mlsanityData to 7 Oct 2026

Captioning Images Taken by People Who Are Blind

arXiv 2002.08565 ↗First posted 20 Feb 2020cs.CVcited by 108

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Cited by 26 in Multimodal LLMs / vision-language models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

While an important problem in the vision community is to design algorithms that can automatically caption images, few publicly-available datasets for algorithm development directly address the interests of real users. Observing that people who are blind have relied on (human-based) image captioning services to learn about images they take for nearly a decade, we introduce the first image captioning dataset to represent this real use case. This new dataset, which we call VizWiz-Captions, consists of over 39,000 images originating from people who are blind that are each paired with five captions. We analyze this dataset to (1) characterize the typical captions, (2) characterize the diversity of content found in the images, and (3) compare its content to that found in eight popular vision datasets. We also analyze modern image captioning algorithms to identify what makes this new dataset challenging for the vision community. We publicly-share the dataset with captioning challenge instructions at https://vizwiz.org

Key facts. Cited by 108 papers in the map (data through 7 Oct 2026). First posted on arXiv 20 Feb 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 11; 2022: 22; 2023: 26; 2024: 29; 2025: 11; 2026: 9.

108 papers.

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  1. 2021Conceptual 12M: Pushing Web-Scale Image-Text Pre-Training To Recognize Long-Tail Visual Conceptscited by 1,209
  2. 2022PaLI: A Jointly-Scaled Multilingual Language-Image Modelcited by 762
  3. 2022GIT: A Generative Image-to-text Transformer for Vision and Languagecited by 536
  4. 2023PaLI-X: On Scaling up a Multilingual Vision and Language Modelcited by 254
  5. 2023Multimodal Large Language Models: A Surveycited by 193
  6. 2021TextOCR: Towards large-scale end-to-end reasoning for arbitrary-shaped scene textcited by 170
  7. 2021From Show to Tell: A Survey on Deep Learning-based Image Captioningcited by 137
  8. 2022Vision-Language Pre-training: Basics, Recent Advances, and Future Trendscited by 117
  9. 2022SmallCap: Lightweight Image Captioning Prompted with Retrieval Augmentationcited by 82
  10. 2023Self-Supervised Multimodal Learning: A Surveycited by 58
  11. 2024ImageInWords: Unlocking Hyper-Detailed Image Descriptionscited by 56
  12. 2024From Pixels to Prose: A Large Dataset of Dense Image Captionscited by 52
38 more
  1. 2023AutoAD II: The Sequel -- Who, When, and What in Movie Audio Descriptioncited by 48
  2. 2022Grounding Answers for Visual Questions Asked by Visually Impaired Peoplecited by 47
  3. 2024Polos: Multimodal Metric Learning from Human Feedback for Image Captioningcited by 46
  4. 2022Deep Learning Approaches on Image Captioning: A Reviewcited by 43
  5. 2023Text encoders bottleneck compositionality in contrastive vision-language modelscited by 34
  6. 2022SceneTrilogy: On Human Scene-Sketch and its Complementarity with Photo and Textcited by 30
  7. 2022PreSTU: Pre-Training for Scene-Text Understandingcited by 27
  8. 2025Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuningcited by 27
  9. 2022I Can't Believe There's No Images! Learning Visual Tasks Using only Language Supervisioncited by 26
  10. 2023Omni-SMoLA: Boosting Generalist Multimodal Models with Soft Mixture of Low-rank Expertscited by 26
  11. 2023From Image to Language: A Critical Analysis of Visual Question Answering (VQA) Approaches, Challenges, and Opportunitiescited by 24
  12. 2022Prompt-based Learning for Unpaired Image Captioningcited by 23
  13. 2021CIDEr-R: Robust Consensus-based Image Description Evaluationcited by 22
  14. 2024The Evolution of Multimodal Model Architecturescited by 21
  15. 2022Context Matters for Image Descriptions for Accessibility: Challenges for Referenceless Evaluation Metricscited by 18
  16. 2023With a Little Help from your own Past: Prototypical Memory Networks for Image Captioningcited by 18
  17. 2022DALL-E for Detection: Language-driven Compositional Image Synthesis for Object Detectioncited by 17
  18. 2022LineCap: Line Charts for Data Visualization Captioning Modelscited by 17
  19. 2023Fine-grained Audible Video Descriptioncited by 17
  20. 2024Learning from Observer Gaze:Zero-Shot Attention Prediction Oriented by Human-Object Interaction Recognitioncited by 17
  21. 2024FINEMATCH: Aspect-based Fine-grained Image and Text Mismatch Detection and Correctioncited by 16
  22. 2024Positive-Augmented Contrastive Learning for Vision-and-Language Evaluation and Trainingcited by 16
  23. 2021Concadia: Towards Image-Based Text Generation with a Purposecited by 15
  24. 2022Multi-modal Misinformation Detection: Approaches, Challenges and Opportunitiescited by 14
  25. 2025Beyond Visual Perception: Insights from Smartphone Interaction of Visually Impaired Users with Large Multimodal Modelscited by 13
  26. 2025Stealthy Backdoor Attack in Self-Supervised Learning Vision Encoders for Large Vision Language Modelscited by 13
  27. 2025EditMGT: Unleashing Potentials of Masked Generative Transformers in Image Editingcited by 12
  28. 2022CapOnImage: Context-driven Dense-Captioning on Imagecited by 11
  29. 2022VizWiz-FewShot: Locating Objects in Images Taken by People With Visual Impairmentscited by 11
  30. 2024InfiMM-HD: A Leap Forward in High-Resolution Multimodal Understandingcited by 11
  31. 2024What Makes for Good Image Captions?cited by 11
  32. 2024SURf: Teaching Large Vision-Language Models to Selectively Utilize Retrieved Informationcited by 11
  33. 2024DENEB: A Hallucination-Robust Automatic Evaluation Metric for Image Captioningcited by 11
  34. 2025Evaluating Multimodal Language Models as Visual Assistants for Visually Impaired Userscited by 11
  35. 2023Beyond Generation: Harnessing Text to Image Models for Object Detection and Segmentationcited by 10
  36. 2024A Comprehensive Survey of 3D Dense Captioning: Localizing and Describing Objects in 3D Scenescited by 10
  37. 2024OmChat: A Recipe to Train Multimodal Language Models with Strong Long Context and Video Understandingcited by 10
  38. 2021Question-controlled Text-aware Image Captioningcited by 9

50 most cited of 108 All 108 (JSON)