activity
20172019
most citedGANosaic: Mosaic Creation with Generative Texture Manifolds

7 citations · 10 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV20193 cited

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…

cs.CV2019

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…

cs.CV2018

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…

cs.CV20177 cited

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…

stat.ML2017

The Conditional Analogy GAN: Swapping Fashion Articles on People Images

Nikolay Jetchev, Urs Bergmann

We present a novel method to solve image analogy problems : it allows to learn the relation between paired images present in training data, and then generalize and generate images…