Task: Question Answering
Input (English): The question is encoded with a 1024-dimensional LSTM model that takes in a one-hot descriptor of each word in the question. The image is described with the 4096-dimensional output from the last fully connected layer of the Convolutional Neural Network (CNN), VGG16 BIBREF25 . The system performs an element-wise multiplication of the image and question features, after linearly transforming the image descriptor to 1024 dimensions. The final layer of the architecture is a softmax layer. 
 Question: What is the model architecture used?
Output (English): LSTM to encode the question, VGG16 to extract visual features. The outputs of LSTM and VGG16 are multiplied element-wise and sent to a softmax layer.