Visual Question Answering (VQA) is a category of vision models to which you can ask a question about a model and retrieve a response.

VQA models can be used to reduce visual barriers for visually impaired individuals by allowing them to get information about images from the web and the ...

The goal of VQA is to teach machines to understand the content of an image and answer questions about it in natural language. Image Source: visualqa.org ...

Image retrieval: VQA models can be used to retrieve images with specific characteristics. For example, the user can ask “Is there a dog?” to find all images ...

VQA is a new dataset containing open-ended questions about images. These questions require an understanding of vision, language and commonsense knowledge to ... VQA v1 · VQA Challenge 2016 · VQA Challenge 2020 · VQA Challenge 2018

VQA is a state-of-the-art AI model that is much more than task-specific algorithms. Being an image-understanding model, VQA is going to be a major development ...

13 мар. 2024 г. · VQA is like training the computer to not only see the visual elements but also to understand and speak about them when prompted with questions.

8 апр. 2024 г. · Welcome to a quick guide into Visual Question Answering (VQA) models. In this post, we will explore the capabilities and limitations of an off-the-shelf VQA ...

Imagen for Captioning & VQA answers a question provided for a given image, even if it hasn't been seen before by the model. To explore this model in the console ...

The current state-of-the-art on VQA v2 test-std is BEiT-3. See a full comparison of 39 papers with code.