CASIA OpenIR

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Everybody’s Talkin’: Let Me Talk as You Want 期刊论文
IEEE Transactions on Information Forensics and Security, 2022, 卷号: 17, 期号: 1, 页码: 585 - 598
作者:  宋林森;  吴文岩;  钱晨;  赫然;  Loy, Chen Change
Adobe PDF(15432Kb)  |  收藏  |  浏览/下载:108/16  |  提交时间:2023/06/29
Talking face generation  Video generation  GAN  Audio dubbing  
Combining 2D texture and 3D geometry features for Reliable iris presentation attack detection using light field focal stack 期刊论文
IET BIOMETRICS, 2022, 页码: 10
作者:  Luo, Zhengquan;  Wang, Yunlong;  Liu, Nianfeng;  Wang, Zilei
Adobe PDF(1236Kb)  |  收藏  |  浏览/下载:277/42  |  提交时间:2022/11/14
Velocity-to-velocity human motion forecasting 期刊论文
PATTERN RECOGNITION, 2022, 卷号: 124, 页码: 11
作者:  Wang, Hongsong;  Wang, Liang;  Feng, Jiashi;  Zhou, Daquan
收藏  |  浏览/下载:232/0  |  提交时间:2022/06/10
Human motion prediction  Action anticipation  
Theme-Aware Aesthetic Distribution Prediction With Full-Resolution Photographs 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2022, 页码: 15
作者:  Jia, Gengyun;  Li, Peipei;  He, Ran
Adobe PDF(10845Kb)  |  收藏  |  浏览/下载:292/47  |  提交时间:2022/06/06
Aesthetic quality assessment (AQA)  full resolution  region of image (RoM) pooling  theme  
From Individual to Whole: Reducing Intra-class Variance by Feature Aggregation 期刊论文
INTERNATIONAL JOURNAL OF COMPUTER VISION, 2022, 卷号: 130, 期号: 3, 页码: 800-819
作者:  Zhang, Zhaoxiang;  Luo, Chuanchen;  Wu, Haiping;  Chen, Yuntao;  Wang, Naiyan;  Song, Chunfeng
Adobe PDF(1762Kb)  |  收藏  |  浏览/下载:318/45  |  提交时间:2022/06/06
Feature aggregation  Deep learning  Intra-class variance  Person re-identification  Video object detection  
Learning 3D Human Shape and Pose from Dense Body Parts 期刊论文
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2022, 卷号: 44, 期号: 5, 页码: 2610-2627
作者:  Zhang, Hongwen;  Cao, Jie;  Lu, Guo;  Ouyang, Wanli;  Sun, Zhenan
Adobe PDF(4759Kb)  |  收藏  |  浏览/下载:237/58  |  提交时间:2021/06/16
3D human shape and pose estimation  decompose-and-aggregate network  position-aided rotation feature refinement  part-based dropout