Wouldn't it be fascinating to be in the same room as Abraham Lincoln, visit Thomas Edison in his laboratory, or step onto the streets of New York a hundred years ago? We explore this thought experiment, by tracing ideas from science fiction through antique stereographs to the latest work in generative adversarial networks (GANs) to step back in time to experience these historical people and places not in black and white, but much closer to how they really appeared. In the process, I'll present our latest work on Keystone Depth, and Time Travel Rephotography.
Bio: Steven M. Seitz (Senior Member, IEEE) received the B.A. degree in computer science and mathematics from the University of California, Berkeley, in 1991 and the Ph.D. degree in computer sciences from the University of Wisconsin, Madison, in 1997.,He is a Professor in the Department of Computer Science and Engineering, University of Washington, Seattle, and also directs an imaging group at Google's Seattle office. Following his doctoral work, he spent one year visiting the Vision Technology Group, Microsoft Research, and subsequently two years as an Assistant Professor in the Robotics Institute, Carnegie Mellon University, Pittsburgh, PA. He joined the faculty at the University of Washington in July 2000. He is interested in problems in computer vision and computer graphics. His current research focuses on 3-D modeling and visualization from large photo collections.,Dr. Seitz was twice awarded the David Marr Prize for the best paper at the International Conference of Computer Vision, and has received a National Science Foundation (NSF) Career Award, an Office of Naval Research (ONR) Young Investigator Award, and an Alfred P. Sloan Fellowship. His work on Photo Tourism (joint with N. Snavely and R. Szeliski) formed the basis of Microsoft's Photosynth technology.