17 citations · 18 across the 5 of their papers we have counts for
6 papers
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…
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…