1. 

   Cluster and Aggregate: Face Recognition with Large Probe Set

   Minchul Kim, Feng Liu, Anil K. Jain, Xiaoming Liu

   Feature fusion plays a crucial role in unconstrained face recognition where inputs (probes) comprise of a set of N low quality images whose individual qualities vary. Advances in attention and recurrent modules have led to feature fusion that can model the relationship among the images in the input set. However ...

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   Keywords: Face recognition, Biometrics

2. 

   AdaFace: Quality Adaptive Margin for Face Recognition

   Minchul Kim, Anil K. Jain, Xiaoming Liu

   Recognition in low quality face datasets is challenging because facial attributes are obscured and degraded. Advances in margin-based loss functions have resulted in enhanced discriminability of faces in the embedding space. Further, previous studies have studied the effect of adaptive losses to assign more importance to misclassified (hard) examples. In ...

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   Keywords: Face recognition, Biometrics

2022

• AdaFace: Quality Adaptive Margin for Face Recognition
  Minchul Kim, Anil K. Jain, Xiaoming Liu
  In Proceeding of IEEE Computer Vision and Pattern Recognition (CVPR 2022), New Orleans, LA, Jun. 2022 (Oral presentation)
  Bibtex | PDF | arXiv | Supplemental | Project Webpage | Code
@inproceedings{ adaface-quality-adaptive-margin-for-face-recognition,
  author = { Minchul Kim and Anil K. Jain and Xiaoming Liu },
  title = { AdaFace: Quality Adaptive Margin for Face Recognition },
  booktitle = { In Proceeding of IEEE Computer Vision and Pattern Recognition },
  address = { New Orleans, LA },
  month = { June },
  year = { 2022 },
}