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 276–300 of 2167 papers

Title	Date	Tasks	Status	Hype	Score
Instruction-Guided Visual Masking	May 30, 2024	Instruction FollowingVisual Grounding	CodeCode Available	1	5
Declaration-based Prompt Tuning for Visual Question Answering	May 5, 2022	Image-text matchingLanguage Modeling	CodeCode Available	1	5
AIGV-Assessor: Benchmarking and Evaluating the Perceptual Quality of Text-to-Video Generation with LMM	Nov 26, 2024	BenchmarkingText-to-Video Generation	CodeCode Available	1	5
ActiView: Evaluating Active Perception Ability for Multimodal Large Language Models	Oct 7, 2024	Question AnsweringVisual Question Answering	CodeCode Available	1	5
AI2-THOR: An Interactive 3D Environment for Visual AI	Dec 14, 2017	Deep Reinforcement LearningImitation Learning	CodeCode Available	1	5
Debiasing Multimodal Models via Causal Information Minimization	Nov 28, 2023	Visual Question Answering (VQA)	CodeCode Available	1	5
Hypergraph Transformer: Weakly-supervised Multi-hop Reasoning for Knowledge-based Visual Question Answering	Apr 22, 2022	Question AnsweringVisual Question Answering	CodeCode Available	1	5
Does Vision-and-Language Pretraining Improve Lexical Grounding?	Sep 21, 2021	Question AnsweringVisual Question Answering	CodeCode Available	1	5
Detecting and Preventing Hallucinations in Large Vision Language Models	Aug 11, 2023	16kHallucination	CodeCode Available	1	5
Debiased Visual Question Answering from Feature and Sample Perspectives	Dec 1, 2021	Bias DetectionQuestion Answering	CodeCode Available	1	5
DataEnvGym: Data Generation Agents in Teacher Environments with Student Feedback	Oct 8, 2024	MathSequential Decision Making	CodeCode Available	1	5
Decoupled Seg Tokens Make Stronger Reasoning Video Segmenter and Grounder	Jun 28, 2025	Image SegmentationLarge Language Model	CodeCode Available	1	5
HYDRA: A Hyper Agent for Dynamic Compositional Visual Reasoning	Mar 19, 2024	Reinforcement Learning (RL)Visual Grounding	CodeCode Available	1	5
I Can't Believe There's No Images! Learning Visual Tasks Using only Language Supervision	Nov 17, 2022	Image CaptioningQuestion Answering	CodeCode Available	1	5
Inter-GPS: Interpretable Geometry Problem Solving with Formal Language and Symbolic Reasoning	May 10, 2021	Arithmetic ReasoningGeometry Problem Solving	CodeCode Available	1	5
Language Prior Is Not the Only Shortcut: A Benchmark for Shortcut Learning in VQA	Oct 10, 2022	Question AnsweringVisual Question Answering	CodeCode Available	1	5
Cross-modal Retrieval for Knowledge-based Visual Question Answering	Jan 11, 2024	Cross-Modal RetrievalQuestion Answering	CodeCode Available	1	5
A Hitchhikers Guide to Fine-Grained Face Forgery Detection Using Common Sense Reasoning	Oct 1, 2024	Common Sense ReasoningDeepFake Detection	CodeCode Available	1	5
Hierarchical multimodal transformers for Multi-Page DocVQA	Dec 7, 2022	DecoderQuestion Answering	CodeCode Available	1	5
Cross-Modality Relevance for Reasoning on Language and Vision	May 12, 2020	Question AnsweringVisual Question Answering	CodeCode Available	1	5
Hierarchical Conditional Relation Networks for Video Question Answering	Feb 25, 2020	Audio-Visual Question Answering (AVQA)Question Answering	CodeCode Available	1	5
Hierarchical Question-Image Co-Attention for Visual Question Answering	May 31, 2016	Visual DialogVisual Question Answering	CodeCode Available	1	5
A Good Prompt Is Worth Millions of Parameters: Low-resource Prompt-based Learning for Vision-Language Models	Oct 16, 2021	Image CaptioningLanguage Modeling	CodeCode Available	1	5
Are Vision Language Models Ready for Clinical Diagnosis? A 3D Medical Benchmark for Tumor-centric Visual Question Answering	May 25, 2025	AnatomyBenchmarking	CodeCode Available	1	5
Harnessing the Power of Multi-Task Pretraining for Ground-Truth Level Natural Language Explanations	Dec 8, 2022	Explanation GenerationVisual Entailment	CodeCode Available	1	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