5 citations · 13 across the 16 of their papers we have counts for
18 papers
Realistic and Controllable 3D Gaussian-Guided Object Editing for Driving Video Generation
Jiusi Li, Jackson Jiang, Jinyu Miao +10
Corner cases are crucial for training and validating autonomous driving systems, yet collecting them from the real world is often costly and hazardous. Editing objects within captu…
PriorFusion: Unified Integration of Priors for Robust Road Perception in Autonomous Driving
Xuewei Tang, Mengmeng Yang, Tuopu Wen +7
With the growing interest in autonomous driving, there is an increasing demand for accurate and reliable road perception technologies. In complex environments without high-definiti…
A Survey on Vision-Language-Action Models for Autonomous Driving
Sicong Jiang, Zilin Huang, Kangan Qian +17
The rapid progress of multimodal large language models (MLLM) has paved the way for Vision-Language-Action (VLA) paradigms, which integrate visual perception, natural language unde…
COME: Adding Scene-Centric Forecasting Control to Occupancy World Model
Yining Shi, Kun Jiang, Qiang Meng +6
World models are critical for autonomous driving to simulate environmental dynamics and generate synthetic data. Existing methods struggle to disentangle ego-vehicle motion (perspe…
CleanMAP: Distilling Multimodal LLMs for Confidence-Driven Crowdsourced HD Map Updates
Ankit Kumar Shaw, Kun Jiang, Tuopu Wen +5
The rapid growth of intelligent connected vehicles (ICVs) and integrated vehicle-road-cloud systems has increased the demand for accurate, real-time HD map updates. However, ensuri…
POD: Predictive Object Detection with Single-Frame FMCW LiDAR Point Cloud
Yining Shi, Kun Jiang, Xin Zhao +5
LiDAR-based 3D object detection is a fundamental task in the field of autonomous driving. This paper explores the unique advantage of Frequency Modulated Continuous Wave (FMCW) LiD…
Advancing Autonomous Vehicle Intelligence: Deep Learning and Multimodal LLM for Traffic Sign Recognition and Robust Lane Detection
Chandan Kumar Sah, Ankit Kumar Shaw, Xiaoli Lian +5
Autonomous vehicles (AVs) require reliable traffic sign recognition and robust lane detection capabilities to ensure safe navigation in complex and dynamic environments. This paper…
RAVE: End-to-end Hierarchical Visual Localization with Rasterized and Vectorized HD map
Jinyu Miao, Tuopu Wen, Kun Jiang +8
Accurate localization serves as an important component in autonomous driving systems. Traditional rule-based localization involves many standalone modules, which is theoretically f…
Residual Learning towards High-fidelity Vehicle Dynamics Modeling with Transformer
Jinyu Miao, Rujun Yan, Bowei Zhang +6
The vehicle dynamics model serves as a vital component of autonomous driving systems, as it describes the temporal changes in vehicle state. In a long period, researchers have made…
Enhancing Lane Segment Perception and Topology Reasoning with Crowdsourcing Trajectory Priors
Peijin Jia, Ziang Luo, Tuopu Wen +4
In autonomous driving, recent advances in lane segment perception provide autonomous vehicles with a comprehensive understanding of driving scenarios. Moreover, incorporating prior…
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…
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…
DiffMap: Enhancing Map Segmentation with Map Prior Using Diffusion Model
Peijin Jia, Tuopu Wen, Ziang Luo +9
Constructing high-definition (HD) maps is a crucial requirement for enabling autonomous driving. In recent years, several map segmentation algorithms have been developed to address…
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…
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…
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,…
GDRQ: Group-based Distribution Reshaping for Quantization
Haibao Yu, Tuopu Wen, Guangliang Cheng +3
Low-bit quantization is challenging to maintain high performance with limited model capacity (e.g., 4-bit for both weights and activations). Naturally, the distribution of both wei…
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…