{"ID":2892628,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2507.15000","arxiv_id":"2507.15000","title":"Axis-Aligned Document Dewarping","abstract":"Document dewarping is crucial for many applications. However, existing learning-based methods rely heavily on supervised regression with annotated data without fully leveraging the inherent geometric properties of physical documents. Our key insight is that a well-dewarped document is defined by its axis-aligned feature lines. This property aligns with the inherent axis-aligned nature of the discrete grid geometry in planar documents. Harnessing this property, we introduce three synergistic contributions: for the training phase, we propose an axis-aligned geometric constraint to enhance document dewarping; for the inference phase, we propose an axis alignment preprocessing strategy to reduce the dewarping difficulty; and for the evaluation phase, we introduce a new metric, Axis-Aligned Distortion (AAD), that not only incorporates geometric meaning and aligns with human visual perception but also demonstrates greater robustness. As a result, our method achieves state-of-the-art performance on multiple existing benchmarks, improving the AAD metric by 18.2% to 34.5%. The code is publicly available at https://github.com/chaoyunwang/AADD.","short_abstract":"Document dewarping is crucial for many applications. However, existing learning-based methods rely heavily on supervised regression with annotated data without fully leveraging the inherent geometric properties of physical documents. Our key insight is that a well-dewarped document is defined by its axis-aligned featur...","url_abs":"https://arxiv.org/abs/2507.15000","url_pdf":"https://arxiv.org/pdf/2507.15000v2","authors":"[\"Chaoyun Wang\",\"I-Chao Shen\",\"Takeo Igarashi\",\"Caigui Jiang\"]","published":"2025-07-20T15:12:57Z","proceeding":"cs.CV","tasks":"[\"cs.CV\"]","methods":"[]","has_code":false,"code_links":[{"ID":612004,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_id":2892628,"paper_url":"https://arxiv.org/abs/2507.15000","paper_title":"Axis-Aligned Document Dewarping","repo_url":"https://github.com/chaoyunwang/AADD","is_official":false,"mentioned_in_paper":false,"mentioned_in_github":true,"github_stars":0}]}