**5. Conclusions**

In this paper, we proposed an action recognition framework by utilizing frame-level deep features of the 3D-CNN and processing it through LSTM. First, we introduced a 3Dconv-based model MMN and its iterative training method to integrate the discriminative information of a video into motion maps. Three-dimensional convolutional components extract compact and efficient spatiotemporal features from the input video in the form of feature maps. Moreover, we design a linear weighted fusion method to effectively fuse spatial and temporal feature maps. Finally, we adopt LSTM encoder/decoder to obtain video level representations to conduct video classification. According to the experimental results, our model takes the complementary information contained in multiple features (both spatial and motion features). It is also proof that the motion maps generated by our model intuitively integrate the dynamic information in an efficient manner, and that they retain more discriminative aspects. Moreover, our fusion method makes the features more detailed and specific. To verify the effectiveness of our framework, extensive experiments have been carried out on benchmark datasets, and the obtained results showed that our approach achieves promising performance.

**Author Contributions:** For research articles with several authors, a short paragraph specifying their individual contributions must be provided. The following statements should be used "Conceptualization, S.A. and J.W.; Methodology, S.A. and Z.F.; Software, T.U.H.; Validation, S.A., T.U.H. and J.W.; Formal Analysis, S.A. and T.U.H.; Investigation, S.A. and T.U.H.; Resources, J.W.; Data Curation, T.U.H.; Writing-Original Draft Preparation, S.A.; Writing-Review & Editing, S.A. and Z.F.; Visualization, S.A.; Supervision, J.W.; Project Administration, J.W. and Z.F.

**Acknowledgments:** The research was supported by Research Institute of Communication Technology (RICT) in Beijing Institute of Technology.

**Conflicts of Interest:** The authors declare no conflict of interest.
