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DeepVI: A Novel Framework for Learning Deep View-Invariant Human Action Representations using a Single RGB Camera
PAPADOPOULOS, Konstantinos; GHORBEL, Enjie; OYEDOTUN, Oyebade et al.
2020In IEEE International Conference on Automatic Face and Gesture Recognition, Buenos Aires 18-22 May 2020
Peer reviewed
 

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Disciplines :
Computer science
Author, co-author :
PAPADOPOULOS, Konstantinos ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
GHORBEL, Enjie  ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
OYEDOTUN, Oyebade ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
AOUADA, Djamila  ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
OTTERSTEN, Björn  ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
External co-authors :
no
Language :
English
Title :
DeepVI: A Novel Framework for Learning Deep View-Invariant Human Action Representations using a Single RGB Camera
Publication date :
2020
Event name :
IEEE International Conference on Automatic Face and Gesture Recognition
Event date :
from 18-05-2020 to 22-05-2020
Main work title :
IEEE International Conference on Automatic Face and Gesture Recognition, Buenos Aires 18-22 May 2020
Peer reviewed :
Peer reviewed
FnR Project :
FNR10415355 - 3d Action Recognition Using Refinement And Invariance Strategies For Reliable Surveillance, 2015 (01/06/2016-31/05/2019) - Bjorn Ottersten
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since 11 February 2020

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