The recent advances in 3D sensing technology have made possible the capture of point
clouds in significantly high resolution. However, increased detail usually comes at the …

The recent proliferation of 3D content that can be consumed on hand-held devices
necessitates efficient tools for transmitting large geometric data, eg, 3D meshes, over the …

Reducing a graph while preserving its overall structure is an important problem with many
applications. Typically, reduction approaches either remove edges (sparsification) or merge …

Geodesic paths and distances are among the most popular intrinsic properties of 3D
surfaces. Traditionally, geodesic paths on discrete polygon surfaces were computed using …

Geometric feature learning for 3-D surfaces is critical for many applications in computer
graphics and 3-D vision. However, deep learning currently lags in hierarchical modeling of 3 …

With the expansion of model scale and the improvement of model accuracy, the real-time
rendering and displaying of 3D mesh models remain infeasible. To relieve such pressure …

Abstract Most three-dimensional (3D) computer-aided design (CAD) models of mechanical
parts, created during the design stage, have high shape complexity. The shape complexity …

This paper introduces a new learning-based method, NASM, for anisotropic surface
meshing. Our key idea is to propose a graph neural network to embed an input mesh into a …

Text-to-3D generation is a challenging but significant task and has gained widespread
attention. Its capability to rapidly generate 3D digital assets holds huge potential application …

Recent work on using neural fields to represent surfaces has resulted in significant
improvements in representational capability and computational efficiency. However, to our …