Exploring Models and Data for Image Question Answering
Table 1: COCO-QA question type break-down
['Category Object', 'Train 54992', '% 69.84%', 'Test 27206', '% 69.85%']
It should be noted that since we applied the QA pair rejection process, mode-guessing performs very poorly on COCO-QA. However, COCO-QA questions are actually easier to answer than DAQUAR from a human point of view. This encourages the model to exploit salient object relations instead of exhaustively searching all possible relations. COCO-QA dataset can be downloaded at http://www.cs.toronto.edu/~mren/imageqa/data/cocoqa