Meta Faster R-CNN: Towards Accurate Few-Shot Object Detection with Attentive Feature Alignment. (arXiv:2104.07719v4 [cs.CV] UPDATED)

Few-shot object detection (FSOD) aims to detect objects using only a few
examples. How to adapt state-of-the-art object detectors to the few-shot domain
remains challenging. Object proposal is a key ingredient in modern object
detectors. However, the quality of proposals generated for few-shot classes
using existing methods is far worse than that of many-shot classes, e.g.,
missing boxes for few-shot classes due to misclassification or inaccurate
spatial locations with respect to true objects. To address the noisy proposal
problem, we …

alignment arxiv cnn cv detection feature meta r-cnn