output
20082025
most citedExploiting deep residual networks for human action recognition from skeletal data

85 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions
Showing 2018 · cs.CVShow all

4 papers · 2 filters

cs.CV2018★ 40 cited

Learning to Recognize 3D Human Action from A New Skeleton-based Representation Using Deep Convolutional Neural Networks

Huy-Hieu Pham, Louahdi Khoudour, Alain Crouzil +2

Recognizing human actions in untrimmed videos is an important challenging task. An effective 3D motion representation and a powerful learning model are two key factors influencing…

cs.CV2018★ 6 cited

Skeletal Movement to Color Map: A Novel Representation for 3D Action Recognition with Inception Residual Networks

Huy Hieu Pham, Louahdi Khoudour, Alain Crouzil +2

We propose a novel skeleton-based representation for 3D action recognition in videos using Deep Convolutional Neural Networks (D-CNNs). Two key issues have been addressed: First, h…

cs.CV2018★ 85 cited

Exploiting deep residual networks for human action recognition from skeletal data

Huy-Hieu Pham, Louahdi Khoudour, Alain Crouzil +2

The computer vision community is currently focusing on solving action recognition problems in real videos, which contain thousands of samples with many challenges. In this process,…

cs.CV2018★ 18 cited

Learning and Recognizing Human Action from Skeleton Movement with Deep Residual Neural Networks

Huy-Hieu Pham, Louahdi Khoudour, Alain Crouzil +2

Automatic human action recognition is indispensable for almost artificial intelligent systems such as video surveillance, human-computer interfaces, video retrieval, etc. Despite a…