OK-VQA: A Visual Question Answering Benchmark Requiring External Knowledge

@article{Marino2019OKVQAAV,
  title={OK-VQA: A Visual Question Answering Benchmark Requiring External Knowledge},
  author={Kenneth Marino and Mohammad Rastegari and Ali Farhadi and Roozbeh Mottaghi},
  journal={2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2019},
  pages={3190-3199}
}
Visual Question Answering (VQA) in its ideal form lets us study reasoning in the joint space of vision and language and serves as a proxy for the AI task of scene understanding. [] Key Result Our analysis shows that our knowledge-based VQA task is diverse, difficult, and large compared to previous knowledge-based VQA datasets. We hope that this dataset enables researchers to open up new avenues for research in this domain.

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