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Haichen Zhou

2 accepted papers

2024

Compositional Few-Shot Class-Incremental Learning

ICML 2024poster

Few-shot class-incremental learning (FSCIL) is proposed to continually learn from novel classes with only a few samples after the (pre-)training on base classes with sufficient data. However, this remains a challenge. In contrast, humans can easily recognize novel classes with a few samples. Cogniti…

2024

Delve into Base-Novel Confusion: Redundancy Exploration for Few-Shot Class-Incremental Learning

IJCAI 2024poster

Few-shot class-incremental learning (FSCIL) aims to acquire knowledge from novel classes with limited samples while retaining information about base classes. Existing methods address catastrophic forgetting and overfitting by freezing the feature extractor during novel-class learning. However, these…

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