Survey of methods for detecting new objects with only a few examples

Survey of methods for detecting new objects with only a few examples

Few-Shot Object Detection: A Survey

arXiv paper abstract https://arxiv.org/abs/2112.11699v1

arXiv PDF paper https://arxiv.org/pdf/2112.11699v1.pdf

Humans are able to learn to recognize new objects even from a few examples.

In contrast, training deep-learning-based object detectors requires huge amounts of annotated data.

To avoid the need to acquire and annotate these huge amounts of data, few-shot object detection aims to learn from few object instances of new categories in the target domain.

In this survey, ... provide an overview of the state of the art in few-shot object detection.

... categorize approaches according to their training scheme and architectural layout.

For each type of approaches, ... describe the general realization as well as concepts to improve the performance on novel categories.

... introduce commonly used datasets and their evaluation protocols and analyze reported benchmark results. ...

Please like and share this post if you enjoyed it using the buttons at the bottom! Stay up to date. Subscribe to my posts https://morrislee1234.wixsite.com/website/contact Web site with my other posts by category https://morrislee1234.wixsite.com/website #ComputerVision #ObjectDetection #AINewsClips #AI #ML #ArtificialIntelligence #MachineLearning