4 papers · 1 filter
Parameterized Prompt for Incremental Object Detection
Zijia An, Boyu Diao, Ruiqi Liu +5
Recent studies have demonstrated that incorporating trainable prompts into pretrained models enables effective incremental learning. However, the application of prompts in incremen…
Semantic-Guided Dynamic Sparsification for Pre-Trained Model-based Class-Incremental Learning
Ruiqi Liu, Boyu Diao, Zijia An +4
Class-Incremental Learning (CIL) requires a model to continually learn new classes without forgetting old ones. A common and efficient solution freezes a pre-trained model and empl…
Dynamical Adapter Fusion: Constructing A Global Adapter for Pre-Trained Model-based Class-Incremental Learning
Ruiqi Liu, Boyu Diao, Zijia An +3
Class-Incremental Learning (CIL) requires models to continuously acquire new classes without forgetting previously learned ones. A dominant paradigm involves freezing a pre-trained…
PrePrompt: Predictive prompting for class incremental learning
Libo Huang, Zhulin An, Chuanguang Yang +5
Class Incremental Learning (CIL) based on pre-trained models offers a promising direction for open-world continual learning. Existing methods typically rely on correlation-based st…