Neural implicit representation is a promising approach for reconstructing surfaces from point
clouds. Existing methods combine various regularization terms, such as the Eikonal and …

How to realize the switching between various topology optimization approaches such as
SIMP and moving morphable component (MMC) method, is a crucial challenge in the field of …

Surface reconstruction is a challenging task when input point clouds, especially real scans,
are noisy and lack normals. Observing that the Multilayer Perceptron (MLP) and the implicit …

Despite recent advances in reconstructing an organic model with the neural signed distance
function (SDF), the high-fidelity reconstruction of a CAD model directly from low-quality …

Constructing smooth surface representations from point clouds is a fundamental problem in
geometric modeling and computer graphics, and a wealthy of literature has focused on this …

The three-dimensional structures and shapes of biomolecules provide essential information
about their interactions and functions. Unfortunately, the computational cost of biomolecular …

In this paper, we propose a method of reconstructing surface from point cloud using sparse
ellipsoid radial basis functions (RBFs). The experimental results illustrate that our method …

Geometric shape representation algorithms are key technologies in the fields of computer
graphics and geometric modeling. The Medial Axis Transform (MAT) is an important …

In this paper, we propose a model and algorithm for sparse representing Gaussian
molecular surface. The original Gaussian molecular surface is approximated by a relatively …