Light traveling in the 3D world interacts with the scene through intricate processes before being captured by a camera. These processes result in the dazzling effects like colour and shading, complex surface and material appearance, different weathering, just to name a few. Physics based vision aims to invert the processes to recover the scene properties, such as shape, reflectance, light distribution, medium properties, etc., from the images by modelling and analyzing the imaging process to extract desired features or information. When physics based vision meets deep learning, there will be mutual benefits. On one hand, classic physics based vision tasks can be implemented in a data-fashion way to handle complex scenes. On the other hand, high-level vision task can also be benefitted by awareness of the physics principles.
22/07/2024
Where: Aula T1, via regina elena 295, Dipartimento di Informatica
Dr. Shaodi You is an Assistant Professor (with Tenure) at University of Amsterdam (UvA), Netherlands. He receives his Ph.D. and M.E. degrees from The University of Tokyo, Japan in 2015 and 2012 and his bachelor’s degree from Tsinghua University, P. R. China in 2009. His research interests are physics based vision and deep learning. He serves as area chair of CVPR, Neurips and ECCV. He is the primary organizer of 1st-4th Workshop on Physics Based Vision meets Deep Learning with CVPR and ICCV. He is an associate editor of IJCV.