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