Task-Adaptive Saliency Guidance for Exemplar-free Class Incremental Learning

arXiv:2212.08251v2 Announce Type: replace
Abstract: Exemplar-free Class Incremental Learning (EFCIL) aims to sequentially learn tasks with access only to data from the current one. EFCIL is of interest because it mitigates concerns about privacy and long-term storage of data, while at the same time alleviating the problem of catastrophic forgetting in incremental learning. In this work, we introduce task-adaptive saliency for EFCIL and propose a new framework, which we call Task-Adaptive Saliency Supervision (TASS), for mitigating the negative effects of …

arxiv class cs.cv free guidance incremental type