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Inverse Graphics GAN: Learning to Generate 3D Shapes from Unstructured 2D Data

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IGGAN

Unoffical code for the research paper Inverse Graphics GAN.

Under construction.

RenderNet

Includes a PyTorch implementation of RenderNet as a necessary part of the architecture.

movie.mp4

Notes

CUDA training requires about 10G of VRAM.

Credits

Generator architecture based on 3DGAN-PyTorch.

RenderNet architecture is original code referencing the TensorFlow implementation of RenderNet, since it seems to conflict heavily with the architecture as described in the paper.

SpectralNorm code taken from pytorch-spectral-normalization-gan.

Discriminator architecture based on the PyTorch example DCGAN.

Binvox handling taken from binvox-rw-py.

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Inverse Graphics GAN: Learning to Generate 3D Shapes from Unstructured 2D Data

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