activity
20182020
most citedYou Only Need Adversarial Supervision for Semantic Image Synthesis

70 citations · 72 across the 2 of their papers we have counts for

collaborators

7 papers

cs.CV202070 cited

You Only Need Adversarial Supervision for Semantic Image Synthesis

Vadim Sushko, Edgar Schönfeld, Dan Zhang +3

Despite their recent successes, GAN models for semantic image synthesis still suffer from poor image quality when trained with only adversarial supervision. Historically, additiona…

cs.CV20202 cited

Improving Augmentation and Evaluation Schemes for Semantic Image Synthesis

Prateek Katiyar, Anna Khoreva

Despite data augmentation being a de facto technique for boosting the performance of deep neural networks, little attention has been paid to developing augmentation strategies for…

cs.CV2020

A U-Net Based Discriminator for Generative Adversarial Networks

Edgar Schönfeld, Bernt Schiele, Anna Khoreva

Among the major remaining challenges for generative adversarial networks (GANs) is the capacity to synthesize globally and locally coherent images with object shapes and textures i…

cs.CV2019

Grid Saliency for Context Explanations of Semantic Segmentation

Lukas Hoyer, Mauricio Munoz, Prateek Katiyar +2

Recently, there has been a growing interest in developing saliency methods that provide visual explanations of network predictions. Still, the usability of existing methods is limi…

cs.CV2019

Progressive Augmentation of GANs

Dan Zhang, Anna Khoreva

Training of Generative Adversarial Networks (GANs) is notoriously fragile, requiring to maintain a careful balance between the generator and the discriminator in order to perform w…

cs.CV2018

Learning to Refine Human Pose Estimation

Mihai Fieraru, Anna Khoreva, Leonid Pishchulin +1

Multi-person pose estimation in images and videos is an important yet challenging task with many applications. Despite the large improvements in human pose estimation enabled by th…