Algorithmic Ways of Seeing: Using Object Detection to Facilitate Art Exploration
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Abstract (arXiv)
This Research through Design paper explores how object detection may be applied to a large digital art museum collection to facilitate new ways of encountering and experiencing art. We present the design and evaluation of an interactive application called SMKExplore, which allows users to explore a museum's digital collection of paintings by browsing through objects detected in the images, as a novel form of open-ended exploration. We provide three contributions. First, we show how an object detection pipeline can be integrated into a design process for visual exploration. Second, we present the design and development of an app that enables exploration of an art museum's collection. Third, we offer reflections on future possibilities for museums and HCI researchers to incorporate object detection techniques into the digitalization of museums.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 22 of its 94 references that are in the map. First posted on arXiv 28 Mar 2024.
Builds on
22 of 94 references.
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10 more
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Built on by
Citing papers per year: 2024: 2; 2025: 1; 2026: 1.
4 papers.
- 2024Human-LLM Compound System for Scientific Ideation through Facet Recombination and Novelty Evaluationcited by 39
- 2024No Annotations for Object Detection in Art through Stable Diffusioncited by 2
- 2025KidsArtBench: Multi-Dimensional Children's Art Evaluation with Attribute-Aware MLLMscited by 0
- 2026If These Walls Could Talk: Critical Play with Large Language Models in Museumscited by 0
- 2026If These Walls Could Talk: Critical Play with Large Language Models in Museums14 Jun 2026
- 2025KidsArtBench: Multi-Dimensional Children's Art Evaluation with Attribute-Aware MLLMs14 Dec 2025
- 2024No Annotations for Object Detection in Art through Stable Diffusion9 Dec 2024
- 2024Human-LLM Compound System for Scientific Ideation through Facet Recombination and Novelty Evaluation23 Sep 2024