This course will be held in English only
Selected Topics in 3D Shape Analysis
In this seminar, we will cover topics from Shape Analysis (i.e. the extraction of more abstract information from a collection of 3D shapes). More concretely, the topics include the analysis of single shapes, how to map between pairs of shapes and a range of possible shape representations (with their individual benefits and disadvantages) for expressive machine learning techniques such as neural networks in order to analyze whole collections of shapes.
5 ECTS for B.Sc.
4 ECTS für B.Sc. (PO 2022)
4 ECTS für M.Sc.
Fields Of Study
- Informatik (B.Sc.)
- Informatik (M.Sc.)
- Media Informatics (M.Sc.)
- Software Systems Engineering (M.Sc.)
- Data Science (M.Sc.)
- Technical Communication (B.Sc.)
- Technical Communication (M.Sc.)
- Master Erasmus
The grade will be calculated as follows:
- Written Paper: 50%
- Presentation & Participation: 50%
To pass the course, you need to attend all presentations.
All submissions have to be sent to the supervisor until 12:00 (noon) via mail. Include the tag [PDUI] and the name of the topic and the milestone (e.g., „[Seminar] Explainable AI, Report Outline“).
- 4.4.2023 (12:15) @ room 118 (E3)
- 5.4.2023 (12:00)
- 19.4.2023 (12:00)
- 16.5.2023 & 17.5.2022 @ room 118 (E3)
- 14.6.2023 (12:00)
Revised Report Deadline:
- 12.7.2023 (12:00)
For further details see the RWTHmoodle.