23 citations · 55 across the 13 of their papers we have counts for
7 papers · 1 filter
FSNet: Redesign Self-Supervised MonoDepth for Full-Scale Depth Prediction for Autonomous Driving
Yuxuan Liu, Zhenhua Xu, Huaiyang Huang +2
Predicting accurate depth with monocular images is important for low-cost robotic applications and autonomous driving. This study proposes a comprehensive self-supervised framework…
CP-loss: Connectivity-preserving Loss for Road Curb Detection in Autonomous Driving with Aerial Images
Zhenhua Xu, Yuxiang Sun, Lujia Wang +1
Road curb detection is important for autonomous driving. It can be used to determine road boundaries to constrain vehicles on roads, so that potential accidents could be avoided. M…
Learning Interpretable End-to-End Vision-Based Motion Planning for Autonomous Driving with Optical Flow Distillation
Hengli Wang, Peide Cai, Yuxiang Sun +2
Recently, deep-learning based approaches have achieved impressive performance for autonomous driving. However, end-to-end vision-based methods typically have limited interpretabili…
YOLOStereo3D: A Step Back to 2D for Efficient Stereo 3D Detection
Yuxuan Liu, Lujia Wang, Ming Liu
Object detection in 3D with stereo cameras is an important problem in computer vision, and is particularly crucial in low-cost autonomous mobile robots without LiDARs. Nowadays, mo…
A Robust Stereo Camera Localization Method with Prior LiDAR Map Constrains
Dong Han, Zuhao Zou, Lujia Wang +1
In complex environments, low-cost and robust localization is a challenging problem. For example, in a GPSdenied environment, LiDAR can provide accurate position information, but th…
A Novel Dual-Lidar Calibration Algorithm Using Planar Surfaces
Jianhao Jiao, Qinghai Liao, Yilong Zhu +5
Multiple lidars are prevalently used on mobile vehicles for rendering a broad view to enhance the performance of localization and perception systems. However, precise calibration o…