Seminar on Current Works in Computer Vision

Prof. Thomas Brox

Computer Vision is a very active research field with many practical applications, for instance in quality control, robotics, or driver assistance systems. The goal of Computer Vision is to imitate the flexibility and robustness of the human visual system. Research has made significant progress in recent years particularly due to deep learning. Almost all research in Computer Vision has shifted to deep learning based methods.
In this seminar we have cherry-picked mostly papers from the last ICCV conference. For each paper there will be one person, who performs a more detailed investigation of a research paper and its background and who will give a presentation. The presentation is followed by a discussion with all participants about the merits and limitations of the respective paper. You will learn to read and understand contemporary research papers, to give a good oral presentation, to ask questions, and to openly discuss a research problem.

This seminar will happen in presence only.

Seminar: (2 SWS) Wednesday, 14:00, building 52, room 02-17 Contact person: Silvio Galesso Beginning: If you want to participate, register in HisInOne for the course, attend the introduction meeting on October 18 14:15, and send an email with your name and your paper priorities (S1-S9, favorite paper first) to Silvio Galesso before October 23. Recommended semester: 6 (Bachelor), any (Master) Requirements: Background in computer vision Remarks: The language in this course is English. There is a strongly related Blockseminar on Deep Learning offered by apl Prof. Olaf Ronneberger from Google DeepMind. The introduction meeting will be jointly for both seminars. Students, who did not attend the introduction meeting on Oct. 18, cannot participate in the seminar. For all students, who attended the introduction meeting, seat assignment will be done centrally via HisInOne via the provided priorities. For all students with an assigned seat, we will assign topics by preference. We want to avoid that people grab a topic and then jump off during the semester. Thus, please have a coarse look at all available papers to make an informed decision before you commit. The listed papers are not yet sorted by the date of presentation. If you don't attend the meeting (or not send a paper preference) but choose this seminar together with only other overbooked seminars in HisInOne, you may end up without a seminar place this semester. Students who just need to attend (failed SL from previous semester), need not send a preference for a paper, but just reply with "SL only". All participants must read all papers and answer a few questions. The questions will be available in the 'Questions' column of the table below at least one week before the corresponding presentation. The answers must be sent to the advisor of the paper before the paper is presented. All participants must attend all sessions.

---

Material:

Seminar organization
Giving a good presentation
Proper scientific behavior

Slides of the introductory lecture
Powerpoint template for your presentation (optional)

Papers:

Date	Paper	Questions	Presenting student	Slides	Advisor
6.12	Diffusion with Forward Models	questions	Emmanuel Hofmann		Adam Kortylewski
13.12	Tracking	questions	Tobias Buerger		Max Argus
20.12	Unsupervised learning	questions	Marta Gulida		Silvio Galesso
10.1	Compositionality	questions	Zacharias Haeringer		Simon Schrodi
17.1	Feature accentuation	questions	Kathapet Nawongs		Sudhanshu Mittal
24.1	Segment anything	questions	Simon Baermann		Jelena Bratulic
31.1	ControlNet	questions	Simon Blauth		Leonhard Sommer
7.2	Concept discovery	questions	Elias Kempf		Simon Schrodi