Attention on Attention: Architectures for Visual Question Answering (VQA)
Autor: | Singh, Jasdeep, Ying, Vincent, Nutkiewicz, Alex |
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Rok vydání: | 2018 |
Předmět: | |
Druh dokumentu: | Working Paper |
Popis: | Visual Question Answering (VQA) is an increasingly popular topic in deep learning research, requiring coordination of natural language processing and computer vision modules into a single architecture. We build upon the model which placed first in the VQA Challenge by developing thirteen new attention mechanisms and introducing a simplified classifier. We performed 300 GPU hours of extensive hyperparameter and architecture searches and were able to achieve an evaluation score of 64.78%, outperforming the existing state-of-the-art single model's validation score of 63.15%. Comment: Visual Question Answering Project |
Databáze: | arXiv |
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