mlsanityData to 7 Oct 2026

A survey of image labelling for computer vision applications

arXiv 2104.08885 ↗First posted 18 Apr 2021cs.CV cs.HC cs.LGcited by 18

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Abstract (arXiv)

Supervised machine learning methods for image analysis require large amounts of labelled training data to solve computer vision problems. The recent rise of deep learning algorithms for recognising image content has led to the emergence of many ad-hoc labelling tools. With this survey, we capture and systematise the commonalities as well as the distinctions between existing image labelling software. We perform a structured literature review to compile the underlying concepts and features of image labelling software such as annotation expressiveness and degree of automation. We structure the manual labelling task by its organisation of work, user interface design options, and user support techniques to derive a systematisation schema for this survey. Applying it to available software and the body of literature, enabled us to uncover several application archetypes and key domains such as image retrieval or instance identification in healthcare or television.

Key facts. Cited by 18 papers in the map (data through 7 Oct 2026). Builds on 11 of its 95 references that are in the map. First posted on arXiv 18 Apr 2021.

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11 of 95 references.

References · 11

  1. 2019A Survey of Deep Learning Techniques for Autonomous Drivingcited by 401
  2. 2019FreiHAND: A Dataset for Markerless Capture of Hand Pose and Shape from Single RGB Imagescited by 271
  3. 2019The VIA Annotation Software for Images, Audio and Videocited by 166
  4. 2016Superpixels: An Evaluation of the State-of-the-Artcited by 52
  5. 2021labelCloud: A Lightweight Domain-Independent Labeling Tool for 3D Object Detection in Point Cloudscited by 8
  6. 2019Interactive Image Segmentation using Label Propagation through Complex Networkscited by 6
  7. 2016Automatic Image Annotation via Label Transfer in the Semantic Spacecited by 3
  8. 2016Who's that Actor? Automatic Labelling of Actors in TV series starting from IMDB Imagescited by 2
  9. 2017Semi-automated labelling of medical images: benefits of a collaborative work in the evaluation of prostate cancer in MRIcited by 1
  10. 2018Learning Image Conditioned Label Space for Multilabel Classificationcited by 1
  11. 2019VISIR: Visual and Semantic Image Label Refinementcited by 1

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 3; 2023: 5; 2024: 5; 2025: 4; 2026: 1.

18 papers.

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  1. 2022ECCV Caption: Correcting False Negatives by Collecting Machine-and-Human-verified Image-Caption Associations for MS-COCOcited by 37
  2. 2024Evaluating the Utility of Conformal Prediction Sets for AI-Advised Image Labelingcited by 12
  3. 2024SpatialDreamer: Self-supervised Stereo Video Synthesis from Monocular Inputcited by 11
  4. 2023Neglected Free Lunch -- Learning Image Classifiers Using Annotation Byproductscited by 4
  5. 2022Survey and Systematization of 3D Object Detection Models and Methodscited by 3
  6. 2024No Need to Sacrifice Data Quality for Quantity: Crowd-Informed Machine Annotation for Cost-Effective Understanding of Visual Datacited by 2
  7. 2023Annotating Ambiguous Images: General Annotation Strategy for High-Quality Data with Real-World Biomedical Validationcited by 1
  8. 2023LiDAR-based curb detection for ground truth annotation in automated driving validationcited by 1
  9. 2025It's Not Just Labeling -- A Research on LLM Generated Feedback Interpretability and Image Labeling Sketch Featurescited by 1
  10. 2025QualitEye: Public and Privacy-preserving Gaze Data Quality Verificationcited by 1
  11. 2022A Light in the Dark: Deep Learning Practices for Industrial Computer Visioncited by 0
  12. 2023BI-LAVA: Biocuration with Hierarchical Image Labeling through Active Learning and Visual Analysiscited by 0
6 more
  1. 2023Exploring Different Levels of Supervision for Detecting and Localizing Solar Panels on Remote Sensing Imagerycited by 0
  2. 2024Situated Ground Truths: Enhancing Bias-Aware AI by Situating Data Labels with SituAnnotatecited by 0
  3. 2024Assistive Image Annotation Systems with Deep Learning and Natural Language Capabilities: A Reviewcited by 0
  4. 2025The Achilles Heel of AI: Fundamentals of Risk-Aware Training Data for High-Consequence Modelscited by 0
  5. 2025Skeleton-Snippet Contrastive Learning with Multiscale Feature Fusion for Action Localizationcited by 0
  6. 2026From Bounding Boxes to Visual Reasoning: An On-Policy Data Annotation Tool for Vision-Language Modelscited by 0