I designed a free parameter self-attention convolutional block module using pytorch.
My work is inspired from CBAM 9.
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
ZCBAM 15.