This course will be held in English only

Selected Topics in 3D Shape Analysis

Summer 2023

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.

Contact

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Isaak Lim

Class Information

Language
Credits

 

 

English
5 ECTS for B.Sc.
4 ECTS for B.Sc. (PO 2022)
4 ECTS for M.Sc.

Fields Of Study

  • Computer Science (B.Sc.)
  • Computer Science (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

Grading

The grade will be calculated as follows:

  • Written Paper: 50%
  • Presentation & Participation: 50%

Attendance Policy

To pass the course, you need to attend all presentations.

Submission Milestones

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“).

Dates

Kickoff Meeting:

  • 4.4.2023 (12:15) @ room 118 (E3)

Topic Deadline:

  • 5.4.2023 (12:00)

Outline Deadline:

  • 19.4.2023 (12:00)

Presentations:

  • 16.5.2023 & 17.5.2022 @ room 118 (E3)

Report Deadline:

  • 14.6.2023 (12:00)

Revised Report Deadline:

  • 12.7.2023 (12:00)

For further details see the RWTHmoodle.

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