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of 117
pro vyhledávání: '"Banerjee, Sudipta"'
Autor:
Banerjee, Sudipta, Ross, Arun
Near-duplicate images are often generated when applying repeated photometric and geometric transformations that produce imperceptible variants of the original image. Consequently, a deluge of near-duplicates can be circulated online posing copyright
Externí odkaz:
http://arxiv.org/abs/2408.07689
Through a large-scale study over diverse face images, we show that facial attribute editing using modern generative AI models can severely degrade automated face recognition systems. This degradation persists even with identity-preserving generative
Externí odkaz:
http://arxiv.org/abs/2403.08092
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. We focus on dictionary attacks at the t
Externí odkaz:
http://arxiv.org/abs/2403.12047
The performance of automated face recognition systems is inevitably impacted by the facial aging process. However, high quality datasets of individuals collected over several years are typically small in scale. In this work, we propose, train, and va
Externí odkaz:
http://arxiv.org/abs/2307.08585
Autor:
Shukla, Nitish, Banerjee, Sudipta
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. Such noise margins confine the magnitude of permissibl
Externí odkaz:
http://arxiv.org/abs/2304.04386
Impact due to demographic factors such as age, sex, race, etc., has been studied extensively in automated face recognition systems. However, the impact of \textit{digitally modified} demographic and facial attributes on face recognition is relatively
Externí odkaz:
http://arxiv.org/abs/2209.02941
A face morph is created by strategically combining two or more face images corresponding to multiple identities. The intention is for the morphed image to match with multiple identities. Current morph attack detection strategies can detect morphs but
Externí odkaz:
http://arxiv.org/abs/2209.02933
Autor:
Chinnadurai, Jayaprakash, Karthik, A., Venkata Naga Ramesh, Janjhyam, Banerjee, Sudipta, Rajlakshmi, P.V., Venkateswara Rao, Katakam, Sudarvizhi, D., Rajaram, A.
Publikováno v:
In Biomedical Signal Processing and Control November 2024 97
Autor:
Ramu, K., Patthi, Sridhar, Prajapati, Yogendra Narayan, Ramesh, Janjhyam Venkata Naga, Banerjee, Sudipta, Rao, K.B.V. Brahma, Alzahrani, Saleh I., ayyasamy, Rajaram
Publikováno v:
In Biomedical Signal Processing and Control February 2025 100 Part B
Autor:
Banerjee, Sudipta, Ross, Arun
We present the task of differential face morph attack detection using a conditional generative network (cGAN). To determine whether a face image in an identification document, such as a passport, is morphed or not, we propose an algorithm that learns
Externí odkaz:
http://arxiv.org/abs/2107.02162