Hadar Averbuch (Tel-Aviv University)
Tuesday, 13.6.2017, 11:30
In the talk, I will present a distillation algorithm which operates on a large, unstructured, and noisy collections of internet images returned from an online object query. I will introduce the notion of a distilled set, which is a clean, coherent, and structured subset of inlier images, where the object of interest is properly segmented out throughout the set. I will also demonstrate the utility of our technique with a number of interesting graphics applications, including a novel data-driven morphing technique.
Hadar Averbuch-Elor received a B.Sc. in Electrical Engineering from the Technion (cum laude) in 2012. She is currently a Ph.D. candidate in Tel Aviv University, under the supervision of Prof. Daniel Cohen-Or. She worked as an computer vision algorithms developer in the defense industry from 2011 to 2015. In 2016, she was a research intern in the Computational Photography group at Facebook (Seattle) and currently continues to work part-time from the Facebook TLV office. Her research interests include multi-view systems and unstructured image collections.