Fen9 / TRiG

Implementation of CVPR2022 paper: Transform-Retrieve-Generate: Natural Language-Centric Outside-Knowledge Visual Question Answering

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TRiG

Redrecting the implementation of CVPR2022 paper: Transform-Retrieve-Generate: Natural Language-Centric Outside-Knowledge Visual Question Answering web .

Link to TRiG implementation

Thanks to my fellow @Weizhe Lin, an unofficial implementation of TRiG can be found here: https://github.com/LinWeizheDragon/Retrieval-Augmented-Visual-Question-Answering?tab=readme-ov-file#trig.

I (the first author) certify that this implementation achieves very similar performances of TRiG, following the same method from the official manuscript: pdf

You are also welcomed to implement TRiG by yourself as it is straightforward to understand.

DisClaimer

Due to the policies of Amazon, the official implementation of TRiG is not permitted to release (2023/12). Fortunately, you can find the 3rd party implementation from above link for your convenience. Note that, Amazon has not supported or certified the above implementation.

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Implementation of CVPR2022 paper: Transform-Retrieve-Generate: Natural Language-Centric Outside-Knowledge Visual Question Answering

License:MIT License