Learning and Inference in Low-Level Vision
Yair Weiss
2009 Invited Talk
Abstract
Low level vision addresses the issues of labeling and organizing image pixels according to scene related properties - such as motion, contrast, depth and reflectance. I will describe our attempts to understand low-level vision in humans and machines as optimal inference given the statistics of the world. If time permits, I will discuss my favorite NIPS rejected papers.
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