Workshop and Challenge on
Perceptual Image Restoration
and Manipulation

Alexei A. Efros is a professor at EECS Department at UC Berkeley, where he is part of the Berkeley Artificial Intelligence Research Lab (BAIR). Before that, he spent nine years on the faculty of the Robotics Institute at CMU. He did his post-doc with Andrew Zisserman at Oxford. Starting in 2007, he have also been closely collaborating with Team WILLOW at École Normale Supérieure / INRIA in Paris. The central goal of his research is to use vast amounts of visual data to understand, model, and recreate the visual world around us. His research has been mainly in data-driven computer vision, as well as its projection onto computer graphics and computational photography. Other interests include human vision, unsupervised learning, visual data mining, robotics, and the applications of computer vision to the visual arts and the humanities. For a high-level overview of his research, see a recent Heidelberg Forum talk on "Self-Supervised Visual Learning and Synthesis".

Eli Shechtman is a Principal Scientist at the Creative Intelligence Lab at Adobe Research. He received the B.Sc. degree in Electrical Engineering (magna cum laude) from Tel-Aviv University in 1996. Between 2001 and 2007 he attended the Weizmann Institute of Science where he received with honors his M.Sc. and Ph.D. degrees in Applied Mathematics and Computer Science. In 2007 he joined Adobe and started sharing his time as a post-doc with the University of Washington in Seattle. He published over 60 academic publications and holds over 20 issued patents. He served as a Technical Paper Committee member at SIGGRAPH 2013 and 2014, as an Area Chair at CVPR’15, ICCV’15 and CVPR’17 and serves an Associate Editor at TPAMI. He received several honors and awards, including the Best Paper prize at ECCV 2002, a Best Poster Award at CVPR 2004, a Best Reviewer Award at ECCV 2014, published two Research Highlights papers in the Communication of the ACM journal and recently he awarded the Hemholtz Prize at ICCV’17.

Tomer Michaeli is an Assistant Professor at the EE faculty at the Technion -- Israel Institute of Technology. He completed his B.Sc. (summa cum laude) and Ph.D degrees at the EE faculty at the Technion in 2005 and 2012, respectively. From 2012 to 2015 he was a postdoctoral fellow at the CS and Applied Math Department at the Weizmann Institute Science. In 2015 he joined the Technion as a faculty member. His research lies in the fields of Signal and Image Processing, Computer Vision, Graphics, and Machine Learning. In particular, he studies statistical and machine-learning techniques for signal recovery problems (noise removal, blur removal, resolution enhancement), feature extraction and visualization, and analyzes fundamental tradeoffs and limitations in those domains. He won several awards, including the Alon Fellowship, the Konigsberg Award for Excellence in Teaching, and the Hershel Rich Technion Innovation Award.