{"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/self-adaptively-learning-to-demoire-from","title":"Self-Adaptively Learning to Demoire from Focused and Defocused Image Pairs","arxiv_id":"2011.02055","date":"2020-11-03","proceeding":null,"authors":["Lin Liu","Shanxin Yuan","Jianzhuang Liu","Liping Bao","Gregory Slabaugh","Qi Tian"],"abstract":"Moire artifacts are common in digital photography, resulting from the interference between high-frequency scene content and the color filter array of the camera. Existing deep learning-based demoireing methods trained on large scale datasets are limited in handling various complex moire patterns, and mainly focus on demoireing of photos taken of digital displays. Moreover, obtaining moire-free ground-truth in natural scenes is difficult but needed for training. In this paper, we propose a self-adaptive learning method for demoireing a high-frequency image, with the help of an additional defocused moire-free blur image. Given an image degraded with moire artifacts and a moire-free blur image, our network predicts a moire-free clean image and a blur kernel with a self-adaptive strategy that does not require an explicit training stage, instead performing test-time adaptation. Our model has two sub-networks and works iteratively. During each iteration, one sub-network takes the moire image as input, removing moire patterns and restoring image details, and the other sub-network estimates the blur kernel from the blur image. The two sub-networks are jointly optimized. Extensive experiments demonstrate that our method outperforms state-of-the-art methods and can produce high-quality demoired results. It can generalize well to the task of removing moire artifacts caused by display screens. In addition, we build a new moire dataset, including images with screen and texture moire artifacts. As far as we know, this is the first dataset with real texture moire patterns.","url_abs":"https://arxiv.org/abs/2011.02055v2","url_pdf":"https://arxiv.org/pdf/2011.02055v2.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":"self-adaptively-learning-to-demoire-from","repo_url":"https://github.com/baolp/demoireing_with_focused_and_defocused_images_pairs","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":null,"task_name":"Demoire"},{"task_slug":"test-time-adaptation","task_name":"Test-time Adaptation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=2011.02055","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2011.02055"}},"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. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/baolp/demoireing_with_focused_and_defocused_images_pairs","reach":null}],"summary":{"unverified":5},"by_repo_kind":{"listed":{"samples":5,"ran":0,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":5,"samples":[{"code_sha256_prefix":"5d583ab6be8f447d","entry":"ListModule","repo":"baolp/demoireing_with_focused_and_defocused_images_pairs","repo_kind":"listed","path":"models/unet.py","file_url":"https://github.com/baolp/demoireing_with_focused_and_defocused_images_pairs/blob/HEAD/models/unet.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"5d583ab6be8f447d"}},{"code_sha256_prefix":"3c4a8073d576856e","entry":"UNet","repo":"baolp/demoireing_with_focused_and_defocused_images_pairs","repo_kind":"listed","path":"models/unet.py","file_url":"https://github.com/baolp/demoireing_with_focused_and_defocused_images_pairs/blob/HEAD/models/unet.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"3c4a8073d576856e"}},{"code_sha256_prefix":"3244d74e888d4915","entry":"unetConv2","repo":"baolp/demoireing_with_focused_and_defocused_images_pairs","repo_kind":"listed","path":"models/unet.py","file_url":"https://github.com/baolp/demoireing_with_focused_and_defocused_images_pairs/blob/HEAD/models/unet.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"3244d74e888d4915"}},{"code_sha256_prefix":"3f9d0ca5da480a02","entry":"unetDown","repo":"baolp/demoireing_with_focused_and_defocused_images_pairs","repo_kind":"listed","path":"models/unet.py","file_url":"https://github.com/baolp/demoireing_with_focused_and_defocused_images_pairs/blob/HEAD/models/unet.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"3f9d0ca5da480a02"}},{"code_sha256_prefix":"d9b991a9561f5be4","entry":"unetUp","repo":"baolp/demoireing_with_focused_and_defocused_images_pairs","repo_kind":"listed","path":"models/unet.py","file_url":"https://github.com/baolp/demoireing_with_focused_and_defocused_images_pairs/blob/HEAD/models/unet.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"d9b991a9561f5be4"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}