Ab 2. November 2020 findet das Herbstsemester 2020 online statt. Ausnahmen: Veranstaltungen, die nur mit Präsenz vor Ort durchführbar sind.
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Suchergebnis: Katalogdaten im Frühjahrssemester 2019

Informatik Master Information
Vertiefungsfächer
Vertiefung in Visual Computing
Seminar in Visual Computing
NummerTitelTypECTSUmfangDozierende
252-5704-00LAdvanced Methods in Computer Graphics Information Belegung eingeschränkt - Details anzeigen
Number of participants limited to 24.

The deadline for deregistering expires at the end of the second week of the semester. Students who are still registered after that date, but do not attend the seminar, will officially fail the seminar.
W2 KP2SM. Gross, O. Sorkine Hornung
KurzbeschreibungThis seminar covers advanced topics in computer graphics with a focus on the latest research results. Topics include modeling, rendering, visualization,
animation, physical simulation, computational photography, and others.
LernzielThe goal is to obtain an in-depth understanding of actual problems and
research topics in the field of computer graphics as well as improve
presentation and critical analysis skills.
263-5904-00LDeep Learning for Computer Vision: Seminal Work Information Belegung eingeschränkt - Details anzeigen
Number of participants limited to 24.

The deadline for deregistering expires at the end of the second week of the semester. Students who are still registered after that date, but do not attend the seminar, will officially fail the seminar.
W2 KP2SZ. Cui
KurzbeschreibungThis seminar covers seminal papers on the topic of deep learning for computer vision. The students will present and discuss the papers and gain an understanding of the most influential research in this area - both past and present.
LernzielThe objectives of this seminar are two-fold. Firstly, the aim is to provide a solid understanding of key contributions to the field of deep learning for vision (including a historical perspective as well as recent work). Secondly, the students will learn to critically read and analyse original research papers and judge their impact, as well as how to give a scientific presentation and lead a discussion on their topic.
InhaltThe seminar will start with introductory lectures to provide (1) a compact overview of challenges and relevant machine learning and deep learning research, and (2) a tutorial on critical analysis and presentation of research papers. Each student then chooses one paper from the provided collection to present during the remainder of the seminar. The students will be supported in the preparation of their presentation by the seminar assistants.
SkriptThe selection of research papers will be presented at the beginning of the semester.
LiteraturThe course "Machine Learning" is recommended.
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