Open Access

REVIEW

Action Recognition and Detection Based on Deep Learning: A Comprehensive Summary

by Yong Li^1,4, Qiming Liang^2,*, Bo Gan³, Xiaolong Cui⁴

1 College of Information Engineering, Engineering University of PAP, Xi’an, 710086, China
2 PAP of Heilongjiang Province, Heihe Detachment, Heihe, 164300, China
3 National Key Laboratory of Science and Technology on Electromagnetic Energy, Naval University of Engineering, Wuhan, 430033, China
4 Joint Laboratory of Counter Terrorism Command and Information Engineering, Engineering University of PAP, Xi’an, 710086, China

* Corresponding Author: Qiming Liang. Email:

Computers, Materials & Continua 2023, 77(1), 1-23. https://doi.org/10.32604/cmc.2023.042494

Received 01 June 2023; Accepted 30 August 2023; Issue published 31 October 2023

Abstract

Action recognition and detection is an important research topic in computer vision, which can be divided into action recognition and action detection. At present, the distinction between action recognition and action detection is not clear, and the relevant reviews are not comprehensive. Thus, this paper summarized the action recognition and detection methods and datasets based on deep learning to accurately present the research status in this field. Firstly, according to the way that temporal and spatial features are extracted from the model, the commonly used models of action recognition are divided into the two stream models, the temporal models, the spatiotemporal models and the transformer models according to the architecture. And this paper briefly analyzes the characteristics of the four models and introduces the accuracy of various algorithms in common data sets. Then, from the perspective of tasks to be completed, action detection is further divided into temporal action detection and spatiotemporal action detection, and commonly used datasets are introduced. From the perspectives of the two-stage method and one-stage method, various algorithms of temporal action detection are reviewed, and the various algorithms of spatiotemporal action detection are summarized in detail. Finally, the relationship between different parts of action recognition and detection is discussed, the difficulties faced by the current research are summarized in detail, and future development was prospected.

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Keywords

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