300 citations · 927 across the 29 of their papers we have counts for
15 papers · 1 filter
GmCN: Graph Mask Convolutional Network
Bo Jiang, Beibei Wang, Jin Tang +1
Graph Convolutional Networks (GCNs) have shown very powerful for graph data representation and learning tasks. Existing GCNs usually conduct feature aggregation on a fixed neighbor…
GLMNet: Graph Learning-Matching Networks for Feature Matching
Bo Jiang, Pengfei Sun, Jin Tang +1
Recently, graph convolutional networks (GCNs) have shown great potential for the task of graph matching. It can integrate graph node feature embedding, node-wise affinity learning…
Context-Aware Graph Attention Networks
Bo Jiang, Leiling Wang, Jin Tang +1
Graph Neural Networks (GNNs) have been widely studied for graph data representation and learning. However, existing GNNs generally conduct context-aware learning on node feature re…
Edge-guided Non-local Fully Convolutional Network for Salient Object Detection
Zhengzheng Tu, Yan Ma, Chenglong Li +2
Fully Convolutional Neural Network (FCN) has been widely applied to salient object detection recently by virtue of high-level semantic feature extraction, but existing FCN based me…
Semi-supervised Learning with Adaptive Neighborhood Graph Propagation Network
Bo Jiang, Leiling Wang, Jin Tang +1
Graph Convolutional Networks (GCNs) have been widely studied for compact data representation and semi-supervised learning tasks. However, existing GCNs usually use a fixed neighbor…
Separable Reversible Data Hiding Based on Integer Mapping and Multi-MSB Prediction for Encrypted 3D Mesh Models
Zhaoxia Yin, Na Xu, Feng Wang
Reversible data hiding in encrypted domain (RDH-ED) has received tremendous attention from the research community because data can be embedded into cover media without exposing it…