40 citations · 157 across the 30 of their papers we have counts for
5 papers · 1 filter
Graph Learning-Convolutional Networks
Bo Jiang, Ziyan Zhang, Doudou Lin +1
Recently, graph Convolutional Neural Networks (graph CNNs) have been widely used for graph data representation and semi-supervised learning tasks. However, existing graph CNNs gene…
Graph Diffusion-Embedding Networks
Bo Jiang, Doudou Lin, Jin Tang
We present a novel graph diffusion-embedding networks (GDEN) for graph structured data. GDEN is motivated by our closed-form formulation on regularized feature diffusion on graph.…
Graph Laplacian Regularized Graph Convolutional Networks for Semi-supervised Learning
Bo Jiang, Doudou Lin
Recently, graph convolutional network (GCN) has been widely used for semi-supervised classification and deep feature representation on graph-structured data. However, existing GCN…
Towards Discrete Solution: A Sparse Preserving Method for Correspondence Problem
Bo Jiang
Many problems of interest in computer vision can be formulated as a problem of finding consistent correspondences between two feature sets. Feature correspondence (matching) proble…
Temporal Coherent and Graph Optimized Manifold Ranking for Visual Tracking
Bo Jiang, Doudou Lin, Bin Luo +1
Recently, weighted patch representation has been widely studied for alleviating the impact of background information included in bounding box to improve visual tracking results. Ho…