Basic Information
I work on developing robust and efficient algorithms for the analysis, synthesis and prediction of complex 3D real-world phenomena. My current research interests are centered around capturing and photorealistic rendering of 3D scenes, and I am especially interested in the area that combines classic computer graphics with modern deep learning approaches.
Social
Publications
ResFields: Residual Neural Fields for Spatiotemporal Signals
Conference: International Conference on Learning Representations (ICLR 2024) spotlight presentation
Authors:Marko Mihajlovic, Sergey Prokudin, Marc Pollefeys, Siyu Tang
ResField layers incorporates time-dependent weights into MLPs to effectively represent complex temporal signals.
Authors:Sergey Prokudin, Qianli Ma, Maxime Raafat, Julien Valentin, Siyu Tang
We propose to model dynamic surfaces with a point-based model, where the motion of a point over time is represented by an implicit deformation field. Working directly with points (rather than SDFs) allows us to easily incorporate various well-known deformation constraints, e.g. as-isometric-as-possible. We showcase the usefulness of this approach for creating animatable avatars in complex clothing.
Authors:Korrawe Karunratanakul, Sergey Prokudin, Otmar Hilliges, Siyu Tang
We present HARP (HAnd Reconstruction and Personalization), a personalized hand avatar creation approach that takes a short monocular RGB video of a human hand as input and reconstructs a faithful hand avatar exhibiting a high-fidelity appearance and geometry.