 17189.75 26258.10 27891.60 8692.69 103
114514_t80.68 13579.51 13984.20 11994.09 4167.27 15289.64 8891.11 13158.75 32374.08 23790.72 11558.10 19795.04 9669.70 18089.42 11490.30 180
PAPM_NR83.02 9182.41 9184.82 9892.47 7766.37 16587.93 14691.80 10773.82 13177.32 16990.66 11667.90 8994.90 10270.37 17289.48 11393.19 86
LS3D76.95 21874.82 23083.37 14790.45 10467.36 15189.15 9986.94 23861.87 29969.52 28490.61 11751.71 25494.53 11346.38 33886.71 14788.21 250
VPNet78.69 17978.66 15678.76 25588.31 17555.72 32084.45 23686.63 24276.79 6678.26 15090.55 11859.30 19189.70 26466.63 20777.05 25190.88 159
UniMVSNet_ETH3D79.10 17078.24 16881.70 19886.85 21460.24 26887.28 16188.79 19874.25 12276.84 17890.53 11949.48 27791.56 22767.98 19382.15 19993.29 80
ACMP74.13 681.51 11780.57 11984.36 11389.42 12768.69 12589.97 7991.50 12074.46 11775.04 22790.41 12053.82 23194.54 11277.56 11082.91 19089.86 204
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
PCF-MVS73.52 780.38 14278.84 15485.01 8987.71 19368.99 11383.65 25091.46 12163.00 28677.77 16190.28 12166.10 10695.09 9561.40 24988.22 12890.94 158
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
NP-MVS89.62 11968.32 13190.24 122
HQP-MVS82.61 9782.02 10084.37 11289.33 13166.98 15689.17 9592.19 8976.41 7477.23 17290.23 12360.17 18995.11 9177.47 11185.99 15891.03 154
PS-MVSNAJss82.07 10381.31 10784.34 11586.51 22067.27 15289.27 9391.51 11771.75 16279.37 13090.22 12463.15 13894.27 12077.69 10982.36 19891.49 140
TSAR-MVS + GP.85.71 5785.33 6086.84 5391.34 8972.50 3789.07 10187.28 23276.41 7485.80 4490.22 12474.15 3795.37 8381.82 7591.88 8292.65 105
Regformer-186.41 4786.33 4486.64 5889.33 13170.93 7588.43 12391.39 12282.14 386.65 3890.09 12674.39 3295.01 9783.97 5190.63 9893.97 47
Regformer-286.63 4386.53 4286.95 5189.33 13171.24 6788.43 12392.05 9382.50 186.88 3690.09 12674.45 2995.61 6384.38 4390.63 9894.01 45
test_part182.78 9482.08 9884.89 9690.66 10066.97 15890.96 5592.93 5777.19 5480.53 12290.04 12863.44 13095.39 7976.04 12576.90 25392.31 115
Regformer-385.23 6485.07 6685.70 7688.95 15069.01 11288.29 13389.91 16280.95 885.01 5390.01 12972.45 4894.19 12682.50 7187.57 13193.90 51
Regformer-485.68 5885.45 5886.35 6288.95 15069.67 10088.29 13391.29 12481.73 585.36 4990.01 12972.62 4795.35 8483.28 5887.57 13194.03 43
CS-MVS-test85.02 6985.21 6484.46 10889.28 13865.70 17991.16 5293.56 2677.83 3881.80 10589.89 13170.67 6495.61 6380.39 8792.34 8092.06 125
TranMVSNet+NR-MVSNet80.84 12680.31 12582.42 18587.85 18762.33 24287.74 15091.33 12380.55 1177.99 15789.86 13265.23 11692.62 19267.05 20575.24 28692.30 116
diffmvs82.10 10181.88 10382.76 18083.00 27863.78 21583.68 24989.76 16572.94 14882.02 10189.85 13365.96 11190.79 24882.38 7387.30 13893.71 61
BH-RMVSNet79.61 15578.44 16183.14 15889.38 13065.93 17384.95 22287.15 23573.56 13678.19 15289.79 13456.67 21293.36 16659.53 26386.74 14690.13 186
GeoE81.71 11081.01 11483.80 13789.51 12464.45 20388.97 10388.73 20471.27 17178.63 14289.76 13566.32 10493.20 17269.89 17886.02 15793.74 60
CS-MVS84.53 7384.97 6883.23 15487.54 20163.27 22888.82 11093.50 2875.98 8783.07 8989.73 13670.29 6895.23 8682.07 7493.70 6991.18 148
AdaColmapbinary80.58 13979.42 14184.06 12593.09 6168.91 11589.36 9188.97 19469.27 20875.70 20689.69 13757.20 20995.77 6063.06 23388.41 12687.50 265
ACMM73.20 880.78 13479.84 13283.58 14089.31 13668.37 13089.99 7891.60 11470.28 18977.25 17089.66 13853.37 23493.53 15974.24 13982.85 19188.85 235
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
CNLPA78.08 19476.79 20381.97 19490.40 10671.07 6987.59 15384.55 26566.03 25372.38 25389.64 13957.56 20386.04 30359.61 26283.35 18488.79 238
test_yl81.17 12080.47 12283.24 15289.13 14563.62 21686.21 19289.95 16072.43 15381.78 10789.61 14057.50 20493.58 15470.75 16786.90 14392.52 106
DCV-MVSNet81.17 12080.47 12283.24 15289.13 14563.62 21686.21 19289.95 16072.43 15381.78 10789.61 14057.50 20493.58 15470.75 16786.90 14392.52 106
EI-MVSNet-Vis-set84.19 7483.81 7685.31 8088.18 17767.85 14087.66 15189.73 16780.05 1682.95 9089.59 14270.74 6394.82 10680.66 8684.72 16793.28 81
PAPR81.66 11380.89 11683.99 13290.27 10764.00 21086.76 17891.77 11168.84 22377.13 17789.50 14367.63 9194.88 10467.55 19788.52 12493.09 88
jajsoiax79.29 16577.96 17283.27 15084.68 24666.57 16389.25 9490.16 15569.20 21275.46 21189.49 14445.75 30493.13 17876.84 11980.80 21390.11 188
MVSFormer82.85 9382.05 9985.24 8387.35 20270.21 8890.50 6490.38 14668.55 22781.32 11189.47 14561.68 16093.46 16378.98 9590.26 10392.05 126
jason81.39 11880.29 12684.70 10286.63 21969.90 9585.95 19886.77 24063.24 28281.07 11789.47 14561.08 17692.15 21078.33 10490.07 10892.05 126
jason: jason.
mvs_tets79.13 16977.77 18083.22 15584.70 24566.37 16589.17 9590.19 15469.38 20675.40 21489.46 14744.17 31293.15 17676.78 12080.70 21590.14 185
UGNet80.83 12879.59 13884.54 10588.04 18268.09 13689.42 9088.16 21176.95 6176.22 19489.46 14749.30 28093.94 13668.48 19090.31 10191.60 135
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
VPA-MVSNet80.60 13780.55 12080.76 22288.07 18160.80 26186.86 17291.58 11575.67 9380.24 12489.45 14963.34 13290.25 25570.51 17179.22 23491.23 147
MVS_Test83.15 8783.06 8383.41 14686.86 21363.21 23086.11 19592.00 9774.31 11982.87 9289.44 15070.03 7093.21 17077.39 11388.50 12593.81 57
EI-MVSNet-UG-set83.81 7683.38 7985.09 8787.87 18667.53 14687.44 15789.66 16979.74 1882.23 9989.41 15170.24 6994.74 10979.95 9183.92 17592.99 95
RPSCF73.23 26071.46 26178.54 25982.50 29059.85 27082.18 26982.84 29458.96 32071.15 26589.41 15145.48 30684.77 31358.82 27171.83 31491.02 156
RRT_MVS79.88 15278.38 16384.38 11185.42 23470.60 8488.71 11788.75 20372.30 15578.83 13889.14 15344.44 31092.18 20978.50 10079.33 23290.35 178
UniMVSNet_NR-MVSNet81.88 10681.54 10682.92 16988.46 17063.46 22387.13 16392.37 7980.19 1478.38 14789.14 15371.66 5693.05 18270.05 17576.46 26192.25 118
tttt051779.40 16277.91 17483.90 13688.10 18063.84 21388.37 13084.05 27371.45 16976.78 18189.12 15549.93 27494.89 10370.18 17483.18 18792.96 96
DU-MVS81.12 12280.52 12182.90 17087.80 18963.46 22387.02 16791.87 10579.01 2778.38 14789.07 15665.02 11893.05 18270.05 17576.46 26192.20 120
NR-MVSNet80.23 14579.38 14382.78 17887.80 18963.34 22686.31 18991.09 13279.01 2772.17 25589.07 15667.20 9692.81 19166.08 21275.65 27292.20 120
DELS-MVS85.41 6285.30 6285.77 7588.49 16867.93 13985.52 21493.44 3278.70 2983.63 8589.03 15874.57 2895.71 6280.26 9094.04 6593.66 62
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
baseline176.98 21776.75 20677.66 27188.13 17855.66 32185.12 21881.89 30173.04 14676.79 18088.90 15962.43 15087.78 29263.30 23171.18 31889.55 214
DP-MVS76.78 22074.57 23283.42 14493.29 5469.46 10788.55 12283.70 27763.98 27970.20 27288.89 16054.01 23094.80 10746.66 33581.88 20386.01 297
ab-mvs79.51 15778.97 15281.14 21488.46 17060.91 25983.84 24789.24 18170.36 18779.03 13388.87 16163.23 13690.21 25665.12 21982.57 19692.28 117
PEN-MVS77.73 20377.69 18477.84 26887.07 21253.91 33087.91 14791.18 12877.56 4473.14 24488.82 16261.23 17289.17 27259.95 25972.37 30990.43 175
test_djsdf80.30 14479.32 14583.27 15083.98 25765.37 18790.50 6490.38 14668.55 22776.19 19588.70 16356.44 21393.46 16378.98 9580.14 22390.97 157
PAPM77.68 20676.40 21281.51 20287.29 20861.85 24983.78 24889.59 17064.74 26771.23 26388.70 16362.59 14693.66 15352.66 30587.03 14289.01 227
DTE-MVSNet76.99 21676.80 20277.54 27586.24 22253.06 33787.52 15490.66 13977.08 5972.50 25088.67 16560.48 18589.52 26657.33 28570.74 32090.05 195
PS-CasMVS78.01 19878.09 17077.77 27087.71 19354.39 32788.02 14191.22 12677.50 4773.26 24288.64 16660.73 17988.41 28561.88 24473.88 29890.53 172
cdsmvs_eth3d_5k19.96 33526.61 3370.00 3550.00 3780.00 3790.00 36689.26 1800.00 3730.00 37488.61 16761.62 1620.00 3740.00 3720.00 3720.00 370
lupinMVS81.39 11880.27 12784.76 10187.35 20270.21 8885.55 21086.41 24462.85 28981.32 11188.61 16761.68 16092.24 20778.41 10390.26 10391.83 130
F-COLMAP76.38 22874.33 23782.50 18489.28 13866.95 16088.41 12689.03 18964.05 27766.83 30688.61 16746.78 29492.89 18757.48 28278.55 23587.67 259
mvs_anonymous79.42 16179.11 14980.34 22984.45 24957.97 28882.59 26587.62 22567.40 23776.17 19888.56 17068.47 8589.59 26570.65 17086.05 15693.47 75
CP-MVSNet78.22 18978.34 16577.84 26887.83 18854.54 32587.94 14591.17 12977.65 3973.48 24088.49 17162.24 15488.43 28462.19 24074.07 29490.55 171
PVSNet_Blended_VisFu82.62 9681.83 10484.96 9190.80 9969.76 9888.74 11591.70 11269.39 20578.96 13488.46 17265.47 11494.87 10574.42 13688.57 12290.24 182
CANet_DTU80.61 13679.87 13182.83 17285.60 23163.17 23387.36 15888.65 20576.37 7875.88 20388.44 17353.51 23393.07 18173.30 14989.74 11192.25 118
PLCcopyleft70.83 1178.05 19676.37 21383.08 16191.88 8567.80 14188.19 13789.46 17364.33 27369.87 28188.38 17453.66 23293.58 15458.86 27082.73 19387.86 256
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
WR-MVS79.49 15879.22 14880.27 23188.79 15858.35 28185.06 21988.61 20778.56 3077.65 16288.34 17563.81 12990.66 25164.98 22177.22 24991.80 133
XXY-MVS75.41 24075.56 21874.96 29883.59 26357.82 29280.59 28583.87 27666.54 24774.93 22988.31 17663.24 13580.09 33462.16 24176.85 25686.97 279
Effi-MVS+83.62 8083.08 8285.24 8388.38 17367.45 14788.89 10689.15 18575.50 9582.27 9888.28 17769.61 7594.45 11677.81 10887.84 12993.84 55
API-MVS81.99 10581.23 10984.26 11890.94 9570.18 9391.10 5389.32 17671.51 16878.66 14188.28 17765.26 11595.10 9464.74 22391.23 9387.51 264
thisisatest053079.40 16277.76 18184.31 11687.69 19565.10 19287.36 15884.26 27170.04 19277.42 16688.26 17949.94 27294.79 10870.20 17384.70 16893.03 91
hse-mvs281.72 10980.94 11584.07 12488.72 16167.68 14485.87 20187.26 23376.02 8584.67 6388.22 18061.54 16393.48 16182.71 6773.44 30391.06 152
xiu_mvs_v1_base_debu80.80 13179.72 13584.03 12987.35 20270.19 9085.56 20788.77 19969.06 21681.83 10288.16 18150.91 26092.85 18878.29 10587.56 13389.06 222
xiu_mvs_v1_base80.80 13179.72 13584.03 12987.35 20270.19 9085.56 20788.77 19969.06 21681.83 10288.16 18150.91 26092.85 18878.29 10587.56 13389.06 222
xiu_mvs_v1_base_debi80.80 13179.72 13584.03 12987.35 20270.19 9085.56 20788.77 19969.06 21681.83 10288.16 18150.91 26092.85 18878.29 10587.56 13389.06 222
UniMVSNet (Re)81.60 11481.11 11183.09 16088.38 17364.41 20487.60 15293.02 4678.42 3278.56 14388.16 18169.78 7393.26 16969.58 18276.49 26091.60 135
AUN-MVS79.21 16777.60 18684.05 12688.71 16267.61 14585.84 20387.26 23369.08 21577.23 17288.14 18553.20 23693.47 16275.50 13273.45 30291.06 152
Anonymous2023121178.97 17477.69 18482.81 17490.54 10364.29 20690.11 7691.51 11765.01 26576.16 19988.13 18650.56 26593.03 18569.68 18177.56 24691.11 151
pm-mvs177.25 21376.68 20878.93 25384.22 25258.62 28086.41 18688.36 21071.37 17073.31 24188.01 18761.22 17389.15 27364.24 22573.01 30689.03 226
LTVRE_ROB69.57 1376.25 22974.54 23481.41 20488.60 16564.38 20579.24 29789.12 18870.76 18169.79 28387.86 18849.09 28293.20 17256.21 29380.16 22186.65 286
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
WTY-MVS75.65 23675.68 21775.57 29286.40 22156.82 30477.92 31282.40 29765.10 26276.18 19687.72 18963.13 14180.90 33160.31 25781.96 20189.00 229
TAMVS78.89 17677.51 18883.03 16487.80 18967.79 14284.72 22685.05 26067.63 23376.75 18287.70 19062.25 15390.82 24758.53 27487.13 14090.49 173
BH-untuned79.47 15978.60 15782.05 19189.19 14365.91 17486.07 19688.52 20872.18 15675.42 21387.69 19161.15 17493.54 15860.38 25686.83 14586.70 285
COLMAP_ROBcopyleft66.92 1773.01 26270.41 27380.81 22187.13 21165.63 18088.30 13284.19 27262.96 28763.80 33087.69 19138.04 33992.56 19546.66 33574.91 28884.24 316
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
OurMVSNet-221017-074.26 24772.42 25479.80 23983.76 26159.59 27385.92 20086.64 24166.39 24866.96 30387.58 19339.46 33391.60 22565.76 21569.27 32488.22 249
Baseline_NR-MVSNet78.15 19378.33 16677.61 27385.79 22756.21 31686.78 17685.76 25373.60 13577.93 15887.57 19465.02 11888.99 27567.14 20475.33 28287.63 260
WR-MVS_H78.51 18378.49 15978.56 25888.02 18356.38 31388.43 12392.67 6777.14 5673.89 23887.55 19566.25 10589.24 27158.92 26973.55 30190.06 194
EI-MVSNet80.52 14079.98 12982.12 18884.28 25063.19 23286.41 18688.95 19574.18 12478.69 13987.54 19666.62 9992.43 19872.57 15780.57 21790.74 164
CVMVSNet72.99 26372.58 25274.25 30584.28 25050.85 34686.41 18683.45 28444.56 35373.23 24387.54 19649.38 27885.70 30565.90 21378.44 23886.19 292
ACMH+68.96 1476.01 23274.01 23982.03 19288.60 16565.31 18888.86 10787.55 22670.25 19067.75 29587.47 19841.27 32793.19 17458.37 27575.94 26987.60 261
RRT_test8_iter0578.38 18677.40 18981.34 20886.00 22558.86 27786.55 18491.26 12572.13 15975.91 20187.42 19944.97 30793.73 15177.02 11775.30 28391.45 143
TransMVSNet (Re)75.39 24174.56 23377.86 26785.50 23357.10 30186.78 17686.09 25172.17 15771.53 26187.34 20063.01 14289.31 27056.84 28961.83 34287.17 273
GBi-Net78.40 18477.40 18981.40 20587.60 19663.01 23488.39 12789.28 17771.63 16475.34 21687.28 20154.80 21991.11 23862.72 23479.57 22690.09 190
test178.40 18477.40 18981.40 20587.60 19663.01 23488.39 12789.28 17771.63 16475.34 21687.28 20154.80 21991.11 23862.72 23479.57 22690.09 190
FMVSNet278.20 19177.21 19381.20 21287.60 19662.89 23887.47 15689.02 19071.63 16475.29 22087.28 20154.80 21991.10 24162.38 23879.38 23089.61 212
FMVSNet177.44 20976.12 21581.40 20586.81 21663.01 23488.39 12789.28 17770.49 18674.39 23487.28 20149.06 28391.11 23860.91 25378.52 23690.09 190
v2v48280.23 14579.29 14683.05 16383.62 26264.14 20887.04 16689.97 15973.61 13478.18 15387.22 20561.10 17593.82 14376.11 12376.78 25891.18 148
ITE_SJBPF78.22 26381.77 30060.57 26383.30 28569.25 20967.54 29787.20 20636.33 34487.28 29654.34 29874.62 29186.80 282
anonymousdsp78.60 18177.15 19482.98 16780.51 31967.08 15487.24 16289.53 17165.66 25775.16 22287.19 20752.52 23792.25 20677.17 11579.34 23189.61 212
MVSTER79.01 17277.88 17682.38 18683.07 27564.80 19584.08 24688.95 19569.01 21978.69 13987.17 20854.70 22392.43 19874.69 13580.57 21789.89 203
thres100view90076.50 22375.55 21979.33 24789.52 12356.99 30285.83 20483.23 28773.94 12876.32 19287.12 20951.89 25191.95 21648.33 32683.75 17889.07 220
thres600view776.50 22375.44 22179.68 24189.40 12857.16 29985.53 21283.23 28773.79 13276.26 19387.09 21051.89 25191.89 21948.05 33183.72 18190.00 196
XVG-ACMP-BASELINE76.11 23174.27 23881.62 19983.20 27164.67 19783.60 25389.75 16669.75 20071.85 25887.09 21032.78 35192.11 21169.99 17780.43 21988.09 251
HY-MVS69.67 1277.95 19977.15 19480.36 22887.57 20060.21 26983.37 25787.78 22366.11 25075.37 21587.06 21263.27 13490.48 25361.38 25082.43 19790.40 177
CHOSEN 1792x268877.63 20775.69 21683.44 14389.98 11468.58 12878.70 30487.50 22856.38 33775.80 20586.84 21358.67 19491.40 23261.58 24885.75 16190.34 179
v879.97 15179.02 15182.80 17584.09 25464.50 20187.96 14390.29 15374.13 12675.24 22186.81 21462.88 14393.89 14274.39 13775.40 28090.00 196
AllTest70.96 27668.09 28879.58 24485.15 23863.62 21684.58 23279.83 32262.31 29560.32 34086.73 21532.02 35288.96 27850.28 31671.57 31686.15 293
TestCases79.58 24485.15 23863.62 21679.83 32262.31 29560.32 34086.73 21532.02 35288.96 27850.28 31671.57 31686.15 293
mvs-test180.88 12479.40 14285.29 8185.13 24069.75 9989.28 9288.10 21374.99 10576.44 19086.72 21757.27 20794.26 12473.53 14483.18 18791.87 129
LCM-MVSNet-Re77.05 21576.94 19977.36 27687.20 20951.60 34180.06 28980.46 31675.20 10267.69 29686.72 21762.48 14888.98 27663.44 22989.25 11591.51 138
1112_ss77.40 21176.43 21180.32 23089.11 14960.41 26783.65 25087.72 22462.13 29773.05 24586.72 21762.58 14789.97 25962.11 24380.80 21390.59 170
ab-mvs-re7.23 3389.64 3410.00 3550.00 3780.00 3790.00 3660.00 3790.00 3730.00 37486.72 2170.00 3780.00 3740.00 3720.00 3720.00 370
IterMVS-LS80.06 14879.38 14382.11 18985.89 22663.20 23186.79 17589.34 17574.19 12375.45 21286.72 21766.62 9992.39 20072.58 15676.86 25590.75 163
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
ACMH67.68 1675.89 23373.93 24081.77 19788.71 16266.61 16288.62 11989.01 19169.81 19766.78 30786.70 22241.95 32691.51 23055.64 29478.14 24187.17 273
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
Test_1112_low_res76.40 22775.44 22179.27 24889.28 13858.09 28481.69 27487.07 23659.53 31672.48 25186.67 22361.30 17089.33 26960.81 25580.15 22290.41 176
FMVSNet377.88 20176.85 20180.97 21886.84 21562.36 24186.52 18588.77 19971.13 17275.34 21686.66 22454.07 22991.10 24162.72 23479.57 22689.45 215
pmmvs674.69 24473.39 24578.61 25781.38 30757.48 29786.64 18087.95 21864.99 26670.18 27386.61 22550.43 26789.52 26662.12 24270.18 32288.83 236
ET-MVSNet_ETH3D78.63 18076.63 20984.64 10386.73 21869.47 10585.01 22084.61 26469.54 20366.51 31286.59 22650.16 26991.75 22276.26 12284.24 17392.69 103
testgi66.67 30566.53 30367.08 33575.62 34741.69 36275.93 31976.50 33866.11 25065.20 32286.59 22635.72 34674.71 35443.71 34573.38 30484.84 310
CLD-MVS82.31 9981.65 10584.29 11788.47 16967.73 14385.81 20592.35 8075.78 8978.33 14986.58 22864.01 12694.35 11776.05 12487.48 13690.79 161
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
v1079.74 15478.67 15582.97 16884.06 25564.95 19387.88 14890.62 14073.11 14475.11 22486.56 22961.46 16694.05 13273.68 14275.55 27489.90 202
CDS-MVSNet79.07 17177.70 18383.17 15787.60 19668.23 13484.40 23986.20 24867.49 23676.36 19186.54 23061.54 16390.79 24861.86 24587.33 13790.49 173
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
xiu_mvs_v2_base81.69 11181.05 11283.60 13989.15 14468.03 13884.46 23590.02 15870.67 18281.30 11486.53 23163.17 13794.19 12675.60 13088.54 12388.57 244
TR-MVS77.44 20976.18 21481.20 21288.24 17663.24 22984.61 23186.40 24567.55 23577.81 15986.48 23254.10 22893.15 17657.75 28182.72 19487.20 272
EIA-MVS83.31 8682.80 8884.82 9889.59 12065.59 18188.21 13692.68 6674.66 11278.96 13486.42 23369.06 8195.26 8575.54 13190.09 10693.62 69
tfpn200view976.42 22675.37 22579.55 24689.13 14557.65 29485.17 21583.60 27873.41 14176.45 18786.39 23452.12 24491.95 21648.33 32683.75 17889.07 220
thres40076.50 22375.37 22579.86 23789.13 14557.65 29485.17 21583.60 27873.41 14176.45 18786.39 23452.12 24491.95 21648.33 32683.75 17890.00 196
v7n78.97 17477.58 18783.14 15883.45 26565.51 18288.32 13191.21 12773.69 13372.41 25286.32 23657.93 19893.81 14469.18 18575.65 27290.11 188
MAR-MVS81.84 10780.70 11785.27 8291.32 9071.53 6089.82 8190.92 13469.77 19978.50 14486.21 23762.36 15194.52 11465.36 21792.05 8189.77 208
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
v114480.03 14979.03 15083.01 16583.78 26064.51 19987.11 16590.57 14271.96 16078.08 15686.20 23861.41 16793.94 13674.93 13477.23 24890.60 169
V4279.38 16478.24 16882.83 17281.10 31365.50 18385.55 21089.82 16371.57 16778.21 15186.12 23960.66 18293.18 17575.64 12875.46 27889.81 207
PVSNet_BlendedMVS80.60 13780.02 12882.36 18788.85 15265.40 18486.16 19492.00 9769.34 20778.11 15486.09 24066.02 10994.27 12071.52 16182.06 20087.39 266
v119279.59 15678.43 16283.07 16283.55 26464.52 19886.93 17090.58 14170.83 17777.78 16085.90 24159.15 19293.94 13673.96 14177.19 25090.76 162
SixPastTwentyTwo73.37 25671.26 26679.70 24085.08 24257.89 29085.57 20683.56 28071.03 17565.66 31685.88 24242.10 32492.57 19459.11 26763.34 34188.65 242
EPNet_dtu75.46 23874.86 22977.23 28082.57 28954.60 32486.89 17183.09 29171.64 16366.25 31485.86 24355.99 21488.04 28954.92 29686.55 14989.05 225
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
sss73.60 25473.64 24473.51 30982.80 28355.01 32376.12 31881.69 30462.47 29474.68 23285.85 24457.32 20678.11 34160.86 25480.93 21087.39 266
ETV-MVS84.90 7284.67 7385.59 7789.39 12968.66 12688.74 11592.64 7179.97 1784.10 7685.71 24569.32 7895.38 8080.82 8391.37 9092.72 100
v124078.99 17377.78 17982.64 18183.21 27063.54 22086.62 18190.30 15269.74 20277.33 16885.68 24657.04 21093.76 14873.13 15276.92 25290.62 167
v14419279.47 15978.37 16482.78 17883.35 26663.96 21186.96 16890.36 14969.99 19377.50 16485.67 24760.66 18293.77 14774.27 13876.58 25990.62 167
tfpnnormal74.39 24573.16 24878.08 26586.10 22458.05 28584.65 23087.53 22770.32 18871.22 26485.63 24854.97 21889.86 26043.03 34775.02 28786.32 289
PS-MVSNAJ81.69 11181.02 11383.70 13889.51 12468.21 13584.28 24190.09 15770.79 17981.26 11585.62 24963.15 13894.29 11875.62 12988.87 11888.59 243
v192192079.22 16678.03 17182.80 17583.30 26863.94 21286.80 17490.33 15069.91 19677.48 16585.53 25058.44 19693.75 14973.60 14376.85 25690.71 165
test_040272.79 26570.44 27279.84 23888.13 17865.99 17185.93 19984.29 26965.57 25867.40 30085.49 25146.92 29392.61 19335.88 35674.38 29380.94 340
v14878.72 17877.80 17881.47 20382.73 28561.96 24886.30 19088.08 21573.26 14376.18 19685.47 25262.46 14992.36 20271.92 16073.82 29990.09 190
USDC70.33 28268.37 28376.21 28780.60 31756.23 31579.19 29986.49 24360.89 30461.29 33785.47 25231.78 35489.47 26853.37 30276.21 26782.94 331
MVP-Stereo76.12 23074.46 23681.13 21585.37 23569.79 9784.42 23887.95 21865.03 26467.46 29885.33 25453.28 23591.73 22458.01 27983.27 18581.85 335
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
MVS78.19 19276.99 19881.78 19685.66 22966.99 15584.66 22790.47 14455.08 34272.02 25785.27 25563.83 12894.11 13166.10 21189.80 11084.24 316
cl-mvsnet177.72 20476.76 20480.58 22482.48 29260.48 26583.09 26087.86 22169.22 21074.38 23585.24 25662.10 15691.53 22871.09 16575.40 28089.74 209
cl-mvsnet____77.72 20476.76 20480.58 22482.49 29160.48 26583.09 26087.87 22069.22 21074.38 23585.22 25762.10 15691.53 22871.09 16575.41 27989.73 210
HyFIR lowres test77.53 20875.40 22383.94 13589.59 12066.62 16180.36 28688.64 20656.29 33876.45 18785.17 25857.64 20293.28 16861.34 25183.10 18991.91 128
pmmvs474.03 25171.91 25780.39 22781.96 29868.32 13181.45 27782.14 29959.32 31769.87 28185.13 25952.40 24088.13 28860.21 25874.74 29084.73 312
TDRefinement67.49 29964.34 30876.92 28273.47 35661.07 25784.86 22482.98 29259.77 31358.30 34685.13 25926.06 35787.89 29047.92 33260.59 34681.81 336
Fast-Effi-MVS+80.81 12979.92 13083.47 14288.85 15264.51 19985.53 21289.39 17470.79 17978.49 14585.06 26167.54 9293.58 15467.03 20686.58 14892.32 114
PVSNet_Blended80.98 12380.34 12482.90 17088.85 15265.40 18484.43 23792.00 9767.62 23478.11 15485.05 26266.02 10994.27 12071.52 16189.50 11289.01 227
CMPMVSbinary51.72 2170.19 28468.16 28676.28 28673.15 35857.55 29679.47 29583.92 27448.02 35256.48 35184.81 26343.13 31686.42 30162.67 23781.81 20484.89 309
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
EU-MVSNet68.53 29667.61 29671.31 32278.51 33747.01 35584.47 23384.27 27042.27 35466.44 31384.79 26440.44 33183.76 31858.76 27268.54 32983.17 325
BH-w/o78.21 19077.33 19280.84 22088.81 15665.13 19184.87 22387.85 22269.75 20074.52 23384.74 26561.34 16993.11 17958.24 27785.84 16084.27 315
pmmvs571.55 27270.20 27575.61 29177.83 33856.39 31281.74 27380.89 30857.76 32867.46 29884.49 26649.26 28185.32 30957.08 28775.29 28485.11 308
thres20075.55 23774.47 23578.82 25487.78 19257.85 29183.07 26283.51 28172.44 15275.84 20484.42 26752.08 24691.75 22247.41 33383.64 18286.86 281
eth_miper_zixun_eth77.92 20076.69 20781.61 20183.00 27861.98 24783.15 25989.20 18369.52 20474.86 23084.35 26861.76 15992.56 19571.50 16372.89 30790.28 181
cl_fuxian78.75 17777.91 17481.26 21082.89 28261.56 25384.09 24589.13 18769.97 19475.56 20784.29 26966.36 10392.09 21273.47 14775.48 27690.12 187
Fast-Effi-MVS+-dtu78.02 19776.49 21082.62 18283.16 27466.96 15986.94 16987.45 23072.45 15071.49 26284.17 27054.79 22291.58 22667.61 19680.31 22089.30 218
IterMVS-SCA-FT75.43 23973.87 24280.11 23382.69 28664.85 19481.57 27683.47 28369.16 21370.49 26984.15 27151.95 24988.15 28769.23 18472.14 31287.34 268
131476.53 22275.30 22780.21 23283.93 25862.32 24384.66 22788.81 19760.23 30970.16 27584.07 27255.30 21790.73 25067.37 19983.21 18687.59 263
cl-mvsnet278.07 19577.01 19681.23 21182.37 29461.83 25083.55 25487.98 21768.96 22075.06 22683.87 27361.40 16891.88 22073.53 14476.39 26389.98 199
EG-PatchMatch MVS74.04 25071.82 25980.71 22384.92 24367.42 14885.86 20288.08 21566.04 25264.22 32683.85 27435.10 34792.56 19557.44 28380.83 21282.16 334
thisisatest051577.33 21275.38 22483.18 15685.27 23663.80 21482.11 27083.27 28665.06 26375.91 20183.84 27549.54 27694.27 12067.24 20286.19 15491.48 141
test20.0367.45 30066.95 30168.94 32975.48 34844.84 35877.50 31377.67 33266.66 24363.01 33283.80 27647.02 29278.40 33942.53 34968.86 32883.58 322
miper_ehance_all_eth78.59 18277.76 18181.08 21682.66 28761.56 25383.65 25089.15 18568.87 22275.55 20883.79 27766.49 10192.03 21373.25 15076.39 26389.64 211
MSDG73.36 25870.99 26780.49 22684.51 24865.80 17680.71 28386.13 25065.70 25665.46 31783.74 27844.60 30890.91 24651.13 31176.89 25484.74 311
IterMVS74.29 24672.94 25078.35 26281.53 30463.49 22281.58 27582.49 29668.06 23269.99 27883.69 27951.66 25585.54 30665.85 21471.64 31586.01 297
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
tpm72.37 26971.71 26074.35 30482.19 29652.00 33879.22 29877.29 33564.56 26972.95 24683.68 28051.35 25683.26 32358.33 27675.80 27087.81 257
Effi-MVS+-dtu80.03 14978.57 15884.42 11085.13 24068.74 12088.77 11288.10 21374.99 10574.97 22883.49 28157.27 20793.36 16673.53 14480.88 21191.18 148
baseline275.70 23573.83 24381.30 20983.26 26961.79 25182.57 26680.65 31266.81 23966.88 30483.42 28257.86 20092.19 20863.47 22879.57 22689.91 201
bset_n11_16_dypcd77.12 21475.47 22082.06 19081.12 31265.99 17181.37 27983.20 28969.94 19576.09 20083.38 28347.75 28892.26 20578.51 9977.91 24287.95 252
TinyColmap67.30 30264.81 30674.76 30181.92 29956.68 30880.29 28881.49 30660.33 30756.27 35283.22 28424.77 35887.66 29345.52 34169.47 32379.95 344
CostFormer75.24 24273.90 24179.27 24882.65 28858.27 28380.80 28082.73 29561.57 30075.33 21983.13 28555.52 21591.07 24464.98 22178.34 24088.45 246
miper_lstm_enhance74.11 24973.11 24977.13 28180.11 32259.62 27272.23 33486.92 23966.76 24170.40 27082.92 28656.93 21182.92 32469.06 18772.63 30888.87 234
GA-MVS76.87 21975.17 22881.97 19482.75 28462.58 23981.44 27886.35 24772.16 15874.74 23182.89 28746.20 29992.02 21468.85 18981.09 20991.30 146
K. test v371.19 27468.51 28279.21 25083.04 27757.78 29384.35 24076.91 33772.90 14962.99 33382.86 28839.27 33491.09 24361.65 24752.66 35488.75 239
MS-PatchMatch73.83 25272.67 25177.30 27883.87 25966.02 17081.82 27184.66 26361.37 30368.61 29182.82 28947.29 29088.21 28659.27 26484.32 17277.68 349
lessismore_v078.97 25281.01 31457.15 30065.99 36061.16 33882.82 28939.12 33591.34 23459.67 26146.92 35988.43 247
D2MVS74.82 24373.21 24779.64 24379.81 32662.56 24080.34 28787.35 23164.37 27268.86 28882.66 29146.37 29690.10 25867.91 19481.24 20886.25 290
Anonymous2023120668.60 29467.80 29371.02 32380.23 32150.75 34778.30 30880.47 31556.79 33566.11 31582.63 29246.35 29778.95 33743.62 34675.70 27183.36 324
MIMVSNet70.69 27869.30 27774.88 29984.52 24756.35 31475.87 32279.42 32564.59 26867.76 29482.41 29341.10 32881.54 32946.64 33781.34 20686.75 284
OpenMVS_ROBcopyleft64.09 1970.56 28068.19 28577.65 27280.26 32059.41 27585.01 22082.96 29358.76 32265.43 31882.33 29437.63 34191.23 23745.34 34376.03 26882.32 332
miper_enhance_ethall77.87 20276.86 20080.92 21981.65 30161.38 25582.68 26488.98 19265.52 25975.47 20982.30 29565.76 11392.00 21572.95 15376.39 26389.39 216
test0.0.03 168.00 29867.69 29568.90 33077.55 33947.43 35375.70 32372.95 34966.66 24366.56 30882.29 29648.06 28675.87 35044.97 34474.51 29283.41 323
PVSNet64.34 1872.08 27170.87 27075.69 29086.21 22356.44 31174.37 33080.73 31162.06 29870.17 27482.23 29742.86 31883.31 32254.77 29784.45 17187.32 269
MIMVSNet168.58 29566.78 30273.98 30780.07 32351.82 33980.77 28184.37 26664.40 27159.75 34382.16 29836.47 34383.63 32042.73 34870.33 32186.48 288
CL-MVSNet_2432*160072.37 26971.46 26175.09 29779.49 33253.53 33280.76 28285.01 26169.12 21470.51 26882.05 29957.92 19984.13 31652.27 30666.00 33587.60 261
tpm273.26 25971.46 26178.63 25683.34 26756.71 30780.65 28480.40 31756.63 33673.55 23982.02 30051.80 25391.24 23656.35 29278.42 23987.95 252
PatchMatch-RL72.38 26870.90 26876.80 28488.60 16567.38 15079.53 29476.17 33962.75 29169.36 28682.00 30145.51 30584.89 31253.62 30180.58 21678.12 348
FMVSNet569.50 28867.96 28974.15 30682.97 28055.35 32280.01 29082.12 30062.56 29363.02 33181.53 30236.92 34281.92 32748.42 32574.06 29585.17 307
CR-MVSNet73.37 25671.27 26579.67 24281.32 31065.19 18975.92 32080.30 31859.92 31272.73 24881.19 30352.50 23886.69 29859.84 26077.71 24387.11 277
Patchmtry70.74 27769.16 27975.49 29480.72 31554.07 32974.94 32980.30 31858.34 32470.01 27681.19 30352.50 23886.54 29953.37 30271.09 31985.87 300
IB-MVS68.01 1575.85 23473.36 24683.31 14884.76 24466.03 16983.38 25685.06 25970.21 19169.40 28581.05 30545.76 30394.66 11165.10 22075.49 27589.25 219
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
cascas76.72 22174.64 23182.99 16685.78 22865.88 17582.33 26889.21 18260.85 30572.74 24781.02 30647.28 29193.75 14967.48 19885.02 16389.34 217
LF4IMVS64.02 31662.19 31969.50 32870.90 36053.29 33676.13 31777.18 33652.65 34758.59 34480.98 30723.55 35976.52 34753.06 30466.66 33278.68 347
Anonymous2024052168.80 29367.22 29973.55 30874.33 35154.11 32883.18 25885.61 25458.15 32561.68 33680.94 30830.71 35581.27 33057.00 28873.34 30585.28 304
gm-plane-assit81.40 30653.83 33162.72 29280.94 30892.39 20063.40 230
UnsupCasMVSNet_eth67.33 30165.99 30471.37 31973.48 35551.47 34375.16 32585.19 25865.20 26160.78 33980.93 31042.35 32077.20 34557.12 28653.69 35385.44 302
MVS_030472.48 26670.89 26977.24 27982.20 29559.68 27184.11 24483.49 28267.10 23866.87 30580.59 31135.00 34887.40 29459.07 26879.58 22584.63 313
MDTV_nov1_ep1369.97 27683.18 27253.48 33377.10 31680.18 32160.45 30669.33 28780.44 31248.89 28486.90 29751.60 30978.51 237
pmmvs-eth3d70.50 28167.83 29278.52 26077.37 34166.18 16881.82 27181.51 30558.90 32163.90 32980.42 31342.69 31986.28 30258.56 27365.30 33783.11 327
PM-MVS66.41 30764.14 30973.20 31273.92 35356.45 31078.97 30164.96 36363.88 28164.72 32380.24 31419.84 36283.44 32166.24 20864.52 33979.71 345
SCA74.22 24872.33 25579.91 23684.05 25662.17 24579.96 29179.29 32666.30 24972.38 25380.13 31551.95 24988.60 28259.25 26577.67 24588.96 231
Patchmatch-test64.82 31463.24 31469.57 32779.42 33349.82 35063.49 35569.05 35751.98 34959.95 34280.13 31550.91 26070.98 35940.66 35273.57 30087.90 255
tpmrst72.39 26772.13 25673.18 31380.54 31849.91 34979.91 29279.08 32763.11 28471.69 26079.95 31755.32 21682.77 32565.66 21673.89 29786.87 280
DSMNet-mixed57.77 32256.90 32460.38 33967.70 36235.61 36569.18 34453.97 36732.30 36357.49 34879.88 31840.39 33268.57 36138.78 35472.37 30976.97 350
MDA-MVSNet-bldmvs66.68 30463.66 31275.75 28979.28 33460.56 26473.92 33178.35 32964.43 27050.13 35779.87 31944.02 31383.67 31946.10 33956.86 34983.03 329
PatchmatchNetpermissive73.12 26171.33 26478.49 26183.18 27260.85 26079.63 29378.57 32864.13 27471.73 25979.81 32051.20 25885.97 30457.40 28476.36 26688.66 241
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
ppachtmachnet_test70.04 28567.34 29878.14 26479.80 32761.13 25679.19 29980.59 31359.16 31965.27 31979.29 32146.75 29587.29 29549.33 32266.72 33186.00 299
EPMVS69.02 29168.16 28671.59 31779.61 33049.80 35177.40 31466.93 35962.82 29070.01 27679.05 32245.79 30277.86 34356.58 29075.26 28587.13 276
PMMVS69.34 28968.67 28171.35 32175.67 34662.03 24675.17 32473.46 34750.00 35168.68 28979.05 32252.07 24778.13 34061.16 25282.77 19273.90 352
test-LLR72.94 26472.43 25374.48 30281.35 30858.04 28678.38 30577.46 33366.66 24369.95 27979.00 32448.06 28679.24 33566.13 20984.83 16586.15 293
test-mter71.41 27370.39 27474.48 30281.35 30858.04 28678.38 30577.46 33360.32 30869.95 27979.00 32436.08 34579.24 33566.13 20984.83 16586.15 293
DIV-MVS_2432*160068.81 29267.59 29772.46 31574.29 35245.45 35677.93 31187.00 23763.12 28363.99 32878.99 32642.32 32184.77 31356.55 29164.09 34087.16 275
KD-MVS_2432*160066.22 30963.89 31073.21 31075.47 34953.42 33470.76 33984.35 26764.10 27566.52 31078.52 32734.55 34984.98 31050.40 31450.33 35781.23 338
miper_refine_blended66.22 30963.89 31073.21 31075.47 34953.42 33470.76 33984.35 26764.10 27566.52 31078.52 32734.55 34984.98 31050.40 31450.33 35781.23 338
DWT-MVSNet_test73.70 25371.86 25879.21 25082.91 28158.94 27682.34 26782.17 29865.21 26071.05 26678.31 32944.21 31190.17 25763.29 23277.28 24788.53 245
tpmvs71.09 27569.29 27876.49 28582.04 29756.04 31778.92 30281.37 30764.05 27767.18 30278.28 33049.74 27589.77 26149.67 32172.37 30983.67 321
our_test_369.14 29067.00 30075.57 29279.80 32758.80 27877.96 31077.81 33159.55 31562.90 33478.25 33147.43 28983.97 31751.71 30867.58 33083.93 320
MDA-MVSNet_test_wron65.03 31262.92 31571.37 31975.93 34456.73 30569.09 34774.73 34457.28 33354.03 35477.89 33245.88 30074.39 35649.89 32061.55 34382.99 330
YYNet165.03 31262.91 31671.38 31875.85 34556.60 30969.12 34674.66 34657.28 33354.12 35377.87 33345.85 30174.48 35549.95 31961.52 34483.05 328
ambc75.24 29673.16 35750.51 34863.05 35687.47 22964.28 32577.81 33417.80 36389.73 26357.88 28060.64 34585.49 301
tpm cat170.57 27968.31 28477.35 27782.41 29357.95 28978.08 30980.22 32052.04 34868.54 29277.66 33552.00 24887.84 29151.77 30772.07 31386.25 290
dp66.80 30365.43 30570.90 32479.74 32948.82 35275.12 32774.77 34359.61 31464.08 32777.23 33642.89 31780.72 33248.86 32466.58 33383.16 326
TESTMET0.1,169.89 28769.00 28072.55 31479.27 33556.85 30378.38 30574.71 34557.64 32968.09 29377.19 33737.75 34076.70 34663.92 22684.09 17484.10 319
CHOSEN 280x42066.51 30664.71 30771.90 31681.45 30563.52 22157.98 35768.95 35853.57 34462.59 33576.70 33846.22 29875.29 35355.25 29579.68 22476.88 351
PatchT68.46 29767.85 29170.29 32580.70 31643.93 35972.47 33374.88 34260.15 31070.55 26776.57 33949.94 27281.59 32850.58 31274.83 28985.34 303
RPMNet73.51 25570.49 27182.58 18381.32 31065.19 18975.92 32092.27 8357.60 33072.73 24876.45 34052.30 24195.43 7548.14 33077.71 24387.11 277
ADS-MVSNet266.20 31163.33 31374.82 30079.92 32458.75 27967.55 34975.19 34153.37 34565.25 32075.86 34142.32 32180.53 33341.57 35068.91 32685.18 305
ADS-MVSNet64.36 31562.88 31768.78 33279.92 32447.17 35467.55 34971.18 35053.37 34565.25 32075.86 34142.32 32173.99 35741.57 35068.91 32685.18 305
new-patchmatchnet61.73 31861.73 32061.70 33872.74 35924.50 37269.16 34578.03 33061.40 30156.72 35075.53 34338.42 33776.48 34845.95 34057.67 34884.13 318
N_pmnet52.79 32553.26 32651.40 34478.99 3367.68 37569.52 3423.89 37551.63 35057.01 34974.98 34440.83 33065.96 36237.78 35564.67 33880.56 343
patchmatchnet-post74.00 34551.12 25988.60 282
GG-mvs-BLEND75.38 29581.59 30355.80 31979.32 29669.63 35467.19 30173.67 34643.24 31588.90 28050.41 31384.50 16981.45 337
Patchmatch-RL test70.24 28367.78 29477.61 27377.43 34059.57 27471.16 33670.33 35162.94 28868.65 29072.77 34750.62 26485.49 30769.58 18266.58 33387.77 258
FPMVS53.68 32451.64 32759.81 34065.08 36351.03 34569.48 34369.58 35541.46 35540.67 35972.32 34816.46 36570.00 36024.24 36265.42 33658.40 359
UnsupCasMVSNet_bld63.70 31761.53 32170.21 32673.69 35451.39 34472.82 33281.89 30155.63 34057.81 34771.80 34938.67 33678.61 33849.26 32352.21 35580.63 341
PVSNet_057.27 2061.67 31959.27 32268.85 33179.61 33057.44 29868.01 34873.44 34855.93 33958.54 34570.41 35044.58 30977.55 34447.01 33435.91 36071.55 354
pmmvs357.79 32154.26 32568.37 33364.02 36456.72 30675.12 32765.17 36140.20 35652.93 35569.86 35120.36 36175.48 35245.45 34255.25 35272.90 353
new_pmnet50.91 32650.29 32852.78 34368.58 36134.94 36763.71 35456.63 36639.73 35744.95 35865.47 35221.93 36058.48 36334.98 35756.62 35064.92 356
gg-mvs-nofinetune69.95 28667.96 28975.94 28883.07 27554.51 32677.23 31570.29 35263.11 28470.32 27162.33 35343.62 31488.69 28153.88 30087.76 13084.62 314
JIA-IIPM66.32 30862.82 31876.82 28377.09 34261.72 25265.34 35275.38 34058.04 32764.51 32462.32 35442.05 32586.51 30051.45 31069.22 32582.21 333
LCM-MVSNet54.25 32349.68 32967.97 33453.73 36745.28 35766.85 35180.78 31035.96 36039.45 36062.23 3558.70 37178.06 34248.24 32951.20 35680.57 342
PMMVS240.82 33038.86 33346.69 34553.84 36616.45 37348.61 36049.92 36837.49 35931.67 36160.97 3568.14 37256.42 36428.42 35930.72 36267.19 355
MVS-HIRNet59.14 32057.67 32363.57 33781.65 30143.50 36071.73 33565.06 36239.59 35851.43 35657.73 35738.34 33882.58 32639.53 35373.95 29664.62 357
ANet_high50.57 32746.10 33063.99 33648.67 37039.13 36370.99 33880.85 30961.39 30231.18 36257.70 35817.02 36473.65 35831.22 35815.89 36779.18 346
PMVScopyleft37.38 2244.16 32940.28 33255.82 34140.82 37242.54 36165.12 35363.99 36434.43 36124.48 36457.12 3593.92 37376.17 34917.10 36555.52 35148.75 360
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
test_method31.52 33229.28 33638.23 34727.03 3746.50 37620.94 36562.21 3654.05 36922.35 36752.50 36013.33 36647.58 36727.04 36134.04 36160.62 358
DeepMVS_CXcopyleft27.40 35040.17 37326.90 37024.59 37417.44 36723.95 36548.61 3619.77 36926.48 36918.06 36424.47 36328.83 363
MVEpermissive26.22 2330.37 33425.89 33843.81 34644.55 37135.46 36628.87 36439.07 37118.20 36618.58 36840.18 3622.68 37447.37 36817.07 36623.78 36448.60 361
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
Gipumacopyleft45.18 32841.86 33155.16 34277.03 34351.52 34232.50 36380.52 31432.46 36227.12 36335.02 3639.52 37075.50 35122.31 36360.21 34738.45 362
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
E-PMN31.77 33130.64 33435.15 34852.87 36827.67 36957.09 35847.86 36924.64 36416.40 36933.05 36411.23 36854.90 36514.46 36718.15 36522.87 364
EMVS30.81 33329.65 33534.27 34950.96 36925.95 37156.58 35946.80 37024.01 36515.53 37030.68 36512.47 36754.43 36612.81 36817.05 36622.43 365
tmp_tt18.61 33621.40 33910.23 3524.82 37510.11 37434.70 36230.74 3731.48 37023.91 36626.07 36628.42 35613.41 37127.12 36015.35 3687.17 366
X-MVStestdata80.37 14377.83 17788.00 1594.42 2273.33 2092.78 1792.99 4979.14 2283.67 8312.47 36767.45 9396.60 3483.06 6094.50 5694.07 41
test_post5.46 36850.36 26884.24 315
test_post178.90 3035.43 36948.81 28585.44 30859.25 265
wuyk23d16.82 33715.94 34019.46 35158.74 36531.45 36839.22 3613.74 3766.84 3686.04 3712.70 3701.27 37524.29 37010.54 36914.40 3692.63 367
testmvs6.04 3408.02 3430.10 3540.08 3760.03 37869.74 3410.04 3770.05 3710.31 3721.68 3710.02 3770.04 3720.24 3700.02 3700.25 369
test1236.12 3398.11 3420.14 3530.06 3770.09 37771.05 3370.03 3780.04 3720.25 3731.30 3720.05 3760.03 3730.21 3710.01 3710.29 368
uanet_test0.00 3420.00 3450.00 3550.00 3780.00 3790.00 3660.00 3790.00 3730.00 3740.00 3730.00 3780.00 3740.00 3720.00 3720.00 370
pcd_1.5k_mvsjas5.26 3417.02 3440.00 3550.00 3780.00 3790.00 3660.00 3790.00 3730.00 3740.00 37363.15 1380.00 3740.00 3720.00 3720.00 370
sosnet-low-res0.00 3420.00 3450.00 3550.00 3780.00 3790.00 3660.00 3790.00 3730.00 3740.00 3730.00 3780.00 3740.00 3720.00 3720.00 370
sosnet0.00 3420.00 3450.00 3550.00 3780.00 3790.00 3660.00 3790.00 3730.00 3740.00 3730.00 3780.00 3740.00 3720.00 3720.00 370
uncertanet0.00 3420.00 3450.00 3550.00 3780.00 3790.00 3660.00 3790.00 3730.00 3740.00 3730.00 3780.00 3740.00 3720.00 3720.00 370
Regformer0.00 3420.00 3450.00 3550.00 3780.00 3790.00 3660.00 3790.00 3730.00 3740.00 3730.00 3780.00 3740.00 3720.00 3720.00 370
uanet0.00 3420.00 3450.00 3550.00 3780.00 3790.00 3660.00 3790.00 3730.00 3740.00 3730.00 3780.00 3740.00 3720.00 3720.00 370
FOURS195.00 1072.39 4295.06 193.84 1874.49 11591.30 15
MSC_two_6792asdad89.16 194.34 2975.53 292.99 4997.53 189.67 196.44 994.41 26
No_MVS89.16 194.34 2975.53 292.99 4997.53 189.67 196.44 994.41 26
eth-test20.00 378
eth-test0.00 378
IU-MVS95.30 271.25 6392.95 5666.81 23992.39 688.94 1196.63 494.85 12
save fliter93.80 4472.35 4590.47 6691.17 12974.31 119
test_0728_SECOND87.71 3495.34 171.43 6293.49 994.23 597.49 389.08 796.41 1294.21 36
GSMVS88.96 231
test_part295.06 872.65 3391.80 13
sam_mvs151.32 25788.96 231
sam_mvs50.01 270
MTGPAbinary92.02 94
MTMP92.18 3332.83 372
test9_res84.90 3395.70 3192.87 98
agg_prior282.91 6395.45 3392.70 101
agg_prior92.85 6671.94 5491.78 10984.41 6994.93 98
test_prior472.60 3589.01 102
test_prior86.33 6392.61 7469.59 10192.97 5495.48 7193.91 49
旧先验286.56 18358.10 32687.04 3588.98 27674.07 140
新几何286.29 191
无先验87.48 15588.98 19260.00 31194.12 12967.28 20088.97 230
原ACMM286.86 172
testdata291.01 24562.37 239
segment_acmp73.08 43
testdata184.14 24375.71 90
test1286.80 5592.63 7370.70 8191.79 10882.71 9671.67 5596.16 4794.50 5693.54 73
plane_prior790.08 11268.51 129
plane_prior689.84 11768.70 12460.42 186
plane_prior592.44 7595.38 8078.71 9786.32 15291.33 144
plane_prior368.60 12778.44 3178.92 136
plane_prior291.25 4979.12 24
plane_prior189.90 116
plane_prior68.71 12290.38 7077.62 4086.16 155
n20.00 379
nn0.00 379
door-mid69.98 353
test1192.23 86
door69.44 356
HQP5-MVS66.98 156
HQP-NCC89.33 13189.17 9576.41 7477.23 172
ACMP_Plane89.33 13189.17 9576.41 7477.23 172
BP-MVS77.47 111
HQP4-MVS77.24 17195.11 9191.03 154
HQP3-MVS92.19 8985.99 158
HQP2-MVS60.17 189
MDTV_nov1_ep13_2view37.79 36475.16 32555.10 34166.53 30949.34 27953.98 29987.94 254
ACMMP++_ref81.95 202
ACMMP++81.25 207
Test By Simon64.33 123