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Found 2 papers, 1 papers with code
A Robust Learning Approach to Domain Adaptive Object Detection
To adapt to the domain shift, the model is trained on the target domain using a set of noisy object bounding boxes that are obtained by a detection model trained only in the source domain.
Semi-Supervised Semantic Image Segmentation with Self-correcting Networks
Building a large image dataset with high-quality object masks for semantic segmentation is costly and time consuming.
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