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# Visual Question Answering in Tensorflow
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[](https://gitter.im/neural-vqa-tensorflow/Lobby?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)
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This is a Tensorflow implementation of the VIS + LSTM visual question answering model from the paper [Exploring Models and Data for Image Question Answering][1]
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by Mengye Ren, Ryan Kiros & Richard Zemel. The model architectures vaires slightly from the original - the image embedding is plugged into the last lstm step (after the question) instead of the first. The LSTM model uses the same hyperparameters as those in the [Torch implementation of neural-VQA][2].
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