An image-computable model of human visual shape similarity
Fig 7
ShapeComp predicts perceptual uniformities in human shape similarity across shape arrays.
(A,B,C,D) The top row shows four example 2D shape arrays that are roughly uniform in ShapeComp and highly correlated to the GAN arrangement (r>0.9). The bottom row shows the mean arrangement by 16 human observers. (E) In 3 out of 4 shape sets that are highly correlated in terms of GAN and ShapeComp arrangements, human responses are nearly indistinguishable from the predictions of ShapeComp (blue), given the inherent noise across observers measured as the lower noise ceiling (red; 95% confidence interval showing correlation of each participant’s data with mean of others). Error bars (in black) show 95% confidence interval around human-model correlation.