INSPATIO-WORLD: A Real-Time 4D World Simulator via Spatiotemporal Autoregressive Modeling
Authors: name: InSpatio Team, name: Donghui Shen, name: Guofeng Zhang, name: Haomin Liu, name: Haoyu Ji, name: Hujun Bao, name: Hongjia Zhai, name: Jialin Liu, name: Jing Guo, name: Nan Wang, name: Siji Pan, name: Weihong Pan, name: Weijian Xie, name: Xianbin Liu, name: Xiaojun Xiang, name: Xiaoyu Zhang, name: Xinyu Chen, name: Yifu Wang, name: Yipeng Chen, name: Zhenzhou Fan, name: Zhewen Le, name: Zhichao Ye, name: Ziqiang Zhao

Building world models with spatial consistency and real-time interactivity remains a fundamental challenge in computer vision. Current video generation paradigms often struggle with a lack of spatial persistence and insufficient visual realism, making it difficult to support seamless navigation in complex environments. To address these challenges, we propose INSPATIO-WORLD, a novel real-time framework capable of recovering and generating high-fidelity, dynamic interactive scenes from a single reference video. At the core of our approach is a Spatiotemporal Autoregressive (STAR) architecture, which enables consistent and controllable scene evolution through two tightly coupled components: Implicit Spatiotemporal Cache aggregates reference and historical observations into a latent world representation, ensuring global consistency during long-horizon navigation; Explicit Spatial Constraint Module enforces geometric structure and translates user interactions into precise and physically plausible camera trajectories. Furthermore, we introduce Joint Distribution Matching Distillation (JDMD). By using real-world data distributions as a regularizing guide, JDMD effectively overcomes the fidelity degradation typically caused by over-reliance on synthetic data. Extensive experiments demonstrate that INSPATIO-WORLD significantly outperforms existing state-of-the-art (SOTA) models in spatial consistency and interaction precision, ranking first among real-time interactive methods on the WorldScore-Dynamic benchmark, and establishing a practical pipeline for navigating 4D environments reconstructed from monocular videos.