VCL23
* *Visual Continual Learning
* Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learning
* AR-TTA: A Simple Method for Real-World Continual Test-Time Adaptation
* Class-Incremental Learning using Diffusion Model for Distillation and Replay
* Clustering-based Domain-Incremental Learning
* Comparative Study of Natural Replay and Experience Replay in Online Object Detection
* Comprehensive Empirical Evaluation on Online Continual Learning, A
* Confusion Mixup Regularized Multimodal Fusion Network for Continual Egocentric Activity Recognition
* Continual Evidential Deep Learning for Out-of-Distribution Detection
* Continual Learning with Deep Streaming Regularized Discriminant Analysis
* Decision Boundary Optimization for Few-shot Class-Incremental Learning
* Experience Replay as an Effective Strategy for Optimizing Decentralized Federated Learning
* FedRCIL: Federated Knowledge Distillation for Representation based Contrastive Incremental Learning
* Flashback for Continual Learning
* Identification of Novel Classes for Improving Few-Shot Object Detection
* Improving Replay Sample Selection and Storage for Less Forgetting in Continual Learning
* Instant Continual Learning of Neural Radiance Fields
* Looking through the past: better knowledge retention for generative replay in continual learning
* Margin Contrastive Learning with Learnable-Vector for Continual Learning
* Memory Population in Continual Learning via Outlier Elimination
* Memory-augmented Variational Adaptation for Online Few-shot Segmentation
* Multi-Task Consistency for Active Learning
* Multi-Task Hypergraphs for Semi-supervised Learning using Earth Observations
* Multimodal Parameter-Efficient Few-Shot Class Incremental Learning
* On the Effectiveness of LayerNorm Tuning for Continual Learning in Vision Transformers
* OpenIncrement: A Unified Framework for Open Set Recognition and Deep Class-Incremental Learning
* Progressive Feature Adjustment for Semi-supervised Learning from Pretrained Models
* SAM-Adapter: Adapting Segment Anything in Underperformed Scenes
* SATHUR: Self Augmenting Task Hallucinal Unified Representation for Generalized Class Incremental Learning
* ScrollNet: Dynamic Weight Importance for Continual Learning
* Selective Freezing for Efficient Continual Learning
* Simple Signal for Domain Shift, A
* TKIL: Tangent Kernel Optimization for Class Balanced Incremental Learning
* Trajectory-Prediction with Vision: A Survey
* Transformer-Based Sensor Fusion for Autonomous Driving: A Survey
* Unseen and Adverse Outdoor Scenes Recognition Through Event-based Captions
36 for VCL23