7 papers
Enhancing Single-Image Facial Demorphing using Multimodal Large Language Models
Nitish Shukla, Arun Ross
Face recognition systems are increasingly vulnerable to morphing attacks, where a composite image is crafted to match multiple identities, enabling unauthorized access and identity…
S2H-DPO: Hardness-Aware Preference Optimization for Vision-Language Models
Nitish Shukla, Surgan Jandial, Arun Ross
Vision-Language Models (VLMs) have demonstrated remarkable progress in single-image understanding, yet effective reasoning across multiple images remains challenging. We identify a…
MLLM-based Textual Explanations for Face Comparison
Redwan Sony, Anil K Jain, Arun Ross
Multimodal Large Language Models (MLLMs) have recently been proposed as a means to generate natural-language explanations for face recognition decisions. While such explanations fa…
diffDemorph: Extending Reference-Free Demorphing to Unseen Faces
Nitish Shukla, Arun Ross
A face morph is created by combining two face images corresponding to two identities to produce a composite that successfully matches both the constituent identities. Reference-fre…
Facial Demorphing from a Single Morph Using a Latent Conditional GAN
Nitish Shukla, Arun Ross
A morph is created by combining two (or more) face images from two (or more) identities to create a composite image that is highly similar to all constituent identities, allowing t…
dc-GAN: Dual-Conditioned GAN for Face Demorphing From a Single Morph
Nitish Shukla, Arun Ross
A facial morph is an image strategically created by combining two face images pertaining to two distinct identities. The goal is to create a face image that can be matched to two d…