Proximity-Aware Hierarchical Clustering of unconstrained faces

作者：

Highlights：

• Deep representations and clustering can be combined to group faces with distinct identities.

• Local structure of deep features should be exploited for improved clustering performance.

• Proposed clustering algorithm can be applied to curate training data for deep networks without human annotation.

摘要

•Deep representations and clustering can be combined to group faces with distinct identities.•Local structure of deep features should be exploited for improved clustering performance.•Proposed clustering algorithm can be applied to curate training data for deep networks without human annotation.

论文关键词：Face recognition,Clustering

论文评审过程：Received 3 October 2017, Revised 21 May 2018, Accepted 21 June 2018, Available online 5 July 2018, Version of Record 20 July 2018.

论文官网地址：https://doi.org/10.1016/j.imavis.2018.06.007