Deep Internal Learning
, The Weizmann Institute of Science
Date: Wednesday, May 01, 2019
Time: 12:00 PM to 1:00 PM
Location: 32-D463 Star Conference Room
Event Type: Seminar
Host: Bill Freeman, MIT CSAIL
Contact: Lukas Murmann, firstname.lastname@example.org
Speaker URL: http://www.weizmann.ac.il/math/irani/home
TALK: Michal Irani, "Deep Internal Learning"
In this talk I will show how complex visual inference tasks can be performed using Deep-Learning, in a totally unsupervised way, by exploiting the internal redundancy inside a single image. The strong recurrence of information inside a single natural image provides powerful internal examples which suffice for self-supervision of CNNs, without any prior examples or training data. This new “Deep Internal Learning” paradigm gives rise to true “Zero-Shot Learning”. I will show the power of this approach to a variety of problems, including super-resolution, image-segmentation, transparent layer separation, blind image-dehazing, image-retargeting, and more.
AI & Machine Learning, Graphics & Vision
Created by Lukas Murmann at Friday, April 19, 2019 at 10:20 AM.