Pub Date : 2024-08-23DOI: 10.1109/tcsvt.2024.3448351
Ming Li, Zhaoli Yang, Tao Wang, Yushu Zhang, Wenying Wen
{"title":"Dual Protection for Image Privacy and Copyright via Traceable Adversarial Examples","authors":"Ming Li, Zhaoli Yang, Tao Wang, Yushu Zhang, Wenying Wen","doi":"10.1109/tcsvt.2024.3448351","DOIUrl":"https://doi.org/10.1109/tcsvt.2024.3448351","url":null,"abstract":"","PeriodicalId":13082,"journal":{"name":"IEEE Transactions on Circuits and Systems for Video Technology","volume":"9 1","pages":""},"PeriodicalIF":8.4,"publicationDate":"2024-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142177197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Automatic, Robust and Blind Video Watermarking Resisting Camera Recording","authors":"Lina Lin, Deyang Wu, Jiayan Wang, Yanli Chen, Xinpeng Zhang, Hanzhou Wu","doi":"10.1109/tcsvt.2024.3448502","DOIUrl":"https://doi.org/10.1109/tcsvt.2024.3448502","url":null,"abstract":"","PeriodicalId":13082,"journal":{"name":"IEEE Transactions on Circuits and Systems for Video Technology","volume":"383 1","pages":""},"PeriodicalIF":8.4,"publicationDate":"2024-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142177200","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-23DOI: 10.1109/tcsvt.2024.3449070
Xuehui Wu, Huanliang Xu, Henry Leung, Xiaobo Lu, Yanbin Li
{"title":"F2CENet: Single-Image Object Counting Based on Block Co-saliency Density Map Estimation","authors":"Xuehui Wu, Huanliang Xu, Henry Leung, Xiaobo Lu, Yanbin Li","doi":"10.1109/tcsvt.2024.3449070","DOIUrl":"https://doi.org/10.1109/tcsvt.2024.3449070","url":null,"abstract":"","PeriodicalId":13082,"journal":{"name":"IEEE Transactions on Circuits and Systems for Video Technology","volume":"31 1","pages":""},"PeriodicalIF":8.4,"publicationDate":"2024-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142177201","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-13DOI: 10.1109/TCSVT.2024.3418228
Wenguan Wang;Tianfei Zhou;Dongfang Liu;Zheng Thomas Tang;Alexander C. Loui
Currently, the success of image processing relies heavily on large well-annotated datasets. However, collecting and labeling video data are significantly more labor-intensive, posing major challenges for training video algorithms and limiting their practical applications. While label-efficient techniques for image data have advanced, solutions for video data are still emerging. Unlabeled video data, with their inherent structured nature, offer valuable assets for label-efficient learning. Unlike image data, video data naturally captures realistic transformations, providing rich samples for learning. Moreover, from a border perspective, video tasks hold great potential for applications like autonomous driving and video surveillance but present unique challenges due to the need to understand both spatial and temporal aspects. Leveraging label-efficient learning is essential for comprehensively understanding visual content and enabling a wide range of real-world video applications. This Special Issue on “Label-Efficient Learning for Video Data” seeks to advance research in this area, offering new insights and solutions to benefit both researchers and practitioners.
{"title":"Guest Editorial Introduction to the Special Issue on Label-Efficient Learning on Video Data","authors":"Wenguan Wang;Tianfei Zhou;Dongfang Liu;Zheng Thomas Tang;Alexander C. Loui","doi":"10.1109/TCSVT.2024.3418228","DOIUrl":"https://doi.org/10.1109/TCSVT.2024.3418228","url":null,"abstract":"Currently, the success of image processing relies heavily on large well-annotated datasets. However, collecting and labeling video data are significantly more labor-intensive, posing major challenges for training video algorithms and limiting their practical applications. While label-efficient techniques for image data have advanced, solutions for video data are still emerging. Unlabeled video data, with their inherent structured nature, offer valuable assets for label-efficient learning. Unlike image data, video data naturally captures realistic transformations, providing rich samples for learning. Moreover, from a border perspective, video tasks hold great potential for applications like autonomous driving and video surveillance but present unique challenges due to the need to understand both spatial and temporal aspects. Leveraging label-efficient learning is essential for comprehensively understanding visual content and enabling a wide range of real-world video applications. This Special Issue on “Label-Efficient Learning for Video Data” seeks to advance research in this area, offering new insights and solutions to benefit both researchers and practitioners.","PeriodicalId":13082,"journal":{"name":"IEEE Transactions on Circuits and Systems for Video Technology","volume":"34 8","pages":"6615-6619"},"PeriodicalIF":8.3,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10634312","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141980002","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-12DOI: 10.1109/TCSVT.2024.3436237
{"title":"IEEE Transactions on Circuits and Systems for Video Technology Publication Information","authors":"","doi":"10.1109/TCSVT.2024.3436237","DOIUrl":"https://doi.org/10.1109/TCSVT.2024.3436237","url":null,"abstract":"","PeriodicalId":13082,"journal":{"name":"IEEE Transactions on Circuits and Systems for Video Technology","volume":"34 8","pages":"C2-C2"},"PeriodicalIF":8.3,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10634007","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141979978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Our world is becoming rapidly dependent on data of increasing complexity, diversity, and volume which calls for robust and powerful tools to process such big data. Probabilistic generative models fulfill this goal by learning latent characteristic data relations, especially for the recent emergence of large-scale deep generative models that are able to create realistic content, namely, artificial intelligence-generated content (AIGC). The applications of AIGC span across various domains, and witness rich potential in multimedia content creation, including dialog generation, text-to-speech conversion, image/video generation, and cross-modal content generation.
{"title":"Introduction to the Special Issue on AI-Generated Content for Multimedia","authors":"Shengxi Li;Xuelong Li;Leonardo Chiariglione;Jiebo Luo;Wenwu Wang;Zhengyuan Yang;Danilo Mandic;Hamido Fujita","doi":"10.1109/TCSVT.2024.3427488","DOIUrl":"https://doi.org/10.1109/TCSVT.2024.3427488","url":null,"abstract":"Our world is becoming rapidly dependent on data of increasing complexity, diversity, and volume which calls for robust and powerful tools to process such big data. Probabilistic generative models fulfill this goal by learning latent characteristic data relations, especially for the recent emergence of large-scale deep generative models that are able to create realistic content, namely, artificial intelligence-generated content (AIGC). The applications of AIGC span across various domains, and witness rich potential in multimedia content creation, including dialog generation, text-to-speech conversion, image/video generation, and cross-modal content generation.","PeriodicalId":13082,"journal":{"name":"IEEE Transactions on Circuits and Systems for Video Technology","volume":"34 8","pages":"6809-6813"},"PeriodicalIF":8.3,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10634078","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141980003","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-12DOI: 10.1109/TCSVT.2024.3436239
{"title":"IEEE Circuits and Systems Society Information","authors":"","doi":"10.1109/TCSVT.2024.3436239","DOIUrl":"https://doi.org/10.1109/TCSVT.2024.3436239","url":null,"abstract":"","PeriodicalId":13082,"journal":{"name":"IEEE Transactions on Circuits and Systems for Video Technology","volume":"34 8","pages":"C3-C3"},"PeriodicalIF":8.3,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10634008","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141973507","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-09DOI: 10.1109/tcsvt.2024.3404865
Yanjun Liu, Wenming Yang, Qingmin Liao
{"title":"DiffVein: A Unified Diffusion Network for Finger Vein Segmentation and Authentication","authors":"Yanjun Liu, Wenming Yang, Qingmin Liao","doi":"10.1109/tcsvt.2024.3404865","DOIUrl":"https://doi.org/10.1109/tcsvt.2024.3404865","url":null,"abstract":"","PeriodicalId":13082,"journal":{"name":"IEEE Transactions on Circuits and Systems for Video Technology","volume":"23 1","pages":""},"PeriodicalIF":8.4,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141940452","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Preprocessing Enhanced Image Compression for Machine Vision","authors":"Guo Lu, Xingtong Ge, Tianxiong Zhong, Qiang Hu, Jing Geng","doi":"10.1109/tcsvt.2024.3441049","DOIUrl":"https://doi.org/10.1109/tcsvt.2024.3441049","url":null,"abstract":"","PeriodicalId":13082,"journal":{"name":"IEEE Transactions on Circuits and Systems for Video Technology","volume":"8 1","pages":""},"PeriodicalIF":8.4,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141940450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-09DOI: 10.1109/tcsvt.2024.3441036
Yaoyan Zheng, Hongyu Yang, Di Huang
{"title":"Deep Common Feature Mining for Efficient Video Semantic Segmentation","authors":"Yaoyan Zheng, Hongyu Yang, Di Huang","doi":"10.1109/tcsvt.2024.3441036","DOIUrl":"https://doi.org/10.1109/tcsvt.2024.3441036","url":null,"abstract":"","PeriodicalId":13082,"journal":{"name":"IEEE Transactions on Circuits and Systems for Video Technology","volume":"58 1","pages":""},"PeriodicalIF":8.4,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141940455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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