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The code of IJCAI2022 paper, Declaration-based Prompt Tuning for Visual Question Answering
The BaiduYun links in README has been cancelled. The new link is: https://pan.baidu.com/s/1HhPSum0aCqvEtgCe1Yxl0Q?pwd=8888
Hi,
The link to download object features is unavailable now (microsoft/Oscar#198).
Could you provide the object feature file of GQA and COCO?
Thanks a lot!
Hi,
Thanks for the open-source code provided in this repository for the paper, and I'm very interested in the zero/few-shot ability as shown in your great work, but as I investigate to evaluate the model under zero-shot MLM+ITM setting in run_gqa_prompt_zero_few.py
, I found that the ITM head (i.e. model.cls_ans.seq_relationship
) is newly initialized (and of different shape from original pretrained ITM head) and actually not used in the evaluation. Am I wrong on the usage of this code or is ITM head not participating in the evaluation?
Thanks a lot for your time and attention.
Does the model supports declaration generation on custom datasets such as CLEVRER, or just can be applied on GQA and VQA v2.0?
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