Recurrent Spatial-Temporal Attention Network for Action Recognition in Videos

• Published in: IEEE transactions on image processing Vol. 27; no. 3; pp. 1347 - 1360
• Main Authors: Du, Wenbin, Wang, Yali, Qiao, Yu
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.03.2018; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Action recognition; actor-attention regularization; attention-driven fusion; Computer vision; Feature extraction; Human motion; Image recognition; Moving object recognition; Neural networks; Optical imaging; Recognition; Recurrent neural networks; Regularization; RSTAN; spatial-temporal attention; Three-dimensional displays; Videos

Recent years have witnessed the popularity of using recurrent neural network (RNN) for action recognition in videos. However, videos are of high dimensionality and contain rich human dynamics with various motion scales, which makes the traditional RNNs difficult to capture complex action information...