Learning to Cluster Faces

This repo provides an official implementation for [1, 2] and a re-implementation of [3].

Paper

1. Learning to Cluster Faces on an Affinity Graph, CVPR 2019 (Oral) [Project Page]
2. Learning to Cluster Faces via Confidence and Connectivity Estimation, CVPR 2020 [Project Page]
3. Linkage-based Face Clustering via Graph Convolution Network, CVPR 2019

Requirements

• Python >= 3.6
• PyTorch >= 0.4.0
• faiss
• mmcv

Setup and get data

Install dependencies

conda install faiss-gpu -c pytorch
pip install -r requirements.txt

Datasets

Please refer to DATASET.md for data preparation.

Model zoo

Pretrained models are available in the model zoo.

Run

0. Fetch code & Create soft link

git clone [email protected]:yl-1993/learn-to-cluster.git
cd learn-to-cluster
ln -s xxx/data data

1. Run algorithms

Follow the instructions in dsgcn, vegcn and lgcn to run algorithms.

Results on part1_test (584K)

Note that the prpsls in above table indicate the number of parameters for generating proposals, rather than the actual number of proposals. For example, 2 prpsls generates 34578 proposals and 20 prpsls generates 283552 proposals.

Benchmarks (5.21M)

1, 3, 5, 7, 9 denotes different scales of clustering. Details can be found in Face Clustering Benchmarks.

Results on YouTube-Faces

Results on DeepFashion

Face Recognition

For training face recognition and feature extraction, you may use any frameworks below, including but not limited to:

https://github.com/yl-1993/hfsoftmax

https://github.com/XiaohangZhan/face_recognition_framework

Citation

Please cite the following paper if you use this repository in your reseach.

@inproceedings{yang2019learning,
  title={Learning to Cluster Faces on an Affinity Graph},
  author={Yang, Lei and Zhan, Xiaohang and Chen, Dapeng and Yan, Junjie and Loy, Chen Change and Lin, Dahua},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2019}
}
@inproceedings{yang2020learning,
  title={Learning to Cluster Faces via Confidence and Connectivity Estimation},
  author={Yang, Lei and Chen, Dapeng and Zhan, Xiaohang and Zhao, Rui and Loy, Chen Change and Lin, Dahua},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
  year={2020}
}