THE GEOMETRY OF DEEP GENERATIVE IMAGE MODELS AND ITS APPLICATIONS

This paper aims to make GAN inversion and interpretability possible. Through the lens of differential geometry, the authors propose that the metric tensor has various interpretability properties – by realising it as the Hessian matrix of the distance metric.

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