Papers by Amir Mazaheri

1 papers
MMFT-BERT: Multimodal Fusion Transformer with BERT Encodings for Visual Question Answering (2020.findings-emnlp)

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Challenge: MMFT-BERT is a multimodal fusion transformer that decomposes input modalities into different BERT instances with similar architectures, but variable weights.
Approach: They propose a multimodal fusion transformer with BERT encodings to solve Visual Question Answering (VQA) .
Outcome: The proposed method achieves SOTA results on the TVQA dataset and TVQA-Visual, an isolated diagnostic subset of TVQA, which strictly requires the knowledge of visual (V) modality based on a human annotator’s judgment.

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