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A Generative Model for Volume Rendering
2018
IEEE Transactions on Visualization and Computer Graphics
We present a technique to synthesize and analyze volume-rendered images using generative models. We use the Generative Adversarial Network (GAN) framework to compute a model from a large collection of volume renderings, conditioned on (1) viewpoint and (2) transfer functions for opacity and color. Our approach facilitates tasks for volume analysis that are challenging to achieve using existing rendering techniques such as ray casting or texture-based methods. We show how to guide the user in
doi:10.1109/tvcg.2018.2816059
pmid:29993811
fatcat:jqfaopyry5c6pj64ouvuc4hgm4