Dense Learning based Semi-Supervised Object Detection

Semi-supervised object detection (SSOD) aims to facilitate the training and deployment of object detectors with the help of a large amount of unlabeled data. Though various self-training based and consistency-regularization based SSOD methods have been proposed, most of them are anchor-based detecto...

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Vydáno v:	Proceedings (IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Online) s. 4805 - 4814
Hlavní autoři:	Chen, Binghui, Li, Pengyu, Chen, Xiang, Wang, Biao, Zhang, Lei, Hua, Xian-Sheng
Médium:	Konferenční příspěvek
Jazyk:	angličtina
Vydáno:	IEEE 01.06.2022
Témata:	Bridges categorization Codes Computer vision Detectors Filtering grouping and shape analysis; Self-& semi-& meta- & unsupervised learning Recognition: detection retrieval; Deep learning architectures and techniques; Scene analysis and understanding; Segmentation Training Uncertainty
ISSN:	1063-6919
On-line přístup:	Získat plný text
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