Self-Supervised Deep Correlation Tracking

The training of a feature extraction network typically requires abundant manually annotated training samples, making this a time-consuming and costly process. Accordingly, we propose an effective self-supervised learning-based tracker in a deep correlation framework (named: self-SDCT). Motivated by...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 30(2021) vom: 01., Seite 976-985
1. Verfasser:	Yuan, Di (VerfasserIn)
Weitere Verfasser:	Chang, Xiaojun, Huang, Po-Yao, Liu, Qiao, He, Zhenyu
Format:	Online-Aufsatz
Sprache:	English
Veröffentlicht:	2021
Zugriff auf das übergeordnete Werk:	IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Schlagworte:	Journal Article