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 bysorted bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort by
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.
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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.
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
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
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
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
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
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
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
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
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
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
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
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
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.
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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-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.
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
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
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
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
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
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
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
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
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
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.
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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)
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
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
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)
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
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
HQP4-MVS77.24 4095.11 2091.03 35
lessismore_v078.97 9481.01 11657.15 11165.99 14061.16 12682.82 10139.12 12391.34 7359.67 8346.92 14288.43 77
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
door69.44 136
HQP5-MVS66.98 50
HQP-NCC89.33 3589.17 3276.41 1477.23 41
ACMP_Plane89.33 3589.17 3276.41 1477.23 41
BP-MVS77.47 24
HQP3-MVS92.19 1685.99 52
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
HQP2-MVS60.17 53
NP-MVS90.24 38
MDTV_nov1_ep13_2view37.79 14275.16 12155.10 13066.53 11349.34 9453.98 10787.94 85
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
ACMMP++_ref81.95 69
ACMMP++81.25 74
HQP-MVS21.25 140
Test By Simon64.33 25
door-mid69.98 134