26 citations · 72 across the 18 of their papers we have counts for
26 papers
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…
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…
Neuro-Spectral Architectures for Causal Physics-Informed Networks
Arthur Bizzi, Leonardo M. Moreira, Márcio Marques +9
Physics-Informed Neural Networks (PINNs) have emerged as a powerful framework for solving partial differential equations (PDEs). However, standard MLP-based PINNs often fail to con…
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…
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…
Understanding Sinusoidal Neural Networks
Tiago Novello
In this work, we investigate the structure and representation capacity of sinusoidal MLPs - multilayer perceptron networks that use sine as the activation function. These neural ne…
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…
Neural Implicit Surface Evolution
Tiago Novello, Vinicius da Silva, Guilherme Schardong +3
This work investigates the use of smooth neural networks for modeling dynamic variations of implicit surfaces under the level set equation (LSE). For this, it extends the represent…
Exploring Differential Geometry in Neural Implicits
Tiago Novello, Guilherme Schardong, Luiz Schirmer +3
We introduce a neural implicit framework that exploits the differentiable properties of neural networks and the discrete geometry of point-sampled surfaces to approximate them as t…
Neural Implicit Mapping via Nested Neighborhoods
Vinícius da Silva, Tiago Novello, Guilherme Schardong +3
We introduce a novel approach for rendering static and dynamic 3D neural signed distance functions (SDF) in real-time. We rely on nested neighborhoods of zero-level sets of neural…
Real-time rendering of complex fractals
Vinícius da Silva, Tiago Novello, Hélio Lopes +1
This chapter describes how to use intersection and closest-hit shaders to implement real-time visualizations of complex fractals using distance functions. The Mandelbulb and Julia…
Proceduray -- A light-weight engine for procedural primitive ray tracing
Vinícius da Silva, Tiago Novello, Hélio Lopes +1
We introduce Proceduray, an engine for real-time ray tracing of procedural geometry. Its motivation is the current lack of mid-level abstraction tools for scenes with primitives in…
Design and visualization of Riemannian metrics
Tiago Novello, Vinícius da Silva, Luiz Velho
Local and global illumination were recently defined in Riemannian manifolds to visualize classical Non-Euclidean spaces. This work focuses on Riemannian metric construction in $\ma…
How to see the eight Thurston geometries
Tiago Novello, Vinícius da Silva, Luiz Velho +1
In this expository paper, we present a survey about the history of the geometrization conjecture and the background material on the classification of Thurston's eight geometries. W…
Global Illumination of non-Euclidean spaces
Tiago Novello, Vinicius da Silva, Luiz Velho
This paper presents a path tracer algorithm to compute the global illumination of non-Euclidean manifolds. We use the 3D torus as an example.
Discrete Line Fields on Surfaces
Tiago Novello, João Paixão, Carlos Tomei +1
Vector fields and line fields, their counterparts without orientations on tangent lines, are familiar objects in the theory of dynamical systems. Among the techniques used in their…