852 citations · 1.5k across the 82 of their papers we have counts for
4 papers · 1 filter
MODNet: Moving Object Detection Network with Motion and Appearance for Autonomous Driving
Mennatullah Siam, Heba Mahgoub, Mohamed Zahran +3
We propose a novel multi-task learning system that combines appearance and motion cues for a better semantic reasoning of the environment. A unified architecture for joint vehicle…
Deep Semantic Segmentation for Automated Driving: Taxonomy, Roadmap and Challenges
Mennatullah Siam, Sara Elkerdawy, Martin Jagersand +1
Semantic segmentation was seen as a challenging computer vision problem few years ago. Due to recent advancements in deep learning, relatively accurate solutions are now possible f…
Rejection-Cascade of Gaussians: Real-time adaptive background subtraction framework
B Ravi Kiran, Arindam Das, Senthil Yogamani
Background-Foreground classification is a well-studied problem in computer vision. Due to the pixel-wise nature of modeling and processing in the algorithm, it is usually difficult…
Deep Reinforcement Learning framework for Autonomous Driving
Ahmad El Sallab, Mohammed Abdou, Etienne Perot +1
Reinforcement learning is considered to be a strong AI paradigm which can be used to teach machines through interaction with the environment and learning from their mistakes. Despi…