Puffin-World: Scaling a Unified Multimodal Model with Native 3D World States

Puffin-World is a unified multimodal world model designed to represent and generate physically grounded 3D environments rather than only plausible RGB frames, combining appearance, depth-based geometry, and physical orientation represented through gravity and latitude. Its Omni-Camera representation merges absolute camera information with relative ray-based motion, enabling single-image camera calibration, controllable image generation, multi-view synthesis, challenging rotational and translational trajectories, and direct reconstruction without external perception modules. The system jointly connects language-based understanding with diffusion-based generation, allowing tasks to be specified through combinations of text, images, camera conditions, and role masks. To support training, the authors introduce Puffin-16M, including 15 million camera-annotated panorama-derived samples and one million varied camera trajectories, while also releasing absolute camera annotations for roughly 44.5 million images from public datasets. Reported results indicate strong camera-parameter estimation, viewpoint-controlled generation, and coherent appearance-and-geometry prediction for image-to-3D and text-to-3D tasks. Although it currently focuses on static scenes and limited physical states, the project presents its code, models, dataset, and annotations as resources for research into virtual reality, embodied intelligence, and interactive world models.

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