Kavli Affiliate: Zheng Zhu
| First 5 Authors: Zheng Zhu, Xiaofeng Wang, Wangbo Zhao, Chen Min, Nianchen Deng
| Summary:
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.
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