Out of the Box: Reasoning with Graph Convolution Nets for Factual Visual Question Answering

作者: Medhini Narasimhan, Svetlana Lazebnik, Alexander Schwing

摘要

Accurately answering a question about a given image requires combining observations with general knowledge. While this is effortless for humans, reasoning with general knowledge remains an algorithmic challenge. To advance research in this direction a novel

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