{"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/class-rectification-hard-mining-for","title":"Class Rectification Hard Mining for Imbalanced Deep Learning","arxiv_id":"1712.03162","date":"2017-12-08","proceeding":"ICCV 2017 10","authors":["Qi Dong","Shaogang Gong","Xiatian Zhu"],"abstract":"Recognising detailed facial or clothing attributes in images of people is a\nchallenging task for computer vision, especially when the training data are\nboth in very large scale and extremely imbalanced among different attribute\nclasses. To address this problem, we formulate a novel scheme for batch\nincremental hard sample mining of minority attribute classes from imbalanced\nlarge scale training data. We develop an end-to-end deep learning framework\ncapable of avoiding the dominant effect of majority classes by discovering\nsparsely sampled boundaries of minority classes. This is made possible by\nintroducing a Class Rectification Loss (CRL) regularising algorithm. We\ndemonstrate the advantages and scalability of CRL over existing\nstate-of-the-art attribute recognition and imbalanced data learning models on\ntwo large scale imbalanced benchmark datasets, the CelebA facial attribute\ndataset and the X-Domain clothing attribute dataset.","url_abs":"http://arxiv.org/abs/1712.03162v1","url_pdf":"http://arxiv.org/pdf/1712.03162v1.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":"class-rectification-hard-mining-for","repo_url":"https://github.com/JoyLuo/face-attribute-recognition-paper-list","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}}],"tasks":[{"task_slug":"attribute","task_name":"Attribute"},{"task_slug":"deep-learning","task_name":"Deep Learning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1712.03162","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}