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OpenWorldLib: A Unified Codebase and Definition of Advanced World Models

DataFlow Team, Bohan Zeng, Daili Hua, Kaixin Zhu, Yifan Dai, Bozhou Li, Yuran Wang, Chengzhuo Tong, Yifan Yang, Mingkun Chang, Jianbin Zhao, Zhou Liu, Hao Liang, Xiaochen Ma, Ruichuan An, Junbo Niu, Zimo Meng, Tianyi Bai, Meiyi Qiang, Huanyao Zhang, Zhiyou Xiao, Tianyu Guo, Qinhan Yu, Runhao Zhao, Zhengpin Li, Xinyi Huang, Yisheng Pan, Yiwen Tang, Yang Shi, Yue Ding, Xinlong Chen, Hongcheng Gao, Minglei Shi, Jialong Wu, Zekun Wang, Yuanxing Zhang, Xintao Wang, Pengfei Wan, Yiren Song, Mike Zheng Shou, Wentao Zhang

Abstract

World models have garnered significant attention as a promising research direction in artificial intelligence, yet a clear and unified definition remains lacking. In this paper, we introduce OpenWorldLib, a comprehensive and standardized inference framework for Advanced World Models. Drawing on the evolution of world models, we propose a clear definition: a world model is a model or framework centered on perception, equipped with interaction and long-term memory capabilities, for understanding and predicting the complex world. We further systematically categorize the essential capabilities of world models. Based on this definition, OpenWorldLib integrates models across different tasks within a unified framework, enabling efficient reuse and collaborative inference. Finally, we present additional reflections and analyses on potential future directions for world model research. Code link: https://github.com/OpenDCAI/OpenWorldLib

OpenWorldLib: A Unified Codebase and Definition of Advanced World Models

Abstract

World models have garnered significant attention as a promising research direction in artificial intelligence, yet a clear and unified definition remains lacking. In this paper, we introduce OpenWorldLib, a comprehensive and standardized inference framework for Advanced World Models. Drawing on the evolution of world models, we propose a clear definition: a world model is a model or framework centered on perception, equipped with interaction and long-term memory capabilities, for understanding and predicting the complex world. We further systematically categorize the essential capabilities of world models. Based on this definition, OpenWorldLib integrates models across different tasks within a unified framework, enabling efficient reuse and collaborative inference. Finally, we present additional reflections and analyses on potential future directions for world model research. Code link: https://github.com/OpenDCAI/OpenWorldLib

Paper Structure

This paper contains 28 sections, 1 equation, 6 figures.

Table of Contents

  1. Introduction
  2. Background and Related Works
  3. World Model Related Tasks
  4. Interactivate Video Generation.
  5. Multimodal Reasoning.
  6. Vision-Language-Action.
  7. The Role of 3D and Simulators in World Models
  8. Methods Not Considered World Models
  9. OpenWorldLib Framework Design
  10. Operator
  11. Synthesis Module
  12. Visual Synthesis
  13. Audio Synthesis
  14. Other Signal Synthesis
  15. Reasoning Module
  16. ...and 13 more sections

Figures (6)

  • Figure 1: Overview of our OpenWorldLib. Our OpenWorldLib establishes a unified framework for existing world model-related tasks, encompassing perception, understanding, memory, and generation of physical world inputs.
  • Figure 2: Illustration of our OpenWorldLib framework.
  • Figure 3: Demonstration of world model Implicit representation and explicit representation.
  • Figure 4: Demonstration of interactive video generation results.
  • Figure 5: Demonstration of 3D scene generation results.
  • ...and 1 more figures