Is BertEncoder fine-tuned on the visual grounding tasks?

[PlumedSerpent]

It seems that BertEncoder will be finetuned and updated during training, which is unfair compared to "Improving one-stage visual grounding by recursive sub-query construction" and "A fast and accurate one- stage approach to visual grounding".

[hbb1]

@PlumedSerpent
Thanks for you attention. We fine-tuned Bert for comparing to SQC-large (see their codebase) in refcocog.
Actually, we achieve comparable or even better results with LSTM to SQC-large (BertEncoder) in refcoco, referit, refcoco+.
Completely fair comparison to their algorithms (SQC) is not practical, e.g. they use more parameters, large resolution input, etc. Furthermore, our contribution does not lie in the language side so our paper seems orthogonal to SQC.

[hbb1]

I am going to close this issue. Please open more if there is any other comment.