20 citations · 20 across the 6 of their papers we have counts for
5 papers
Online Continual Learning via the Meta-learning Update with Multi-scale Knowledge Distillation and Data Augmentation
Ya-nan Han, Jian-wei Liu
Continual learning aims to rapidly and continually learn the current task from a sequence of tasks. Compared to other kinds of methods, the methods based on experience replay have…
-CapsNet: Learning Disentangled Representation for CapsNet by Information Bottleneck
Ming-fei Hu, Jian-wei Liu
We present a framework for learning disentangled representation of CapsNet by information bottleneck constraint that distills information into a compact form and motivates to learn…
Selecting Related Knowledge via Efficient Channel Attention for Online Continual Learning
Ya-nan Han, Jian-wei Liu
Continual learning aims to learn a sequence of tasks by leveraging the knowledge acquired in the past in an online-learning manner while being able to perform well on all previous…
Multi-Scale Iterative Refinement Network for RGB-D Salient Object Detection
Ze-yu Liu, Jian-wei Liu, Xin Zuo +1
The extensive research leveraging RGB-D information has been exploited in salient object detection. However, salient visual cues appear in various scales and resolutions of RGB ima…
Partially latent factors based multi-view subspace learning
Run-kun Lu, Jian-wei Liu, Ze-yu Liu +1
Multi-view subspace clustering always performs well in high-dimensional data analysis, but is sensitive to the quality of data representation. To this end, a two stage fusion strat…