Attentive Information Bottleneck

Overview

Pytorch code for "Information Bottleneck Approach to Spatial Attention Learning (IJCAI2021)".

What's in this repo so far:

• Code for CIFAR-10/-100 experiments (VGG backbone) (this folder)
• Code for CIFAR-10/-100 experiments (WRN backbone) (this folder)
• Code for CUB experiments (VGG and WRN backbone) (this folder)

Reference Codes

[1] Attention Transfer

[2] Attention Branch Network

[3] LearnToPayAttention

Requirements

Create an anaconda environment:

$ conda env create -f environment.yaml

To run the code:

$ source activate torch36
$ <run_python_command> # see the examples in sub folders.

Citation

If you find this repository is useful, please cite the following reference.

@inproceedings{lai2021information,
    title = {Information Bottleneck Approach to Spatial Attention Learning},
    author = {Lai, Qiuxia and Li, Yu and Zeng, Ailing and Liu, Minhao and Sun, Hanqiu and Xu, Qiang},
    booktitle = {International Joint Conference on Artificial Intelligence},
    year = {2021}
}