most citedRGB and LiDAR fusion based 3D Semantic Segmentation for Autonomous Driving

23 citations · 47 across the 6 of their papers we have counts for

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9 papers · 1 filter

cs.CV2021

BEV-MODNet: Monocular Camera based Bird's Eye View Moving Object Detection for Autonomous Driving

Hazem Rashed, Mariam Essam, Maha Mohamed +2

Detection of moving objects is a very important task in autonomous driving systems. After the perception phase, motion planning is typically performed in Bird's Eye View (BEV) spac…

cs.CV2021

VM-MODNet: Vehicle Motion aware Moving Object Detection for Autonomous Driving

Hazem Rashed, Ahmad El Sallab, Senthil Yogamani

Moving object Detection (MOD) is a critical task in autonomous driving as moving agents around the ego-vehicle need to be accurately detected for safe trajectory planning. It also…

cs.CV20198 cited

FisheyeMultiNet: Real-time Multi-task Learning Architecture for Surround-view Automated Parking System

Pullarao Maddu, Wayne Doherty, Ganesh Sistu +7

Automated Parking is a low speed manoeuvring scenario which is quite unstructured and complex, requiring full 360° near-field sensing around the vehicle. In this paper, we discuss…

cs.CV2019

Let's Get Dirty: GAN Based Data Augmentation for Camera Lens Soiling Detection in Autonomous Driving

Michal Uricar, Ganesh Sistu, Hazem Rashed +5

Wide-angle fisheye cameras are commonly used in automated driving for parking and low-speed navigation tasks. Four of such cameras form a surround-view system that provides a compl…

cs.CV201916 cited

RST-MODNet: Real-time Spatio-temporal Moving Object Detection for Autonomous Driving

Mohamed Ramzy, Hazem Rashed, Ahmad El Sallab +1

Moving Object Detection (MOD) is a critical task for autonomous vehicles as moving objects represent higher collision risk than static ones. The trajectory of the ego-vehicle is pl…

cs.CV2019

FuseMODNet: Real-Time Camera and LiDAR based Moving Object Detection for robust low-light Autonomous Driving

Hazem Rashed, Mohamed Ramzy, Victor Vaquero +3

Moving object detection is a critical task for autonomous vehicles. As dynamic objects represent higher collision risk than static ones, our own ego-trajectories have to be planned…