Free parameter self convolutional block attention module

I designed a free parameter self-attention convolutional block module using pytorch.

My work is inspired from CBAM.

I tested my work on CIFAR-100 dataset and residual18 network.

Model Param. Acc1. Acc2. Acc3. Acc4. Acc5. Best Acc. Avg Acc.
resnet18 11.22M 76.36% 75.94% 76.38% 76.03% 76.37% 76.38% 76.22%
with CBAM 11.39M 76.20% 76.55% 76.23% 76.26% 76.16% 76.55% 76.28%
with ZCBAM(Max) 11.22M 75.64% 75.97% 76.20% 75.99% 75.87% 76.20% 75.93%
with ZCBAM(Avg) 11.22M 76.89% 76.77% 76.51% 76.45% 76.68% 76.89% 76.66%
with ZCBAM(Avg&Max) 11.22M 76.46% 76.95% 76.62% 76.34% 76.12% 76.95% 76.50%

If you are interested in my work, please refer to

1 Like

Interesting work!
Thanks for sharing! :slight_smile:



Would you mind if I upload my works like this post here later?

I wonder if my post is not proper to be posted in this community.

I think it would be great to see your work here and discuss it.
Iā€™m not familiar with your current approach, but we have a lot of experienced user in our community, who could discuss your work here. :slight_smile: