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Domain Adaptation by Class Centroid Matching and Local Manifold Self-Learning 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2020, 卷号: 29, 页码: 9703-9718
作者:  Tian, Lei;  Tang, Yongqiang;  Hu, Liangchen;  Ren, Zhida;  Zhang, Wensheng
Adobe PDF(3443Kb)  |  收藏  |  浏览/下载：385/83  |  提交时间：2021/01/06
Domain adaptation  class centroid matching  local manifold self-learning  
DID: Disentangling-Imprinting-Distilling for Continuous Low-Shot Detection 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2020, 卷号: 29, 页码: 7765-7778
作者:  Chen, Xianyu;  Wang, Yali;  Liu, Jianzhuang;  Qiao, Yu
收藏  |  浏览/下载：179/0  |  提交时间：2020/08/21
Object detection  low-shot learning  continuous learning  deep learning  transfer learning  
Tangent Fisher Vector on Matrix Manifolds for Action Recognition 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2020, 卷号: 29, 期号: 1, 页码: 3052-3064
作者:  Luo, Guan;  Wei, Jiutong;  Hu, Weiming;  Maybank, Stephen J.
浏览  |  Adobe PDF(2396Kb)  |  收藏  |  浏览/下载：400/84  |  提交时间：2020/04/07
Manifolds  Video sequences  Observability  Videos  Covariance matrices  Kernel  Computational modeling  Action recognition  Fisher vector  Grassmann manifold  Hankel matrix  matrix manifold  
Deep Unbiased Embedding Transfer for Zero-Shot Learning 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2020, 卷号: 29, 期号: 29, 页码: 1958-1971
作者:  Jia, Zhen;  Zhang, Zhang;  Wang, Liang;  Shan, Caifeng;  Tan, Tieniu
浏览  |  Adobe PDF(3428Kb)  |  收藏  |  浏览/下载：430/72  |  提交时间：2020/03/30
Visualization  Feature extraction  Semantics  Training  Seals  Prototypes  Indexes  Zero-shot learning  image classification  projection domain shift  convolutional neural network  generative adversarial network  
Progressive Object Transfer Detection 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2020, 卷号: 29, 页码: 986-1000
作者:  Chen, Hao;  Wang, Yali;  Wang, Guoyou;  Bai, Xiang;  Qiao, Yu
收藏  |  浏览/下载：293/0  |  提交时间：2020/03/30
Detectors  Object detection  Proposals  Task analysis  Benchmark testing  Deep learning  Labeling  Object detection  deep learning  transfer learning  weakly  semi-supervised detection  low-shot learning