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检索条件"机构=Laboratory for Advanced Computing and Intelligence Engineering"
547 条 记 录,以下是151-160 订阅
排序:
Graph Prompt Clustering
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IEEE Transactions on Pattern Analysis and Machine intelligence 2025年 PP卷 PP页
作者: Chen, Man-Sheng Lai, Pei-Yuan Liao, De-Zhang Wang, Chang-Dong Lai, Jian-Huang Sun Yat-sen University School of Computer Science and Engineering Guangzhou China Ministry of Education Key Laboratory of Machine Intelligence and Advanced Computing China Guangdong University of Technology School of Information Engineering Guangzhou China South China Technology Commercialization Center Guangzhou China
Due to the wide existence of unlabeled graph-structured data (e.g. molecular structures), the graph-level clustering has recently attracted increasing attention, whose goal is to divide the input graphs into several d... 详细信息
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DeepFake Videos Detection Based on Texture Features
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Computers, Materials & Continua 2021年 第7期68卷 1375-1388页
作者: Bozhi Xu Jiarui Liu Jifan Liang Wei Lu Yue Zhang School of Computer Science and Engineering Guangdong Province Key Laboratory of Information Security TechnologyMinistry of Education Key Laboratory of Machine Intelligence and Advanced ComputingSun Yat-sen UniversityGuangzhou510006China Department of Computer Science University of Massachusetts LowellLowell01854MAUSA
In recent years,with the rapid development of deep learning technologies,some neural network models have been applied to generate fake ***,a deep learning based forgery technology,can tamper with the face easily and g... 详细信息
来源: 评论
Progressive Human Motion Generation Based on Text and Few Motion Frames
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IEEE Transactions on Circuits and Systems for Video Technology 2025年
作者: Zeng, Ling-An Wu, Gaojie Wu, Ancong Hu, Jian-Fang Zheng, Wei-Shi Sun Yat-sen University School of Artificial Intelligence Guangdong Zhuhai519082 China Sun Yat-sen University School of Computer Science and Engineering Guangdong Guangzhou510275 China Sun Yat-sen University School of Computer Science and Engineering China Guangdong Key Laboratory of Information Security Technology China Ministry of Education Key Laboratory of Machine Intelligence and Advanced Computing China Peng Cheng Laboratory China
Although existing text-to-motion (T2M) methods can produce realistic human motion from text description, it is still difficult to align the generated motion with the desired postures since using text alone is insuffic... 详细信息
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When Prompt-based Incremental Learning Does Not Meet Strong Pretraining
arXiv
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arXiv 2023年
作者: Tang, Yu-Ming Peng, Yi-Xing Zheng, Wei-Shi School of Computer Science and Engineering Sun Yat-sen University China Peng Cheng Laboratory Shenzhen China Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education China
Incremental learning aims to overcome catastrophic forgetting when learning deep networks from sequential tasks. With impressive learning efficiency and performance, prompt-based methods adopt a fixed backbone to sequ... 详细信息
来源: 评论
When Prompt-based Incremental Learning Does Not Meet Strong Pretraining
When Prompt-based Incremental Learning Does Not Meet Strong ...
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International Conference on Computer Vision (ICCV)
作者: Yu-Ming Tang Yi-Xing Peng Wei-Shi Zheng School of Computer Science and Engineering Sun Yat-sen University China Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education China Peng Cheng Laboratory Shenzhen China
Incremental learning aims to overcome catastrophic forgetting when learning deep networks from sequential tasks. With impressive learning efficiency and performance, prompt-based methods adopt a fixed backbone to sequ...
来源: 评论
AsyFOD: An Asymmetric Adaptation Paradigm for Few-Shot Domain Adaptive Object Detection
AsyFOD: An Asymmetric Adaptation Paradigm for Few-Shot Domai...
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Conference on Computer Vision and Pattern Recognition (CVPR)
作者: Yipeng Gao Kun-Yu Lin Junkai Yan Yaowei Wang Wei-Shi Zheng School of Computer Science and Engineering Sun Yat-sen University China Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education China Pengcheng Lab
In this work, we study few-shot domain adaptive object detection (FSDAOD), where only a few target labeled images are available for training in addition to sufficient source labeled images. Critically, in FSDAOD, the ...
来源: 评论
A Sample-driven Selection Framework: Towards Graph Contrastive Networks with Reinforcement Learning  24
A Sample-driven Selection Framework: Towards Graph Contrasti...
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32nd ACM International Conference on Multimedia, MM 2024
作者: Zheng, Xiangping Hao, Xiuxin Wu, Bo Bao, Xigang Zhang, Xuan Li, Wei Liang, Xun College of Computer Science and Technology Harbin Engineering University Heilongjiang Harbin China Modeling and Emulation in E-Government National Engineering Laboratory Heilongjiang Harbin China Qingdao Innovation and Development Base of Harbin Engineering University Shandong Qindao China R&d and External Relations Department Xiangjiang Laboratory Hunan Changsha China School of Artificial Intelligence and Advanced Computing Hunan University of Technology and Business Hunan Changsha China Changsha Artificial Intelligence Social Laboratory Hunan Changsha China School of Information Renmin University of China Beijing China Guanghua School of Management Peking University Beijing China Harvest Fund Management Co. Ltd. Beijing China
Graph Contrastive Learning (GCL) aims to address the issue of label scarcity by leveraging graph structures to propagate labels from a limited set of labeled data to a broader range of unlabeled data. However, recent ... 详细信息
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Incorporating Retrieval-based Causal Learning with Information Bottlenecks for Interpretable Graph Neural Networks
arXiv
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arXiv 2024年
作者: Rao, Jiahua Xie, Jiancong Lin, Hanjing Zheng, Shuangjia Wang, Zhen Yang, Yuedong School of Computer Science and Engineering Sun Yat-sen University China Shanghai Jiao Tong University China Key Laboratory of Machine Intelligence and Advanced Computing Sun Yat-sen University China
Graph Neural Networks (GNNs) have gained considerable traction for their capability to effectively process topological data, yet their interpretability remains a critical concern. Current interpretation methods are do... 详细信息
来源: 评论
PPVF: An Efficient Privacy-Preserving Online Video Fetching Framework with Correlated Differential Privacy
arXiv
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arXiv 2024年
作者: Zhang, Xianzhi Zhou, Yipeng Wu, Di Sheng, Quan Z. Hu, Miao Xiao, Linchang The School of Computer Science and Engineering Sun Yat-Sen University Guangzhou510006 China The Key Laboratory of Machine Intelligence and Advanced Computing Sun Yat-Sen University Ministry of Education China The School of Computing Macquarie University NSW2109 Australia
Online video streaming has evolved into an integral component of the contemporary Internet landscape. Yet, the disclosure of user requests presents formidable privacy challenges. As users stream their preferred online... 详细信息
来源: 评论
IMPROVING WEAKLY SUPERVISED OBJECT LOCALIZATION BY UNCERTAINTY ESTIMATION OF PSEUDO SUPERVISION
IMPROVING WEAKLY SUPERVISED OBJECT LOCALIZATION BY UNCERTAIN...
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2021 IEEE International Conference on Multimedia and Expo, ICME 2021
作者: Chen, Xi Ma, Andy J. Guo, Nanxi Chen, Jiajia School of Computer Science and Engineering Sun Yat-sen University Guangzhou China Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education China
Pseudo bounding box supervision is a promising approach for weakly supervised object localization (WSOL) with only image-level labels. However, the generated pseudo bounding boxes may be inaccurate or even completely ... 详细信息
来源: 评论