1 citations · 1 across the 6 of their papers we have counts for
7 papers
ARIQA-3DS: A Stereoscopic Image Quality Assessment Dataset for Realistic Augmented Reality
Aymen Sekhri, Seyed Ali Amirshahi, Mohamed-Chaker Larabi
As Augmented Reality (AR) technologies advance towards immersive consumer adoption, the need for rigorous Quality of Experience (QoE) assessment becomes critical. However, existing…
Multi-Feature Fusion Approach for Generative AI Images Detection
Abderrezzaq Sendjasni, Mohamed-Chaker Larabi
The rapid evolution of Generative AI (GenAI) models has led to synthetic images of unprecedented realism, challenging traditional methods for distinguishing them from natural photo…
NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results
Xin Li, Kun Yuan, Bingchen Li +110
This paper presents a review for the NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement. The challenge comprises two tracks: (i) Efficient Video Qualit…
Embedding Similarity Guided License Plate Super Resolution
Abderrezzaq Sendjasni, Mohamed-Chaker Larabi
Super-resolution (SR) techniques play a pivotal role in enhancing the quality of low-resolution images, particularly for applications such as security and surveillance, where accur…
Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation
Aymen Sekhri, Seyed Ali Amirshahi, Mohamed-Chaker Larabi
Augmented Reality (AR) is a major immersive media technology that enriches our perception of reality by overlaying digital content (the foreground) onto physical environments (the…
Embedding-Driven Data Distillation for 360-Degree IQA With Residual-Aware Refinement
Abderrezzaq Sendjasni, Seif-Eddine Benkabou, Mohamed-Chaker Larabi
This article identifies and addresses a fundamental bottleneck in data-driven 360-degree image quality assessment (IQA): the lack of intelligent, sample-level data selection. Hence…
Deriving Explanation of Deep Visual Saliency Models
Sai Phani Kumar Malladi, Jayanta Mukhopadhyay, Chaker Larabi +1
Deep neural networks have shown their profound impact on achieving human level performance in visual saliency prediction. However, it is still unclear how they learn the task and w…