41 citations · 64 across the 7 of their papers we have counts for
6 papers · 1 filter
Synthesizing 3D Abstractions by Inverting Procedural Buildings with Transformers
Maximilian Dax, Jordi Berbel, Jan Stria +2
We generate abstractions of buildings, reflecting the essential aspects of their geometry and structure, by learning to invert procedural models. We first build a dataset of abstra…
Transform the Set: Memory Attentive Generation of Guided and Unguided Image Collages
Nikolay Jetchev, Urs Bergmann, Gökhan Yildirim
Cutting and pasting image segments feels intuitive: the choice of source templates gives artists flexibility in recombining existing source material. Formally, this process takes a…
Generating High-Resolution Fashion Model Images Wearing Custom Outfits
Gökhan Yildirim, Nikolay Jetchev, Roland Vollgraf +1
Visualizing an outfit is an essential part of shopping for clothes. Due to the combinatorial aspect of combining fashion articles, the available images are limited to a pre-determi…
Copy the Old or Paint Anew? An Adversarial Framework for (non-) Parametric Image Stylization
Nikolay Jetchev, Urs Bergmann, Gokhan Yildirim
Parametric generative deep models are state-of-the-art for photo and non-photo realistic image stylization. However, learning complicated image representations requires compute-int…
Disentangling Multiple Conditional Inputs in GANs
Gökhan Yildirim, Calvin Seward, Urs Bergmann
In this paper, we propose a method that disentangles the effects of multiple input conditions in Generative Adversarial Networks (GANs). In particular, we demonstrate our method in…
GANosaic: Mosaic Creation with Generative Texture Manifolds
Nikolay Jetchev, Urs Bergmann, Calvin Seward
This paper presents a novel framework for generating texture mosaics with convolutional neural networks. Our method is called GANosaic and performs optimization in the latent noise…