The success of neural fields for 3D vision tasks is now indisputable. Following this trend,
several methods aiming for visual localization (eg, SLAM) have been proposed to estimate …

Omnidirectional videos capture environmental scenes effectively, but they have rarely been
used for geometry reconstruction. In this work, we propose an egocentric 3D reconstruction …

Abstract We propose POse-guided SElective Fusion (POSEFusion), a single-view human
volumetric capture method that leverages tracking-based methods and tracking-free …

Efficient photorealistic scene capture is a challenging task. Current online reconstruction
systems can operate very efficiently, but images generated from the models captured by …

A valuable aspect during crime scene investigation is the digital documentation of the scene.
Traditional means of documentation include photography and in situ measurements from …

Fine-detailed reconstructions are in high demand in many applications. However, most of
the existing RGB-D reconstruction methods rely on pre-calculated accurate camera poses to …

We present Gradient-SDF, a novel representation for 3D geometry that combines the
advantages of implict and explicit representations. By storing at every voxel both the signed …

The registration of time-varying 3D shapes with high degrees of freedom remains a
challenging task. Most existing techniques attempt to address this issue by solving an …

Restoring high-fidelity textures for 3D reconstructed models are an increasing demand in
AR/VR, cultural heritage protection, entertainment, and other relevant fields. Due to …

We present DeepSurfels, a novel hybrid scene representation for geometry and appearance
information. DeepSurfels combines explicit and neural building blocks to jointly encode …