2 citations · 3 across the 15 of their papers we have counts for
16 papers
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…
SwiftGS: Episodic Priors for Immediate Satellite Surface Recovery
Rong Fu, Jiekai Wu, Xiaowen Ma +4
Rapid, large-scale 3D reconstruction from multi-date satellite imagery is vital for environmental monitoring, urban planning, and disaster response, yet remains difficult due to il…
Missing-by-Design: Certifiable Modality Deletion for Revocable Multimodal Sentiment Analysis
Rong Fu, Ziming Wang, Chunlei Meng +4
As multimodal systems increasingly process sensitive personal data, the ability to selectively revoke specific data modalities has become a critical requirement for privacy complia…
Smooth Operator: Smooth Verifiable Reward Activates Spatial Reasoning Ability of Vision-Language Model
Siwen Jiao, Tianxiong Lv, Kangan Qian +7
Vision-Language Models (VLMs) face a critical bottleneck in achieving precise numerical prediction for 3D scene understanding. Traditional reinforcement learning (RL) approaches, p…
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…
EvaDrive: Evolutionary Adversarial Policy Optimization for End-to-End Autonomous Driving
Siwen Jiao, Kangan Qian, Hao Ye +12
Autonomous driving faces significant challenges in achieving human-like iterative decision-making, which continuously generates, evaluates, and refines trajectory proposals. Curren…
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…
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…
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…
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…
How Cars Move: Analyzing Driving Dynamics for Safer Urban Traffic
Kangan Qian, Jinyu Miao, Xinyu Jiao +6
Understanding the spatial dynamics of cars within urban systems is essential for optimizing infrastructure management and resource allocation. Recent empirical approaches for analy…
FASIONAD : FAst and Slow FusION Thinking Systems for Human-Like Autonomous Driving with Adaptive Feedback
Kangan Qian, Zhikun Ma, Yangfan He +13
Ensuring safe, comfortable, and efficient navigation is a critical goal for autonomous driving systems. While end-to-end models trained on large-scale datasets excel in common driv…
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…