2023
DOI: 10.18293/seke2023-129
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Few-Shot Object Detection via Instance-wise and Prototypical Contrastive Learning

Qiaoning Lei,
Yinsai Guo,
Liyan Ma
et al.

Abstract: Few-shot object detection (FSOD), which involves training the detector with few annotated data to detect novel objects, has aroused a wide range of research interests. However, the performance of FSOD is still limited by insufficient data. Existing works usually adopt fine-tuning paradigm, which first uses rich base classes for pre-training and then uses them to carve the novel class feature space. In the fine-tuning phase, the balance space learned by the pre-trained model will be broken leading to an interse… Show more

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