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README.md
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---
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license: cc-by-4.0
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task_categories:
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- image-to-text
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language:
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- en
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---
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# Dataset Card for CompreCap
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### Dataset Description
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The CompreCap benchmark is characterized by human-annotated scene graph and focuses on the evaluation of comprehensive image captioning.
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It provides new semantic segmentation annotations for common objects in images, with an average mask coverage of 95.83%.
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Beyond the careful annotation of objects, CompreCap also includes high-quality descriptions of the attributes bound to the objects, as well as directional relational descriptions between the objects, composing a complete and directed scene graph structure.
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Based on the CompreCap benchmark, researchers can comprehensively accessing the quality of image captions generated by large vision-language models.
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### Licensing Information
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We distribute the image under a standard Creative Common CC-BY-4.0 license. The individual images are under their own copyrights.
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## Citation
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BibTeX:
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```bibtex
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@article{CompreCap,
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title={Benchmarking Large Vision-Language Models via Directed Scene Graph for Comprehensive Image Captioning},
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author={Fan Lu, Wei Wu, Kecheng Zheng, Shuailei Ma, Biao Gong, Jiawei Liu, Wei Zhai, Yang Cao, Yujun Shen, Zheng-Jun Zha},
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booktitle={arXiv},
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year={2024}
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}
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```
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