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I am concerned about the self.embedding_maskfeature in your code. In your code I see that this module is something like you just decrease then increase the number of channel, is it right? or is there any other purpose of this module?
The text was updated successfully, but these errors were encountered:
Hi, self.embedding_maskfeature is used for adding some trainable parameters to the learning of maskfeature.
Since the maskdecoder is fixed and we find that adding learnable parameter on maskfeature can improve the perfomance of results on HQ-Seg44K dataset.
Thank you for replying; I also have a question about your ablation study in
Table 2: What does SAM + HQ-Output Token mean? I understand that you just
added a learnable token is self.hq_token, then dot product with
upscaled_embedding, is this right? If it's right, *what is *different*
between self.hq_token and self.mask_tokens.*
Thanks so much!
Thank you for the impressive repo!
I am concerned about the self.embedding_maskfeature in your code. In your code I see that this module is something like you just decrease then increase the number of channel, is it right? or is there any other purpose of this module?
The text was updated successfully, but these errors were encountered: