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Implement Attention Augmented Conv2d for improving object detection #2438

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dhananjaisharma10 opened this issue Jan 2, 2021 · 1 comment
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enhancement Improvements or good new features

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@dhananjaisharma10
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🚀 Feature

I would like to add support for the Attention Augmented Conv2d layer from the paper Attention Augmented Convolutional Networks.

Motivation & Examples

This feature is useful for the following key reasons:

  • Attention mechanism from NLP is increasingly being proved to be beneficial for computer vision problems as it helps get a global context in an image.
  • The paper proves that the relative, multi-head attention is better than 4 other attention mechanisms including Squeeze and Excitation attention.
  • It also shows that this layer yields a 1.4% mAP improvement over a strong RetinaNet baseline; this is the main reason for adding it inside detectron2.

The feature would simply be a class inheriting torch.nn.Module.

I look forward to hearing from the team. Thank you!

@dhananjaisharma10 dhananjaisharma10 added the enhancement Improvements or good new features label Jan 2, 2021
@dhananjaisharma10 dhananjaisharma10 changed the title Implement Attention Augmented Conv2d for improved object detection Implement Attention Augmented Conv2d for improving object detection Jan 2, 2021
@tyler-mccarthy
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Any idea wether this was ever implemented?

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