{"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/compression-artifacts-removal-using","title":"Compression Artifacts Removal Using Convolutional Neural Networks","arxiv_id":"1605.00366","date":"2016-05-02","proceeding":null,"authors":["Pavel Svoboda","Michal Hradis","David Barina","Pavel Zemcik"],"abstract":"This paper shows that it is possible to train large and deep convolutional\nneural networks (CNN) for JPEG compression artifacts reduction, and that such\nnetworks can provide significantly better reconstruction quality compared to\npreviously used smaller networks as well as to any other state-of-the-art\nmethods. We were able to train networks with 8 layers in a single step and in\nrelatively short time by combining residual learning, skip architecture, and\nsymmetric weight initialization. We provide further insights into convolution\nnetworks for JPEG artifact reduction by evaluating three different objectives,\ngeneralization with respect to training dataset size, and generalization with\nrespect to JPEG quality level.","url_abs":"http://arxiv.org/abs/1605.00366v1","url_pdf":"http://arxiv.org/pdf/1605.00366v1.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":"compression-artifacts-removal-using","repo_url":"https://github.com/ShakedDovrat/JpegArtifactRemoval","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1605.00366","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}