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LEAP aims to develop artificial systems that can analyze and predict dynamic visual patterns using vast amounts of visual data from various sources. By creating new models and methodologies, it seeks to enhance our understanding of visual experiences and improve applications in safety, healthcare, and navigation.
People constantly draw on past visual experiences to anticipate future events and better understand, navigate, and interact with their environment, for example, when seeing an angry dog or a quickly approaching car.
Currently there is no artificial system with a similar level of visual analysis and prediction capabilities. LEAP is a first step in that direction, leveraging the emerging collective visual memory formed by the unprecedented amount of visual data available in public archives, on the…
INSTITUT NATIONAL DE RECHERCHE EN INFORMATIQUE ET AUTOMATIQUE
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