9 citations · 28 across the 30 of their papers we have counts for
32 papers
Leveraging Visual and Geometric Priors for Metric-scale and Complete Vehicle Gaussian Reconstruction from Limited Views
Jinyu Miao, Jiusi Li, Yifei He +4
High-fidelity vehicle assets are essential for controllable traffic scene generation, particularly for synthesizing rare and safety-critical long-tail scenarios. However, reconstru…
nuTruck: Benchmarking Autonomous Driving Planning for Distributed Electric-drive Trucks
Jinyu Miao, Pu Zhang, Yifei He +5
The dominance of traditional rule-based methods in autonomous driving has gradually been replaced by learning-based approaches. While learning-based planners have achieved consider…
MapAgent: An Industrial-Grade Agentic Framework for City-scale Lane-level Map Generation
Deguo Xia, Zihan Li, Haochen Zhao +6
Lane-level maps are critical infrastructure for autonomous driving and lane-level navigation, yet constructing and maintaining standardized lane networks for hundreds of cities rem…
Envision4D: Envisioning Visual Futures via Feed-forward 4D Gaussian Splatting for Autonomous Driving
Qi Song, Yifei He, Chi Zhang +6
Forecasting the future evolution of dynamic scenes is crucial in autonomous driving. However, existing feed-forward paradigms are primarily designed for interpolation. When extende…
UniT: Unified Geometry Learning with Group Autoregressive Transformer
Haotian Wang, Yusong Huang, Zhaonian Kuang +4
Recent feed-forward models have significantly advanced geometry perception for inferring dense 3D structure from sensor observations. However, its essential capabilities remain fra…
4DLidarOpen: An Open 4D FMCW Lidar Dataset for Motion-Aware Autonomous Driving
Kane Qian, Xin Zhao, Yining Shi +7
We present 4DLidarOpen, a large-scale open multi-modal dataset for autonomous driving, centered on 4D frequency-modulated continuous-wave (FMCW) Lidar sensing. Unlike conventional…
XEmbodied: A Foundation Model with Enhanced Geometric and Physical Cues for Large-Scale Embodied Environments
Kangan Qian, ChuChu Xie, Yang Zhong +13
Vision-Language-Action (VLA) models drive next-generation autonomous systems, but training them requires scalable, high-quality annotations from complex environments. Current cloud…
Physics-informed Deep Mixture-of-Koopmans Vehicle Dynamics Model with Dual-branch Encoder for Distributed Electric-drive Trucks
Jinyu Miao, Pu Zhang, Rujun Yan +8
Advanced autonomous driving systems require accurate vehicle dynamics modeling. However, identifying a precise dynamics model remains challenging due to strong nonlinearities and t…
MTRDrive: Memory-Tool Synergistic Reasoning for Robust Autonomous Driving in Corner Cases
Ziang Luo, Kangan Qian, Jiahua Wang +13
Vision-Language Models(VLMs) have demonstrated significant potential for end-to-end autonomous driving, yet a substantial gap remains between their current capabilities and the rel…
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…
Multimodal HD Mapping for Intersections by Intelligent Roadside Units
Zhongzhang Chen, Miao Fan, Shengtong Xu +4
High-definition (HD) semantic mapping of complex intersections poses significant challenges for traditional vehicle-based approaches due to occlusions and limited perspectives. Thi…
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…
AgentThink: A Unified Framework for Tool-Augmented Chain-of-Thought Reasoning in Vision-Language Models for Autonomous Driving
Kangan Qian, Sicong Jiang, Yang Zhong +18
Vision-Language Models (VLMs) show promise for autonomous driving, yet their struggle with hallucinations, inefficient reasoning, and limited real-world validation hinders accurate…
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…
FASIONAD++ : Integrating High-Level Instruction and Information Bottleneck in FAt-Slow fusION Systems for Enhanced Safety in Autonomous Driving with Adaptive Feedback
Kangan Qian, Ziang Luo, Sicong Jiang +16
Ensuring safe, comfortable, and efficient planning is crucial for autonomous driving systems. While end-to-end models trained on large datasets perform well in standard driving sce…
LEGO-Motion: Learning-Enhanced Grids with Occupancy Instance Modeling for Class-Agnostic Motion Prediction
Kangan Qian, Jinyu Miao, Ziang Luo +7
Accurate and reliable spatial and motion information plays a pivotal role in autonomous driving systems. However, object-level perception models struggle with handling open scenari…
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…
LDMapNet-U: An End-to-End System for City-Scale Lane-Level Map Updating
Deguo Xia, Weiming Zhang, Xiyan Liu +6
An up-to-date city-scale lane-level map is an indispensable infrastructure and a key enabling technology for ensuring the safety and user experience of autonomous driving systems.…
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…