31 citations · 69 across the 10 of their papers we have counts for
13 papers
KRNet: Towards Efficient Knowledge Replay
Yingying Zhang, Qiaoyong Zhong, Di Xie +1
The knowledge replay technique has been widely used in many tasks such as continual learning and continuous domain adaptation. The key lies in how to effectively encode the knowled…
Self-distilled Knowledge Delegator for Exemplar-free Class Incremental Learning
Fanfan Ye, Liang Ma, Qiaoyong Zhong +2
Exemplar-free incremental learning is extremely challenging due to inaccessibility of data from old tasks. In this paper, we attempt to exploit the knowledge encoded in a previousl…
Topology-aware Convolutional Neural Network for Efficient Skeleton-based Action Recognition
Kailin Xu, Fanfan Ye, Qiaoyong Zhong +1
In the context of skeleton-based action recognition, graph convolutional networks (GCNs) have been rapidly developed, whereas convolutional neural networks (CNNs) have received les…
Divide-and-Assemble: Learning Block-wise Memory for Unsupervised Anomaly Detection
Jinlei Hou, Yingying Zhang, Qiaoyong Zhong +3
Reconstruction-based methods play an important role in unsupervised anomaly detection in images. Ideally, we expect a perfect reconstruction for normal samples and poor reconstruct…
Modulating Localization and Classification for Harmonized Object Detection
Taiheng Zhang, Qiaoyong Zhong, Shiliang Pu +1
Object detection involves two sub-tasks, i.e. localizing objects in an image and classifying them into various categories. For existing CNN-based detectors, we notice the widesprea…
Dynamic GCN: Context-enriched Topology Learning for Skeleton-based Action Recognition
Fanfan Ye, Shiliang Pu, Qiaoyong Zhong +3
Graph Convolutional Networks (GCNs) have attracted increasing interests for the task of skeleton-based action recognition. The key lies in the design of the graph structure, which…