Skeleton-Based Action Recognition With Gated Convolutional Neural Networks

• Published in: IEEE transactions on circuits and systems for video technology Vol. 29; no. 11; pp. 3247 - 3257
• Main Authors: Cao, Congqi, Lan, Cuiling, Zhang, Yifan, Zeng, Wenjun, Lu, Hanqing, Zhang, Yanning
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.11.2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: action recognition; Artificial neural networks; Bells; Convolutional neural networks; gated connection; Image classification; Learning; Logic gates; Matrix converters; Neural networks; Permutations; Recognition; Recurrent neural networks; Skeleton; Task analysis; Three-dimensional displays

For skeleton-based action recognition, most of the existing works used recurrent neural networks. Using convolutional neural networks (CNNs) is another attractive solution considering their advantages in parallelization, effectiveness in feature learning, and model base sufficiency. Besides these, s...