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 326–350 of 2167 papers

Title	Date	Tasks	Status	Hype	Score
KVQ: Boosting Video Quality Assessment via Saliency-guided Local Perception	Mar 13, 2025	Video Quality AssessmentVisual Question Answering (VQA)	CodeCode Available	1	5
KAT: A Knowledge Augmented Transformer for Vision-and-Language	Dec 16, 2021	Answer GenerationDecoder	CodeCode Available	1	5
CLEVR-Math: A Dataset for Compositional Language, Visual and Mathematical Reasoning	Aug 10, 2022	MathMathematical Reasoning	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
Light-VQA: A Multi-Dimensional Quality Assessment Model for Low-Light Video Enhancement	May 16, 2023	Video EnhancementVideo Quality Assessment	CodeCode Available	1	5
Deep Multimodal Neural Architecture Search	Apr 25, 2020	DecoderImage-text matching	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
Knowledge-Based Video Question Answering with Unsupervised Scene Descriptions	Jul 17, 2020	Question AnsweringVideo Question Answering	CodeCode Available	1	5
JDocQA: Japanese Document Question Answering Dataset for Generative Language Models	Mar 28, 2024	HallucinationQuestion Answering	CodeCode Available	1	5
DeVLBert: Learning Deconfounded Visio-Linguistic Representations	Aug 16, 2020	Image RetrievalQuestion Answering	CodeCode Available	1	5
Just Ask: Learning to Answer Questions from Millions of Narrated Videos	Dec 1, 2020	Question AnsweringQuestion Generation	CodeCode Available	1	5
Knowledge-Routed Visual Question Reasoning: Challenges for Deep Representation Embedding	Dec 14, 2020	Question AnsweringVisual Question Answering	CodeCode Available	1	5
Declaration-based Prompt Tuning for Visual Question Answering	May 5, 2022	Image-text matchingLanguage Modeling	CodeCode Available	1	5
InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks	Dec 21, 2023	Image RetrievalImage-to-Text Retrieval	CodeCode Available	1	5
Clover: Towards A Unified Video-Language Alignment and Fusion Model	Jul 16, 2022	Language ModelingLanguage Modelling	CodeCode Available	1	5
Coarse-to-Fine Reasoning for Visual Question Answering	Oct 6, 2021	Question AnsweringVisual Question Answering	CodeCode Available	1	5
Coarse-to-Fine Vision-Language Pre-training with Fusion in the Backbone	Jun 15, 2022	Described Object DetectionImage Captioning	CodeCode Available	1	5
Interpreting Chest X-rays Like a Radiologist: A Benchmark with Clinical Reasoning	May 29, 2025	DiagnosticQuestion Answering	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
CAT-ViL: Co-Attention Gated Vision-Language Embedding for Visual Question Localized-Answering in Robotic Surgery	Jul 11, 2023	Question AnsweringScene Understanding	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
COBRA: Contrastive Bi-Modal Representation Algorithm	May 7, 2020	Cross-Modal RetrievalImage Captioning	CodeCode Available	1	5
CoCa: Contrastive Captioners are Image-Text Foundation Models	May 4, 2022	Action ClassificationDecoder	CodeCode Available	1	5
MAPL: Parameter-Efficient Adaptation of Unimodal Pre-Trained Models for Vision-Language Few-Shot Prompting	Oct 13, 2022	Image CaptioningQuestion Answering	CodeCode Available	1	5
Debiased Visual Question Answering from Feature and Sample Perspectives	Dec 1, 2021	Bias DetectionQuestion Answering	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