W Li, Z Fan, J Huo, Y Gao - … of the IEEE/CVF Conference on …, 2023 - openaccess.thecvf.com
Novel class discovery (NCD) aims at learning a model that transfers the common knowledge from a class-disjoint labelled dataset to another unlabelled dataset and discovers new …
M Yang, L Wang, C Deng… - Proceedings of the IEEE …, 2023 - openaccess.thecvf.com
Abstract Novel Class Discovery (NCD) aims to discover unknown classes without any annotation, by exploiting the transferable knowledge already learned from a base set of …
M Yang, Y Zhu, J Yu, A Wu… - Proceedings of the IEEE …, 2022 - openaccess.thecvf.com
In response to the explosively-increasing requirement of annotated data, Novel Class Discovery (NCD) has emerged as a promising alternative to automatically recognize …
In this paper, we study the problem of Novel Class Discovery (NCD). NCD aims at inferring novel object categories in an unlabeled set by leveraging from prior knowledge of a labeled …
Deep clustering gradually becomes an important branch in unsupervised learning methods. However, current approaches hardly take into consideration the semantic sample …
In this paper, we tackle the problem of discovering new classes in unlabeled visual data given labeled data from disjoint classes. Existing methods typically first pre-train a model …
In this paper, we propose an online clustering method called Contrastive Clustering (CC) which explicitly performs the instance-and cluster-level contrastive learning. To be specific …
Y Sun, Z Shi, Y Liang, Y Li - arXiv preprint arXiv:2308.05017, 2023 - arxiv.org
Novel Class Discovery (NCD) aims at inferring novel classes in an unlabeled set by leveraging prior knowledge from a labeled set with known classes. Despite its importance …
J Yin, H Wu, S Sun - Information Fusion, 2023 - Elsevier
As an indispensable branch of unsupervised learning, deep clustering is rapidly emerging along with the growth of deep neural networks. Recently, contrastive learning paradigm has …