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 901–925 of 2167 papers

Title	Date	Tasks	Status	Score
MIRTT: Learning Multimodal Interaction Representations from Trilinear Transformers for Visual Question Answering	Nov 1, 2021	multimodal interactionMultiple-choice	CodeCode Available	5
Are Red Roses Red? Evaluating Consistency of Question-Answering Models	Jul 1, 2019	Question Answeringvalid	CodeCode Available	5
MHSAN: Multi-Head Self-Attention Network for Visual Semantic Embedding	Jan 11, 2020	Image CaptioningImage-text Retrieval	CodeCode Available	5
Mimic and Fool: A Task Agnostic Adversarial Attack	Jun 11, 2019	Adversarial AttackImage Captioning	CodeCode Available	5
Is Multimodal Vision Supervision Beneficial to Language?	Feb 10, 2023	Image RetrievalNatural Language Understanding	CodeCode Available	5
Med-PMC: Medical Personalized Multi-modal Consultation with a Proactive Ask-First-Observe-Next Paradigm	Aug 16, 2024	Decision MakingMedical Visual Question Answering	CodeCode Available	5
Benchmarking Multi-dimensional AIGC Video Quality Assessment: A Dataset and Unified Model	Jul 31, 2024	BenchmarkingLarge Language Model	CodeCode Available	5
Medical Large Vision Language Models with Multi-Image Visual Ability	May 25, 2025	Question AnsweringVisual Question Answering (VQA)	CodeCode Available	5
Towards a Unified Multimodal Reasoning Framework	Dec 22, 2023	Multimodal ReasoningMultiple-choice	CodeCode Available	5
MedHallTune: An Instruction-Tuning Benchmark for Mitigating Medical Hallucination in Vision-Language Models	Feb 28, 2025	Decision MakingHallucination	CodeCode Available	5
Explainable and Explicit Visual Reasoning over Scene Graphs	Dec 5, 2018	Inductive BiasVisual Question Answering (VQA)	CodeCode Available	5
CAST: Cross-modal Alignment Similarity Test for Vision Language Models	Sep 17, 2024	cross-modal alignmentQuestion Answering	CodeCode Available	5
Cascaded Mutual Modulation for Visual Reasoning	Sep 6, 2018	Question AnsweringVisual Question Answering	CodeCode Available	5
Measuring Faithful and Plausible Visual Grounding in VQA	May 24, 2023	Question AnsweringVisual Grounding	CodeCode Available	5
ActionCOMET: A Zero-shot Approach to Learn Image-specific Commonsense Concepts about Actions	Oct 17, 2024	Visual Question Answering (VQA)	CodeCode Available	5
CARETS: A Consistency And Robustness Evaluative Test Suite for VQA	Mar 15, 2022	NegationQuestion Generation	CodeCode Available	5
Towards Knowledge-Augmented Visual Question Answering	Dec 1, 2020	General KnowledgeGraph Attention	CodeCode Available	5
Marten: Visual Question Answering with Mask Generation for Multi-modal Document Understanding	Mar 18, 2025	document understandingQuestion Answering	CodeCode Available	5
μ-Bench: A Vision-Language Benchmark for Microscopy Understanding	Jul 1, 2024	Cell DetectionClassification	CodeCode Available	5
A Question-Centric Model for Visual Question Answering in Medical Imaging	Mar 2, 2020	Medical Image AnalysisQuestion Answering	CodeCode Available	5
Applying recent advances in Visual Question Answering to Record Linkage	Jul 12, 2020	Question AnsweringVisual Question Answering	CodeCode Available	5
MaMMUT: A Simple Architecture for Joint Learning for MultiModal Tasks	Mar 29, 2023	Cross-Modal RetrievalDecoder	CodeCode Available	5
ERVQA: A Dataset to Benchmark the Readiness of Large Vision Language Models in Hospital Environments	Oct 8, 2024	DecoderQuestion Answering	CodeCode Available	5
Knowing Earlier what Right Means to You: A Comprehensive VQA Dataset for Grounding Relative Directions via Multi-Task Learning	Jul 6, 2022	DiagnosticMulti-Task Learning	CodeCode Available	5
Making the V in VQA Matter: Elevating the Role of Image Understanding in Visual Question Answering	Dec 2, 2016	Visual Question AnsweringVisual Question Answering (VQA)	CodeCode Available	5

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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