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 DMTet, a deep 3D conditional generative model that can synthesize high-
resolution 3D shapes using simple user guides such as coarse voxels. It marries the merits …

In this work, we develop intuitive controls for editing the style of 3D objects. Our framework,
Text2Mesh, stylizes a 3D mesh by predicting color and local geometric details which …

We present Magic123, a two-stage coarse-to-fine approach for high-quality, textured 3D
meshes generation from a single unposed image in the wild using both2D and 3D priors. In …

In recent years, neural implicit representations gained popularity in 3D reconstruction due to
their expressiveness and flexibility. However, the implicit nature of neural implicit …

We present a novel method for reconstructing a 3D implicit surface from a large-scale,
sparse, and noisy point cloud. Our approach builds upon the recently introduced Neural …

Surface reconstruction for point clouds is an important task in 3D computer vision. Most of
the latest methods resolve this problem by learning signed distance functions (SDF) from …

Reconstructing 3D objects from a single image guided by pretrained diffusion models has
demonstrated promising outcomes. However, due to utilizing the case-agnostic rigid …

Flexible Isosurface Extraction for Gradient- Based Mesh Optimization Page 1 Flexible Isosurface
Extraction for GradientBased Mesh Optimization Tianchang Shen, Jacob Munkberg, Jon …

We present SP-GAN, a new unsupervised sphere-guided generative model for direct
synthesis of 3D shapes in the form of point clouds. Compared with existing models, SP-GAN …