Neural Template: Topology-aware Reconstruction and Disentangled Generation of 3D Meshes. (arXiv:2206.04942v1 [cs.CV])

This paper introduces a novel framework called DTNet for 3D mesh
reconstruction and generation via Disentangled Topology. Beyond previous works,
we learn a topology-aware neural template specific to each input then deform
the template to reconstruct a detailed mesh while preserving the learned
topology. One key insight is to decouple the complex mesh reconstruction into
two sub-tasks: topology formulation and shape deformation. Thanks to the
decoupling, DT-Net implicitly learns a disentangled representation for the
topology and shape in the latent …

3d arxiv cv generation template topology