1 citations · 1 across the 4 of their papers we have counts for
4 papers
Unmasking Face Embeddings: Reading, Rendering and Naming with Foundation Models
Fizza Rubab, Yiying Tong, Arun Ross
Modern face recognition (FR) owes much of its success to deep neural networks that learn to extract compact identity embeddings from face images. These models are typically trained…
Compatibility of Face Embeddings Across Deep Neural Networks
Fizza Rubab, Yiying Tong, Arun Ross
Automated face recognition has made rapid strides over the past decade due to the unprecedented rise of deep neural network (DNN) models that can be trained for domain-specific tas…
Shielding Latent Face Representations From Privacy Attacks
Arjun Ramesh Kaushik, Bharat Chandra Yalavarthi, Arun Ross +2
In today's data-driven analytics landscape, deep learning has become a powerful tool, with latent representations, known as embeddings, playing a central role in several applicatio…
Enhancing Privacy in Face Analytics Using Fully Homomorphic Encryption
Bharat Yalavarthi, Arjun Ramesh Kaushik, Arun Ross +2
Modern face recognition systems utilize deep neural networks to extract salient features from a face. These features denote embeddings in latent space and are often stored as templ…