Yongchun Lü

Not All Classes are Equal: Adaptively Focus-Aware Confidence for Semi-Supervised Object Detection

Semi-supervised object detection (SSOD) is a significant application of Semi-supervised learning to further improve object detectors but suffers more seriously from confirmation bias and error accumulation caused by the classes imbalance. Existing SSOD approaches have attempted to address this issue…