An image-computable model of human visual shape similarity
Fig 4
Interpreting ShapeComp dimensions.
Example GAN shapes that vary along the first 6 MDS dimensions. Two shapes (in black) are varied along one dimension (in different colours, dimensions 1–6) while the remaining dimensions are held roughly constant. The different GAN shapes that varied in their MDS coordinates were optimized with a genetic algorithm from MATLAB’s global optimization toolbox to reduce RMS error between a GAN shapes 22-D representation and a desired 22-D representation.