Listen to invited talks from some of the pioneers within the field, Paul Debevec and Manmohan Chandraker!
We are very proud to announce that the two main invited speakers at the workshop will be Paul Debevec and Manmohan Chandraker, both having made great contributions to the challenge of measuring and modelling shape and appearance.
Paul Debevec is Senior Staff Engineer at Google VR and Adjunct Research Professor of Computer Science in the Viterbi School of Engineering at the University of Southern California, working within the Vision and Graphics Laboratory at the USC Institute for Creative Technologies. He earned degrees in Math and Computer Engineering at the University of Michigan in 1992 and a Ph.D. in Computer Science from UC Berkeley in 1996. In 1991, he combined techniques from computer vision and computer graphics to create an image-based model of a Chevette automobile from photographs. At Interval Research Corporation he contributed to Michael Naimark’s Immersion ’94 virtual exploration of Banff National forest and collaborated with Golan Levin on the interactive art installation Rouen Revisited.
Manmohan Chandraker received a B.Tech. in Electrical Engineering at the Indian Institute of Technology, Bombay and a PhD in Computer Science at the University of California, San Diego. Following a postdoctoral scholarship at the University of California, Berkeley, he joined NEC Labs America in Cupertino, where he conducts research in computer vision. His principal research interests are sparse and dense 3D reconstruction, including structure-from-motion, 3D scene understanding and dense modeling under complex illumination or material behavior, with applications to autonomous driving, robotics or human-computer interfaces. His work on provably optimal algorithms for structure and motion estimation received the Marr Prize Honorable Mention for Best Paper at ICCV 2007, the 2009 CSE Dissertation Award for Best Thesis at UC San Diego and was a nominee for the 2010 ACM Dissertation Award. His work on shape recovery from motion cues for complex material and illumination received the Best Paper Award at CVPR 2014.