Reconstructing a continuous surface from a raw 3D point cloud is a challenging task. Recent
methods usually train neural networks to overfit on single point clouds to infer signed …

Neural implicit surfaces can be used to recover accurate 3D geometry from imperfect point
clouds. In this work, we show that state-of-the-art techniques work by minimizing an …

Abstract The 3D Gaussian Splatting technique has significantly advanced the construction of
radiance fields from multi‐view images, enabling real‐time rendering. While point‐based …

This paper introduces CoFie, a novel local geometry-aware neural surface representation.
CoFie is motivated by the theoretical analysis of local SDFs with quadratic approximation …

Neural implicit representation, the parameterization of distance function as a coordinate
neural field, has emerged as a promising lead in tackling surface reconstruction from …

3D Gaussian Splatting (3DGS) has shown its impressive power in novel view synthesis.
However, creating relightable 3D assets, especially for objects with ill-defined shapes (eg …

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 …

Estimating consistently oriented normals for point clouds enables a number of important
applications in computer graphics such as surface reconstruction. While local normal …

We present STITCH, a novel approach for neural implicit surface reconstruction of a sparse
and irregularly spaced point cloud while enforcing topological constraints (such as having a …

Accurate 3D modeling of the ventricles through cine cardiovascular magnetic resonance
(CMR) imaging benefits precise clinical assessment of cardiac morphology and motion …