# Projects based on EasyFL

We have been doing research on federated learning for several years and published [several papers](https://weiming.me/#publications) in top-tier conferences and journals. EasyFL is developed based on deep insights from our research. It further facilitated us built other federated learning several projects.

## Applications

We have released the following implementations of federated learning applications:

- FedReID: [[code]](https://github.com/EasyFL-AI/EasyFL/tree/master/applications/fedreid) for [Performance Optimization for Federated Person Re-identification via Benchmark Analysis](https://dl.acm.org/doi/10.1145/3394171.3413814) (_ACMMM'2020_).
- FedSSL: [[code]](https://github.com/EasyFL-AI/EasyFL/tree/master/applications/fedssl) for two papers: [Divergence-aware Federated Self-Supervised Learning](https://openreview.net/forum?id=oVE1z8NlNe) (_ICLR'2022_)  and [Collaborative Unsupervised Visual Representation Learning From Decentralized Data](https://openaccess.thecvf.com/content/ICCV2021/html/Zhuang_Collaborative_Unsupervised_Visual_Representation_Learning_From_Decentralized_Data_ICCV_2021_paper.html) (_ICCV'2021_)

## Papers

The following are the projects and papers built on EasyFL:

- EasyFL: A Low-code Federated Learning Platform For Dummies, _IEEE Internet-of-Things Journal_. [[paper]](https://arxiv.org/abs/2105.07603)
- Divergence-aware Federated Self-Supervised Learning, _ICLR'2022_. [[paper]](https://openreview.net/forum?id=oVE1z8NlNe)
- Collaborative Unsupervised Visual Representation Learning From Decentralized Data, _ICCV'2021_. [[paper]](https://openaccess.thecvf.com/content/ICCV2021/html/Zhuang_Collaborative_Unsupervised_Visual_Representation_Learning_From_Decentralized_Data_ICCV_2021_paper.html)
- Joint Optimization in Edge-Cloud Continuum for Federated Unsupervised Person Re-identification, _ACMMM'2021_. [[paper]](https://arxiv.org/abs/2108.06493)

If you have built new projects using EasyFL, please feel free to create PR to update this page.