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Found 12 papers, 1 papers with code
Mitigating the Impact of Attribute Editing on Face Recognition
To mitigate this issue, we propose two novel techniques for local and global attribute editing.
Alpha-wolves and Alpha-mammals: Exploring Dictionary Attacks on Iris Recognition Systems
A dictionary attack in a biometric system entails the use of a small number of strategically generated images or templates to successfully match with a large number of identities, thereby compromising security.
Identity-Preserving Aging of Face Images via Latent Diffusion Models
The performance of automated face recognition systems is inevitably impacted by the facial aging process.
Generating Adversarial Attacks in the Latent Space
Adversarial attacks in the input (pixel) space typically incorporate noise margins such as $L_1$ or $L_{\infty}$-norm to produce imperceptibly perturbed data that confound deep learning networks.
Can GAN-induced Attribute Manipulations Impact Face Recognition?
Impact due to demographic factors such as age, sex, race, etc., has been studied extensively in automated face recognition systems.
Facial De-morphing: Extracting Component Faces from a Single Morph
In this work, we propose a novel de-morphing method that can recover images of both identities simultaneously from a single morphed face image without needing a reference image or prior information about the morphing process.
Conditional Identity Disentanglement for Differential Face Morph Detection
We performed experiments on AMSL face morph, MorGAN, and EMorGAN datasets to demonstrate the effectiveness of the proposed method.
One-shot Representational Learning for Joint Biometric and Device Authentication
In this work, we propose a method to simultaneously perform (i) biometric recognition (i. e., identify the individual), and (ii) device recognition, (i. e., identify the device) from a single biometric image, say, a face image, using a one-shot schema.
Smartphone Camera De-identification while Preserving Biometric Utility
The principle of Photo Response Non Uniformity (PRNU) is often exploited to deduce the identity of the smartphone device whose camera or sensor was used to acquire a certain image.
Face Phylogeny Tree Using Basis Functions
We also utilize the same basis functions to model geometric transformations and deep-learning based transformations.
Some Research Problems in Biometrics: The Future Beckons
The need for reliably determining the identity of a person is critical in a number of different domains ranging from personal smartphones to border security; from autonomous vehicles to e-voting; from tracking child vaccinations to preventing human trafficking; from crime scene investigation to personalization of customer service.
Spoofing PRNU Patterns of Iris Sensors while Preserving Iris Recognition
The principle of Photo Response Non-Uniformity (PRNU) is used to link an image with its source, i. e., the sensor that produced it.
