1) The contribution of this paper is to exploit the knowledge from the multiple pretrained deep models for VQA, while the practical method is doubtful. First, I am wondering why there are different pretrained models for different datasets. It is better to have a deeper analysis or insight into the fusion mechanism of various pretrained deep models. How the different pretrained models contribute to the quality-aware feature extraction is also valuable to be studied. 2) There are many pretrained models for various tasks, more pretrained models are encouraged to study for VQA. 3) I am still unclear about the motivation of intra-consistency and inter-divisibility loss related to quality assessment.
2) There are many pretrained models for various tasks, more pretrained models are encouraged to study for VQA.