1. An opposition to LOCUS David Lee

2. Unsupervised? Poor dataset and How to take advantage of it with top-down generative approach

4. Unsupervised? Images themselves are already a crude segmentation Assumptions (Tell the system that…)  There exists one horse,  facing left,  occupying 15-30% of the image,  centered (although authors claim they’re not),  strong edge between foreground & background  small color/texture variance within foreground  Weizmann horses & Caltech 101 !!

5. Mean of Canny edges

6. Mean of hand-labeled mask

7. Top-down generative approach When the data has strong constraints, take advantage of that high level prior knowledge. If you know what the data is like, let the generative model be it.

8. My Universal Horse Segmentation MUHS 70%

10. My Universal Horse Segmentation 0.536240 0.880552 0.493996 0.708324 0.718089 0.530342 0.802334 0.545985 0.470904