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Class Incremental Learning

Papers

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Showing 351–400 of 634 papers

TitleStatusHype
AdaER: An Adaptive Experience Replay Approach for Continual Lifelong Learning—0
Improving Vision Transformers for Incremental Learning—0
INCPrompt: Task-Aware incremental Prompting for Rehearsal-Free Class-incremental Learning—0
Incremental Concept Learning via Online Generative Memory Recall—0
Incremental few-shot learning via vector quantization in deep embedded space—0
StPR: Spatiotemporal Preservation and Routing for Exemplar-Free Video Class-Incremental Learning—0
Incrementally Zero-Shot Detection by an Extreme Value Analyzer—0
Incremental One-Class Models for Data Classification—0
Incremental Prototype Tuning for Class Incremental Learning—0
Inductive Graph Few-shot Class Incremental Learning—0
Strategic Base Representation Learning via Feature Augmentations for Few-Shot Class Incremental Learning—0
Initial Classifier Weights Replay for Memoryless Class Incremental Learning—0
Concept Representation Learning with Contrastive Self-Supervised Learning—0
Integrating Dual Prototypes for Task-Wise Adaption in Pre-Trained Model-Based Class-Incremental Learning—0
Striking a Balance Between Stability and Plasticity for Class-Incremental Learning—0
Towards Diverse Evaluation of Class Incremental Learning: A Representation Learning Perspective—0
Joint Input and Output Coordination for Class-Incremental Learning—0
Just a Glimpse: Rethinking Temporal Information for Video Continual Learning—0
Knowledge Adaptation Network for Few-Shot Class-Incremental Learning—0
Knowledge Consolidation based Class Incremental Online Learning with Limited Data—0
Knowledge Graph Enhanced Generative Multi-modal Models for Class-Incremental Learning—0
Knowledge Memorization and Rumination for Pre-trained Model-based Class-Incremental Learning—0
Complementary Learning Subnetworks for Parameter-Efficient Class-Incremental Learning—0
Active Class Incremental Learning for Imbalanced Datasets—0
A Comprehensive Study of Class Incremental Learning Algorithms for Visual Tasks—0
Label Mapping Neural Networks with Response Consolidation for Class Incremental Learning—0
Language-Inspired Relation Transfer for Few-shot Class-Incremental Learning—0
A Comparative Study of Calibration Methods for Imbalanced Class Incremental Learning—0
Latent-Insensitive autoencoders for Anomaly Detection—0
Latest Advancements Towards Catastrophic Forgetting under Data Scarcity: A Comprehensive Survey on Few-Shot Class Incremental Learning—0
Combining Past, Present and Future: A Self-Supervised Approach for Class Incremental Learning—0
Learnable Distribution Calibration for Few-Shot Class-Incremental Learning—0
Learnable Expansion-and-Compression Network for Few-shot Class-Incremental Learning—0
Learn by Reasoning: Analogical Weight Generation for Few-Shot Class-Incremental Learning—0
Learning a Condensed Frame for Memory-Efficient Video Class-Incremental Learning—0
UCIL: An Unsupervised Class Incremental Learning Approach for Sound Event Detection—0
Susceptibility of Continual Learning Against Adversarial Attacks—0
Learning Conditional Space-Time Prompt Distributions for Video Class-Incremental Learning—0
Closed-form merging of parameter-efficient modules for Federated Continual Learning—0
Learning "O" Helps for Learning More: Handling the Concealed Entity Problem for Class-incremental NER—0
CLIP with Generative Latent Replay: a Strong Baseline for Incremental Learning—0
Learning to Learn: How to Continuously Teach Humans and Machines—0
Class-Wise Buffer Management for Incremental Object Detection: An Effective Buffer Training Strategy—0
Continual Learning with Evolving Class Ontologies—0
Class-Independent Increment: An Efficient Approach for Multi-label Class-Incremental Learning—0
Class Incremental Online Streaming Learning—0
Class Incremental Learning with Task-Specific Batch Normalization and Out-of-Distribution Detection—0
Learning with Style: Continual Semantic Segmentation Across Tasks and Domains—0
Class Incremental Learning with Self-Supervised Pre-Training and Prototype Learning—0
Class Incremental Learning with Pre-trained Vision-Language 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