Recent Advances in Video Action Recognition with 3D Convolutions

Kensho HARA  

IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E104-A   No.6   pp.846-856
Publication Date: 2021/06/01
Publicized: 2020/12/07
Online ISSN: 1745-1337
DOI: 10.1587/transfun.2020IMP0012
Type of Manuscript: INVITED PAPER (Special Section on Image Media Quality)
video recognition,  action recognition,  3D convolutions,  survey,  

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The performance of video action recognition has improved significantly in recent decades. Current recognition approaches mainly utilize convolutional neural networks to acquire video feature representations. In addition to the spatial information of video frames, temporal information such as motions and changes is important for recognizing videos. Therefore, the use of convolutions in a spatiotemporal three-dimensional (3D) space for representing spatiotemporal features has garnered significant attention. Herein, we introduce recent advances in 3D convolutions for video action recognition.