20 citations · 28 across the 5 of their papers we have counts for
5 papers
DGNN: Decoupled Graph Neural Networks with Structural Consistency between Attribute and Graph Embedding Representations
Jinlu Wang, Jipeng Guo, Yanfeng Sun +4
Graph neural networks (GNNs) demonstrate a robust capability for representation learning on graphs with complex structures, showcasing superior performance in various applications.…
Grassmannian Graph-attentional Landmark Selection for Domain Adaptation
Bin Sun, Shaofan Wang, Dehui Kong +2
Domain adaptation aims to leverage information from the source domain to improve the classification performance in the target domain. It mainly utilizes two schemes: sample reweigh…
GAN for Vision, KG for Relation: a Two-stage Deep Network for Zero-shot Action Recognition
Bin Sun, Dehui Kong, Shaofan Wang +3
Zero-shot action recognition can recognize samples of unseen classes that are unavailable in training by exploring common latent semantic representation in samples. However, most m…
Real-time Human Action Recognition Using Locally Aggregated Kinematic-Guided Skeletonlet and Supervised Hashing-by-Analysis Model
Bin Sun, Shaofan Wang, Dehui Kong +2
3D action recognition is referred to as the classification of action sequences which consist of 3D skeleton joints. While many research work are devoted to 3D action recognition, i…
Connectivity-preserving Geometry Images
Shaofan Wang, Dehui Kong, Juan Xue +4
We propose connectivity-preserving geometry images (CGIMs), which map a three-dimensional mesh onto a rectangular regular array of an image, such that the reconstructed mesh produc…