activity
20162024
most citedRecognizability Embedding Enhancement for Very Low-Resolution Face Recognition and Quality Estimation

3 citations · 7 across the 10 of their papers we have counts for

collaborators

10 papers

cs.CR2024

WiFaKey: Generating Cryptographic Keys from Face in the Wild

Xingbo Dong, Hui Zhang, Yen Lung Lai +4

Deriving a unique cryptographic key from biometric measurements is a challenging task due to the existing noise gap between the biometric measurements and error correction coding.…

cs.CV2024

Face Reconstruction Transfer Attack as Out-of-Distribution Generalization

Yoon Gyo Jung, Jaewoo Park, Xingbo Dong +3

Understanding the vulnerability of face recognition systems to malicious attacks is of critical importance. Previous works have focused on reconstructing face images that can penet…

cs.CV2024

Beyond First-Order: A Multi-Scale Approach to Finger Knuckle Print Biometrics

Chengrui Gao, Ziyuan Yang, Andrew Beng Jin Teoh +1

Recently, finger knuckle prints (FKPs) have gained attention due to their rich textural patterns, positioning them as a promising biometric for identity recognition. Prior FKP reco…

cs.CV2023

Scale-aware competition network for palmprint recognition

Chengrui Gao, Ziyuan Yang, Min Zhu +1

Palmprint biometrics garner heightened attention in palm-scanning payment and social security due to their distinctive attributes. However, prevailing methodologies singularly prio…

cs.CV2023

Energizing Federated Learning via Filter-Aware Attention

Ziyuan Yang, Zerui Shao, Huijie Huangfu +5

Federated learning (FL) is a promising distributed paradigm, eliminating the need for data sharing but facing challenges from data heterogeneity. Personalized parameter generation…

cs.CV20231 cited

Understanding the Feature Norm for Out-of-Distribution Detection

Jaewoo Park, Jacky Chen Long Chai, Jaeho Yoon +1

A neural network trained on a classification dataset often exhibits a higher vector norm of hidden layer features for in-distribution (ID) samples, while producing relatively lower…