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Self-supervised Learning of 3D Facial Reconstruction from Videos
The Hong Kong University of Science and Technology Department of Computer Science and Engineering Final Year Thesis Oral Defense Title: "Self-supervised Learning of 3D Facial Reconstruction from Videos" by LIU Zichen Abstract: 3D facial reconstruction is the task of getting the 3D facial model of a human. It has been an extensively studied topic in the computer vision and graphics community and has many applications in VR/AR telepresence and games. However, annotated 3D labeled facial data is expensive to get. As a result, some unsupervised methods that do not rely on labeled data have been proposed for 3D facial reconstruction. Recently, methods that can create animatable personal facial avatars have drawn much attention and shown promising results in readily available settings (e.g., from monocular videos or portrait photo sequences). The goal of this final year thesis is creating personalized facial avatars under fine-grained control over expression while approaching photorealism and acquiring accurate facial geometry. Date : 2 May 2023 (Tuesday) Time : 10:00 - 10:40 Venue : Room 2406 (near lifts 17/18), HKUST Advisor : Dr. XU Dan 2nd Reader : Dr. WANG Shuai