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cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…