Abstract: Self-training is a novel learning paradigm that generates pseudolabels for unlabeled data, enabling deep learning models to be trained without the need for humanlabeled data. This article ...

Abstract: Open-world class-agnostic object detection aims to localize all objects in images regardless of whether their categories are known during training. Most existing studies focus on unannotated ...