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Class Incremental Learning

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 351–375 of 634 papers

TitleStatusHype
AdaER: An Adaptive Experience Replay Approach for Continual Lifelong Learning—0
Improving Vision Transformers for Incremental Learning—0
INCPrompt: Task-Aware incremental Prompting for Rehearsal-Free Class-incremental Learning—0
Incremental Concept Learning via Online Generative Memory Recall—0
Incremental few-shot learning via vector quantization in deep embedded space—0
StPR: Spatiotemporal Preservation and Routing for Exemplar-Free Video Class-Incremental Learning—0
Incrementally Zero-Shot Detection by an Extreme Value Analyzer—0
Incremental One-Class Models for Data Classification—0
Incremental Prototype Tuning for Class Incremental Learning—0
Inductive Graph Few-shot Class Incremental Learning—0
Strategic Base Representation Learning via Feature Augmentations for Few-Shot Class Incremental Learning—0
Initial Classifier Weights Replay for Memoryless Class Incremental Learning—0
Concept Representation Learning with Contrastive Self-Supervised Learning—0
Integrating Dual Prototypes for Task-Wise Adaption in Pre-Trained Model-Based Class-Incremental Learning—0
Striking a Balance Between Stability and Plasticity for Class-Incremental Learning—0
Towards Diverse Evaluation of Class Incremental Learning: A Representation Learning Perspective—0
Joint Input and Output Coordination for Class-Incremental Learning—0
Just a Glimpse: Rethinking Temporal Information for Video Continual Learning—0
Knowledge Adaptation Network for Few-Shot Class-Incremental Learning—0
Knowledge Consolidation based Class Incremental Online Learning with Limited Data—0
Knowledge Graph Enhanced Generative Multi-modal Models for Class-Incremental Learning—0
Knowledge Memorization and Rumination for Pre-trained Model-based Class-Incremental Learning—0
Complementary Learning Subnetworks for Parameter-Efficient Class-Incremental Learning—0
Active Class Incremental Learning for Imbalanced Datasets—0
A Comprehensive Study of Class Incremental Learning Algorithms for Visual Tasks—0
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All datasetscifar100CIFAR-100 - 50 classes + 10 steps of 5 classesCIFAR-100 - 50 classes + 5 steps of 10 classesCifar100-B0(10 tasks)-no-exemplarsCifar100-B0(20 tasks)-no-exemplarsCIFAR100-B0(50 tasks)-no-exemplars

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1S&B10-stage average accuracy68.18—Unverified
2SCR10-stage average accuracy65.98—Unverified
3iCaRL10-stage average accuracy63.24—Unverified
4LUCIR10-stage average accuracy56.53—Unverified
5ABD10-stage average accuracy54.44—Unverified
6EWC10-stage average accuracy50.53—Unverified
7EMR10-stage average accuracy48.66—Unverified
8A-GEM10-stage average accuracy45.76—Unverified
#ModelMetricClaimedVerifiedStatus
1PPCA-SWSLFinal Accuracy77.07—Unverified
2PPCA-CLIPFinal Accuracy69.71—Unverified
#ModelMetricClaimedVerifiedStatus
1PPCA-SWSLFinal Accuracy77.07—Unverified
2PPCA-CLIPFinal Accuracy69.71—Unverified
#ModelMetricClaimedVerifiedStatus
1SEEDAverage Incremental Accuracy61.7—Unverified
#ModelMetricClaimedVerifiedStatus
1SEEDAverage Incremental Accuracy56.2—Unverified
#ModelMetricClaimedVerifiedStatus
1SEEDAverage Incremental Accuracy42.6—Unverified