Corpus ID: 220713216

Few-shot Visual Reasoning with Meta-analogical Contrastive Learning

@article{Kim2020FewshotVR,
  title={Few-shot Visual Reasoning with Meta-analogical Contrastive Learning},
  author={Youngsung Kim and Jinwoo Shin and Eunho Yang and Sung Ju Hwang},
  journal={ArXiv},
  year={2020},
  volume={abs/2007.12020}
}
While humans can solve a visual puzzle that requires logical reasoning by observing only few samples, it would require training over large amount of data for state-of-the-art deep reasoning models to obtain similar performance on the same task. In this work, we propose to solve such a few-shot (or low-shot) visual reasoning problem, by resorting to analogical reasoning, which is a unique human ability to identify structural or relational similarity between two sets. Specifically, given training… Expand

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