2 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.CV2024
Exemplar-Free Class Incremental Learning via Incremental Representation
Libo Huang, Zhulin An, Yan Zeng +3
Exemplar-Free Class Incremental Learning (efCIL) aims to continuously incorporate the knowledge from new classes while retaining previously learned information, without storing any…
cs.CV2023★ 1 cited
eTag: Class-Incremental Learning with Embedding Distillation and Task-Oriented Generation
Libo Huang, Yan Zeng, Chuanguang Yang +3
Class-Incremental Learning (CIL) aims to solve the neural networks' catastrophic forgetting problem, which refers to the fact that once the network updates on a new task, its perfo…
cs.CV2022★ 2 cited
MixSKD: Self-Knowledge Distillation from Mixup for Image Recognition
Chuanguang Yang, Zhulin An, Helong Zhou +5
Unlike the conventional Knowledge Distillation (KD), Self-KD allows a network to learn knowledge from itself without any guidance from extra networks. This paper proposes to perfor…