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Found 3 papers, 2 papers with code
PD-Flow: A Point Cloud Denoising Framework with Normalizing Flows
By considering noisy point clouds as a joint distribution of clean points and noise, the denoised results can be derived from disentangling the noise counterpart from latent point representation, and the mapping between Euclidean and latent spaces is modeled by normalizing flows.
PU-Flow: a Point Cloud Upsampling Network with Normalizing Flows
Point cloud upsampling aims to generate dense point clouds from given sparse ones, which is a challenging task due to the irregular and unordered nature of point sets.
STD-Net: Structure-preserving and Topology-adaptive Deformation Network for 3D Reconstruction from a Single Image
3D reconstruction from a single view image is a long-standing prob-lem in computer vision.
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