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Digital Twin-Driven Real2Sim2Real for Simulator-Conditioned Data Generation
US & West ·
The study examines how far a DT-R2S2R pipeline can substitute for real target-region data: recorded driving clips are reconstructed in a georeferenced digital twin and a diffusion model is conditioned on geometrically aligned simulator renderings, yielding a digital-twin-grounded Sim2Real model.
Why it matters
It shows a practical way to cut data costs for perception and prediction in a new region using a georeferenced digital twin instead of manual annotation.
arXiv:2610.31864v1 Announce Type: new Abstract: Existing stealthy attacks presuppose white- or grey-box access to the target system, unrealistic in practice. This paper develops a model-free stealthy attack framework that learns an attack policy directly from nominal measurement data, without…
Wireless digital twins (DTs) are increasingly integrated with artificial intelligence to support online modeling, prediction, and network optimization. However, most existing approaches perform adaptation within predefined learning or optimization structures, which may become unsuitable when…