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Class Incremental Learning

Papers

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Showing 276–300 of 634 papers

TitleStatusHype
DSS: A Diverse Sample Selection Method to Preserve Knowledge in Class-Incremental Learning—0
PBES: PCA Based Exemplar Sampling Algorithm for Continual Learning—0
Class-Wise Buffer Management for Incremental Object Detection: An Effective Buffer Training Strategy—0
Read Between the Layers: Leveraging Multi-Layer Representations for Rehearsal-Free Continual Learning with Pre-Trained ModelsCode0
Learn or Recall? Revisiting Incremental Learning with Pre-trained Language ModelsCode1
Few-Shot Class-Incremental Learning via Training-Free Prototype CalibrationCode1
TLCE: Transfer-Learning Based Classifier Ensembles for Few-Shot Class-Incremental Learning—0
Enhancing Robustness in Incremental Learning with Adversarial TrainingCode0
Pseudo Replay-based Class Continual Learning for Online New Category Anomaly Detection in Advanced Manufacturing—0
MIND: Multi-Task Incremental Network DistillationCode0
Efficient Expansion and Gradient Based Task Inference for Replay Free Incremental Learning—0
Prompt-Based Exemplar Super-Compression and Regeneration for Class-Incremental LearningCode0
Sketch Input Method Editor: A Comprehensive Dataset and Methodology for Systematic Input RecognitionCode0
Evaluating Pretrained models for Deployable Lifelong Learning—0
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
Rethinking Class-incremental Learning in the Era of Large Pre-trained Models via Test-Time AdaptationCode1
Federated Class-Incremental Learning with Prompting—0
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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