Funding providers: Engineering and Physical Sciences Research Council (EPSRC) and Swansea University's Faculty of Science and Engineering
Subject areas: Computer vision, artificial intelligence
Project start date:
- 1 January 2024 (Enrolment open from mid-December)
Project supervisors:
- Dr Lin Wu, Swansea University
- Professor Xianghua Xie, Swansea University
- Hao Chen, Zhejiang University, China
- Professor Mohammed Bennamoun, University of Western Australia, Australia
Aligned programme of study: PhD in Computer Science
Mode of study: Full-time
Project description:
Video instance segmentation aims at simultaneous detection, segmentation and tracking of object instances in videos. Given a test video, the task requires not only the masks of all instances of a predefined category set to be labelled but also the instance identities across frames to be associated. Existing methods follow a detection and association paradigm, which essentially performs spatial priors’ estimation and a temporal stitching afterwards. This may hinder VIS in the occlusion and long-term videos. High-resolution (HR) features appear to be helpful to identify small and or occluded objects in static images. Thus, it is interesting to explore this valuable information that may benefit VIS. At the same time, HR feature fusion at temporal level to facilitate the long-term VIS remains open challenge. This project is motivated to design a latent space where HR features of instances can be properly fused at their temporal evolution. The research results will be also applied to related video-based tasks such as optical flow estimation, 3D reconstruction and 3D object detection.
Eligibility
Candidates must hold an Upper Second Class (2.1) honours degree or an appropriate master’s degree with a minimum overall grade at ‘Merit’ in Computer Science, Mathematics or a closely related discipline. If you are eligible to apply for the scholarship (i.e. a student who is eligible to pay the UK rate of tuition fees) but do not hold a UK degree, you can check our comparison entry requirements. Please note that you may need to provide evidence of your English Language proficiency.
Due to funding restrictions, this scholarship is not open to applications from international students (unless eligible to pay UK tuition fee rates as defined by UKCISA regulations).
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