[CVPR2025] Dataset Distillation with Neural Characteristic Function: A Minmax Perspective
Official PyTorch implementation of the paper “Dataset Distillation with Neural Characteristic Function” (NCFM) in CVPR 2025.
:fire: News
- [2025/03/02] The code of our paper has been released.
- [2025/02/27] Our NCFM paper has been accepted to CVPR 2025 (Rating: 555). Thanks!
:rocket: Pipeline
Here’s an overview of the process behind our Neural Characteristic Function Matching (NCFM) method:
🛠️ Getting Started
To get started with NCFM, follow the installation instructions below.
- Clone the repo
git clone https://github.com/gszfwsb/NCFM.git
- Install dependencies
pip install -r requirements.txt
- Pretrain the models yourself, or download the pretrained_models from huggingface.
cd pretrain
torchrun --nproc_per_node={n_gpus} --nnodes=1 pretrain_script.py --gpu={gpu_ids} --config_path=../config/{ipc}/{dataset}.yaml
- Condense
cd condense
torchrun --nproc_per_node={n_gpus} --nnodes=1 condense_script.py --gpu={gpu_ids} --ipc={ipc} --config_path=../config/{ipc}/{dataset}.yaml
- Evaluation or or download the condensed dataset from huggingface
cd evaluation
torchrun --nproc_per_node={n_gpus} --nnodes=1 evaluation_script.py --gpu={gpu_ids} --ipc={ipc} --config_path=../config/{ipc}/{dataset}.yaml --load_path={distilled_dataset.pt}
:blue_book: Example Usage
- CIFAR-10
#ipc50
cd condense
torchrun --nproc_per_node=8 --nnodes=1 --master_port=34153 condense_script.py --gpu="0,1,2,3,4,5,6,7" --ipc=50 --config_path=../config/ipc50/cifar10.yaml
- CIFAR-100
#ipc10
cd condense
torchrun --nproc_per_node=8 --nnodes=1 --master_port=34153 condense_script.py --gpu="0,1,2,3,4,5,6,7" --ipc=10 --config_path=../config/ipc10/cifar100.yaml
:postbox: Contact
If you have any questions, please contact Shaobo Wang([email protected]).
:pushpin: Citation
If you find NCFM useful for your research and applications, please cite using this BibTeX:
@inproceedings{wang2025NCFM,
title={Dataset Distillation with Neural Characteristic Function: A Minmax Perspective},
author={Shaobo Wang and Yicun Yang and Zhiyuan Liu and Chenghao Sun and Xuming Hu and Conghui He and Linfeng Zhang},
booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
year={2025}
}
Acknowledgement
We sincerely thank the developers of the following projects for their valuable contributions and inspiration: MTT, DATM, DC/DM, IDC, SRe2L, RDED, DANCE. We draw inspiration from these fantastic projects!
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