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Class Incremental Learning

Papers

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Showing 476–500 of 634 papers

TitleStatusHype
SCLIFD:Supervised Contrastive Knowledge Distillation for Incremental Fault Diagnosis under Limited Fault Data—0
Avalanche: A PyTorch Library for Deep Continual Learning—0
Class-Incremental Learning with RepetitionCode0
RMM: Reinforced Memory Management for Class-Incremental LearningCode0
Effective Decision Boundary Learning for Class Incremental Learning—0
Online Class-Incremental Learning For Real-World Food Image ClassificationCode0
Continual HyperTransformer: A Meta-Learner for Continual Few-Shot Learning—0
Architect, Regularize and Replay (ARR): a Flexible Hybrid Approach for Continual Learning—0
Endpoints Weight Fusion for Class Incremental Semantic Segmentation—0
DKT: Diverse Knowledge Transfer Transformer for Class Incremental Learning—0
Towards Realistic Evaluation of Industrial Continual Learning Scenarios with an Emphasis on Energy Consumption and Computational FootprintCode0
Prototype Reminiscence and Augmented Asymmetric Knowledge Aggregation for Non-Exemplar Class-Incremental Learning—0
Space-time Prompting for Video Class-incremental Learning—0
Self-Organizing Pathway Expansion for Non-Exemplar Class-Incremental Learning—0
CafeBoost: Causal Feature Boost To Eliminate Task-Induced Bias for Class Incremental Learning—0
Multi-Centroid Task Descriptor for Dynamic Class Incremental Inference—0
GKEAL: Gaussian Kernel Embedded Analytic Learning for Few-Shot Class Incremental Task—0
Scalable Learning with Incremental Probabilistic PCACode0
Task-Adaptive Saliency Guidance for Exemplar-free Class Incremental LearningCode0
Evidential Deep Learning for Class-Incremental Semantic Segmentation—0
DA-CIL: Towards Domain Adaptive Class-Incremental 3D Object Detection—0
Continual Learning with Optimal Transport based Mixture Model—0
Learning to Learn: How to Continuously Teach Humans and Machines—0
An Investigation of the Combination of Rehearsal and Knowledge Distillation in Continual Learning for Spoken Language UnderstandingCode0
Prototypical quadruplet for few-shot class 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