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