GenSP learns a continuous neural deformation model from sphere coordinates and latent codes to produce consistent spherical parameterizations for genus-0 shapes.
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cs.CV 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
ARAPDiffusion adds ARAP regularization losses to a latent diffusion model and alternates between improving the shape autoencoder and the diffusion model to learn continuous deformable shape spaces from limited data.
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GenSP: Consistent Spherical Parameterization via Learning Shape Generative Models
GenSP learns a continuous neural deformation model from sphere coordinates and latent codes to produce consistent spherical parameterizations for genus-0 shapes.
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ARAPDiffusion: ARAP Regularization for Diffusion-Based Deformable Shape Space Learning
ARAPDiffusion adds ARAP regularization losses to a latent diffusion model and alternates between improving the shape autoencoder and the diffusion model to learn continuous deformable shape spaces from limited data.