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CASIA OpenIR
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Temporal Action Proposal Generation With Action Frequency Adaptive Network 期刊论文
IEEE Transactions on Multimedia, 2023, 卷号: 26, 页码: 2340 - 2353
作者:  Yepeng Tang;  Weining Wang;  Chunjie Zhang;  Jing Liu;  Yao Zhao
Adobe PDF(10095Kb)  |  收藏  |  浏览/下载：76/25  |  提交时间：2024/03/26
Proposals  Task analysis  Data models  Time-frequency analysis  Representation learning  Predictive models  Information science  Temporal action proposal generation  expert learning  fine-gained detection  action frequency  
Dual Transformer With Multi-Grained Assembly for Fine-Grained Visual Classification 期刊论文
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2023, 卷号: 33, 期号: 9, 页码: 5009-5021
作者:  Ji, Ruyi;  Li, Jiaying;  Zhang, Libo;  Liu, Jing;  Wu, Yanjun
Adobe PDF(4636Kb)  |  收藏  |  浏览/下载：171/16  |  提交时间：2023/11/16
Transformer  multi-grained assembly  fine-grained visual classification  
Semi-supervised Temporal Action Proposal Generation via Exploiting 2-d Proposal Map 期刊论文
IEEE Transactions on Multimedia, 2021, 页码: 3624 - 3635
作者:  Wang, Weining;  Lin, Tianwei;  He, Dongliang;  Li, Fu;  Wen, Shilei;  Wang, Liang;  Liu, Jing
Adobe PDF(4851Kb)  |  收藏  |  浏览/下载：164/27  |  提交时间：2023/05/03
Semi-supervised learning  proposal map oriented mean-teacher  pseudo label  
Sounding Video Generator: A Unified Framework for Text-guided Sounding Video Generation 期刊论文
IEEE Transactions on Multimedia, 2023, 卷号: 26, 页码: 1 - 13
作者:  Liu, Jiawei;  Wang, Weining;  Chen, Sihan;  Zhu, Xinxin;  Liu, Jing
Adobe PDF(7741Kb)  |  收藏  |  浏览/下载：169/36  |  提交时间：2023/05/03
Text-guided sounding-video generation  Videoaudio representation  Contrastive learning  Transformer  
Deep residual contextual and subpixel convolution network for automated neuronal structure segmentation in micro-connectomics 期刊论文
Computer Methods and Programs in Biomedicine, 2022, 卷号: 219, 页码: 106759
作者:  Xiao, Chi;  Hong, Bei;  Liu, Jing;  Tang, Yuanyan;  Xie, Qiwei;  Han, Hua
Adobe PDF(2731Kb)  |  收藏  |  浏览/下载：317/77  |  提交时间：2023/01/12
Deep learning  Neuronal structure segmentation  Subpixel convolution  Electron microscopy  Micro-Connectomics  
Joint reconstruction of neuron and ultrastructure via connectivity consensus in electron microscope volumes 期刊论文
BMC Bioinformatics, 2022, 卷号: 23, 期号: 1, 页码: 23
作者:  Hong,Bei;  Liu,Jing;  Zhai,Hao;  Liu,Jiazheng;  Shen,Lijun;  Chen,Xi;  Xie,Qiwei;  Han,Hua
Adobe PDF(3091Kb)  |  收藏  |  浏览/下载：378/86  |  提交时间：2022/11/14
Connectomics  Reconstruction  Connectivity concept  Joint optimization  Electron microscope volumes  
Question-Guided Erasing-Based Spatiotemporal Attention Learning for Video Question Answering 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 0
作者:  Liu, Fei;  Liu, Jing;  Hong, Richang;  Lu, Hanqing
Adobe PDF(3550Kb)  |  收藏  |  浏览/下载：367/93  |  提交时间：2022/01/27
video question answering  attention mechanism  metric learning  
Visual Question Answering With Dense Inter- and Intra-Modality Interactions 期刊论文
IEEE TRANSACTIONS ON MULTIMEDIA, 2021, 卷号: 23, 页码: 3518-3529
作者:  Liu, Fei;  Liu, Jing;  Fang, Zhiwei;  Hong, Richang;  Lu, Hanqing
Adobe PDF(2891Kb)  |  收藏  |  浏览/下载：337/76  |  提交时间：2021/12/28
Visualization  Knowledge discovery  Connectors  Encoding  Task analysis  Image coding  Stacking  Visual question answering  attention  dense interactions  
Sparse self-attention aggregation networks for neural sequence slice interpolation 期刊论文
BioData Mining, 2021, 卷号: 14, 期号: 1, 页码: 19
作者:  Wang, Zejin;  Liu, Jing;  Chen, Xi;  Li, Guoqing;  Han, Hua
Adobe PDF(5022Kb)  |  收藏  |  浏览/下载：320/45  |  提交时间：2021/02/18
Slice interpolation  Biological tissue recovery  EM images  Sparse self-attention network  Adaptive style-balance loss  
Attention-Guided Network for Semantic Video Segmentation 期刊论文
IEEE ACCESS, 2019, 卷号: 7, 页码: 140680-140689
作者:  Li, Jiangyun;  Zhao, Yikai;  Fu, Jun;  Wu, Jiajia;  Liu, Jing
收藏  |  浏览/下载：277/0  |  提交时间：2020/03/30
Semantics  Image segmentation  Feature extraction  Active appearance model  Optical imaging  Context modeling  Task analysis  Semantic video segmentation  attention  convolutional neural networks