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Class Incremental Learning

Papers

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Showing 151–200 of 634 papers

TitleStatusHype
Learning Invariant Representation for Continual LearningCode1
Learning Prompt with Distribution-Based Feature Replay for Few-Shot Class-Incremental LearningCode1
Few-Shot Class-Incremental Learning by Sampling Multi-Phase TasksCode1
Continual Learning Based on OOD Detection and Task MaskingCode1
Always Be Dreaming: A New Approach for Data-Free Class-Incremental LearningCode1
Continual Learning: Forget-free Winning Subnetworks for Video RepresentationsCode1
Continual Learning for LiDAR Semantic Segmentation: Class-Incremental and Coarse-to-Fine strategies on Sparse DataCode1
Less is more: Summarizing Patch Tokens for efficient Multi-Label Class-Incremental LearningCode1
Margin-Based Few-Shot Class-Incremental Learning with Class-Level Overfitting MitigationCode1
Continual Learning Using a Kernel-Based Method Over Foundation ModelsCode1
Brain-inspired replay for continual learning with artificial neural networksCode1
Memory Replay with Data Compression for Continual LearningCode1
GDumb: A Simple Approach that Questions Our Progress in Continual LearningCode1
Mamba-FSCIL: Dynamic Adaptation with Selective State Space Model for Few-Shot Class-Incremental LearningCode1
Mnemonics Training: Multi-Class Incremental Learning without ForgettingCode1
Self-Sustaining Representation Expansion for Non-Exemplar Class-Incremental LearningCode1
A Multi-Head Model for Continual Learning via Out-of-Distribution ReplayCode1
On Tiny Episodic Memories in Continual LearningCode1
Continual Prototype Evolution: Learning Online from Non-Stationary Data StreamsCode1
Enhancing Efficient Continual Learning with Dynamic Structure Development of Spiking Neural Networks—0
Audio-Visual Class-Incremental Learning for Fish Feeding intensity Assessment in Aquaculture—0
Class Incremental Learning with Pre-trained Vision-Language Models—0
Adversary Aware Continual Learning—0
Enhancing Generative Class Incremental Learning Performance with Model Forgetting Approach—0
Attraction Diminishing and Distributing for Few-Shot Class-Incremental Learning—0
Adversarial Targeted Forgetting in Regularization and Generative Based Continual Learning Models—0
Active Class Incremental Learning for Imbalanced Datasets—0
Enhancing Pre-Trained Model-Based Class-Incremental Learning through Neural Collapse—0
A Survey on Few-Shot Class-Incremental Learning—0
Adversarial Incremental Learning—0
Energy Aligning for Biased Models—0
Enhanced Few-Shot Class-Incremental Learning via Ensemble Models—0
Class-Incremental Learning Using Generative Experience Replay Based on Time-aware Regularization—0
Class-Incremental Learning using Diffusion Model for Distillation and Replay—0
Improving Continual Learning Performance and Efficiency with Auxiliary Classifiers—0
Class-incremental Learning using a Sequence of Partial Implicitly Regularized Classifiers—0
Class-incremental learning: survey and performance evaluation on image classification—0
Balanced Residual Distillation Learning for 3D Point Cloud Class-Incremental Semantic Segmentation—0
Enhancing Consistency and Mitigating Bias: A Data Replay Approach for Incremental Learning—0
Enhancing Visual Continual Learning with Language-Guided Supervision—0
Class-Incremental Learning of Plant and Disease Detection: Growing Branches with Knowledge Distillation—0
SS-IL: Separated Softmax for Incremental Learning—0
Class incremental learning for video action classification—0
Architect, Regularize and Replay (ARR): a Flexible Hybrid Approach for Continual Learning—0
Addressing Imbalance for Class Incremental Learning in Medical Image Classification—0
Class-Incremental Learning for Sound Event Localization and Detection—0
Class-Incremental Learning for Multi-Label Audio Classification—0
Class-Incremental Learning for Honey Botanical Origin Classification with Hyperspectral Images: A Study with Continual Backpropagation—0
A Data-Free Approach to Mitigate Catastrophic Forgetting in Federated Class Incremental Learning for Vision Tasks—0
A Comprehensive Study of Class Incremental Learning Algorithms for Visual Tasks—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