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Many object classes are primarily defined by their functions. However, this fact has been left largely unexploited by visual object categorization or detection systems. The authors propose a method to learn an affordance detector. It identifies locations in the 3D space which "Support" the particular function. Their novel approach "Imagines" an actor performing an action typical for the target object class, instead of relying purely on the visual object appearance. So, function is handled as a cue complementary to appearance, rather than being a consideration after appearance-based detection.
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