1 code implementation • 19 Jul 2024 • Ayman Beghdadi, Azeddine Beghdadi, Mohib Ullah, Faouzi Alaya Cheikh, Malik Mallem
Scene understanding plays an important role in several high-level computer vision applications, such as autonomous vehicles, intelligent video surveillance, or robotics.
1 code implementation • 12 Nov 2023 • Ayman Beghdadi, Azeddine Beghdadi, Malik Mallem, Lotfi Beji, Faouzi Alaya Cheikh
These new local distortions are generated by considering the scene context of the images that guarantees a high level of photo-realism.
1 code implementation • 9 Feb 2022 • Zohaib Amjad Khan, Azeddine Beghdadi, Mounir Kaaniche, Faouzi Alaya Cheikh, Osama Gharbi
Video quality assessment is a challenging problem having a critical significance in the context of medical imaging.
no code implementations • 12 Jun 2021 • Zohaib Amjad Khan, Azeddine Beghdadi, Mounir Kaaniche, Faouzi Alaya Cheikh
Laparoscopic images and videos are often affected by different types of distortion like noise, smoke, blur and nonuniform illumination.
no code implementations • 26 Oct 2020 • Tarik Ayaou, Azeddine Beghdadi, Karim Afdel, Abdellah Amghar
Road signs detection and recognition in natural scenes is one of the most important tasksin the design of Intelligent Transport Systems (ITS).
no code implementations • 25 Jul 2019 • Noor Almaadeed, Omar Elharrouss, Somaya Al-Maadeed, Ahmed Bouridane, Azeddine Beghdadi
For that, this paper proposes a new technic for multiple human action recognition and summarization for surveillance videos.
no code implementations • 13 Jul 2019 • Congcong Wang, Faouzi Alaya Cheikh, Azeddine Beghdadi, Ole Jakob Elle
The object sizes in images are diverse, therefore, capturing multiple scale context information is essential for semantic segmentation.
no code implementations • 27 Dec 2018 • Congcong Wang, Vivek Sharma, Yu Fan, Faouzi Alaya Cheikh, Azeddine Beghdadi, Ole Jacob Elle, Rainer Stiefelhagen
For feature extraction, we use statistical features based on bivariate histogram distribution of gradient magnitude~(GM) and Laplacian of Gaussian~(LoG).