Survey of semi-supervised object detection
Survey of semi-supervised object detection
Semi-supervised Object Detection: A Survey on Recent Research and Progress
arXiv paper abstract https://arxiv.org/abs/2306.14106
arXiv PDF paper https://arxiv.org/pdf/2306.14106.pdf
In recent years, deep learning technology has been maturely applied in the field of object detection, and most algorithms tend to be supervised learning.
… Semi-supervised object detection (SSOD) … learn information by using small amounts of labeled data and large amounts of unlabeled data.
… present a comprehensive and up-to-date survey on the SSOD approaches from five aspects.
… first briefly introduce several ways of data augmentation.
… dive the mainstream semi-supervised strategies into pseudo labels, consistent regularization, graph based and transfer learning based methods, and introduce some methods in challenging settings.
… present widely-used loss functions … outline the common benchmark datasets and compare the accuracy among different representative approaches …
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