Visual Question Answering Dataset
VQA: Visual Question Answering
VQA is a new dataset containing open-ended questions about images. These questions require an understanding of vision, language and commonsense knowledge to ...
Visual Question Answering Dataset - Papers With Code
Visual Question Answering (VQA) is a dataset containing open-ended questions about images. These questions require an understanding of vision, language and ...
Visual Question Answering v2.0 Dataset - Papers With Code
Visual Question Answering (VQA) v2.0 is a dataset containing open-ended questions about images. These questions require an understanding of vision, ...
Visual Question Answering - Transformers - Hugging Face
Load the data. For illustration purposes, in this guide we use a very small sample of the annotated visual question answering Graphcore/vqa dataset. You ...
Exploring Visual Question Answering (VQA) Datasets - Comet.ml
This article provides a comprehensive exploration of Visual Question Answering (VQA) datasets, highlighting current challenges and proposing recommendations ...
Download - VQA: Visual Question Answering
The annotations we release are the result of the following post-processing steps on the raw crowdsourced data: ... Please follow the instructions in the README to ...
OK-VQA is a new dataset for visual question answering that requires methods which can draw upon outside knowledge to answer questions.
Robust Visual Question Answering: Datasets, Methods, and Future ...
Visual question answering requires a system to provide an accurate natural language answer given an image and a natural language question.
Visual Question Answering - VizWiz
For this purpose, we introduce the visual question answering (VQA) dataset coming from this population, which we call VizWiz-VQA. It originates from a natural ...
Datasets built on top of VQA - VQA: Visual Question Answering
The VQA-HAT dataset consists of ~60k attention annotations from humans of where they choose to look while answering questions about images, collected via a game ...
ViTextVQA: A Large-Scale Visual Question Answering Dataset for ...
We introduce the first large-scale dataset in Vietnamese specializing in the ability to understand text appearing in images, we call it ViTextVQA.
VisualQuestionAnswering - Kaggle
Visual Question Answering (VQA) is a novel problem domain where multi-modal inputs must be processed in order to solve the task given in the form of a natural ...
Introduction to Visual Question Answering: Datasets, Approaches ...
In this article I will briefly go through some of the current datasets, approaches and evaluation metrics in VQA, and on how this challenging task can be ...
Visual Question Answering Dataset for Bilingual Image Understanding
We have created a Japanese VQA dataset by using crowdsourced annotation with images from the Visual Genome dataset. This is the first such dataset in Japanese.
A dataset of clinically generated visual questions and answers about ...
We introduce VQA-RAD, a manually constructed VQA dataset in radiology where questions and answers about images are naturally created and ...
Visual question answering: A survey of methods and datasets
In the most common form of Visual Question Answering (VQA), the computer is presented with an image and a textual question about this image (see examples in Fig ...
yukezhu/visual7w-qa-models - GitHub
Visual7W is a large-scale visual question answering (QA) dataset, with object-level groundings and multimodal answers.
Introduction to Visual Question Answering in PyTorch | by Farooq Sk
Easy VQA is a dataset created by Victor Zhou, this dataset has simple images accompanied by questions and answers about each one of the images.
Debiased Visual Question Answering from Feature and Sample ...
Visual question answering ... However, recent observations show that many VQA models may only capture the biases between questions and answers in a dataset rather ...
What is Visual Question Answering? - Hugging Face
Visual Question Answering is the task of answering open-ended questions based on an image. They output natural language responses to natural language questions.