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Class Incremental Learning

Papers

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Showing 551–575 of 634 papers

TitleStatusHype
SCLIFD:Supervised Contrastive Knowledge Distillation for Incremental Fault Diagnosis under Limited Fault Data—0
Sculpting [CLS] Features for Pre-Trained Model-Based Class-Incremental Learning—0
SDDGR: Stable Diffusion-based Deep Generative Replay for Class Incremental Object Detection—0
SEC-Prompt:SEmantic Complementary Prompting for Few-Shot Class-Incremental Learning—0
Self-distilled Knowledge Delegator for Exemplar-free Class Incremental Learning—0
Self-Organizing Pathway Expansion for Non-Exemplar Class-Incremental Learning—0
Self-Paced Imbalance Rectification for Class Incremental Learning—0
Adversary Aware Continual Learning—0
DSS: A Diverse Sample Selection Method to Preserve Knowledge in Class-Incremental Learning—0
Dual-Consistency Model Inversion for Non-Exemplar Class Incremental Learning—0
Dual Embodied-Symbolic Concept Representations for Deep Learning—0
Dual-Enhanced Coreset Selection with Class-wise Collaboration for Online Blurry Class Incremental Learning—0
DualMix: Unleashing the Potential of Data Augmentation for Online Class-Incremental Learning—0
Dual-Teacher Class-Incremental Learning With Data-Free Generative Replay—0
Dynamic Feature Learning and Matching for Class-Incremental Learning—0
Dynamic Integration of Task-Specific Adapters for Class Incremental Learning—0
Dynamic Prompt Adjustment for Multi-Label Class-Incremental Learning—0
Self-Supervised Class Incremental Learning—0
Self-Supervised Learning Aided Class-Incremental Lifelong Learning—0
Adversarial Targeted Forgetting in Regularization and Generative Based Continual Learning Models—0
DS-AL: A Dual-Stream Analytic Learning for Exemplar-Free Class-Incremental Learning—0
eCIL-MU: Embedding based Class Incremental Learning and Machine Unlearning—0
Doodle It Yourself: Class Incremental Learning by Drawing a Few Sketches—0
Effective Decision Boundary Learning for Class Incremental Learning—0
Efficient Expansion and Gradient Based Task Inference for Replay Free Incremental Learning—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