Reasoning about Object Affordances in a Knowledge Base Representation

  title={Reasoning about Object Affordances in a Knowledge Base Representation},
  author={Yuke Zhu and Alireza Fathi and Li Fei-Fei},
Reasoning about objects and their affordances is a fundamental problem for visual intelligence. Most of the previous work casts this problem as a classification task where separate classifiers are trained to label objects, recognize attributes, or assign affordances. In this work, we consider the problem of object affordance reasoning using a knowledge base representation. Diverse information of objects are first harvested from images and other meta-data sources. We then learn a knowledge base… CONTINUE READING
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