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Class Incremental Learning

Papers

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Showing 251–300 of 634 papers

TitleStatusHype
EXACFS -- A CIL Method to mitigate Catastrophic Forgetting—0
Exemplar-Based Contrastive Self-Supervised Learning with Few-Shot Class Incremental Learning—0
A New Benchmark for Few-Shot Class-Incremental Learning: Redefining the Upper Bound—0
Latest Advancements Towards Catastrophic Forgetting under Data Scarcity: A Comprehensive Survey on Few-Shot Class Incremental Learning—0
Dense Network Expansion for Class Incremental Learning—0
Demystifying the Base and Novel Performances for Few-shot Class-incremental Learning—0
Improving Vision Transformers for Incremental Learning—0
Delve into Base-Novel Confusion: Redundancy Exploration for Few-Shot Class-Incremental Learning—0
Defying Imbalanced Forgetting in Class Incremental Learning—0
An Efficient Replay for Class-Incremental Learning with Pre-trained Models—0
Adaptive Weighted Parameter Fusion with CLIP for Class-Incremental Learning—0
Balanced Residual Distillation Learning for 3D Point Cloud Class-Incremental Semantic Segmentation—0
INCPrompt: Task-Aware incremental Prompting for Rehearsal-Free Class-incremental Learning—0
Incremental One-Class Models for Data Classification—0
Integrating Dual Prototypes for Task-Wise Adaption in Pre-Trained Model-Based Class-Incremental Learning—0
Learning Conditional Space-Time Prompt Distributions for Video Class-Incremental Learning—0
Decision Boundary-aware Knowledge Consolidation Generates Better Instance-Incremental Learner—0
ClaRe: Practical Class Incremental Learning By Remembering Previous Class Representations—0
Hyperbolic Uncertainty-Aware Few-Shot Incremental Point Cloud Segmentation—0
CEAT: Continual Expansion and Absorption Transformer for Non-Exemplar Class-Incremental Learning—0
Data-Free Federated Class Incremental Learning with Diffusion-Based Generative Memory—0
A Comparative Study of Calibration Methods for Imbalanced Class Incremental Learning—0
Hyperparameters in Continual Learning: A Reality Check—0
Data-Free Class Incremental Gesture Recognition via Synthetic Feature Sampling—0
Completely Weakly Supervised Class-Incremental Learning for Semantic Segmentation—0
DA-CIL: Towards Domain Adaptive Class-Incremental 3D Object Detection—0
AnchorInv: Few-Shot Class-Incremental Learning of Physiological Signals via Representation Space Guided Inversion—0
Hyperbolic Dual Feature Augmentation for Open-Environment—0
Adaptive Discovering and Merging for Incremental Novel Class Discovery—0
Cross-Class Feature Augmentation for Class Incremental Learning—0
Hebbian Continual Representation Learning—0
Harnessing Neural Unit Dynamics for Effective and Scalable Class-Incremental Learning—0
An Analysis of Initial Training Strategies for Exemplar-Free Class-Incremental Learning—0
HCIL: Hierarchical Class Incremental Learning for Longline Fishing Visual Monitoring—0
Memory Is Not the Bottleneck: Cost-Efficient Continual Learning via Weight Space Consolidation—0
Controllable Relation Disentanglement for Few-Shot Class-Incremental Learning—0
AnalyticKWS: Towards Exemplar-Free Analytic Class Incremental Learning for Small-footprint Keyword Spotting—0
Hard ASH: Sparsity and the right optimizer make a continual learner—0
Hybrid Memory Replay: Blending Real and Distilled Data for Class Incremental Learning—0
Controllable Forgetting Mechanism for Few-Shot Class-Incremental Learning—0
Contrastive Augmented Graph2Graph Memory Interaction for Few Shot Continual Learning—0
CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning—0
CafeBoost: Causal Feature Boost To Eliminate Task-Induced Bias for Class Incremental Learning—0
Bypassing Logits Bias in Online Class-Incremental Learning with a Generative Framework—0
Buffer-free Class-Incremental Learning with Out-of-Distribution Detection—0
Continual learning with task specialist—0
A Multi-label Continual Learning Framework to Scale Deep Learning Approaches for Packaging Equipment Monitoring—0
GRASP: A Rehearsal Policy for Efficient Online Continual Learning—0
Continual Learning with Optimal Transport based Mixture Model—0
Continual Learning with Fully Probabilistic Models—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