What exactly is the purpose of Bounding Box Regression Decoder?

[furkanpala]

Hi, thanks for the implementation. I have a confusion about the reason authors came up with the bounding box regression decoder part. Is it for instance segmentation? As much as I understand, it helps to distinguish instances from the same classes. Is this correct? Also, I have a custom dataset which contains just the detected words by OCR and labels for each word. It is like a Named Entity Recognition (NER) dataset. I do not have interested regions annotated like items, company name etc. I have only words, bounding box and label for each word. In this case, I have implemented only the semantic segmentation decoder. Since I am not interested in instance segmentation, I thought that I do not the bounding box regression decoder branch. Is this a correct assumption or does the bounding box regression decoder improves the accuracy?