Website
http://dataportal.arc.gov.au/NCGP/API/grants/DE240100967
Funding Status
Active
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Funded Activity Summary
Open-world computer vision by detecting and tracking hierarchical objects. This project examines the problem of detecting and tracking objects using computer vision. A fundamental limitation of current algorithms is that they require labelled training data for every object class and therefore cannot be trusted to operate in unconstrained environments. This project aims to address this limitation using novel techniques that incorporate hierarchical relationships between object classes. Expected outcomes include new paradigms for algorithm design and evaluation, and establishing the problem as a focus of international research. The key practical benefit would be to accelerate the wider deployment of visual perception in applications such as autonomous vehicles, interactive robotics, and video analysis.Funded Activity Details
Start Date: 2024
End Date: 12-2026
Funding Scheme: Discovery Early Career Researcher Award
Funding Amount: $366,000.00
Funder: Australian Research Council
Research Topics
ANZSRC Field of Research (FoR)
Deep learning | Computer vision | Computer vision and multimedia computation |
ANZSRC Socio-Economic Objective (SEO)
