mlsanityData to 7 Oct 2026

Detecting People in Artwork with CNNs

arXiv 1610.08871 ↗First posted 27 Oct 2016cs.CVcited by 25

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Abstract (arXiv)

CNNs have massively improved performance in object detection in photographs. However research into object detection in artwork remains limited. We show state-of-the-art performance on a challenging dataset, People-Art, which contains people from photos, cartoons and 41 different artwork movements. We achieve this high performance by fine-tuning a CNN for this task, thus also demonstrating that training CNNs on photos results in overfitting for photos: only the first three or four layers transfer from photos to artwork. Although the CNN's performance is the highest yet, it remains less than 60% AP, suggesting further work is needed for the cross-depiction problem. The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-46604-057

Key facts. Cited by 25 papers in the map (data through 7 Oct 2026). First posted on arXiv 27 Oct 2016.

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Citing papers per year: 2021: 5; 2022: 3; 2023: 6; 2024: 8; 2025: 3.

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  1. 2023Human-Art: A Versatile Human-Centric Dataset Bridging Natural and Artificial Scenescited by 68
  2. 2021Understanding and Creating Art with AI: Review and Outlookcited by 60
  3. 2024Adaptive Length Image Tokenization via Recurrent Allocationcited by 40
  4. 2023Robustness of SAM: Segment Anything Under Corruptions and Beyondcited by 30
  5. 2021Improving Object Detection in Art Images Using Only Style Transfercited by 15
  6. 2022DEArt: Dataset of European Artcited by 9
  7. 2022Semi-supervised Human Pose Estimation in Art-historical Imagescited by 6
  8. 2023Poses of People in Art: A Data Set for Human Pose Estimation in Digital Art Historycited by 6
  9. 2023SniffyArt: The Dataset of Smelling Personscited by 6
  10. 2021A deep learning approach to clustering visual artscited by 4
  11. 2024Algorithmic Ways of Seeing: Using Object Detection to Facilitate Art Explorationcited by 4
  12. 2024Seeing Faces in Things: A Model and Dataset for Pareidoliacited by 4
13 more
  1. 2023Transfer Learning for Olfactory Object Detectioncited by 3
  2. 2021Object Retrieval and Localization in Large Art Collections using Deep Multi-Style Feature Fusion and Iterative Votingcited by 2
  3. 2024Context-Infused Visual Grounding for Artcited by 2
  4. 2024Stylistic Multi-Task Analysis of Ukiyo-e Woodblock Printscited by 2
  5. 2024No Annotations for Object Detection in Art through Stable Diffusioncited by 2
  6. 2025Smelly, dense, and spreaded: The Object Detection for Olfactory References (ODOR) datasetcited by 2
  7. 2021Quantitative analysis of visual representation of sign elements in COVID-19 contextcited by 1
  8. 2024Artificial Intelligence for Geometry-Based Feature Extraction, Analysis and Synthesis in Artistic Images: A Surveycited by 1
  9. 2024Gesture Classification in Artworks Using Contextual Image Featurescited by 1
  10. 2022Analysis of the use of color and its emotional relationship in visual creations based on experiences during the context of the COVID-19 pandemiccited by 0
  11. 2023Improving Performance of Object Detection using the Mechanisms of Visual Recognition in Humanscited by 0
  12. 2025BOOST: Out-of-Distribution-Informed Adaptive Sampling for Bias Mitigation in Stylistic Convolutional Neural Networkscited by 0
  13. 2025Data Augmentation via Latent Diffusion Models for Detecting Smell-Related Objects in Historical Artworkscited by 0