File:ATW CNN architecture.png

Summary

Description
English: ATW CNN architecture. Three CNN streams are used to process spatial RGB images, temporal optical flow images, and temporal warped optical flow images, respectively. An attention model is employed to assign temporal weights between snippets for each stream/modality. Weighted sum is used to fuse predictions from the three streams/modalities.
Date
Source Own work
Author Bikingdog

Licensing

I, the copyright holder of this work, hereby publish it under the following license:
w:en:Creative Commons
attribution share alike
This file is licensed under the Creative Commons Attribution-Share Alike 4.0 International license.
You are free:
  • to share – to copy, distribute and transmit the work
  • to remix – to adapt the work
Under the following conditions:
  • attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
  • share alike – If you remix, transform, or build upon the material, you must distribute your contributions under the same or compatible license as the original.
Category:CC-BY-SA-4.0#ATW%20CNN%20architecture.pngCategory:Self-published work
Category:Computer vision Category:Machine learning Category:Deep learning Category:Convolutional neural networks
Category:CC-BY-SA-4.0 Category:Computer vision Category:Convolutional neural networks Category:Deep learning Category:Machine learning Category:Self-published work