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 551–575 of 2167 papers

Title	Date	Tasks	Status	Hype
Answer Mining from a Pool of Images: Towards Retrieval-Based Visual Question Answering	Jun 29, 2023	Answer GenerationQuestion Answering	CodeCode Available	1
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
Large Language Models are Temporal and Causal Reasoners for Video Question Answering	Oct 24, 2023	Natural Language UnderstandingQuestion Answering	CodeCode Available	1
Large-Scale Adversarial Training for Vision-and-Language Representation Learning	Jun 11, 2020	Image-text RetrievalQuestion Answering	CodeCode Available	1
End-to-end Document Recognition and Understanding with Dessurt	Mar 30, 2022	document understandingVisual Question Answering (VQA)	CodeCode Available	1
Expectation-Maximization Contrastive Learning for Compact Video-and-Language Representations	Nov 21, 2022	Contrastive LearningRepresentation Learning	CodeCode Available	1
End-to-end Knowledge Retrieval with Multi-modal Queries	Jun 1, 2023	BenchmarkingCross-Modal Retrieval	CodeCode Available	1
Calibrating Concepts and Operations: Towards Symbolic Reasoning on Real Images	Oct 1, 2021	Question AnsweringVisual Question Answering	CodeCode Available	1
How Much Can CLIP Benefit Vision-and-Language Tasks?	Jul 13, 2021	Question AnsweringVision and Language Navigation	CodeCode Available	1
GraghVQA: Language-Guided Graph Neural Networks for Graph-based Visual Question Answering	Apr 20, 2021	Graph Neural NetworkGraph Question Answering	CodeCode Available	1
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization	Oct 7, 2016	General ClassificationImage Attribution	CodeCode Available	1
Learning to Discretely Compose Reasoning Module Networks for Video Captioning	Jul 17, 2020	DecoderQuestion Answering	CodeCode Available	1
Can I Trust Your Answer? Visually Grounded Video Question Answering	Sep 4, 2023	Grounded Video Question AnsweringQuestion Answering	CodeCode Available	1
Less is More: ClipBERT for Video-and-Language Learning via Sparse Sampling	Feb 11, 2021	Question AnsweringRetrieval	CodeCode Available	1
Light-VQA: A Multi-Dimensional Quality Assessment Model for Low-Light Video Enhancement	May 16, 2023	Video EnhancementVideo Quality Assessment	CodeCode Available	1
Light-VQA+: A Video Quality Assessment Model for Exposure Correction with Vision-Language Guidance	May 6, 2024	Exposure CorrectionVideo Enhancement	CodeCode Available	1
Graphhopper: Multi-Hop Scene Graph Reasoning for Visual Question Answering	Jul 13, 2021	NavigateQuestion Answering	CodeCode Available	1
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
Dual-Key Multimodal Backdoors for Visual Question Answering	Dec 14, 2021	Question AnsweringVisual Question Answering	CodeCode Available	1
GQA: A New Dataset for Real-World Visual Reasoning and Compositional Question Answering	Feb 25, 2019	Question AnsweringVisual Question Answering (VQA)	CodeCode Available	1
Graph Optimal Transport for Cross-Domain Alignment	Jun 26, 2020	Graph MatchingImage Captioning	CodeCode Available	1
Enhancing Visual Question Answering through Question-Driven Image Captions as Prompts	Apr 12, 2024	Image CaptioningQuestion Answering	CodeCode Available	1
ERNIE-Layout: Layout Knowledge Enhanced Pre-training for Visually-rich Document Understanding	Oct 12, 2022	document-image-classificationDocument Image Classification	CodeCode Available	1
eP-ALM: Efficient Perceptual Augmentation of Language Models	Mar 20, 2023	In-Context LearningVisual Question Answering (VQA)	CodeCode Available	1
Greedy Gradient Ensemble for Robust Visual Question Answering	Jul 27, 2021	Question AnsweringVisual Question Answering	CodeCode Available	1

Show:10 25 50

← PrevPage 23 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