Grouping data is a useful tool for many computer vision tasks.
Relevant papers
- M. Andreetto, L. Zelnik-Manor and P. Perona, Unsupervised Learning of Categorical Segments in Image Collections, IEEE Trans. on Pattern Analysis and Machine Intelligence (PAMI), 34(9): 1842–1855, Sep. 2012.
- B. Hariharan, L. Zelnik-Manor, S.V. N. Vishwanathan and M. Varma, Large Scale Max-Margin Multi-Label Classification with Priors, ICML’2010 (pdf)
- M. Andreetto, L. Zelnik-Manor and P. Perona, Unsupervised Learning of Categorical Segments in Image Collections, The Sixth IEEE Computer Society Workshop on Perceptual Organization in Computer Vision (POCV’08), in Computer Vision and Pattern Recognition, Jun. 2008. (pdf)
- M. Andreetto, L. Zelnik-Manor and P. Perona, Non-parametric Probabilistic Image Segmentation, ICCV’2007. (pdf, Project web-page)
- T. Hassner, L. Zelnik-Manor, G. Leifman and R. Basri, Minimal-Cut Model Composition, IEEE Shape Modeling International Conference (SMI’05), pp. 72-81, June 2005. (pdf, Project page)
Winner of “SMI best student paper award” and “AIM@SHAPE Best paper award 2005”
- S. Agarwal, J. Lim, L. Zelnik-Manor, P. Perona, D. Kriegman and S. Belongie, Beyond Pairwise Clustering, IEEE Conference on Computer Vision and Pattern Recognition,Vol. 2, pp. 838-845,June 2005 (CVPR’2005). (pdf, Project page)
- L. Zelnik-Manor and P. Perona, Self-Tuning Spectral Clustering, Advances in Neural Information Processing Systems 17, pp. 1601-1608, 2005, (NIPS’2004). (pdf, Project page)