CASIA OpenIR

浏览/检索结果: 共5条,第1-5条 帮助

限定条件    
已选(0)清除 条数/页:   排序方式:
Skeleton-Based Action Recognition With Multi-Stream Adaptive Graph Convolutional Networks 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2020, 期号: 29, 页码: 9532-9545
作者:  Shi, Lei;  Zhang, Yifan;  Cheng, Jian;  Lu, Hanqing
浏览  |  Adobe PDF(2849Kb)  |  收藏  |  浏览/下载:414/160  |  提交时间:2020/11/05
Skeleton-based action recognition, graph convolutional network, adaptive graph, multi-stream network.  
Moving Object Detection Using Tensor-Based Low-Rank and Saliently Fused-Sparse Decomposition 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2017, 卷号: 26, 期号: 2, 页码: 724-737
作者:  Hu, Wenrui;  Yang, Yehui;  Zhang, Wensheng;  Xie, Yuan
浏览  |  Adobe PDF(13016Kb)  |  收藏  |  浏览/下载:548/205  |  提交时间:2017/09/12
Moving Object Detection  Tensor Nuclear Norm  Tensor Total Variation  Space-time Visual Saliency  
Removing Turbulence Effect via Hybrid Total Variation and Deformation-Guided Kernel Regression 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2016, 卷号: 25, 期号: 10, 页码: 4943-4958
作者:  Xie, Yuan;  Zhang, Wensheng;  Tao, Dacheng;  Hu, Wenrui;  Qu, Yanyun;  Wang, Hanzi;  Yuan Xie
浏览  |  Adobe PDF(9193Kb)  |  收藏  |  浏览/下载:541/163  |  提交时间:2016/10/22
Image Restoration  Atmospheric Turbulence  Total Variation  Deformation-guided Kernel  
Speeding Up the Bilateral Filter: A Joint Acceleration Way 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2016, 卷号: 25, 期号: 6, 页码: 2657-2672
作者:  Dai, Longquan;  Yuan, Mengke;  Zhang, Xiaopeng
浏览  |  Adobe PDF(7883Kb)  |  收藏  |  浏览/下载:322/88  |  提交时间:2016/10/20
Fast Bilateral Filter  Best N-term Approximation  Haar Functions  Truncated Trigonometric Functions  
Spectral Unmixing via Data-Guided Sparsity 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2014, 卷号: 23, 期号: 12, 页码: 5412-5427
作者:  Zhu, Feiyun;  Wang, Ying;  Fan, Bin;  Xiang, Shiming;  Meng, Gaofeng;  Pan, Chunhong
浏览  |  Adobe PDF(6232Kb)  |  收藏  |  浏览/下载:407/114  |  提交时间:2015/08/12
Data-guided Sparse (Dgs)  Data-guided Map (dgMap)  Nonnegative Matrix Factorization (Nmf)  Dgs-nmf  Mixed Pixel  Hyperspectral Unmixing (Hu)