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

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

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

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

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




Method Infoallhigh-res
multi-view
indooroutdoorbotani.boulde.bridgedoorexhibi.lectur.living.loungeobserv.old co.statueterrac.
sort bysort bysort bysort bysort bysort bysorted bysort bysort bysort bysort bysort bysort bysort bysort bysort by
CP-MVS87.11 586.92 687.68 694.20 473.86 193.98 192.82 1376.62 1283.68 894.46 367.93 1395.95 1284.20 794.39 993.23 16
SteuartSystems-ACMMP88.72 188.86 188.32 292.14 1772.96 493.73 293.67 480.19 488.10 394.80 173.76 497.11 187.51 195.82 294.90 3
Skip Steuart: Steuart Systems R&D Blog.
3Dnovator+77.84 485.48 1284.47 1588.51 191.08 2273.49 393.18 393.78 380.79 376.66 4893.37 1060.40 5296.75 577.20 2593.73 1395.29 1
ACMMPcopyleft85.89 1185.39 1187.38 893.59 872.63 792.74 493.18 976.78 1180.73 1993.82 864.33 2596.29 982.67 990.69 2593.23 16
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
EPP-MVSNet83.40 2083.02 1884.57 3090.13 3064.47 7092.32 590.73 3574.45 2679.35 2491.10 2769.05 1295.12 1972.78 3687.22 4294.13 8
PHI-MVS86.43 986.17 1087.24 990.88 2470.96 1692.27 694.07 172.45 3585.22 591.90 1969.47 1196.42 883.28 895.94 194.35 5
HPM-MVS87.11 586.98 587.50 793.88 672.16 1292.19 793.33 876.07 1883.81 793.95 769.77 1096.01 1185.15 394.66 894.32 6
HPM-MVS_fast85.35 1484.95 1386.57 1493.69 770.58 1992.15 891.62 2673.89 3082.67 1294.09 662.60 3395.54 1680.93 1192.93 1493.57 12
CPTT-MVS83.73 1683.33 1784.92 2593.28 1170.86 1892.09 990.38 3868.75 6479.57 2292.83 1360.60 5193.04 5880.92 1291.56 2190.86 39
APD-MVS87.44 487.52 487.19 1094.24 372.39 991.86 1092.83 1173.01 3388.58 294.52 273.36 596.49 784.26 695.01 692.70 21
QAPM80.88 3879.50 4385.03 2288.01 6068.97 3191.59 1192.00 1866.63 7475.15 6592.16 1657.70 5695.45 1763.52 5888.76 3590.66 42
IS-MVSNet83.15 2282.81 2084.18 3889.94 3163.30 7491.59 1188.46 6279.04 579.49 2392.16 1665.10 2494.28 3767.71 4691.86 1894.95 2
DeepC-MVS_fast79.65 386.91 886.62 887.76 493.52 972.37 1091.26 1393.04 1076.62 1284.22 693.36 1171.44 896.76 480.82 1395.33 594.16 7
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
NCCC88.06 388.01 388.24 394.41 273.62 291.22 1492.83 1181.50 185.79 493.47 973.02 697.00 384.90 494.94 794.10 9
API-MVS81.99 3181.23 3184.26 3690.94 2370.18 2291.10 1589.32 4871.51 4178.66 2988.28 5865.26 2395.10 2264.74 5791.23 2287.51 90
EPNet83.72 1782.92 1986.14 1784.22 8869.48 2691.05 1685.27 8181.30 276.83 4591.65 2166.09 1995.56 1576.00 2893.85 1293.38 14
CSCG86.41 1086.19 987.07 1192.91 1372.48 890.81 1793.56 573.95 2983.16 1091.07 2975.94 295.19 1879.94 1694.38 1093.55 13
3Dnovator76.31 583.38 2182.31 2386.59 1387.94 6172.94 590.64 1892.14 1777.21 875.47 5692.83 1358.56 5494.72 3173.24 3492.71 1592.13 26
OpenMVScopyleft72.83 1079.77 4978.33 5384.09 4085.17 8269.91 2390.57 1990.97 3266.70 7372.17 8291.91 1854.70 6993.96 4261.81 7190.95 2488.41 78
test_djsdf80.30 4779.32 4683.27 5083.98 8965.37 6390.50 2090.38 3868.55 6576.19 5388.70 5156.44 6193.46 5078.98 1780.14 8390.97 37
MVSFormer82.85 2582.05 2685.24 2187.35 6970.21 2090.50 2090.38 3868.55 6581.32 1589.47 4461.68 4093.46 5078.98 1790.26 2792.05 28
DeepC-MVS79.81 287.08 786.88 787.69 591.16 2172.32 1190.31 2293.94 277.12 982.82 1194.23 472.13 797.09 284.83 595.37 493.65 11
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
Vis-MVSNetpermissive83.46 1882.80 2185.43 1990.25 2968.74 3690.30 2390.13 4276.33 1680.87 1892.89 1261.00 4894.20 4072.45 3890.97 2393.35 15
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
LPG-MVS_test82.08 3081.27 3084.50 3289.23 4068.76 3490.22 2491.94 2175.37 2076.64 4991.51 2454.29 7294.91 2578.44 1983.78 5689.83 57
ACMM73.20 880.78 4179.84 3983.58 4589.31 3768.37 3889.99 2591.60 2770.28 5077.25 3989.66 4153.37 8093.53 4974.24 3382.85 6188.85 69
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
ACMP74.13 681.51 3480.57 3484.36 3489.42 3368.69 3789.97 2691.50 2974.46 2575.04 6790.41 3653.82 7794.54 3377.56 2382.91 6089.86 56
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
MAR-MVS81.84 3280.70 3385.27 2091.32 2071.53 1489.82 2790.92 3369.77 5478.50 3086.21 8362.36 3694.52 3565.36 5292.05 1789.77 59
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
114514_t80.68 4279.51 4284.20 3794.09 567.27 4989.64 2891.11 3158.75 12074.08 7290.72 3358.10 5595.04 2469.70 4389.42 3490.30 48
DeepPCF-MVS80.84 188.10 288.56 286.73 1292.24 1669.03 2889.57 2993.39 777.53 789.79 194.12 578.98 196.58 685.66 295.72 394.58 4
UGNet80.83 3979.59 4184.54 3188.04 5968.09 4089.42 3088.16 6376.95 1076.22 5289.46 4649.30 9593.94 4468.48 4490.31 2691.60 32
Wanjuan Su, Qingshan Xu, Wenbing Tao: Uncertainty-guided Multi-view Stereo Network for Depth Estimation. IEEE Transactions on Circuits and Systems for Video Technology, 2022
AdaColmapbinary80.58 4479.42 4484.06 4193.09 1268.91 3289.36 3188.97 5869.27 6075.70 5589.69 4057.20 5995.77 1363.06 6188.41 3887.50 91
HQP-NCC89.33 3589.17 3276.41 1477.23 41
ACMP_Plane89.33 3589.17 3276.41 1477.23 41
LS3D76.95 7074.82 7483.37 4790.45 2667.36 4889.15 3486.94 7261.87 10669.52 10090.61 3551.71 8894.53 3446.38 12986.71 4988.21 81
ACMH+68.96 1476.01 7774.01 8082.03 6388.60 5165.31 6488.86 3587.55 6870.25 5167.75 10787.47 6541.27 11793.19 5558.37 9175.94 10587.60 89
DP-MVS Recon83.11 2382.09 2586.15 1694.44 170.92 1788.79 3692.20 1570.53 4779.17 2591.03 3164.12 2796.03 1068.39 4590.14 2991.50 34
PVSNet_Blended_VisFu82.62 2781.83 2884.96 2490.80 2569.76 2588.74 3791.70 2569.39 5878.96 2788.46 5565.47 2294.87 2974.42 3288.57 3690.24 49
ACMH67.68 1675.89 7873.93 8181.77 6588.71 4966.61 5288.62 3889.01 5769.81 5366.78 11286.70 7741.95 11691.51 7155.64 10378.14 9387.17 96
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
DP-MVS76.78 7174.57 7683.42 4693.29 1069.46 2788.55 3983.70 9163.98 9470.20 9388.89 4954.01 7694.80 3046.66 12681.88 7086.01 108
F-COLMAP76.38 7474.33 7882.50 5889.28 3866.95 5188.41 4089.03 5564.05 9366.83 11188.61 5346.78 10192.89 5957.48 9678.55 8887.67 88
test178.40 5777.40 5881.40 6987.60 6463.01 7788.39 4189.28 4971.63 3875.34 6087.28 6654.80 6691.11 7762.72 6279.57 8490.09 52
GBi-Net78.40 5777.40 5881.40 6987.60 6463.01 7788.39 4189.28 4971.63 3875.34 6087.28 6654.80 6691.11 7762.72 6279.57 8490.09 52
FMVSNet177.44 6776.12 6981.40 6986.81 7463.01 7788.39 4189.28 4970.49 4874.39 7187.28 6649.06 9791.11 7760.91 7778.52 8990.09 52
COLMAP_ROBcopyleft66.92 1773.01 9970.41 10580.81 7787.13 7265.63 6088.30 4484.19 8862.96 9863.80 12287.69 6238.04 12692.56 6246.66 12674.91 11084.24 117
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
PLCcopyleft70.83 1178.05 6376.37 6783.08 5391.88 1867.80 4288.19 4589.46 4664.33 9169.87 9888.38 5653.66 7993.58 4758.86 8882.73 6387.86 86
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
MG-MVS83.41 1983.45 1683.28 4992.74 1462.28 8388.17 4689.50 4575.22 2281.49 1492.74 1566.75 1695.11 2072.85 3591.58 2092.45 23
TAPA-MVS73.13 979.15 5377.94 5482.79 5789.59 3262.99 8088.16 4791.51 2865.77 8077.14 4391.09 2860.91 4993.21 5350.26 11987.05 4592.17 25
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
OMC-MVS82.69 2681.97 2784.85 2688.75 4867.42 4587.98 4890.87 3474.92 2379.72 2191.65 2162.19 3993.96 4275.26 3086.42 5193.16 19
PAPM_NR83.02 2482.41 2284.82 2792.47 1566.37 5387.93 4991.80 2373.82 3177.32 3890.66 3467.90 1494.90 2770.37 4189.48 3393.19 18
CNLPA78.08 6276.79 6481.97 6490.40 2771.07 1587.59 5084.55 8566.03 7972.38 8189.64 4257.56 5786.04 10959.61 8483.35 5988.79 70
FMVSNet278.20 6177.21 6181.20 7287.60 6462.89 8187.47 5189.02 5671.63 3875.29 6487.28 6654.80 6691.10 8062.38 6679.38 8789.61 61
EPNet_dtu75.46 8174.86 7377.23 10482.57 10654.60 12086.89 5283.09 9471.64 3766.25 11485.86 8655.99 6388.04 9854.92 10486.55 5089.05 65
IterMVS-LS80.06 4879.38 4582.11 6185.89 7863.20 7686.79 5389.34 4774.19 2775.45 5786.72 7466.62 1792.39 6572.58 3776.86 10090.75 41
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
PAPR81.66 3380.89 3283.99 4290.27 2864.00 7286.76 5491.77 2468.84 6377.13 4489.50 4367.63 1594.88 2867.55 4788.52 3793.09 20
Vis-MVSNet (Re-imp)78.36 5978.45 5178.07 10188.64 5051.78 12686.70 5579.63 11874.14 2875.11 6690.83 3261.29 4589.75 9458.10 9491.60 1992.69 22
FMVSNet377.88 6576.85 6380.97 7586.84 7362.36 8286.52 5688.77 6071.13 4275.34 6086.66 7954.07 7591.10 8062.72 6279.57 8489.45 62
PVSNet_BlendedMVS80.60 4380.02 3882.36 6088.85 4465.40 6186.16 5792.00 1869.34 5978.11 3386.09 8466.02 2094.27 3871.52 3982.06 6787.39 92
BH-untuned79.47 5278.60 5082.05 6289.19 4265.91 5786.07 5888.52 6172.18 3675.42 5887.69 6261.15 4693.54 4860.38 8086.83 4786.70 104
MVS_111021_HR85.14 1584.75 1486.32 1591.65 1972.70 685.98 5990.33 4176.11 1782.08 1391.61 2371.36 994.17 4181.02 1092.58 1692.08 27
jason81.39 3580.29 3684.70 2986.63 7569.90 2485.95 6086.77 7363.24 9581.07 1789.47 4461.08 4792.15 6778.33 2290.07 3192.05 28
jason: jason.
test_040272.79 10070.44 10479.84 8388.13 5865.99 5585.93 6184.29 8765.57 8267.40 10985.49 8846.92 10092.61 6035.88 13874.38 11380.94 124
OurMVSNet-221017-074.26 8772.42 8879.80 8483.76 9059.59 9685.92 6286.64 7466.39 7666.96 11087.58 6439.46 12191.60 7065.76 5069.27 12588.22 80
EG-PatchMatch MVS74.04 8871.82 9280.71 7884.92 8467.42 4585.86 6388.08 6466.04 7864.22 12083.85 9435.10 13292.56 6257.44 9780.83 7682.16 122
CLD-MVS82.31 2981.65 2984.29 3588.47 5567.73 4485.81 6492.35 1475.78 1978.33 3186.58 8064.01 2894.35 3676.05 2787.48 4090.79 40
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
SixPastTwentyTwo73.37 9371.26 9879.70 8585.08 8357.89 10685.57 6583.56 9271.03 4465.66 11685.88 8542.10 11492.57 6159.11 8763.34 13288.65 73
lupinMVS81.39 3580.27 3784.76 2887.35 6970.21 2085.55 6686.41 7662.85 9981.32 1588.61 5361.68 4092.24 6678.41 2190.26 2791.83 30
DELS-MVS85.41 1385.30 1285.77 1888.49 5467.93 4185.52 6793.44 678.70 683.63 989.03 4874.57 395.71 1480.26 1594.04 1193.66 10
MVS_111021_LR82.61 2882.11 2484.11 3988.82 4671.58 1385.15 6886.16 7974.69 2480.47 2091.04 3062.29 3790.55 8780.33 1490.08 3090.20 50
OpenMVS_ROBcopyleft64.09 1970.56 11168.19 11477.65 10280.26 12259.41 9985.01 6982.96 9658.76 11965.43 11882.33 10437.63 12891.23 7645.34 13176.03 10482.32 120
BH-RMVSNet79.61 5078.44 5283.14 5289.38 3465.93 5684.95 7087.15 6973.56 3278.19 3289.79 3956.67 6093.36 5259.53 8686.74 4890.13 51
BH-w/o78.21 6077.33 6080.84 7688.81 4765.13 6784.87 7187.85 6569.75 5574.52 7084.74 9361.34 4393.11 5758.24 9385.84 5384.27 116
TDRefinement67.49 11964.34 12376.92 10573.47 13461.07 8784.86 7282.98 9559.77 11558.30 13185.13 9026.06 13687.89 9947.92 12460.59 13481.81 123
TAMVS78.89 5677.51 5783.03 5487.80 6267.79 4384.72 7385.05 8467.63 6876.75 4687.70 6162.25 3890.82 8558.53 9087.13 4490.49 44
TR-MVS77.44 6776.18 6881.20 7288.24 5763.24 7584.61 7486.40 7767.55 7077.81 3586.48 8254.10 7493.15 5657.75 9582.72 6487.20 95
PVSNet_Blended80.98 3780.34 3582.90 5688.85 4465.40 6184.43 7592.00 1867.62 6978.11 3385.05 9166.02 2094.27 3871.52 3989.50 3289.01 66
CDS-MVSNet79.07 5477.70 5683.17 5187.60 6468.23 3984.40 7686.20 7867.49 7176.36 5186.54 8161.54 4290.79 8661.86 7087.33 4190.49 44
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
K. test v371.19 10768.51 11179.21 9183.04 9857.78 10884.35 7776.91 12572.90 3462.99 12482.86 10039.27 12291.09 8261.65 7252.66 14088.75 71
MVSTER79.01 5577.88 5582.38 5983.07 9764.80 6884.08 7888.95 5969.01 6278.69 2887.17 7154.70 6992.43 6474.69 3180.57 7989.89 55
ab-mvs79.51 5178.97 4881.14 7488.46 5660.91 8883.84 7989.24 5270.36 4979.03 2688.87 5063.23 3190.21 8965.12 5382.57 6592.28 24
PAPM77.68 6676.40 6681.51 6787.29 7161.85 8583.78 8089.59 4464.74 8771.23 8788.70 5162.59 3493.66 4652.66 11387.03 4689.01 66
1112_ss77.40 6976.43 6580.32 8189.11 4360.41 9183.65 8187.72 6762.13 10473.05 7486.72 7462.58 3589.97 9362.11 6880.80 7790.59 43
PCF-MVS73.52 780.38 4678.84 4985.01 2387.71 6368.99 3083.65 8191.46 3063.00 9777.77 3690.28 3766.10 1895.09 2361.40 7388.22 3990.94 38
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
XVG-ACMP-BASELINE76.11 7674.27 7981.62 6683.20 9464.67 6983.60 8389.75 4369.75 5571.85 8387.09 7232.78 13392.11 6869.99 4280.43 8088.09 83
XVG-OURS-SEG-HR80.81 4079.76 4083.96 4485.60 8168.78 3383.54 8490.50 3670.66 4676.71 4791.66 2060.69 5091.26 7476.94 2681.58 7291.83 30
IB-MVS68.01 1575.85 7973.36 8583.31 4884.76 8566.03 5483.38 8585.06 8370.21 5269.40 10181.05 11345.76 10394.66 3265.10 5475.49 10889.25 64
Christian Sormann, Mattia Rossi, Andreas Kuhn and Friedrich Fraundorfer: IB-MVS: An Iterative Algorithm for Deep Multi-View Stereo based on Binary Decisions. BMVC 2021
HY-MVS69.67 1277.95 6477.15 6280.36 8087.57 6860.21 9283.37 8687.78 6666.11 7775.37 5987.06 7363.27 2990.48 8861.38 7482.43 6690.40 47
XVG-OURS80.41 4579.23 4783.97 4385.64 8069.02 2983.03 8790.39 3771.09 4377.63 3791.49 2654.62 7191.35 7275.71 2983.47 5891.54 33
PT_06_test75.20 8473.77 8379.49 8882.69 10460.19 9382.34 8886.99 7169.71 5772.52 7978.31 12356.27 6290.07 9262.03 6973.11 11788.23 79
PatchFormer_test73.70 9071.86 9179.21 9182.91 10158.94 10082.34 8882.17 10465.21 8371.05 8978.31 12344.21 10890.17 9063.29 5977.28 9788.53 74
cascas76.72 7274.64 7582.99 5585.78 7965.88 5882.33 9089.21 5360.85 11072.74 7681.02 11447.28 9993.75 4567.48 4885.02 5489.34 63
RPSCF73.23 9771.46 9478.54 9782.50 10759.85 9582.18 9182.84 9758.96 11871.15 8889.41 4745.48 10584.77 11358.82 8971.83 12091.02 36
tpmp4_e2373.45 9271.17 9980.31 8283.55 9259.56 9781.88 9282.33 10257.94 12470.51 9281.62 10951.19 9291.63 6953.96 10877.51 9689.75 60
Test_1112_low_res76.40 7375.44 7279.27 8989.28 3858.09 10481.69 9387.07 7059.53 11772.48 8086.67 7861.30 4489.33 9660.81 7980.15 8290.41 46
PatchFormer-LS_test74.50 8573.05 8678.86 9582.95 10059.55 9881.65 9482.30 10367.44 7271.62 8678.15 12552.34 8388.92 9765.05 5575.90 10688.12 82
IterMVS74.29 8672.94 8778.35 9981.53 11363.49 7381.58 9582.49 9968.06 6769.99 9783.69 9651.66 8985.54 11165.85 4971.64 12186.01 108
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
Test473.95 8972.20 8979.21 9182.91 10158.94 10081.25 9682.17 10465.21 8371.05 8982.44 10244.21 10890.17 9063.29 5977.28 9788.53 74
CostFormer75.24 8373.90 8279.27 8982.65 10558.27 10380.80 9782.73 9861.57 10775.33 6383.13 9955.52 6491.07 8364.98 5678.34 9288.45 76
MIMVSNet168.58 11766.78 11973.98 11880.07 12351.82 12580.77 9884.37 8664.40 9059.75 12882.16 10636.47 13083.63 11442.73 13270.33 12386.48 106
MSDG73.36 9570.99 10080.49 7984.51 8765.80 5980.71 9986.13 8065.70 8165.46 11783.74 9544.60 10690.91 8451.13 11776.89 9984.74 115
tpm273.26 9671.46 9478.63 9683.34 9356.71 11380.65 10080.40 11356.63 12673.55 7382.02 10751.80 8791.24 7556.35 10178.42 9187.95 84
XXY-MVS75.41 8275.56 7174.96 11383.59 9157.82 10780.59 10183.87 9066.54 7574.93 6888.31 5763.24 3080.09 12662.16 6776.85 10186.97 100
TinyColmap67.30 12164.81 12274.76 11581.92 11056.68 11480.29 10281.49 10960.33 11256.27 13683.22 9824.77 13787.66 10145.52 13069.47 12479.95 127
FMVSNet569.50 11467.96 11774.15 11782.97 9955.35 11880.01 10382.12 10662.56 10263.02 12381.53 11036.92 12981.92 12048.42 12274.06 11485.17 113
tpmrst72.39 10172.13 9073.18 12180.54 12049.91 13279.91 10479.08 12063.11 9671.69 8579.95 11855.32 6582.77 11865.66 5173.89 11686.87 101
PatchmatchNetpermissive73.12 9871.33 9678.49 9883.18 9560.85 8979.63 10578.57 12164.13 9271.73 8479.81 12051.20 9185.97 11057.40 9876.36 10288.66 72
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
PatchMatch-RL72.38 10270.90 10176.80 10788.60 5167.38 4779.53 10676.17 12662.75 10169.36 10282.00 10845.51 10484.89 11253.62 10980.58 7878.12 131
CMPMVSbinary51.72 2170.19 11368.16 11576.28 10873.15 13557.55 10979.47 10783.92 8948.02 13756.48 13584.81 9243.13 11086.42 10862.67 6581.81 7184.89 114
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
LTVRE_ROB69.57 1376.25 7574.54 7781.41 6888.60 5164.38 7179.24 10889.12 5470.76 4569.79 9987.86 5949.09 9693.20 5456.21 10280.16 8186.65 105
Andreas Kuhn, Heiko Hirschmüller, Daniel Scharstein, Helmut Mayer: A TV Prior for High-Quality Scalable Multi-View Stereo Reconstruction. International Journal of Computer Vision 2016
tpm72.37 10371.71 9374.35 11682.19 10952.00 12479.22 10977.29 12364.56 8972.95 7583.68 9751.35 9083.26 11658.33 9275.80 10787.81 87
USDC70.33 11268.37 11276.21 10980.60 11956.23 11779.19 11086.49 7560.89 10961.29 12585.47 8931.78 13489.47 9553.37 11076.21 10382.94 119
tpm cat170.57 11068.31 11377.35 10382.41 10857.95 10578.08 11180.22 11652.04 13268.54 10577.66 12652.00 8687.84 10051.77 11472.07 11986.25 107
WTY-MVS75.65 8075.68 7075.57 11186.40 7656.82 11277.92 11282.40 10165.10 8676.18 5487.72 6063.13 3280.90 12360.31 8181.96 6889.00 68
EPMVS69.02 11668.16 11571.59 12379.61 12549.80 13377.40 11366.93 13962.82 10070.01 9579.05 12145.79 10277.86 13156.58 10075.26 10987.13 97
MDTV_nov1_ep1369.97 10683.18 9553.48 12277.10 11480.18 11760.45 11169.33 10380.44 11748.89 9886.90 10351.60 11578.51 90
LF4IMVS64.02 12462.19 12569.50 12970.90 13753.29 12376.13 11577.18 12452.65 13158.59 12980.98 11523.55 13876.52 13453.06 11266.66 12778.68 130
sss73.60 9173.64 8473.51 12082.80 10355.01 11976.12 11681.69 10862.47 10374.68 6985.85 8757.32 5878.11 13060.86 7880.93 7587.39 92
CR-MVSNet73.37 9371.27 9779.67 8681.32 11465.19 6575.92 11780.30 11459.92 11472.73 7781.19 11152.50 8186.69 10459.84 8277.71 9487.11 98
RPMNet71.62 10568.94 10979.67 8681.32 11465.19 6575.92 11778.30 12257.60 12572.73 7776.45 13052.30 8486.69 10448.14 12377.71 9487.11 98
MIMVSNet70.69 10969.30 10774.88 11484.52 8656.35 11675.87 11979.42 11964.59 8867.76 10682.41 10341.10 11881.54 12246.64 12881.34 7386.75 103
PMMVS69.34 11568.67 11071.35 12575.67 13062.03 8475.17 12073.46 13250.00 13568.68 10479.05 12152.07 8578.13 12961.16 7582.77 6273.90 134
MDTV_nov1_ep13_2view37.79 14275.16 12155.10 13066.53 11349.34 9453.98 10787.94 85
UnsupCasMVSNet_eth67.33 12065.99 12071.37 12473.48 13351.47 12875.16 12185.19 8265.20 8560.78 12780.93 11642.35 11377.20 13357.12 9953.69 13985.44 111
dp66.80 12265.43 12170.90 12679.74 12448.82 13575.12 12374.77 13159.61 11664.08 12177.23 12742.89 11180.72 12448.86 12166.58 12883.16 118
Patchmtry70.74 10869.16 10875.49 11280.72 11754.07 12174.94 12480.30 11458.34 12170.01 9581.19 11152.50 8186.54 10653.37 11071.09 12285.87 110
PVSNet64.34 1872.08 10470.87 10275.69 11086.21 7756.44 11574.37 12580.73 11162.06 10570.17 9482.23 10542.86 11283.31 11554.77 10584.45 5587.32 94
UnsupCasMVSNet_bld63.70 12561.53 12670.21 12873.69 13251.39 12972.82 12681.89 10755.63 12957.81 13271.80 13338.67 12478.61 12849.26 12052.21 14180.63 125
PatchT68.46 11867.85 11870.29 12780.70 11843.93 13772.47 12774.88 13060.15 11370.55 9176.57 12849.94 9381.59 12150.58 11874.83 11185.34 112
MVS-HIRNet59.14 12857.67 12963.57 13381.65 11243.50 13871.73 12865.06 14139.59 14051.43 13957.73 14038.34 12582.58 11939.53 13473.95 11564.62 138
ANet_high50.57 13646.10 13663.99 13248.67 14539.13 14170.99 12980.85 11061.39 10831.18 14457.70 14117.02 14373.65 13731.22 14215.89 14979.18 128
HyFIR71.37 10670.50 10373.97 11980.52 12159.87 9470.92 13082.42 10056.28 12765.84 11576.50 12953.72 7883.21 11761.07 7687.21 4378.84 129
N_pmnet52.79 13253.26 13251.40 14278.99 1277.68 14969.52 1313.89 14951.63 13457.01 13474.98 13140.83 11965.96 14337.78 13664.67 13080.56 126
FPMVS53.68 13151.64 13359.81 13565.08 14151.03 13069.48 13269.58 13541.46 13840.67 14272.32 13216.46 14470.00 14124.24 14465.42 12958.40 140
DSMNet-mixed57.77 12956.90 13160.38 13467.70 14035.61 14369.18 13353.97 14432.30 14557.49 13379.88 11940.39 12068.57 14238.78 13572.37 11876.97 133
PVSNet_057.27 2061.67 12659.27 12768.85 13079.61 12557.44 11068.01 13473.44 13355.93 12858.54 13070.41 13444.58 10777.55 13247.01 12535.91 14371.55 135
LP61.36 12757.78 12872.09 12275.54 13158.53 10267.16 13575.22 12951.90 13354.13 13769.97 13537.73 12780.45 12532.74 14155.63 13777.29 132
JIA-IIPM66.32 12362.82 12476.82 10677.09 12861.72 8665.34 13675.38 12858.04 12364.51 11962.32 13942.05 11586.51 10751.45 11669.22 12682.21 121
PMVScopyleft37.38 2244.16 13840.28 13955.82 13840.82 14842.54 13965.12 13763.99 14234.43 14224.48 14657.12 1423.92 14776.17 13517.10 14755.52 13848.75 142
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
new_pmnet50.91 13550.29 13452.78 14168.58 13934.94 14663.71 13856.63 14339.73 13944.95 14065.47 13721.93 13958.48 14534.98 13956.62 13664.92 137
HyFIR lowres test51.79 13350.01 13557.11 13768.82 13849.21 13460.50 13953.26 14534.52 14143.77 14164.94 13820.34 14171.75 13939.87 13364.06 13150.39 141
PNet_i23d38.26 14035.42 14046.79 14358.74 14235.48 14459.65 14051.25 14632.45 14423.44 14847.53 1452.04 14958.96 14425.60 14318.09 14845.92 145
no-one51.08 13445.79 13766.95 13157.92 14450.49 13159.63 14176.04 12748.04 13631.85 14356.10 14319.12 14280.08 12736.89 13726.52 14470.29 136
wuykxyi23d39.76 13933.18 14159.51 13646.98 14644.01 13657.70 14267.74 13824.13 14613.98 15034.33 1481.27 15071.33 14034.23 14018.23 14763.18 139
testpf56.51 13057.58 13053.30 14071.99 13641.19 14046.89 14369.32 13758.06 12252.87 13869.45 13627.99 13572.73 13859.59 8562.07 13345.98 144
wuyk23d16.82 14215.94 14319.46 14658.74 14231.45 14739.22 1443.74 1506.84 1496.04 1512.70 1491.27 15024.29 14810.54 14914.40 1502.63 148
Gipumacopyleft45.18 13741.86 13855.16 13977.03 12951.52 12732.50 14580.52 11232.46 14327.12 14535.02 1479.52 14675.50 13622.31 14560.21 13538.45 146
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
MVEpermissive26.22 2330.37 14125.89 14243.81 14444.55 14735.46 14528.87 14639.07 14718.20 14718.58 14940.18 1462.68 14847.37 14617.07 14823.78 14648.60 143
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
ab-mvs-re7.23 1439.64 1440.00 1470.00 1500.00 1500.00 1470.00 1510.00 1500.00 15286.72 740.00 1520.00 1490.00 1500.00 1510.00 149
DeepMVS_CXcopyleft27.40 14540.17 14926.90 14824.59 14817.44 14823.95 14748.61 1449.77 14526.48 14718.06 14624.47 14528.83 147
ITE_SJBPF78.22 10081.77 11160.57 9083.30 9369.25 6167.54 10887.20 7036.33 13187.28 10254.34 10674.62 11286.80 102
Test By Simon64.33 25
HQP-MVS21.25 140
ACMMP++81.25 74
ACMMP++_ref81.95 69
NP-MVS90.24 38
HQP2-MVS60.17 53
HQP3-MVS92.19 1685.99 52
HQP4-MVS77.24 4095.11 2091.03 35
BP-MVS77.47 24
HQP5-MVS66.98 50
door69.44 136
LGP-MVS_train84.50 3289.23 4068.76 3491.94 2175.37 2076.64 4991.51 2454.29 7294.91 2578.44 1983.78 5689.83 57
lessismore_v078.97 9481.01 11657.15 11165.99 14061.16 12682.82 10139.12 12391.34 7359.67 8346.92 14288.43 77
door-mid69.98 134