CORDIS Project
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The SEED project aims to enhance computer vision by developing methods that allow systems to learn to recognize and predict objects and actions in dynamic scenes with minimal training. It focuses on semantic segmentation of video data to improve understanding of both indoor and outdoor environments.
The goal of SEED is to fundamentally advance the methodology of computer vision by exploiting a dynamic analysis perspective in order to acquire accurate, yet tractable models, that can automatically learn to sense our visual world,
localize still and animate objects (e.g. chairs, phones, computers, bicycles or cars, people and animals), actions and interactions, as well as qualitative geometrical and physical scene properties, by propagating and consolidating temporal
information, with minimal…
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