3D Computer Vision

Anpei Chen (PostDoc)

We plan to design cutting-edge algorithms to enable fast and generalizable 3D reconstruction, novel view synthesis, and 3D-aware image synthesis by combining advances in computer vision and computer graphics. This project includes three main parts: (1) Geometric modeling and reconstruction are fundamental to computer vision and graphics. The classical point graph geometric modeling and feature matching-based reconstruction methods have long served as the workhorse of 3D digital applications. (2) Realistic appearance rendering. Reconstructing spatial-varying reflectance or radiance field in public spaces has increased dramatically in recent years. Our focus is to develop lightweight, fast and generalizable solutions by coupling inverse physical-based rendering with new computer vision algorithms. (3) Controllable image synthesis conditioning on labels, for instance, 2D semantic segmentation map, text, camera poses, geometric, material, and lighting parameters, etc.

Primary Host:	Andreas Geiger (University of Tübingen & Max Planck Institute for Intelligent Systems)
Exchange Host:	Siyu Tang (ETH Zürich)
PostDoc Duration:	15 August 2022 - 31 May 2025
Exchange Duration:	01 June 2023 - 31 May 2025 - Ongoing