Zhaoyang Lv
Research Scientist,
Facebook Reality Labs Research
Previous Education:
Ph.D. in Robotics, School of Interactive Computing, Georgia Institute of Technology
M.Sc., Artificial Intelligence in Computing, Imperial College London
B.Sc., Electrical Engineering in Aeronauntics, Northwestern Polytechnical University
I finished my Ph.D. at Georgia Tech, jointly advised by Prof. James Rehg, and
Prof. Frank Dellaert. During my Ph.D., I am also fortunate to intern at Nvidia Research in the group of
Jan Kautz and at Max Planck Institute with
Prof. Andreas Geiger. Before I started my Ph.D., I finished my Master thesis under the supervision
of Prof. Andrew Davison at Imperial College
London.
I am a believer that VR/AR will become ubiquitous and fundamentally change the way we interact with world. Quote Steve Jobs' comments on GUI when he visited Xerox PARC in 1979:
I am excited to do the computer vision research in this field and push it forward.
My current research interest is to explore a fully end-to-end dynamic scene representation by rethinking from camera sensing and image formation system to the virtual rendered novel view video. My PhD thesis research focus was to explore fast, accurate approaches for dense 3D motion from visual signals in unconstrained environments.
I am a believer that VR/AR will become ubiquitous and fundamentally change the way we interact with world. Quote Steve Jobs' comments on GUI when he visited Xerox PARC in 1979:
You could argue about the number of years it would take, and you could argue about who would be the winners and the losers, but I don't think you could argue that every computer in the world wouldn't eventually work this way.
I am excited to do the computer vision research in this field and push it forward.
My current research interest is to explore a fully end-to-end dynamic scene representation by rethinking from camera sensing and image formation system to the virtual rendered novel view video. My PhD thesis research focus was to explore fast, accurate approaches for dense 3D motion from visual signals in unconstrained environments.
