Abstract: Highlights•A novel semi-supervised object detection framework named Robust Teacher is proposed.•A self-correcting pseudo-label module is designed to correct false class annotations.•The re-balanced focal loss is introduced to alleviate the class bias in pseudo-labels.•A copy-paste methodology is presented and applied to unlabeled data.
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