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Class Incremental Learning

Papers

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Showing 401–425 of 634 papers

TitleStatusHype
Density Distribution-based Learning Framework for Addressing Online Continual Learning ChallengesCode0
Towards interpretable-by-design deep learning algorithms—0
Combining Past, Present and Future: A Self-Supervised Approach for Class Incremental Learning—0
A Data-Free Approach to Mitigate Catastrophic Forgetting in Federated Class Incremental Learning for Vision Tasks—0
Robust Feature Learning and Global Variance-Driven Classifier Alignment for Long-Tail Class Incremental LearningCode0
Class Incremental Learning with Pre-trained Vision-Language Models—0
Constructing Sample-to-Class Graph for Few-Shot Class-Incremental LearningCode0
Look At Me, No Replay! SurpriseNet: Anomaly Detection Inspired Class Incremental LearningCode0
Wakening Past Concepts without Past Data: Class-Incremental Learning from Online Placebos—0
Federated Class-Incremental Learning with Prompting—0
Aggregated f-average Neural Network for Interpretable Ensembling—0
OpenIncrement: A Unified Framework for Open Set Recognition and Deep Class-Incremental LearningCode0
Hadamard Domain Training with Integers for Class Incremental Quantized Learning—0
Class-Incremental Learning Using Generative Experience Replay Based on Time-aware Regularization—0
Continual Contrastive Spoken Language Understanding—0
COOLer: Class-Incremental Learning for Appearance-Based Multiple Object TrackingCode0
Elephant Neural Networks: Born to Be a Continual Learner—0
Multivariate Prototype Representation for Domain-Generalized Incremental Learning—0
MultIOD: Rehearsal-free Multihead Incremental Object Detector—0
Prompt Learning With Knowledge Memorizing Prototypes For Generalized Few-Shot Intent Detection—0
Image-Object-Specific Prompt Learning for Few-Shot Class-Incremental Learning—0
Rotation Augmented Distillation for Exemplar-Free Class Incremental Learning with Detailed Analysis—0
GRASP: A Rehearsal Policy for Efficient Online Continual Learning—0
Dynamic Residual Classifier for Class Incremental LearningCode0
Category Adaptation Meets Projected Distillation in Generalized Continual Category DiscoveryCode0
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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