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The 'template' has target information and embeds A, C region as a dissimilarity map (D_t).
Actually, I did not mention this detailed motivation in my paper....
I conjecture that:
When a target moves from red to blue region, the S_(t-n) gives attention to the red region (A+B).
Therefore, we know where is A + B region in f8_t
However, the real target information is located in B + C region inside of f8_t.
Therefore, B has strong target information (attention from S_t-n and target feature),
and C (target feature) has less strong target information.
The template matching uses the 'template' and recognizes the B and C region from f8_t.
So finally, we can know and divide where is B and C regions,
and creates a dissimilarity map (D_t) for A and C region.
Yes, refine-translator is added after backbone (feature extractor)
You can insert refine-translator middle of generating mask (refined network).
Please let me know if you have further questions.
I would like to ask the following questions: 1. What exactly do templates refer to in template matching; 2. Refine-translator is added after backbone?
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