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20182021
most citedGroupFace: Learning Latent Groups and Constructing Group-based Representations for Face Recognition

10 citations · 32 across the 6 of their papers we have counts for

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7 papers · 1 filter

cs.CV2021

Multi-level Distance Regularization for Deep Metric Learning

Yonghyun Kim, Wonpyo Park

We propose a novel distance-based regularization method for deep metric learning called Multi-level Distance Regularization (MDR). MDR explicitly disturbs a learning procedure by r…

cs.CV20202 cited

Suppressing Spoof-irrelevant Factors for Domain-agnostic Face Anti-spoofing

Taewook Kim, Yonghyun Kim

Face anti-spoofing aims to prevent false authentications of face recognition systems by distinguishing whether an image is originated from a human face or a spoof medium. We propos…

cs.CV20207 cited

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

Yonghyun Kim, Wonpyo Park, Jongju Shin

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…

cs.CV202010 cited

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

Yonghyun Kim, Wonpyo Park, Myung-Cheol Roh +1

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 enc…

cs.CV2019

Detector With Focus: Normalizing Gradient In Image Pyramid

Yonghyun Kim, Bong-Nam Kang, Daijin Kim

An image pyramid can extend many object detection algorithms to solve detection on multiple scales. However, interpolation during the resampling process of an image pyramid causes…

cs.CV2018

Pairwise Relational Networks for Face Recognition

Bong-Nam Kang, Yonghyun Kim, Daijin Kim

Existing face recognition using deep neural networks is difficult to know what kind of features are used to discriminate the identities of face images clearly. To investigate the e…