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Computer Vision Group
TUM School of Computation, Information and Technology
Technical University of Munich

Technical University of Munich

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Informatik IX
Computer Vision Group

Boltzmannstrasse 3
85748 Garching info@vision.in.tum.de

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News

04.03.2024

We have twelve papers accepted to CVPR 2024. Check our publication page for more details.

18.07.2023

We have four papers accepted to ICCV 2023. Check out our publication page for more details.

02.03.2023

CVPR 2023

We have six papers accepted to CVPR 2023. Check out our publication page for more details.

15.10.2022

NeurIPS 2022

We have two papers accepted to NeurIPS 2022. Check out our publication page for more details.

15.10.2022

WACV 2023

We have two papers accepted at WACV 2023. Check out our publication page for more details.

More


Practical Course: Learning For Self-Driving Cars and Intelligent Systems (10 ECTS)

Summer Semester 2023, TU München

Correspondence

Please forward any queries related to the lab to: intellisys-ws21.vision.in@tum.de.

Course Registration

Assignment to the lab is done via the matching system. In addition to applying to the matching system please remember to also send in your application documents latest by 14 February 2023.

The preliminary meeting took place on 7 February 2023. The application form can be downloaded here. The slides from the preliminary meeting can be downloaded from here.

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

Course Content

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 visual localization and mapping, control, and semantic understanding. We will also explore the synergy of learning-based methods with classical geometry-based approaches such as visual odometry and 3D reconstruction. Some applications may also involve working on massive datasets including unstructured or unordered data.

Prerequisites
  • 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. For e.g. 1, 2, 3 etc.
  • OR participation in at least one of the lectures / labs covering the basics of Multi-View Geometry. Some example courses include: 1, 2, 3, etc.
  • Other courses with matching content may be considered. Please highlight this in your application.
Structure

Programming tasks will be given in the initial weeks to get the participants up to speed. Afterwards, 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.

Schedule

Time: Tuesdays 11 am - 1 pm
Room: 02.07.014
Format: Hybrid

Rechte Seite

Informatik IX
Computer Vision Group

Boltzmannstrasse 3
85748 Garching info@vision.in.tum.de

Follow us on:

News

04.03.2024

We have twelve papers accepted to CVPR 2024. Check our publication page for more details.

18.07.2023

We have four papers accepted to ICCV 2023. Check out our publication page for more details.

02.03.2023

CVPR 2023

We have six papers accepted to CVPR 2023. Check out our publication page for more details.

15.10.2022

NeurIPS 2022

We have two papers accepted to NeurIPS 2022. Check out our publication page for more details.

15.10.2022

WACV 2023

We have two papers accepted at WACV 2023. Check out our publication page for more details.

More