Vision
Visual question answering (VQA)
Visual question answering (VQA) is a multidisciplinary AI task that involves answering questions about images. A VQA system takes an image and a natural language question as input and generates a natural language answer.
Explanation
VQA combines computer vision and natural language processing techniques. A typical VQA system uses a CNN (Convolutional Neural Network) to extract visual features from the image, and an NLP model (e.g., an LSTM or a Transformer) to encode the question. The extracted visual features and the encoded question are then fused, often using attention mechanisms, to predict the answer. VQA is important because it requires a deeper understanding of both the visual content and the question being asked, going beyond simple object recognition. It pushes AI systems toward more human-like reasoning and comprehension capabilities.