AVDD

This repository includes code for : Audio Visual Dataset Distillation (TMLR 2024).

Create env

conda create -n avdd python=3.9 -y
conda activate avdd
pip install torch==2.1.1 torchvision==0.16.1 torchaudio==2.1.1 --index-url https://download.pytorch.org/whl/cu118

git clone https://github.com/sakshamsingh1/AVDD
cd AVDD
pip install -r requirements.txt

Inference code

Download and unzip VGG-10k distilled and real data.

bash scripts/download_vgg_subset.sh

Evaluate VGG-10k data. The code will evaluate 3 distilled data for 5 times.

bash scripts/vgg10k_evaluate.sh

Note: Please uncomment different commands in the file to test different IPC settings
Similar scripts are present for other datasets.

Visualization

You can visualize the distilled data using the visualize_data.ipynb notebook.

TODO

• Inference code
• Training code
• Parallelized training code
• Retrieval code

🤗 Citation

@article{kushwahaaudio,
  title={Audio-Visual Dataset Distillation},
  author={Kushwaha, Saksham Singh and Vasireddy, Siva Sai Nagender and Wang, Kai and Tian, Yapeng},
  journal={Transactions on Machine Learning Research}
}

The code is based on Distribution Matching, AV-robustness