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IrisGuideNet: Guided Localization and Segmentation Network for Unconstrained Iris Biometrics 期刊论文
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, 2023, 卷号: 18, 页码: 2723-2736
作者:  Muhammad, Jawad;  Wang, Caiyong;  Wang, Yunlong;  Zhang, Kunbo;  Sun, Zhenan
收藏  |  浏览/下载：99/0  |  提交时间：2023/11/17
Iris biometrics  iris segmentation  iris localization  heuristics guide  
Controllable Multi-Attribute Editing of High-Resolution Face Images 期刊论文
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, 2021, 卷号: 16, 期号: 0, 页码: 1410-1423
作者:  Deng, Qiyao;  Li, Qi;  Cao, Jie;  Liu, Yunfan;  Sun, Zhenan
Adobe PDF(8442Kb)  |  收藏  |  浏览/下载：307/39  |  提交时间：2021/03/02
Faces  Image resolution  Face recognition  Wavelet transforms  Generative adversarial networks  Computational modeling  Face attribute editing  Face synthesis  Generative adversarial network  
Facial Age and Expression Synthesis Using Ordinal Ranking Adversarial Networks 期刊论文
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, 2020, 卷号: 15, 页码: 2960-2972
作者:  Sun, Yunlian;  Tang, Jinhui;  Sun, Zhenan;  Tistarelli, Massimo
收藏  |  浏览/下载：254/0  |  提交时间：2020/06/02
Face image aging  facial expression synthesis  generative adversarial networks  ordinal ranking  
Towards Complete and Accurate Iris Segmentation Using Deep Multi-Task Attention Network for Non-Cooperative Iris Recognition 期刊论文
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, 2020, 卷号: 15, 期号: 1, 页码: 2944-2959
作者:  Wang, Caiyong;  Muhammad, Jawad;  Wang, Yunlong;  He, Zhaofeng;  Sun, Zhenan
浏览  |  Adobe PDF(8655Kb)  |  收藏  |  浏览/下载：536/223  |  提交时间：2020/06/02
Iris segmentation  iris localization  attention mechanism  multi-task learning  iris recognition  
Deep Feature Fusion for Iris and Periocular Biometrics on Mobile Devices 期刊论文
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, 2018, 卷号: 13, 期号: 11, 页码: 2897-2912
作者:  Zhang, Qi;  Li, Haiqing;  Sun, Zhenan;  Tan, Tieniu
收藏  |  浏览/下载：310/0  |  提交时间：2019/12/16
Iris recognition  periocular recognition  deep feature fusion  adaptive weights  mobile devices