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DEXTERA: From a Single Image to Deployable Dexterous Manipulation via Real-to-Sim-to-Real

arXiv · AI, language, vision and robotics · article · Sep 17, 2026 · UTC

Collecting real-world robot data for dexterous manipulation is costly and time-consuming. While high-fidelity physics simulators enable scalable data synthesis and policy learning, constructing deployment-ready digital twins manually remains labor-intensive, and residual visual, geometric, and dynamics gaps hinder reliable sim-to-real transfer. We present DEXTERA, an automated real-to-sim-to-real framework that transforms a single RGB image into deployable policies for dexterous manipulation across four unified stages: (1) single-image scene factorization into a static Gaussian background and

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