OmniRoam: World Wandering via Long-Horizon Panoramic Video Generation

• URL: http://arxiv.org/abs/2603.30045v1
• Date: Tue, 31 Mar 2026 17:59:33 GMT
• Title: OmniRoam: World Wandering via Long-Horizon Panoramic Video Generation
• Abstract summary: We propose OmniRoam, a controllable panoramic video generation framework.<n>Our framework exploits the rich per-frame scene coverage and inherent long-term spatial and temporal consistency of panoramic representation.<n> Experiments show that our framework consistently outperforms state-of-the-art methods in terms of visual quality, controllability, and long-term scene consistency.
• Score: 42.159343032593014
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Modeling scenes using video generation models has garnered growing research interest in recent years. However, most existing approaches rely on perspective video models that synthesize only limited observations of a scene, leading to issues of completeness and global consistency. We propose OmniRoam, a controllable panoramic video generation framework that exploits the rich per-frame scene coverage and inherent long-term spatial and temporal consistency of panoramic representation, enabling long-horizon scene wandering. Our framework begins with a preview stage, where a trajectory-controlled video generation model creates a quick overview of the scene from a given input image or video. Then, in the refine stage, this video is temporally extended and spatially upsampled to produce long-range, high-resolution videos, thus enabling high-fidelity world wandering. To train our model, we introduce two panoramic video datasets that incorporate both synthetic and real-world captured videos. Experiments show that our framework consistently outperforms state-of-the-art methods in terms of visual quality, controllability, and long-term scene consistency, both qualitatively and quantitatively. We further showcase several extensions of this framework, including real-time video generation and 3D reconstruction. Code is available at https://github.com/yuhengliu02/OmniRoam.

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