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 WS21-22!

General Course Structure


The course will be held virtually. Lecture slides and videos will be re-used from the summer semester and will be fully available from the beginning. Note that the dates in those lectures are not updated.

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 one or two persons. Each team/project will be aligned with a TA, who will be responsible for the progress check and all project-related questions.

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


Lecture


See lecture links below.

Lecturer: Prof. Dr. Matthias Niessner

ECTS: 8

SWS: 5


Project


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 are expected to present their project with a poster as in top-tier computer vision conferences

Every participant is required to submit a 4-page project report written with the CVPR paper template

Topics:

Presentation dates: TBD

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


Lecture Slides and Recordings



Prerequisites



Forum


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: adl4cv-i28@in.tum.de. 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.


People



Future Semesters


This class will be offered next semester (SS22) as well. Project grades can be transfered.