Person-MinkUNet: 3D Person Detection with LiDAR Point Cloud

07/03/2021
by   Dan Jia, et al.
0

In this preliminary work we attempt to apply submanifold sparse convolution to the task of 3D person detection. In particular, we present Person-MinkUNet, a single-stage 3D person detection network based on Minkowski Engine with U-Net architecture. The network achieves a 76.4 3D detection benchmark.

READ FULL TEXT
research
11/24/2016

3D Fully Convolutional Network for Vehicle Detection in Point Cloud

2D fully convolutional network has been recently successfully applied to...
research
03/11/2021

Wandering and getting lost: the architecture of an app activating local communities on dementia issues

We describe the architecture of Sammen Om Demens (SOD), an application f...
research
01/23/2019

AlteregoNets: a way to human augmentation

A person dependent network, called an AlterEgo net, is proposed for deve...
research
12/09/2018

A Comparison of Embedded Deep Learning Methods for Person Detection

Recent advancements in parallel computing, GPU technology and deep learn...
research
10/09/2019

Patch Refinement – Localized 3D Object Detection

We introduce Patch Refinement a two-stage model for accurate 3D object d...
research
03/27/2023

Binarizing Sparse Convolutional Networks for Efficient Point Cloud Analysis

In this paper, we propose binary sparse convolutional networks called BS...

Please sign up or login with your details

Forgot password? Click here to reset