9 citations · 11 across the 5 of their papers we have counts for
6 papers
FSD-CAP: Fractional Subgraph Diffusion with Class-Aware Propagation for Graph Feature Imputation
Xin Qiao, Shijie Sun, Anqi Dong +5
Imputing missing node features in graphs is challenging, particularly under high missing rates. Existing methods based on latent representations or global diffusion often fail to p…
Multi-Granularity Mutual Refinement Network for Zero-Shot Learning
Ning Wang, Long Yu, Cong Hua +5
Zero-shot learning (ZSL) aims to recognize unseen classes with zero samples by transferring semantic knowledge from seen classes. Current approaches typically correlate global visu…
Intervening in Black Box: Concept Bottleneck Model for Enhancing Human Neural Network Mutual Understanding
Nuoye Xiong, Anqi Dong, Ning Wang +5
Recent advances in deep learning have led to increasingly complex models with deeper layers and more parameters, reducing interpretability and making their decisions harder to unde…
Spatial Parsing and Dynamic Temporal Pooling networks for Human-Object Interaction detection
Hongsheng Li, Guangming Zhu, Wu Zhen +5
The key of Human-Object Interaction(HOI) recognition is to infer the relationship between human and objects. Recently, the image's Human-Object Interaction(HOI) detection has made…
Spatio-Temporal Interaction Graph Parsing Networks for Human-Object Interaction Recognition
Ning Wang, Guangming Zhu, Liang Zhang +3
For a given video-based Human-Object Interaction scene, modeling the spatio-temporal relationship between humans and objects are the important cue to understand the contextual info…
A Systematic Collection of Medical Image Datasets for Deep Learning
Johann Li, Guangming Zhu, Cong Hua +11
The astounding success made by artificial intelligence (AI) in healthcare and other fields proves that AI can achieve human-like performance. However, success always comes with cha…