Reconstruction of a continuous surface of two-dimensional manifold from its raw, discrete
point cloud observation is a long-standing problem in computer vision and graphics …

We introduce MeshGPT a new approach for generating triangle meshes that reflects the
compactness typical of artist-created meshes in contrast to dense triangle meshes extracted …

Currently it requires an artist to create 3D human avatars with realistic clothing that can
move naturally. Despite progress on 3D scanning and modeling of human bodies, there is …

We introduce neural dual contouring (NDC), a new data-driven approach to mesh
reconstruction based on dual contouring (DC). Like traditional DC, it produces exactly one …

Learning to model and reconstruct humans in clothing is challenging due to articulation, non-
rigid deformation, and varying clothing types and topologies. To enable learning, the choice …

Intelligent Mesh Generation (IMG) represents a novel and promising field of research,
utilizing machine learning techniques to generate meshes. Despite its relative infancy, IMG …

Constrained by the limitations of learning toolkits engineered for other applications, such as
those in image processing, many mesh-based learning algorithms employ data flows that …

Abstract We introduce Point2Skeleton, an unsupervised method to learn skeletal
representations from point clouds. Existing skeletonization methods are limited to tubular …

We present a method for reconstructing triangle meshes from point clouds. Existing learning-
based methods for mesh reconstruction mostly generate triangles individually, making it …

The task of explicit surface reconstruction is to generate a surface mesh by interpolating a
given point cloud. Explicit surface reconstruction is necessary when the point cloud is …