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检索条件"机构=Computer Vision and Pattern Recognition"
818 条 记 录,以下是301-310 订阅
排序:
ICDAR 2019 CROHME + TFD: Competition on recognition of Handwritten Mathematical Expressions and Typeset Formula Detection
ICDAR 2019 CROHME + TFD: Competition on Recognition of Handw...
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International Conference on Document Analysis and recognition
作者: Mahshad Mahdavi Richard Zanibbi Harold Mouchere Christian Viard-Gaudin Utpal Garain Document and Pattern Recognition Lab Rochester Institute of Technology Rochester NY USA University of Nantes Nantes France LS2N - UMR CNRS 6004 University of Nantes Nantes France Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India
We summarize the tasks, protocol, and outcome for the 6th Competition on recognition of Handwritten Mathematical Expressions (CROHME), which includes a new formula detection in document images task (+ TFD). For CROHME... 详细信息
来源: 评论
RankSRGAN: Generative Adversarial Networks With Ranker for Image Super-Resolution
RankSRGAN: Generative Adversarial Networks With Ranker for I...
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International Conference on computer vision (ICCV)
作者: Wenlong Zhang Yihao Liu Chao Dong Yu Qiao 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 Chinese Academy of Sciences
Generative Adversarial Networks (GAN) have demonstrated the potential to recover realistic details for single image super-resolution (SISR). To further improve the visual quality of super-resolved results, PIRM2018-SR... 详细信息
来源: 评论
Modulating image restoration with continual levels via adaptive feature modification layers
arXiv
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arXiv 2019年
作者: He, Jingwen Dong, Chao Qiao, Yu ShenZhen Key Lab of Computer Vision and Pattern Recognition SIAT-SenseTime Joint Lab Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China Chinese University of Hong Kong
In image restoration tasks, like denoising and superresolution, continual modulation of restoration levels is of great importance for real-world applications, but has failed most of existing deep learning based image ... 详细信息
来源: 评论
Robust Text Line Detection in Equipment Nameplate Images*
Robust Text Line Detection in Equipment Nameplate Images*
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IEEE International Conference on Robotics and Biomimetics
作者: Jiangyu Lai Lanqing Guo Yu Qiao Xiaolong Chen Zhengfu Zhang Canping Liu Ying Li Bin Fu Guangzhou Power Supply Bureau Co. Ltd. Guangzhou China ShenZhen Key Lab of Computer Vision and Pattern Recognition Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences
Scene text detection for equipment nameplates in the wild is important for equipment inspection robot since it enables inspection robot to take specific actions for different equipment's. Although text detection i...
来源: 评论
Box-driven Class-wise Region Masking and Filling Rate Guided Loss for Weakly Supervised Semantic Segmentation
Box-driven Class-wise Region Masking and Filling Rate Guided...
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IEEE/CVF Conference on computer vision and pattern recognition
作者: Chunfeng Song Yan Huang Wanli Ouyang Liang Wang Center for Research on Intelligent Perception and Computing (CRIPAC) National Laboratory of Pattern Recognition (NLPR) Institute of Automation Chinese Academy of Sciences (CASIA) The University of Sydney SenseTime Computer Vision Research Group
Semantic segmentation has achieved huge progress via adopting deep Fully Convolutional Networks (FCN). However, the performance of FCN based models severely rely on the amounts of pixel-level annotations which are exp... 详细信息
来源: 评论
Frame attention networks for facial expression recognition in videos
arXiv
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arXiv 2019年
作者: Meng, Debin Peng, Xiaojiang Wang, Kai Qiao, Yu Shenzhen Institutes of Advanced Technology Chinese Academy of Science Shenzhen China Shenzhen Key Lab of Computer Vision and Pattern Recognition Shenzhen China University of Chinese Academy of Sciences Beijing China
The video-based facial expression recognition aims to classify a given video into several basic emotions. How to integrate facial features of individual frames is crucial for this task. In this paper, we propose the F... 详细信息
来源: 评论
Affine Non-negative Collaborative Representation Based pattern Classification
arXiv
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arXiv 2020年
作者: Yin, He-Feng Wu, Xiao-Jun Feng, Zhen-Hua Kittler, Josef School of Artificial Intelligence and Computer Science Jiangnan University Wuxi214122 China Jiangsu Provincial Engineering Laboratory of Pattern Recognition and Computational Intelligence Jiangnan University Wuxi214122 China Department of Computer Science University of Surrey GuildfordGU2 7XH United Kingdom Centre for Vision Speech and Signal Processing University of Surrey GuildfordGU2 7XH United Kingdom
—During the past decade, representation-based classification methods have received considerable attention in pattern recognition. In particular, the recently proposed non-negative representation based classification ... 详细信息
来源: 评论
RankSRGAN: Generative adversarial networks with ranker for image super-resolution
arXiv
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arXiv 2019年
作者: Zhang, Wenlong Liu, Yihao Dong, Chao Qiao, Yu 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 Chinese Academy of Sciences
Generative Adversarial Networks (GAN) have demonstrated the potential to recover realistic details for single image super-resolution (SISR). To further improve the visual quality of super-resolved results, PIRM2018-SR... 详细信息
来源: 评论
A Kalman filtering induced heuristic optimization based partitional data clustering
arXiv
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arXiv 2019年
作者: Pakrashi, Arjun Chaudhuri, Bidyut B. Insight Centre for Data Analytics University College Dublin Ireland Computer Vision & Pattern Recognition Unit Indian Statistical Institute 203 B.T. Road Kolkata700108 India
Clustering algorithms have regained momentum with recent popularity of data mining and knowledge discovery approaches. To obtain good clustering in reasonable amount of time, various meta-heuristic approaches and thei... 详细信息
来源: 评论
A comprehensive study on temporal modeling for online action detection
arXiv
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arXiv 2020年
作者: Wang, Wen Peng, Xiaojiang Qiao, Yu Cheng, Jian School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu Sichuan611731 China ShenZhen Key Lab of Computer Vision and Pattern Recognition SIAT-SenseTime Joint Lab Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences SIAT Branch Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences
—Online action detection (OAD) is a practical yet challenging task, which has attracted increasing attention in recent years. A typical OAD system mainly consists of three modules: a frame-level feature extractor whi... 详细信息
来源: 评论