510 citations · 652 across the 8 of their papers we have counts for
10 papers · 1 filter
Surf: Implicit Surface Reconstruction for Semi-Transparent and Thin Objects with Decoupled Geometry and Opacity
Tianhao Wu, Hanxue Liang, Fangcheng Zhong +4
Implicit surface representations such as the signed distance function (SDF) have emerged as a promising approach for image-based surface reconstruction. However, existing optimizat…
Stable View Synthesis
Gernot Riegler, Vladlen Koltun
We present Stable View Synthesis (SVS). Given a set of source images depicting a scene from freely distributed viewpoints, SVS synthesizes new views of the scene. The method operat…
NeRF++: Analyzing and Improving Neural Radiance Fields
Kai Zhang, Gernot Riegler, Noah Snavely +1
Neural Radiance Fields (NeRF) achieve impressive view synthesis results for a variety of capture settings, including 360 capture of bounded scenes and forward-facing capture of bou…
Free View Synthesis
Gernot Riegler, Vladlen Koltun
We present a method for novel view synthesis from input images that are freely distributed around a scene. Our method does not rely on a regular arrangement of input views, can syn…
OctNetFusion: Learning Depth Fusion from Data
Gernot Riegler, Ali Osman Ulusoy, Horst Bischof +1
In this paper, we present a learning based approach to depth fusion, i.e., dense 3D reconstruction from multiple depth images. The most common approach to depth fusion is based on…
OctNet: Learning Deep 3D Representations at High Resolutions
Gernot Riegler, Ali Osman Ulusoy, Andreas Geiger
We present OctNet, a representation for deep learning with sparse 3D data. In contrast to existing models, our representation enables 3D convolutional networks which are both deep…
A Deep Primal-Dual Network for Guided Depth Super-Resolution
Gernot Riegler, David Ferstl, Matthias Rüther +1
In this paper we present a novel method to increase the spatial resolution of depth images. We combine a deep fully convolutional network with a non-local variational method in a d…
ATGV-Net: Accurate Depth Super-Resolution
Gernot Riegler, Matthias Rüther, Horst Bischof
In this work we present a novel approach for single depth map super-resolution. Modern consumer depth sensors, especially Time-of-Flight sensors, produce dense depth measurements,…
Efficiently Creating 3D Training Data for Fine Hand Pose Estimation
Markus Oberweger, Gernot Riegler, Paul Wohlhart +1
While many recent hand pose estimation methods critically rely on a training set of labelled frames, the creation of such a dataset is a challenging task that has been overlooked s…
Filament and Flare Detection in Hα image sequences
Gernot Riegler, Thomas Pock, Werner Pötzi +1
Solar storms can have a major impact on the infrastructure of the earth. Some of the causing events are observable from ground in the Hα spectral line. In this paper we propose a n…