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2019年7月5日學術報告(劉俊 博士,新加坡南洋理工大學)
2019年07月03日16時 人評論

報告題目:Context Modeling for Human Action Recognition

報告時間:201975日(周)上午10:00

報告地點:葡京娛樂场APPB404會議室

報告人:劉俊

報告人單位:新加坡南洋理工大學

 

報告人簡介:

Jun Liu is completing his PhD work at the Rapid-Rich Object Search Lab, Nanyang Technological University, Singapore. He obtained the M.Sc degree in Computer Science from Fudan University, China in 2014, and the B.Eng degree in Software Engineering from Central South University, China in 2011. He published 4 TPAMI, 1 TIP, 2 CVPR, and 1 ECCV papers as the first author during his PhD study. His Google Scholar citations reach 1200. His research interests include computer vision and deep learning. 

報告摘要

Human action understanding is an important and hot research problem due to its wide applications in security surveillance, self-driving vehicles, robotics, and human-machine interaction. Spatio-temporal context modeling and learning is crucial for this task. In this talk, several deep learning architectures for human action recognition will be introduced, which include networks on modeling the spatio-temporal context dependencies in action video sequences, frameworks on selecting the most important and proper context for action analysis, and mechanisms on improving robustness of deep networks by taking advantage of the spatio-temporal context information.   

 

邀請人:杜博 教授


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