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This document presents a novel framework for the simultaneous acquisition of geometry and material properties of translucent objects using a combination of physically grounded and data-driven strategies. The approach utilizes a hybrid rendering supervision scheme that integrates a differentiable physical renderer with a learned neural renderer, allowing for improved reconstruction from flash/no-flash image pairs. The authors validate their method on a large-scale synthetic dataset and a new real-world datas

Author

benaya josua

Language

EN