EE Seminar: Live Semantic Face Editing in Video using Deep Adversarial Autoencoders
Speaker: Oran Gafni
M.Sc. student under the supervision of Prof. Lior Wolf
Wednesday, February 27th 2019 at 15:30
Room 011, Kitot Bldg., Faculty of Engineering
Live Semantic Face Editing in Video using Deep Adversarial Autoencoders
Abstract
We propose a method for face editing in video that enables live face effects at high frame rates. Two applications are considered (i) replacing the face with a similar face that is not recognizable as the same identity, and (ii) modifying parts of the face. These applications require maintaining the pose, the apparent illumination, and the expression of the face in the input frames while making natural-looking modifications according to the desired task.
We achieve this by a novel feed forward encoder-decoder architecture that is conditioned on the target high-level features of a single image. The network is global, in the sense that it does not need to be retrained for a given video or based on the desired outcome, and it creates naturally looking sequences with little distortions.
