Mobilenerf: Exploiting the polygon rasterization pipeline for efficient neural field rendering on mobile architectures
Abstract Neural Radiance Fields (NeRFs) have demonstrated amazing ability to synthesize
images of 3D scenes from novel views. However, they rely upon specialized volumetric …
images of 3D scenes from novel views. However, they rely upon specialized volumetric …
[PDF][PDF] Flexible Isosurface Extraction for Gradient-Based Mesh Optimization.
Flexible Isosurface Extraction for Gradient- Based Mesh Optimization Page 1 Flexible Isosurface
Extraction for GradientBased Mesh Optimization Tianchang Shen, Jacob Munkberg, Jon …
Extraction for GradientBased Mesh Optimization Tianchang Shen, Jacob Munkberg, Jon …
Neat: Learning neural implicit surfaces with arbitrary topologies from multi-view images
Recent progress in neural implicit functions has set new state-of-the-art in reconstructing
high-fidelity 3D shapes from a collection of images. However, these approaches are limited …
high-fidelity 3D shapes from a collection of images. However, these approaches are limited …
Controllable mesh generation through sparse latent point diffusion models
Mesh generation is of great value in various applications involving computer graphics and
virtual content, yet designing generative models for meshes is challenging due to their …
virtual content, yet designing generative models for meshes is challenging due to their …
What's the Situation With Intelligent Mesh Generation: A Survey and Perspectives
Intelligent Mesh Generation (IMG) represents a novel and promising field of research,
utilizing machine learning techniques to generate meshes. Despite its relative infancy, IMG …
utilizing machine learning techniques to generate meshes. Despite its relative infancy, IMG …
Voromesh: Learning watertight surface meshes with voronoi diagrams
In stark contrast to the case of images, finding a concise, learnable discrete representation of
3D surfaces remains a challenge. In particular, while polygon meshes are arguably the most …
3D surfaces remains a challenge. In particular, while polygon meshes are arguably the most …
Nerve: Neural volumetric edges for parametric curve extraction from point cloud
Extracting parametric edge curves from point clouds is a fundamental problem in 3D vision
and geometry processing. Existing approaches mainly rely on keypoint detection, a …
and geometry processing. Existing approaches mainly rely on keypoint detection, a …
Surface extraction from neural unsigned distance fields
We propose a method, named DualMesh-UDF, to extract a surface from unsigned distance
functions (UDFs), encoded by neural networks, or neural UDFs. Neural UDFs are becoming …
functions (UDFs), encoded by neural networks, or neural UDFs. Neural UDFs are becoming …
Robust zero level-set extraction from unsigned distance fields based on double covering
In this paper, we propose a new method, called DoubleCoverUDF, for extracting the zero
level-set from unsigned distance fields (UDFs). DoubleCoverUDF takes a learned UDF and …
level-set from unsigned distance fields (UDFs). DoubleCoverUDF takes a learned UDF and …
Robust low-poly meshing for general 3d models
We propose a robust re-meshing approach that can automatically generate visual-
preserving low-poly meshes for any high-poly models found in the wild. Our method can be …
preserving low-poly meshes for any high-poly models found in the wild. Our method can be …