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CKDF: Cascaded Knowledge Distillation Framework for Robust Incremental Learning 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2022, 卷号: 31, 页码: 3825–3837
作者:  Li KC(李焜炽);  Wan J(万军);  Yu S(余山)
Adobe PDF(3813Kb)  |  收藏  |  浏览/下载：39/10  |  提交时间：2024/05/28
Narrowing the Gap: Improved Detector Training With Noisy Location Annotations 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2022, 卷号: 31, 页码: 6369-6380
作者:  Wang, Shaoru;  Gao, Jin;  Li, Bing;  Hu, Weiming
Adobe PDF(1489Kb)  |  收藏  |  浏览/下载：239/31  |  提交时间：2022/11/14
Annotations  Noise measurement  Detectors  Task analysis  Training  Object detection  Degradation  Object detection  noisy label  Bayesian estimation  teacher-student learning  
An Iterative Co-Training Transductive Framework for Zero Shot Learning 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2021, 卷号: 30, 页码: 6943-6956
作者:  Liu, Bo;  Hu, Lihua;  Dong, Qiulei;  Hu, Zhanyi
Adobe PDF(2452Kb)  |  收藏  |  浏览/下载：279/62  |  提交时间：2021/11/02
Visualization  Semantics  Training  Feature extraction  Testing  Detectors  Predictive models  Zero-shot learning  transductive learning co-training  
Efficient Center Voting for Object Detection and 6D Pose Estimation in 3D Point Cloud 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2021, 卷号: 30, 期号: 1, 页码: 5072-5084
作者:  Guo, Jianwei;  Xing, Xuejun;  Quan, Weize;  Yan, Dong-Ming;  Gu, Qingyi;  Liu, Yang;  Zhang, Xiaopeng
Adobe PDF(8313Kb)  |  收藏  |  浏览/下载：207/4  |  提交时间：2021/08/15
Three-dimensional displays  Pose estimation  Shape  Object detection  Feature extraction  Object recognition  Transmission line matrix methods  6D pose estimation  3D object recognition  point pair features  3D point cloud  
Nocal-Siam: Refining Visual Features and Response With Advanced Non-Local Blocks for Real-Time Siamese Tracking 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2021, 卷号: 30, 页码: 2656-2668
作者:  Tan, Huibin;  Zhang, Xiang;  Zhang, Zhipeng;  Lan, Long;  Zhang, Wenju;  Luo, Zhigang
Adobe PDF(2898Kb)  |  收藏  |  浏览/下载：187/46  |  提交时间：2021/03/29
Target tracking  Visualization  Feature extraction  Real-time systems  Oceans  Convolution  Task analysis  Siamese trackers  non-local attention  supervisedly attentive  
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：358/72  |  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：168/0  |  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：375/81  |  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：415/69  |  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：277/0  |  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