MEST: An Action Recognition Network with Motion Encoder and Spatio-Temporal Module.As a sub-field of video content analysis, action recognition has received extensive attention in recent years, which aims to recognize human actions in videos.  In this paper, an efficient network to extract spatio-temporal information with relatively low computational load (dubbed MEST) is proposed.  Experiments are conducted on five public datasets of action recognition, Something-Something-V1 and -V2, Jester, UCF101 and HMDB51, where MEST exhibits competitive performance compared to other popular methods. 
MEST
MEST: An Action Recognition Network with Motion Encoder and Spatio-Temporal Module.As a sub-field of video content analysis, action recognition has received extensive attention in recent years, which aims to recognize human actions in videos.  In this paper, an efficient network to extract spatio-temporal information with relatively low computational load (dubbed MEST) is proposed.  Experiments are conducted on five public datasets of action recognition, Something-Something-V1 and -V2, Jester, UCF101 and HMDB51, where MEST exhibits competitive performance compared to other popular methods. 
MEST