Generative artificial intelligence (AI) can efficiently create realistic, real-world object stimuli

The availability of real-world object stimuli that meet researchers’ requirements, for example regarding colour, orientation and resolution, is an ongoing challenge in visual cognition research. Traditionally, there has been a reliance on manually curated object stimuli, which are inefficient to create and may afford researchers limited control over stimulus characteristics. However, recent advances in artificial intelligence (AI) can facilitate the generation of custom-made, highly realistic visual stimuli. We report a generative AI method we used to efficiently generate 200 images of everyday objects for use in research. We also report the results from a subsequent validation study in which we assessed the nameability, perceived realism and familiarity of the stimuli in a sample of 45 younger (18-35) and 45 older (65-85) adults. As anticipated, the majority of the stimuli were rated highly across all three measures, and no significant age differences were observed. The results thus generally validated most of the stimuli for future research requiring nameable, realistic everyday object images. The stimuli, each in seven colours, and the corresponding validation scores are openly available for future use by others. Our research highlights the broader utility of an AI-based approach for generating realistic object stimuli. Our method is reproducible, flexible, and efficient, providing a valuable reference for researchers seeking to custom-create their own object stimuli.