Bogdan Alexe, Thomas Deselaers, and Vittorio Ferrari

Overview

Welcome to this release of ClassCut [1]. ClassCut is a method for unsupervised class segmentation. Its goal is to jointly segment objects of the same unknown class from a set of images. ClassCut is based on a binary pairwise energy function similar to those used in interactive/supervised segmentation, but as opposed to those, its energy function is defined over a set of images rather than on a single image. ClassCut alternates two stages: (1) learning/ updating a class model given the current segmentations; (2) jointly segmenting the objects in all images given the current class model. It converges when the segmentation is unchanged in two consecutive iterations.

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References

1. ClassCut for Unsupervised Class Segmentation
   Bogdan Alexe, Thomas Deselaers and Vittorio Ferrari,
   In European Conference in Computer Vision (ECCV), 2010.