Search Results for author:
Found 3 papers, 1 papers with code
Learning Smooth Neural Functions via Lipschitz Regularization
The latent descriptor of a neural field acts as a deformation handle for the 3D shape it represents.
Neural Subdivision
During inference, our method takes a coarse triangle mesh as input and recursively subdivides it to a finer geometry by applying the fixed topological updates of Loop Subdivision, but predicting vertex positions using a neural network conditioned on the local geometry of a patch.
Beyond Pixel Norm-Balls: Parametric Adversaries using an Analytically Differentiable Renderer
As such, we propose the direct perturbation of physical parameters that underly image formation: lighting and geometry.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
