BAM & CBAM Pytorch
Pytorch implementation of BAM and CBAM.
BAM & CBAM Pytorch
This code purpose to evaluate of popular attention model architectures, such as BAM, CBAM on the CIFAR dataset.
Getting Started
$ git clone https://github.com/asdf2kr/BAM-CBAM-pytorch.git
$ cd BAM-CBAM-pytorch
$ python main.py --arch bam (default: bam network based on resnet50)
Performance
The table below shows models, dataset and performances
Model | Backbone | Dataset | Top-1 | Top-5 | Size |
---|---|---|---|---|---|
ResNet | resnet50 | CIFAR-100 | 78.93% | - | 23.70M |
BAM | resnet50 | CIFAR-100 | 79.62% | - | 24.06M |
CBAM | resnet50 | CIFAR-100 | 81.02% | - | 26.23M |
To-do
Simple setup readme Add ImageNet datasets.