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Class Incremental Learning

Papers

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Showing 76–100 of 634 papers

TitleStatusHype
Continuous Knowledge-Preserving Decomposition for Few-Shot Continual LearningCode1
MalCL: Leveraging GAN-Based Generative Replay to Combat Catastrophic Forgetting in Malware ClassificationCode1
Knowledge Memorization and Rumination for Pre-trained Model-based Class-Incremental Learning—0
Enhancing Few-Shot Class-Incremental Learning via Training-Free Bi-Level Modality CalibrationCode1
Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning—0
Attraction Diminishing and Distributing for Few-Shot Class-Incremental Learning—0
Activating Sparse Part Concepts for 3D Class Incremental LearningCode0
Revisiting Generative Replay for Class Incremental Object DetectionCode1
Hyperbolic Uncertainty-Aware Few-Shot Incremental Point Cloud Segmentation—0
SEC-Prompt:SEmantic Complementary Prompting for Few-Shot Class-Incremental Learning—0
pFedMxF: Personalized Federated Class-Incremental Learning with Mixture of Frequency Aggregation—0
Learning Conditional Space-Time Prompt Distributions for Video Class-Incremental Learning—0
Automatic Construction of Pattern Classifiers Capable of Continuous Incremental Learning and Unlearning Tasks Based on Compact-Sized Probabilistic Neural Network—0
ACIL: Active Class Incremental Learning for Image Classification—0
Dynamic Prompt Adjustment for Multi-Label Class-Incremental Learning—0
Make Domain Shift a Catastrophic Forgetting Alleviator in Class-Incremental Learning—0
Breaking Fine-Grained Classification Barriers with Cost-Free Data in Few-Shot Class-Incremental Learning—0
Exemplar-condensed Federated Class-incremental Learning—0
Adapter Merging with Centroid Prototype Mapping for Scalable Class-Incremental LearningCode1
Video Domain Incremental Learning for Human Action Recognition in Home Environments—0
Continual Learning Using a Kernel-Based Method Over Foundation ModelsCode1
AnchorInv: Few-Shot Class-Incremental Learning of Physiological Signals via Representation Space Guided Inversion—0
CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning—0
ALADE-SNN: Adaptive Logit Alignment in Dynamically Expandable Spiking Neural Networks for Class Incremental Learning—0
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning—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