Functionality Discovery and Prediction of Physical Objects


  • Lei Ji UCAS
  • Botian Shi BIT
  • Xianglin Guo BIT
  • Xilin Chen UCAS



Functionality is a fundamental attribute of an object which indicates the capability to be used to perform specific actions. It is critical to empower robots the functionality knowledge in discovering appropriate objects for a task e.g. cut cake using knife. Existing research works have focused on understanding object functionality through human-object-interaction from extensively annotated image or video data and are hard to scale up. In this paper, we (1) mine object-functionality knowledge through pattern-based and model-based methods from text, (2) introduce a novel task on physical object-functionality prediction, which consumes an image and an action query to predict whether the object in the image can perform the action, and (3) propose a method to leverage the mined functionality knowledge for the new task. Our experimental results show the effectiveness of our methods.




How to Cite

Ji, L., Shi, B., Guo, X., & Chen, X. (2020). Functionality Discovery and Prediction of Physical Objects. Proceedings of the AAAI Conference on Artificial Intelligence, 34(01), 123-130.



AAAI Technical Track: AI and the Web