MeshSDF

Makes the mesh extracted from a deep signed distance function differentiable: it derives how each surface vertex moves when the implicit field changes, so a loss on the explicit mesh (here, drag from a pressure-predicting mesh CNN) can be back-propagated to the latent shape code, and the topology may change.

Published

NeurIPS

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