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 ...
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