SOTAVerified

Class Incremental Learning

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 151–200 of 634 papers

TitleStatusHype
Constructing Enhanced Mutual Information for Online Class-Incremental Learning—0
CLIP with Generative Latent Replay: a Strong Baseline for Incremental LearningCode0
A Life-long Learning Intrusion Detection System for 6G-Enabled IoV—0
Class-Incremental Learning with CLIP: Adaptive Representation Adjustment and Parameter FusionCode2
PASS++: A Dual Bias Reduction Framework for Non-Exemplar Class-Incremental Learning—0
Continual Learning for Remote Physiological Measurement: Minimize Forgetting and Simplify InferenceCode0
Addressing Imbalance for Class Incremental Learning in Medical Image Classification—0
Mitigating Background Shift in Class-Incremental Semantic SegmentationCode1
CroMo-Mixup: Augmenting Cross-Model Representations for Continual Self-Supervised LearningCode0
Overcoming Catastrophic Forgetting in Federated Class-Incremental Learning via Federated Global Twin Generator—0
iNeMo: Incremental Neural Mesh Models for Robust Class-Incremental LearningCode0
Exemplar-free Continual Representation Learning via Learnable Drift CompensationCode1
TACLE: Task and Class-aware Exemplar-free Semi-supervised Class Incremental LearningCode0
Rethinking Few-shot Class-incremental Learning: Learning from YourselfCode1
OpenCIL: Benchmarking Out-of-Distribution Detection in Class-Incremental LearningCode1
Mamba-FSCIL: Dynamic Adaptation with Selective State Space Model for Few-Shot Class-Incremental LearningCode1
Mind the Interference: Retaining Pre-trained Knowledge in Parameter Efficient Continual Learning of Vision-Language ModelsCode2
UCIL: An Unsupervised Class Incremental Learning Approach for Sound Event Detection—0
TEAL: New Selection Strategy for Small Buffers in Experience Replay Class Incremental LearningCode1
The impact of model size on catastrophic forgetting in Online Continual Learning—0
The Championship-Winning Solution for the 5th CLVISION Challenge 2024—0
CCSI: Continual Class-Specific Impression for Data-free Class Incremental LearningCode0
Data-Free Generative Replay for Class-Incremental Learning on Imbalanced DataCode0
Decision Boundary-aware Knowledge Consolidation Generates Better Instance-Incremental Learner—0
Federated Class-Incremental Learning with Hierarchical Generative Prototypes—0
Harnessing Neural Unit Dynamics for Effective and Scalable Class-Incremental Learning—0
Multi-label Class Incremental Emotion Decoding with Augmented Emotional Semantics Learning—0
Federated Continual Learning Goes Online: Uncertainty-Aware Memory Management for Vision Tasks and Beyond—0
Recent Advances of Foundation Language Models-based Continual Learning: A Survey—0
Compositional Few-Shot Class-Incremental LearningCode0
Few-shot Tuning of Foundation Models for Class-incremental LearningCode0
On Sequential Loss Approximation for Continual LearningCode0
Rethinking Class-Incremental Learning from a Dynamic Imbalanced Learning PerspectiveCode0
Less is more: Summarizing Patch Tokens for efficient Multi-Label Class-Incremental LearningCode1
Data-Free Federated Class Incremental Learning with Diffusion-Based Generative Memory—0
Mitigating Interference in the Knowledge Continuum through Attention-Guided Incremental LearningCode0
FeTT: Continual Class Incremental Learning via Feature Transformation Tuning—0
Bayesian Learning-driven Prototypical Contrastive Loss for Class-Incremental Learning—0
Dynamic Feature Learning and Matching for Class-Incremental Learning—0
Feature Expansion and enhanced Compression for Class Incremental LearningCode0
Few-Shot Class Incremental Learning via Robust Transformer ApproachCode0
Delve into Base-Novel Confusion: Redundancy Exploration for Few-Shot Class-Incremental Learning—0
Continual Learning in the Presence of Repetition—0
FedProK: Trustworthy Federated Class-Incremental Learning via Prototypical Feature Knowledge Transfer—0
Few Shot Class Incremental Learning using Vision-Language models—0
Hard ASH: Sparsity and the right optimizer make a continual learner—0
Revisiting Neural Networks for Continual Learning: An Architectural PerspectiveCode1
Brain-Inspired Continual Learning-Robust Feature Distillation and Re-Consolidation for Class Incremental Learning—0
DynaMMo: Dynamic Model Merging for Efficient Class Incremental Learning for Medical ImagesCode0
Realistic Continual Learning Approach using Pre-trained Models—0
Show:102550
← PrevPage 4 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