activity
20182021
most citedLearning to Recognize 3D Human Action from A New Skeleton-based Representation Using Deep Convolutional Neural Networks

40 citations · 42 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV2021

Sparse LiDAR and Stereo Fusion (SLS-Fusion) for Depth Estimationand 3D Object Detection

Nguyen Anh Minh Mai, Pierre Duthon, Louahdi Khoudour +2

The ability to accurately detect and localize objects is recognized as being the most important for the perception of self-driving cars. From 2D to 3D object detection, the most di…

cs.CV20192 cited

A Unified Deep Framework for Joint 3D Pose Estimation and Action Recognition from a Single RGB Camera

Huy Hieu Pham, Houssam Salmane, Louahdi Khoudour +3

We present a deep learning-based multitask framework for joint 3D human pose estimation and action recognition from RGB video sequences. Our approach proceeds along two stages. In…

cs.CV201840 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

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

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…