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Thanks for this great work first.
I have question about the network structure, this is, why the length of output bbox is 8? If we use class-agonistic bbox regression, the length of bbox vector should be 4. Are the first 4 values regressed for background, and the last 4 values regressed for objects?
The text was updated successfully, but these errors were encountered:
Yes, in agonistic bbox regression it is actually a 2-class bbox regression, the first 4 dims are for background and the last 4 dims are for foreground. In fact the first 4 dims will never be used.
Thanks for this great work first.
I have question about the network structure, this is, why the length of output bbox is 8? If we use class-agonistic bbox regression, the length of bbox vector should be 4. Are the first 4 values regressed for background, and the last 4 values regressed for objects?
The text was updated successfully, but these errors were encountered: