CVQN

This repository is for Channel-Level Variable Quantization Network for Deep Image Compression.

(to appear in IJCAI, 2020)

By Zhisheng Zhong, Hiroaki Akutsu and Kiyoharu Aizawa.

Table of contents

• Overview
• Data Download
• Folder Structure
• Training and Evaluation

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Overview

Framework of the channel-level variable quantization network.

Dependencies

• Python (3.7.5)
• PyTorch (1.2.0)
• torchvision (0.4.0)
• PyYaml (5.2)
• tensorboard (2.0.1)

Data Download

These training datasets can be downloaded from the above links.

• DIV2K
• Flickr2K
• CLIC2019

Folder Structure

Your CVQN folder may be similar to this:

-- logs (log folder)
-- ckps (checkpoint folder)
-- tbs (tensorboard log folder)
-- yaml (yaml folder)
-- pytorch_msssim
-- config
-- *.py

Training and Evaluation

Please modify the training & evaluation dataset path in yaml/XXX.yaml.

You can also modify other parameters to change the model and training strategy in the same file.

An example to train a model:

python main_train_eval.py --config yaml/XXX.yaml

Citation

If you find this code useful, please cite our paper:

@inproceedings{Zhong2020CVQN,
  title     = {Channel-Level Variable Quantization Network for Deep Image Compression},
  author    = {Zhong, Zhisheng and Akutsu, Hiroaki and Aizawa, Kiyoharu},
  booktitle = {Proceedings of the International Joint Conference on Artificial Intelligence},
  year      = {2020}
}

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