DUDF: Differentiable Unsigned Distance Fields with Hyperbolic Scaling

Mostrar todas las versiones(3)

In recent years, there has been a growing interest in training Neural Networks to approximate Unsigned Distance Fields (UDFs) for representing open surfaces in the context of 3D reconstruction. However, UDFs are non-differentiable at the zero level set which leads to significant errors in distances...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autores principales: Fainstein, Miguel, Siless, Viviana, Iarussi, Emmanuel
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2024
Materias:
Ciencias Informáticas
Neural implicit representations
Unsigned distance functions
Open surfaces
Deep neural networks
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/178813
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata

Ejemplares similares

Ejemplares similares