Panode: World Exploration via Incremental Panoramic Node Generation

Generating explorable worlds from a single image is a foundational capability for interactive content creation. Existing methods mostly expand the world through perspective video generation, leading to error accumulation over long-range exploration. To address this, we present **Panode**, which recasts world exploration as sparse panoramic node generation. Instead of densely sampling frames, we build up the world from a sequence of panoramic nodes, each producing a full 360° observation. At each node, a generative model jointly completes the panoramic RGB and depth, yielding a geometry-consistent omnidirectional observation. The new RGB-D panorama is then lifted into a 3D Gaussian scene and refined via sliding-window optimization over recent nodes. For efficient exploration, we further design an active trajectory planner that chooses the next node by balancing exploration value against motion feasibility. By tightly coupling generation, reconstruction, and planning, Panode progressively expands a single image into a coherent, explorable world. Experiments demonstrate that Panode achieves strong generation quality and exploration efficiency.