Learning to Cluster Faces via Confidence and Connectivity Estimation

Lei Yang1      Dapeng Chen2      Xiaohang Zhan1      Rui Zhao2      Chen Change Loy3      Dahua Lin1
1The Chinese University of Hong Kong
2SenseTime Group Limited, 3Nanyang Technological University
Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR 2020)


Face clustering is an essential tool for exploiting the unlabeled face data, and has a wide range of applications including face annotation and retrieval. Recent works show that supervised clustering can result in noticeable performance gain. However, they usually involve heuristic steps and require numerous overlapped subgraphs, severely restricting their accuracy and efficiency. In this paper, we propose a fully learnable clustering framework without requiring a large number of overlapped subgraphs. Instead, we transform the clustering problem into two sub-problems. Specifically, two graph convolutional networks, named GCN-V and GCN-E, are designed to estimate the confidence of vertices and the connectivity of edges, respectively. With the vertex confidence and edge connectivity, we can naturally organize more relevant vertices on the affinity graph and group them into clusters. Experiments on two large-scale benchmarks show that our method significantly improves clustering accuracy and thus performance of the recognition models trained on top, yet it is an order of magnitude more efficient than existing supervised methods.




Code and Models


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Related Publication

Consensus-Driven Propagation in Massive Unlabeled Data for Face Recognition. Xiaohang Zhan, Ziwei Liu, Junjie Yan, Dahua Lin, Chen Change Loy. In Proceedings of European Conference on Computer Vision (ECCV), 2018 [PDF] [Project Page] [Code]

Learning to Cluster Faces on an Affinity Graph. Lei Yang, Xiaohang Zhan, Dapeng Chen, Junjie Yan, Chen Change Loy, Dahua Lin. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019 [PDF] [Project Page] [Code]


  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},