3 papers
cs.LG2024
Distribution-Level Memory Recall for Continual Learning: Preserving Knowledge and Avoiding Confusion
Shaoxu Cheng, Kanglei Geng, Chiyuan He +7
Continual Learning (CL) aims to enable Deep Neural Networks (DNNs) to learn new data without forgetting previously learned knowledge. The key to achieving this goal is to avoid con…
cs.CV2023
GRSDet: Learning to Generate Local Reverse Samples for Few-shot Object Detection
Hefei Mei, Taijin Zhao, Shiyuan Tang +5
Few-shot object detection (FSOD) aims to achieve object detection only using a few novel class training data. Most of the existing methods usually adopt a transfer-learning strateg…
cs.MM2023
Instance-Wise Adaptive Tuning and Caching for Vision-Language Models
Chunjin Yang, Fanman Meng, Shuai Chen +2
Large-scale vision-language models (LVLMs) pretrained on massive image-text pairs have achieved remarkable success in visual representations. However, existing paradigms to transfe…