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Understanding and Mitigating Overfitting in Prompt Tuning for Vision-Language Models 期刊论文
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2023, 卷号: 33, 期号: 9, 页码: 4616-4629
作者:  Ma, Chengcheng;  Liu, Yang;  Deng, Jiankang;  Xie, Lingxi;  Dong, Weiming;  Xu, Changsheng
Adobe PDF(1644Kb)  |  收藏  |  浏览/下载：80/11  |  提交时间：2023/11/16
Vision-language model  prompt tuning  over-fitting  subspace learning  gradient projection  
Learning Accurate and Stable Point-to-Point Motions: A Dynamic System Approach 期刊论文
IEEE ROBOTICS AND AUTOMATION LETTERS, 2022, 卷号: 7, 期号: 2, 页码: 1510-1517
作者:  Zhang, Yu;  Cheng, Long;  Li, Houcheng;  Cao, Ran
Adobe PDF(3334Kb)  |  收藏  |  浏览/下载：200/19  |  提交时间：2022/02/16
Point-to-point tasks  neural network  dynamic system  generalization performance  high dimensional data  
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：187/23  |  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  
Holographic Feature Learning of Egocentric-Exocentric Videos for Multi-Domain Action Recognition 期刊论文
IEEE TRANSACTIONS ON MULTIMEDIA, 2022, 卷号: 24, 页码: 2273-2286
作者:  Huang, Yi;  Yang, Xiaoshan;  Gao, Junyun;  Xu, Changsheng
Adobe PDF(2409Kb)  |  收藏  |  浏览/下载：288/61  |  提交时间：2022/07/25
Videos  Feature extraction  Visualization  Task analysis  Computational modeling  Target recognition  Prototypes  Egocentric videos  exocentric videos  holographic feature  multi-domain  action recognition  
Weakly-Supervised Video Object Grounding Via Learning Uni-Modal Associations 期刊论文
IEEE Transactions on Multimedia, 2022, 卷号: 25, 页码: 1-12
作者:  Wang, Wei;  Gao, Junyu;  Xu, Changsheng
Adobe PDF(5406Kb)  |  收藏  |  浏览/下载：78/21  |  提交时间：2023/04/25
Visualization  Grounding  Task analysis  Prototypes  Annotations  Uncertainty  Proposals  Cross-modal retrieval  weakly-supervised learning  video object grounding  uni-modal association  
AutoDet: Pyramid Network Architecture Search for Object Detection 期刊论文
INTERNATIONAL JOURNAL OF COMPUTER VISION, 2021, 期号: 4, 页码: 1087-1105
作者:  Li, Zhihang;  Xi, Teng;  Zhang, Gang;  Liu, Jingtuo;  He, Ran
Adobe PDF(2604Kb)  |  收藏  |  浏览/下载：244/38  |  提交时间：2021/03/01
Object detection  Neural architecture search  Feature pyramids  
Show, Tell, and Polish: Ruminant Decoding for Image Captioning 期刊论文
IEEE TRANSACTIONS ON MULTIMEDIA, 2020, 卷号: 22, 期号: 8, 页码: 2149-2162
作者:  Guo, Longteng;  Liu, Jing;  Lu, Shichen;  Lu, Hanqing
Adobe PDF(4378Kb)  |  收藏  |  浏览/下载：197/28  |  提交时间：2020/08/31
Image captioning  Multi-pass decoding  Rumination  
Deep Self-Evolution Clustering 期刊论文
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2020, 卷号: 42, 期号: 4, 页码: 809-823
作者:  Chang, Jianlong;  Meng, Gaofeng;  Wang, Lingfeng;  Xiang, Shiming;  Pan, Chunhong
浏览  |  Adobe PDF(4817Kb)  |  收藏  |  浏览/下载：380/85  |  提交时间：2020/06/02
Task analysis  Unsupervised learning  Training  Clustering methods  Pattern analysis  Clustering  deep self-evolution clustering  self-evolution clustering training  deep unsupervised learning  
Local-Aggregation Graph Networks 期刊论文
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020, 卷号: 42, 期号: 11, 页码: 2874-2886
作者:  Jianlong Chang;  Lingfeng Wang;  Gaofeng Meng;  Shiming Xiang;  Chunhong Pan
浏览  |  Adobe PDF(3090Kb)  |  收藏  |  浏览/下载：227/87  |  提交时间：2020/10/20
Local-aggregation function  local-aggregation graph neural network  non-Euclidean structured signal  
EDP: An Efficient Decomposition and Pruning Scheme for Convolutional Neural Network Compression 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2020, 卷号: 32, 期号: 0, 页码: 0
作者:  Ruan, Xiaofeng;  Liu, Yufan;  Yuan, Chunfeng;  Li, Bing;  Hu, Weiming;  Li, Yangxi;  Maybank, Stephen
Adobe PDF(3625Kb)  |  收藏  |  浏览/下载：269/42  |  提交时间：2021/06/17
Data-driven  low-rank decomposition  model compression and acceleration  structured pruning