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检索条件"机构=Shenzhen Key Laboratory of Robotics and Computer Vision"
497 条 记 录,以下是241-250 订阅
排序:
Few-Shot Medical Image Segmentation with High-Fidelity Prototypes
arXiv
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arXiv 2024年
作者: Tang, Song Yan, Shaxu Qi, Xiaozhi Gao, Jianxin Ye, Mao Zhang, Jianwei Zhu, Xiatian IMI Group School of Health Sciences and Engineering University of Shanghai for Science and Technology Shanghai China TAMS Group Department of Informatics Universität Hamburg Hamburg Germany School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China Surrey Institute for People-Centred Artificial Intelligence Centre for Vision Speech and Signal Processing University of Surrey Guildford United Kingdom Shenzhen Key Laboratory of Minimally Invasive Surgical Robotics and System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences China
Few-shot Semantic Segmentation (FSS) aims to adapt a pretrained model to new classes with as few as a single labelled training sample per class. Despite the prototype based approaches have achieved substantial success... 详细信息
来源: 评论
Attention-Driven Dynamic Graph Convolutional Network for Multi-label Image Recognition  16th
Attention-Driven Dynamic Graph Convolutional Network for Mul...
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16th European Conference on computer vision, ECCV 2020
作者: Ye, Jin He, Junjun Peng, Xiaojiang Wu, Wenhao Qiao, Yu ShenZhen Key Lab of Computer Vision and Pattern Recognition Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China School of Biomedical Engineering the Institute of Medical Robotics Shanghai Jiao Tong University Shanghai China
Recent studies often exploit Graph Convolutional Network (GCN) to model label dependencies to improve recognition accuracy for multi-label image recognition. However, constructing a graph by counting the label co-occu... 详细信息
来源: 评论
Unsupervised Multi-Branch Network with High-Frequency Enhancement for Image Dehazing
SSRN
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SSRN 2023年
作者: Sun, Hang Luo, Zhiming Ren, Dong Du, Bo Chang, Laibin Wan, Jun Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering China Three Gorges University Yichang443002 China College of Computer and Information Technology China Three Gorges University Yichang443002 China School of Computer Science Wuhan University Wuhan430072 China Shenzhen University China
Recently, CycleGAN-based methods have been widely applied to the unsupervised image dehazing and achieved significant results. However, most existing CycleGAN-based methods ignore that the input of the generator conta... 详细信息
来源: 评论
Ensemble diverse hypotheses and knowledge distillation for unsupervised cross-subject adaptation
arXiv
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arXiv 2022年
作者: Zhang, Kuangen Chen, Jiahong Wang, Jing Chen, Xinxing Leng, Yuquan de Silva, Clarence W. Fu, Chenglong Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Department of Mechanical and Energy Engineering Southern University of Science and Technology Shenzhen518055 China Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and Technology Shenzhen518055 China Department of Mechanical Engineering The University of British Columbia VancouverBC Canada Department of Electrical and Computer Engineering The University of British Columbia VancouverBC Canada
Recognizing human locomotion intent and activities is important for controlling the wearable robots while walking in complex environments. However, human-robot interface signals are usually user-dependent, which cause... 详细信息
来源: 评论
Provably Convergent Federated Trilevel Learning
arXiv
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arXiv 2023年
作者: Jiao, Yang Yang, Kai Wu, Tiancheng Jian, Chengtao Huang, Jianwei Department of Computer Science and Technology Tongji University China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University China Shanghai Research Institute for Intelligent Autonomous Systems China School of Science and Engineering The Chinese University of Hong Kong Shenzhen China Shenzhen Institute of Artificial Intelligence and Robotics for Society China
Trilevel learning, also called trilevel optimization (TLO), has been recognized as a powerful modelling tool for hierarchical decision process and widely applied in many machine learning applications, such as robust n... 详细信息
来源: 评论
Style Transfer Enabled Sim2Real Framework for Efficient Learning of Robotic Ultrasound Image Analysis Using Simulated Data
arXiv
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arXiv 2023年
作者: Li, keyu Mao, Xinyu Ye, Chengwei Li, Ang Xu, Yangxin Meng, Max Q.-H. The Department of Electronic Engineering The Chinese University of Hong Kong Hong Kong Shenzhen Key Laboratory of Robotics Perception and Intelligence The Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen China The Department of Electronic Engineering The Chinese University of Hong Kong Hong Kong The Department of Electrical and Computer Engineering The University of Alberta Canada
Robotic ultrasound (US) systems have shown great potential to make US examinations easier and more accurate. Recently, various machine learning techniques have been proposed to realize automatic US image interpretatio... 详细信息
来源: 评论
LVAgent: Long Video Understanding by Multi-Round Dynamical Collaboration of MLLM Agents
arXiv
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arXiv 2025年
作者: Chen, Boyu Yue, Zhengrong Chen, Siran Wang, Zikang Liu, Yang Li, Peng Wang, Yali Shenzhen Key Lab of Computer Vision and Pattern Recognition Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China School of Artificial Intelligence University of Chinese Academy of Sciences China Tsinghua University Beijing China Dept. of Comp. Sci. & Tech. Institute for AI Tsinghua University Beijing China Shanghai Artificial Intelligence Laboratory China Shanghai Jiao Tong University China
Existing Multimodal Large Language Models (MLLMs) encounter significant challenges in modeling the temporal context within long videos. Currently, mainstream Agent-based methods use external tools (e.g., search engine... 详细信息
来源: 评论
ReactFace: Online Multiple Appropriate Facial Reaction Generation in Dyadic Interactions
arXiv
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arXiv 2023年
作者: Luo, Cheng Song, Siyang Xie, Weicheng Spitale, Micol Ge, Zongyuan Shen, Linlin Gunes, Hatice Computer Vision Institute College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China Guangdong Provincial Key Laboratory of Intelligent Information Processing Shenzhen University Shenzhen518060 China Department of Computer Science University of Nottingham Ningbo China Ningbo315100 China Computer Sciences University of Exeter ExeterEX4 4PY United Kingdom Department of Computer Science and Technology University of Cambridge CambridgeCB3 0FT United Kingdom Airdoc-Monash Research Centre Monash University Faculty of IT Monash University Melbourne Australia
In dyadic interaction, predicting the listener’s facial reactions is challenging as different reactions could be appropriate in response to the same speaker’s behaviour. Previous approaches predominantly treated thi... 详细信息
来源: 评论
Blueprint Separable Residual Network for Efficient Image Super-Resolution
arXiv
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arXiv 2022年
作者: Li, Zheyuan Liu, Yingqi Chen, Xiangyu Cai, Haoming Gu, Jinjin Qiao, Yu Dong, Chao ShenZhen Key Lab of Computer Vision and Pattern Recognition SIAT-SenseTime Joint Lab Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China University of Macau China Shanghai AI Laboratory Shanghai China The University of Sydney Australia
Recent advances in single image super-resolution (SISR) have achieved extraordinary performance, but the computational cost is too heavy to apply in edge devices. To alleviate this problem, many novel and effective so... 详细信息
来源: 评论
SATO: Stable Text-to-Motion Framework
arXiv
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arXiv 2024年
作者: Chen, Wenshuo Xiao, Hongru Zhang, Erhang Hu, Lijie Wang, Lei Liu, Mengyuan Chen, Chen Shandong University Qingdao China Tongji University Shanghai China King Abdullah University of Science and Technology Jeddah Saudi Arabia Australian National University & Data61/CSIRO Canberra Australia State Key Laboratory of General Artificial Intelligence Peking University Shenzhen Graduate School Shenzhen China Center for Research in Computer Vision University of Central Florida Orlando United States
Is the Text to Motion model robust? Recent advancements in Text to Motion models primarily stem from more accurate predictions of specific actions. However, the text modality typically relies solely on pre-trained Con... 详细信息
来源: 评论