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Jongju Shin

2 accepted papers

2020

BroadFace: Looking at Tens of Thousands of People at Once for Face Recognition

ECCV 2020poster

The datasets of face recognition contain an enormous number of identities and instances. However, conventional methods have difficulty in reflecting the entire distribution of the datasets because a mini-batch of small size contains only a small portion of all identities. To overcome this difficulty…

Cited by 61SourcePDFScholar
2020

GroupFace: Learning Latent Groups and Constructing Group-Based Representations for Face Recognition

CVPR 2020poster

In the field of face recognition, a model learns to distinguish millions of face images with fewer dimensional embedding features, and such vast information may not be properly encoded in the conventional model with a single branch. We propose a novel face-recognition-specialized architecture called…

Cited by 129PDFScholar