Advanced Deep Learning for Computer Vision: Visual Computing (ADL4CV) (IN2390)

Advanced Deep Learning for Computer Vision: Visual Computing (ADL4CV) (IN2390)

Welcome to the Advanced Deep Learning for Computer Vision course offered in summer semester 2023!

General Course Structure

The lecture will be held virtually. Lecture slides and videos will be published on this website. Some lectures are already available, more will appear during the semester. For the meantime, we keep the lecture slides and recordings from the previous semesters on the website as well, as a reference.

In addition, the class will feature practical projects. At the end of this course, all students are expected to deliver complete projects as teams of two persons. Each team/project will be aligned with a TA, who will be responsible for all project-related questions.

We will cover the class structure and planning in more detail in the first lecture at the beginning of the course.


See lecture links below.

Lecturer: Prof. Dr. Matthias Niessner


SWS: 5


In order to secure the steady progress of each project, we will schedule two presentations during the semester. The current project status and/or preliminary results are required in the presentation.

In addition to the regular presentations, we will also arrange a final poster presentation at the end of the course, where every team is expected to present their project with a poster as in top-tier computer vision conferences

Every team is required to submit a 4-page project report written with the CVPR paper template (Use the file PaperForReview.tex).


Presentation dates: TBD

Teaching Assistants: Dave Zhenyu Chen , Yinyu Nie, David Rozenberszki, and Barbara Roessle

Lecture Slides and Recordings

Previous Slides and Recodings



We will use Moodle for announcements, discussions and course-related information.

Contact us

If you have any questions regarding the organization of the course, do not hesitate to contact us at: Please refrain from using the personal email addresses.

For questions on the syllabus, exercises or any other questions on the content of the lecture, we will use the forum discussion board.


Future Semesters

This class will be offered next semester (SS23) as well. Project grades can be transfered.