Out of the Box: Reasoning with Graph Convolution Nets for Factual Visual Question Answering
Out of the Box: Reasoning with Graph Convolution Nets for Factual Visual Question Answering
2018
Neural Information Processing Systems · 143 Citations
TLDR
This work develops an entity graph and uses a graph convolutional network to `reason' about the correct answer by jointly considering all entities and shows that this leads to an improvement in accuracy of around 7% compared to the state of the art.