Papers by Gerhard Roethlin


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Denoising with Kernel Prediction and Asymmetric Loss Functions

Thijs Vogels, Fabrice Rouselle, Brian McWilliams, Gerhard Roethlin, Alex Harvill, David Adler, Mark Meyer, Jan Novak
May 2018

We present a modular convolutional architecture for denoising rendered images. We expand on the capabilities of kernel-predicting networks by combining them with a number of task-specific modules, and optimizing the assembly using an asymmetric loss. The source aware encoder - the first module in the assembly - extracts ... more

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