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Register a new userDiversity and Consistency: Exploring Visual Question-Answer Pair Generation
التنوع والاتساق: استكشاف جيل زوج الإجابة السؤال المرئي
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على الرغم من إظهار قيم واعدة للتطبيقات المصب، فإن توليد السؤال والإجابة معا يتم استكشافها. في هذه الورقة، نقدم مهمة جديدة تستهدف توليد زوج الإجابة على الأسئلة من الصور المرئية. لا يتطلب عدم توليد أزواج حول الإجابات المتنوعة فقط ولكن أيضا الحفاظ على الاتساق منهم. نحن ندرس نماذج جيل مختلفة لهذه المهمة واقتراح ثلاث نماذج: نموذج خط الأنابيب، النموذج المشترك، النموذج المتسلسل. نحن ندمج الاستدلال الاختلافي في هذه النماذج لتحقيق التنوع والاتساق. ونحن نقترح أيضا تقدير تمثيل المنطقة ومحاذاة الاهتمام لتحسين الاتساق أكثر. ونحن أخيرا وضع مقيم كقيط كمي للاتساق. نحن نقوم بالتحقق من نهجنا على معيارين، VQA2.0 و Visual-7W، من خلال تقييم التنوع والاتساق يدويا يدويا. تظهر النتائج التجريبية فعالية نماذجنا: يمكن أن تولد أزواج متنوعة أو متسقة. علاوة على ذلك، يمكن استخدام هذه المهمة لتحسين جيل السؤال المرئي والإجابة على السؤال المرئي.
Although showing promising values to downstream applications, generating question and answer together is under-explored. In this paper, we introduce a novel task that targets question-answer pair generation from visual images. It requires not only generating diverse question-answer pairs but also keeping the consistency of them. We study different generation paradigms for this task and propose three models: the pipeline model, the joint model, and the sequential model. We integrate variational inference into these models to achieve diversity and consistency. We also propose region representation scaling and attention alignment to improve the consistency further. We finally devise an evaluator as a quantitative metric for consistency. We validate our approach on two benchmarks, VQA2.0 and Visual-7w, by automatically and manually evaluating diversity and consistency. Experimental results show the effectiveness of our models: they can generate diverse or consistent pairs. Moreover, this task can be used to improve visual question generation and visual question answering.
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