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CLEVR-DC

CLEVR-DC dataset used for paper:

Viewpoint-Agnostic Change Captioning with Cycle Consistency <br /> Hoeseong Kim, Jongseok Kim, Hyungseok Lee, Hyunsung Park, Gunhee Kim <br /> To appear at ICCV 2021

Reference

If you find this repository useful, please cite the following paper:

@inproceedings{kim2021viewpoint,
  title={Viewpoint-Agnostic Change Captioning with Cycle Consistency},
  author={Kim, Hoeseong and Kim, Jongseok and Lee, Hyungseok and Park, Hyunsung
          and Kim, Gunhee}
  booktitle={ICCV},
  year={2021}
}

Introduction

CLEVR-DC is a CLEVR dataset for change captioning under drastic viewpoint changes. In contrast to other datasets with relatively small camera jitters, we reposition the camera to a random location in the after image. For the after scene, we perform one of the following:

• Change the color of one of the objects
• Change the texture (material) of one of the objects
• Add a random object
• Remove a random object
• Move a random object
• Do nothing (distractor)

We generate 8,000 images for each action. The split we used is included in split.json.

Examples