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DenseNet for Dense Flow

Abstract: 

Efficient Large-Scale Video Understanding in The Wild

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Paper Details

Authors:
Yi Zhu,Shawn Newsam
Submitted On:
16 September 2017 - 2:54am
Short Link:
Type:
Poster
Event:
Presenter's Name:
Yi Zhu
Paper Code:
PhD forum
Document Year:
2017
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Document Files

ICIP17_phd_forum_poster.pdf

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[1] Yi Zhu,Shawn Newsam, "DenseNet for Dense Flow", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2182. Accessed: Dec. 18, 2017.
@article{2182-17,
url = {http://sigport.org/2182},
author = {Yi Zhu;Shawn Newsam },
publisher = {IEEE SigPort},
title = {DenseNet for Dense Flow},
year = {2017} }
TY - EJOUR
T1 - DenseNet for Dense Flow
AU - Yi Zhu;Shawn Newsam
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2182
ER -
Yi Zhu,Shawn Newsam. (2017). DenseNet for Dense Flow. IEEE SigPort. http://sigport.org/2182
Yi Zhu,Shawn Newsam, 2017. DenseNet for Dense Flow. Available at: http://sigport.org/2182.
Yi Zhu,Shawn Newsam. (2017). "DenseNet for Dense Flow." Web.
1. Yi Zhu,Shawn Newsam. DenseNet for Dense Flow [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2182