# Algorithmic Ways of Seeing: Using Object Detection to Facilitate Art Exploration

Source: [Algorithmic Ways of Seeing: Using Object Detection to Facilitate Art Exploration](<https://www.sota2.com/research/paper/68fa72ad1e209131cea57ce2>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-26T02:31:50.592Z

Authors: Louie S{\\o}s Meyer, Johanne Engel Aaen, Anitamalina Regitse Tranberg, Peter Kun, Matthias Freiberger, Sebastian Risi, Anders Sundnes L{\\o}vlie

Published: 2024-03-28T06:46:45.000Z

## Abstract

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.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2403.19174>)

[PDF](<https://arxiv.org/pdf/2403.19174.pdf>)