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Advanced Topics in Neural Rendering and Reconstruction
Course Description
Neural rendering and reconstruction is the cornerstone of digitizing our world, with several applications in VR/AR, movie and media production, robotics, and many more. The digitization pipeline usually consists of three main stages; data capture, 3D model building, and finally, reconstruction and rendering/synthesis. This course will cover advanced topics in this digitization pipeline, with a focus on data-driven approaches using neural-based formulations. We will cover 3D scene representations, including explicit approaches as well as the more recent learnable implicit-based approaches. We will discuss how to build 3D morphable models for important objects such as the human face and body. We will also cover approaches for both 2D and 3D neural rendering. While the vast majority of the topics will focus on using data captured by RGB cameras, we will also discuss other means of capturing data using advanced sensors such as IMUs and event cameras. Finally, we will discuss quantum visual computing and the impact it can bring to the field. For more information, please check out the course webpage: https://vcai.mpi-inf.mpg.de/teaching/vcai_lecture_WS2324/index.html
Schedule and other details:
Course webpage: https://vcai.mpi-inf.mpg.de/teaching/vcai_lecture_WS2324/index.html
Format: 1 lecture per week. Only in person attendance
Time: Wednesdays from 14:00-16:00
Location: Lecture hall 003 in E1 3
Credit Points: 3 CP
Prerequisites:
The course is more tailored towards the students of Visual Computing (M.Sc.), Computer Science (M.Sc.) and Data Science and Artificial Intelligence (M.Sc.).
It is preferred, but not necessarily required, that students have already studied IPCV and Computer Graphics 1, or something equivalent.
Course Content
| Topics | Date |
|---|---|
| Introduction and Overview | 25.10 |
| Computer Graphics Basics | 08.11 |
| Deep Learning for Visual Computing | 15.11 |
| 2D Generative Models | 22.11 |
| 3D Scene Representations and Transformations | 29.11 |
| Parametric Scene Representations for Geometry and Appearance | 06.12 |
| Conditional 2D Neural Rendering | 20.12 |
| Inverse Graphics 1 | 10.01 |
| Inverse Graphics 2 | 17.01 |
| 3D Neural Representations and Rendering | 24.01 |
| 3D Sensing beyond RGB Cameras | 31.01 |
| Quantum Visual Computing | 07.02 |
| Open Lecture and Recap (Optional) | TBD |