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School of Computing · ANU College of Systems and Society
The goal of Computer Vision is to enable the computer or AI agent to ‘see’ and ‘understand’ the world like if not better than human beings. To that end, the computer needs to use sensors such as RGB or depth sensors to interact with the world. It mainly includes the understanding of the environment (scene understanding), humans, and further interaction with humans. Mapping to specific computer vision problems, this course will cover advanced topics in computer vision, such as 1) Scene Understanding, 2)Graphical Models, 3)3D visual perception , 4) Human Analysis and modeling. This course will review current research literature in the above fields and update students with state-of-the-art techniques. Students will work on group projects related to concrete research problems and present their research results in the form of seminars.
Literature Reading Reports
Learning outcomes 1, 2, 5
Research/Design Project
Learning outcomes 2, 3
Seminar Presentation
Learning outcomes 3, 4, 5
A total of 130 hours including lectures, tutorials and self-study
Not required. Preliminary Reading The reading list includes the most recent following conference proceedings for computer vision and machine learning, which are: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) International Conference on Computer Vision (ICCV) European Conference on Computer Vision (ECCV) Advances in Neural Information Processing Systems (NIPS) International Conference on Learning Representations (ICLR)