Novel Class Discovery

The goal of Novel Class Discovery (NCD) is to identify new classes in unlabeled data, by exploiting prior knowledge from known classes. In this specific setup, the data is split in two sets. The first is a labeled set containing known classes and the second is an unlabeled set containing unknown classes that must be discovered.

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 26–50 of 65 papers

Title	Date	Tasks	Status	Hype
Novel class discovery meets foundation models for 3D semantic segmentation	Dec 6, 2023	3D Semantic SegmentationNovel Class Discovery	—Unverified	0
Enhancing Novel Object Detection via Cooperative Foundational Models	Nov 19, 2023	Novel Class DiscoveryNovel Object Detection	CodeCode Available	1
A Practical Approach to Novel Class Discovery in Tabular Data	Nov 9, 2023	ClusteringNovel Class Discovery	CodeCode Available	0
Towards Novel Class Discovery: A Study in Novel Skin Lesions Clustering	Sep 28, 2023	ClusteringContrastive Learning	—Unverified	0
Bridging the Gap: Learning Pace Synchronization for Open-World Semi-Supervised Learning	Sep 21, 2023	Novel Class DiscoveryOpen-World Semi-Supervised Learning	CodeCode Available	1
Reinforcement Learning Based Multi-modal Feature Fusion Network for Novel Class Discovery	Aug 26, 2023	Novel Class Discoveryreinforcement-learning	CodeCode Available	0
MetaGCD: Learning to Continually Learn in Generalized Category Discovery	Aug 21, 2023	Incremental LearningMeta-Learning	CodeCode Available	1
When and How Does Known Class Help Discover Unknown Ones? Provable Understanding Through Spectral Analysis	Aug 9, 2023	Novel Class Discovery	CodeCode Available	1
Novel Class Discovery for Long-tailed Recognition	Aug 6, 2023	Novel Class Discovery	CodeCode Available	0
Class-relation Knowledge Distillation for Novel Class Discovery	Jul 18, 2023	Knowledge DistillationNovel Class Discovery	CodeCode Available	1
An Interactive Interface for Novel Class Discovery in Tabular Data	Jun 22, 2023	ClusteringNovel Class Discovery	CodeCode Available	0
Supervised Knowledge May Hurt Novel Class Discovery Performance	Jun 6, 2023	Novel Class DiscoverySemantic Similarity	CodeCode Available	0
Open-world Semi-supervised Novel Class Discovery	May 22, 2023	Contrastive LearningNovel Class Discovery	CodeCode Available	1
Large-scale Pre-trained Models are Surprisingly Strong in Incremental Novel Class Discovery	Mar 28, 2023	Novel Class DiscoveryNovel Concepts	CodeCode Available	1
Novel Class Discovery for 3D Point Cloud Semantic Segmentation	Mar 21, 2023	2D Semantic SegmentationNovel Class Discovery	CodeCode Available	1
Novel Class Discovery: an Introduction and Key Concepts	Feb 22, 2023	Contrastive LearningNovel Class Discovery	CodeCode Available	0
Bootstrap Your Own Prior: Towards Distribution-Agnostic Novel Class Discovery	Jan 1, 2023	Novel Class Discovery	CodeCode Available	1
On-the-Fly Category Discovery	Jan 1, 2023	DisentanglementInductive Learning	CodeCode Available	1
Découvrir de nouvelles classes dans des données tabulaires	Nov 28, 2022	Multi-Task LearningNovel Class Discovery	CodeCode Available	0
Boosting Novel Category Discovery Over Domains with Soft Contrastive Learning and All-in-One Classifier	Nov 21, 2022	AllContrastive Learning	—Unverified	0
Parametric Classification for Generalized Category Discovery: A Baseline Study	Nov 21, 2022	ClassificationNovel Class Discovery	CodeCode Available	1
Learning to Discover and Detect Objects	Oct 19, 2022	Novel Class DiscoveryNovel Object Detection	CodeCode Available	1
Modeling Inter-Class and Intra-Class Constraints in Novel Class Discovery	Oct 7, 2022	Novel Class Discovery	CodeCode Available	1
A Closer Look at Novel Class Discovery from the Labeled Set	Sep 19, 2022	Novel Class DiscoverySemantic Similarity	—Unverified	0
A Method for Discovering Novel Classes in Tabular Data	Sep 2, 2022	Multi-Task LearningNovel Class Discovery	CodeCode Available	0

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All datasets CIFAR10 cifar100 SVHN

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	AutoNovel	Clustering Accuracy	0.92	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	AutoNovel	Clustering Accuracy	0.75	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	AutoNovel	Clustering Accuracy	0.95	—	Unverified