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English(EN) Preserving Cultural Records: A Large-Scale Benchmark and Visual-Prior Routing Network for Ancient Book Image Restoration

新基准和模型应对古籍图像修复挑战

研究人员推出了 AncBench,这是一个大规模基准数据集,包含 100,000 张配对图像,旨在模拟古籍中发现的真实退化情况。该数据集旨在提高图像修复模型的泛化能力,而现有基准使用简化的退化模拟,这限制了其能力。配套的 AncRestore 网络动态集成基于学习到的退化表示的视觉先验,采用专家级和区域级路由策略,以自适应地调整先验贡献,从而优化全局外观和局部文本细节的修复。 AI

影响 这项研究可能通过改进的图像修复技术,更好地保护历史文献。

排序理由 该条目描述了一篇介绍基准数据集和针对特定研究问题的新颖模型的新学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CV 阅读 →

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新基准和模型应对古籍图像修复挑战

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该条目描述了一篇介绍基准数据集和针对特定研究问题的新颖模型的新学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.CV TIER_1 English(EN) · Shumin Fan, Tianyu Song, Hongming Chen, Xiaodong Zhou, Xiang Chen ·

    保护文化遗产:古籍图像修复的大规模基准和视觉先导路由网络

    arXiv:2611.13010v1 Announce Type: new Abstract: Ancient books preserve invaluable cultural heritage, yet their images often suffer from complex degradations caused by long-term ageing, environmental exposure, and physical damage. Existing ancient book image restoration benchmarks…