4 papers
Prior-Constrained Association Learning for Fine-Grained Generalized Category Discovery
Menglin Wang, Zhun Zhong, Xiaojin Gong
This paper addresses generalized category discovery (GCD), the task of clustering unlabeled data from potentially known or unknown categories with the help of labeled instances fro…
Happy: A Debiased Learning Framework for Continual Generalized Category Discovery
Shijie Ma, Fei Zhu, Zhun Zhong +3
Constantly discovering novel concepts is crucial in evolving environments. This paper explores the underexplored task of Continual Generalized Category Discovery (C-GCD), which aim…
Active Generalized Category Discovery
Shijie Ma, Fei Zhu, Zhun Zhong +2
Generalized Category Discovery (GCD) is a pragmatic and challenging open-world task, which endeavors to cluster unlabeled samples from both novel and old classes, leveraging some l…
Memory Consistency Guided Divide-and-Conquer Learning for Generalized Category Discovery
Yuanpeng Tu, Zhun Zhong, Yuxi Li +1
Generalized category discovery (GCD) aims at addressing a more realistic and challenging setting of semi-supervised learning, where only part of the category labels are assigned to…