pith. sign in

arxiv: 1611.08069 · v2 · pith:VC3X2KYPnew · submitted 2016-11-24 · 💻 cs.CV · cs.RO

3D Fully Convolutional Network for Vehicle Detection in Point Cloud

classification 💻 cs.CV cs.RO
keywords detectioncloudpointconvolutionalfullynetworkvehicleapplied
0
0 comments X
read the original abstract

2D fully convolutional network has been recently successfully applied to object detection from images. In this paper, we extend the fully convolutional network based detection techniques to 3D and apply it to point cloud data. The proposed approach is verified on the task of vehicle detection from lidar point cloud for autonomous driving. Experiments on the KITTI dataset shows a significant performance improvement over the previous point cloud based detection approaches.

This paper has not been read by Pith yet.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. RGB-D image-based Object Detection: from Traditional Methods to Deep Learning Techniques

    cs.CV 2019-07 unverdicted novelty 2.0

    A survey of RGB-D object detection from traditional hand-crafted features with machine learning to deep learning techniques.