Gesture Classification in Artworks Using Contextual Image Features
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Abstract (arXiv)
Recognizing gestures in artworks can add a valuable dimension to art understanding and help to acknowledge the role of the sense of smell in cultural heritage. We propose a method to recognize smell gestures in historical artworks. We show that combining local features with global image context improves classification performance notably on different backbones.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 17 of its 35 references that are in the map. First posted on arXiv 4 Dec 2024.
Builds on
17 of 35 references.
References · 17
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5 more
- 2020An analysis of the transfer learning of convolutional neural networks for artistic imagescited by 11
- 2022DEArt: Dataset of European Artcited by 9
- 2023Poses of People in Art: A Data Set for Human Pose Estimation in Digital Art Historycited by 6
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- 2023SniffyArt: The Dataset of Smelling Personscited by 6
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Citing papers per year: 2025: 1.
1 paper.