{"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/shadowformer-global-context-helps-image","title":"ShadowFormer: Global Context Helps Image Shadow Removal","arxiv_id":"2302.01650","date":"2023-02-03","proceeding":null,"authors":["Lanqing Guo","Siyu Huang","Ding Liu","Hao Cheng","Bihan Wen"],"abstract":"Recent deep learning methods have achieved promising results in image shadow removal. However, most of the existing approaches focus on working locally within shadow and non-shadow regions, resulting in severe artifacts around the shadow boundaries as well as inconsistent illumination between shadow and non-shadow regions. It is still challenging for the deep shadow removal model to exploit the global contextual correlation between shadow and non-shadow regions. In this work, we first propose a Retinex-based shadow model, from which we derive a novel transformer-based network, dubbed ShandowFormer, to exploit non-shadow regions to help shadow region restoration. A multi-scale channel attention framework is employed to hierarchically capture the global information. Based on that, we propose a Shadow-Interaction Module (SIM) with Shadow-Interaction Attention (SIA) in the bottleneck stage to effectively model the context correlation between shadow and non-shadow regions. We conduct extensive experiments on three popular public datasets, including ISTD, ISTD+, and SRD, to evaluate the proposed method. Our method achieves state-of-the-art performance by using up to 150X fewer model parameters.","url_abs":"https://arxiv.org/abs/2302.01650v1","url_pdf":"https://arxiv.org/pdf/2302.01650v1.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":"shadowformer-global-context-helps-image","repo_url":"https://github.com/guolanqing/shadowformer","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"shadowformer-global-context-helps-image","repo_url":"https://github.com/BlackJoke76/OmniSR","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"image-shadow-removal","task_name":"Image Shadow Removal"},{"task_slug":"shadow-removal","task_name":"Shadow Removal"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/shadow-removal-on-istd","task":"Shadow Removal","dataset":"ISTD","model":"ShadowFormer","rank_in_archive_order":1,"of":10,"metrics":{"MAE":"4.79"},"uses_additional_data":false},{"leaderboard":"/sota/shadow-removal-on-istd-1","task":"Shadow Removal","dataset":"ISTD+","model":"ShadowFormer (AAAI 2023) (512x512)","rank_in_archive_order":7,"of":26,"metrics":{"LPIPS":"0.204","PSNR":"28.07","RMSE":"3.06","SSIM":"0.847"},"uses_additional_data":false},{"leaderboard":"/sota/shadow-removal-on-istd-1","task":"Shadow Removal","dataset":"ISTD+","model":"ShadowFormer (AAAI 2023) (256x256)","rank_in_archive_order":20,"of":26,"metrics":{"LPIPS":"0.35","PSNR":"26.55","RMSE":"3.45","SSIM":"0.728"},"uses_additional_data":false},{"leaderboard":"/sota/shadow-removal-on-srd","task":"Shadow Removal","dataset":"SRD","model":"ShadowFormer (AAAI 2023) (512x512)","rank_in_archive_order":5,"of":25,"metrics":{"LPIPS":"0.228","PSNR":"25.6","RMSE":"3.9","SSIM":"0.819"},"uses_additional_data":false},{"leaderboard":"/sota/shadow-removal-on-srd","task":"Shadow Removal","dataset":"SRD","model":"ShadowFormer (AAAI 2023) (256x256)","rank_in_archive_order":16,"of":25,"metrics":{"LPIPS":"0.348","PSNR":"24.28","RMSE":"4.44","SSIM":"0.715"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2302.01650","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}