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Matlab & mex implementation of "Intrinsic Image Decomposition Using Structure-Texture Separation and Surface Normals", ECCV 2014

Home Page: http://cg.postech.ac.kr/research/intrinsic/

License: MIT License

MATLAB 64.09% HTML 0.56% M 0.02% C 17.82% C++ 17.41% Batchfile 0.08% Mercury 0.01%

coupe.intrinsic_texture's Introduction

Intrinsic Images using Texture Filtering

Unoptimized implementation of "Intrinsic Image Decomposition Using Structure-Texture Separation and Surface Normals" in Matlab and C++ MEX.

How to use it

You can try demo.m using included RGB & depth image.
Included input RGB and depth images are extracted from NYU Depth V2 dataset.
Algorithm requires texture-removed RGB image. Authors' code of regcovsmoothing and RGF are included.
You can use any structure-texture separation algorithm instead of it.

Hardware/software requirements

  1. Original code is tested on Matlab 2015a 64bit, Windows 7.
  2. For other platform (32bit Windows, Linux, MacOS), compile the C++ mex source codes in 'mex' directory.
  3. To compile mex source codes, corresponding ann and opencv library is required (please refer the compile.m).

Contributors

Junho Jeon ([email protected])

Citation

Cite our papers if you find this software useful.

  1. Junho Jeon, Sunghyun Cho, Xin Tong, Seungyong Lee, "Intrinsic Image Decomposition using Structure-Texture Separation and Surface Normals", European Conference on Computer Vision (ECCV 2014), September 2014.

coupe.intrinsic_texture's People

Contributors

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