Dima Damen

University of Bristol, Institut de la Vision

Papers

Total Citations

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About

Dima Damen is a leading researcher in computer vision and cognitive robotics, with a focus on enabling machines to learn and interact with the world efficiently. Her work spans object recognition, 3D detection, and robot learning from passive video. A key contribution is her 2019 paper on "Learning Discriminative Embeddings for Object Recognition on-the-fly" (11 citations), which tackles the challenge of recognizing new objects without costly fine-tuning—a breakthrough for real-time, scalable AI systems. Earlier, her 2011 work on "Detecting and Localising Multiple 3D Objects" (5 citations) introduced a fast, scalable framework for detecting texture-minimal objects in cluttered environments, advancing robotic perception. Most recently, her 2024 paper "Rank2Reward: Learning Shaped Reward Functions from Passive Video" (4 citations) pioneers a method to teach robots novel skills using action-free video, reducing the burden of human demonstrations. Damen also contributed to the 2015 survey "Cognitive Robotics Systems" (3 citations), synthesizing progress in the field. Her work is highly cited and influential, bridging vision and robotics to create adaptable, autonomous systems.