Cover Image

ConsisDrive: Identity-Preserving Driving World Models for Video Generation by Instance Mask

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Yang, Zhuoran, Zhang, Yanyong
Format:	Preprint
Published:	2026
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

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

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

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

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

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

DreamWorld: Unified World Modeling in Video Generation
by: Tan, Boming, et al.
Published: (2026)

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

Foundation Models for Amodal Video Instance Segmentation in Automated Driving
by: Breitenstein, Jasmin, et al.
Published: (2024)

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

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

Self-Supervised Pre-training with Combined Datasets for 3D Perception in Autonomous Driving
by: Wang, Shumin, et al.
Published: (2025)

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

Drive&Gen: Co-Evaluating End-to-End Driving and Video Generation Models
by: Wang, Jiahao, et al.
Published: (2025)

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

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

WildActor: Unconstrained Identity-Preserving Video Generation
by: Guo, Qin, et al.
Published: (2026)

MIM4D: Masked Modeling with Multi-View Video for Autonomous Driving Representation Learning
by: Zou, Jialv, et al.
Published: (2024)

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

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

Cosmos-Drive-Dreams: Scalable Synthetic Driving Data Generation with World Foundation Models
by: Ren, Xuanchi, et al.
Published: (2025)

DriveCtrl: Conditioned Sim-to-Real Driving Video Generation
by: Zhao, Haonan, et al.
Published: (2026)

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

ConsiStyle: Style Diversity in Training-Free Consistent T2I Generation
by: Mazuz, Yohai, et al.
Published: (2025)

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

InstDrive: Instance-Aware 3D Gaussian Splatting for Driving Scenes
by: Liu, Hongyuan, et al.
Published: (2025)

Are AI-Generated Driving Videos Ready for Autonomous Driving? A Diagnostic Evaluation Framework
by: Xiang, Xinhao, et al.
Published: (2025)

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

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

DriveFine: Refining-Augmented Masked Diffusion VLA for Precise and Robust Driving
by: Dang, Chenxu, et al.
Published: (2026)

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

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

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)

Panacea+: Panoramic and Controllable Video Generation for Autonomous Driving
by: Wen, Yuqing, et al.
Published: (2024)

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

MARS: An Instance-aware, Modular and Realistic Simulator for Autonomous Driving
by: Wu, Zirui, et al.
Published: (2023)

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

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

FAR-Drive: Frame-AutoRegressive Video Generation in Closed-Loop Autonomous Driving
by: Li, Yaoru, et al.
Published: (2026)

DriveScape: Towards High-Resolution Controllable Multi-View Driving Video Generation
by: Wu, Wei, et al.
Published: (2024)

Challenger: Affordable Adversarial Driving Video Generation
by: Xu, Zhiyuan, et al.
Published: (2025)