activity
20192023
most citedAn Attention Enhanced Graph Convolutional LSTM Network for Skeleton-Based Action Recognition

97 citations · 116 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2023★ 9 cited

Semantic Prompt for Few-Shot Image Recognition

Wentao Chen, Chenyang Si, Zhang Zhang +3

Few-shot learning is a challenging problem since only a few examples are provided to recognize a new class. Several recent studies exploit additional semantic information, e.g. tex…

cs.CV2022

Cross-Domain Cross-Set Few-Shot Learning via Learning Compact and Aligned Representations

Wentao Chen, Zhang Zhang, Wei Wang +3

Few-shot learning (FSL) aims to recognize novel queries with only a few support samples through leveraging prior knowledge from a base dataset. In this paper, we consider the domai…

cs.CR2022★ 5 cited

Semi-WTC: A Practical Semi-supervised Framework for Attack Categorization through Weight-Task Consistency

Zihan Li, Wentao Chen, Zhiqing Wei +2

Supervised learning has been widely used for attack categorization, requiring high-quality data and labels. However, the data is often imbalanced and it is difficult to obtain suff…

cs.CV2021

Few-Shot Learning with Part Discovery and Augmentation from Unlabeled Images

Wentao Chen, Chenyang Si, Wei Wang +3

Few-shot learning is a challenging task since only few instances are given for recognizing an unseen class. One way to alleviate this problem is to acquire a strong inductive bias…

cs.CV2021★ 4 cited

Quantization of Deep Neural Networks for Accurate Edge Computing

Wentao Chen, Hailong Qiu, Jian Zhuang +7

Deep neural networks (DNNs) have demonstrated their great potential in recent years, exceeding the per-formance of human experts in a wide range of applications. Due to their large…

cs.CV2019★ 1 cited

Progressive Cluster Purification for Transductive Few-shot Learning

Chenyang Si, Wentao Chen, Wei Wang +2

Few-shot learning aims to learn to generalize a classifier to novel classes with limited labeled data. Transductive inference that utilizes unlabeled test set to deal with low-data…

cs.CV2019★ 97 cited

An Attention Enhanced Graph Convolutional LSTM Network for Skeleton-Based Action Recognition

Chenyang Si, Wentao Chen, Wei Wang +2

Skeleton-based action recognition is an important task that requires the adequate understanding of movement characteristics of a human action from the given skeleton sequence. Rece…