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 451–475 of 2167 papers

Title	Date	Tasks	Status	Hype
Highly Efficient No-reference 4K Video Quality Assessment with Full-Pixel Covering Sampling and Training Strategy	Jul 30, 2024	4kVideo Quality Assessment	—Unverified	0
Bayesian Low-Rank LeArning (Bella): A Practical Approach to Bayesian Neural Networks	Jul 30, 2024	Visual Question Answering (VQA)	CodeCode Available	0
Pyramid Coder: Hierarchical Code Generator for Compositional Visual Question Answering	Jul 30, 2024	Code GenerationQuestion Answering	—Unverified	0
Take A Step Back: Rethinking the Two Stages in Visual Reasoning	Jul 29, 2024	Logical ReasoningQuestion Answering	—Unverified	0
Multi-label Cluster Discrimination for Visual Representation Learning	Jul 24, 2024	Contrastive LearningImage-text Retrieval	CodeCode Available	4
Fréchet Video Motion Distance: A Metric for Evaluating Motion Consistency in Videos	Jul 23, 2024	Image GenerationPoint Tracking	CodeCode Available	2
Improved Few-Shot Image Classification Through Multiple-Choice Questions	Jul 23, 2024	ArticlesFew-Shot Image Classification	—Unverified	0
Exploring the Effectiveness of Object-Centric Representations in Visual Question Answering: Comparative Insights with Foundation Models	Jul 22, 2024	Question AnsweringRepresentation Learning	—Unverified	0
QuIIL at T3 challenge: Towards Automation in Life-Saving Intervention Procedures from First-Person View	Jul 18, 2024	Action AnticipationAction Recognition	CodeCode Available	0
Visual Haystacks: A Vision-Centric Needle-In-A-Haystack Benchmark	Jul 18, 2024	GPUImage Retrieval	CodeCode Available	1
Multimodal Reranking for Knowledge-Intensive Visual Question Answering	Jul 17, 2024	Answer GenerationQuestion Answering	—Unverified	0
EchoSight: Advancing Visual-Language Models with Wiki Knowledge	Jul 17, 2024	ArticlesQuestion Answering	—Unverified	0
ProcTag: Process Tagging for Assessing the Efficacy of Document Instruction Data	Jul 17, 2024	Question AnsweringVisual Question Answering	—Unverified	0
ReLaX-VQA: Residual Fragment and Layer Stack Extraction for Enhancing Video Quality Assessment	Jul 16, 2024	Optical Flow EstimationVideo Compression	CodeCode Available	1
TM-PATHVQA:90000+ Textless Multilingual Questions for Medical Visual Question Answering	Jul 16, 2024	Medical Visual Question AnsweringQuestion Answering	—Unverified	0
SPIQA: A Dataset for Multimodal Question Answering on Scientific Papers	Jul 12, 2024	ArticlesQuestion Answering	CodeCode Available	2
Segmentation-guided Attention for Visual Question Answering from Remote Sensing Images	Jul 11, 2024	Question AnsweringSegmentation	—Unverified	0
Extracting Training Data from Document-Based VQA Models	Jul 11, 2024	MemorizationQuestion Answering	—Unverified	0
VQA-Diff: Exploiting VQA and Diffusion for Zero-Shot Image-to-3D Vehicle Asset Generation in Autonomous Driving	Jul 9, 2024	Autonomous DrivingImage to 3D	—Unverified	0
Large Language Models Understand Layout	Jul 8, 2024	Question AnsweringVisual Question Answering	CodeCode Available	0
WSI-VQA: Interpreting Whole Slide Images by Generative Visual Question Answering	Jul 8, 2024	DiagnosticGenerative Visual Question Answering	CodeCode Available	2
CLIPVQA:Video Quality Assessment via CLIP	Jul 6, 2024	Video Quality AssessmentVisual Question Answering (VQA)	CodeCode Available	0
RULE: Reliable Multimodal RAG for Factuality in Medical Vision Language Models	Jul 6, 2024	Medical DiagnosisRAG	CodeCode Available	2
FlowLearn: Evaluating Large Vision-Language Models on Flowchart Understanding	Jul 6, 2024	Optical Character Recognition (OCR)Visual Question Answering (VQA)	CodeCode Available	1
Black-box Model Ensembling for Textual and Visual Question Answering via Information Fusion	Jul 4, 2024	Question AnsweringVisual Question Answering	CodeCode Available	0

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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