Imagen de Portada

2nd Place Solution for CVPR2024 E2E Challenge: End-to-End Autonomous Driving Using Vision Language Model

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Guo, Zilong, Luo, Yi, Sha, Long, Wang, Dongxu, Wang, Panqu, Xu, Chenyang, Yang, Yi
Formato:	Preprint
Publicado:	2025
Materias:	Computer Vision and Pattern Recognition Robotics
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Driving in Corner Case: A Real-World Adversarial Closed-Loop Evaluation Platform for End-to-End Autonomous Driving
por: Geng, Jiaheng, et al.
Publicado: (2025)

DriveE2E: Closed-Loop Benchmark for End-to-End Autonomous Driving through Real-to-Simulation
por: Yu, Haibao, et al.
Publicado: (2025)

ComDrive: Comfort-Oriented End-to-End Autonomous Driving
por: Wang, Junming, et al.
Publicado: (2024)

DriveMoE: Mixture-of-Experts for Vision-Language-Action Model in End-to-End Autonomous Driving
por: Yang, Zhenjie, et al.
Publicado: (2025)

Senna: Bridging Large Vision-Language Models and End-to-End Autonomous Driving
por: Jiang, Bo, et al.
Publicado: (2024)

Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition
por: Hao, Ruiyang, et al.
Publicado: (2025)

Reinforced Refinement with Self-Aware Expansion for End-to-End Autonomous Driving
por: Liu, Haochen, et al.
Publicado: (2025)

Exploring the Causality of End-to-End Autonomous Driving
por: Li, Jiankun, et al.
Publicado: (2024)

AutoMoT: A Unified Vision-Language-Action Model with Asynchronous Mixture-of-Transformers for End-to-End Autonomous Driving
por: Huang, Wenhui, et al.
Publicado: (2026)

AppleVLM: End-to-end Autonomous Driving with Advanced Perception and Planning-Enhanced Vision-Language Models
por: Han, Yuxuan, et al.
Publicado: (2026)

Don't Shake the Wheel: Momentum-Aware Planning in End-to-End Autonomous Driving
por: Song, Ziying, et al.
Publicado: (2025)

ReCogDrive: A Reinforced Cognitive Framework for End-to-End Autonomous Driving
por: Li, Yongkang, et al.
Publicado: (2025)

FlowDrive: Energy Flow Field for End-to-End Autonomous Driving
por: Jiang, Hao, et al.
Publicado: (2025)

ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving
por: Feng, Renju, et al.
Publicado: (2025)

Embodied Cognition Augmented End2End Autonomous Driving
por: Niu, Ling, et al.
Publicado: (2025)

End-to-End Autonomous Driving through V2X Cooperation
por: Yu, Haibao, et al.
Publicado: (2024)

VADv2: End-to-End Vectorized Autonomous Driving via Probabilistic Planning
por: Jiang, Bo, et al.
Publicado: (2024)

DiffusionDrive: Truncated Diffusion Model for End-to-End Autonomous Driving
por: Liao, Bencheng, et al.
Publicado: (2024)

VECTOR-Drive: Tightly Coupled Vision-Language and Trajectory Expert Routing for End-to-End Autonomous Driving
por: Zhao, Rui, et al.
Publicado: (2026)

Prioritizing Perception-Guided Self-Supervision: A New Paradigm for Causal Modeling in End-to-End Autonomous Driving
por: Huang, Yi, et al.
Publicado: (2025)

A Containerized Microservice Architecture for a ROS 2 Autonomous Driving Software: An End-to-End Latency Evaluation
por: Betz, Tobias, et al.
Publicado: (2024)

LeGo-Drive: Language-enhanced Goal-oriented Closed-Loop End-to-End Autonomous Driving
por: Paul, Pranjal, et al.
Publicado: (2024)

UniSTPA: A Safety Analysis Framework for End-to-End Autonomous Driving
por: Kou, Hongrui, et al.
Publicado: (2025)

V2X-VLM: End-to-End V2X Cooperative Autonomous Driving Through Large Vision-Language Models
por: You, Junwei, et al.
Publicado: (2024)

UniMM-V2X: MoE-Enhanced Multi-Level Fusion for End-to-End Cooperative Autonomous Driving
por: Song, Ziyi, et al.
Publicado: (2025)

HiST-VLA: A Hierarchical Spatio-Temporal Vision-Language-Action Model for End-to-End Autonomous Driving
por: Wang, Yiru, et al.
Publicado: (2026)

E2E Parking Dataset: An Open Benchmark for End-to-End Autonomous Parking
por: Gao, Kejia, et al.
Publicado: (2025)

Using Ensemble Diffusion to Estimate Uncertainty for End-to-End Autonomous Driving
por: Wintel, Florian, et al.
Publicado: (2025)

Generalizing End-To-End Autonomous Driving In Real-World Environments Using Zero-Shot LLMs
por: Dong, Zeyu, et al.
Publicado: (2024)

HERMES: A Holistic End-to-End Risk-Aware Multimodal Embodied System with Vision-Language Models for Long-Tail Autonomous Driving
por: Tang, Weizhe, et al.
Publicado: (2026)

Unveiling the Surprising Efficacy of Navigation Understanding in End-to-End Autonomous Driving
por: Hua, Zhihua, et al.
Publicado: (2026)

Cognitive-Hierarchy Guided End-to-End Planning for Autonomous Driving
por: Wang, Zhennan, et al.
Publicado: (2025)

DriveSafer: End-to-End Autonomous Driving with Safety Guidance
por: Sural, Shounak, et al.
Publicado: (2026)

DIVER: Reinforced Diffusion Breaks Imitation Bottlenecks in End-to-End Autonomous Driving
por: Song, Ziying, et al.
Publicado: (2025)

FocalAD: Local Motion Planning for End-to-End Autonomous Driving
por: Sun, Bin, et al.
Publicado: (2025)

DriveDPO: Policy Learning via Safety DPO For End-to-End Autonomous Driving
por: Shang, Shuyao, et al.
Publicado: (2025)

Unleashing the Potential of Diffusion Models for End-to-End Autonomous Driving
por: Zheng, Yinan, et al.
Publicado: (2026)

DiffE2E: Rethinking End-to-End Driving with a Hybrid Action Diffusion and Supervised Policy
por: Zhao, Rui, et al.
Publicado: (2025)

End-to-end Autonomous Driving: Challenges and Frontiers
por: Chen, Li, et al.
Publicado: (2023)

Beyond Imitation: Learning Safe End-to-End Autonomous Driving from Hard Negatives
por: Wang, Junli, et al.
Publicado: (2026)