Drawings of THINGS: A large-scale drawing dataset of 1854 object concepts

TL;DR

This paper introduces a dataset of human drawings of 1854 object concepts, aiming to study how people express and recognize visual knowledge.

Contribution

The novel dataset, Drawing of THINGS (DoT), includes stroke histories, recognition data, and metadata on participants and object properties.

Findings

People's ability to recognize drawings is compared to their recognition of real-world images.

The dataset explores how object memorability and typicality affect drawing understanding.

DoT is positioned as a tool to advance understanding of human visual concept expression.

Abstract

The development of large datasets of natural images has galvanized progress in psychology, neuroscience, and computer science. Notably, the THINGS database constitutes a collective effort towards understanding of human visual knowledge by accumulating rich data on a shared set of visual object concepts across several studies. In this paper, we introduce Drawing of THINGS ( DoT ), a novel dataset of 28,627 human drawings of 1854 diverse object concepts, sampled systematically from concrete picturable and nameable nouns in the American English language, mirroring the structure of the THINGS image database. In addition to data on drawings’ stroke history, we further collected fine-grained recognition data for each drawing, along with metadata on participant demographics, drawing ability, and mental imagery. We characterize people’s ability to communicate and recognize semantic information encoded in drawings and compare this ability to their ability to recognize real-world images of the same visual objects. We also explore the relationship between drawing understanding and the memorability and typicality of the objects contained in THINGS. In sum, we envision DoT as a powerful tool that builds on the THINGS database to advance understanding of how humans express knowledge about visual concepts.

The online version contains supplementary material available at 10.3758/s13428-025-02887-w.

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