92 citations · 96 across the 3 of their papers we have counts for
4 papers
CBA: Improving Online Continual Learning via Continual Bias Adaptor
Quanziang Wang, Renzhen Wang, Yichen Wu +2
Online continual learning (CL) aims to learn new knowledge and consolidate previously learned knowledge from non-stationary data streams. Due to the time-varying training setting,…
Imbalanced Semi-supervised Learning with Bias Adaptive Classifier
Renzhen Wang, Xixi Jia, Quanziang Wang +2
Pseudo-labeling has proven to be a promising semi-supervised learning (SSL) paradigm. Existing pseudo-labeling methods commonly assume that the class distributions of training data…
Label Hierarchy Transition: Delving into Class Hierarchies to Enhance Deep Classifiers
Renzhen Wang, De cai, Kaiwen Xiao +3
Hierarchical classification aims to sort the object into a hierarchical structure of categories. For example, a bird can be categorized according to a three-level hierarchy of orde…
A Benchmark for Edge-Preserving Image Smoothing
Feida Zhu, Zhetong Liang, Xixi Jia +2
Edge-preserving image smoothing is an important step for many low-level vision problems. Though many algorithms have been proposed, there are several difficulties hindering its fur…