Yu Xie, Lianhang Luo, Tianpei Cao, Bin Yu, A. K. Qin
{"title":"用于无监督图匹配的对比学习网络","authors":"Yu Xie, Lianhang Luo, Tianpei Cao, Bin Yu, A. K. Qin","doi":"10.1109/tcsvt.2024.3457575","DOIUrl":null,"url":null,"abstract":"","PeriodicalId":13082,"journal":{"name":"IEEE Transactions on Circuits and Systems for Video Technology","volume":"62 1","pages":""},"PeriodicalIF":8.3000,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Contrastive Learning Network for Unsupervised Graph Matching\",\"authors\":\"Yu Xie, Lianhang Luo, Tianpei Cao, Bin Yu, A. K. Qin\",\"doi\":\"10.1109/tcsvt.2024.3457575\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\",\"PeriodicalId\":13082,\"journal\":{\"name\":\"IEEE Transactions on Circuits and Systems for Video Technology\",\"volume\":\"62 1\",\"pages\":\"\"},\"PeriodicalIF\":8.3000,\"publicationDate\":\"2024-09-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Circuits and Systems for Video Technology\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1109/tcsvt.2024.3457575\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Circuits and Systems for Video Technology","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1109/tcsvt.2024.3457575","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
期刊介绍:
The IEEE Transactions on Circuits and Systems for Video Technology (TCSVT) is dedicated to covering all aspects of video technologies from a circuits and systems perspective. We encourage submissions of general, theoretical, and application-oriented papers related to image and video acquisition, representation, presentation, and display. Additionally, we welcome contributions in areas such as processing, filtering, and transforms; analysis and synthesis; learning and understanding; compression, transmission, communication, and networking; as well as storage, retrieval, indexing, and search. Furthermore, papers focusing on hardware and software design and implementation are highly valued. Join us in advancing the field of video technology through innovative research and insights.