29 citations · 51 across the 9 of their papers we have counts for
9 papers
Mask-aware inference with State-Space Models
Ignasi Mas, Ramon Morros, Javier-Ruiz Hidalgo +1
Many real-world computer vision tasks, such as depth completion, must handle inputs with arbitrarily shaped regions of missing or invalid data. For Convolutional Neural Networks (C…
Learning task-specific features for 3D pointcloud graph creation
Elías Abad-Rocamora, Javier Ruiz-Hidalgo
Processing 3D pointclouds with Deep Learning methods is not an easy task. A common choice is to do so with Graph Neural Networks, but this framework involves the creation of edges…
SkinningNet: Two-Stream Graph Convolutional Neural Network for Skinning Prediction of Synthetic Characters
Albert Mosella-Montoro, Javier Ruiz-Hidalgo
This work presents SkinningNet, an end-to-end Two-Stream Graph Neural Network architecture that computes skinning weights from an input mesh and its associated skeleton, without ma…
Channel redundancy and overlap in convolutional neural networks with channel-wise NNK graphs
David Bonet, Antonio Ortega, Javier Ruiz-Hidalgo +1
Feature spaces in the deep layers of convolutional neural networks (CNNs) are often very high-dimensional and difficult to interpret. However, convolutional layers consist of multi…
2D-3D Geometric Fusion Network using Multi-Neighbourhood Graph Convolution for RGB-D Indoor Scene Classification
Albert Mosella-Montoro, Javier Ruiz-Hidalgo
Multi-modal fusion has been proved to help enhance the performance of scene classification tasks. This paper presents a 2D-3D Fusion stage that combines 3D Geometric Features with…
FuCiTNet: Improving the generalization of deep learning networks by the fusion of learned class-inherent transformations
Manuel Rey-Area, Emilio Guirado, Siham Tabik +1
It is widely known that very small datasets produce overfitting in Deep Neural Networks (DNNs), i.e., the network becomes highly biased to the data it has been trained on. This iss…
3D hierarchical optimization for Multi-view depth map coding
Marc Maceira, David Varas, Josep-Ramon Morros +2
Depth data has a widespread use since the popularity of high-resolution 3D sensors. In multi-view sequences, depth information is used to supplement the color data of each view. Th…
Residual Attention Graph Convolutional Network for Geometric 3D Scene Classification
Albert Mosella-Montoro, Javier Ruiz-Hidalgo
Geometric 3D scene classification is a very challenging task. Current methodologies extract the geometric information using only a depth channel provided by an RGB-D sensor. These…
Hybrid Cosine Based Convolutional Neural Networks
Adrià Ciurana, Albert Mosella-Montoro, Javier Ruiz-Hidalgo
Convolutional neural networks (CNNs) have demonstrated their capability to solve different kind of problems in a very huge number of applications. However, CNNs are limited for the…