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Yes, certainly. To obtain more fine-grained segmentation masks, you can consider applying the normalized cut algorithm to the initial masks. This algorithm can help to provide more fine-grained results.
Alternatively, you can also explore using k-Means clustering or spectral clustering methods to obtain more part segmentation masks. These clustering techniques can help further partition the objects into smaller regions or parts, allowing for a more comprehensive and detailed segmentation of the objects in the image.
Can I achieve more fine-grained segmentation? For example, dividing the parts of an object.Thanks for your reply.
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