Computer Vision III: Detection, Segmentation, and Tracking (IN2375)
Course 0000000435 in WS 2022/3
General Data
| Course Type | lecture with integrated exercises |
|---|---|
| Semester Weekly Hours | 4 SWS |
| Organisational Unit | Informatics 9 - Chair of Computer Vision and Artificial Intelligence (Prof. Cremers) |
| Lecturers |
Nikita Araslanov Björn Häfner Simon Weber Responsible/Coordination: Daniel Cremers Assistants: Regine Hartwig Dominik Muhle |
| Dates |
Tue, 16:00–18:00, Interims II 004 Thu, 08:00–10:00, MI HS1 |
Assignment to Modules
-
IN2375: Computer Vision III: Detektion, Segmentierung und Tracking / Computer Vision III: Detection, Segmentation, and Tracking
This module is included in the following catalogs:- Focus Area Imaging in M.Sc. Biomedical Engineering and Medical Physics
Further Information
Courses are together with exams the building blocks for modules. Please keep in mind that information on the contents, learning outcomes and, especially examination conditions are given on the module level only – see section "Assignment to Modules" above.
| additional remarks | - Proposal-based object detection (Faster-RCNN) - One-stage detectors (YOLO, SSD, RetinaNet) - Point-based detection - Instance segmentation (Mask-RCNN) - Semantic segmentation - Panoptic segmentation - Video object segmentation (OSVOS) - Visual object tracking - Multiple object tracking - Graph neural networks for object tracking - 3D object tracking - Trajectory prediction |
|---|---|
| Links |
E-Learning course (e. g. Moodle) TUMonline entry |