Before revision:  We present a method to train models with procedurally generated Q-A pairs from captions using techniques, such as templates and annotation frameworks like QASRL. As most VQA models rely on dense and costly object annotations extracted from object detectors, we propose spatial-pyramid image patches as a simple but effective alternative to object bounding boxes, and demonstrate that our method uses fewer human annotations .
After revision:  We present a method to train models with procedurally generated Q-A pairs generated procedurally from captions. Additionally, we demonstrate the efficacy of spatial-pyramid image patches as a simple but effective alternative to object bounding boxes, and demonstrate that our method uses fewer human annotations .