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Visually Guided Sound Source Separation With Audio-Visual Predictive Coding 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2023, 页码: 15
作者:  Song, Zengjie;  Zhang, Zhaoxiang
收藏  |  浏览/下载：73/0  |  提交时间：2023/11/17
Feature fusion  multimodal learning  predictive coding (PC)  self-supervised learning  sound source separation  
Learning to Adapt Across Dual Discrepancy for Cross-Domain Person Re-Identification 期刊论文
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2023, 卷号: 45, 期号: 2, 页码: 1963-1980
作者:  Luo, Chuanchen;  Song, Chunfeng;  Zhang, Zhaoxiang
Adobe PDF(2539Kb)  |  收藏  |  浏览/下载：268/80  |  提交时间：2023/03/20
Person re-identification  domain adaptation  cross-domain mixup  camera-aware learning  self-paced learning  
3D PostureNet: A unified framework for skeleton-based posture recognition 期刊论文
PATTERN RECOGNITION LETTERS, 2020, 卷号: 140, 期号: 140, 页码: 143-149
作者:  Liu, Jianbo;  Wang, Ying;  Liu, Yongcheng;  Xiang, Shiming;  Pan, Chunhong
Adobe PDF(1997Kb)  |  收藏  |  浏览/下载：302/46  |  提交时间：2021/03/02
Human posture recognition  Static hand gesture recognition  Skeleton-based  3D convolutional neural network  
Multi-Domain Image-to-Image Translation via a Unified Circular Framework 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2020, 期号: 30, 页码: 670-684
作者:  Wang, Yuxi;  Zhang, Zhaoxiang;  Hao, Wangli;  Song, Chunfeng
Adobe PDF(3399Kb)  |  收藏  |  浏览/下载：351/67  |  提交时间：2021/03/02
Task analysis  Semantics  Visualization  Generative adversarial networks  Generators  Feature extraction  Meteorology  Image-to-image transfer  sharing knowledge module  multiple domain pairs  GANs  
Attention Guided Multiple Source and Target Domain Adaptation 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2020, 期号: 30, 页码: 892-906
作者:  Wang, Yuxi;  Zhang, Zhaoxiang;  Hao, Wangli;  Song, Chunfeng
Adobe PDF(3460Kb)  |  收藏  |  浏览/下载：321/53  |  提交时间：2021/03/02
Semantics  Task analysis  Generators  Generative adversarial networks  Feature extraction  Visualization  Meteorology  Domain adaptation  multiple source and target domains  attention