1、Roger Grosse, Micah K. Johnson, Edward H. Adelson, and William T. Freeman, Ground truth dataset and baseline evaluations for intrinsic image algorithms, in Proceedings of the International Conference on Computer Vision (ICCV), 2009
http://people.csail.mit.edu/rgrosse/intrinsic/downloads.html
https://github.com/akanazawa/Intrinsic-Image/tree/master/MIT-intrinsic
code: python
2、Recovering Intrinsic Images with a Global Sparsity Prior on Reflectance
http://people.tuebingen.mpg.de/mkiefel/projects/intrinsic/
code: matlab/python/C++
3、User-assisted Intrinsic Images
http://people.csail.mit.edu/sparis/
https://sites.google.com/site/masterreports/nov3
http://code.google.com/p/jh-cv/source/browse/trunk/IntrinsicImage/?r=188#IntrinsicImage
4、Intrinsic Image Decomposition Using Optimization and User Scribbles/Intrinsic Images Using Optimization
Jianbing Shen, Xiaoshan Yang, Yunde Jia, Xuelong Li. IEEE Computer Vision and Pattern Recognition (IEEE CVPR 2011), pp. 3481-3487, Colorado, USA, 2011
http://cs.bit.edu.cn/shenjianbing/
5、A Closed-form Solution to Retinex with Non-local Texture Constraints
https://windrocblog.sinaapp.com/?p=427
code: vc(*)
6、Illumination decomposition for material recoloring with consistent interreflections
Robert Carroll, Ravi Ramamoorthi, Maneesh Agrawala
SIGGRAPH '11: SIGGRAPH 2011 papers
http://vis.berkeley.edu/papers/interreflections/
7、Color Constancy, Intrinsic Images, and Shape Estimation
Jonathan T. Barron, Jitendra Malik
European Conference on Computer Vision (ECCV), 2012
http://www.cs.berkeley.edu/~barron/
code: matlab