Learning spatio-temporal representation with local and global diffusion

Learning spatio-temporal representation with local and global diffusion

Convolutional Neural Networks (CNN) have been regarded as a powerful class of models for visual recognition problems. Nevertheless, the convolutional filters in these networks are local operations while ignoring the large-range dependency. Such drawback becomes even worse particularly for video reco...

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Bibliographic Details
Main Authors: QIU, Zhaofan, YAO, Ting, NGO, Chong-wah, TIAN, Xinmei, MEI, Tao
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2019
Subjects:
Video Analytics
Graphics and Human Computer Interfaces
OS and Networks
Online Access:https://ink.library.smu.edu.sg/sis_research/6458
https://ink.library.smu.edu.sg/context/sis_research/article/7461/viewcontent/Qiu_Learning_Spatio_Temporal_Representation_With_Local_and_Global_Diffusion_CVPR_2019_paper.pdf
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Institution: Singapore Management University
Language: English

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https://ink.library.smu.edu.sg/sis_research/6458
https://ink.library.smu.edu.sg/context/sis_research/article/7461/viewcontent/Qiu_Learning_Spatio_Temporal_Representation_With_Local_and_Global_Diffusion_CVPR_2019_paper.pdf

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