Ask Your Neurons:A Deep Learning Approach to Visual Question Answering
Table 10: Results on VQA validation set, “Question-only” model: Analysis of CNN questions encoders with different filter lengths, accuracy in %, see Section 6.2.1 for discussion.
['kernel length', 'single view', 'multi view']
encoder We first examine different hyper-parameters for CNNs to encode the question. We first consider the filter’s length of the convolutional kernel. We notice that increasing the kernel lengths improves performance up to length 3 were the performance levels out, we thus use kernel length 3 in the following experiments for, such CNN can be interpreted as a trigram model. We also tried to run simultaneously a few kernels with different lengths. However, we find that the best performance still achieve with a single view and kernel length 3 or 4.