Ce Zheng
Ph.D. candidate at Center for Research in Computer Vision
University of Central Florida
Monday, December 11
3:30 pm to 4:30 pm
Newell-Simon Hall 3305
3:30 pm to 4:30 pm
Newell-Simon Hall 3305
Reconstructing 3D Humans from Visual Data
Abstract: Abstract: Understanding humans in visual content is fundamental for numerous computer vision applications. Extensive research has been conducted in the field of human pose estimation (HPE) to accurately locate joints and construct body representations from images and videos. Expanding on HPE, human mesh recovery (HMR) addresses the more complex task of estimating the 3D pose and shape of the entire human body. HPE and HMR have gained significant attention due to their applications in areas such as digital human avatar modeling, AI coaching, and virtual reality. Despite the progress made so far, HPE and HMR come with notable challenges. The research community continues to strive for robust, accurate, and efficient solutions for HPE and HMR. This talk introduce the achievements from video-based HPE to image and video-based HMR during my Ph.D. journey. It tackles various challenges and outline the potential future research directions in the domains of HPE and HMR.
Bio: Ce Zheng is a Ph.D. candidate at Center for Research in Computer Vision (CRCV) of University of Central Florida (UCF), advised by Prof. Chen Chen. Before joining UCF, he obtained his Master’s degree at Tufts University in Aug 2019, working with Prof. Shuchin Aeron and Prof. Eric Miller. He received my Bachelor’s Degree at University of Bridgeport in June 2016. He have a broad interest in deep learning and computer vision, currently focus on Human Pose Estimation (HPE) and Human Mesh Recovery (HMR). His work has been published at major AI conferences including CVPR, ICCV, NeurIPS, IJCAI, and ACM MM. Since his first publication in 2020, his works on HPE and HMR have garnered over 600 citations. He has served as a reviewer for CVPR, ICCV, ICLR, NeurIPS, SIGGRAPH Asia, TIP, and TPAMI.
Homepage: Ce Zheng (zczcwh.github.io)
Sponsored in part by: Meta Reality Labs Pittsburgh