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 driving assistance systems. The ultimate goal of Computer Vision is to imitate the great capabilies of the human visual system, allowing the computer not only to record images but also to interpret them. Research has made significant progress in recent years.
In this seminar we will take a detailed look at the most interesting recent works. For each paper there will be one person, who performs a more detailed investigation of a research paper and its background and 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.

(2 SWS)
Wednesday, 14-16 (hct),
Room: 52-2-17
Contact person: Özgün Cicek

Beginning: Wednesday, October 19, 2016, 14:15
Allocation of seminar topics

ECTS Credits: 4

Recommended semester:

6 (Bachelor), any (Master)
Requirements: Background in computer vision

Remarks: The language in this course is English.

There is a related Blockseminar on Biomedical Image Analysis offered by apl Prof. Olaf Ronneberger from Google DeepMind.

Topics will be assigned for both seminars in the first meeting. Please register for one of the seminars online before the first meeting. If there are more interested students than places, places will be assigned by a mixture of motivation in the first meeting and priority suggestions of the system. The date of registration is NOT important. In particular, we want to avoid that people grab a topic and then jump off during the semester. Please have a coarse look at all available papers to make an informed decision in the first meeting. The listed papers are not yet sorted by the date of presentation.

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.

Slides of first session with instructions for a good presentation
Powerpoint template (optional)


Date   Paper Questions  Presenting student   Slides   Advisor
30.11 Deep network architectures Questions Alexander Thiemann Slides Anton Böhm
14.12 Next frame prediction in video Questions Sebastian Dufner Slides Nima Sedaghat
11.01 Image compression with deep networks Questions Mohammad Fattouh Slides Robert Bensch
18.01 Multi-view reconstruction Questions Pablo de Andres Slides Benjamin Ummenhofer
25.01 Distributed training of deep networks Questions Boris Martinovic Slides Dominic Mai
01.02 Scene reconstruction Questions Alexander Mitrofanov Slides Huizhong Zhou
08.02 Human pose estimation Questions Alexandra Berkel Gabriel Oliveira