Organizers: Qadeer Khan, Prof. Dr. Daniel Cremers

Please forward any queries related to the lab to: intellisys-ss21.vision.in@tum.de

Assignment to the lab is done via the matching system. Please additionally send your application documents to the correspondence email. The preliminary meeting took place online on 5 February 2021, 12pm. The preliminary meeting slides can be found here

In addition to applying to the matching system please remember to also send in your application documents latest by 16 February.

Note that the course goes by the name Lernbasierte Ansätze für autonome Fahrzeuge und intelligente Systeme on the matching system

Learning-based approaches have recently made tremendous progress in the computer vision and robotics research community. In this practical course, we will solve challenging real-world problems in the area of self-driving cars and intelligent systems. Topics will be in the direction of perception, control, and environmental understanding. This may also involve working on massive datasets including unstructured or unordered data.

• Good knowledge of the Python language and basic mathematics such as linear algebra, analysis, probability and numerics etc. is required.
• Good knowledge of a deep learning framework such as PyTorch, TensorFlow, etc.
• Participation in at least one of the offered deep learning lectures at TUM is required.

Students will work in groups of max. 2 persons on research oriented projects. To review progress and assist with resolving any issues, students are invited to meet the supervisors on a weekly basis.

Time: Mondays 10-12pm
Room: [TBD, most likely online]