260 citations · 512 across the 34 of their papers we have counts for
7 papers · 1 filter
csBoundary: City-scale Road-boundary Detection in Aerial Images for High-definition Maps
Zhenhua Xu, Yuxuan Liu, Lu Gan +4
High-Definition (HD) maps can provide precise geometric and semantic information of static traffic environments for autonomous driving. Road-boundary is one of the most important i…
On Bundle Adjustment for Multiview PointCloud Registration
Huaiyang Huang, Yuxiang Sun, Jin Wu +5
Multiview registration is used to estimate Rigid Body Transformations (RBTs) from multiple frames and reconstruct a scene with corresponding scans. Despite the success of pairwise…
Incorporating Learnt Local and Global Embeddings into Monocular Visual SLAM
Huaiyang Huang, Haoyang Ye, Yuxiang Sun +2
Traditional approaches for Visual Simultaneous Localization and Mapping (VSLAM) rely on low-level vision information for state estimation, such as handcrafted local features or the…
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…
Greedy-Based Feature Selection for Efficient LiDAR SLAM
Jianhao Jiao, Yilong Zhu, Haoyang Ye +5
Modern LiDAR-SLAM (L-SLAM) systems have shown excellent results in large-scale, real-world scenarios. However, they commonly have a high latency due to the expensive data associati…
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…