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 626–650 of 2167 papers

Title	Date	Tasks	Status	Score
Did the Model Understand the Question?	May 14, 2018	modelQuestion Answering	CodeCode Available	5
Dialog without Dialog Data: Learning Visual Dialog Agents from VQA Data	Jul 24, 2020	Visual DialogVisual Question Answering (VQA)	CodeCode Available	5
Diagnosing and Mitigating Modality Interference in Multimodal Large Language Models	May 26, 2025	image-classificationImage Classification	CodeCode Available	5
Beyond Bilinear: Generalized Multimodal Factorized High-order Pooling for Visual Question Answering	Aug 10, 2017	Question AnsweringVisual Question Answering	CodeCode Available	5
Beyond Accuracy: A Consolidated Tool for Visual Question Answering Benchmarking	Oct 11, 2021	BenchmarkingQuestion Answering	CodeCode Available	5
BERTHop: An Effective Vision-and-Language Model for Chest X-ray Disease Diagnosis	Aug 10, 2021	Language ModelingLanguage Modelling	CodeCode Available	5
Design as Desired: Utilizing Visual Question Answering for Multimodal Pre-training	Mar 30, 2024	Contrastive LearningQuestion Answering	CodeCode Available	5
NAAQA: A Neural Architecture for Acoustic Question Answering	Jun 11, 2021	Acoustic Question AnsweringQuestion Answering	CodeCode Available	5
Navigating Cultural Chasms: Exploring and Unlocking the Cultural POV of Text-To-Image Models	Oct 3, 2023	Image GenerationVisual Question Answering (VQA)	CodeCode Available	5
NeSyCoCo: A Neuro-Symbolic Concept Composer for Compositional Generalization	Dec 20, 2024	Compositional Generalization (AVG)Novel Concepts	CodeCode Available	5
A Dual-Attention Learning Network with Word and Sentence Embedding for Medical Visual Question Answering	Oct 1, 2022	Medical Visual Question AnsweringQuestion Answering	CodeCode Available	5
Multiview Contrastive Learning for Completely Blind Video Quality Assessment of User Generated Content	Jul 13, 2022	Contrastive LearningOptical Flow Estimation	CodeCode Available	5
Delving Deeper into Cross-lingual Visual Question Answering	Feb 15, 2022	Inductive BiasQuestion Answering	CodeCode Available	5
Multi-Target Embodied Question Answering	Apr 9, 2019	Embodied Question AnsweringNavigate	CodeCode Available	5
MUREL: Multimodal Relational Reasoning for Visual Question Answering	Feb 25, 2019	Relational ReasoningVisual Question Answering	CodeCode Available	5
Multiscale Byte Language Models -- A Hierarchical Architecture for Causal Million-Length Sequence Modeling	Feb 20, 2025	DecoderGPU	CodeCode Available	5
Deep Modular Co-Attention Networks for Visual Question Answering	Jun 25, 2019	Question AnsweringVisual Question Answering	CodeCode Available	5
Multi-Sourced Compositional Generalization in Visual Question Answering	May 29, 2025	Question AnsweringVisual Question Answering	CodeCode Available	5
MUTAN: Multimodal Tucker Fusion for Visual Question Answering	May 18, 2017	Visual Question AnsweringVisual Question Answering (VQA)	CodeCode Available	5
Multimodal Residual Learning for Visual QA	Jun 5, 2016	Multiple-choiceQuestion 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
Multi-Page Document Visual Question Answering using Self-Attention Scoring Mechanism	Apr 29, 2024	document understandingGPU	CodeCode Available	5
Multimodal Hypothetical Summary for Retrieval-based Multi-image Question Answering	Dec 19, 2024	Contrastive LearningLanguage Modeling	CodeCode Available	5
Multiple interaction learning with question-type prior knowledge for constraining answer search space in visual question answering	Sep 23, 2020	Question AnsweringVisual Question Answering	CodeCode Available	5
No Images, No Problem: Retaining Knowledge in Continual VQA with Questions-Only Memory	Feb 6, 2025	Continual LearningQuestion Answering	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	InternVL-C	Accuracy	81.2	—	Unverified
10	Lyrics	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