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Visual Question Answering (VQA) datasets
archive 2025-07-28144 datasets carry the task tag "Visual Question Answering (VQA)" (the task itself: Visual Question Answering (VQA)), ordered by the archive's paper count. Page 1 of 3: 48 shown of 144. Facet routes are this site's own (the archive records the tag string, not a page).
The archive holds 12,214 dataset rows; 12,172 are listed. 6 are withheld from every listing and count here as vandalised before snapshot (6 with contact-centre spam in the title, 0 with a spam description on a row that has no homepage, no paper and no papers counted; none with more than 1 paper, 0 with a benchmark), listed in withheld.json; 1 listed row carries a vandalised description, withheld on its page. This gate never withholds a row with a homepage or a paper that resolves, and a clean description; the content rules below withhold a row whose name is spam whatever else it carries. The gate is a phrase list: these are the rows it caught, not a claim that the rest is clean. Before that gate, the site's content rules withhold 36 more rows (invite-code, gambling, travel-booking, contact-centre and similar spam in the name or on a row with nothing real behind it); they have no page and are listed in withheld.json.
Filter 50 task tags shown of 3,717, by dataset count; the full filter by modality, task and language is on /datasets
All 12,172
Question Answering 413Semantic Segmentation 347Object Detection 332Image Classification 283Classification 222Text Classification 167Language Modelling 166Text Generation 162Visual Question Answering (VQA) 144Named Entity Recognition (NER) 130Pose Estimation 124Anomaly Detection 119Action Recognition 115Instance Segmentation 111Sentiment Analysis 104Text Summarization 98Domain Adaptation 96Speech Recognition 96Reading Comprehension 95Information Retrieval 932D Object Detection 92Image Retrieval 87Machine Translation 82Relation Extraction 822D Semantic Segmentation 81Natural Language Inference 81Image Captioning 79Image Generation 79Depth Estimation 77Node Classification 75Natural Language Understanding 72Autonomous Driving 70Code Generation 70Object Tracking 693D Object Detection 67Face Recognition 67Link Prediction 67Person Re-Identification 65Data Augmentation 63Multi-Task Learning 593D Reconstruction 58Common Sense Reasoning 56Recommendation Systems 56Video Understanding 56Optical Character Recognition (OCR) 55Graph Classification 54Abstractive Text Summarization 52Emotion Recognition 52Medical Image Segmentation 52Word Embeddings 52
Visual Question Answering (VQA) datasets 1–48 of 144
The ImageNet dataset contains 14,197,122 annotated images according to the WordNet hierarchy.
15,430 papers · 52 benchmarks
The COCO (Common Objects in Context) dataset is a large-scale object detection, segmentation, and captioning dataset.
11,922 papers · 77 benchmarks
Visual Genome contains Visual Question Answering data in a multi-choice setting.
1,256 papers · 15 benchmarks
The ActivityNet dataset contains 200 different types of activities and a total of 849 hours of videos collected from YouTube.
807 papers · 17 benchmarks
The GQA dataset is a large-scale visual question answering dataset with real images from the Visual Genome dataset and balanced question-answer pairs.
749 papers · 8 benchmarks
CLEVR (Compositional Language and Elementary Visual Reasoning)
CLEVR (Compositional Language and Elementary Visual Reasoning) is a synthetic Visual Question Answering dataset.
657 papers · 3 benchmarks
TextVQA is a dataset to benchmark visual reasoning based on text in images.
476 papers · 3 benchmarks
OK-VQA (Outside Knowledge Visual Question Answering)
Outside Knowledge Visual Question Answering (OK-VQA) includes more than 14,000 questions that require external knowledge to answer.
368 papers · 2 benchmarks
Visual Question Answering v2.0 (VQA v2.0)
Visual Question Answering (VQA) v2.0 is a dataset containing open-ended questions about images.
366 papers · 7 benchmarks
Automatic image captioning is the task of producing a natural-language utterance (usually a sentence) that correctly reflects the visual content of an image.
352 papers · 2 benchmarks
MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities
339 papers · 2 benchmarks
ScienceQA (Science Question Answering)
Science Question Answering (ScienceQA) is a new benchmark that consists of 21,208 multimodal multiple choice questions with diverse science topics and annotations of their answers with corresponding lectures and explanations.
339 papers · 1 benchmark
DocVQA consists of 50,000 questions defined on 12,000+ document images.
290 papers · 3 benchmarks
VizWiz (VizWiz-VQA)
The VizWiz-VQA dataset originates from a natural visual question answering setting where blind people each took an image and recorded a spoken question about it, together with 10 crowdsourced answers per visual question.
260 papers · 7 benchmarks
MathVista (Mathematical Reasoning of in Visual Contexts)
MathVista is a consolidated Mathematical reasoning benchmark within Visual contexts.
242 papers · 0 benchmarks
AI2D (AI2 Diagrams)
AI2 Diagrams (AI2D) is a dataset of over 5000 grade school science diagrams with over 150000 rich annotations, their ground truth syntactic parses, and more than 15000 corresponding multiple choice questions.
207 papers · 1 benchmark
VCR (Visual Commonsense Reasoning)
Visual Commonsense Reasoning (VCR) is a large-scale dataset for cognition-level visual understanding.
179 papers · 13 benchmarks
VisDial (Visual Dialog)
Visual Dialog (VisDial) dataset contains human annotated questions based on images of MS COCO dataset.
159 papers · 6 benchmarks
A-OKVQA is crowdsourced visual question answering dataset composed of a diverse set of about 25K questions requiring a broad base of commonsense and world knowledge to answer.
154 papers · 1 benchmark
The ActivityNet-QA dataset contains 58,000 human-annotated QA pairs on 5,800 videos derived from the popular ActivityNet dataset.
146 papers · 2 benchmarks
MVBench is a comprehensive Multi-modal Video understanding Benchmark.
139 papers · 3 benchmarks
SHAPES (Swarm Heuristics based Adaptive and Penalized Estimation of Splines)
SHAPES is a dataset of synthetic images designed to benchmark systems for understanding of spatial and logical relations among multiple objects.
120 papers · 1 benchmark
Visual Entailment (VE) consists of image-sentence pairs whereby a premise is defined by an image, rather than a natural language sentence as in traditional Textual Entailment tasks.
117 papers · 2 benchmarks
EgoSchema is very long-form video question-answering dataset, and benchmark to evaluate long video understanding capabilities of modern vision and language systems.
112 papers · 3 benchmarks
Visual7W is a large-scale visual question answering (QA) dataset, with object-level groundings and multimodal answers.
112 papers · 1 benchmark
The TGIF-QA dataset contains 165K QA pairs for the animated GIFs from the TGIF dataset [Li et al.
92 papers · 3 benchmarks
ST-VQA (Scene Text Visual Question Answering)
ST-VQA aims to highlight the importance of exploiting high-level semantic information present in images as textual cues in the VQA process.
90 papers · 0 benchmarks
PathVQA consists of 32,799 open-ended questions from 4,998 pathology images where each question is manually checked to ensure correctness.
89 papers · 0 benchmarks
The ReferIt dataset contains 130,525 expressions for referring to 96,654 objects in 19,894 images of natural scenes.
80 papers · 0 benchmarks
VQG (Visual Question Generation)
VQG is a collection of datasets for visual question generation.
80 papers · 1 benchmark
The MSR-VTT-QA dataset is a benchmark for the task of Visual Question Answering (VQA) on the MSR-VTT (Microsoft Research Video to Text) dataset.
66 papers · 5 benchmarks
COCO-QA is a dataset for visual question answering.
62 papers · 0 benchmarks
FigureQA is a visual reasoning corpus of over one million question-answer pairs grounded in over 100,000 images.
61 papers · 1 benchmark
The MSVD-QA dataset is a Video Question Answering (VideoQA) dataset.
61 papers · 5 benchmarks
TVQA+ contains 310.8K bounding boxes, linking depicted objects to visual concepts in questions and answers.
60 papers · 0 benchmarks
PMC-VQA is a large-scale medical visual question-answering dataset that contains 227k VQA pairs of 149k images that cover various modalities or diseases.
55 papers · 2 benchmarks
DAQUAR (DAtaset for QUestion Answering on Real-world images) is a dataset of human question answer pairs about images.
54 papers · 0 benchmarks
Large language models (LLMs), after being aligned with vision models and integrated into vision-language models (VLMs), can bring impressive improvement in image reasoning tasks.
53 papers · 1 benchmark
InfographicVQA is a dataset that comprises a diverse collection of infographics along with natural language questions and answers annotations.
52 papers · 1 benchmark
The large-scale MUSIC-AVQA dataset of musical performance contains 45,867 question-answer pairs, distributed in 9,288 videos for over 150 hours.
51 papers · 1 benchmark
PlotQA is a VQA dataset with 28.9 million question-answer pairs grounded over 224,377 plots on data from real-world sources and questions based on crowd-sourced question templates.
50 papers · 5 benchmarks
DVQA (Data Visualizations via Question Answering)
DVQA is a synthetic question-answering dataset on images of bar-charts.
49 papers · 1 benchmark
TQA (Textbook Question Answering)
The TextbookQuestionAnswering (TQA) dataset is drawn from middle school science curricula.
48 papers · 1 benchmark
WebQA, is a new benchmark for multimodal multihop reasoning in which systems are presented with the same style of data as humans when searching the web: Snippets and Images.
43 papers · 0 benchmarks
IconQA (Icon Question Answering)
Current visual question answering (VQA) tasks mainly consider answering human-annotated questions for natural images in the daily-life context.
42 papers · 1 benchmark
TDIUC (Task Directed Image Understanding Challenge)
Task Directed Image Understanding Challenge (TDIUC) dataset is a Visual Question Answering dataset which consists of 1.6M questions and 170K images sourced from MS COCO and the Visual Genome Dataset.
39 papers · 1 benchmark
CV-Bench (Cambrian Vision-Centric Benchmark)
The Cambrian Vision-Centric Benchmark (CV-Bench) is designed to address the limitations of existing vision-centric benchmarks by providing a comprehensive evaluation framework for multimodal large language models (MLLMs).
37 papers · 0 benchmarks
InfoSeek (Visual Information Seeking)
In this project, we introduce InfoSeek, a visual question answering dataset tailored for information-seeking questions that cannot be answered with only common sense knowledge.
36 papers · 2 benchmarks
Paper counts and descriptions are the archive's, frozen 2025-07-28; no citation counts, no stars, no trending. Sorting by "most cited" or "newest" was a live-site feature the archive does not carry.