10 citations · 13 across the 6 of their papers we have counts for
8 papers
M-plicits: Neural Implicit Surfaces via Nested Multiscale Residuals
Vinícius da Silva, Isabelle Melo, Matheus Bessa +8
Encoding input coordinates with sinusoidal functions into multi-layer perceptrons (MLPs) has proven effective for implicit neural representations (INRs) of surfaces defined as zero…
Functional Gradient Descent with Adaptive Representations
Daniel Csillag, Rodrigo Schuller, Pedro Dall'Antonia +3
Functional optimization problems are typically solved by optimizing the parameters of a fixed representation, such as a neural network, resulting in highly nonconvex losses that co…
Geometric implicit neural representations for signed distance functions
Luiz Schirmer, Tiago Novello, Vinícius da Silva +5
\textit{Implicit neural representations} (INRs) have emerged as a promising framework for representing signals in low-dimensional spaces. This survey reviews the existing literatur…
Adaptive Training of INRs via Pruning and Densification
Diana Aldana, João Paulo Lima, Daniel Csillag +4
Encoding input coordinates with sinusoidal functions into multilayer perceptrons (MLPs) has proven effective for implicit neural representations (INRs) of low-dimensional signals,…
From Volume Rendering to 3D Gaussian Splatting: Theory and Applications
Vitor Pereira Matias, Daniel Perazzo, Vinicius Silva +4
The problem of 3D reconstruction from posed images is undergoing a fundamental transformation, driven by continuous advances in 3D Gaussian Splatting (3DGS). By modeling scenes exp…
FLOWING: Implicit Neural Flows for Structure-Preserving Morphing
Arthur Bizzi, Matias Grynberg, Vitor Matias +7
Morphing is a long-standing problem in vision and computer graphics, requiring a time-dependent warping for feature alignment and a blending for smooth interpolation. Recently, mul…
Tuning the Frequencies: Robust Training for Sinusoidal Neural Networks
Tiago Novello, Diana Aldana, Andre Araujo +1
Sinusoidal neural networks have been shown effective as implicit neural representations (INRs) of low-dimensional signals, due to their smoothness and high representation capacity.…
Implicit Neural Representation of Tileable Material Textures
Hallison Paz, Tiago Novello, Luiz Velho
We explore sinusoidal neural networks to represent periodic tileable textures. Our approach leverages the Fourier series by initializing the first layer of a sinusoidal neural netw…