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

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 526–550 of 2167 papers

Title	Date	Tasks	Status	Hype	Score
MMFT-BERT: Multimodal Fusion Transformer with BERT Encodings for Visual Question Answering	Oct 27, 2020	DiagnosticQuestion Answering	CodeCode Available	1	5
Are Bias Mitigation Techniques for Deep Learning Effective?	Apr 1, 2021	Deep LearningQuestion Answering	CodeCode Available	1	5
MMNeuron: Discovering Neuron-Level Domain-Specific Interpretation in Multimodal Large Language Model	Jun 17, 2024	Language ModelingLanguage Modelling	CodeCode Available	1	5
Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering	Jul 25, 2017	Image CaptioningVisual Question Answering	CodeCode Available	1	5
Evaluating Multimodal Representations on Visual Semantic Textual Similarity	Apr 4, 2020	BenchmarkingImage Captioning	CodeCode Available	1	5
DualVGR: A Dual-Visual Graph Reasoning Unit for Video Question Answering	Jul 10, 2021	Graph AttentionQuestion Answering	CodeCode Available	1	5
Break It Down: A Question Understanding Benchmark	Jan 31, 2020	Open-Domain Question AnsweringQuestion Answering	CodeCode Available	1	5
Expert Knowledge-Aware Image Difference Graph Representation Learning for Difference-Aware Medical Visual Question Answering	Jul 22, 2023	Graph Representation LearningLanguage Modeling	CodeCode Available	1	5
MLP Architectures for Vision-and-Language Modeling: An Empirical Study	Dec 8, 2021	Language ModelingLanguage Modelling	CodeCode Available	1	5
MixPHM: Redundancy-Aware Parameter-Efficient Tuning for Low-Resource Visual Question Answering	Mar 2, 2023	Mixture-of-ExpertsQuestion Answering	CodeCode Available	1	5
MMBERT: Multimodal BERT Pretraining for Improved Medical VQA	Apr 3, 2021	Language ModelingLanguage Modelling	CodeCode Available	1	5
Exploring Opinion-unaware Video Quality Assessment with Semantic Affinity Criterion	Feb 26, 2023	Video Quality AssessmentVisual Question Answering (VQA)	CodeCode Available	1	5
Boosting the Power of Small Multimodal Reasoning Models to Match Larger Models with Self-Consistency Training	Nov 23, 2023	Multimodal ReasoningScience Question Answering	CodeCode Available	1	5
Bridging the Gap between 2D and 3D Visual Question Answering: A Fusion Approach for 3D VQA	Feb 24, 2024	3D Question Answering (3D-QA)Question Answering	CodeCode Available	1	5
Faithful Multimodal Explanation for Visual Question Answering	Sep 8, 2018	Explanatory Visual Question AnsweringQuestion Answering	CodeCode Available	1	5
Dual-Key Multimodal Backdoors for Visual Question Answering	Dec 14, 2021	Question AnsweringVisual Question Answering	CodeCode Available	1	5
FaceBench: A Multi-View Multi-Level Facial Attribute VQA Dataset for Benchmarking Face Perception MLLMs	Mar 27, 2025	AttributeBenchmarking	CodeCode Available	1	5
Efficient Vision-Language Pretraining with Visual Concepts and Hierarchical Alignment	Aug 29, 2022	cross-modal alignmentImage-text Retrieval	CodeCode Available	1	5
EHRXQA: A Multi-Modal Question Answering Dataset for Electronic Health Records with Chest X-ray Images	Oct 28, 2023	Decision MakingMedical Visual Question Answering	CodeCode Available	1	5
FloodNet: A High Resolution Aerial Imagery Dataset for Post Flood Scene Understanding	Dec 5, 2020	image-classificationImage Classification	CodeCode Available	1	5
FFAA: Multimodal Large Language Model based Explainable Open-World Face Forgery Analysis Assistant	Aug 19, 2024	DescriptiveFace Swapping	CodeCode Available	1	5
FiLM: Visual Reasoning with a General Conditioning Layer	Sep 22, 2017	Image Retrieval with Multi-Modal QueryVisual Question Answering (VQA)	CodeCode Available	1	5
End-to-end Knowledge Retrieval with Multi-modal Queries	Jun 1, 2023	BenchmarkingCross-Modal Retrieval	CodeCode Available	1	5
HIDRO-VQA: High Dynamic Range Oracle for Video Quality Assessment	Nov 18, 2023	Video Quality AssessmentVisual Question Answering (VQA)	CodeCode Available	1	5
End-to-end Document Recognition and Understanding with Dessurt	Mar 30, 2022	document understandingVisual Question Answering (VQA)	CodeCode Available	1	5

Show:10 25 50

← PrevPage 22 of 87Next →

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