Tag Archives: PBR

Neural material (de)compression – data-driven nonlinear dimensionality reduction

In this post I come back to something I didn’t expect coming back to – dimensionality reduction and compression for whole material texture sets (as opposed to single textures) – a significantly underexplored topic. In one of my past posts … Continue reading

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Compressing PBR material texture sets with sparsity and k-SVD dictionary learning

Introduction In this blog post, I am going to continue exploration of compressing whole PBR texture sets together (as opposed to compressing each texture from the set separately) and using the fact that those textures are strongly correlated. In my … Continue reading

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Dimensionality reduction for image and texture set compression

In this blog post I am going to describe some of my past investigations on reducing the number of channels in textures / texture sets automatically and generally – without assuming anything about texture contents other than correspondence to some … Continue reading

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White balance and physically based rendering pipelines. Part 2 – practical problems.

White balance and lighting conditions After this long introduction (be sure to check part one if you haven’t!), we can finally go to the problem that started whole idea for this post (as in my opinion it is unsolved problem – … Continue reading

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White balance and physically based rendering pipelines. Part 1 – introduction.

This is part one of the whole article. Part two is here. In this two posts (started as one, but I had to split it to make it more… digestible) I’m going to talk a bit about the white balance. First … Continue reading

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