2 citations · 3 across the 26 of their papers we have counts for
20 papers · 1 filter
AffectFlow-DINO: Uncertainty-Aware Multi-Task Affect Estimation via Conditional Rectified Flow
Salah Eddine Bekhouche, Abdellah Zakaria Sellam, Fadi Dornaika +1
We present \textbf{AffectFlow-DINO}, a multi-task learning system for the 11th ABAW challenge that extends a standard deterministic architecture with a conditional rectified-flow h…
Can Visual Mamba Improve AI-Generated Image Detection? An In-Depth Investigation
Mamadou Keita, Wassim Hamidouche, Hessen Bougueffa Eutamene +3
In recent years, computer vision has witnessed remarkable progress, fueled by the development of innovative architectures such as Convolutional Neural Networks (CNNs), Generative A…
SPARK-IL: Spectral Retrieval-Augmented RAG for Knowledge-driven Deepfake Detection via Incremental Learning
Hessen Bougueffa Eutamene, Abdellah Zakaria Sellam, Abdelmalik Taleb-Ahmed +1
Detecting AI-generated images remains a significant challenge because detectors trained on specific generators often fail to generalize to unseen models; however, while pixel-level…
RF-HiT: Rectified Flow Hierarchical Transformer for General Medical Image Segmentation
Ahmed Marouane Djouamaa, Abir Belaala, Abdellah Zakaria Sellam +3
Accurate medical image segmentation requires both long-range contextual reasoning and precise boundary delineation, a task where existing transformer- and diffusion-based paradigms…
Conflict-Aware Multimodal Fusion for Ambivalence and Hesitancy Recognition
Salah Eddine Bekhouche, Hichem Telli, Azeddine Benlamoudi +3
Ambivalence and hesitancy (A/H) are subtle affective states where a person shows conflicting signals through different channels -- saying one thing while their face or voice tells…
Decoding Matters: Efficient Mamba-Based Decoder with Distribution-Aware Deep Supervision for Medical Image Segmentation
Fares Bougourzi, Fadi Dornaika, Abdenour Hadid
Deep learning has achieved remarkable success in medical image segmentation, often reaching expert-level accuracy in delineating tumors and tissues. However, most existing approach…