8 papers · 1 filter
FaceMoE: Mixture of Experts for Low-Resolution Face Recognition
Kartik Narayan, Vishal M. Patel
Low-resolution face recognition (LR-FR) remains a challenging task due to poor feature extraction and aggregation, as probe images often contain limited identity information result…
DeepMMSearch-R1: Empowering Multimodal LLMs in Multimodal Web Search
Kartik Narayan, Yang Xu, Tian Cao +7
Multimodal Large Language Models (MLLMs) in real-world applications require access to external knowledge sources and must remain responsive to the dynamic and ever-changing real-wo…
TransFIRA: Transfer Learning for Face Image Recognizability Assessment
Allen Tu, Kartik Narayan, Joshua Gleason +4
Face recognition in unconstrained environments such as surveillance, video, and web imagery must contend with extreme variation in pose, blur, illumination, and occlusion, where co…
Training Free Stylized Abstraction
Aimon Rahman, Kartik Narayan, Vishal M. Patel
Stylized abstraction synthesizes visually exaggerated yet semantically faithful representations of subjects, balancing recognizability with perceptual distortion. Unlike image-to-i…
RestoreVAR: Visual Autoregressive Generation for All-in-One Image Restoration
Sudarshan Rajagopalan, Kartik Narayan, Vishal M. Patel
The use of latent diffusion models (LDMs) such as Stable Diffusion has significantly improved the perceptual quality of All-in-One image Restoration (AiOR) methods, while also enha…
FaceXBench: Evaluating Multimodal LLMs on Face Understanding
Kartik Narayan, Vibashan VS, Vishal M. Patel
Multimodal Large Language Models (MLLMs) demonstrate impressive problem-solving abilities across a wide range of tasks and domains. However, their capacity for face understanding h…