Computational origins of shape perception
Fig 8
Training generic fitting models with different artificial image augmentations.
(a) Generic fitting models trained with no artificial image augmentations developed color-based representational spaces, as shown in the RDMs (top) and color/shape scores (bottom). (b-d) Likewise, generic fitting models trained with gaussian blur, horizontal flip, or random cropping developed color-based representational spaces. (e-f) Conversely, generic fitting models trained with color jitter or grayscale developed shape-based representational spaces. For all RDMs, the images used to make the RDMs were the same as those used in Fig 1. Error bars denote standard error for each model across the color cells and shape cells shown in Fig 1b, c.