Deconvolutional Networks for Point-Cloud Vehicle Detection and Tracking
in Driving Scenarios

Deconvolutional Networks for Point-Cloud Vehicle Detection and Tracking in Driving Scenarios

23 August 2018

Francesc Moreno-Noguer

Alberto Sanfeliu

Juan Andrade-Cetto

Papers citing "Deconvolutional Networks for Point-Cloud Vehicle Detection and Tracking in Driving Scenarios"

5 / 5 papers shown

Title
LiMoSeg: Real-time Bird's Eye View based LiDAR Motion Segmentation S. Mohapatra Mona Hodaei S. Yogamani Stefan Milz H. Gotzig Martin Simon Hazem Rashed Patrick Mäder 17 27 0 08 Nov 2021
Autonomous Driving with Deep Learning: A Survey of State-of-Art Technologies Yu Huang Yue Chen 3DPC 43 82 0 10 Jun 2020
FuseMODNet: Real-Time Camera and LiDAR based Moving Object Detection for robust low-light Autonomous Driving Hazem Rashed M. Ramzy Victor Vaquero Ahmad El-Sallab Ganesh Sistu S. Yogamani 3DPC 25 90 0 11 Oct 2019
Learning Object Bounding Boxes for 3D Instance Segmentation on Point Clouds Bo Yang Jianan Wang R. Clark Qingyong Hu Sen Wang Andrew Markham A. Trigoni 3DPC 25 324 0 04 Jun 2019
Vote3Deep: Fast Object Detection in 3D Point Clouds Using Efficient Convolutional Neural Networks Martin Engelcke Dushyant Rao Dominic Zeng Wang Chi Hay Tong Ingmar Posner 3DPC 192 521 0 21 Sep 2016