Cover Image

ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Wang, Xiaodong, Peng, Peixi
Format:	Preprint
Published:	2025
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

LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model
by: Wang, Xiaodong, et al.
Published: (2025)

GaussianDWM: 3D Gaussian Driving World Model for Unified Scene Understanding and Multi-Modal Generation
by: Deng, Tianchen, et al.
Published: (2025)

UniDWM: Towards a Unified Driving World Model via Multifaceted Representation Learning
by: Liu, Shuai, et al.
Published: (2026)

LeanPO: Lean Preference Optimization for Likelihood Alignment in Video-LLMs
by: Wang, Xiaodong, et al.
Published: (2025)

FreeGen: Feed-Forward Reconstruction-Generation Co-Training for Free-Viewpoint Driving Scene Synthesis
by: Chen, Shijie, et al.
Published: (2025)

LiViBench: An Omnimodal Benchmark for Interactive Livestream Video Understanding
by: Wang, Xiaodong, et al.
Published: (2026)

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

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

GeoDrive: 3D Geometry-Informed Driving World Model with Precise Action Control
by: Chen, Anthony, et al.
Published: (2025)

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT
by: Hu, Xiaotao, et al.
Published: (2024)

Out of Sight, Out of Mind? Evaluating State Evolution in Video World Models
by: Ma, Ziqi, et al.
Published: (2026)

DriveDreamer-2: LLM-Enhanced World Models for Diverse Driving Video Generation
by: Zhao, Guosheng, et al.
Published: (2024)

UniFuture: A 4D Driving World Model for Future Generation and Perception
by: Liang, Dingkang, et al.
Published: (2025)

LiveWorld: Simulating Out-of-Sight Dynamics in Generative Video World Models
by: Duan, Zicheng, et al.
Published: (2026)

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

Incantation: Natural Language as the Action Interface for Multi-Entity Video World Models
by: Zhu, Shangwen, et al.
Published: (2026)

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

Towards Interactive Video World Modeling: Frontiers, Challenges, Benchmarks, and Future Trends
by: Liu, Jiuming, et al.
Published: (2026)

GenieDrive: Towards Physics-Aware Driving World Model with 4D Occupancy Guided Video Generation
by: Yang, Zhenya, et al.
Published: (2025)

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

GigaWorld-Policy: An Efficient Action-Centered World--Action Model
by: Ye, Angen, et al.
Published: (2026)

ConsisDrive: Identity-Preserving Driving World Models for Video Generation by Instance Mask
by: Yang, Zhuoran, et al.
Published: (2026)

Learning Vision-Language-Action World Models for Autonomous Driving
by: Wang, Guoqing, et al.
Published: (2026)

The DAWN of World-Action Interactive Models
by: Lu, Hongbo, et al.
Published: (2026)

DriveVA: Video Action Models are Zero-Shot Drivers
by: Liu, Mengmeng, et al.
Published: (2026)

Out of Sight but Not Out of Mind: Hybrid Memory for Dynamic Video World Models
by: Chen, Kaijin, et al.
Published: (2026)

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

MaskGWM: A Generalizable Driving World Model with Video Mask Reconstruction
by: Ni, Jingcheng, et al.
Published: (2025)

DriveLaW:Unifying Planning and Video Generation in a Latent Driving World
by: Xia, Tianze, et al.
Published: (2025)

Is the Future Compatible? Diagnosing Dynamic Consistency in World Action Models
by: Ruan, Bo-Kai, et al.
Published: (2026)

Toward Physically Consistent Driving Video World Models under Challenging Trajectories
by: Zhou, Jiawei, et al.
Published: (2026)

DriveMA: Driving Vision-Language-Action Models with verifiable Meta-Actions
by: Zheng, Weicheng, et al.
Published: (2026)

FutureX: Enhance End-to-End Autonomous Driving via Latent Chain-of-Thought World Model
by: Lin, Hongbin, et al.
Published: (2025)

Latent-WAM: Latent World Action Modeling for End-to-End Autonomous Driving
by: Wang, Linbo, et al.
Published: (2026)

World Models as Group Actions
by: Wang, Zijie, et al.
Published: (2026)

DynVLA: Learning World Dynamics for Action Reasoning in Autonomous Driving
by: Shang, Shuyao, et al.
Published: (2026)

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

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

OneDrive: Unified Multi-Paradigm Driving with Vision-Language-Action Models
by: Zhang, Yiwei, et al.
Published: (2026)

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