Collaborative Feature-Logits Contrastive Learning for Open-Set Semi-Supervised Object Detection

X Zhong, S Jiao, Y Zhao, Y Wei - Proceedings of the 6th ACM …, 2024 - dl.acm.org
Current Semi-Supervised Object Detection (SSOD) methods enhance detector performance
by leveraging large amounts of unlabeled data, assuming that both labeled and unlabeled …

Class-balanced Open-set Semi-supervised Object Detection for Medical Images

Z Lu, R Gu, H Cheng, S Pang, M Xu, P Xu… - arxiv preprint arxiv …, 2024 - arxiv.org
Medical image datasets in the real world are often unlabeled and imbalanced, and Semi-
Supervised Object Detection (SSOD) can utilize unlabeled data to improve an object …