Cross Domain Adaptation of Crowd Counting with Model-Agnostic Meta-Learning

Cross Domain Adaptation of Crowd Counting with Model-Agnostic Meta-Learning

Counting people in crowd scenarios is extensively conducted in drone inspections, video surveillance, and public safety applications. Today, crowd count algorithms with supervised learning have improved significantly, but with a reliance on a large amount of manual annotation. However, in real world...

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Bibliographic Details
Main Authors:	Xiaoyu Hou, Jihui Xu, Jinming Wu, Huaiyu Xu
Format:	Article
Language:	English
Published:	MDPI AG 2021-12-01
Series:	Applied Sciences
Subjects:	crowd counting domain adaptation cross-domain meta-learning synthetic dataset
Online Access:	https://www.mdpi.com/2076-3417/11/24/12037

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