Date：2025/7/16 16:00-17:00
Location：R210, CSIE
Speakers：Prof. Jia-Bin Huang（University of Maryland）
Host：莊永裕
Abstract:
Reconstructing and editing visual worlds from images lies at the heart of computer graphics and computer vision. Recent advances—driven by neural rendering and learning-based techniques—have significantly improved the fidelity of 3D reconstruction. However, several challenges remain, especially under extreme lighting variation, complex material properties, and limited observations. In the first part of this talk, I will present our recent work addressing these challenges. We propose novel methods that improve robustness to lighting changes and enable accurate reconstruction in diverse scenarios. In the second part, I will discuss how we can leverage learning-based priors for editing images/videos without explicitly modeling complex visual appearances. Finally, I will conclude with emerging trends and open challenges.
Biography:
Jia-Bin Huang is a Capital One-endowed Associate Professor of Computer Science at the University of Maryland, College Park. Before coming to UMD, Huang was a research scientist at Meta Reality Labs. Before that, he was an Assistant Professor of Electrical and Computer Engineering at Virginia Tech. Huang received his Ph.D. from the University of Illinois, Urbana-Champaign (UIUC) in 2016. His research interests include 3D computer vision, generative models, and computational photography. Huang is the recipient of the Thomas & Margaret Huang Award, NSF CRII award, faculty award from Samsung, Google, 3M, Qualcomm, and a Google Research Scholar Award.