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Disentangling geometry and texture in neural mesh representations unlocks versatile editing capabilities that traditional methods can't match.
Spear accelerates the synthesis of optimal abstract transformers by exploiting parallelism, outperforming state-of-the-art solvers in both efficiency and scalability.
