Pre-recorded Sessions: From 4 December 2020 | Live Sessions: 10 – 13 December 2020
4 – 13 December 2020
MotioNet: 3D Human Motion Reconstruction from Monocular Video with Skeleton Consistency
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Ultimate Supporter
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Ultimate Attendee
Date/Time:
04 – 13 December 2020
All presentations are available in the virtual platform on-demand.
Lecturer(s):
Mingyi Shi, Shandong University, China
Kfir Aberman, Tel Aviv University, Beijing Film Academy, Israel
Andreas Aristidou, University of Cyprus, Interdisciplinary Center Herzliya Efi Arazi School of Computer Science, Cyprus
Taku Komura, University of Edinburgh, United Kingdom
Dani Lischinski, Tel Aviv The Hebrew University of Jerusalem, Israel
Daniel Cohen-Or, Tel Aviv University, Israel
Baoquan Chen, Peking University, China
Bio:
Description: MotioNet is a deep neural network that reconstructs a kinematic skeleton from monocular video, and directly outputs the complete, commonly used, motion representation in character animation.