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In contrast to existing studies that mainly focus on parsing well-aligned tabular images with simple layouts from scanned PDF documents, we aim to establish a practical table structure parsing system for real-world scenarios where tabular input images are taken or scanned with severe deformation, bending or occlusions. For designing such a system, we propose an approach named Cycle-CenterNet on the top of CenterNet with a novel cycle-pairing module to simultaneously detect and group tabular cells into structured tables. In the cycle-pairing module, a new pairing loss function is proposed for the network training. Alongside with our Cycle-CenterNet, we also present a large-scale dataset, named Wired Table in the Wild (WTW), which includes well-annotated structure parsing of multiple style tables in several scenes like the photo, scanning files, web pages, \\emph{etc.}. In experiments, we demonstrate that our Cycle-CenterNet consistently achieves the best accuracy of table structure parsing on the new WTW dataset by 24.6\\% absolute improvement evaluated by the TEDS metric. A more comprehensive experimental analysis also validates the advantages of our proposed methods for the TSP task.","url_abs":"https://arxiv.org/abs/2109.02199v1","url_pdf":"https://arxiv.org/pdf/2109.02199v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"parsing-table-structures-in-the-wild","repo_url":"https://github.com/wangwen-whu/wtw-dataset","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"NOASSERTION"}},{"paper_slug":"parsing-table-structures-in-the-wild","repo_url":"https://github.com/ArchieAlexArkhipov/Cycle-CenterNet","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"pytorch","reach":{"status":"ok","spdx":"Apache-2.0"}},{"paper_slug":"parsing-table-structures-in-the-wild","repo_url":"https://github.com/cycloneboy/pdf_table","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"object-detection","task_name":"Object Detection"}],"methods":[{"method_slug":"batch-normalization","method_name":"Batch Normalization"},{"method_slug":"cascade-corner-pooling","method_name":"Cascade Corner Pooling"},{"method_slug":"center-pooling","method_name":"Center Pooling"},{"method_slug":"centernet","method_name":"CenterNet"},{"method_slug":"convolution","method_name":"Convolution"},{"method_slug":"cycle-centernet","method_name":"Cycle-CenterNet"},{"method_slug":"dla","method_name":"DLA"}],"datasets_introduced":[{"slug":"wtw","name":"WTW","full_name":"Wired Table in the Wild"}],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=2109.02199","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2109.02199"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. 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