Computer Vision III offers a comprehensive review of methods for high-level computer vision tasks: object detection, image segmentation and object tracking. These tasks are one of the most compelling applications of computer vision in the real world. Research on these applications is still very active and highly impactful in computer vision. The material of this course spans the recent literature leveraging deep learning, as well as more classical optimisation-based and probabilistic methods.

To attend the course, please register in TUMonline.
Keep in mind that you will have to register for the exam separately later on.

All course material, announcements and the discussion forum will be provided on Moodle.

• Strongly recommended: Introduction to Deep Learning (I2DL) (IN2346)
• Mathematical background: Linear algebra and calculus.
• Knowledge of Python is mandatory.
• Knowledge of PyTorch is highly recommended.

• Youtube Playlist WS 21/22

If you have any questions that may be relevant to other students, please post in the forum on Moodle. For individual inquiries, you can send us an email to cv3-ws24@vision.in.tum.de.

The course material this semester will be heavily based on the previous iterations, which were developed by Prof. Laura Leal-Taixé.