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 1221–1230 of 2167 papers

Title	Date	Tasks	Status
Can You Explain That? Lucid Explanations Help Human-AI Collaborative Image Retrieval	Apr 5, 2019	Image RetrievalQuestion Answering	—Unverified
Lyrics: Boosting Fine-grained Language-Vision Alignment and Comprehension via Semantic-aware Visual Objects	Dec 8, 2023	Image Captioningobject-detection	—Unverified
M4CXR: Exploring Multi-task Potentials of Multi-modal Large Language Models for Chest X-ray Interpretation	Aug 29, 2024	Instruction FollowingMedical Report Generation	—Unverified
MAGIC-VQA: Multimodal And Grounded Inference with Commonsense Knowledge for Visual Question Answering	Mar 24, 2025	Graph Neural NetworkQuestion Answering	—Unverified
Making the V in Text-VQA Matter	Aug 1, 2023	Optical Character Recognition (OCR)TextVQA	—Unverified
Making Video Quality Assessment Models Sensitive to Frame Rate Distortions	May 21, 2022	Video Quality AssessmentVisual Question Answering (VQA)	—Unverified
Making Video Quality Assessment Models Robust to Bit Depth	Apr 25, 2023	Video Quality AssessmentVisual Question Answering (VQA)	—Unverified
MAMO: Masked Multimodal Modeling for Fine-Grained Vision-Language Representation Learning	Oct 9, 2022	Image-text Retrievalmultimodal interaction	—Unverified
MANGO: Enhancing the Robustness of VQA Models via Adversarial Noise Generation	Jan 16, 2022	Logical ReasoningQuestion Answering	—Unverified
Mask4Align: Aligned Entity Prompting with Color Masks for Multi-Entity Localization Problems	Jan 1, 2024	Question AnsweringVisual Question Answering	—Unverified

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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