2 citations · 2 across the 6 of their papers we have counts for
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cs.CV2021
Octree Transformer: Autoregressive 3D Shape Generation on Hierarchically Structured Sequences
Moritz Ibing, Gregor Kobsik, Leif Kobbelt
Autoregressive models have proven to be very powerful in NLP text generation tasks and lately have gained popularity for image generation as well. However, they have seen limited u…
cs.CV2021
Intuitive Shape Editing in Latent Space
Tim Elsner, Moritz Ibing, Victor Czech +2
The use of autoencoders for shape editing or generation through latent space manipulation suffers from unpredictable changes in the output shape. Our autoencoder-based method enabl…
cs.CV2021
3D Shape Generation with Grid-based Implicit Functions
Moritz Ibing, Isaak Lim, Leif Kobbelt
Previous approaches to generate shapes in a 3D setting train a GAN on the latent space of an autoencoder (AE). Even though this produces convincing results, it has two major shortc…