BriefGPT.xyz
Dec, 2017
学习正确的行为：从图像预测和解释可供性
Learning to Act Properly: Predicting and Explaining Affordances from Images
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Ching-Yao Chuang, Jiaman Li, Antonio Torralba, Sanja Fidler
TL;DR
本文提出使用图神经网络对场景中的操作、物体可用性进行详细的推理，并解决了在特定环境下不应该采取某些行动以及采取这些行动后可能发生的情况的问题。
Abstract
We address the problem of
affordance reasoning
in diverse scenes that appear in the real world. Affordances relate the agent's actions to their effects when taken on the surrounding objects. In our work, we take the
ego
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