6 papers
Scene2Demo: Self-Evolving Embodied Data Generation via Object-Action Graph
Xiang Liu, Sen Cui, Guocai Yao +4
We present Scene2Demo, an automated framework for offline embodied data generation. Given a single RGB scene image and a user query, Scene2Demo constructs an interactive simulated…
nuCarla: A nuScenes-Style Bird's-Eye View Perception Dataset for CARLA Simulation
Zhijie Qiao, Zhong Cao, Henry X. Liu
End-to-end (E2E) autonomous driving heavily relies on closed-loop simulation, where perception, planning, and control are jointly trained and evaluated in interactive environments.…
Boosting Zero-Shot VLN via Abstract Obstacle Map-Based Waypoint Prediction with TopoGraph-and-VisitInfo-Aware Prompting
Boqi Li, Siyuan Li, Weiyi Wang +3
With the rapid progress of foundation models and robotics, vision-language navigation (VLN) has emerged as a key task for embodied agents with broad practical applications. We addr…
End2Race: An End-to-End Learning Framework for Multi-Vehicle Autonomous Racing
Zhijie Qiao, Haowei Li, Zhong Cao +1
Autonomous racing serves as a compelling testbed for advancing autonomous vehicle systems. The 1/10-scale F1Tenth platform is widely adopted for education and research, with annual…
RADE: Learning Risk-Adjustable Driving Environment via Multi-Agent Conditional Diffusion
Jiawei Wang, Xintao Yan, Yao Mu +3
Generating safety-critical scenarios in high-fidelity simulations offers a promising and cost-effective approach for efficient testing of autonomous vehicles. Existing methods typi…
LightEMMA: A Longitudinal Evaluation of Vision-Language Models for Autonomous Driving
Zhijie Qiao, Haowei Li, Zhong Cao +1
Rapid advances in vision-language models (VLMs) have generated growing interest in their application to autonomous driving. A prevailing assumption is that successive VLM generatio…