26 citations · 72 across the 18 of their papers we have counts for
11 papers · 1 filter
PCAsplat: Gaussian Splatting with Local PCA Regularization
Vitor Matias, Filipe Nascimento, Kiyohiro Nakayama +6
Gaussian splatting has emerged as a flexible representation for 3D reconstruction from posed images. However, existing methods are optimized primarily using rasterization-based los…
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…
An overview of 3D Vision-Language Models
Márcus Lobo, Vitor Matias, Afonso Paiva +3
Vision-Language Models (VLMs) are reshaping computer vision by aligning visual and textual embeddings, allowing models to recognize visual concepts and reason about them using natu…
SuperFlex: Deformable Superquadrics for Point Cloud Decomposition
Gabriel Tavernini, Elisabetta Fedele, Tiago Novello +3
Superquadrics have proven to provide a compact, geometrically meaningful representation for 3D objects. However, existing methods suffer from limited reconstruction accuracy, are r…
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…
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…
Neural Implicit Morphing of Face Images
Guilherme Schardong, Tiago Novello, Hallison Paz +4
Face morphing is a problem in computer graphics with numerous artistic and forensic applications. It is challenging due to variations in pose, lighting, gender, and ethnicity. This…
Multiresolution Neural Networks for Imaging
Hallison Paz, Tiago Novello, Vinicius Silva +5
We present MR-Net, a general architecture for multiresolution neural networks, and a framework for imaging applications based on this architecture. Our coordinate-based networks ar…