Is Sora a World Simulator? A Comprehensive Survey on General World Models and Beyond
<|reference_start|>Is Sora a World Simulator? A Comprehensive Survey on General World Models and Beyond: General world models represent a crucial pathway toward achieving Artificial General Intelligence (AGI), serving as the cornerstone for various applications ranging from virtual environments to decision-making systems. Recently, the emergence of the Sora model has attained significant attention due to its remarkable simulation capabilities, which exhibits an incipient comprehension of physical laws. In this survey, we embark on a comprehensive exploration of the latest advancements in world models. Our analysis navigates through the forefront of generative methodologies in video generation, where world models stand as pivotal constructs facilitating the synthesis of highly realistic visual content. Additionally, we scrutinize the burgeoning field of autonomous-driving world models, meticulously delineating their indispensable role in reshaping transportation and urban mobility. Furthermore, we delve into the intricacies inherent in world models deployed within autonomous agents, shedding light on their profound significance in enabling intelligent interactions within dynamic environmental contexts. At last, we examine challenges and limitations of world models, and discuss their potential future directions. We hope this survey can serve as a foundational reference for the research community and inspire continued innovation. This survey will be regularly updated at: https://github.com/GigaAI-research/General-World-Models-Survey.<|reference_end|>
@article{zhu2024is,
    title={Is Sora a World Simulator? A Comprehensive Survey on General World
  Models and Beyond},
    author={Zheng Zhu, Xiaofeng Wang, Wangbo Zhao, Chen Min, Nianchen Deng, Min
  Dou, Yuqi Wang, Botian Shi, Kai Wang, Chi Zhang, Yang You, Zhaoxiang Zhang,
  Dawei Zhao, Liang Xiao, Jian Zhao, Jiwen Lu, Guan Huang},
    journal={arXiv preprint arXiv:2405.03520},
    year={2024},
    archivePrefix={arXiv},
    eprint={2405.03520},
    primaryClass={cs.CV}
}