The Matrix: Infinite-Horizon World Generation with Real-Time Moving Control

Ruili Feng, Han Zhang, Zhantao Yang, Jie Xiao, Zhilei Shu +5 more
12/4/2024
cs.AI

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Abstract

We present The Matrix, the first foundational realistic world simulator capable of generating continuous 720p high-fidelity real-scene video streams with real-time, responsive control in both first- and third-person perspectives, enabling immersive exploration of richly dynamic environments. Trained on limited supervised data from AAA games like Forza Horizon 5 and Cyberpunk 2077, complemented by large-scale unsupervised footage from real-world settings like Tokyo streets, The Matrix allows users to traverse diverse terrains -- deserts, grasslands, water bodies, and urban landscapes -- in continuous, uncut hour-long sequences. Operating at 16 FPS, the system supports real-time interactivity and demonstrates zero-shot generalization, translating virtual game environments to real-world contexts where collecting continuous movement data is often infeasible. For example, The Matrix can simulate a BMW X3 driving through an office setting--an environment present in neither gaming data nor real-world sources. This approach showcases the potential of AAA game data to advance robust world models, bridging the gap between simulations and real-world applications in scenarios with limited data.

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@article{feng2024matrix,
  title  = {The Matrix: Infinite-Horizon World Generation with Real-Time Moving Control},
  author = {Ruili Feng and Han Zhang and Zhantao Yang and Jie Xiao and Zhilei Shu and Zhiheng Liu and Andy Zheng and Yukun Huang and Yu Liu and Hongyang Zhang},
  year   = {2024},
  eprint = {2412.03568},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2412.03568v1}
}

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