About the Project
This project aims at understanding the human context of paintings, drawings and cartoon, which are also known as non-photorealistic imagery, with advanced computer vision algorithms.
Deep learning based computer vision has enabled computers to analyze images and recognize their content. In this project, you will research on state-of-the-art deep learning algorithms to empower computers understanding non-photorealistic imagery such as painting, drawings and cartoon. Artworks that consists of human beings are of particular interest, as they usually come with heavier context delivered through the humans’ postures and the facial expressions. As artworks may come with different styles and the drawn humans may not closely resemble the real-world ones, you will research on algorithms to transfer the success of real-world images based human identification/posture recognition/expression identification algorithms into the domain of artistic-styles images. This can facilitate a large-scale, data-driven analysis of artworks for a better understanding of art trend and history.
Related past research from our team includes:
- High-Speed Multi-Person Pose Estimation with Deep Feature Transfer, Computer Vision and Image Understanding http://hubertshum.com/pbl_cviu2020pose.htm
- Makeup Style Transfer on Low-quality Images with Weighted Multi-scale Attention, Proceedings of the 2020 International Conference on Pattern Recognition http://hubertshum.com/pbl_icpr2020makeup.htm
- A Two-Stream Recurrent Network for Skeleton-Based Human Interaction Recognition, Proceedings of the 2020 International Conference on Pattern Recognition http://hubertshum.com/pbl_icpr2020interaction.htm
As a PhD student, you will be supervised by Dr Hubert Shum (http://hubertshum.com/), who is an Associate Professor in Computer Science at Durham University. He has published over 100 research papers in the fields of computer vision, computer graphics, motion analysis and machine learning. He has led funded research projects awarded by the UK Research Council, the Ministry of Defence and the Royal Society. This has facilitated him to supervised 23 PhDs and 6 Post-doctoral Researchers. Engaging both the academic and the industry, he hosted international conferences such as BMVC and the ACM SIGGRAPH Conference on MIG, as well as served as an Associate Editor of CGF and a Guest Editor of IJCV.
During the PhD study, you will receive comprehensive training and research coaching through regular one-to-one meetings with Dr Shum. Such interactive and tailored support can develop your strength and consolidate your research knowledge. Furthermore, Dr Shum’s research team has a supportive culture with team members from all over the world, which provides assistance and collaboration opportunities to each other. These have facilitated his past PhDs to publish their research in prestige journals (e.g. IEEE TIP, IEEE TVCG and IEEE TMM) and to develop their successful career.
The position is based in Durham University, which is ranked the 4th in the UK by the Guardian and top 100 in the world by QS Top Universities. As a member of the elite Russell Group, Durham University focuses on research excellence delivered by world-class academics. It is located at Durham in North East England, which is one of the safest cities in the UK with an affordable living cost. The Department of Computer Science is one of the fastest-growing departments in the University, supported by major investments in staff recruitment and a £40m new academic building. 83% of its research outputs are considered as “world-leading” and “internationally excellent” by the UK Research Excellence Framework.
- A research interest in computer vision and machine learning
- Knowledge in any modern programming languages
- A relevant undergraduate or master degree with good scores
- Good English https://www.dur.ac.uk/learningandteaching.handbook/1/3/3/1/
How to Apply
Formal applications should be done via https://www.dur.ac.uk/computer.science/postgraduate/research/
Why not add a message here
Based on your current searches we recommend the following search filters.
Based on your current search criteria we thought you might be interested in these.