About

My research strives to find a bridge between prior knowledge and deep networks. Deep learning in computer vision thrives under examples but commonly ignores additional explicit knowledge about the research problem. Think about hierarchical relations between categories, relational knowledge between tasks, or spatio-temporal knowledge. The research of me and my team focuses on discovering the shared geometry between pixels and knowledge. Specifically, we research hyperbolic and hyperspherical geometry for deep learning and learning with prototypes. Advances in these research directions are investigated on various computer vision problems, including but not limited to hierarchical recognition, search, localisation, and zero-shot recognition in images and videos.

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2022

2021

2020

2019