Paper page - WorldRover: A Scalable Synthetic Video Data Engine for World Exploration with Rich Annotations

Source: https://huggingface.co/papers/2608.15659

Abstract

WorldRover is a synthetic data engine that generates long-range, richly annotated video sequences with depth, camera motion, and tracking signals to support training models for coherent world exploration.

Learning to generate or reconstruct explorable worlds requires video paired with more than RGB: camera motion, scene geometry, temporal correspondence and, for interactive models, control signals. Real capture can provide some of these signals, but dense geometry and long-range correspondence usually rely on estimation or specialised instrumentation. Rendering provides these quantities directly, yet existing synthetic resources rarely combine them on the same frames while also supporting controlled changes of viewpoint and appearance. We introduce WorldRover, a data engine for generating richly annotated, long-range explorations of artist-built environments. At its core, WorldRover-Engine is an Unreal Engine pipeline that executes and offline-renders minute-scale routes while preserving their full trajectories and scene geometry. The same exploration can be replayed from first-person, third-person, and 360panoramic camerasunder different environmental states. Using WorldRover-Engine, we construct WorldRover-10M, whose sequences pair RGB withmetric depth,camera trajectories, and trajectory-derivedaction signalsthroughout each exploration. Third-person subsets additionally provide denseoptical flow, long-range2D/3D point trackswithvisibility, and a character trajectory distinct from the camera trajectory. The engine can render a traversal from first-person, third-person and 360 panoramic viewpoints, under different environmental states or with a neutral white material, while preserving the route and scene geometry. WorldRover therefore turns long-horizon world exploration into a scalable data-generation problem, providing supervision for models that must build, maintain, and revisit coherent representations of an explorable world.

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