Registration for this course is open until Friday, 29.11.2024 23:59.

News

First session on Oct 16

Written on 14.10.24 by Thomas Leimkühler

Our first session will be on Wednesday, Oct 16, at 2 PM in lecture hall 003, building E1.3. In this session, we will cover the course logistics and provide an overview of the content discussed in the subsequent lectures.

Advanced Topics in Neural Rendering and Reconstruction

 

Course Description

Neural rendering and reconstruction form the foundation of digitizing the physical world, with applications in virtual/augmented reality (VR/AR), film production, robotics, and beyond. This course explores advanced topics in this space, emphasizing data-driven approaches using neural models. After reviewing the basics of computer graphics and machine learning, we will delve into 3D scene representation and reconstruction using differentiable rendering, generative models, morphable models, human reconstruction and synthesis, and quantum visual computing.

 

Schedule and other details

Course webpage: https://vcai.mpi-inf.mpg.de/teaching/vcai_lecture_WS2425/

Format: 1 lecture per week, in-person attendance

Time: Wednesdays, 14:15-15:45

Location: Lecture hall 003 in E1 3

Credit Points: 3 CP

Exam: Written exam

 

Prerequisites

The course is tailored towards 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 Image Processing and Computer Vision and Computer Graphics 1, or something equivalent.

 

Course Content

Topics Date
Introduction and Overview 16.10.
Computer Graphics Basics 23.10.
Deep Learning for Visual Computing 30.10.
Generative Models 06.11.
3D Scene Representations 13.11.
Differentiable Rendering 20.11.
Neural Scene Reconstruction 27.11.
3D Generative Models 04.12.
Morphable Models for Geometry and Appearance 11.12.
Human Reconstruction 08.01.
Motion Reconstruction and Synthesis 15.01.
Quantum Visual Computing, Part 1 22.01.
Quantum Visual Computing, Part 2 29.01.
Revision 05.02.

 

 

 

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