Da-Wei Zhou

Bi-Compatible Task-Agnostic Feature Augmentation for Expansion-Based Class-Incremental Learning

This paper systematically identifies one of the fundamental challenges behind CIL, named feature collision, where the features learned by the current task-specific model may collide with those of the previous models, leading to forgetting of previously learned tasks and hindering the learning of new tasks.