Https://arxiv.org/pd F/1606.05433.pdf

1606.05433.pdf
Preview of https://arxiv.org/pd f/1606.05433.pdf
🔗 Source: arxiv.org
📊 Size: 3.88 MB
📄 Pages: 16 pages
⬇️ Downloads: 59

Summary

Researchers introduce FVQA, a Visual Question Answering (VQA) dataset that requires external information to answer questions, supporting deeper reasoning and common sense. FVQA contains image-question-answer triplets with additional supporting facts, represented as structural triplets. The dataset is designed to evaluate a vision system's capacity for deeper image understanding, going beyond direct analysis of the question and image. The authors propose a novel model that can reason about an image based on supporting facts and evaluate its performance on the FVQA dataset.

Description

Researchers introduce FVQA, a Visual Question Answering (VQA) dataset that requires external information to answer questions, supporting deeper reasoning and...

Technical Information

  • File Format: PDF
  • File Size: 3.88 MB
  • Pages: 16
  • Language: EN
  • Total Downloads: 59
  • Last Updated: 3 weeks ago

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