Dual Graph Convolutional Network for Hyperspectral Images With Spatial Graph and Spectral Multigraph
Abstract: To accurately represent the graph structure of the pixel nodes in the hyperspectral remote sensing image classification based on graph convolutional networks (GCNs), a spectral multigraph ...
This is the code repository for our IEEE VIS19 Paper entitled "DeepDrawing: A Deep Learning Approach to Graph Drawing". We propose a deep learning based approach to learn from existing graph drawings ...
We address the task of Probabilistic 3D Human Motion Prediction: from the past, predict the future. Here is an example from AMASS: Together with the latent diffusion model SkeletonDiffusion, we ...
Abstract: Graph representation is an important part of graph clustering. Recently, contrastive learning, which maximizes the mutual information between augmented graph views that share the same ...
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