Visual Question Answering (VQA)

Visual Question Answering (VQA) is a task in computer vision that involves answering questions about an image. 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

Papers

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Showing 1951–1975 of 2167 papers

Title	Date	Tasks	Status
Beyond Raw Videos: Understanding Edited Videos with Large Multimodal Model	Jun 15, 2024	Question AnsweringVideo Understanding	CodeCode Available
A Question-Centric Model for Visual Question Answering in Medical Imaging	Mar 2, 2020	Medical Image AnalysisQuestion Answering	CodeCode Available
Did the Model Understand the Question?	May 14, 2018	modelQuestion Answering	CodeCode Available
Dialog without Dialog Data: Learning Visual Dialog Agents from VQA Data	Jul 24, 2020	Visual DialogVisual Question Answering (VQA)	CodeCode Available
InstructOCR: Instruction Boosting Scene Text Spotting	Dec 20, 2024	Optical Character Recognition (OCR)Text Spotting	CodeCode Available
VinVL+L: Enriching Visual Representation with Location Context in VQA	Feb 22, 2023	Question AnsweringTAG	CodeCode Available
QACE: Asking Questions to Evaluate an Image Caption	Aug 28, 2021	Question AnsweringVisual Question Answering (VQA)	CodeCode Available
Inferring and Executing Programs for Visual Reasoning	May 10, 2017	Visual Question Answering (VQA)Visual Reasoning	CodeCode Available
Incorporating Probing Signals into Multimodal Machine Translation via Visual Question-Answering Pairs	Oct 26, 2023	AttributeMachine Translation	CodeCode Available
QAVA: Query-Agnostic Visual Attack to Large Vision-Language Models	Apr 15, 2025	Question AnsweringVisual Question Answering	CodeCode Available
Diagnosing and Mitigating Modality Interference in Multimodal Large Language Models	May 26, 2025	image-classificationImage Classification	CodeCode Available
Improving Zero-shot Visual Question Answering via Large Language Models with Reasoning Question Prompts	Nov 15, 2023	Question AnsweringSentence	CodeCode Available
Beyond Bilinear: Generalized Multimodal Factorized High-order Pooling for Visual Question Answering	Aug 10, 2017	Question AnsweringVisual Question Answering	CodeCode Available
QLEVR: A Diagnostic Dataset for Quantificational Language and Elementary Visual Reasoning	May 6, 2022	DiagnosticQuestion Answering	CodeCode Available
ViQuAE, a Dataset for Knowledge-based Visual Question Answering about Named Entities	Nov 16, 2021	ArticlesFace Recognition	CodeCode Available
Tips and Tricks for Visual Question Answering: Learnings from the 2017 Challenge	Aug 9, 2017	GPUVisual Question Answering	CodeCode Available
Beyond Accuracy: A Consolidated Tool for Visual Question Answering Benchmarking	Oct 11, 2021	BenchmarkingQuestion Answering	CodeCode Available
Quantifying and Alleviating the Language Prior Problem in Visual Question Answering	May 13, 2019	Information RetrievalQuestion Answering	CodeCode Available
Improving the Cross-Lingual Generalisation in Visual Question Answering	Sep 7, 2022	Cross-Lingual TransferQuestion Answering	CodeCode Available
Value-Spectrum: Quantifying Preferences of Vision-Language Models via Value Decomposition in Social Media Contexts	Nov 18, 2024	BenchmarkingMultimodal Large Language Model	CodeCode Available
Query and Attention Augmentation for Knowledge-Based Explainable Reasoning	Jan 1, 2022	Question AnsweringVisual Question Answering	CodeCode Available
VizWiz Grand Challenge: Answering Visual Questions from Blind People	Feb 22, 2018	Question AnsweringVisual Question Answering	CodeCode Available
Improved RAMEN: Towards Domain Generalization for Visual Question Answering	Sep 6, 2021	Domain GeneralizationQuestion Answering	CodeCode Available
Design as Desired: Utilizing Visual Question Answering for Multimodal Pre-training	Mar 30, 2024	Contrastive LearningQuestion Answering	CodeCode Available
VisFIS: Visual Feature Importance Supervision with Right-for-the-Right-Reason Objectives	Jun 22, 2022	Feature ImportanceQuestion Answering	CodeCode Available

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All datasets GQA Test2019 VQA v2 test-dev VQA v2 test-std OK-VQA MSVD-QA DocVQA test MSRVTT-QA InfographicVQA GQA test-dev VizWiz 2020 VQA A-OKVQA CLEVR

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	human	Accuracy	89.3	—	Unverified
2	DREAM+Unicoder-VL (MSRA)	Accuracy	76.04	—	Unverified
3	TRRNet (Ensemble)	Accuracy	74.03	—	Unverified
4	MIL-nbgao	Accuracy	73.81	—	Unverified
5	Kakao Brain	Accuracy	73.33	—	Unverified
6	Coarse-to-Fine Reasoning, Single Model	Accuracy	72.14	—	Unverified
7	270	Accuracy	70.23	—	Unverified
8	NSM ensemble (updated)	Accuracy	67.55	—	Unverified
9	VinVL-DPT	Accuracy	64.92	—	Unverified
10	VinVL+L	Accuracy	64.85	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	PaLI	Accuracy	84.3	—	Unverified
2	BEiT-3	Accuracy	84.19	—	Unverified
3	VLMo	Accuracy	82.78	—	Unverified
4	ONE-PEACE	Accuracy	82.6	—	Unverified
5	mPLUG (Huge)	Accuracy	82.43	—	Unverified
6	CuMo-7B	Accuracy	82.2	—	Unverified
7	X2-VLM (large)	Accuracy	81.9	—	Unverified
8	MMU	Accuracy	81.26	—	Unverified
9	Lyrics	Accuracy	81.2	—	Unverified
10	InternVL-C	Accuracy	81.2	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	BEiT-3	overall	84.03	—	Unverified
2	mPLUG-Huge	overall	83.62	—	Unverified
3	ONE-PEACE	overall	82.52	—	Unverified
4	X2-VLM (large)	overall	81.8	—	Unverified
5	VLMo	overall	81.3	—	Unverified
6	SimVLM	overall	80.34	—	Unverified
7	X2-VLM (base)	overall	80.2	—	Unverified
8	VAST	overall	80.19	—	Unverified
9	VALOR	overall	78.62	—	Unverified
10	Prompt Tuning	overall	78.53	—	Unverified