Alpha Matting Evaluation Website
www.alphamatting.com

Source Code

We will update this website with links to more source code soon.

Please not that we cannot provide code for "Easy Matting" [3], "Robust Matting" [4] and "Bayesian Matting" [5] due to licensing issues.

Source code for [1],[2],[6],[7], and [10] can be obtained from the authors' websites at:
[1]: Direct link to download
[2]: Download from project website
[6]: Download from Matlab Central
[7]: Download from project website
[10]: Download from GitHub

Source code for [8] and [9] was obtained from the authors:
[8]: Direct link to download
[9]: Direct link to download

References:
[1] A. Levin D. Lischinski and Y. Weiss. A Closed Form Solution to Natural Image Matting.
Conference on Computer Vision and Pattern Recognition (CVPR), June 2007.
[2] A. Levin, A. Rav-Acha, D. Lischinski. Spectral Matting.
Conference on Computer Vision and Pattern Recognition (CVPR), June 2006.
[3] Y. Guan, W. Cheny, X. Liang, Z. Ding, Q. Peng, Easy Matting: A Stroke Based Approach for Continuous Image Matting.
Eurographics, 2006.
[4] J. Wang, M. Cohen, Optimized Color Sampling for Robust Matting.
Conference on Computer Vision and Pattern Recognition (CVPR), 2007.
[5] Bayesian MattingY.Y. Chuang, B. Curless, D. Salesin, R. Szeliski, A Bayesian Approach to Digital Matting.
Conference on Computer Vision and Pattern Recognition (CVPR), 2001.
[6] Y. Zheng, C. Kambhamettu. Learning Based Digital Matting.
ICCV 2009
[7] Q. Chen, D. Li, C.-K. Tang. KNN Matting.
Conference on Computer Vision and Pattern Recognition (CVPR), June 2012.
[8] E.Shahrian, D.Rajan, B.Price, S.Cohen. Improving Image Matting using Comprehensive Sampling Sets.
Conference on Computer Vision and Pattern Recognition (CVPR), June 2013.
[9] E.Shahrian, D.Rajan. Weighted Color and Texture Sample Selection for Image Matting.
IEEE Transaction on Image Processing, Volume:PP, Issue: 99, 2013.
[10] Yagiz Aksoy, Tunc Ozan Aydin, Marc Pollefeys. Designing Effective Inter-Pixel Information Flow for Natural Image Matting.
Conference on Computer Vision and Pattern Recognition (CVPR), 2017.