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The Beyond Reality Image Collection (BRIC).

Noga Segal-Gordon1, Yoav Bar-Anan2

  • 1School of Psychological Sciences, Tel Aviv University, Tel Aviv, Israel. nogasegal1@mail.tau.ac.il.

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Summary
This summary is machine-generated.

The Beyond Reality Image Collection (BRIC) offers 648 nonrealistic images for studying human evaluative responses. This diverse dataset reveals consistent yet sometimes discrepant emotional reactions across various assessment methods.

Keywords:
Affective ratingEvaluative ratingsImagesNormsVisual stimuli

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Area of Science:

  • Psychology
  • Computer Science
  • Art and Aesthetics

Background:

  • Existing image datasets often focus on realistic visuals.
  • The Beyond Reality Image Collection (BRIC) was created to address this gap by focusing on nonrealistic imagery.
  • BRIC includes a diverse range of nonrealistic visuals, from abstract art to AI-generated fantastical creatures.

Purpose of the Study:

  • To introduce the Beyond Reality Image Collection (BRIC), a novel dataset of nonrealistic images.
  • To investigate human evaluative responses to a wide array of nonrealistic visual stimuli.
  • To provide a resource for research on affective responses and evaluative processes.

Main Methods:

  • Collected 648 nonrealistic images, including paintings and AI-generated visuals.
  • Gathered evaluative ratings from 16,208 participants across 25,321 sessions.
  • Employed multiple evaluation measures: binary categorization, seven-point scales (with and without time pressure), and evaluative priming.

Main Results:

  • Mean evaluations across different measures were highly correlated, indicating general agreement.
  • A subset of images consistently elicited discrepant evaluative reactions across measures.
  • Participant responses varied based on the degree of unreal elements in the images.

Conclusions:

  • The BRIC is a valuable resource for studying evaluative processes and affective responses to nonrealistic stimuli.
  • The dataset can facilitate research into the nuances of human perception and emotional reactions to art and AI-generated imagery.
  • Findings highlight the complexity of human evaluation, even for nonrealistic visual content.