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检索条件"机构=Shenzhen Key Laboratory of Robotics and Computer Vision"
493 条 记 录,以下是321-330 订阅
排序:
UniTSFace: Unified Threshold Integrated Sample-to-Sample Loss for Face Recognition
arXiv
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arXiv 2023年
作者: Li, Qiufu Jia, Xi Zhou, Jiancan Shen, Linlin Duan, Jinming National Engineering Laboratory for Big Data System Computing Technology Shenzhen University China Computer Vision Institute Shenzhen University China School of Computer Science University of Birmingham United Kingdom Aqara Lumi United Technology Co. Ltd China Alan Turing Institute United Kingdom SZU Branch Shenzhen Institute of Artificial Intelligence and Robotics for Society China
Sample-to-class-based face recognition models can not fully explore the cross-sample relationship among large amounts of facial images, while sample-to-sample-based models require sophisticated pairing processes for t... 详细信息
来源: 评论
Age-Group Classification of Facial Images
Age-Group Classification of Facial Images
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International Conference on Machine Learning and Applications (ICMLA)
作者: Li Liu Jianming Liu Jun Cheng Shenzhen Institutes of Advanced Technolozv Chinese Academv of Science Computer Science and Engineering Department School of Guilin University of Electronic Technology Guilin China Guangdong Provincial Key Laboratory of Robotics and Intelligent System
This paper presents the age-group classification based on facial images. We perform age-group classification by dividing ages into five age groups according to the incremental regulation of age. Features are extracted... 详细信息
来源: 评论
Augmented Box Replay: Overcoming Foreground Shift for Incremental Object Detection
Augmented Box Replay: Overcoming Foreground Shift for Increm...
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International Conference on computer vision (ICCV)
作者: Yuyang Liu Yang Cong Dipam Goswami Xialei Liu Joost van de Weijer State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences University of Chinese Academy of Sciences South China University of Technology Computer Vision Center Barcelona VCIP CS Nankai University Department of Computer Science Universitat Autònoma de Barcelona
In incremental learning, replaying stored samples from previous tasks together with current task samples is one of the most efficient approaches to address catastrophic forgetting. However, unlike incremental classifi...
来源: 评论
MM-3DScene: 3D Scene Understanding by Customizing Masked Modeling with Informative-Preserved Reconstruction and Self-Distilled Consistency
arXiv
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arXiv 2022年
作者: Xu, Mingye Xu, Mutian He, Tong Ouyang, Wanli Wang, Yali Han, Xiaoguang Qiao, Yu The Guangdong Provincial Key Laboratory of Computer Vision and Virtual Reality Technology Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China SSE CUHKSZ China University of Chinese Academy of Sciences China Shanghai Artificial Intelligence Laboratory China FNii CUHKSZ China
Masked Modeling (MM) has demonstrated widespread success in various vision challenges, by reconstructing masked visual patches. Yet, applying MM for large-scale 3D scenes remains an open problem due to the data sparsi... 详细信息
来源: 评论
Pseudo-label Guided Cross-video Pixel Contrast for Robotic Surgical Scene Segmentation with Limited Annotations
arXiv
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arXiv 2022年
作者: Yu, Yang Zhao, Zixu Jin, Yueming Chen, Guangyong Dou, Qi Heng, Pheng-Ann The Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong Guangdong Provincial Key Laboratory of Computer Vision and Virtual Reality Technology Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China The Department of Computer Science University College London United Kingdom Zhejiang Lab China
Surgical scene segmentation is fundamentally crucial for prompting cognitive assistance in robotic surgery. However, pixel-wise annotating surgical video in a frame-by-frame manner is expensive and time consuming. To ... 详细信息
来源: 评论
BTI Aging Monitoring based on SRAM Start-up Behavior
BTI Aging Monitoring based on SRAM Start-up Behavior
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Asian Test Symposium (ATS)
作者: Shengyu Duan Peng Wang Gaole Sai School of Computer Engineering and Science Shanghai University Shanghai China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences China State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology China
Bias Temperature Instability (BTI) is one of the dominant CMOS aging mechanisms. It causes time-dependent variation, threatening circuit lifetime reliability. BTI-induced circuit errors are not detectable at the fabri... 详细信息
来源: 评论
Few Shot Transfer Active Learning for Logo Detection in Sports Video
SSRN
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SSRN 2022年
作者: Su, Hang Qiu, Guoping College of Electronic and Information Engineering Shenzhen University Shenzhen518052 China Guangdong Key Lab for Intelligent Information Processing Shenzhen University Shenzhen518052 China Shenzhen Institute of AI and Robotics for Society Shenzhen518172 China Pengcheng Laboratory Shenzhen518055 China School of Computer Science University of Nottingham NottinghamNG8 1BB United Kingdom
We exploit the power of deep convolutional neural network (DCNN) and take advantage of established datasets from existing applications to develop a deep transfer active learning (DTAL) algorithm to select the most val... 详细信息
来源: 评论
Clustering-Based Representation Learning through Output Translation and Its Application to Remote-Sensing Images
arXiv
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arXiv 2021年
作者: Li, Qinglin Li, Bin Garibaldi, Jonathan M. Qiu, Guoping College of Electronic and Information Engineering Shenzhen University Shenzhen518052 China Guangdong Key Lab for Intelligent Information Processing Shenzhen University Shenzhen518052 China School of Computer Science The University of Nottingham NottinghamNG8 1BB United Kingdom Shenzhen Institute of AI and Robotics for Society Shenzhen518172 China Pengcheng Laboratory Shenzhen518055 China
In supervised deep learning, learning good representations for remote-sensing images (RSI) relies on manual annotations. However, in the area of remote sensing, it is hard to obtain huge amounts of labeled data. Recen... 详细信息
来源: 评论
FeCAM: Exploiting the Heterogeneity of Class Distributions in Exemplar-Free Continual Learning
arXiv
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arXiv 2023年
作者: Goswami, Dipam Liu, Yuyang Twardowski, Bartlomiej van de Weijer, Joost Department of Computer Science Universitat Autònoma de Barcelona Spain Computer Vision Center Barcelona Spain University of Chinese Academy of Sciences China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences China IDEAS-NCBR
Exemplar-free class-incremental learning (CIL) poses several challenges since it prohibits the rehearsal of data from previous tasks and thus suffers from catastrophic forgetting. Recent approaches to incrementally le... 详细信息
来源: 评论
Spatial Pyramid Pooling based Convolutional Autoencoder Network for Loop Closure Detection
Spatial Pyramid Pooling based Convolutional Autoencoder Netw...
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IEEE International Conference on Real-time Computing and robotics (RCAR)
作者: Rong Xiang Yuan Liu Qieshi Zhang Jun Cheng School of Computer Science and Information Security Guilin University of Electronic Technology GuangXi China Guangdong Provincial Key Laboratory of Computer Vision and Virtual Reality Technology Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China The Chinese University of Hong Kong Hong Kong China
Loop closure detection is a crucial module in simultaneous localization and mapping (SLAM), which reduces accumulative error in building environment map. Traditional appearance-based methods for loop closure detection... 详细信息
来源: 评论