sam-hq
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About Semantic Segmentation
Hello, I want to ask how to achieve the semantic segmentation effect described in the article images, such as identifying a person, cow, car?
Hi thanks for the question. For example, on the COCO dataset, we use a SOTA detector FocalNet-DINO trained on the COCO dataset as our box prompt generator to produce mask. The box prompt already contains the category information.
I wonder whether SAM-HQ still has the ability to perform zero-shot labeling by using detector for semantic segmentation.
Hi thanks for the question. For example, on the COCO dataset, we use a SOTA detector FocalNet-DINO trained on the COCO dataset as our box prompt generator to produce mask. The box prompt already contains the category information.
Hi . I want to know when you use the box prompt, if only boxes greater than the threshold are used as input?