FedPD: Federated Open Set Recognition with Parameter Disentanglement

Official implementation of the paper FedPD: Federated Open Set Recognition with Parameter Disentanglement (ICCV 2023).

Please use the following bib entry to cite the paper if you are using resources from this repo.

@InProceedings{Yang_2023_ICCV,
    author = {Yang, Chen and Zhu, Meilu and Liu, Yifan and Yuan, Yixuan},
    title = {FedPD: Federated Open Set Recognition with Parameter Disentanglement},
    booktitle = {IEEE/CVF International Conference on Computer Vision (ICCV)},
    year = {2023},
}

Setup

cd data
pip install -e .

Dataset & Pretrained Modeel

Benchmark(Digits)

• Please download our pre-processed datasets here, put under data/ directory and perform following commands:

  cd ./data
  unzip digit_dataset.zip

Training

Baseline

Our local training is based on popolar open-set recognition framework Proser. A simple baseline for federated open-set recognition is provided:

python tools/proser_federated.py --log 

Testing