There is a growing body of work investigating the visual perception of material properties like gloss, yet practically nothing is known about how the brain recognizes different material classes like plastic, pearl, satin, and steel, nor the precise relationship between material properties like gloss and perceived material class. We report a series of experiments that show that parametrically changing reflectance parameters leads to qualitative changes in material appearance beyond those expected by the reflectance function used. We measure visual (image) features that predict these changes in appearance, and causally manipulate these features to confirm their role in perceptual categorization. Furthermore, our results suggest that the same visual features underlie both material recognition and surface gloss perception. However, the predictiveness of each feature to perceived gloss changes with material category, suggesting that the pockets of feature space occupied by different material classes affect the processing of those very features when estimating surface glossiness. Our results do not support a traditional feedforward view that assumes that material perception proceeds from low-level image measurements, to mid-level estimates of surface properties, to high-level material classes, nor the idea that material properties like gloss and material class are simultaneously “read out” from visual gloss features. Instead, we suggest that the perception and neural processing of material properties like surface gloss should be considered in the context of material recognition.