23 citations · 31 across the 5 of their papers we have counts for
5 papers
Visual Object Tracking by Segmentation with Graph Convolutional Network
Bo Jiang, Panpan Zhang, Lili Huang
Segmentation-based tracking has been actively studied in computer vision and multimedia. Superpixel based object segmentation and tracking methods are usually developed for this ta…
AttKGCN: Attribute Knowledge Graph Convolutional Network for Person Re-identification
Bo Jiang, Xixi Wang, Jin Tang
Discriminative feature representation of person image is important for person re-identification (Re-ID) task. Recently, attributes have been demonstrated beneficially in guiding fo…
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…
Multiple Graph Adversarial Learning
Bo Jiang, Ziyan Zhang, Jin Tang +1
Recently, Graph Convolutional Networks (GCNs) have been widely studied for graph-structured data representation and learning. However, in many real applications, data are coming wi…