VQA (v2.0) stands for Visual Question Answering (v2.0), which is a manually annotated, open-ended question-answering dataset about images. To answer these questions, you need to have a certain understanding of images, language, and common sense. Example image: The dataset includes:

• 265,016 images (from COCO and abstract scenes datasets)
• The number of questions per image is greater than or equal to 3 (average 5.4 questions)
• Each question contains 10 ground truths
• Each question has 3 plausible (but not necessarily correct) answers
• Automatic evaluation metrics The VQA dataset was first released in October 2015, and VQA v2.0 was released in April 2017.**This dataset is version v2.0.**Compared to VQA v1.0, v2.0 supplements each question with images to minimize language bias.