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| Main Authors: | , , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2508.00834 |
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| _version_ | 1866911087870345216 |
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| author | Wu, Wei Wang, Wenjie Tan, Yang Liu, Ying Diao, Liang Huang, Lin Xu, Kaihe Xie, Wenfeng Lin, Ziling |
| author_facet | Wu, Wei Wang, Wenjie Tan, Yang Liu, Ying Diao, Liang Huang, Lin Xu, Kaihe Xie, Wenfeng Lin, Ziling |
| contents | This report presents Team PA-VGG's solution for the ICDAR'25 Competition on Understanding Chinese College Entrance Exam Papers. In addition to leveraging high-resolution image processing and a multi-image end-to-end input strategy to address the challenges of dense OCR extraction and complex document layouts in Gaokao papers, our approach introduces domain-specific post-training strategies. Experimental results demonstrate that our post-training approach achieves the most outstanding performance, securing first place with an accuracy rate of 89.6%. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_00834 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Team PA-VCG's Solution for Competition on Understanding Chinese College Entrance Exam Papers in ICDAR'25 Wu, Wei Wang, Wenjie Tan, Yang Liu, Ying Diao, Liang Huang, Lin Xu, Kaihe Xie, Wenfeng Lin, Ziling Computer Vision and Pattern Recognition This report presents Team PA-VGG's solution for the ICDAR'25 Competition on Understanding Chinese College Entrance Exam Papers. In addition to leveraging high-resolution image processing and a multi-image end-to-end input strategy to address the challenges of dense OCR extraction and complex document layouts in Gaokao papers, our approach introduces domain-specific post-training strategies. Experimental results demonstrate that our post-training approach achieves the most outstanding performance, securing first place with an accuracy rate of 89.6%. |
| title | Team PA-VCG's Solution for Competition on Understanding Chinese College Entrance Exam Papers in ICDAR'25 |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2508.00834 |