Modern Computer Vision Methods
This seminar course addresses recent methods in the domain of computer vision and their broader impact and application. A list of selected papers is proposed and will be studied and discussed. The advantages and drawback of modern computer vision methods are discussed and put in historic perspective in the field. Application domains include 2D and 3D object detection, image/video/spatial content segmentation, 3D reconstruction, multi-view imaging, sensor fusion, multi-modal imaging, vision for autonomous driving, camera and object pose estimation, SLAM, as well as deformable and rigid registration.
- First Session: Monday, October 17, 2022 at 12.00 in room MI 03.13.010
For the application, please sent us your motivation (+ previous experience / CV / transcript in the field to increase your chances for matching) via e-mail to:
firstname.lastname@example.org (Application Deadline: July 26, 2022)
Please also register in the TUM matching system for the course. Keep in mind that your chances to be assigned to the course increase if you give it a higher rank in your choices. For further details about how the matching system works and its schedule please check this website.
We select appropriate candidates based on their background, interests, and motivation.