mlsanityData to 14 Oct 2026

Where To Look: Focus Regions for Visual Question Answering

arXiv 1511.07394 ↗First posted 23 Nov 2015cs.CVcited by 64

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Abstract (arXiv)

We present a method that learns to answer visual questions by selecting image regions relevant to the text-based query. Our method exhibits significant improvements in answering questions such as "what color," where it is necessary to evaluate a specific location, and "what room," where it selectively identifies informative image regions. Our model is tested on the VQA dataset which is the largest human-annotated visual question answering dataset to our knowledge.

Key facts. Cited by 64 papers in the map (data through 14 Oct 2026). First posted on arXiv 23 Nov 2015.

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Citing papers per year: 2021: 16; 2022: 16; 2023: 19; 2024: 8; 2025: 3; 2026: 2.

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  1. 2023To See is to Believe: Prompting GPT-4V for Better Visual Instruction Tuningcited by 144
  2. 2022CLEVR-Math: A Dataset for Compositional Language, Visual and Mathematical Reasoningcited by 120
  3. 2022Vision-Language Pre-training: Basics, Recent Advances, and Future Trendscited by 117
  4. 2024Natural Language Understanding and Inference with MLLM in Visual Question Answering: A Surveycited by 76
  5. 2023A Comprehensive Survey on Applications of Transformers for Deep Learning Taskscited by 71
  6. 2021Attention, please! A survey of Neural Attention Models in Deep Learningcited by 51
  7. 2022GAMMA Challenge:Glaucoma grAding from Multi-Modality imAgescited by 46
  8. 2021N24News: A New Dataset for Multimodal News Classificationcited by 40
  9. 2022From Easy to Hard: Learning Language-guided Curriculum for Visual Question Answering on Remote Sensing Datacited by 39
  10. 2022Vision-Language Intelligence: Tasks, Representation Learning, and Large Modelscited by 28
  11. 2022Interpretable by Design: Learning Predictors by Composing Interpretable Queriescited by 28
  12. 2023Multi-modal Machine Learning in Engineering Design: A Review and Future Directionscited by 27
38 more
  1. 2022Towards Explainable 3D Grounded Visual Question Answering: A New Benchmark and Strong Baselinecited by 25
  2. 2023From Image to Language: A Critical Analysis of Visual Question Answering (VQA) Approaches, Challenges, and Opportunitiescited by 25
  3. 2022Vision+X: A Survey on Multimodal Learning in the Light of Datacited by 22
  4. 2021ProTo: Program-Guided Transformer for Program-Guided Taskscited by 21
  5. 2022LVP-M3: Language-aware Visual Prompt for Multilingual Multimodal Machine Translationcited by 21
  6. 2023HRVQA: A Visual Question Answering Benchmark for High-Resolution Aerial Imagescited by 21
  7. 2024LOVA3: Learning to Visual Question Answering, Asking and Assessmentcited by 21
  8. 2021Multimodal Integration of Human-Like Attention in Visual Question Answeringcited by 20
  9. 2023Interpretable Medical Image Visual Question Answering via Multi-Modal Relationship Graph Learningcited by 17
  10. 2022CLEVR-X: A Visual Reasoning Dataset for Natural Language Explanationscited by 16
  11. 2023Generate then Select: Open-ended Visual Question Answering Guided by World Knowledgecited by 16
  12. 2021VQA-Aid: Visual Question Answering for Post-Disaster Damage Assessment and Analysiscited by 15
  13. 2021Asking questions on handwritten document collectionscited by 14
  14. 2024Exploring Phrase-Level Grounding with Text-to-Image Diffusion Modelcited by 13
  15. 2023Diagnosing Human-object Interaction Detectorscited by 11
  16. 2021X-GGM: Graph Generative Modeling for Out-of-Distribution Generalization in Visual Question Answeringcited by 10
  17. 2023Answer Mining from a Pool of Images: Towards Retrieval-Based Visual Question Answeringcited by 10
  18. 2021Answer Questions with Right Image Regions: A Visual Attention Regularization Approachcited by 9
  19. 2024ViOCRVQA: Novel Benchmark Dataset and Vision Reader for Visual Question Answering by Understanding Vietnamese Text in Imagescited by 8
  20. 2024A Comprehensive Survey on Visual Question Answering Datasets and Algorithmscited by 8
  21. 2022From Pixels to Objects: Cubic Visual Attention for Visual Question Answeringcited by 7
  22. 2023Dual-Gated Fusion with Prefix-Tuning for Multi-Modal Relation Extractioncited by 7
  23. 2023Multi-Modal Knowledge Graph Transformer Framework for Multi-Modal Entity Alignmentcited by 7
  24. 2022Is GPT-3 all you need for Visual Question Answering in Cultural Heritage?cited by 6
  25. 2021Saying the Unseen: Video Descriptions via Dialog Agentscited by 5
  26. 2022Recent, rapid advancement in visual question answering architecture: a reviewcited by 5
  27. 2022DoRO: Disambiguation of referred object for embodied agentscited by 5
  28. 2022AlignVE: Visual Entailment Recognition Based on Alignment Relationscited by 5
  29. 2024Text-Guided Coarse-to-Fine Fusion Network for Robust Remote Sensing Visual Question Answeringcited by 5
  30. 2022Understanding Attention for Vision-and-Language Taskscited by 4
  31. 2023Semi-Supervised Panoptic Narrative Groundingcited by 4
  32. 2021Relation-aware Hierarchical Attention Framework for Video Question Answeringcited by 3
  33. 2025DepthFocus: Controllable Depth Estimation for See-Through Scenescited by 3
  34. 2021Latent Variable Models for Visual Question Answeringcited by 2
  35. 2021Visual Question Answering based on Local-Scene-Aware Referring Expression Generationcited by 2
  36. 2023Learning to Agree on Vision Attention for Visual Commonsense Reasoningcited by 2
  37. 2023Dynamic Clue Bottlenecks: Towards Interpretable-by-Design Visual Question Answeringcited by 2
  38. 2023Attention-Based Methods For Audio Question Answeringcited by 2

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