{"type":"ScholarlyArticle","title":"Weakening the Influence of Clothing: Universal Clothing Attribute Disentanglement for Person Re-Identification","authors":[{"name":"Yuming Yan","slug":"yuming-yan","given":"Yuming","family":"Yan","affiliation":"College of Information Science and Electronic Engineering , Zhejiang University; ZJU-League Research & Development Center"},{"name":"Huimin Yu","slug":"huimin-yu","given":"Huimin","family":"Yu","affiliation":"College of Information Science and Electronic Engineering , Zhejiang University; ZJU-League Research & Development Center; State Key Lab of CAD&CG , Zhejiang University; Zhejiang Provincial Key Laboratory of Information Processing, Communication and Networking"},{"name":"Shuzhao Li","slug":"shuzhao-li","given":"Shuzhao","family":"Li","affiliation":"College of Information Science and Electronic Engineering , Zhejiang University; ZJU-League Research & Development Center"},{"name":"Zhaohui Lu","slug":"zhaohui-lu","given":"Zhaohui","family":"Lu","affiliation":"College of Information Science and Electronic Engineering , Zhejiang University; ZJU-League Research & Development Center; Zhejiang Lijia Electronic Technology Company Ltd. {12231016 , yhm2005 , 11631045 ,"},{"name":"Jianfeng He","slug":"jianfeng-he","given":"Jianfeng","family":"He","affiliation":"College of Information Science and Electronic Engineering , Zhejiang University"},{"name":"Haozhuo Zhang","slug":"haozhuo-zhang","given":"Haozhuo","family":"Zhang","affiliation":"College of Information Science and Electronic Engineering , Zhejiang University; ZJU-League Research & Development Center"},{"name":"Runfa Wang","slug":"runfa-wang","given":"Runfa","family":"Wang","affiliation":"College of Information Science and Electronic Engineering , Zhejiang University; ZJU-League Research & Development Center"}],"abstract":"Most existing Re-ID studies focus on the short-term cloth-consistent setting and thus dominate by the visual appearance of clothing. However, the same person would wear different clothes and different people would wear the same clothes in reality, which invalidates these methods. To tackle the challenge of clothes change, we propose a Universal Clothing Attribute Disentanglement network (UCAD) which can effectively weaken the influence of clothing (identity-unrelated) and force the model to learn identity-related features that are unrelated to the worn clothing. For further study of Re-ID in cloth-changing scenarios, we construct a large-scale dataset called CSCC with the following unique features: (1) Severe: A large number of people have cloth-changing over four seasons. (2) High definition: The resolution of the cameras ranges from 1920×1080 to 3840×2160, which ensures that the recorded people are clear. Furthermore, we provide two variants of CSCC considering different degrees of cloth-changing, namely moderate and severe, so that researchers can effectively evaluate their models from various aspects. Experiments on several cloth-changing datasets including our CSCC and short-term dataset Market-1501 prove the superiority of UCAD. The dataset is available at https://github.com/yomin-y/UCAD.","doi":"10.24963/ijcai.2022/212","url":"https://ijcai.org/proceedings/2022/212","pdf":"https://ijcai.org/proceedings/2022/0212.pdf","markdown":"https://ijcai.org/proceedings/2022/212.md","bibtex":"https://ijcai.org/proceedings/2022/bibtex/212","volume":{"slug":"2022","title":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2022","url":"https://ijcai.org/proceedings/2022/","year":2022,"location":"Vienna","dates":"23-29 July 2022","editors":"Luc De Raedt","isbn":"978-1-956792-00-3","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2022"},"section":"Computer Vision","track":"Main Track","number":212,"pages":{"first":1523,"last":1529},"keywords":["Computer Vision: Image and Video retrieval","Computer Vision: Representation Learning"],"videos":[{"label":"Video #1","url":"https://slideslive.com/38986466","length_sec":90,"provider":"slideslive"},{"label":"Video #2","url":"https://slideslive.com/38984609","length_sec":355,"provider":"slideslive"}],"references":[{"position":1,"raw":"[Chen et al., 2019] Binghui Chen, Weihong Deng, and Jiani Hu. 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