- A Comprehensive Survey of Continual Learning: Theory, Method and Application (TPAMI 2024) [paper]
- A Comprehensive Empirical Evaluation on Online Continual Learning (ICCV Workshop 2023) [paper][code]
- A Survey on Few-Shot Class-Incremental Learning (Neural Networks 2024) [paper]
- A wholistic view of continual learning with deep neural networks: Forgotten lessons and the bridge to active and open world learning (Neural Networks 2023) [paper]
- An Introduction to Lifelong Supervised Learning (arXiv 2022) [paper]
- A Survey on Incremental Update for Neural Recommender Systems (arXiv 2023) [paper]
- Deep Class-Incremental Learning: A Survey (arXiv 2023) [paper]
- Continual Learning of Natural Language Processing Tasks: A Survey (arXiv 2022) [paper]
- Continual Learning for Real-World Autonomous Systems: Algorithms, Challenges and Frameworks (arXiv 2022) [paper]
- Recent Advances of Continual Learning in Computer Vision: An Overview (arXiv 2021) [paper]
- Replay in Deep Learning: Current Approaches and Missing Biological Elements (Neural Computation 2021) [paper]
- Online Continual Learning in Image Classification: An Empirical Survey (Neurocomputing 2021) [paper] [code]
- Continual Lifelong Learning in Natural Language Processing: A Survey (COLING 2020) [paper]
- Class-incremental learning: survey and performance evaluation (TPAMI 2022) [paper] [code]
- A Comprehensive Study of Class Incremental Learning Algorithms for Visual Tasks (Neural Networks) [paper] [code]
- A continual learning survey: Defying forgetting in classification tasks (TPAMI 2021) [paper] [arxiv]
- Continual Lifelong Learning with Neural Networks: A Review (Neural Networks) [paper]
- Three scenarios for continual learning (Nature Machine Intelligence 2022) [paper][code]
- SIESTA: Efficient Online Continual Learning with Sleep (TMLR 2023)[paper]
- Sub-network Discovery and Soft-masking for Continual Learning of Mixed Tasks (EMNLP 2023)[paper]
- Incorporating neuro-inspired adaptability for continual learning in artificial intelligence (Nature Machine Intelligence 2023) [paper]
- Loss Decoupling for Task-Agnostic Continual Learning (NeurIPS 2023) [paper]
- Bilevel Coreset Selection in Continual Learning: A New Formulation and Algorithm (NeurIPS 2023)[paper]
- Fairness Continual Learning Approach to Semantic Scene Understanding in Open-World Environments (NeurIPS 2023)[paper]
- An Efficient Dataset Condensation Plugin and Its Application to Continual Learning (NeurIPS 2023)[paper]
- Overcoming Recency Bias of Normalization Statistics in Continual Learning: Balance and Adaptation (NeurIPS 2023)[paper]
- Prediction and Control in Continual Reinforcement Learning (NeurIPS 2023)[paper]
- On the Stability-Plasticity Dilemma in Continual Meta-Learning: Theory and Algorithm (NeurIPS 2023)[paper]
- Saving 100x Storage: Prototype Replay for Reconstructing Training Sample Distribution in Class-Incremental Semantic Segmentation (NeurIPS 2023)[paper]
- A Data-Free Approach to Mitigate Catastrophic Forgetting in Federated Class Incremental Learning for Vision Tasks (NeurIPS 2023)[paper]
- Few-Shot Class-Incremental Learning via Training-Free Prototype Calibration (NeurIPS 2023)[paper]
- A Unified Approach to Domain Incremental Learning with Memory: Theory and Algorithm (NeurIPS 2023)[paper][code]
- Minimax Forward and Backward Learning of Evolving Tasks with Performance Guarantees (NeurIPS 2023)[paper][code]
- Recasting Continual Learning as Sequence Modeling (NeurIPS 2023)[paper]
- Augmented Memory Replay-based Continual Learning Approaches for Network Intrusion Detection (NeurIPS 2023)[paper]
- Does Continual Learning Meet Compositionality? New Benchmarks and An Evaluation Framework (NeurIPS 2023)[paper]
- CL-NeRF: Continual Learning of Neural Radiance Fields for Evolving Scene Representation (NeurIPS 2023)[paper]
- TriRE: A Multi-Mechanism Learning Paradigm for Continual Knowledge Retention and Promotion (NeurIPS 2023)[paper]
- Selective Amnesia: A Continual Learning Approach to Forgetting in Deep Generative Models (NeurIPS 2023)[paper]
- A Definition of Continual Reinforcement Learning (NeurIPS 2023)[paper]
- RanPAC: Random Projections and Pre-trained Models for Continual Learning (NeurIPS 2023)[paper]
- Hierarchical Decomposition of Prompt-Based Continual Learning: Rethinking Obscured Sub-optimality (NeurIPS 2023)[paper]
- FeCAM: Exploiting the Heterogeneity of Class Distributions in Exemplar-Free Continual Learning (NeurIPS 2023)[paper]
- The Ideal Continual Learner: An Agent That Never Forgets (ICML2023) [paper]
- Continual Learners are Incremental Model Generalizers (ICML2023)[paper]
- Learnability and Algorithm for Continual Learning (ICML2023)[paper][code]
- Parameter-Level Soft-Masking for Continual Learning (ICML2023)[paper]
- Continual Learning in Linear Classification on Separable Data (ICML2023)[paper]
- DualHSIC: HSIC-Bottleneck and Alignment for Continual Learning (ICML2023)[paper]
- BiRT: Bio-inspired Replay in Vision Transformers for Continual Learning (ICML2023)[paper]
- DDGR: Continual Learning with Deep Diffusion-based Generative Replay (ICML2023)[paper]
- Neuro-Symbolic Continual Learning: Knowledge, Reasoning Shortcuts and Concept Rehearsal (ICML2023)[paper]
- Theory on Forgetting and Generalization of Continual Learning (ICML2023)[paper]
- Poisoning Generative Replay in Continual Learning to Promote Forgetting (ICML2023)[paper]
- Continual Vision-Language Representation Learning with Off-Diagonal Information (ICML2023)[paper]
- Prototype-Sample Relation Distillation: Towards Replay-Free Continual Learning (ICML2023)[paper]
- Does Continual Learning Equally Forget All Parameters? (ICML2023)[paper]
- Growing a Brain with Sparsity-Inducing Generation for Continual Learning (ICCV 2023)[paper][code]
- Self-regulating Prompts: Foundational Model Adaptation without Forgetting (ICCV 2023)[paper][code]
- Prototype Reminiscence and Augmented Asymmetric Knowledge Aggregation for Non-Exemplar Class-Incremental Learning (ICCV 2023)[paper][code]
- Tangent Model Composition for Ensembling and Continual Fine-tuning (ICCV 2023)[paper][code]
- CBA: Improving Online Continual Learning via Continual Bias Adaptor (ICCV 2023)[paper]
- NAPA-VQ: Neighborhood Aware Prototype Augmentation with Vector Quantization for Continual Learning (ICCV 2023)[paper][code]
- Online Continual Learning on Hierarchical Label Expansion (ICCV 2023)[paper]
- Class-Incremental Grouping Network for Continual Audio-Visual Learning (ICCV 2023)[paper][code]
- Rapid Adaptation in Online Continual Learning: Are We Evaluating It Right? (ICCV 2023)[paper][code]
- When Prompt-based Incremental Learning Does Not Meet Strong Pretraining (ICCV 2023)[paper]
- Online Class Incremental Learning on Stochastic Blurry Task Boundary via Mask and Visual Prompt Tuning (ICCV 2023)[paper][code]
- Dynamic Residual Classifier for Class Incremental Learning (ICCV 2023)[paper]
- First Session Adaptation: A Strong Replay-Free Baseline for Class-Incremental Learning (ICCV 2023)[paper]
- Masked Autoencoders are Efficient Class Incremental Learners (ICCV 2023)[paper]
- Introducing Language Guidance in Prompt-based Continual Learning (ICCV 2023)[paper]
- CLNeRF: Continual Learning Meets NeRFs (ICCV 2023)[paper]
- Preventing Zero-Shot Transfer Degradation in Continual Learning of Vision-Language Models (ICCV 2023)[paper][code]
- LFS-GAN: Lifelong Few-Shot Image Generation (ICCV 2023)[paper]
- TARGET: Federated Class-Continual Learning via Exemplar-Free Distillation (ICCV 2023)[paper]
- Learning to Learn: How to Continuously Teach Humans and Machines (ICCV 2023)[paper]
- Audio-Visual Class-Incremental Learning (ICCV 2023)[paper][code]
- MetaGCD: Learning to Continually Learn in Generalized Category Discovery (ICCV 2023)[paper]
- Exemplar-Free Continual Transformer with Convolutions (ICCV 2023)[paper][code]
- A Unified Continual Learning Framework with General Parameter-Efficient Tuning (ICCV 2023)[paper]
- Incremental Generalized Category Discovery (ICCV 2023)[paper]
- Heterogeneous Forgetting Compensation for Class-Incremental Learning (ICCV 2023)[paper][code]
- Augmented Box Replay: Overcoming Foreground Shift for Incremental Object Detection (ICCV 2023)[paper][code]
- MRN: Multiplexed Routing Network for Incremental Multilingual Text Recognition (ICCV 2023)[paper][code]
- CLR: Channel-wise Lightweight Reprogramming for Continual Learning (ICCV 2023)[paper][code]
- ICICLE: Interpretable Class Incremental Continual Learning (ICCV 2023)[paper]
- Proxy Anchor-based Unsupervised Learning for Continuous Generalized Category Discovery (ICCV 2023)[paper]
- SLCA: Slow Learner with Classifier Alignment for Continual Learning on a Pre-trained Model (ICCV 2023)[paper][code]
- Online Prototype Learning for Online Continual Learning (ICCV 2023)[paper][code]
- Analyzing and Reducing the Performance Gap in Cross-Lingual Transfer with Fine-tuning Slow and Fast (ACL2023)[paper]
- Class-Incremental Learning based on Label Generation (ACL2023)[paper]
- Computationally Budgeted Continual Learning: What Does Matter? (CVPR2023)[paper][code]
- Real-Time Evaluation in Online Continual Learning: A New Hope (CVPR2023)[paper]
- Dealing With Cross-Task Class Discrimination in Online Continual Learning (CVPR2023)[paper][code]
- Decoupling Learning and Remembering: A Bilevel Memory Framework With Knowledge Projection for Task-Incremental Learning (CVPR2023)[paper][code]
- GKEAL: Gaussian Kernel Embedded Analytic Learning for Few-shot Class Incremental Task (CVPR2023)[paper]
- EcoTTA: Memory-Efficient Continual Test-time Adaptation via Self-distilled Regularization (CVPR2023)[paper]
- Endpoints Weight Fusion for Class Incremental Semantic Segmentation (CVPR2023)[paper]
- On the Stability-Plasticity Dilemma of Class-Incremental Learning (CVPR2023)[paper]
- Regularizing Second-Order Influences for Continual Learning (CVPR2023)[paper][code]
- Rebalancing Batch Normalization for Exemplar-based Class-Incremental Learning (CVPR2023)[paper]
- Task Difficulty Aware Parameter Allocation & Regularization for Lifelong Learning (CVPR2023)[paper]
- A Probabilistic Framework for Lifelong Test-Time Adaptation (CVPR2023)[paper][code]
- Continual Semantic Segmentation with Automatic Memory Sample Selection (CVPR2023)[paper]
- Exploring Data Geometry for Continual Learning (CVPR2023)[paper]
- PCR: Proxy-based Contrastive Replay for Online Class-Incremental Continual Learning (CVPR2023)[paper][code]
- Learning with Fantasy: Semantic-Aware Virtual Contrastive Constraint for Few-Shot Class-Incremental Learning (CVPR2023)[paper][code]
- Foundation Model Drives Weakly Incremental Learning for Semantic Segmentation (CVPR2023)[paper]
- Continual Detection Transformer for Incremental Object Detection (CVPR2023)[paper][code]
- PIVOT: Prompting for Video Continual Learning (CVPR2023)[paper]
- CODA-Prompt: COntinual Decomposed Attention-based Prompting for Rehearsal-Free Continual Learning (CVPR2023)[paper][code]
- Principles of Forgetting in Domain-Incremental Semantic Segmentation in Adverse Weather Conditions (CVPR2023)[paper]
- Class-Incremental Exemplar Compression for Class-Incremental Learning (CVPR2023)[paper][code]
- Dense Network Expansion for Class Incremental Learning (CVPR2023)[paper]
- Online Bias Correction for Task-Free Continual Learning (ICLR2023)[paper]
- Sparse Distributed Memory is a Continual Learner (ICLR2023)[paper]
- Continual Learning of Language Models (ICLR2023)[paper]
- Progressive Prompts: Continual Learning for Language Models without Forgetting (ICLR2023)[paper]
- Is Forgetting Less a Good Inductive Bias for Forward Transfer? (ICLR2023)[paper]
- Online Boundary-Free Continual Learning by Scheduled Data Prior (ICLR2023)[paper]
- Incremental Learning of Structured Memory via Closed-Loop Transcription (ICLR2023)[paper]
- Better Generative Replay for Continual Federated Learning (ICLR2023)[paper]
- 3EF: Class-Incremental Learning via Efficient Energy-Based Expansion and Fusion (ICLR2023)[paper]
- Progressive Voronoi Diagram Subdivision Enables Accurate Data-free Class-Incremental Learning (ICLR2023)[paper]
- Learning without Prejudices: Continual Unbiased Learning via Benign and Malignant Forgetting (ICLR2023)[paper]
- Building a Subspace of Policies for Scalable Continual Learning (ICLR2023)[paper]
- A Model or 603 Exemplars: Towards Memory-Efficient Class-Incremental Learning (ICLR2023)[paper]
- Continual evaluation for lifelong learning: Identifying the stability gap (ICLR2023)[paper]
- Continual Unsupervised Disentangling of Self-Organizing Representations (ICLR2023)[paper]
- Warping the Space: Weight Space Rotation for Class-Incremental Few-Shot Learning (ICLR2023)[paper]
- Neural Collapse Inspired Feature-Classifier Alignment for Few-Shot Class-Incremental Learning (ICLR2023)[paper]
- On the Soft-Subnetwork for Few-Shot Class Incremental Learning (ICLR2023)[paper]
- Task-Aware Information Routing from Common Representation Space in Lifelong Learning (ICLR2023)[paper]
- Error Sensitivity Modulation based Experience Replay: Mitigating Abrupt Representation Drift in Continual Learning (ICLR2023)[paper]
- Neural Weight Search for Scalable Task Incremental Learning (WACV2023)[paper]
- Attribution-aware Weight Transfer: A Warm-Start Initialization for Class-Incremental Semantic Segmentation (WACV2023)[paper]
- FeTrIL: Feature Translation for Exemplar-Free Class-Incremental Learning (WACV2023)[paper]
- Do Pre-trained Models Benefit Equally in Continual Learning? (WACV2023)[paper] [code]
- Sparse Coding in a Dual Memory System for Lifelong Learning (AAAI2023)[paper] [code]
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Online Continual Learning through Mutual Information Maximization (ICML2022)[paper]
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Prototype-guided continual adaptation for class-incremental unsupervised domain adaptation (ECCV2022)[paper] [code]
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Balanced softmax cross-entropy for incremental learning with and without memory (CVIU)[paper]
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Incremental Prompting: Episodic Memory Prompt for Lifelong Event Detection (COLING2022) [paper] [code]
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Improving Task-free Continual Learning by Distributionally Robust Memory Evolution (ICML2022)[paper]
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Forget-free Continual Learning with Winning Subnetworks (ICML2022)[paper]
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NISPA: Neuro-Inspired Stability-Plasticity Adaptation for Continual Learning in Sparse Networks (ICML2022)[paper]
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Continual Learning via Sequential Function-Space Variational Inference (ICML2022)[paper]
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A Theoretical Study on Solving Continual Learning (NeurIPS2022) [paper] [code]
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ACIL: Analytic Class-Incremental Learning with Absolute Memorization and Privacy Protection (NeurIPS2022) [paper]
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Beyond Not-Forgetting: Continual Learning with Backward Knowledge Transfer (NeurIPS2022) [paper]
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Memory Efficient Continual Learning with Transformers (NeurIPS2022) [paper]
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(Transformer)视觉transformer里面加适配器+知识蒸馏，里面任务间相似性度量可参考
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Margin-Based Few-Shot Class-Incremental Learning with Class-Level Overfitting Mitigation (NeurIPS2022) [paper] [code]
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Disentangling Transfer in Continual Reinforcement Learning (NeurIPS2022) [paper]
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Task-Free Continual Learning via Online Discrepancy Distance Learning (NeurIPS2022) [paper]
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A simple but strong baseline for online continual learning: Repeated Augmented Rehearsal (NeurIPS2022) [paper]
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S-Prompts Learning with Pre-trained Transformers: An Occam’s Razor for Domain Incremental Learning (NeurIPS2022) [paper]
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Lifelong Neural Predictive Coding: Learning Cumulatively Online without Forgetting (NeurIPS2022) [paper]
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Few-Shot Continual Active Learning by a Robot (NeurIPS2022) [paper]
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Continual learning: a feature extraction formalization, an efficient algorithm, and fundamental obstructions(NeurIPS2022) [paper]
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SparCL: Sparse Continual Learning on the Edge(NeurIPS2022) [paper]
-
CLiMB: A Continual Learning Benchmark for Vision-and-Language Tasks (NeurIPS2022) [paper] [code]
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Continual Learning In Environments With Polynomial Mixing Times (NeurIPS2022) [paper] [code]
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Exploring Example Influence in Continual Learning (NeurIPS2022) [paper] [code]
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ALIFE: Adaptive Logit Regularizer and Feature Replay for Incremental Semantic Segmentation (NeurIPS2022) [paper]
-
On the Effectiveness of Lipschitz-Driven Rehearsal in Continual Learning (NeurIPS2022) [paper] [code]
-
On Reinforcement Learning and Distribution Matching for Fine-Tuning Language Models with no Catastrophic Forgetting (NeurIPS2022)[paper]
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CGLB: Benchmark Tasks for Continual Graph Learning (NeurIPS2022)[paper] [code]
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How Well Do Unsupervised Learning Algorithms Model Human Real-time and Life-long Learning? (NeurIPS2022)[paper]
-
CoSCL: Cooperation of Small Continual Learners is Stronger than a Big One (ECCV2022)[paper] [code]
-
Generative Negative Text Replay for Continual Vision-Language Pretraining (ECCV2022) [paper]
-
DualPrompt: Complementary Prompting for Rehearsal-free Continual Learning (ECCV2022) [paper] [code]
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The Challenges of Continuous Self-Supervised Learning (ECCV2022)[paper]
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Helpful or Harmful: Inter-Task Association in Continual Learning (ECCV2022)[paper]
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incDFM: Incremental Deep Feature Modeling for Continual Novelty Detection (ECCV2022)[paper]
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S3C: Self-Supervised Stochastic Classifiers for Few-Shot Class-Incremental Learning (ECCV2022)[paper]
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Online Task-free Continual Learning with Dynamic Sparse Distributed Memory (ECCV2022)[paper][code]
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Balancing between Forgetting and Acquisition in Incremental Subpopulation Learning (ECCV2022)[paper]
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Class-Incremental Learning with Cross-Space Clustering and Controlled Transfer (ECCV2022) [paper] [code]
-
FOSTER: Feature Boosting and Compression for Class-Incremental Learning (ECCV2022) [paper] [code]
-
Meta-Learning with Less Forgetting on Large-Scale Non-Stationary Task Distributions (ECCV2022) [paper]
-
R-DFCIL: Relation-Guided Representation Learning for Data-Free Class Incremental Learning (ECCV2022) [paper] [code]
-
DLCFT: Deep Linear Continual Fine-Tuning for General Incremental Learning (ECCV2022) [paper]
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Learning with Recoverable Forgetting (ECCV2022) [paper]
-
Prototype-Guided Continual Adaptation for Class-Incremental Unsupervised Domain Adaptation (ECCV2022) [paper] [code]
-
Balancing Stability and Plasticity through Advanced Null Space in Continual Learning (ECCV2022) [paper]
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Long-Tailed Class Incremental Learning (ECCV2022) [paper]
-
Anti-Retroactive Interference for Lifelong Learning (ECCV2022) [paper]
-
Novel Class Discovery without Forgetting (ECCV2022) [paper]
-
Class-incremental Novel Class Discovery (ECCV2022) [paper]
-
Few-Shot Class Incremental Learning From an Open-Set Perspective(ECCV2022)[paper]
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Incremental Task Learning with Incremental Rank Updates(ECCV2022)[paper]
-
Few-Shot Class-Incremental Learning via Entropy-Regularized Data-Free Replay(ECCV2022)[paper]
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Online Continual Learning with Contrastive Vision Transformer (ECCV2022)[paper]
-
Continual Training of Language Models for Few-Shot Learning (EMNLP2022) [paper] [code]
-
Uncertainty-aware Contrastive Distillation for Incremental Semantic Segmentation (TPAMI2022) [paper]
-
MgSvF: Multi-Grained Slow vs. Fast Framework for Few-Shot Class-Incremental Learning (TPAMI2022) [paper]
-
Class-Incremental Continual Learning into the eXtended DER-verse (TPAMI2022) [paper] [code]
-
Few-Shot Class-Incremental Learning by Sampling Multi-Phase Tasks (TPAMI2022) [paper] [code]
-
Continual Semi-Supervised Learning through Contrastive Interpolation Consistency (PRL2022) [paper][code]
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GCR: Gradient Coreset Based Replay Buffer Selection for Continual Learning (CVPR2022) [paper]
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Learning Bayesian Sparse Networks With Full Experience Replay for Continual Learning (CVPR2022) [paper]
-
Continual Learning With Lifelong Vision Transformer (CVPR2022) [paper]
-
Towards Better Plasticity-Stability Trade-Off in Incremental Learning: A Simple Linear Connector (CVPR2022) [paper]
-
Doodle It Yourself: Class Incremental Learning by Drawing a Few Sketches (CVPR2022) [paper]
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Continual Learning for Visual Search with Backward Consistent Feature Embedding (CVPR2022) [paper]
-
Online Continual Learning on a Contaminated Data Stream with Blurry Task Boundaries (CVPR2022) [paper]
-
Not Just Selection, but Exploration: Online Class-Incremental Continual Learning via Dual View Consistency (CVPR2022) [paper]
-
Bring Evanescent Representations to Life in Lifelong Class Incremental Learning (CVPR2022) [paper]
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Lifelong Graph Learning (CVPR2022) [paper]
-
Lifelong Unsupervised Domain Adaptive Person Re-identification with Coordinated Anti-forgetting and Adaptation (CVPR2022) [paper]
-
vCLIMB: A Novel Video Class Incremental Learning Benchmark (CVPR2022) [paper]
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Class-Incremental Learning by Knowledge Distillation with Adaptive Feature Consolidation(CVPR2022) [paper]
-
Few-Shot Incremental Learning for Label-to-Image Translation (CVPR2022) [paper]
-
MetaFSCIL: A Meta-Learning Approach for Few-Shot Class Incremental Learning (CVPR2022) [paper]
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Incremental Learning in Semantic Segmentation from Image Labels (CVPR2022) [paper]
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Self-Supervised Models are Continual Learners (CVPR2022) [paper] [code]
-
Learning to Imagine: Diversify Memory for Incremental Learning using Unlabeled Data (CVPR2022) [paper]
-
General Incremental Learning with Domain-aware Categorical Representations (CVPR2022) [paper]
-
Constrained Few-shot Class-incremental Learning (CVPR2022) [paper]
-
Overcoming Catastrophic Forgetting in Incremental Object Detection via Elastic Response Distillation (CVPR2022) [paper]
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Class-Incremental Learning with Strong Pre-trained Models (CVPR2022) [paper]
-
Energy-based Latent Aligner for Incremental Learning (CVPR2022) [paper] [code]
-
Meta-attention for ViT-backed Continual Learning (CVPR2022) [paper] [code]
-
Learning to Prompt for Continual Learning (CVPR2022) [paper] [code]
-
On Generalizing Beyond Domains in Cross-Domain Continual Learning (CVPR2022) [paper]
-
Probing Representation Forgetting in Supervised and Unsupervised Continual Learning (CVPR2022) [paper]
-
Incremental Transformer Structure Enhanced Image Inpainting with Masking Positional Encoding (CVPR2022) [paper] [code]
-
Mimicking the Oracle: An Initial Phase Decorrelation Approach for Class Incremental Learning (CVPR2022) [paper] [code]
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Forward Compatible Few-Shot Class-Incremental Learning (CVPR2022) [paper] [code]
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Self-Sustaining Representation Expansion for Non-Exemplar Class-Incremental Learning (CVPR2022) [paper]
-
DyTox: Transformers for Continual Learning with DYnamic TOken eXpansion (CVPR2022) [paper]
-
(Transformer)利用transformer获取关系的能力获取任务ID和图片的关系
-
Federated Class-Incremental Learning (CVPR2022) [paper] [code]
-
Representation Compensation Networks for Continual Semantic Segmentation (CVPR2022) [paper]
-
A Multi-Head Model for Continual Learning via Out-of-Distribution Replay (CoLLAs2022) [paper] [code]
-
Continual Attentive Fusion for Incremental Learning in Semantic Segmentation (TMM2022) [paper]
-
Self-training for class-incremental semantic segmentation (TNNLS2022) [paper]
-
Effects of Auxiliary Knowledge on Continual Learning (ICPR2022) [paper]
-
Continual Sequence Generation with Adaptive Compositional Modules (ACL2022) [paper]
-
Learngene: From Open-World to Your Learning Task (AAAI2022) [paper] [code]
-
Rethinking the Representational Continuity: Towards Unsupervised Continual Learning (ICLR2022) [paper]
-
Continual Learning with Filter Atom Swapping (ICLR2022) [paper]
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Continual Learning with Recursive Gradient Optimization (ICLR2022) [paper]
-
TRGP: Trust Region Gradient Projection for Continual Learning (ICLR2022) [paper]
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Looking Back on Learned Experiences For Class/task Incremental Learning (ICLR2022) [paper]
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Continual Normalization: Rethinking Batch Normalization for Online Continual Learning (ICLR2022) [paper]
-
Model Zoo: A Growing Brain That Learns Continually (ICLR2022) [paper]
-
Learning curves for continual learning in neural networks: Self-knowledge transfer and forgetting (ICLR2022) [paper]
-
Memory Replay with Data Compression for Continual Learning (ICLR2022) [paper]
-
Learning Fast, Learning Slow: A General Continual Learning Method based on Complementary Learning System (ICLR2022) [paper]
-
Online Coreset Selection for Rehearsal-based Continual Learning (ICLR2022) [paper]
-
Pretrained Language Model in Continual Learning: A Comparative Study (ICLR2022) [paper]
-
Online Continual Learning on Class Incremental Blurry Task Configuration with Anytime Inference (ICLR2022) [paper]
-
New Insights on Reducing Abrupt Representation Change in Online Continual Learning (ICLR2022) [paper]
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Towards Continual Knowledge Learning of Language Models (ICLR2022) [paper]
-
CLEVA-Compass: A Continual Learning Evaluation Assessment Compass to Promote Research Transparency and Comparability (ICLR2022) [paper]
-
CoMPS: Continual Meta Policy Search (ICLR2022) [paper]
-
Information-theoretic Online Memory Selection for Continual Learning (ICLR2022) [paper]
-
Subspace Regularizers for Few-Shot Class Incremental Learning (ICLR2022) [paper]
-
LFPT5: A Unified Framework for Lifelong Few-shot Language Learning Based on Prompt Tuning of T5 (ICLR2022) [paper]
-
Effect of scale on catastrophic forgetting in neural networks (ICLR2022) [paper]
-
Dataset Knowledge Transfer for Class-Incremental Learning without Memory (WACV2022) [paper]
-
Knowledge Capture and Replay for Continual Learning (WACV2022) [paper]
-
Online Continual Learning via Candidates Voting (WACV2022) [paper]
-
lpSpikeCon: Enabling Low-Precision Spiking Neural Network Processing for Efficient Unsupervised Continual Learning on Autonomous Agents (IJCNN2022) [paper]
-
Unified Probabilistic Deep Continual Learning through Generative Replay and Open Set Recognition (Journal of Imaging 2022) [paper]
- Incremental Object Detection via Meta-Learning (TPAMI 2021) [paper] [code]
- Triple-Memory Networks: A Brain-Inspired Method for Continual Learning (TNNLS 2021) [paper]
- Memory efficient class-incremental learning for image classification (TNNLS 2021) [paper]
- A Procedural World Generation Framework for Systematic Evaluation of Continual Learning (NeurIPS2021) [paper]
- Class-Incremental Learning via Dual Augmentation (NeurIPS2021) [paper]
- SSUL: Semantic Segmentation with Unknown Label for Exemplar-based Class-Incremental Learning (NeurIPS2021) [paper]
- RMM: Reinforced Memory Management for Class-Incremental Learning (NeurIPS2021) [paper]
- Overcoming Catastrophic Forgetting in Incremental Few-Shot Learning by Finding Flat Minima (NeurIPS2021) [paper]
- Lifelong Domain Adaptation via Consolidated Internal Distribution (NeurIPS2021) [paper]
- AFEC: Active Forgetting of Negative Transfer in Continual Learning (NeurIPS2021) [paper]
- Natural continual learning: success is a journey, not (just) a destination (NeurIPS2021) [paper]
- Gradient-based Editing of Memory Examples for Online Task-free Continual Learning (NeurIPS2021) [paper]
- Optimizing Reusable Knowledge for Continual Learning via Metalearning (NeurIPS2021) [paper]
- Formalizing the Generalization-Forgetting Trade-off in Continual Learning (NeurIPS2021) [paper]
- Learning where to learn: Gradient sparsity in meta and continual learning (NeurIPS2021) [paper]
- Flattening Sharpness for Dynamic Gradient Projection Memory Benefits Continual Learning (NeurIPS2021) [paper]
- Posterior Meta-Replay for Continual Learning (NeurIPS2021) [paper]
- Continual Auxiliary Task Learning (NeurIPS2021) [paper]
- Mitigating Forgetting in Online Continual Learning with Neuron Calibration (NeurIPS2021) [paper]
- BNS: Building Network Structures Dynamically for Continual Learning (NeurIPS2021) [paper]
- DualNet: Continual Learning, Fast and Slow (NeurIPS2021) [paper]
- BooVAE: Boosting Approach for Continual Learning of VAE (NeurIPS2021) [paper]
- Generative vs. Discriminative: Rethinking The Meta-Continual Learning (NeurIPS2021) [paper]
- Achieving Forgetting Prevention and Knowledge Transfer in Continual Learning (NeurIPS2021) [paper]
- Bridging Non Co-occurrence with Unlabeled In-the-wild Data for Incremental Object Detection (NeurIPS, 2021) [paper] [code]
- SS-IL: Separated Softmax for Incremental Learning (ICCV, 2021) [paper]
- Striking a Balance between Stability and Plasticity for Class-Incremental Learning (ICCV, 2021) [paper]
- Synthesized Feature based Few-Shot Class-Incremental Learning on a Mixture of Subspaces (ICCV, 2021) [paper]
- Class-Incremental Learning for Action Recognition in Videos (ICCV, 2021) [paper]
- Continual Prototype Evolution:Learning Online from Non-Stationary Data Streams (ICCV, 2021) [paper]
- Rehearsal Revealed: The Limits and Merits of Revisiting Samples in Continual Learning (ICCV, 2021) [paper]
- Co2L: Contrastive Continual Learning (ICCV, 2021) [paper]
- Wanderlust: Online Continual Object Detection in the Real World (ICCV, 2021) [paper]
- Continual Learning on Noisy Data Streams via Self-Purified Replay (ICCV, 2021) [paper]
- Else-Net: Elastic Semantic Network for Continual Action Recognition from Skeleton Data (ICCV, 2021) [paper]
- Detection and Continual Learning of Novel Face Presentation Attacks (ICCV, 2021) [paper]
- Online Continual Learning with Natural Distribution Shifts: An Empirical Study with Visual Data (ICCV, 2021) [paper]
- Continual Learning for Image-Based Camera Localization (ICCV, 2021) [paper]
- Generalized and Incremental Few-Shot Learning by Explicit Learning and Calibration without Forgetting (ICCV, 2021) [paper]
- Always Be Dreaming: A New Approach for Data-Free Class-Incremental Learning (ICCV, 2021) [paper]
- RECALL: Replay-based Continual Learning in Semantic Segmentation (ICCV, 2021) [paper]
- Few-Shot and Continual Learning with Attentive Independent Mechanisms (ICCV, 2021) [paper]
- Learning with Selective Forgetting (IJCAI, 2021) [paper]
- Continuous Coordination As a Realistic Scenario for Lifelong Learning (ICML, 2021) [paper]
- Kernel Continual Learning (ICML, 2021) [paper]
- Variational Auto-Regressive Gaussian Processes for Continual Learning (ICML, 2021) [paper]
- Bayesian Structural Adaptation for Continual Learning (ICML, 2021) [paper]
- Continual Learning in the Teacher-Student Setup: Impact of Task Similarity (ICML, 2021) [paper]
- Continuous Coordination As a Realistic Scenario for Lifelong Learning (ICML, 2021) [paper]
- Federated Continual Learning with Weighted Inter-client Transfer (ICML, 2021) [paper]
- Adapting BERT for Continual Learning of a Sequence of Aspect Sentiment Classification Tasks (NAACL, 2021) [paper]
- Continual Learning for Text Classification with Information Disentanglement Based Regularization (NAACL, 2021) [paper]
- CLASSIC: Continual and Contrastive Learning of Aspect Sentiment Classification Tasks (EMNLP, 2021) [paper][code]
- Co-Transport for Class-Incremental Learning (ACM MM, 2021) [paper]
- Towards Open World Object Detection (CVPR, 2021) [paper] [code] [video]
- Prototype Augmentation and Self-Supervision for Incremental Learning (CVPR, 2021) [paper] [code]
- ORDisCo: Effective and Efficient Usage of Incremental Unlabeled Data for Semi-supervised Continual Learning (CVPR, 2021) [paper]
- Incremental Learning via Rate Reduction (CVPR, 2021) [paper]
- IIRC: Incremental Implicitly-Refined Classification (CVPR, 2021) [paper]
- Continual Adaptation of Visual Representations via Domain Randomization and Meta-learning (CVPR, 2021) [paper]
- Image De-raining via Continual Learning (CVPR, 2021) [paper]
- Continual Learning via Bit-Level Information Preserving (CVPR, 2021) [paper]
- Hyper-LifelongGAN: Scalable Lifelong Learning for Image Conditioned Generation (CVPR, 2021) [paper]
- Lifelong Person Re-Identification via Adaptive Knowledge Accumulation (CVPR, 2021) [paper]
- Distilling Causal Effect of Data in Class-Incremental Learning (CVPR, 2021) [paper]
- Self-Promoted Prototype Refinement for Few-Shot Class-Incremental Learning (CVPR, 2021) [paper]
- Layerwise Optimization by Gradient Decomposition for Continual Learning (CVPR, 2021) [paper]
- Adaptive Aggregation Networks for Class-Incremental Learning (CVPR, 2021) [paper]
- Incremental Few-Shot Instance Segmentation (CVPR, 2021) [paper]
- Efficient Feature Transformations for Discriminative and Generative Continual Learning (CVPR, 2021) [paper]
- On Learning the Geodesic Path for Incremental Learning (CVPR, 2021) [paper]
- Few-Shot Incremental Learning with Continually Evolved Classifiers (CVPR, 2021) [paper]
- Rectification-based Knowledge Retention for Continual Learning (CVPR, 2021) [paper]
- DER: Dynamically Expandable Representation for Class Incremental Learning (CVPR, 2021) [paper]
- Rainbow Memory: Continual Learning with a Memory of Diverse Samples (CVPR, 2021) [paper]
- Training Networks in Null Space of Feature Covariance for Continual Learning (CVPR, 2021) [paper]
- Semantic-aware Knowledge Distillation for Few-Shot Class-Incremental Learning (CVPR, 2021) [paper]
- PLOP: Learning without Forgetting for Continual Semantic Segmentation (CVPR, 2021) [paper]
- Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations (CVPR, 2021) [paper]
- Online Class-Incremental Continual Learning with Adversarial Shapley Value(AAAI, 2021) [paper] [code]
- Lifelong and Continual Learning Dialogue Systems: Learning during Conversation(AAAI, 2021) [paper]
- Continual learning for named entity recognition(AAAI, 2021) [paper]
- Using Hindsight to Anchor Past Knowledge in Continual Learning(AAAI, 2021) [paper]
- Split-and-Bridge: Adaptable Class Incremental Learning within a Single Neural Network(AAAI, 2021) [paper] [code]
- Curriculum-Meta Learning for Order-Robust Continual Relation Extraction(AAAI, 2021) [paper]
- Continual Learning by Using Information of Each Class Holistically(AAAI, 2021) [paper]
- Gradient Regularized Contrastive Learning for Continual Domain Adaptation(AAAI, 2021) [paper]
- Unsupervised Model Adaptation for Continual Semantic Segmentation(AAAI, 2021) [paper]
- A Continual Learning Framework for Uncertainty-Aware Interactive Image Segmentation(AAAI, 2021) [paper]
- Do Not Forget to Attend to Uncertainty While Mitigating Catastrophic Forgetting(WACV, 2021) [paper]
- SpikeDyn: A Framework for Energy-Efficient Spiking Neural Networks with Continual and Unsupervised Learning Capabilities in Dynamic Environments (DAC2021) [paper]
- Rethinking Experience Replay: a Bag of Tricks for Continual Learning(ICPR, 2020) [paper] [code]
- Continual Learning for Natural Language Generation in Task-oriented Dialog Systems(EMNLP, 2020) [paper]
- Distill and Replay for Continual Language Learning(COLING, 2020) [paper]
- Continual Learning of a Mixed Sequence of Similar and Dissimilar Tasks (NeurIPS2020) [paper] [code]
- Meta-Consolidation for Continual Learning (NeurIPS2020) [paper]
- Understanding the Role of Training Regimes in Continual Learning (NeurIPS2020) [paper]
- Continual Learning with Node-Importance based Adaptive Group Sparse Regularization (NeurIPS2020) [paper]
- Online Fast Adaptation and Knowledge Accumulation (OSAKA): a New Approach to Continual Learning (NeurIPS2020) [paper]
- Coresets via Bilevel Optimization for Continual Learning and Streaming (NeurIPS2020) [paper]
- RATT: Recurrent Attention to Transient Tasks for Continual Image Captioning (NeurIPS2020) [paper]
- Continual Deep Learning by Functional Regularisation of Memorable Past (NeurIPS2020) [paper]
- Dark Experience for General Continual Learning: a Strong, Simple Baseline (NeurIPS2020) [paper] [code]
- GAN Memory with No Forgetting (NeurIPS2020) [paper]
- Calibrating CNNs for Lifelong Learning (NeurIPS2020) [paper]
- Mitigating Forgetting in Online Continual Learning via Instance-Aware Parameterization (NeurIPS2020) [paper]
- ADER: Adaptively Distilled Exemplar Replay Towards Continual Learning for Session-based Recommendation(RecSys, 2020) [paper]
- Initial Classifier Weights Replay for Memoryless Class Incremental Learning (BMVC2020) [paper]
- Adversarial Continual Learning (ECCV2020) [paper] [code]
- REMIND Your Neural Network to Prevent Catastrophic Forgetting (ECCV2020) [paper] [code]
- Incremental Meta-Learning via Indirect Discriminant Alignment (ECCV2020) [paper]
- Memory-Efficient Incremental Learning Through Feature Adaptation (ECCV2020) [paper]
- PODNet: Pooled Outputs Distillation for Small-Tasks Incremental Learning (ECCV2020) [paper] [code]
- Reparameterizing Convolutions for Incremental Multi-Task Learning Without Task Interference (ECCV2020) [paper]
- Learning latent representions across multiple data domains using Lifelong VAEGAN (ECCV2020) [paper]
- Online Continual Learning under Extreme Memory Constraints (ECCV2020) [paper]
- Class-Incremental Domain Adaptation (ECCV2020) [paper]
- More Classifiers, Less Forgetting: A Generic Multi-classifier Paradigm for Incremental Learning (ECCV2020) [paper]
- Piggyback GAN: Efficient Lifelong Learning for Image Conditioned Generation (ECCV2020) [paper]
- GDumb: A Simple Approach that Questions Our Progress in Continual Learning (ECCV2020) [paper]
- Imbalanced Continual Learning with Partitioning Reservoir Sampling (ECCV2020) [paper]
- Topology-Preserving Class-Incremental Learning (ECCV2020) [paper]
- GraphSAIL: Graph Structure Aware Incremental Learning for Recommender Systems (CIKM2020) [paper]
- OvA-INN: Continual Learning with Invertible Neural Networks (IJCNN2020) [paper]
- XtarNet: Learning to Extract Task-Adaptive Representation for Incremental Few-Shot Learning (ICLM2020) [paper]
- Optimal Continual Learning has Perfect Memory and is NP-HARD (ICML2020) [paper]
- Neural Topic Modeling with Continual Lifelong Learning (ICML2020) [paper]
- Continual Learning with Knowledge Transfer for Sentiment Classification (ECML-PKDD2020) [paper] [code]
- Semantic Drift Compensation for Class-Incremental Learning (CVPR2020) [paper] [code]
- Few-Shot Class-Incremental Learning (CVPR2020) [paper]
- Modeling the Background for Incremental Learning in Semantic Segmentation (CVPR2020) [paper]
- Incremental Few-Shot Object Detection (CVPR2020) [paper]
- Incremental Learning In Online Scenario (CVPR2020) [paper]
- Maintaining Discrimination and Fairness in Class Incremental Learning (CVPR2020) [paper]
- Conditional Channel Gated Networks for Task-Aware Continual Learning (CVPR2020) [paper]
- Continual Learning with Extended Kronecker-factored Approximate Curvature (CVPR2020) [paper]
- iTAML : An Incremental Task-Agnostic Meta-learning Approach (CVPR2020) [paper] [code]
- Mnemonics Training: Multi-Class Incremental Learning without Forgetting (CVPR2020) [paper] [code]
- ScaIL: Classifier Weights Scaling for Class Incremental Learning (WACV2020) [paper]
- Accepted papers(ICLR2020) [paper]
- Brain-inspired replay for continual learning with artificial neural networks (Natrue Communications 2020) [paper] [code]
- Learning to Continually Learn (ECAI 2020) [paper] [code]
- Compacting, Picking and Growing for Unforgetting Continual Learning (NeurIPS2019)[paper][code]
- Increasingly Packing Multiple Facial-Informatics Modules in A Unified Deep-Learning Model via Lifelong Learning (ICMR2019) [paper][code]
- Towards Training Recurrent Neural Networks for Lifelong Learning (Neural Computation 2019) [paper]
- Complementary Learning for Overcoming Catastrophic Forgetting Using Experience Replay (IJCAI2019) [paper]
- IL2M: Class Incremental Learning With Dual Memory (ICCV2019) [paper]
- Incremental Learning Using Conditional Adversarial Networks (ICCV2019) [paper]
- Adaptive Deep Models for Incremental Learning: Considering Capacity Scalability and Sustainability (KDD2019) [paper]
- Random Path Selection for Incremental Learning (NeurIPS2019) [paper]
- Online Continual Learning with Maximal Interfered Retrieval (NeurIPS2019) [paper]
- Meta-Learning Representations for Continual Learning (NeurIPS2019) [paper] [code]
- Overcoming Catastrophic Forgetting with Unlabeled Data in the Wild (ICCV2019) [paper]
- Continual Learning by Asymmetric Loss Approximation with Single-Side Overestimation (ICCV2019) [paper]
- Lifelong GAN: Continual Learning for Conditional Image Generation (ICCV2019) [paper]
- Continual learning of context-dependent processing in neural networks (Nature Machine Intelligence 2019) [paper] [code]
- Large Scale Incremental Learning (CVPR2019) [paper] [code]
- Learning a Unified Classifier Incrementally via Rebalancing (CVPR2019) [paper] [code]
- Learning Without Memorizing (CVPR2019) [paper]
- Learning to Remember: A Synaptic Plasticity Driven Framework for Continual Learning (CVPR2019) [paper]
- Learn to Grow: A Continual Structure Learning Framework for Overcoming Catastrophic Forgetting (ICML2019) [paper]
- Efficient Lifelong Learning with A-GEM (ICLR2019) [paper] [code]
- Learning to Learn without Forgetting By Maximizing Transfer and Minimizing Interference (ICLR2019) [paper] [code]
- Overcoming Catastrophic Forgetting via Model Adaptation (ICLR2019) [paper]
- A comprehensive, application-oriented study of catastrophic forgetting in DNNs (ICLR2019) [paper]
- Memory Replay GANs: learning to generate images from new categories without forgetting (NIPS2018) [paper] [code]
- Reinforced Continual Learning (NIPS2018) [paper] [code]
- Online Structured Laplace Approximations for Overcoming Catastrophic Forgetting (NIPS2018) [paper]
- Rotate your Networks: Better Weight Consolidation and Less Catastrophic Forgetting (R-EWC) (ICPR2018) [paper] [code]
- Exemplar-Supported Generative Reproduction for Class Incremental Learning (BMVC2018) [paper] [code]
- End-to-End Incremental Learning (ECCV2018) [paper][code]
- Riemannian Walk for Incremental Learning: Understanding Forgetting and Intransigence (ECCV2018)[paper]
- Piggyback: Adapting a Single Network to Multiple Tasks by Learning to Mask Weights (ECCV2018) [paper] [code]
- Memory Aware Synapses: Learning what (not) to forget (ECCV2018) [paper] [code]
- Lifelong Learning via Progressive Distillation and Retrospection (ECCV2018) [paper]
- PackNet: Adding Multiple Tasks to a Single Network by Iterative Pruning (CVPR2018) [paper] [code]
- Overcoming Catastrophic Forgetting with Hard Attention to the Task (ICML2018) [paper] [code]
- Lifelong Learning with Dynamically Expandable Networks (ICLR2018) [paper]
- FearNet: Brain-Inspired Model for Incremental Learning (ICLR2018) [paper]
- Incremental Learning of Object Detectors Without Catastrophic Forgetting (ICCV2017) [paper]
- Overcoming catastrophic forgetting in neural networks (EWC) (PNAS2017) [paper] [code] [code]
- Continual Learning Through Synaptic Intelligence (ICML2017) [paper] [code]
- Gradient Episodic Memory for Continual Learning (NIPS2017) [paper] [code]
- iCaRL: Incremental Classifier and Representation Learning (CVPR2017) [paper] [code]
- Continual Learning with Deep Generative Replay (NIPS2017) [paper] [code]
- Overcoming Catastrophic Forgetting by Incremental Moment Matching (NIPS2017) [paper] [code]
- Expert Gate: Lifelong Learning with a Network of Experts (CVPR2017) [paper]
- Encoder Based Lifelong Learning (ICCV2017) [paper]