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This paper investigates the potential of integrating visual object states for developing methods addressing complex visual intelligence tasks such as Long-Term Action anticipation (LTAA) and proposes that this to achieve this with the aid of a Neurosymbolic (NeSy) framework. We consider that this approach could offer significant advancements in applications requiring nuanced understanding and anticipation of future scenarios and could serve as an inspiration for the further development of Nesy methods exhibiting Visual Intelligence.

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Enabling Visual Intelligence by Leveraging Visual Object States in a Neurosymbolic Framework

  • 会议论文

  • 发表日期：

    2025年

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  • Filippos Gouidis,
  • Konstantinos Papoutsakis,
  • Theodore Patkos,
  • Antonis Argyros,
  • Dimitris Plexousakis

摘要

This paper investigates the potential of integrating visual object states for developing methods addressing complex visual intelligence tasks such as Long-Term Action anticipation (LTAA) and proposes that this to achieve this with the aid of a Neurosymbolic (NeSy) framework. We consider that this approach could offer significant advancements in applications requiring nuanced understanding and anticipation of future scenarios and could serve as an inspiration for the further development of Nesy methods exhibiting Visual Intelligence.