Higher Level Computer Vision
Contents
In this course, we teach the fundamentals of Computer Vision.
Time and Location
- Lecture: Tuesday, 12:00 to 13:30, B6, A2.03, Start: 10.9.2024
- Exercise: Thursday, 13:45 to 15:15, A5, C0.12, Start: 12.09.2024
Instructor
Final mark
- Exam (oral)
Participation
- The course is open to students of the Master Business Informatics and Mannheim Master in Data Science (MMDS).
- The course is restricted to 30 participants.
- Places are assigned on first come/
first serve basis. - Students register for the course by email to me (keuper@uni...).
Requirements
- Basics in linear algebra are beneficial for the lecture
Outline
Week
Lecture Exercise
09.10.2023 Intro and Organization -- 16.10.2023 Basics of Image Processing Ex1 – Image Processing 23.10.2023 Object Identification – Toy Case Ex2 – Object Identification 30.10.2023 DNNs Ex3 – Image Classification 06.11.2023 CNNs Ex4 13.11.2023 CNNs additional Lecture and Discussion Session (maybe remote, tbd.)
Vision Transfomers (short Intro)
20.11.2023 Object Detection Ex5 27.11.2023 Segmentation & Optical Flow additional remote Lecture and Discussion Session
Semi-Supervised Learning
04.12.2023 Self-Supervised Pre-Training Q & A Literature
- R. Szeliski: Computer Vision Algorithms and Applications, Springer, 2010. ISBN: 978-1-84882-934-3. (Online available: http://szeliski.org/Book/)
- I. Goodfellow et al.: Deep Learning, MIT Press, 2016. (Online: www.deeplearningbook.org)