Neural Representation and Rendering of 3D Real-world Scenes
High-quality reconstruction and photo-realistic rendering of real-world scenes are two important tasks that have a wide range of applications in AR/VR, movie production, games, and robotics. These tasks are challenging because real-world scenes contain complex phenomena, such as occlusions, motions and interactions. In this talk, I will introduce our recent work that integrates deep learning techniques into the traditional graphics pipeline for modeling humans and static scenes from RGB images. We have shown the advantages of these new neural approaches over the classical computer graphics methods. Finally, I will discuss challenges and opportunities in this area for future work.