Search Results for author: Zhe Jin

Found 12 papers, 3 papers with code

IFViT: Interpretable Fixed-Length Representation for Fingerprint Matching via Vision Transformer

no code implementations12 Apr 2024 Yuhang Qiu, Honghui Chen, Xingbo Dong, Zheng Lin, Iman Yi Liao, Massimo Tistarelli, Zhe Jin

The first module, an interpretable dense registration module, establishes a Vision Transformer (ViT)-based Siamese Network to capture long-range dependencies and the global context in fingerprint pairs.

On the Computational Entanglement of Distant Features in Adversarial Machine Learning

1 code implementation27 Sep 2023 YenLung Lai, Xingbo Dong, Zhe Jin

Adversarial examples in machine learning has emerged as a focal point of research due to their remarkable ability to deceive models with seemingly inconspicuous input perturbations, potentially resulting in severe consequences.

Reconstruct Face from Features Using GAN Generator as a Distribution Constraint

no code implementations9 Jun 2022 Xingbo Dong, Zhihui Miao, Lan Ma, Jiajun Shen, Zhe Jin, Zhenhua Guo, Andrew Beng Jin Teoh

Yet, the security and privacy of the extracted features from deep learning models (deep features) have been often overlooked.

Face Recognition Privacy Preserving

Abandoning the Bayer-Filter to See in the Dark

1 code implementation CVPR 2022 Xingbo Dong, Wanyan Xu, Zhihui Miao, Lan Ma, Chao Zhang, Jiewen Yang, Zhe Jin, Andrew Beng Jin Teoh, Jiajun Shen

Next, a fully convolutional network is proposed to achieve the low-light image enhancement by fusing colored raw data with synthesized monochrome raw data.

Low-Light Image Enhancement

A Generalized Approach for Cancellable Template and Its Realization for Minutia Cylinder-Code

no code implementations2 Mar 2022 Xingbo Dong, Zhe Jin, KokSheik Wong

In this paper, we proposed a generalized version of IoM hashing namely gIoM, and therefore the unordered and variable size biometric template can be used.

Similarity-based Gray-box Adversarial Attack Against Deep Face Recognition

1 code implementation11 Jan 2022 Hanrui Wang, Shuo Wang, Zhe Jin, Yandan Wang, Cunjian Chen, Massimo Tistarell

This technique applies to both white-box and gray-box attacks against authentication systems that determine genuine or imposter users using the dissimilarity score.

Adversarial Attack Face Recognition

Multi-spectral Facial Landmark Detection

no code implementations9 Jun 2020 Jin Keong, Xingbo Dong, Zhe Jin, Khawla Mallat, Jean-Luc Dugelay

The experiment conducted on Eurecom's visible and thermal paired database shows the superior performance of DMSL over the state-of-the-art for thermal facial landmark detection.

3D Face Reconstruction Boundary Detection +3

On the Risk of Cancelable Biometrics

no code implementations17 Oct 2019 Xingbo Dong, Jaewoo Park, Zhe Jin, Andrew Beng Jin Teoh, Massimo Tistarelli, KokSheik Wong

Cancelable biometrics (CB) employs an irreversible transformation to convert the biometric features into transformed templates while preserving the relative distance between two templates for security and privacy protection.

A Genetic Algorithm Enabled Similarity-Based Attack on Cancellable Biometrics

no code implementations8 May 2019 Xingbo Dong, Zhe Jin, Andrew Teoh Beng Jin

SA produces a preimage, an inverse of transformed template, which can be exploited for impersonation and cross-matching.

A Symmetric Keyring Encryption Scheme for Biometric Cryptosystems

no code implementations28 Sep 2018 Yen-Lung Lai, Jung-Yeon Hwang, Zhe Jin, Soohyong Kim, Sangrae Cho, Andrew Beng Jin Teoh

In this paper, we propose a novel biometric cryptosystem for vectorial biometrics named symmetric keyring encryption (SKE) inspired by Rivest's keyring model (2016).

Ranking Based Locality Sensitive Hashing Enabled Cancelable Biometrics: Index-of-Max Hashing

no code implementations16 Mar 2017 Zhe Jin, Yen-Lung Lai, Jung-Yeon Hwang, Soo-Hyung Kim, Andrew Beng Jin Teoh

In this paper, we propose a ranking based locality sensitive hashing inspired two-factor cancelable biometrics, dubbed "Index-of-Max" (IoM) hashing for biometric template protection.

Rank Correlation Measure: A Representational Transformation for Biometric Template Protection

no code implementations23 Jul 2016 Zhe Jin, Yen-Lung Lai, Andrew Beng Jin Teoh

The former takes care of the accuracy performance mitigating numeric noises/perturbations while the latter offers strong non-invertible transformation via nonlinear feature embedding from Euclidean to Rank space that leads to toughness in inversion.

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