Continual Zero-shot Learning (CZSL) is capable of classifying unseen categories across a sequence of tasks. However, CZSL is often plagued by the challenge of catastrophic forgetting. While recent studies have shown that preserving past data for experience replay can effectively address this issue,...
Continual Zero-Shot Learning through Semantically Guided Generative Random Walks Wenxuan Zhang1 Paul Janson1,2 * Kai Yi1 Ivan Skorokhodov1 Mohamed Elhoseiny1 KAUST1 University of Moratuwa2 {wenxuan.zhang, remond.janson, kai.yi, ivan.skorokhodov, mohamed.elhose...
Continual learning可以帮助预训练视觉模型不需要训练地有效泛化到下游任务上,然而Clip的zero-shot能力在灾难性遗忘后有很明显的下降,现在已有的Continual learning方法可以通过replay 之前的数据达到阻止遗忘,但是由于Clip的数据集是私密的,这种方法行不通。除此之外,尽管repaly可以增强表现,但是也会损害zero-shot的能力。
当前,一般认为持续学习 (Continual Learning) 和增量学习(Incremental Learning)、终身学习 (Lifelong Learning) 是等价表述,它们都是在连续的数据流中训练模型,随着时间的推移,更多的数据逐渐可用,同时旧数据可能由于存储限制或隐私保护等原因而逐渐不可用,并且学习任务的类型和数量没有预定义 (例如分类任务中的类别数)。
Zero-shot action recognition requires a strong ability to generalize from pre-training and seen classes to novel unseen classes. Similarly, continual learning aims to develop models that can generalize effectively and learn new tasks without forgetting the ones previously learned. The generalization goals...
Generalized continual zero- shot learning. CoRR, abs/2011.08508, 2020. [7] Stephen Grossberg. Consciousness CLEARS the mind. Neu- ral Networks, 20(9):1040–1053, 2007. [8] David Ha, Andrew M. Dai, and Quoc V. Le. Hypernet- works. In 5th International Conference o...
Language Models". Our approach Zero-Shot Continual Learning (ZSCL) aims to mitigate forgetting problem existed in the continual learning of large pretrained vision-language models. This repo includes experiments for Multi-domain Task Increamental Learning (MTIL) inmtiland Class Incremental Learning in...
与LAE一样,ZSCL将合并技术应用于CLIP模型,目的是在持续学习过程中保持其zero-shot性能。然而,随着EMA中权衡参数的改变,CLIP性能不再具有鲁棒性。因此,ZSCL建议每隔几次迭代合并参数,从而在模型训练期间创建平滑的损失轨迹。 此外,CoFiMA注意到EMA在Merge过程中对每个参数的重要性是相等的,CoFiMA 在Merge过程中插入Fishe...
Zero-shot learning (Lampert et al., 2009, Palatucci et al., 2009) and one-shot learning (Fei-Fei et al., 2003, Vinyals et al., 2016) aim at performing well on novel tasks but do not prevent catastrophic forgetting on previously learned tasks. An early attempt to realize lifelong ...
Continual Zero-Shot Learning through Semantically Guided Generative Random Walks(ICCV 2023)[paper] A Soft Nearest-Neighbor Framework for Continual Semi-Supervised Learning(ICCV 2023)[paper] Online Continual Learning on Hierarchical Label Expansion(ICCV 2023)[paper] Investigating the Catastrophic Forgetting ...