Cover Image

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Hu, Xiaotao, Yin, Wei, Jia, Mingkai, Deng, Junyuan, Guo, Xiaoyang, Zhang, Qian, Long, Xiaoxiao, Tan, Ping
Format:	Preprint
Published:	2024
Subjects:	Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Epona: Autoregressive Diffusion World Model for Autonomous Driving
by: Zhang, Kaiwen, et al.
Published: (2025)

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

OccTENS: 3D Occupancy World Model via Temporal Next-Scale Prediction
by: Jin, Bu, et al.
Published: (2025)

MGVQ: Could VQ-VAE Beat VAE? A Generalizable Tokenizer with Multi-group Quantization
by: Jia, Mingkai, et al.
Published: (2025)

Boost 3D Reconstruction using Diffusion-based Monocular Camera Calibration
by: Deng, Junyuan, et al.
Published: (2024)

EponaV2: Driving World Model with Comprehensive Future Reasoning
by: Xu, Jiawei, et al.
Published: (2026)

DriveWorld-VLA: Unified Latent-Space World Modeling with Vision-Language-Action for Autonomous Driving
by: jia, Feiyang, et al.
Published: (2026)

DriveWorld: 4D Pre-trained Scene Understanding via World Models for Autonomous Driving
by: Min, Chen, et al.
Published: (2024)

HorizonDrive: Self-Corrective Autoregressive World Model for Long-horizon Driving Simulation
by: Zhang, Conglang, et al.
Published: (2026)

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model
by: Zheng, Yupeng, et al.
Published: (2025)

Driving in the Occupancy World: Vision-Centric 4D Occupancy Forecasting and Planning via World Models for Autonomous Driving
by: Yang, Yu, et al.
Published: (2024)

Composing Driving Worlds through Disentangled Control for Adversarial Scenario Generation
by: Zhan, Yifan, et al.
Published: (2026)

ReSim: Reliable World Simulation for Autonomous Driving
by: Yang, Jiazhi, et al.
Published: (2025)

GoalFlow: Goal-Driven Flow Matching for Multimodal Trajectories Generation in End-to-End Autonomous Driving
by: Xing, Zebin, et al.
Published: (2025)

InstaDrive: Instance-Aware Driving World Models for Realistic and Consistent Video Generation
by: Yang, Zhuoran, et al.
Published: (2026)

DriveWAM: Video Generative Priors Enable Scalable World-Action Modeling for Autonomous Driving
by: Shi, Chen, et al.
Published: (2026)

DOME: Taming Diffusion Model into High-Fidelity Controllable Occupancy World Model
by: Gu, Songen, et al.
Published: (2024)

DrivingGen: A Comprehensive Benchmark for Generative Video World Models in Autonomous Driving
by: Zhou, Yang, et al.
Published: (2026)

Enhancing End-to-End Autonomous Driving with Latent World Model
by: Li, Yingyan, et al.
Published: (2024)

DriveFuture: Future-Aware Latent World Models for Autonomous Driving
by: Hong, Yufeng, et al.
Published: (2026)

Open 3D World in Autonomous Driving
by: Cheng, Xinlong, et al.
Published: (2024)

InfinityDrive: Breaking Time Limits in Driving World Models
by: Guo, Xi, et al.
Published: (2024)

DrivingGPT: Unifying Driving World Modeling and Planning with Multi-modal Autoregressive Transformers
by: Chen, Yuntao, et al.
Published: (2024)

Physical Informed Driving World Model
by: Yang, Zhuoran, et al.
Published: (2024)

SGDrive: Scene-to-Goal Hierarchical World Cognition for Autonomous Driving
by: Li, Jingyu, et al.
Published: (2026)

A Survey of World Models for Autonomous Driving
by: Feng, Tuo, et al.
Published: (2025)

World knowledge-enhanced Reasoning Using Instruction-guided Interactor in Autonomous Driving
by: Zhai, Mingliang, et al.
Published: (2024)

DriveGPT4: Interpretable End-to-end Autonomous Driving via Large Language Model
by: Xu, Zhenhua, et al.
Published: (2023)

Uni-World VLA: Interleaved World Modeling and Planning for Autonomous Driving
by: Liu, Qiqi, et al.
Published: (2026)

DynFlowDrive: Flow-Based Dynamic World Modeling for Autonomous Driving
by: Liu, Xiaolu, et al.
Published: (2026)

SynthDrive: Scalable Real2Sim2Real Sensor Simulation Pipeline for High-Fidelity Asset Generation and Driving Data Synthesis
by: Chen, Zhengqing, et al.
Published: (2025)

Risk-Aware World Model Predictive Control for Generalizable End-to-End Autonomous Driving
by: Sun, Jiangxin, et al.
Published: (2026)

CoWorld-VLA: Thinking in a Multi-Expert World Model for Autonomous Driving
by: Huang, Minqing, et al.
Published: (2026)

Xiaomi Auto World Model: A Joint World Model Integrating Reconstruction and Generation for Autonomous Driving
by: Zhou, Lijun, et al.
Published: (2026)

ResWorld: Temporal Residual World Model for End-to-End Autonomous Driving
by: Zhang, Jinqing, et al.
Published: (2026)

Map-World: Masked Action planning and Path-Integral World Model for Autonomous Driving
by: Hu, Bin, et al.
Published: (2025)

UniDrive-WM: Unified Understanding, Planning and Generation World Model For Autonomous Driving
by: Xiong, Zhexiao, et al.
Published: (2026)

UniDriveDreamer: A Single-Stage Multimodal World Model for Autonomous Driving
by: Zhao, Guosheng, et al.
Published: (2026)

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving
by: Shi, Chen, et al.
Published: (2025)

GGS: Generalizable Gaussian Splatting for Lane Switching in Autonomous Driving
by: Han, Huasong, et al.
Published: (2024)