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Found 2 papers, 2 papers with code
A Good Foundation is Worth Many Labels: Label-Efficient Panoptic Segmentation
A key challenge for the widespread application of learning-based models for robotic perception is to significantly reduce the required amount of annotated training data while achieving accurate predictions.
Few-Shot Panoptic Segmentation With Foundation Models
Concurrently, recent breakthroughs in visual representation learning have sparked a paradigm shift leading to the advent of large foundation models that can be trained with completely unlabeled images.
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