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Reference-GAN (updated on 2/28/2020)

https://pathmind.com/wiki/generative-adversarial-network-gan Notes: Discriminative models learn the boundary between classes Generative models model the distribution of individual classes i.e. the discriminator decides whether each instance of data that it reviews belongs to the actual training dataset or not. Here are the steps a GAN takes: The generator takes in random numbers and returns an image. This generated image is fed into the discriminator alongside a stream of images taken from the actual, ground-truth dataset. The discriminator takes in both real and fake images and returns probabilities, a number between 0 and 1, with 1 representing a prediction of authenticity and 0 representing fake. https://ai.googleblog.com/2017/12/introducing-new-foveation-pipeline-for.html Notes: However, current VR/MR technologies present a fundamental challenge: to present images at the extremely high resolution required for immer...
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Project Progress and Research 3nd round

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Project Progress: In the search of overcoming the incompability of RaymarchingToolkit among different renderers, I eventually found one that could be used on latest RP. This new Toolkit does have the melting effect as the previous one, what it's able to do is to separate a single cube into mutiple hexgons, the amount of which only depends on the scale of cube. I thinks it's pretty fit for the candle body. Also, I'm also trying to give my scene a table cloth as physical-realistic as possible. Fortunately, I found something really interesting. https://github.com/Ninjajie/Fusion#cloth-plugin-user-guide The plugin realized physical object simulation in unity based on Physical-Based-Dynamic, which is not perfectly accurate as physical stuff but fast enough for real-time rendering. Furthermore, authors had a comparsion of the same althorigm between CPU and GPU. They used compute shaders with HLSL for caculations on GPU. I tried to do the simulation and the differenc...
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Failure and New Research

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I tried many ways to fix the issues, but none of them worked, not even on github. One of the packages 'climin' has very rare information online and is barely used. Also, the compatibility between python version and blender is very uncertain, I'm not sure which one would work, so I gave up this AI stuff and tried to look into something new. https://www.youtube.com/watch?v=JVlfSjkvefE There is a image to material tool, materialize, which is able to edit a picture into material with diffuse,normal,metallic maps and etc. After you created the project, it's also easy to import to unity. Maybe I could build up something upon that.
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