Comments (1)
Hi @cyrilzakka ,
Great question! We didn't check segmentation properties, but just released the pre-trained models so you're welcome to check!
My thoughts:
In general, MSN introduces an additional mask invariance, which helps the model discard a lot of instance-level information and produce more abstract representations. This property is helpful for low-shot semantic abstraction tasks, but I imagine could hurt performance on low-level tasks like segmentation. In short, I would expect performance to be similar to DINO on segmentation, although I would be a little surprised if it was better by any significant margin. Having said this, I have not personally checked and would be curious to learn about your findings if you try this.
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Related Issues (20)
- module 'cyanure' has no attribute 'preprocess' HOT 4
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from msn.