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.

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.
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LTVRE69.57 176.25 174.54 181.41 188.60 164.38 279.24 389.12 170.76 169.79 187.86 149.09 193.20 156.21 280.16 286.65 1
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
COLMAPcopyleft66.92 273.01 270.41 280.81 287.13 265.63 188.30 184.19 262.96 263.80 287.69 238.04 392.56 246.66 374.91 384.24 3
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
CMPMVSbinary51.72 370.19 368.16 376.28 373.15 457.55 379.47 283.92 348.02 356.48 384.81 343.13 286.42 362.67 181.81 184.89 2
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
Gipumacopyleft45.18 441.86 455.16 577.03 351.52 432.50 580.52 432.46 527.12 435.02 69.52 475.50 522.31 460.21 438.45 6
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
PMVScopyleft37.38 444.16 540.28 555.82 440.82 642.54 565.12 463.99 534.43 424.48 557.12 43.92 576.17 417.10 555.52 548.75 4
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
MVEpermissive26.22 530.37 625.89 643.81 644.55 535.46 628.87 639.07 618.20 618.58 640.18 52.68 647.37 617.07 623.78 648.60 5
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)