Skip to content (access key 's')
Logo of Technion
Logo of CS Department


Pixel Club: Region Ranking Methods for Image Segmentation
event speaker icon
Payman Yadollahpour (Toyota Technological Institute at Chicago)
event date icon
Sunday, 25.5.2014, 11:30
event location icon
Room 337 Taub Bld.
I will describe some of our recent work on learning systems for image segmentation using a two stage approach: given an image, we first obtain a /diverse/ set of top M most probable segmentations from a discrete probabilistic model, and then rank these using a discriminatively trained ranker that makes use of much more complex features than what could be tractably used in the initial model. The ranking model is learned to minimize the gap with the best segmentation in the set.

This approach allows for better exploration of the solution space than could be achieved by just inferring the most probable segmentation from the initial probabilistic model, and produces excellent segmentation results on a number of challenging datasets.

This is joint work with Gregory Shakhnarovich, Dhruv Batra, and Pavel Kisilev.
[Back to the index of events]