7 papers
LiDAR-BEVMTN: Real-Time LiDAR Bird's-Eye View Multi-Task Perception Network for Autonomous Driving
Sambit Mohapatra, Senthil Yogamani, Varun Ravi Kumar +3
LiDAR is crucial for robust 3D scene perception in autonomous driving. LiDAR perception has the largest body of literature after camera perception. However, multi-task learning acr…
Near Field iToF LIDAR Depth Improvement from Limited Number of Shots
Mena Nagiub, Thorsten Beuth, Ganesh Sistu +2
Indirect Time of Flight LiDARs can indirectly calculate the scene's depth from the phase shift angle between transmitted and received laser signals with amplitudes modulated at a p…
SpikiLi: A Spiking Simulation of LiDAR based Real-time Object Detection for Autonomous Driving
Sambit Mohapatra, Thomas Mesquida, Mona Hodaei +3
Spiking Neural Networks are a recent and new neural network design approach that promises tremendous improvements in power efficiency, computation efficiency, and processing latenc…
A deep learning approach for direction of arrival estimation using automotive-grade ultrasonic sensors
Mohamed Shawki Elamir, Heinrich Gotzig, Raoul Zoellner +1
In this paper, a deep learning approach is presented for direction of arrival estimation using automotive-grade ultrasonic sensors which are used for driving assistance systems suc…
LiMoSeg: Real-time Bird's Eye View based LiDAR Motion Segmentation
Sambit Mohapatra, Mona Hodaei, Senthil Yogamani +5
Moving object detection and segmentation is an essential task in the Autonomous Driving pipeline. Detecting and isolating static and moving components of a vehicle's surroundings a…
BEVDetNet: Bird's Eye View LiDAR Point Cloud based Real-time 3D Object Detection for Autonomous Driving
Sambit Mohapatra, Senthil Yogamani, Heinrich Gotzig +2
3D object detection based on LiDAR point clouds is a crucial module in autonomous driving particularly for long range sensing. Most of the research is focused on achieving higher a…
Exploring Deep Spiking Neural Networks for Automated Driving Applications
Sambit Mohapatra, Heinrich Gotzig, Senthil Yogamani +2
Neural networks have become the standard model for various computer vision tasks in automated driving including semantic segmentation, moving object detection, depth estimation, vi…