End-to-end rapid reconstruction method for gas scene under limited view
A gas and scene technology, applied in neural learning methods, instruments, biological neural network models, etc., can solve problems such as complex, time-consuming optimization and discrete operations, and achieve the effects of ensuring realism, avoiding optimized calculations, and efficient calculations
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[0052] See attached figure 1 , the present invention performs fluid animation parameter estimation and detail enhancement according to the following steps:
[0053] (1) Preliminary estimation of density field based on generative model
[0054] a. Set a random initial smoke source and velocity field, generate and collect the density field of the simulated fluid through the Euler method, and the corresponding front view and side view as training samples and generate a training data set.
[0055] b. Construct and train the conditional generation network; use the trained network to generate the density field by inputting the front view and side view sequences of the fluid animation, and obtain the preliminary density field reconstruction result.
[0056] (2) Velocity field reconstruction based on convolutional neural network
[0057] a. Collect the gas scene data generated by the Euler method as a training sample and generate a training data set, mainly including the velocity fi...
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