20 citations · 45 across the 15 of their papers we have counts for
15 papers
High Definition Map Mapping and Update: A General Overview and Future Directions
Benny Wijaya, Kun Jiang, Mengmeng Yang +6
Along with the rapid growth of autonomous vehicles (AVs), more and more demands are required for environment perception technology. Among others, HD mapping has become one of the m…
PanoSSC: Exploring Monocular Panoptic 3D Scene Reconstruction for Autonomous Driving
Yining Shi, Jiusi Li, Kun Jiang +4
Vision-centric occupancy networks, which represent the surrounding environment with uniform voxels with semantics, have become a new trend for safe driving of camera-only autonomou…
EFFOcc: Learning Efficient Occupancy Networks from Minimal Labels for Autonomous Driving
Yining Shi, Kun Jiang, Jinyu Miao +8
3D occupancy prediction (3DOcc) is a rapidly rising and challenging perception task in the field of autonomous driving. Existing 3D occupancy networks (OccNets) are both computatio…
A Survey on Monocular Re-Localization: From the Perspective of Scene Map Representation
Jinyu Miao, Kun Jiang, Tuopu Wen +8
Monocular Re-Localization (MRL) is a critical component in autonomous applications, estimating 6 degree-of-freedom ego poses w.r.t. the scene map based on monocular images. In rece…
Dynamically Conservative Self-Driving Planner for Long-Tail Cases
Weitao Zhou, Zhong Cao, Nanshan Deng +3
Self-driving vehicles (SDVs) are becoming reality but still suffer from "long-tail" challenges during natural driving: the SDVs will continually encounter rare, safety-critical cas…
Identify, Estimate and Bound the Uncertainty of Reinforcement Learning for Autonomous Driving
Weitao Zhou, Zhong Cao, Nanshan Deng +2
Deep reinforcement learning (DRL) has emerged as a promising approach for developing more intelligent autonomous vehicles (AVs). A typical DRL application on AVs is to train a neur…
Poses as Queries: Image-to-LiDAR Map Localization with Transformers
Jinyu Miao, Kun Jiang, Yunlong Wang +6
High-precision vehicle localization with commercial setups is a crucial technique for high-level autonomous driving tasks. Localization with a monocular camera in LiDAR map is a ne…
Grid-Centric Traffic Scenario Perception for Autonomous Driving: A Comprehensive Review
Yining Shi, Kun Jiang, Jiusi Li +5
Grid-centric perception is a crucial field for mobile robot perception and navigation. Nonetheless, grid-centric perception is less prevalent than object-centric perception as auto…
StreamingFlow: Streaming Occupancy Forecasting with Asynchronous Multi-modal Data Streams via Neural Ordinary Differential Equation
Yining Shi, Kun Jiang, Ke Wang +4
Predicting the future occupancy states of the surrounding environment is a vital task for autonomous driving. However, current best-performing single-modality methods or multi-moda…
Map Container: A Map-based Framework for Cooperative Perception
Kun Jiang, Yining Shi, Benny Wijaya +4
The idea of cooperative perception is to benefit from shared perception data between multiple vehicles and overcome the limitations of on-board sensors on single vehicle. However,…
Bridging the View Disparity Between Radar and Camera Features for Multi-modal Fusion 3D Object Detection
Taohua Zhou, Yining Shi, Junjie Chen +3
Environmental perception with the multi-modal fusion of radar and camera is crucial in autonomous driving to increase accuracy, completeness, and robustness. This paper focuses on…
Long-Tail Prediction Uncertainty Aware Trajectory Planning for Self-driving Vehicles
Weitao Zhou, Zhong Cao, Yunkang Xu +4
A typical trajectory planner of autonomous driving commonly relies on predicting the future behavior of surrounding obstacles. Recently, deep learning technology has been widely ad…
SRCN3D: Sparse R-CNN 3D for Compact Convolutional Multi-View 3D Object Detection and Tracking
Yining Shi, Jingyan Shen, Yifan Sun +5
Detection and tracking of moving objects is an essential component in environmental perception for autonomous driving. In the flourishing field of multi-view 3D camera-based detect…
PandaSet: Advanced Sensor Suite Dataset for Autonomous Driving
Pengchuan Xiao, Zhenlei Shao, Steven Hao +9
The accelerating development of autonomous driving technology has placed greater demands on obtaining large amounts of high-quality data. Representative, labeled, real world data s…
Monocular Vehicle Self-localization method based on Compact Semantic Map
Zhongyang Xiao, Kun Jiang, Shichao Xie +3
High precision localization is a crucial requirement for the autonomous driving system. Traditional positioning methods have some limitations in providing stable and accurate vehic…