227 citations · 262 across the 10 of their papers we have counts for
10 papers
Spatiotemporal Decoupling for Efficient Vision-Based Occupancy Forecasting
Jingyi Xu, Xieyuanli Chen, Junyi Ma +4
The task of occupancy forecasting (OCF) involves utilizing past and present perception data to predict future occupancy states of autonomous vehicle surrounding environments, which…
PRISM: PRogressive dependency maxImization for Scale-invariant image Matching
Xudong Cai, Yongcai Wang, Lun Luo +5
Image matching aims at identifying corresponding points between a pair of images. Currently, detector-free methods have shown impressive performance in challenging scenarios, thank…
BEVPlace++: Fast, Robust, and Lightweight LiDAR Global Localization for Unmanned Ground Vehicles
Lun Luo, Si-Yuan Cao, Xiaorui Li +4
This article introduces BEVPlace++, a novel, fast, and robust LiDAR global localization method for unmanned ground vehicles. It uses lightweight convolutional neural networks (CNNs…
S4TP: Social-Suitable and Safety-Sensitive Trajectory Planning for Autonomous Vehicles
Xiao Wang, Ke Tang, Xingyuan Dai +5
In public roads, autonomous vehicles (AVs) face the challenge of frequent interactions with human-driven vehicles (HDVs), which render uncertain driving behavior due to varying soc…
ModaLink: Unifying Modalities for Efficient Image-to-PointCloud Place Recognition
Weidong Xie, Lun Luo, Nanfei Ye +7
Place recognition is an important task for robots and autonomous cars to localize themselves and close loops in pre-built maps. While single-modal sensor-based methods have shown s…
Distilling Temporal Knowledge with Masked Feature Reconstruction for 3D Object Detection
Haowen Zheng, Dong Cao, Jintao Xu +4
Striking a balance between precision and efficiency presents a prominent challenge in the bird's-eye-view (BEV) 3D object detection. Although previous camera-based BEV methods achi…
Cam4DOcc: Benchmark for Camera-Only 4D Occupancy Forecasting in Autonomous Driving Applications
Junyi Ma, Xieyuanli Chen, Jiawei Huang +6
Understanding how the surrounding environment changes is crucial for performing downstream tasks safely and reliably in autonomous driving applications. Recent occupancy estimation…
SuperFusion: Multilevel LiDAR-Camera Fusion for Long-Range HD Map Generation
Hao Dong, Weihao Gu, Xianjing Zhang +5
High-definition (HD) semantic map generation of the environment is an essential component of autonomous driving. Existing methods have achieved good performance in this task by fus…
Efficient Spatial-Temporal Information Fusion for LiDAR-Based 3D Moving Object Segmentation
Jiadai Sun, Yuchao Dai, Xianjing Zhang +4
Accurate moving object segmentation is an essential task for autonomous driving. It can provide effective information for many downstream tasks, such as collision avoidance, path p…
OverlapTransformer: An Efficient and Rotation-Invariant Transformer Network for LiDAR-Based Place Recognition
Junyi Ma, Jun Zhang, Jintao Xu +3
Place recognition is an important capability for autonomously navigating vehicles operating in complex environments and under changing conditions. It is a key component for tasks s…