Registration for this course is open until Wednesday, 08.11.2023 23:59.


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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:


Schedule and other details:

Course webpage:

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



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


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