235 citations · 329 across the 17 of their papers we have counts for
8 papers · 1 filter
Are We Hungry for 3D LiDAR Data for Semantic Segmentation? A Survey and Experimental Study
Biao Gao, Yancheng Pan, Chengkun Li +2
3D semantic segmentation is a fundamental task for robotic and autonomous driving applications. Recent works have been focused on using deep learning techniques, whereas developing…
Learning from Naturalistic Driving Data for Human-like Autonomous Highway Driving
Donghao Xu, Zhezhang Ding, Xu He +4
Driving in a human-like manner is important for an autonomous vehicle to be a smart and predictable traffic participant. To achieve this goal, parameters of the motion planning mod…
Driver Identification through Stochastic Multi-State Car-Following Modeling
Donghao Xu, Zhezhang Ding, Chenfeng Tu +4
Intra-driver and inter-driver heterogeneity has been confirmed to exist in human driving behaviors by many studies. In this study, a joint model of the two types of heterogeneity i…
Cross Scene Prediction via Modeling Dynamic Correlation using Latent Space Shared Auto-Encoders
Shaochi Hu, Donghao Xu, Huijing Zhao
This work addresses on the following problem: given a set of unsynchronized history observations of two scenes that are correlative on their dynamic changes, the purpose is to lear…
Scene Context Based Semantic Segmentation for 3D LiDAR Data in Dynamic Scene
Jilin Mei, Huijing Zhao
We propose a graph neural network(GNN) based method to incorporate scene context for the semantic segmentation of 3D LiDAR data. The problem is defined as building a graph to repre…
Scene-Aware Error Modeling of LiDAR/Visual Odometry for Fusion-based Vehicle Localization
Xiaoliang Ju, Donghao Xu, Huijing Zhao
Localization is an essential technique in mobile robotics. In a complex environment, it is necessary to fuse different localization modules to obtain more robust results, in which…
Off-Road Drivable Area Extraction Using 3D LiDAR Data
Biao Gao, Anran Xu, Yancheng Pan +3
We propose a method for off-road drivable area extraction using 3D LiDAR data with the goal of autonomous driving application. A specific deep learning framework is designed to dea…
SemanticPOSS: A Point Cloud Dataset with Large Quantity of Dynamic Instances
Yancheng Pan, Biao Gao, Jilin Mei +3
3D semantic segmentation is one of the key tasks for autonomous driving system. Recently, deep learning models for 3D semantic segmentation task have been widely researched, but th…