ABSTRACT
Reconstructing depth and motion of every pixel for arbitrary scenes is a core problem in 3D vision with many downstream applications. In this talk, I will describe some of our recent efforts toward this goal, including various strategies to obtain effective training data for single-image 3D reconstruction, and new neural architectures that advance the state of the art of multiview 3D reconstruction.

PRESENTER
Jia Deng
Jia Deng is an Assistant Professor of Computer Science at Princeton University. His research focuses on computer vision and machine learning. He is a recipient of the Sloan Research Fellowship, the NSF CAREER award, the ONR Young Investigator award, an ICCV Marr Prize, a CVPR test-of-time award, a 3DV Best Student Paper Award, and two ECCV Best Paper Awards.