Cover Image

DriveLaW:Unifying Planning and Video Generation in a Latent Driving World

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Xia, Tianze, Li, Yongkang, Zhou, Lijun, Yao, Jingfeng, Xiong, Kaixin, Sun, Haiyang, Wang, Bing, Ma, Kun, Chen, Guang, Ye, Hangjun, Liu, Wenyu, Wang, Xinggang
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

UniDriveVLA: Unifying Understanding, Perception, and Action Planning for Autonomous Driving
by: Li, Yongkang, et al.
Published: (2026)

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

Genesis: Multimodal Driving Scene Generation with Spatio-Temporal and Cross-Modal Consistency
by: Guo, Xiangyu, et al.
Published: (2025)

Mirage: One-Step Video Diffusion for Photorealistic and Coherent Asset Editing in Driving Scenes
by: Wang, Shuyun, et al.
Published: (2025)

Rethinking Driving World Model as Synthetic Data Generator for Perception Tasks
by: Zeng, Kai, et al.
Published: (2025)

Toward Physically Consistent Driving Video World Models under Challenging Trajectories
by: Zhou, 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)

UFO: Unifying Feed-Forward and Optimization-based Methods for Large Driving Scene Modeling
by: Tan, Kaiyuan, et al.
Published: (2026)

WorldSplat: Gaussian-Centric Feed-Forward 4D Scene Generation for Autonomous Driving
by: Zhu, Ziyue, et al.
Published: (2025)

Matte Anything: Interactive Natural Image Matting with Segment Anything Models
by: Yao, Jingfeng, et al.
Published: (2023)

Reconstruction vs. Generation: Taming Optimization Dilemma in Latent Diffusion Models
by: Yao, Jingfeng, et al.
Published: (2025)

FasterDiT: Towards Faster Diffusion Transformers Training without Architecture Modification
by: Yao, Jingfeng, et al.
Published: (2024)

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

CoGen: 3D Consistent Video Generation via Adaptive Conditioning for Autonomous Driving
by: Ji, Yishen, et al.
Published: (2025)

AlphaDrive: Unleashing the Power of VLMs in Autonomous Driving via Reinforcement Learning and Reasoning
by: Jiang, Bo, et al.
Published: (2025)

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

LVDrive: Latent Visual Representation Enhanced Vision-Language-Action Autonomous Driving Model
by: Mei, Xiaodong, et al.
Published: (2026)

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

Turbo-VAED: Fast and Stable Transfer of Video-VAEs to Mobile Devices
by: Zou, Ya, et al.
Published: (2025)

BEVWorld: A Multimodal World Simulator for Autonomous Driving via Scene-Level BEV Latents
by: Zhang, Yumeng, et al.
Published: (2024)

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

PointForward: Feedforward Driving Reconstruction through Point-Aligned Representations
by: Chi, Cheng, et al.
Published: (2026)

WorldRFT: Latent World Model Planning with Reinforcement Fine-Tuning for Autonomous Driving
by: Yang, Pengxuan, et al.
Published: (2025)

DriveMRP: Enhancing Vision-Language Models with Synthetic Motion Data for Motion Risk Prediction
by: Hou, Zhiyi, et al.
Published: (2025)

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

DGGT: Feedforward 4D Reconstruction of Dynamic Driving Scenes using Unposed Images
by: Chen, Xiaoxue, et al.
Published: (2025)

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

ViSE: A Systematic Approach to Vision-Only Street-View Extrapolation
by: Tan, Kaiyuan, et al.
Published: (2025)

LaST-VLA: Thinking in Latent Spatio-Temporal Space for Vision-Language-Action in Autonomous Driving
by: Luo, Yuechen, et al.
Published: (2026)

LKCell: Efficient Cell Nuclei Instance Segmentation with Large Convolution Kernels
by: Cui, Ziwei, et al.
Published: (2024)

ViTGaze: Gaze Following with Interaction Features in Vision Transformers
by: Song, Yuehao, et al.
Published: (2024)

DiffusionVL: Translating Any Autoregressive Models into Diffusion Vision Language Models
by: Zeng, Lunbin, et al.
Published: (2025)

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

VGGDrive: Empowering Vision-Language Models with Cross-View Geometric Grounding for Autonomous Driving
by: Wang, Jie, et al.
Published: (2026)

DriveVLA-W0: World Models Amplify Data Scaling Law in Autonomous Driving
by: Li, Yingyan, et al.
Published: (2025)

SimScale: Learning to Drive via Real-World Simulation at Scale
by: Tian, Haochen, et al.
Published: (2025)

Mask-Adapter: The Devil is in the Masks for Open-Vocabulary Segmentation
by: Li, Yongkang, et al.
Published: (2024)

DiffusionDriveV2: Reinforcement Learning-Constrained Truncated Diffusion Modeling in End-to-End Autonomous Driving
by: Zou, Jialv, et al.
Published: (2025)

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

MeanFuser: Fast One-Step Multi-Modal Trajectory Generation and Adaptive Reconstruction via MeanFlow for End-to-End Autonomous Driving
by: Wang, Junli, et al.
Published: (2026)