  We present a machine learning approach for efficiently computing order
independent transparency (OIT). Our method is fast, requires a small constant
amount of memory (depends only on the screen resolution and not on the number
of triangles or transparent layers), is more accurate as compared to previous
approximate methods, works for every scene without setup and is portable to all
platforms running even with commodity GPUs. Our method requires a rendering
pass to extract all features that are subsequently used to predict the overall
OIT pixel color with a pre-trained neural network. We provide a comparative
experimental evaluation and shader source code of all methods for reproduction
of the experiments.
