80 citations · 374 across the 49 of their papers we have counts for
9 papers · 2 filters
Multi-View Mesh Reconstruction with Neural Deferred Shading
Markus Worchel, Rodrigo Diaz, Weiwen Hu +3
We propose an analysis-by-synthesis method for fast multi-view 3D reconstruction of opaque objects with arbitrary materials and illumination. State-of-the-art methods use both neur…
Hyperspectral Demosaicing of Snapshot Camera Images Using Deep Learning
Eric L. Wisotzky, Charul Daudkhane, Anna Hilsmann +1
Spectral imaging technologies have rapidly evolved during the past decades. The recent development of single-camera-one-shot techniques for hyperspectral imaging allows multiple sp…
Recovering Fine Details for Neural Implicit Surface Reconstruction
Decai Chen, Peng Zhang, Ingo Feldmann +2
Recent works on implicit neural representations have made significant strides. Learning implicit neural surfaces using volume rendering has gained popularity in multi-view reconstr…
CASAPose: Class-Adaptive and Semantic-Aware Multi-Object Pose Estimation
Niklas Gard, Anna Hilsmann, Peter Eisert
Applications in the field of augmented reality or robotics often require joint localisation and 6D pose estimation of multiple objects. However, most algorithms need one network pe…
Perfusion assessment via local remote photoplethysmography (rPPG)
Benjamin Kossack, Eric Wisotzky, Peter Eisert +3
This paper presents an approach to assess the perfusion of visible human tissue from RGB video files. We propose metrics derived from remote photoplethysmography (rPPG) signals to…
Accurate Human Body Reconstruction for Volumetric Video
Decai Chen, Markus Worchel, Ingo Feldmann +2
In this work, we enhance a professional end-to-end volumetric video production pipeline to achieve high-fidelity human body reconstruction using only passive cameras. While current…
Imposing Temporal Consistency on Deep Monocular Body Shape and Pose Estimation
Alexandra Zimmer, Anna Hilsmann, Wieland Morgenstern +1
Accurate and temporally consistent modeling of human bodies is essential for a wide range of applications, including character animation, understanding human social behavior and AR…
From Explanations to Segmentation: Using Explainable AI for Image Segmentation
Clemens Seibold, Johannes Künzel, Anna Hilsmann +1
The new era of image segmentation leveraging the power of Deep Neural Nets (DNNs) comes with a price tag: to train a neural network for pixel-wise segmentation, a large amount of t…
Combining Local and Global Pose Estimation for Precise Tracking of Similar Objects
Niklas Gard, Anna Hilsmann, Peter Eisert
In this paper, we present a multi-object 6D detection and tracking pipeline for potentially similar and non-textured objects. The combination of a convolutional neural network for…