Summer Semester 2024, TU München

Organisers: Viktoria Ehm, Maolin Gao

2024-04-30: We've updated the presentation schedule on 16.05 and 23.05.2024.

2024-04-18: Our weekly seminar will take place on Thursdays between 12:00-14:00 both at room 00.08.036 and via zoom (link will be sent via mail). The first seminar will take place next week on the 25.04.2024. Looking forward to see you all!

2024-03-28: The topics have been assigned. Please contact your supervisor for your first meeting. If you haven't been assigned to a topic yet, please send us an email.

2024-01-17: The preliminary meeting will take place at 10:00 - 11:00 on 08.02.2024 online via Zoom (Zoom Link: https://tum-conf.zoom-x.de/j/68400268885?pwd=L0ZQL2YrdFc4b0t1SnladHdKOUV1dz09). The slides will be published afterwards. You are encouraged to participate and ask questions directly in the meeting, since it will positively affect the matching process. Please find the zoom link in TUMonline.

2024-04-05: The full presentation schedule has been published. Please reach out to your supervision for presentation preparation.

3D Shape Matching problems are ubiquitous in computer vision, graphics and related fields. Such problems can appear in many different contexts, e.g. shape correspondences, object tracking, 3D reconstruction and interpolation etc., which highlights their high relevance. In this seminar, we will review the classic and recent advances in 3D shape matching, both optimisation-based and machine-learning-based approaches. Students will read a list of selected research papers, and each student will deeply study the problem setting and methods described in one existing paper under our supervision, and report the final outcome in terms of open presentations followed with a Q&A session and reports. There will be no additional written or oral exam.

After attending the seminar, we expect the participants should have a good overview of current approaches to tackle 3D shape matching problems, and a deeper understanding about one particular method, which should lay a good foundation of future hands-on research projects.

All participants should have a solid working knowledge of linear algebra and calculus. In addition, it is useful (but not required), that students have a background in at least one of the following topics: continuous/discrete optimisation, 3D geometry, computer vision, image processing, or computer graphics.

Slides can be found here .