147 citations · 351 across the 22 of their papers we have counts for
10 papers · 1 filter
GIRAFFE: Representing Scenes as Compositional Generative Neural Feature Fields
Michael Niemeyer, Andreas Geiger
Deep generative models allow for photorealistic image synthesis at high resolutions. But for many applications, this is not enough: content creation also needs to be controllable.…
HOTA: A Higher Order Metric for Evaluating Multi-Object Tracking
Jonathon Luiten, Aljosa Osep, Patrick Dendorfer +4
Multi-Object Tracking (MOT) has been notoriously difficult to evaluate. Previous metrics overemphasize the importance of either detection or association. To address this, we presen…
Category Level Object Pose Estimation via Neural Analysis-by-Synthesis
Xu Chen, Zijian Dong, Jie Song +2
Many object pose estimation algorithms rely on the analysis-by-synthesis framework which requires explicit representations of individual object instances. In this paper we combine…
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…
Learning Neural Light Transport
Paul Sanzenbacher, Lars Mescheder, Andreas Geiger
In recent years, deep generative models have gained significance due to their ability to synthesize natural-looking images with applications ranging from virtual reality to data au…
Intrinsic Autoencoders for Joint Neural Rendering and Intrinsic Image Decomposition
Hassan Abu Alhaija, Siva Karthik Mustikovela, Justus Thies +4
Neural rendering techniques promise efficient photo-realistic image synthesis while at the same time providing rich control over scene parameters by learning the physical image for…