Chenxi Liao

This study explores the relationship between visual perception and language in material recognition using psychophysics and unsupervised learning, finding moderate correlation but structural differences in representations.

This paper uses an unsupervised image generation model to discover latent features related to material perception, finding that translucency is encoded in mid-scale features.

This study investigates how color affects perception of translucent materials using real-world object photographs, finding that color improves agreement and accuracy in material classification and attribute ratings.