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Analyzing bias in diffusion-based face generation models
Diffusion models are becoming increasingly popular in synthetic data generation and image
editing applications. However, these models can amplify existing biases and propagate …
editing applications. However, these models can amplify existing biases and propagate …
Recognition performance variation across demographic groups through the eyes of explainable face recognition
Face recognition systems are susceptible to differences in performance across demographic
or non-demographic groups. However, the understanding of the behavior of face recognition …
or non-demographic groups. However, the understanding of the behavior of face recognition …
Sum of group error differences: A critical examination of bias evaluation in biometric verification and a dual-metric measure
A Elobaid, N Ramoly, L Younes… - 2024 IEEE 18th …, 2024 - ieeexplore.ieee.org
Biometric Verification (BV) systems often exhibit accuracy disparities across different
demographic groups, leading to biases in BV applications. Assessing and quantifying these …
demographic groups, leading to biases in BV applications. Assessing and quantifying these …
Unbiased-Diff: Analyzing and Mitigating Biases in Diffusion Model-Based Face Image Generation
Diffusion-based generative models have become increasingly popular in applications such
as synthetic data generation and image editing, due to their ability to generate realistic, high …
as synthetic data generation and image editing, due to their ability to generate realistic, high …
Impact of Sunglasses on One-to-Many Facial Identification Accuracy
One-to-many facial identification is documented to achieve high accuracy in the case where
both the probe and the gallery aremugshot quality'images. However, an increasing number …
both the probe and the gallery aremugshot quality'images. However, an increasing number …