Final Examination of Ce Zheng for the degree of Doctor of Philosophy in Computer Science
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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. However, HPE and HMR come with notable challenges. Despite the progress made so far, the research community continues to strive for robust, accurate, and efficient solutions in HPE and HMR, advancing us closer to the ultimate goals in the field. This dissertation tackles various challenges in the domains of HPE and HMR. Our initial focus is on video-based HPE. Next, we address the heavy computational and memory burden associated with image-based and video-based HMR. These achievements provide practical and efficient solutions for real-world applications in HPE and HMR.
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