5 papers
Scene Reconstruction as Mapping Priors for 3D Detection
Yang Fu, Yuliang Zou, Hao Xiang +8
In autonomous driving, mapping is critical for motion planning but remains an under-utilized resource for perception tasks such as 3D object detection. Maps can provide robust stru…
STELLAR: Scaling 3D Perception Large Models for Autonomous Driving
Yingwei Li, Xin Huang, Yang Liu +13
Model scaling has demonstrated remarkable success through large-scale training on diverse datasets. It remains an open question whether the same paradigm would apply to autonomous…
WOD-E2E: Waymo Open Dataset for End-to-End Driving in Challenging Long-tail Scenarios
Runsheng Xu, Hubert Lin, Wonseok Jeon +11
Vision-based end-to-end (E2E) driving has garnered significant interest in the research community due to its scalability and synergy with multimodal large language models (MLLMs).…
Drive&Gen: Co-Evaluating End-to-End Driving and Video Generation Models
Jiahao Wang, Zhenpei Yang, Yijing Bai +11
Recent advances in generative models have sparked exciting new possibilities in the field of autonomous vehicles. Specifically, video generation models are now being explored as co…
SceneCrafter: Controllable Multi-View Driving Scene Editing
Zehao Zhu, Yuliang Zou, Chiyu Max Jiang +9
Simulation is crucial for developing and evaluating autonomous vehicle (AV) systems. Recent literature builds on a new generation of generative models to synthesize highly realisti…