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检索条件"机构=Pattern Recognition Lab Computer Vision Group"
332 条 记 录,以下是191-200 订阅
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Compressed sensing ensemble classifier for human detection
Compressed sensing ensemble classifier for human detection
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4th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2013
作者: Zhang, Baochang Liu, Juan Gao, Yongsheng Liu, Jianzhuang Science and Technology on Aircraft Control Laboratory School of Automation Science and Electrical Engineering BeiHang University Beijing 100191 China School of Engineering Griffith University Australia Shenzhen Key Lab for Computer Vision and Pattern Recognition Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China Department of Information Engineering Chinese University of Hong Kong Hong Kong Hong Kong
This paper proposes a novel Compressed Sensing Ensemble Classifier (CSEC) for human detection. The proposed CSEC employs the compressed sensing technique to get a more sparse model with a more reasonable selection of ... 详细信息
来源: 评论
Color constancy and non-uniform illumination: Can existing algorithms work?
Color constancy and non-uniform illumination: Can existing a...
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International Conference on computer vision Workshops (ICCV Workshops)
作者: Michael Bleier Christian Riess Shida Beigpour Eva Eibenberger Elli Angelopoulou Tobias Tröger André Kaup Pattern Recognition Lab University of Erlangen-Nuremberg Germany Computer Vision Center Universidad Autónoma de Barcelona Spain Multimedia Communications and Signal Processing University of Erlangen-Nuremberg Germany
The color and distribution of illuminants can significantly alter the appearance of a scene. The goal of color constancy (CC) is to remove the color bias introduced by the illuminants. Most existing CC algorithms assu... 详细信息
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Multiple Transfer Learning and Multi-label Balanced Training Strategies for Facial AU Detection In the Wild
Multiple Transfer Learning and Multi-label Balanced Training...
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IEEE computer Society Conference on computer vision and pattern recognition Workshops (CVPRW)
作者: Sijie Ji Kai Wang Xiaojiang Peng Jianfei Yang Zhaoyang Zeng Yu Qiao Nanyang Technological University Singapore ShenZhen Key Lab of Computer Vision and Pattern Recognition SIAT-SenseTime Joint Lab Shenzhen Institutes of Advanced Technology Chinese Academy of Science Sun Yat-Sen University China
This paper 1 presents SIAT-NTU solution and results of facial action unit (AU) detection in the EmotiNet Challenge 2020. The task aims to detect 23 AUs from facial images in the wild, and its main difficulties lie in... 详细信息
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Memory efficient fingerprint verification
Memory efficient fingerprint verification
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IEEE International Conference on Image Processing
作者: C. Beleznai H. Ramoser B. Wachmann J. Birchbauer H. Bischof W. Kropatsch Advanced Computer Vision Austrian Research Centre Seibersdorf Vienna Austria Programm-und Systementwicklung Siemens AG Österreich Graz Austria Pattern Recognition and Image Processing Group University of Technology Vienna Vienna Austria
Fingerprint recognition and verification are often based on local fingerprint features, usually ridge endings or terminations, also called minutiae. By exploiting the structural uniqueness of the image region around a... 详细信息
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Optimal sub-shape models by minimum description length
Optimal sub-shape models by minimum description length
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Conference on computer vision and pattern recognition (CVPR)
作者: G. Langs P. Peloschek H. Bischof Institute for Computer Graphics and Vision Graz University of Technology Graz Austria Pattern Recognition and Image Processing Group University of Technology Vienna Vienna Austria Department of Clinical Radiology Vienna Medical University Vienna Austria
Active shape models are powerful and widely used tool to interpret complex image data. By building models of shape variation they enable search algorithms to use a priori knowledge in an efficient and gainful way. How... 详细信息
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Self-supervised multi-view stereo via effective co-segmentation and data-augmentation
arXiv
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arXiv 2021年
作者: Xu, Hongbin Zhou, Zhipeng Qiao, Yu Kang, Wenxiong Wu, Qiuxia ShenZhen Key Lab of Computer Vision and Pattern Recognition Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China Shanghai AI Lab Shanghai China South China University of Technology Guangzhou China
Recent studies have witnessed that self-supervised methods based on view synthesis obtain clear progress on multiview stereo (MVS). However, existing methods rely on the assumption that the corresponding points among ... 详细信息
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Blind path obstacle detector using smartphone camera and line laser emitter
Blind path obstacle detector using smartphone camera and lin...
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International Conference on Technology and Innovation in Sports, Health and Wellbeing (TISHW)
作者: Rimon Saffoury Peter Blank Julian Sessner Benjamin H. Groh Christine F. Martindale Eva Dorschky Joerg Franke Bjoern M. Eskofier Digital Sports Group Pattern Recognition Lab Department of Computer Science Institute for Factory Automation and Production Systems Friedrich-Alexander University Erlangen-Numberg (FAU) Erlangen Germany
Visually impaired people find navigating within unfamiliar environments challenging. Many smart systems have been proposed to help blind people in these difficult, often dangerous, situations. However, some of them ar... 详细信息
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Suppressing Uncertainties for Large-Scale Facial Expression recognition
Suppressing Uncertainties for Large-Scale Facial Expression ...
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Conference on computer vision and pattern recognition (CVPR)
作者: Kai Wang Xiaojiang Peng Jianfei Yang Shijian Lu Yu Qiao ShenZhen Key Lab of Computer Vision and Pattern Recognition SIAT-SenseTime Joint Lab Shenzhen Institutes of Advanced Technology Chinese Academy of Science University of Chinese Academy of Sciences China Nanyang Technological University Singapore
Annotating a qualitative large-scale facial expression dataset is extremely difficult due to the uncertainties caused by ambiguous facial expressions, low-quality facial images, and the subjectiveness of annotators. T... 详细信息
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Suppressing uncertainties for large-scale facial expression recognition
arXiv
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arXiv 2020年
作者: Wang, Kai Peng, Xiaojiang Yang, Jianfei Lu, Shijian Qiao, Yu ShenZhen Key Lab of Computer Vision and Pattern Recognition SIAT-SenseTime Joint Lab Shenzhen Institutes of Advanced Technology Chinese Academy of Science University of Chinese Academy of Sciences China Nanyang Technological University Singapore
Annotating a qualitative large-scale facial expression dataset is extremely difficult due to the uncertainties caused by ambiguous facial expressions, low-quality facial images, and the subjectiveness of annotators. T... 详细信息
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Signature segmentation and recognition from scanned documents
Signature segmentation and recognition from scanned document...
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International Conference on Intelligent Systems Design and Applications (ISDA)
作者: Ranju Mandal Partha Pratim Roy Umapada Pal Michael Blumenstein School of Information and Communication Technology Griffith University Queensland Australia Automation Engineering Department Synchromedia Lab Montreal Canada Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India
Signature as a query is important for content-based document image retrieval from a scanned document repository. This paper presents a two-stage approach towards automatic signature segmentation and recognition from s... 详细信息
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