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The Solution for the ICCV 2023 1st Scientific Figure Captioning Challenge
March 27, 2024, 4:45 a.m. | Dian Chao, Xin Song, Shupeng Zhong, Boyuan Wang, Xiangyu Wu, Chen Zhu, Yang Yang
cs.CV updates on arXiv.org arxiv.org
Abstract: In this paper, we propose a solution for improving the quality of captions generated for figures in papers. We adopt the approach of summarizing the textual content in the paper to generate image captions. Throughout our study, we encounter discrepancies in the OCR information provided in the official dataset. To rectify this, we employ the PaddleOCR toolkit to extract OCR information from all images. Moreover, we observe that certain textual content in the official paper …
abstract arxiv captioning captions challenge cs.ai cs.cv figure generate generated iccv image improving information ocr paper papers quality scientific solution study summarizing textual type
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