80 citations · 374 across the 49 of their papers we have counts for
47 papers · 1 filter
Cross-Spectral Dense Correspondence for Multimodal Spectral Medical Imaging
Eric L. Wisotzky, Jost Triller, Simon W. Härtl +3
Precise dense correspondence is a fundamental prerequisite for multimodal spectral imaging systems that fuse disparate wavelength ranges for subsequent analysis in medical and scie…
RIPE: Reinforcement Learning on Unlabeled Image Pairs for Robust Keypoint Extraction
Johannes Künzel, Anna Hilsmann, Peter Eisert
We introduce RIPE, an innovative reinforcement learning-based framework for weakly-supervised training of a keypoint extractor that excels in both detection and description tasks.…
CGS-GAN: 3D Consistent Gaussian Splatting GANs for High Resolution Human Head Synthesis
Florian Barthel, Wieland Morgenstern, Paul Hinzer +2
Recently, 3D GANs based on 3D Gaussian splatting have been proposed for high quality synthesis of human heads. However, existing methods stabilize training and enhance rendering qu…
SPNeRF: Open Vocabulary 3D Neural Scene Segmentation with Superpoints
Weiwen Hu, Niccolò Parodi, Marcus Zepp +3
Open-vocabulary segmentation, powered by large visual-language models like CLIP, has expanded 2D segmentation capabilities beyond fixed classes predefined by the dataset, enabling…
Improving Adaptive Density Control for 3D Gaussian Splatting
Glenn Grubert, Florian Barthel, Anna Hilsmann +1
3D Gaussian Splatting (3DGS) has become one of the most influential works in the past year. Due to its efficient and high-quality novel view synthesis capabilities, it has been wid…
Improving Geometric Consistency for 360-Degree Neural Radiance Fields in Indoor Scenarios
Iryna Repinetska, Anna Hilsmann, Peter Eisert
Photo-realistic rendering and novel view synthesis play a crucial role in human-computer interaction tasks, from gaming to path planning. Neural Radiance Fields (NeRFs) model scene…
Automatic Drywall Analysis for Progress Tracking and Quality Control in Construction
Mariusz Trzeciakiewicz, Aleixo Cambeiro Barreiro, Niklas Gard +2
Digitalization in the construction industry has become essential, enabling centralized, easy access to all relevant information of a building. Automated systems can facilitate the…
Creating Sorted Grid Layouts with Gradient-based Optimization
Kai Uwe Barthel, Florian Tim Barthel, Peter Eisert +2
Visually sorted grid layouts provide an efficient method for organizing high-dimensional vectors in two-dimensional space by aligning spatial proximity with similarity relationship…
Multi-Resolution Generative Modeling of Human Motion from Limited Data
David Eduardo Moreno-Villamarín, Anna Hilsmann, Peter Eisert
We present a generative model that learns to synthesize human motion from limited training sequences. Our framework provides conditional generation and blending across multiple tem…
Adaptive and Temporally Consistent Gaussian Surfels for Multi-view Dynamic Reconstruction
Decai Chen, Brianne Oberson, Ingo Feldmann +3
3D Gaussian Splatting has recently achieved notable success in novel view synthesis for dynamic scenes and geometry reconstruction in static scenes. Building on these advancements,…
3DGS.zip: A survey on 3D Gaussian Splatting Compression Methods
Milena T. Bagdasarian, Paul Knoll, Yi-Hsin Li +4
3D Gaussian Splatting (3DGS) has emerged as a cutting-edge technique for real-time radiance field rendering, offering state-of-the-art performance in terms of both quality and spee…
Gaussian Splatting Decoder for 3D-aware Generative Adversarial Networks
Florian Barthel, Arian Beckmann, Wieland Morgenstern +2
NeRF-based 3D-aware Generative Adversarial Networks (GANs) like EG3D or GIRAFFE have shown very high rendering quality under large representational variety. However, rendering with…
SPVLoc: Semantic Panoramic Viewport Matching for 6D Camera Localization in Unseen Environments
Niklas Gard, Anna Hilsmann, Peter Eisert
In this paper, we present SPVLoc, a global indoor localization method that accurately determines the six-dimensional (6D) camera pose of a query image and requires minimal scene-sp…
Video-Driven Animation of Neural Head Avatars
Wolfgang Paier, Paul Hinzer, Anna Hilsmann +1
We present a new approach for video-driven animation of high-quality neural 3D head models, addressing the challenge of person-independent animation from video input. Typically, hi…
X-maps: Direct Depth Lookup for Event-based Structured Light Systems
Wieland Morgenstern, Niklas Gard, Simon Baumann +2
We present a new approach to direct depth estimation for Spatial Augmented Reality (SAR) applications using event cameras. These dynamic vision sensors are a great fit to be paired…
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…
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…