{"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/scale-recurrent-network-for-deep-image","title":"Scale-recurrent Network for Deep Image Deblurring","arxiv_id":"1802.01770","date":"2018-02-06","proceeding":"CVPR 2018 6","authors":["Xin Tao","Hongyun Gao","Yi Wang","Xiaoyong Shen","Jue Wang","Jiaya Jia"],"abstract":"In single image deblurring, the \"coarse-to-fine\" scheme, i.e. gradually\nrestoring the sharp image on different resolutions in a pyramid, is very\nsuccessful in both traditional optimization-based methods and recent\nneural-network-based approaches. In this paper, we investigate this strategy\nand propose a Scale-recurrent Network (SRN-DeblurNet) for this deblurring task.\nCompared with the many recent learning-based approaches in [25], it has a\nsimpler network structure, a smaller number of parameters and is easier to\ntrain. We evaluate our method on large-scale deblurring datasets with complex\nmotion. Results show that our method can produce better quality results than\nstate-of-the-arts, both quantitatively and qualitatively.","url_abs":"http://arxiv.org/abs/1802.01770v1","url_pdf":"http://arxiv.org/pdf/1802.01770v1.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":"scale-recurrent-network-for-deep-image","repo_url":"https://github.com/jiangsutx/SRN-Deblur","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"tf","reach":{"status":"unanswered"}},{"paper_slug":"scale-recurrent-network-for-deep-image","repo_url":"https://github.com/IMAC-projects/Deblurring-PyTorch","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"unanswered"}},{"paper_slug":"scale-recurrent-network-for-deep-image","repo_url":"https://github.com/IMAC-projects/SRN-Deblurring-PyTorch","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"unanswered"}},{"paper_slug":"scale-recurrent-network-for-deep-image","repo_url":"https://github.com/natuan310/scale-recurrent-network-images-deblurring","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"unanswered"}}],"tasks":[{"task_slug":"deblurring","task_name":"Deblurring"},{"task_slug":"image-deblurring","task_name":"Image Deblurring"},{"task_slug":"image-relighting","task_name":"Image Relighting"},{"task_slug":"single-image-deblurring","task_name":"Single Image Deblurring"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/deblurring-on-gopro","task":"Deblurring","dataset":"GoPro","model":"SRN","rank_in_archive_order":56,"of":56,"metrics":{"SSIM":"0.9342"},"uses_additional_data":true},{"leaderboard":"/sota/deblurring-on-hide-trained-on-gopro","task":"Deblurring","dataset":"HIDE (trained on GOPRO)","model":"SRN","rank_in_archive_order":25,"of":26,"metrics":{"PSNR (sRGB)":"28.36","Params (M)":"8.06","SSIM (sRGB)":"0.915"},"uses_additional_data":false},{"leaderboard":"/sota/deblurring-on-rsblur","task":"Deblurring","dataset":"RSBlur","model":"SRN-Deblur","rank_in_archive_order":12,"of":12,"metrics":{"Average PSNR":"32.53"},"uses_additional_data":false},{"leaderboard":"/sota/deblurring-on-realblur-j-1","task":"Deblurring","dataset":"RealBlur-J","model":"SRN","rank_in_archive_order":16,"of":17,"metrics":{"PSNR (sRGB)":"31.38","Params(M)":"8.06","SSIM (sRGB)":"0.909"},"uses_additional_data":false},{"leaderboard":"/sota/deblurring-on-realblur-j-trained-on-gopro","task":"Deblurring","dataset":"RealBlur-J (trained on GoPro)","model":"SRN","rank_in_archive_order":12,"of":15,"metrics":{"PSNR (sRGB)":"28.56"},"uses_additional_data":false},{"leaderboard":"/sota/deblurring-on-realblur-r","task":"Deblurring","dataset":"RealBlur-R","model":"SRN","rank_in_archive_order":15,"of":17,"metrics":{"PSNR (sRGB)":"38.65","Params":"8.06","SSIM (sRGB)":"0.965"},"uses_additional_data":false},{"leaderboard":"/sota/deblurring-on-realblur-r-trained-on-gopro","task":"Deblurring","dataset":"RealBlur-R (trained on GoPro)","model":"SRN","rank_in_archive_order":14,"of":19,"metrics":{"SSIM (sRGB)":"0.947"},"uses_additional_data":false},{"leaderboard":"/sota/image-deblurring-on-gopro","task":"Image Deblurring","dataset":"GoPro","model":"SRN","rank_in_archive_order":55,"of":55,"metrics":{"Params (M)":"8.06","SSIM":"0.9342"},"uses_additional_data":true},{"leaderboard":"/sota/image-relighting-on-vidit20-validation-set","task":"Image Relighting","dataset":"VIDIT’20 validation set","model":"SRN","rank_in_archive_order":5,"of":5,"metrics":{"LPIPS":"0.4319","MPS":"0.5670","PSNR":"16.94","Runtime(s)":"0.87","SSIM":"0.5660"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1802.01770","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}