Reducing Spatial Labeling Redundancy for Active Semi-Supervised Crowd Counting

Labeling is onerous for crowd counting as it should annotate each individual in crowd images. Recently, several methods have been proposed for semi-supervised crowd counting to reduce the labeling efforts. Given a limited labeling budget, they typically select a few crowd images and densely label al...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	IEEE transactions on pattern analysis and machine intelligence 2023-07, Vol.45 (7), p.9248-9255
Hauptverfasser:	Liu, Yongtuo, Ren, Sucheng, Chai, Liangyu, Wu, Hanjie, Xu, Dan, Qin, Jing, He, Shengfeng
Format:	Artikel
Sprache:	eng
Schlagworte:	Crowd counting Feature extraction Head Labeling Labelling Probabilistic models Propagation Redundancy semi-supervised learning Similarity spatial labeling redundancy Technological innovation Termination of employment Training
Online-Zugang:	Volltext bestellen
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!