Abstract
Human digitalization is required in many applications, such as AR/VR, robotics, games, and social networking. The course covers core techniques and fundamental tools necessary for perceiving and modeling humans. The main topics include human body modeling, human appearance and motion modeling, and human-scene interaction capture and modeling.
Objectives
After attending this course, students will be able to implement basic systems to estimate human pose, shape, and motion from videos; furthermore, students will be able to create basic human avatars from various visual inputs.
Content
We will focus on all aspects of 3D human capture, modelling, and synthesis, including
⁃ Basic concept of 3D representations
⁃ Human body models;
⁃ Human motion capture;
⁃ Non-rigid surface tracking and reconstruction;
⁃ Neural rendering
Lecture Notes
Slides
Literature
Computer Vision: Algorithms and applications by Richard Szeliski.
Deep Learning: by Goodfellow, Bengio, and Courville
Prerequisites
This is an advanced lecture for learning to model and synthesize 3D humans. We assume you have basic knowledge of computer vision, deep learning, and computer graphics; a solid understanding of linear algebra, probability, and calculus.
The following courses are highly recommended as a prerequisite
visual computing, computer vision, and deep learning.
Administration
Number | 263-5906-00L |
---|---|
Lecturer | Prof. Dr. Siyu Tang |
Assistants | Dr. Yan Zhang (Head TA) Dr. Sergey Prokudin Qianli Ma Shaofei Wang |
Location | Tuesday, CAB G 51 |
Moodle Link | https://moodle-app2.let.ethz.ch/course/view.php?id=17072 Lecture recordings and slides will be available on moodle |
ECTS Credits | 5 |
Exam | Graded semester performance |
Schedule
Week | Date (14-16pm) | Topic |
---|---|---|
01 | 22-Feb | Introduction |
02 | 1-Mar | Body models |
03 | 8-Mar | Individual discussion with TAs and supervisers |
04 | 15-Mar | Project presentation |
05 | 22-Mar | Hand models |
06 | 29-Mar | Human pose estimation |
07 | 5-Apr | Rendering |
08 | 12-Apr | Neural Rendering |
10 | 26-Apr | Project presentation |
11 | 3-May | Neural body models |
12 | 10-May | Non-rigid surface tracking |
13 | 17-May | Motion capture and motion matching |
14 | 24-May | Motion modeling |
15 | 31-May | Project final presentation 1 |
Week | Date (14pm-15pm) | Topic |
---|---|---|
01 | 24-Feb | Project overview |
02 | 3-Mar | no tutorial |
03 | 10-Mar | SMPL Tutorial |
04 | 17-Mar | no tutorial |
05 | 24-Mar | paper presentation |
06 | 31-Mar | paper presentation |
07 | 7-Apr | paper presentation |
08 | 14-Apr | paper presentation |
10 | 28-Apr | paper presentation |
11 | 5-May | paper presentation |
12 | 12-May | paper presentation |
13 | 19-May | paper presentation |
14 | 26-May | paper presentation |
15 | 2-Jun | Project final presentation 2 |