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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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+
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+ # Dataset Card for CompreCap
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+
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+
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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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+
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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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+
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+
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+ ## Citation
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+
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+
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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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+ ```