Dolev Ofri (Weizmann Institute of Science)
Tuesday, 11.1.2022, 11:30
Zoom Lecture: https://technion.zoom.us/my/chaimbaskin
While image editing and manipulation tools have seen steady progress, allowing complex editing effects to be achieved by novice users, video editing remains a difficult task: applying edits in a temporally consistent manner to all frames remains a key challenge.
In this talk, I’ll present a novel method that tackles this challenge by decomposing an input video into a set of layered 2D atlases, each providing a unified representation of an object/background over the entire video. Using the learned decomposition, we can then simply edit the 2D atlases (or a single frame), and automatically propagate the edits to the entire video. By operating purely in 2D, our method does not require any prior 3D knowledge about scene geometry or camera poses.
I’ll show a variety of exciting editing results including texture mapping, video style transfer, image-to-video texture transfer, and segmentation/labeling propagation.Project page: https://layered-neural-atlases.github.io/
Dolev Ofri completed her BSc in Electrical Engineering at the Technion with honors. She is an M.Sc. student in the Computer Science and Mathematics department at the Weizmann Institute of Science, under the supervision of Dr. Tali Dekel. Her research is in the intersection of computer vision, computer graphics and deep learning, and mainly focuses on image and video analysis and synthesis using implicit representations.