Efficient Neural Style Transfer For Fluid Simulations
摘要:
A system includes a hardware processor, and a system memory storing a software code and a machine learning (ML) model trained to apply a stylization to an image. The hardware processor executes the software code to receive a first sequence of images and style data describing a desired stylization of content depicted by the first sequence of images. The hardware processor further executes the software code to stylize the content, using the ML model, to provide a stylized content having the desired stylization, wherein stylizing includes applying an exponential moving average (EMA) temporal smoothing algorithm to sequential image pairs of the first sequence of images to generate a second sequence of images providing a depiction of the content having the desired stylization, and output the stylized content having the desired stylization.
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