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Exploring Generative 3D Shapes Using Autoencoder Networks
Autodesk Research
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Procedural Modeling Using Autoencoder Networks
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3D Shape Variational Autoencoder Latent Disentanglement via Mini Batch Feature Swapping | CVPR 2022
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PQ-NET: A Generative Part Seq2Seq Network for 3D Shapes
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WACV18: 3D Shape Processing by Convolutional Denoising Autoencoders on Local Patches
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An Autoencoder for 3D Geometries of Atomic Structures [...] | AI & Molecular World | Tess E. Smidt
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Learning to generate 3D shapes with Generative Cellular Automata
3D Vision Lab at the Seoul National University
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