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Dense Gaussian Processes For Few-Shot Segmentation Few-shot segmentation is a challenging dense prediction task, which entails segmenting a novel query image given only a small annotated support set. the key problem is thus to design a method that aggregates detailed information from the support set, while being robust to large variations in appearance and context. to this end, we propose a few-shot segmentation method based on dense gaussian process (gp) regression. given the support set, our dense gp learns the […]
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