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Pytorch implementation of "Compact Global Descriptor for Neural Networks" (CGD).

License: BSD 2-Clause "Simplified" License

Python 99.80% Shell 0.20%

attention-mechanism convolutional-neural-networks pytorch efficient efficient-attention attention-model

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compact-global-descriptor's Issues

Hello, I can't find your paper online. Can you send it to me?

Hello, I can't find your paper online. Can you send it to me?

Spatiotemporal modeling

Hi, I am little bit confused about the implementation of CGD for spatiotemporal model.

In the paper, it is stated that the weight is shared and the output of each frames is summed to get z. To do so, should I loop through all the frames and run AttentionLayer for every frames and sum all the output?

It would be greatly appreciated if you could elaborate more on spatiotemporal setting.

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