FEXNet: Foreground Extraction Network for Human Action Recognition

• Published in: IEEE transactions on circuits and systems for video technology Vol. 32; no. 5; pp. 3141 - 3151
• Main Authors: Shen, Zhongwei, Wu, Xiao-Jun, Xu, Tianyang
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.05.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: action recognition; Convolutional neural networks; Feature extraction; Feature maps; Foreground-related features; Human activity recognition; Human motion; Image recognition; Iron; Modelling; Modules; Solid modeling; spatiotemporal modeling; Spatiotemporal phenomena; Three-dimensional displays; Two dimensional models

As most human actions in video sequences embody the continuous interactions between foregrounds rather than the background scene, it is significant to disentangle these foregrounds from the background for advanced action recognition systems. In this paper, therefore, we propose a Foreground EXtracti...