MemexQA: Visual Memex Question Answering
Table 1: Comparison with the representative VQA and Visual7W dataset.
['Dataset', '#Img', 'AvgQLen', 'AvgALen', 'FlickrOR', 'CrossImgs', 'Evidence', 'GPS/Meta']
MemexQA is a real-world QA dataset that requires multimodal reasoning based on both vision and language. It compliments existing VQA datasets by allowing users to ask multimodal questions over a collection of photos. As we see, the MemexQA dataset encompasses the most comprehensive information including evidential photos, Time GPS, and metadata. More importantly, it is the only effort that has questions grounded on multiple images. MemexQA is a realistic dataset. It comprises personal photos of 101 real users and 20k faithful questions that users asked to recall their memories. We found that the statistics about MemexQA are closer to the statistics about Flickr photos, from which VQA and Visual7W datasets are crawled. As we see, MemexQA’s ratio is 6% higher than others, which suggests its answers are closer to user interests. Similarly, the question category distribution of MemexQA also seems more realistic (see supplementary materials).