no code implementations • 12 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.
1 code implementation • 27 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.
no code implementations • 9 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.
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.
no code implementations • 2 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.
1 code implementation • 11 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.
no code implementations • 9 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.
no code implementations • 17 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.
no code implementations • 8 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.
no code implementations • 28 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).
no code implementations • 16 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.
no code implementations • 23 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.