[2404.05290] MindSet: Vision. A toolbox for testing DNNs on key psychological experiments

Computer Science > Computer Vision and Pattern Recognition arXiv:2404.05290 (cs) [Submitted on 8 Apr 2024 (v1), last revised 26 Mar 2026 (this version, v2)] Title:MindSet: Vision. A toolbox for testing DNNs on key psychological experiments Authors:Valerio Biscione, Milton L. Montero, Marin Dujmovic, Gaurav Malhotra, Dong Yin, Guillermo Puebla, Federico Adolfi, Rachel F. Heaton, John E. Hummel, Benjamin D. Evans, Karim Habashy, Jeffrey S. Bowers View a PDF of the paper titled MindSet: Vision. A toolbox for testing DNNs on key psychological experiments, by Valerio Biscione and 11 other authors View PDF Abstract:Multiple benchmarks have been developed to assess the alignment between deep neural networks (DNNs) and human vision. In almost all cases these benchmarks are observational in the sense they are composed of behavioural and brain responses to naturalistic images that have not been manipulated to test hypotheses regarding how DNNs or humans perceive and identify objects. Here we introduce the toolbox \textit{MindSet: Vision}, consisting of a collection of image datasets and related scripts designed to test DNNs on 30 psychological findings. In all experimental conditions, the stimuli are systematically manipulated to test specific hypotheses regarding human visual perception and object recognition. In addition to providing pre-generated datasets of images, we provide code to regenerate these datasets, offering many configurable parameters which greatly extend the datase...