报告摘要：Recent advances on deep learning, in particular, neural modeling and rendering, have renewed interests on developing effective 3D imaging solutions. Such techniques aim to overcome the limitations of traditional 3D reconstruction techniques such as structure-from-motion (SfM) and photometric stereo (PS) by reducing reconstruction noise, tackling texture-less regions, and synthesizing high quality free-view rendering. In this talk, I present recent efforts from my group at ShanghaiTech in collaboration with DGene on neural modeling techniques. Specifically, I demonstrate our latest neural human body reconstructor, deep 3D face synthesizer, anatomically correct 3D hand tracker, and ultra-realistic hair modeler. These solutions can produce dynamic virtual humans at an unprecedented visual quality as well as lead to profound changes to MetaVerse creation technologies. Finally I discuss extensions of these LOS oriented techniques to NLOS imaging systems.
报告人简介：虞晶怡教授于2000年获美国加州理工学院（Caltech）双学士学位，2005年获美国麻省理工学院（MIT）博士学位。现任上海科技大学副教务长、信息科学与技术学院教授、执行院长，是上海人工智能咨询委员会委员、叠境数字创始人。虞教授长期从事计算机视觉、计算成像、计算机图形学、生物信息学等领域的研究工作，已发表140多篇学术论文, 其中超90篇发表于国际会议CVPR/ICCV/ECCV和期刊TPAMI，已获得20多项PCT发明专利授权。虞教授是美国国家科学基金杰出青年奖（NSF CAREER Award）获得者。他曾组织多个计算机视觉大会，担任IEEE TPAMI、IEEE TIP等多个顶级期刊编委。虞教授担任ICCP 2016、ICPR 2020、WACV 2021以及人工智能顶会IEEE CVPR 2021和ICCV 2025的程序主席。由于他在计算机视觉领域的贡献，他入选IEEE Fellow。