12 citations · 14 across the 3 of their papers we have counts for
6 papers
MVFuseNet: Improving End-to-End Object Detection and Motion Forecasting through Multi-View Fusion of LiDAR Data
Ankit Laddha, Shivam Gautam, Stefan Palombo +2
In this work, we propose \textit{MVFuseNet}, a novel end-to-end method for joint object detection and motion forecasting from a temporal sequence of LiDAR data. Most existing metho…
LiRaNet: End-to-End Trajectory Prediction using Spatio-Temporal Radar Fusion
Meet Shah, Zhiling Huang, Ankit Laddha +5
In this paper, we present LiRaNet, a novel end-to-end trajectory prediction method which utilizes radar sensor information along with widely used lidar and high definition (HD) map…
RV-FuseNet: Range View Based Fusion of Time-Series LiDAR Data for Joint 3D Object Detection and Motion Forecasting
Ankit Laddha, Shivam Gautam, Gregory P. Meyer +2
Robust real-time detection and motion forecasting of traffic participants is necessary for autonomous vehicles to safely navigate urban environments. In this paper, we present RV-F…
LaserFlow: Efficient and Probabilistic Object Detection and Motion Forecasting
Gregory P. Meyer, Jake Charland, Shreyash Pandey +4
In this work, we present LaserFlow, an efficient method for 3D object detection and motion forecasting from LiDAR. Unlike the previous work, our approach utilizes the native range…
Sensor Fusion for Joint 3D Object Detection and Semantic Segmentation
Gregory P. Meyer, Jake Charland, Darshan Hegde +2
In this paper, we present an extension to LaserNet, an efficient and state-of-the-art LiDAR based 3D object detector. We propose a method for fusing image data with the LiDAR data…
LaserNet: An Efficient Probabilistic 3D Object Detector for Autonomous Driving
Gregory P. Meyer, Ankit Laddha, Eric Kee +2
In this paper, we present LaserNet, a computationally efficient method for 3D object detection from LiDAR data for autonomous driving. The efficiency results from processing LiDAR…