3 papers
cs.CV2025
RAVID: Retrieval-Augmented Visual Detection: A Knowledge-Driven Approach for AI-Generated Image Identification
Mamadou Keita, Wassim Hamidouche, Hessen Bougueffa Eutamene +2
In this paper, we introduce RAVID, the first framework for AI-generated image detection that leverages visual retrieval-augmented generation (RAG). While RAG methods have shown pro…
cs.CV2025
DeeCLIP: A Robust and Generalizable Transformer-Based Framework for Detecting AI-Generated Images
Mamadou Keita, Wassim Hamidouche, Hessen Bougueffa Eutamene +2
This paper introduces DeeCLIP, a novel framework for detecting AI-generated images using CLIP-ViT and fusion learning. Despite significant advancements in generative models capable…
cs.CV2025
PE-CLIP: A Parameter-Efficient Fine-Tuning of Vision Language Models for Dynamic Facial Expression Recognition
Ibtissam Saadi, Abdenour Hadid, Douglas W. Cunningham +2
Vision-Language Models (VLMs) like CLIP offer promising solutions for Dynamic Facial Expression Recognition (DFER) but face challenges such as inefficient full fine-tuning, high co…