CLVision20
* *Continual Learning in Computer Vision
* CatNet: Class Incremental 3D ConvNets for Lifelong Egocentric Gesture Recognition
* Cognitively-Inspired Model for Incremental Learning Using a Few Examples
* Continual Learning for Anomaly Detection in Surveillance Videos
* Continual Learning of Object Instances
* Continual Reinforcement Learning in 3D Non-stationary Environments
* Dropout as an Implicit Gating Mechanism For Continual Learning
* Few-shot Image Recognition for UAV Sports Cinematography
* Generalized Class Incremental Learning
* Generating Accurate Pseudo Examples for Continual Learning
* Generative Feature Replay For Class-Incremental Learning
* Lifelong Machine Learning with Deep Streaming Linear Discriminant Analysis
* M2SGD: Learning to Learn Important Weights
* Noise-based Selection of Robust Inherited Model for Accurate Continual Learning
* Reducing catastrophic forgetting with learning on synthetic data
* Rehearsal-Free Continual Learning over Small Non-I.I.D. Batches
* Relationship Matters: Relation Guided Knowledge Transfer for Incremental Learning of Object Detectors
* StackNet: Stacking feature maps for Continual learning
* Stream-51: Streaming Classification and Novelty Detection from Videos
* What is Happening Inside a Continual Learning Model?: A Representation-Based Evaluation of Representational Forgetting
20 for CLVision20
CLVision21
* *Continual Learning in Computer Vision
* Avalanche: an End-to-End Library for Continual Learning
* Class-Incremental Learning with Generative Classifiers
* Dual-Teacher Class-Incremental Learning With Data-Free Generative Replay
* Essentials for Class Incremental Learning
* Graph-based Person Signature for Person Re-Identifications
* IB-DRR: Incremental Learning with Information-Back Discrete Representation Replay
* ILCOC: An Incremental Learning Framework based on Contrastive One-class Classifiers
* Insights from the Future for Continual Learning
* Neural Architecture Search of Deep Priors: Towards Continual Learning without Catastrophic Interference
* Plastic and Stable Gated Classifiers for Continual Learning
* Selective Replay Enhances Learning in Online Continual Analogical Reasoning
* Supervised Contrastive Replay: Revisiting the Nearest Class Mean Classifier in Online Class-Incremental Continual Learning
* Tale of Two CILs: The Connections between Class Incremental Learning and Class Imbalanced Learning, and Beyond, A
* Ternary Feature Masks: zero-forgetting for task-incremental learning
15 for CLVision21
CLVision22
* *Continual Learning in Computer Vision
* Alleviating Representational Shift for Continual Fine-tuning
* Attenuating Catastrophic Forgetting by Joint Contrastive and Incremental Learning
* CNLL: A Semi-supervised Approach For Continual Noisy Label Learning
* Continual Hippocampus Segmentation with Transformers
* Continual Learning Based on OOD Detection and Task Masking
* Continual Learning with Transformers for Image Classification
* Continually Learning Self-Supervised Representations with Projected Functional Regularization
* CSG0: Continual Urban Scene Generation with Zero Forgetting
* Entropy-based Stability-Plasticity for Lifelong Learning
* Ex-Model: Continual Learning from a Stream of Trained Models
* Incremental Meta-Learning via Episodic Replay Distillation for Few-Shot Image Recognition
* Medusa: Universal Feature Learning via Attentional Multitasking
* Modeling Missing Annotations for Incremental Learning in Object Detection
* Multi-Head Distillation for Continual Unsupervised Domain Adaptation in Semantic Segmentation
* Multi-Task Learning for Video Surveillance with Limited Data
* Online Unsupervised Domain Adaptation for Person Re-identification
* Out-Of-Distribution Detection In Unsupervised Continual Learning
* Spacing Loss for Discovering Novel Categories
* Towards Exemplar-Free Continual Learning in Vision Transformers: an Account of Attention, Functional and Weight Regularization
* Transferring Unconditional to Conditional GANs with Hyper-Modulation
* Unsupervised Continual Learning for Gradually Varying Domains
* Variable Few Shot Class Incremental and Open World Learning
* Visual Goal-Directed Meta-Imitation Learning
24 for CLVision22
CLVision23
* *Continual Learning in Computer Vision
* Are Labels Needed for Incremental Instance Learning?
* Closer Look at Rehearsal-Free Continual Learning *, A
* CLVOS23: A Long Video Object Segmentation Dataset for Continual Learning
* Continual Domain Adaptation through Pruning-aided Domain-specific Weight Modulation
* Continual Learning for LiDAR Semantic Segmentation: Class-Incremental and Coarse-to-Fine strategies on Sparse Data
* CoVIO: Online Continual Learning for Visual-Inertial Odometry
* D3Former: Debiased Dual Distilled Transformer for Incremental Learning
* Density Map Distillation for Incremental Object Counting
* How Efficient Are Today's Continual Learning Algorithms?
* Just a Glimpse: Rethinking Temporal Information for Video Continual Learning
* Lifelong Learning of Task-Parameter Relationships for Knowledge Transfer
* Online Distillation with Continual Learning for Cyclic Domain Shifts
* SCALE: Online Self-Supervised Lifelong Learning without Prior Knowledge
* Simulating Task-Free Continual Learning Streams From Existing Datasets
15 for CLVision23
CLVision24
* *Continual Learning in Computer Vision
* Active Data Collection and Management for Real-World Continual Learning via Pretrained Oracle
* analysis of best-practice strategies for replay and rehearsal in continual learning, An
* Calibrating Higher-Order Statistics for Few-Shot Class-Incremental Learning with Pre-trained Vision Transformers
* Calibration of Continual Learning Models
* Class-Incremental Mixture of Gaussians for Deep Continual Learning
* Continual Learning with Weight Interpolation
* Continual-Zoo: Leveraging Zoo Models for Continual Classification of Medical Images
* DELTA: Decoupling Long-Tailed Online Continual Learning
* Expanding Scope of the Stability Gap: Unveiling its Presence in Joint Incremental Learning of Homogeneous Tasks, The
* MultIOD: Rehearsal-free Multihead Incremental Object Detector
* Tackling Domain Shifts in Person Re-Identification: A Survey and Analysis
* TAME: Task Agnostic Continual Learning using Multiple Experts
* Unveiling the Anomalies in an Ever-Changing World: A Benchmark for Pixel-Level Anomaly Detection in Continual Learning
* VLM-PL: Advanced Pseudo Labeling approach for Class Incremental Object Detection via Vision-Language Model
* Wake-Sleep Energy Based Models for Continual Learning
16 for CLVision24