20 citations · 21 across the 4 of their papers we have counts for
6 papers
ARAH: Animatable Volume Rendering of Articulated Human SDFs
Shaofei Wang, Katja Schwarz, Andreas Geiger +1
Combining human body models with differentiable rendering has recently enabled animatable avatars of clothed humans from sparse sets of multi-view RGB videos. While state-of-the-ar…
StyleGAN-XL: Scaling StyleGAN to Large Diverse Datasets
Axel Sauer, Katja Schwarz, Andreas Geiger
Computer graphics has experienced a recent surge of data-centric approaches for photorealistic and controllable content creation. StyleGAN in particular sets new standards for gene…
On the Frequency Bias of Generative Models
Katja Schwarz, Yiyi Liao, Andreas Geiger
The key objective of Generative Adversarial Networks (GANs) is to generate new data with the same statistics as the provided training data. However, multiple recent works show that…
GRAF: Generative Radiance Fields for 3D-Aware Image Synthesis
Katja Schwarz, Yiyi Liao, Michael Niemeyer +1
While 2D generative adversarial networks have enabled high-resolution image synthesis, they largely lack an understanding of the 3D world and the image formation process. Thus, the…
Towards Unsupervised Learning of Generative Models for 3D Controllable Image Synthesis
Yiyi Liao, Katja Schwarz, Lars Mescheder +1
In recent years, Generative Adversarial Networks have achieved impressive results in photorealistic image synthesis. This progress nurtures hopes that one day the classical renderi…
Multi-Scale Convolutions for Learning Context Aware Feature Representations
Nikolai Ufer, Kam To Lui, Katja Schwarz +2
Finding semantic correspondences is a challenging problem. With the breakthrough of CNNs stronger features are available for tasks like classification but not specifically for the…