SOTAVerified

Class Incremental Learning

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 451–500 of 634 papers

TitleStatusHype
Bring Evanescent Representations to Life in Lifelong Class Incremental Learning—0
Breaking Fine-Grained Classification Barriers with Cost-Free Data in Few-Shot Class-Incremental Learning—0
Neural Architecture Search for Class-incremental Learning—0
Brain-inspired feature exaggeration in generative replay for continual learning—0
Brain-inspired continual pre-trained learner via silent synaptic consolidation—0
Brain-Inspired Continual Learning-Robust Feature Distillation and Re-Consolidation for Class Incremental Learning—0
Neuro-mimetic Task-free Unsupervised Online Learning with Continual Self-Organizing Maps—0
Brain-inspired analogical mixture prototypes for few-shot class-incremental learning—0
ACIL: Active Class Incremental Learning for Image Classification—0
Bias Mitigating Few-Shot Class-Incremental Learning—0
Noise-Tolerant Coreset-Based Class Incremental Continual Learning—0
Non-exemplar Class-incremental Learning by Random Auxiliary Classes Augmentation and Mixed Features—0
Bayesian Learning-driven Prototypical Contrastive Loss for Class-Incremental Learning—0
Balancing the Past and Present: A Coordinated Replay Framework for Federated Class-Incremental Learning—0
On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning—0
Hyperdimensional Representation Learning for Node Classification and Link Prediction—0
Taxonomic Class Incremental Learning—0
Balancing the Causal Effects in Class-Incremental Learning—0
T-CIL: Temperature Scaling using Adversarial Perturbation for Calibration in Class-Incremental Learning—0
Teach YOLO to Remember: A Self-Distillation Approach for Continual Object Detection—0
Balanced Supervised Contrastive Learning for Few-Shot Class-Incremental Learning—0
Improving Continual Learning Performance and Efficiency with Auxiliary Classifiers—0
On the Discrimination and Consistency for Exemplar-Free Class Incremental Learning—0
Video Domain Incremental Learning for Human Action Recognition in Home Environments—0
Balanced softmax cross-entropy for incremental learning with and without memory—0
On the Stability-Plasticity Dilemma of Class-Incremental Learning—0
Avalanche: A PyTorch Library for Deep Continual Learning—0
Wakening Past Concepts without Past Data: Class-incremental Learning from Placebos—0
Open-World Continual Learning: Unifying Novelty Detection and Continual Learning—0
Open-world Machine Learning: A Review and New Outlooks—0
Automatic Construction of Pattern Classifiers Capable of Continuous Incremental Learning and Unlearning Tasks Based on Compact-Sized Probabilistic Neural Network—0
Autoencoder-Based Hybrid Replay for Class-Incremental Learning—0
Overcoming Catastrophic Forgetting in Federated Class-Incremental Learning via Federated Global Twin Generator—0
Audio-Visual Class-Incremental Learning for Fish Feeding intensity Assessment in Aquaculture—0
Overcoming the Stability Gap in Continual Learning—0
A Bag of Tricks for Few-Shot Class-Incremental Learning—0
PAL: Prompting Analytic Learning with Missing Modality for Multi-Modal Class-Incremental Learning—0
PASS++: A Dual Bias Reduction Framework for Non-Exemplar Class-Incremental Learning—0
PBES: PCA Based Exemplar Sampling Algorithm for Continual Learning—0
The Bayesian Approach to Continual Learning: An Overview—0
pFedMxF: Personalized Federated Class-Incremental Learning with Mixture of Frequency Aggregation—0
Attraction Diminishing and Distributing for Few-Shot Class-Incremental Learning—0
The Championship-Winning Solution for the 5th CLVISION Challenge 2024—0
Plastic Learning with Deep Fourier Features—0
PlaStIL: Plastic and Stable Memory-Free Class-Incremental Learning—0
The impact of model size on catastrophic forgetting in Online Continual Learning—0
A Survey on Few-Shot Class-Incremental Learning—0
PointCLIMB: An Exemplar-Free Point Cloud Class Incremental Benchmark—0
SS-IL: Separated Softmax for Incremental Learning—0
Architect, Regularize and Replay (ARR): a Flexible Hybrid Approach for Continual Learning—0
Show:102550
← PrevPage 10 of 13Next →
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