报告人：凌海滨 教授
UC LA
主持人：汤帜 教授
北京大学王选计算机研究所
时 间：2023/6/16 14:00 - 15:00
地 址：燕园校区理科一号楼1131；昌平校区115教室
Tencent Meeting：528-891-953
报告题目：Differentiable Projector-Camera Systems: Algorithm and Applications
报告摘要:
Image-based relighting, projector compensation and depth/normal reconstruction are three important tasks of projector-camera systems (ProCams) and spatial augmented reality (SAR). Although they share a similar pipeline of finding projector-camera image mappings, in tradition, they are addressed independently, sometimes with different prerequisites, devices and sampling images. In practice, this may be cumbersome for SAR applications to address them one-by-one. In this talk, I will introduce a novel end-to-end trainable model named DeProCams to explicitly learn the photometric and geometric mappings of ProCams, and once trained, DeProCams can be applied simultaneously to the three tasks. DeProCams explicitly decomposes the projector-camera image mappings into three subprocesses: shading attributes estimation, rough direct light estimation and photorealistic neural rendering. DeProCams shows clear advantages over previous arts with promising quality and meanwhile being fully differentiable. Moreover, by solving the three tasks in a unified model, DeProCams waives the need for additional optical devices, radiometric calibrations and structured light patterns.
报告人简介:
凌海滨，1997年和2000年于北京大学分别获得学士和硕士学位，2006年在美国马里兰大学获博士学位，2006至2007年在加州大学洛杉矶分校从事博士后研究。2000至2001年任微软亚洲研究院助理研究员，2007至2008年任西门子研究院研究员，2008-2019年任职于美国天普大学（Temple University），2019年加入纽约州立大学计算机系任讲席教授。主要研究领域为计算机视觉、增强现实、医学图像分析和人机交互。获2003年度ACM UIST最佳学生论文奖，2014年度美国自然科学基金CAREER Award，2019年度IEEE VR最佳期刊论文奖。担任期刊IEEE Trans. on Pattern Analysis and Machine Intelligence (PAMI)，IEEE Trans. on Visualization and Computer Graphics (TVCG)，Computer Vision and Image Understanding (CVIU)，和Pattern Recognition的编委，多次担任CVPR、ICCV、ECCV等会议的领域主席。
