6 papers
Comparing Commercial Depth Sensor Accuracy for Medical Applications
Pit Henrich, Maximilian Weiherer, Franziska Hansen +2
Depth estimation has numerous medical and surgical applications. We benchmark four depth sensors on a porcine bone specimen, a porcine belly specimen, and a silicone kidney phantom…
Learning Neural Parametric 3D Breast Shape Models for Metrical Surface Reconstruction From Monocular RGB Videos
Maximilian Weiherer, Antonia von Riedheim, Vanessa Brébant +2
We present a neural parametric 3D breast shape model and, based on this model, introduce a low-cost and accessible 3D surface reconstruction pipeline capable of recovering accurate…
Multi-Spectral Gaussian Splatting with Neural Color Representation
Lukas Meyer, Josef Grün, Maximilian Weiherer +3
We present MS-Splatting -- a multi-spectral 3D Gaussian Splatting (3DGS) framework that is able to generate multi-view consistent novel views from images of multiple, independent c…
Matérn Kernels for Tunable Implicit Surface Reconstruction
Maximilian Weiherer, Bernhard Egger
We propose to use the family of Matérn kernels for implicit surface reconstruction, building upon the recent success of kernel methods for 3D reconstruction of oriented point clou…
Towards Integrating Multi-Spectral Imaging with Gaussian Splatting
Josef Grün, Lukas Meyer, Maximilian Weiherer +3
We present a study of how to integrate color (RGB) and multi-spectral imagery (red, green, red-edge, and near-infrared) into the 3D Gaussian Splatting (3DGS) framework, a state-of-…
iRBSM: A Deep Implicit 3D Breast Shape Model
Maximilian Weiherer, Antonia von Riedheim, Vanessa Brébant +2
We present the first deep implicit 3D shape model of the female breast, building upon and improving the recently proposed Regensburg Breast Shape Model (RBSM). Compared to its PCA-…