A machine learning system receives a reference image and generates a series of projected view images of a physical object represented in the images. Parallel neural networks may receive the reference image and series of projected view images for analysis to determine one or more features of the physical object. By pooling the results from the parallel network, a single output may be provided to a set of decodes that are trained to identify a material property of the one or more items. As a result, a three-dimensional model may be generated that includes a graphical representation of the object as a function of its material properties to enable improved rendering.