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 376–400 of 2167 papers

Title	Date	Tasks	Status	Hype
Symbolic Replay: Scene Graph as Prompt for Continual Learning on VQA Task	Aug 24, 2022	Continual LearningQuestion Answering	CodeCode Available	1
CLEVR-Math: A Dataset for Compositional Language, Visual and Mathematical Reasoning	Aug 10, 2022	MathMathematical Reasoning	CodeCode Available	1
ChiQA: A Large Scale Image-based Real-World Question Answering Dataset for Multi-Modal Understanding	Aug 5, 2022	Image RetrievalQuestion Answering	CodeCode Available	1
TAG: Boosting Text-VQA via Text-aware Visual Question-answer Generation	Aug 3, 2022	Answer GenerationQuestion-Answer-Generation	CodeCode Available	1
Generative Bias for Robust Visual Question Answering	Aug 1, 2022	Knowledge DistillationQuestion Answering	CodeCode Available	1
Cross-Modal Causal Relational Reasoning for Event-Level Visual Question Answering	Jul 26, 2022	Causal InferenceQuestion Answering	CodeCode Available	1
LaKo: Knowledge-driven Visual Question Answering via Late Knowledge-to-Text Injection	Jul 26, 2022	DecoderKnowledge Graphs	CodeCode Available	1
Rethinking Data Augmentation for Robust Visual Question Answering	Jul 18, 2022	Data AugmentationKnowledge Distillation	CodeCode Available	1
Clover: Towards A Unified Video-Language Alignment and Fusion Model	Jul 16, 2022	Language ModelingLanguage Modelling	CodeCode Available	1
Video Graph Transformer for Video Question Answering	Jul 12, 2022	Question AnsweringRelation	CodeCode Available	1
ViQuAE, a Dataset for Knowledge-based Visual Question Answering about Named Entities	Jul 11, 2022	ArticlesFew-Shot Learning	CodeCode Available	1
Weakly Supervised Grounding for VQA in Vision-Language Transformers	Jul 5, 2022	Question AnsweringRepresentation Learning	CodeCode Available	1
A Unified End-to-End Retriever-Reader Framework for Knowledge-based VQA	Jun 30, 2022	Question AnsweringRetrieval	CodeCode Available	1
Consistency-preserving Visual Question Answering in Medical Imaging	Jun 27, 2022	Question AnsweringVisual Question Answering	CodeCode Available	1
Surgical-VQA: Visual Question Answering in Surgical Scenes using Transformer	Jun 22, 2022	Question AnsweringSentence	CodeCode Available	1
Zero-Shot Video Question Answering via Frozen Bidirectional Language Models	Jun 16, 2022	Fill MaskLanguage Modeling	CodeCode Available	1
MixGen: A New Multi-Modal Data Augmentation	Jun 16, 2022	Data AugmentationImage-text Retrieval	CodeCode Available	1
Coarse-to-Fine Vision-Language Pre-training with Fusion in the Backbone	Jun 15, 2022	Described Object DetectionImage Captioning	CodeCode Available	1
A-OKVQA: A Benchmark for Visual Question Answering using World Knowledge	Jun 3, 2022	Question AnsweringVisual Question Answering	CodeCode Available	1
REVIVE: Regional Visual Representation Matters in Knowledge-Based Visual Question Answering	Jun 2, 2022	Question AnsweringRetrieval	CodeCode Available	1
mPLUG: Effective and Efficient Vision-Language Learning by Cross-modal Skip-connections	May 24, 2022	Computational Efficiencycross-modal alignment	CodeCode Available	1
PEVL: Position-enhanced Pre-training and Prompt Tuning for Vision-language Models	May 23, 2022	Language ModelingLanguage Modelling	CodeCode Available	1
Learning to Answer Visual Questions from Web Videos	May 10, 2022	Dataset GenerationQuestion Answering	CodeCode Available	1
Declaration-based Prompt Tuning for Visual Question Answering	May 5, 2022	Image-text matchingLanguage Modeling	CodeCode Available	1
CoCa: Contrastive Captioners are Image-Text Foundation Models	May 4, 2022	Action ClassificationDecoder	CodeCode Available	1

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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