DQ-GAT: Towards Safe and Efficient Autonomous Driving With Deep Q-Learning and Graph Attention Networks.

Correcton to "DiTNet: End-to-End 3D Object Detection and Track ID Assignment in Spatio-temporal World".

VTGNet: A Vision-Based Trajectory Generation Network for Autonomous Vehicles in Urban Environments.

The Role of the Hercules Autonomous Vehicle During the COVID-19 Pandemic: An Autonomous Logistic Vehicle for Contactless Goods Transportation.

PVStereo: Pyramid Voting Module for End-to-End Self-Supervised Stereo Matching.

DiTNet: End-to-End 3D Object Detection and Track ID Assignment in Spatio-Temporal World.

PointMoSeg: Sparse Tensor-Based End-to-End Moving-Obstacle Segmentation in 3-D Lidar Point Clouds for Autonomous Driving.

Vision-Based Autonomous Car Racing Using Deep Imitative Reinforcement Learning.

Carl-Lead: Lidar-based End-to-End Autonomous Driving with Contrastive Deep Reinforcement Learning.

R-PCC: A Baseline for Range Image-based Point Cloud Compression.

Probabilistic End-to-End Vehicle Navigation in Complex Dynamic Environments With Multimodal Sensor Fusion.

High-Speed Autonomous Drifting With Deep Reinforcement Learning.

Learning Collision-Free Space Detection from Stereo Images: Homography Matrix Brings Better Data Augmentation.

Learning Scalable Self-Driving Policies for Generic Traffic Scenarios.

Hercules: An Autonomous Logistic Vehicle for Contact-less Goods Transportation During the COVID-19 Outbreak.