Data to 7 Oct 2026

Visual Question Answering: Datasets, Algorithms, and Future Challenges

arXiv 1610.01465 ↗First posted 5 Oct 2016cs.CV cs.AI cs.CLcited by 56

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Abstract (arXiv)

Visual Question Answering (VQA) is a recent problem in computer vision and natural language processing that has garnered a large amount of interest from the deep learning, computer vision, and natural language processing communities. In VQA, an algorithm needs to answer text-based questions about images. Since the release of the first VQA dataset in 2014, additional datasets have been released and many algorithms have been proposed. In this review, we critically examine the current state of VQA in terms of problem formulation, existing datasets, evaluation metrics, and algorithms. In particular, we discuss the limitations of current datasets with regard to their ability to properly train and assess VQA algorithms. We then exhaustively review existing algorithms for VQA. Finally, we discuss possible future directions for VQA and image understanding research.

Key facts. Cited by 56 papers in the map (data through 7 Oct 2026). First posted on arXiv 5 Oct 2016.

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Citing papers per year: 2021: 12; 2022: 9; 2023: 16; 2024: 7; 2025: 8; 2026: 4.

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2022VLP: A Survey on Vision-Language Pre-trainingcited by 159
2023Large Models for Time Series and Spatio-Temporal Data: A Survey and Outlookcited by 109
2021Learning to Predict Visual Attributes in the Wildcited by 95
2025Perception, Reason, Think, and Plan: A Survey on Large Multimodal Reasoning Modelscited by 89
2022Reliable Visual Question Answering: Abstain Rather Than Answer Incorrectlycited by 86
2022Clotho-AQA: A Crowdsourced Dataset for Audio Question Answeringcited by 84
2024Natural Language Understanding and Inference with MLLM in Visual Question Answering: A Surveycited by 74
2023Unleashing the potential of prompt engineering for large language modelscited by 72
2022A Review of Emerging Research Directions in Abstract Visual Reasoningcited by 33
2023BiCro: Noisy Correspondence Rectification for Multi-modality Data via Bi-directional Cross-modal Similarity Consistencycited by 27
2025Modality Curation: Building Universal Embeddings for Advanced Multimodal Information Retrievalcited by 26
2023From Image to Language: A Critical Analysis of Visual Question Answering (VQA) Approaches, Challenges, and Opportunitiescited by 24

38 more

2023Robust Visual Question Answering: Datasets, Methods, and Future Challengescited by 23
2023Multimodality of AI for Education: Towards Artificial General Intelligencecited by 21
2023Explaining Autonomous Driving Actions with Visual Question Answeringcited by 16
2024OmniCount: Multi-label Object Counting with Semantic-Geometric Priorscited by 16
2021How Modular Should Neural Module Networks Be for Systematic Generalization?cited by 15
2024EfficientEQA: An Efficient Approach to Open-Vocabulary Embodied Question Answeringcited by 15
2022VQA and Visual Reasoning: An Overview of Recent Datasets, Methods and Challengescited by 14
2024Exploring Phrase-Level Grounding with Text-to-Image Diffusion Modelcited by 13
2021Selective Replay Enhances Learning in Online Continual Analogical Reasoningcited by 12
2022Globally Gated Deep Linear Networkscited by 12
2023HaVQA: A Dataset for Visual Question Answering and Multimodal Research in Hausa Languagecited by 12
2021Visual Question Answering: which investigated applications?cited by 11
2021CoLLIE: Continual Learning of Language Grounding from Language-Image Embeddingscited by 11
2024FodFoM: Fake Outlier Data by Foundation Models Creates Stronger Visual Out-of-Distribution Detectorcited by 10
2023Improving Visual Question Answering Models through Robustness Analysis and In-Context Learning with a Chain of Basic Questionscited by 9
2021Bangla Natural Language Processing: A Comprehensive Analysis of Classical, Machine Learning, and Deep Learning Based Methodscited by 8
2025CoralVQA: A Large-Scale Visual Question Answering Dataset for Coral Reef Image Understandingcited by 6
2023Fairness in AI Systems: Mitigating gender bias from language-vision modelscited by 5
2023Synergizing Contrastive Learning and Optimal Transport for 3D Point Cloud Domain Adaptationcited by 5
2023ViCLEVR: A Visual Reasoning Dataset and Hybrid Multimodal Fusion Model for Visual Question Answering in Vietnamesecited by 5
2023Semi-Supervised Panoptic Narrative Groundingcited by 4
2026Mirage Probes: How Vision Models Fake Visual Understandingcited by 4
2023LOIS: Looking Out of Instance Semantics for Visual Question Answeringcited by 3
2022Vision-and-Language Pretrainingcited by 2
2021Chop Chop BERT: Visual Question Answering by Chopping VisualBERT's Headscited by 1
2021Image interpretation by iterative bottom-up top-down processingcited by 1
2021Improved RAMEN: Towards Domain Generalization for Visual Question Answeringcited by 1
2022Can I see an Example? Active Learning the Long Tail of Attributes and Relationscited by 1
2023BinaryVQA: A Versatile Test Set to Evaluate the Out-of-Distribution Generalization of VQA Modelscited by 1
2024SURE-VQA: Systematic Understanding of Robustness Evaluation in Medical VQA Taskscited by 1
2025Light as Deception: GPT-driven Natural Relighting Against Vision-Language Pre-training Modelscited by 1
2025Argus Inspection: Do Multimodal Large Language Models Possess the Eye of Panoptes?cited by 1
2021Understanding in Artificial Intelligencecited by 0
2021EKTVQA: Generalized use of External Knowledge to empower Scene Text in Text-VQAcited by 0
2021On the Significance of Question Encoder Sequence Model in the Out-of-Distribution Performance in Visual Question Answeringcited by 0
2022EBMs vs. CL: Exploring Self-Supervised Visual Pretraining for Visual Question Answeringcited by 0
2023Knowledge-Based Counterfactual Queries for Visual Question Answeringcited by 0
2024QTG-VQA: Question-Type-Guided Architectural for VideoQA Systemscited by 0

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