60 citations · 103 across the 4 of their papers we have counts for
8 papers
Temporal Graph Modeling for Skeleton-based Action Recognition
Jianan Li, Xuemei Xie, Zhifu Zhao +3
Graph Convolutional Networks (GCNs), which model skeleton data as graphs, have obtained remarkable performance for skeleton-based action recognition. Particularly, the temporal dyn…
From Semantic Communication to Semantic-aware Networking: Model, Architecture, and Open Problems
Guangming Shi, Yong Xiao, Yingyu Li +1
Existing communication systems are mainly built based on Shannon's information theory which deliberately ignores the semantic aspects of communication. The recent iteration of wire…
Knowledge-guided Semantic Computing Network
Guangming Shi, Zhongqiang Zhang, Dahua Gao +4
It is very useful to integrate human knowledge and experience into traditional neural networks for faster learning speed, fewer training samples and better interpretability. Howeve…
Full Image Recover for Block-Based Compressive Sensing
Xuemei Xie, Chenye Wang, Jiang Du +1
Recent years, compressive sensing (CS) has improved greatly for the application of deep learning technology. For convenience, the input image is usually measured and reconstructed…
Perceptual Compressive Sensing
Jiang Du, Xuemei Xie, Chenye Wang +1
Compressive sensing (CS) works to acquire measurements at sub-Nyquist rate and recover the scene images. Existing CS methods always recover the scene images in pixel level. This ca…
ConvCSNet: A Convolutional Compressive Sensing Framework Based on Deep Learning
Xiaotong Lu, Weisheng Dong, Peiyao Wang +2
Compressive sensing (CS), aiming to reconstruct an image/signal from a small set of random measurements has attracted considerable attentions in recent years. Due to the high dimen…