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CLEVR

The CLEVR dataset is a diagnostic dataset for compositional language and elementary visual reasoning, designed to help researchers evaluate and develop models that can understand and answer questions about complex visual scenes.

Updated 1/16/2020
github

Description

CLEVR Dataset Overview

Dataset Description

  • Name: CLEVR Dataset
  • Purpose: Diagnostic for compositional language and elementary visual reasoning
  • Origin: Proposed by Justin Johnson, Bharath Hariharan, Laurens van der Maaten, Fei‑Fei Li, C Lawrence Zitnick, Ross Girshick at CVPR 2017

Dataset Generation

  • Image Generation: Images rendered with Blender; a JSON file containing scene information for each image is provided.
  • Question Generation: Questions, functional programs, and answers are generated from the scene information; a JSON file containing all questions is provided.

Dataset Content Examples

  • Image Examples: Several synthetic images such as images/img1.pngimages/img6.png.
  • Question & Answer Examples:
    • Q: How many small spheres are there?
    • A: 2
    • Q: How many cubes are small objects or red metallic objects?
    • A: 2
    • Q: Do the metal sphere and the metal cylinder share the same color?
    • A: Yes
    • Q: Are there more small cylinders than metal objects?
    • A: No
    • Q: Is there a shiny cube to the right of the blue ball behind the large yellow object?
    • A: Yes

Citation

@inproceedings{johnson2017clevr,
  title={CLEVR: A Diagnostic Dataset for Compositional Language and Elementary Visual Reasoning},
  author={Johnson, Justin and Hariharan, Bharath and van der Maaten, Laurens
          and Fei‑Fei, Li and Zitnick, C Lawrence and Girshick, Ross},
  booktitle={CVPR},
  year={2017}
}

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Topics

Visual Reasoning
Natural Language Processing

Source

Organization: github

Created: 5/22/2019

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