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Related papers: Is Your Driving World Model an All-Around Player?

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Vision Large Language Models (VLLMs) have demonstrated impressive capabilities in general visual tasks such as image captioning and visual question answering. However, their effectiveness in specialized, safety-critical domains like…

Computer Vision and Pattern Recognition · Computer Science 2025-04-22 Tong Zeng , Longfeng Wu , Liang Shi , Dawei Zhou , Feng Guo

Video generation has witnessed significant advancements, yet evaluating these models remains a challenge. A comprehensive evaluation benchmark for video generation is indispensable for two reasons: 1) Existing metrics do not fully align…

Computer Vision and Pattern Recognition · Computer Science 2024-11-21 Ziqi Huang , Fan Zhang , Xiaojie Xu , Yinan He , Jiashuo Yu , Ziyue Dong , Qianli Ma , Nattapol Chanpaisit , Chenyang Si , Yuming Jiang , Yaohui Wang , Xinyuan Chen , Ying-Cong Chen , Limin Wang , Dahua Lin , Yu Qiao , Ziwei Liu

Video generation has witnessed significant advancements, yet evaluating these models remains a challenge. A comprehensive evaluation benchmark for video generation is indispensable for two reasons: 1) Existing metrics do not fully align…

Computer Vision and Pattern Recognition · Computer Science 2023-12-01 Ziqi Huang , Yinan He , Jiashuo Yu , Fan Zhang , Chenyang Si , Yuming Jiang , Yuanhan Zhang , Tianxing Wu , Qingyang Jin , Nattapol Chanpaisit , Yaohui Wang , Xinyuan Chen , Limin Wang , Dahua Lin , Yu Qiao , Ziwei Liu

World models - generative models that simulate environment dynamics conditioned on past observations and actions - are gaining prominence in planning, simulation, and embodied AI. However, evaluating their rollouts remains a fundamental…

Autonomous driving world models are expected to work effectively across three core dimensions: state, action, and reward. Existing models, however, are typically restricted to limited state modalities, short video sequences, imprecise…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Bohan Li , Zhuang Ma , Dalong Du , Baorui Peng , Zhujin Liang , Zhenqiang Liu , Chao Ma , Yueming Jin , Hao Zhao , Wenjun Zeng , Xin Jin

Recent advances in creative AI have enabled the synthesis of high-fidelity images and videos conditioned on language instructions. Building on these developments, text-to-video diffusion models have evolved into embodied world models (EWMs)…

Robotics · Computer Science 2025-05-20 Hu Yue , Siyuan Huang , Yue Liao , Shengcong Chen , Pengfei Zhou , Liliang Chen , Maoqing Yao , Guanghui Ren

Recent research has been increasingly focusing on developing 3D world models that simulate complex real-world scenarios. World models have found broad applications across various domains, including embodied AI, autonomous driving,…

Artificial Intelligence · Computer Science 2025-09-09 Yinglin Duan , Zhengxia Zou , Tongwei Gu , Wei Jia , Zhan Zhao , Luyi Xu , Xinzhu Liu , Yenan Lin , Hao Jiang , Kang Chen , Shuang Qiu

Recent advancements in large vision language models (VLMs) tailored for autonomous driving (AD) have shown strong scene understanding and reasoning capabilities, making them undeniable candidates for end-to-end driving systems. However,…

Computer Vision and Pattern Recognition · Computer Science 2026-01-05 Shuo Xing , Hongyuan Hua , Xiangbo Gao , Shenzhe Zhu , Renjie Li , Kexin Tian , Xiaopeng Li , Heng Huang , Tianbao Yang , Zhangyang Wang , Yang Zhou , Huaxiu Yao , Zhengzhong Tu

World models have emerged as a critical frontier in AI research, aiming to enhance large models by infusing them with physical dynamics and world knowledge. The core objective is to enable agents to understand, predict, and interact with…

We consider the problem of generating realistic traffic scenes automatically. Existing methods typically insert actors into the scene according to a set of hand-crafted heuristics and are limited in their ability to model the true…

Computer Vision and Pattern Recognition · Computer Science 2021-01-19 Shuhan Tan , Kelvin Wong , Shenlong Wang , Sivabalan Manivasagam , Mengye Ren , Raquel Urtasun

In the rapidly evolving landscape of autonomous driving, the capability to accurately predict future events and assess their implications is paramount for both safety and efficiency, critically aiding the decision-making process. World…

Machine Learning · Computer Science 2024-05-08 Yanchen Guan , Haicheng Liao , Zhenning Li , Jia Hu , Runze Yuan , Yunjian Li , Guohui Zhang , Chengzhong Xu

World models are central to building AI agents capable of flexible reasoning and planning. Yet current evaluations (i) test only properties measurable from observed interactions, such as next-frame prediction or task return, and (ii) do not…

The construction of World Models capable of learning, simulating, and reasoning about objective physical laws constitutes a foundational challenge in the pursuit of Artificial General Intelligence. Recent advancements represented by video…

Recent advancements in predictive models have demonstrated exceptional capabilities in predicting the future state of objects and scenes. However, the lack of categorization based on inherent characteristics continues to hinder the progress…

Computer Vision and Pattern Recognition · Computer Science 2024-10-24 Yiran Qin , Zhelun Shi , Jiwen Yu , Xijun Wang , Enshen Zhou , Lijun Li , Zhenfei Yin , Xihui Liu , Lu Sheng , Jing Shao , Lei Bai , Wanli Ouyang , Ruimao Zhang

Action-conditioned video prediction models (often referred to as world models) have shown strong potential for robotics applications, but existing approaches are often slow and struggle to capture physically consistent interactions over…

Vision-Language-Action (VLA) models have recently achieved notable progress in end-to-end autonomous driving by integrating perception, reasoning, and control within a unified multimodal framework. However, they often lack explicit modeling…

Computer Vision and Pattern Recognition · Computer Science 2026-04-13 Guoqing Wang , Pin Tang , Xiangxuan Ren , Guodongfang Zhao , Bailan Feng , Chao Ma

Accurately depicting the complex traffic scene is a vital component for autonomous vehicles to execute correct judgments. However, existing benchmarks tend to oversimplify the scene by solely focusing on lane perception tasks. Observing…

Computer Vision and Pattern Recognition · Computer Science 2023-10-31 Huijie Wang , Tianyu Li , Yang Li , Li Chen , Chonghao Sima , Zhenbo Liu , Bangjun Wang , Peijin Jia , Yuting Wang , Shengyin Jiang , Feng Wen , Hang Xu , Ping Luo , Junchi Yan , Wei Zhang , Hongyang Li

Recent advances in generative models have sparked exciting new possibilities in the field of autonomous vehicles. Specifically, video generation models are now being explored as controllable virtual testing environments. Simultaneously,…

Computer Vision and Pattern Recognition · Computer Science 2025-10-08 Jiahao Wang , Zhenpei Yang , Yijing Bai , Yingwei Li , Yuliang Zou , Bo Sun , Abhijit Kundu , Jose Lezama , Luna Yue Huang , Zehao Zhu , Jyh-Jing Hwang , Dragomir Anguelov , Mingxing Tan , Chiyu Max Jiang

Recent video generators achieve striking photorealism, yet remain fundamentally inconsistent in 3D. We present WorldReel, a 4D video generator that is natively spatio-temporally consistent. WorldReel jointly produces RGB frames together…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Shaoheng Fang , Hanwen Jiang , Yunpeng Bai , Niloy J. Mitra , Qixing Huang

In recent years, AI-generated videos have become increasingly realistic and sophisticated. Meanwhile, Large Vision-Language Models (LVLMs) have shown strong potential for detecting such content. However, existing evaluation protocols…

Computer Vision and Pattern Recognition · Computer Science 2026-03-20 Yueying Zou , Pei Pei Li , Zekun Li , Xinyu Guo , Xing Cui , Huaibo Huang , Ran He
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