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cs.CV2024
Mamba-CL: Optimizing Selective State Space Model in Null Space for Continual Learning
De Cheng, Yue Lu, Lingfeng He +4
Continual Learning (CL) aims to equip AI models with the ability to learn a sequence of tasks over time, without forgetting previously learned knowledge. Recently, State Space Mode…
cs.CV2024★ 1 cited
Frequency-Guided Spatial Adaptation for Camouflaged Object Detection
Shizhou Zhang, Dexuan Kong, Yinghui Xing +5
Camouflaged object detection (COD) aims to segment camouflaged objects which exhibit very similar patterns with the surrounding environment. Recent research works have shown that e…
cs.CV2024
Visual Prompt Tuning in Null Space for Continual Learning
Yue Lu, Shizhou Zhang, De Cheng +4
Existing prompt-tuning methods have demonstrated impressive performances in continual learning (CL), by selecting and updating relevant prompts in the vision-transformer models. On…