{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/detecting-overlapping-objects-in-x-ray","title":"Detecting Overlapping Objects in X-ray Security Imagery by a Label-aware Mechanism","arxiv_id":null,"date":"2022-02-28","proceeding":"IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY 2022 2","authors":["C Zhao","L Zhu","S Dou","W Deng","L Wang"],"abstract":"One of the key challenges to the X-ray security check is to detect the overlapped items in backpacks or suitcases in the X-ray images. Most existing methods improve the robustness of models to the object overlapping problem by enhancing the underlying visual information such as colors and edges. However, this strategy ignores the situations in which the objects have similar visual clues as to the background, and objects overlapping each other. Since the two cases rarely appear in existing datasets, we contribute a novel dataset – Cutters and Liquid Containers X-ray Dataset (CLCXray) to complete the related research.","url_abs":"http://shuguang-52.github.io/clcxray","url_pdf":"https://shuguang-52.github.io/papers/22tifs_clcxray.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":"detecting-overlapping-objects-in-x-ray","repo_url":"https://github.com/greysonphoenix/clcxray","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null},{"paper_slug":"detecting-overlapping-objects-in-x-ray","repo_url":"https://github.com/Vill-Lab/2022-TIFS-CLCXray","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"2d-object-detection","task_name":"2D Object Detection"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/2d-object-detection-on-clcxray","task":"2D Object Detection","dataset":"CLCXray","model":"LACLS","rank_in_archive_order":1,"of":1,"metrics":{"Detection: Full (mAP@0.5)":"59.3"},"uses_additional_data":false}],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}