80 citations · 374 across the 49 of their papers we have counts for
15 papers · 1 filter
Multi-task Planar Reconstruction with Feature Warping Guidance
Luan Wei, Anna Hilsmann, Peter Eisert
Piece-wise planar 3D reconstruction simultaneously segments plane instances and recovers their 3D plane parameters from an image, which is particularly useful for indoor or man-mad…
Multispectral Stereo-Image Fusion for 3D Hyperspectral Scene Reconstruction
Eric L. Wisotzky, Jost Triller, Anna Hilsmann +1
Spectral imaging enables the analysis of optical material properties that are invisible to the human eye. Different spectral capturing setups, e.g., based on filter-wheel, push-bro…
Towards Better Morphed Face Images without Ghosting Artifacts
Clemens Seibold, Anna Hilsmann, Peter Eisert
Automatic generation of morphed face images often produces ghosting artifacts due to poorly aligned structures in the input images. Manual processing can mitigate these artifacts.…
Multi-view Inversion for 3D-aware Generative Adversarial Networks
Florian Barthel, Anna Hilsmann, Peter Eisert
Current 3D GAN inversion methods for human heads typically use only one single frontal image to reconstruct the whole 3D head model. This leaves out meaningful information when mul…
Compact 3D Scene Representation via Self-Organizing Gaussian Grids
Wieland Morgenstern, Florian Barthel, Anna Hilsmann +1
3D Gaussian Splatting has recently emerged as a highly promising technique for modeling of static 3D scenes. In contrast to Neural Radiance Fields, it utilizes efficient rasterizat…
Animating NeRFs from Texture Space: A Framework for Pose-Dependent Rendering of Human Performances
Paul Knoll, Wieland Morgenstern, Anna Hilsmann +1
Creating high-quality controllable 3D human models from multi-view RGB videos poses a significant challenge. Neural radiance fields (NeRFs) have demonstrated remarkable quality in…
Animatable Virtual Humans: Learning pose-dependent human representations in UV space for interactive performance synthesis
Wieland Morgenstern, Milena T. Bagdasarian, Anna Hilsmann +1
We propose a novel representation of virtual humans for highly realistic real-time animation and rendering in 3D applications. We learn pose dependent appearance and geometry from…
BTSeg: Barlow Twins Regularization for Domain Adaptation in Semantic Segmentation
Johannes Künzel, Anna Hilsmann, Peter Eisert
We introduce BTSeg (Barlow Twins regularized Segmentation), an innovative, semi-supervised training approach enhancing semantic segmentation models in order to effectively tackle a…
A differentiable Gaussian Prototype Layer for explainable Segmentation
Michael Gerstenberger, Steffen Maaß, Peter Eisert +1
We introduce a Gaussian Prototype Layer for gradient-based prototype learning and demonstrate two novel network architectures for explainable segmentation one of which relies on re…
Automatic Reconstruction of Semantic 3D Models from 2D Floor Plans
Aleixo Cambeiro Barreiro, Mariusz Trzeciakiewicz, Anna Hilsmann +1
Digitalization of existing buildings and the creation of 3D BIM models for them has become crucial for many tasks. Of particular importance are floor plans, which contain informati…
Unsupervised Learning of Style-Aware Facial Animation from Real Acting Performances
Wolfgang Paier, Anna Hilsmann, Peter Eisert
This paper presents a novel approach for text/speech-driven animation of a photo-realistic head model based on blend-shape geometry, dynamic textures, and neural rendering. Trainin…
Fooling State-of-the-Art Deepfake Detection with High-Quality Deepfakes
Arian Beckmann, Anna Hilsmann, Peter Eisert
Due to the rising threat of deepfakes to security and privacy, it is most important to develop robust and reliable detectors. In this paper, we examine the need for high-quality sa…
Towards L-System Captioning for Tree Reconstruction
Jannes S. Magnusson, Anna Hilsmann, Peter Eisert
This work proposes a novel concept for tree and plant reconstruction by directly inferring a Lindenmayer-System (L-System) word representation from image data in an image captionin…
System for 3D Acquisition and 3D Reconstruction using Structured Light for Sewer Line Inspection
Johannes Künzel, Darko Vehar, Rico Nestler +3
The assessment of sewer pipe systems is a highly important, but at the same time cumbersome and error-prone task. We introduce an innovative system based on single-shot structured…
Dynamic Multi-View Scene Reconstruction Using Neural Implicit Surface
Decai Chen, Haofei Lu, Ingo Feldmann +2
Reconstructing general dynamic scenes is important for many computer vision and graphics applications. Recent works represent the dynamic scene with neural radiance fields for phot…