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Class Incremental Learning

Papers

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Showing 401–450 of 634 papers

TitleStatusHype
Density Distribution-based Learning Framework for Addressing Online Continual Learning ChallengesCode0
Towards interpretable-by-design deep learning algorithms—0
Combining Past, Present and Future: A Self-Supervised Approach for Class Incremental Learning—0
A Data-Free Approach to Mitigate Catastrophic Forgetting in Federated Class Incremental Learning for Vision Tasks—0
Robust Feature Learning and Global Variance-Driven Classifier Alignment for Long-Tail Class Incremental LearningCode0
Class Incremental Learning with Pre-trained Vision-Language Models—0
Constructing Sample-to-Class Graph for Few-Shot Class-Incremental LearningCode0
Look At Me, No Replay! SurpriseNet: Anomaly Detection Inspired Class Incremental LearningCode0
Wakening Past Concepts without Past Data: Class-Incremental Learning from Online Placebos—0
Federated Class-Incremental Learning with Prompting—0
Aggregated f-average Neural Network for Interpretable Ensembling—0
OpenIncrement: A Unified Framework for Open Set Recognition and Deep Class-Incremental LearningCode0
Hadamard Domain Training with Integers for Class Incremental Quantized Learning—0
Class-Incremental Learning Using Generative Experience Replay Based on Time-aware Regularization—0
Continual Contrastive Spoken Language Understanding—0
COOLer: Class-Incremental Learning for Appearance-Based Multiple Object TrackingCode0
Elephant Neural Networks: Born to Be a Continual Learner—0
Multivariate Prototype Representation for Domain-Generalized Incremental Learning—0
MultIOD: Rehearsal-free Multihead Incremental Object Detector—0
Prompt Learning With Knowledge Memorizing Prototypes For Generalized Few-Shot Intent Detection—0
Image-Object-Specific Prompt Learning for Few-Shot Class-Incremental Learning—0
Rotation Augmented Distillation for Exemplar-Free Class Incremental Learning with Detailed Analysis—0
GRASP: A Rehearsal Policy for Efficient Online Continual Learning—0
Dynamic Residual Classifier for Class Incremental LearningCode0
Category Adaptation Meets Projected Distillation in Generalized Continual Category DiscoveryCode0
An Analysis of Initial Training Strategies for Exemplar-Free Class-Incremental Learning—0
Few-shot Class-incremental Learning for Classification and Object Detection: A Survey—0
SATHUR: Self Augmenting Task Hallucinal Unified Representation for Generalized Class Incremental Learning—0
Enhancing Efficient Continual Learning with Dynamic Structure Development of Spiking Neural Networks—0
AdaER: An Adaptive Experience Replay Approach for Continual Lifelong Learning—0
Class Incremental Learning with Self-Supervised Pre-Training and Prototype Learning—0
Balanced Destruction-Reconstruction Dynamics for Memory-replay Class Incremental LearningCode0
CBCL-PR: A Cognitively Inspired Model for Class-Incremental Learning in RoboticsCode0
XLDA: Linear Discriminant Analysis for Scaling Continual Learning to Extreme Classification at the Edge—0
Active Class Selection for Few-Shot Class-Incremental LearningCode0
Don't Memorize; Mimic The Past: Federated Class Incremental Learning Without Episodic Memory—0
Class-Incremental Learning using Diffusion Model for Distillation and Replay—0
FedET: A Communication-Efficient Federated Class-Incremental Learning Framework Based on Enhanced Transformer—0
Class-Incremental Learning based on Label GenerationCode0
Complementary Learning Subnetworks for Parameter-Efficient Class-Incremental Learning—0
Knowledge Transfer-Driven Few-Shot Class-Incremental LearningCode0
Multi-View Class Incremental Learning—0
Overcoming the Stability Gap in Continual Learning—0
SHARP: Sparsity and Hidden Activation RePlay for Neuro-Inspired Continual LearningCode0
Just a Glimpse: Rethinking Temporal Information for Video Continual Learning—0
Teamwork Is Not Always Good: An Empirical Study of Classifier Drift in Class-incremental Information ExtractionCode0
Balanced Supervised Contrastive Learning for Few-Shot Class-Incremental Learning—0
Condensed Prototype Replay for Class Incremental Learning—0
Dealing with Cross-Task Class Discrimination in Online Continual LearningCode0
SRIL: Selective Regularization for 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