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Johannes Merz

2 accepted papers

2022

UNIST: Unpaired Neural Implicit Shape Translation Network

CVPR 2022poster

We introduce UNIST, the first deep neural implicit model for general-purpose, unpaired shape-to-shape translation, in both 2D and 3D domains. Our model is built on autoencoding implicit fields, rather than point clouds which represents the state of the art. Furthermore, our translation network is tr…

Cited by 9PDFcodeScholar
2020

GANHopper: Multi-Hop GAN for Unsupervised Image-to-Image Translation

ECCV 2020poster

We introduce GANHopper, an unsupervised image-to-image translation network that transforms images gradually between two domains, through multiple hops. Instead of executing translation directly, we steer the translation by requiring the network to produce in-between images that resemble weighted hyb…

Cited by 31SourcePDFScholar