小样本图像目标检测研究综述

近年来,以深度学习为基础的图像目标检测技术取得了显著成就,并涌现了许多成熟的检测模型,但这些模型均需要利用大量的标注样本进行训练,而在实际场景当中,往往很难获取到相应规模的高质量标注样本,从而限制了其在特定领域的应用和推广.由于对样本数量的依赖性小,小样本条件下的图像目标检测技术逐渐得到研究和发展.基于小样本图像目标检...

Review of Few-Shot Object Detection

Recently,object detection based on deep learning has been achieved remarkable achievements and various of mature models have been proposed.However,most of these models rely on a large number of annotated training samples.Besides,in practical applications,it is often difficult to get access to large scale of high-quality annotated samples,which limits its application and popularization in specific areas.Few-shot object detection has been extensively researched taking advantage of its small dependence on the number of samples.Based on the current research,this paper reviews the current mainstream of the few-shot object detection systematically,including problem definition,mainstream methods,as well as common experimental designs.Then,it points out potential application directions.Furthermore,the generalized few-shot object detection is also briefly introduced.Finally,the paper analyzes challenges of the few-shot object detection technology and discusses corresponding countermeasures.