195 citations · 787 across the 32 of their papers we have counts for
6 papers · 1 filter
Differentiable Manifold Reconstruction for Point Cloud Denoising
Shitong Luo, Wei Hu
3D point clouds are often perturbed by noise due to the inherent limitation of acquisition equipments, which obstructs downstream tasks such as surface reconstruction, rendering an…
Graph Signal Processing for Geometric Data and Beyond: Theory and Applications
Wei Hu, Jiahao Pang, Xianming Liu +3
Geometric data acquired from real-world scenes, e.g., 2D depth images, 3D point clouds, and 4D dynamic point clouds, have found a wide range of applications including immersive tel…
Edge-aware Graph Representation Learning and Reasoning for Face Parsing
Gusi Te, Yinglu Liu, Wei Hu +2
Face parsing infers a pixel-wise label to each facial component, which has drawn much attention recently. Previous methods have shown their efficiency in face parsing, which howeve…
Signed Graph Metric Learning via Gershgorin Disc Perfect Alignment
Cheng Yang, Gene Cheung, Wei Hu
Given a convex and differentiable objective $Q(\M)$ for a real symmetric matrix $\M$ in the positive definite (PD) cone -- used to compute Mahalanobis distances -- we propose a fas…
Dynamic Point Cloud Denoising via Manifold-to-Manifold Distance
Wei Hu, Qianjiang Hu, Zehua Wang +1
3D dynamic point clouds provide a natural discrete representation of real-world objects or scenes in motion, with a wide range of applications in immersive telepresence, autonomous…
Graph Metric Learning via Gershgorin Disc Alignment
Cheng Yang, Gene Cheung, Wei Hu
We propose a fast general projection-free metric learning framework, where the minimization objective is a convex differentiable f…