eDifFIQA: Towards Efficient Face Image Quality Assessment based on Denoising Diffusion Probabilistic Models

This is the eDifFIQA(M) model presented in "eDifFIQA: Towards Efficient Face Image Quality Assessment based on Denoising Diffusion Probabilistic Models" accepted in IEEE TBIOM (Transactions on Biometrics, Behavior, and Identity Science).

The original paper is available here.

For additional information on how to prepare the data and use the models refer to the original GitHub repository.

If you find this model useful, please cite:

 @article{babnikTBIOM2024,
  title={{eDifFIQA: Towards Efficient Face Image Quality Assessment based on Denoising Diffusion Probabilistic Models}},
  author={Babnik, {\v{Z}}iga and Peer, Peter and {\v{S}}truc, Vitomir},
  journal={IEEE Transactions on Biometrics, Behavior, and Identity Science (TBIOM)},
  year={2024},
  publisher={IEEE}
}

 @inproceedings{babnikIJCB2023,
  title={{DifFIQA: Face Image Quality Assessment Using Denoising Diffusion Probabilistic Models}},
  author={Babnik, {\v{Z}}iga and Peer, Peter and {\v{S}}truc, Vitomir},
  booktitle={Proceedings of the IEEE International Joint Conference on Biometrics (IJCB)},
  year={2023},
}