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2025 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops, WACVW 2025

作者： Klenert, Nicolas Schwoerer, Finn Hajarolasvadi, Noushin Bournez, Siloé Arlt, Tobias Mahnke, Heinz-Eberhard Lepper, Verena Baum, Daniel Zuse Institute Berlin Department of Visual and Data-Centric Computing Berlin Germany Helmholtz-Zentrum Berlin für Materialien und Energie Berlin Germany Ägyptisches Museum und Papyrussammlung Staatliche Museen zu Berlin Berlin Germany

ISBN: (纸本)9798331536626

The non-invasive digital unfolding of ancient documents, such as folded papyrus packages, from 3D image data aims to reveal previously hidden writing without risking to damage the precious documents. One of the main tasks in this process is the geometric reconstruction of the writing sub-strate, which is a prerequisite for its subsequent unfolding. All current reconstruction methods require the existence of an interspace between different layers of the document to ensure a correct topology. Layers that appear merged to-gether in the 3D image often result in wrong connections between layers and thus also in a wrong topology of the reconstructed geometry, which hinders the successful unfolding. Here, we propose to use a neural network to facilitate the discrimination of the layers. Using papyrus documents as an example of a particularly difficult writing material, we show that our approach significantly reduces the number of wrong connections and improves the overall identification of the layers. This in turn enables fully automatic digital unfolding of large areas of highly complex papyrus packages. Utilizing explainable AI (XAI) further allows us to explore the results of the applied neural network. © 2025 IEEE.

关键词： Three dimensional computer graphics

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How did we get there? AI applications to biological networks and sequences

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Computers in Biology and Medicine 2025年 190卷 110064-110064页

作者： Anteghini, Marco Gualdi, Francesco Oliva, Baldo Structural Bioinformatics Lab Universitat Pompeu Fabra Barcelona Spain University of Bologna Bologna Italy Visual and Data-Centric Computing Zuse Institut Berlin Berlin Germany Lugano Switzerland

The rapidly advancing field of artificial intelligence (AI) has transformed numerous scientific domains, including biology, where a vast and complex volume of data is available for analysis. This paper provides a comprehensive overview of the current state of AI-driven methodologies in genomics, proteomics, and systems biology. We discuss how machine learning algorithms, particularly deep learning models, have enhanced the accuracy and efficiency of embedding sequences, motif discovery, and the prediction of gene expression and protein structure. Additionally, we explore the integration of AI in the embedding and analysis of biological networks, including protein–protein interaction networks and multi-layered networks. By leveraging large-scale biological data, AI techniques have enabled unprecedented insights into complex biological processes and disease mechanisms. This work underlines the potential of applying AI to complex biological data, highlighting current applications and suggesting directions for future research to further explore AI in this rapidly evolving field. © 2025 The Authors

关键词： Adversarial machine learning

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Improving the Identification of Layers in 3D Images of Ancient Papyrus Using Artificial Neural Networks

Improving the Identification of Layers in 3D Images of Ancie...

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IEEE Winter Applications and Computer Vision Workshops (WACVW)

作者： Nicolas Klenert Finn Schwoerer Noushin Hajarolasvadi Siloé Bournez Tobias Arlt Heinz-Eberhard Mahnke Verena Lepper Daniel Baum Department of Visual and Data-Centric Computing Zuse Institute Berlin Berlin Germany Helmholtz-Zentrum Berlin für Materialien und Energie Berlin Germany Ägyptisches Museum und Papyrussammlung Staatliche Museen zu Berlin Berlin Germany

ISBN: (数字)9798331536626

ISBN: (纸本)9798331536633

关键词： Geometry Computer vision Three-dimensional displays Network topology Explainable AI Conferences Writing Reconstruction algorithms Topology Image reconstruction

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Geodesic B-score for improved assessment of knee osteoarthritis

arXiv

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arXiv 2021年

作者： Ambellan, Felix Zachow, Stefan von Tycowicz, Christoph Visual and Data-centric Computing Zuse Institute Berlin Berlin Germany

Three-dimensional medical imaging enables detailed understanding of osteoarthritis structural status. However, there remains a vast need for automatic, thus, reader-independent measures that provide reliable assessment of subject-specific clinical outcomes. To this end, we derive a consistent generalization of the recently proposed B-score to Riemannian shape spaces. We further present an algorithmic treatment yielding simple, yet efficient computations allowing for analysis of large shape populations with several thousand samples. Our intrinsic formulation exhibits improved discrimination ability over its Euclidean counterpart, which we demonstrate for predictive validity on assessing risks of total knee replacement. This result highlights the potential of the geodesic B-score to enable improved personalized assessment and stratification for interventions. Copyright © 2021, The Authors. All rights reserved.

关键词： Geodesy

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Automatic segmentation of tooth images: Optimization of multi-parameter image processing workflow

Automatic segmentation of tooth images: Optimization of mult...

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24th Eurographics Conference on visualization, EuroVis 2022

作者： Fogalli, Giovani Bressan Line, Sérgio Roberto Peres Baum, Daniel Department of Biosciences Piracicaba Dental School State University of Campinas Brazil Department of Visual and Data-Centric Computing Zuse Institute Berlin Germany

ISBN: (纸本)9783038681854

The development of specific algorithms in image processing are usually related to dataset characteristics. Those characteristics will influence the number of instructions required to solve a problem. Normally, the more complex a set of instructions is, the more parameters need to be set. Dealing with such degrees of freedom, sometimes leading to subjective decision making, is time-consuming and frequently leads to errors or sub-optimal results of the developed model. Here, we deal with a model for segmentation of masks of tooth images containing a pattern of bands called Hunter-Schreger Bands (HSB). They appear on tooth surface when lit from the side. This segmentation process is only one step of a pipeline whose overall goal is human biometric identification to be used, e.g., in forensics. The segmentation algorithm, which exploits the anisotropy of the image, uses several parameters and choosing the optimal combination of them is challenging. The aim of this work was to utilize visual data analysis tools to optimize the chosen parameters and to understand their influence on the performance of the algorithm. Our results reveal that a slightly better combination of parameter values can be found starting from the experimentally determined initial parameters. This approach can be repeatedly performed to achieve even better parameterizations. To more deeply understand the influence of the parameters on the final result, more sophisticated visual interaction tools will be explored in future work. © 2022 The Author(s) Eurographics Proceedings © 2022 The Eurographics Association.

关键词： Image segmentation

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Ridge Regression for Manifold-valued Time-Series with Application to Meteorological Forecast

arXiv

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arXiv 2024年

作者： Nava-Yazdani, Esfandiar Department of Visual and Data-Centric Computing Zuse Institute Berlin Berlin Germany

We propose a natural intrinsic extension of the ridge regression from Euclidean spaces to general manifolds, which relies on Riemannian least-squares fitting, empirical covariance, and Mahalanobis distance. We utilize it for time-series prediction and apply the approach to forecast hurricane tracks and their wind *** Codes 53B, 53C (Primary), 62, 65D (Secondary) © 2024, CC BY.

关键词： Wind forecasting

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FELRec: Efficient Handling of Item Cold-Start With Dynamic Representation Learning in Recommender Systems

arXiv

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arXiv 2022年

作者： Weimann, Kuba Conrad, Tim O.F. Visual and Data-Centric Computing Zuse Institute Berlin Takustr. 7 Berlin14195 Germany

Recommender systems suffer from the cold-start problem whenever a new user joins the platform or a new item is added to the catalog. To address item cold-start, we propose to replace the embedding layer in sequential recommenders with a dynamic storage that has no learnable weights and can keep an arbitrary number of representations. In this paper, we present FELRec, a large embedding network that refines the existing representations of users and items in a recursive manner, as new information becomes available. In contrast to similar approaches, our model represents new users and items without side information and time-consuming finetuning, instead it runs a single forward pass over a sequence of existing representations. During item cold-start, our method outperforms similar method by 29.50%–47.45%. Further, our proposed model generalizes well to previously unseen datasets in zero-shot settings. The source code is publicly available at https://***/kweimann/FELRec. © 2022, CC BY.

关键词： Contrastive Learning

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Numerical examination of a model rotor in brownout conditions

Numerical examination of a model rotor in brownout condition...

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70th American Helicopter Society International Annual Forum 2014

作者： Kutz, Benjamin M. Günther, Tobias Rumpf, Andreas Kuhn, Alexander University of Stuttgart Institute of Aerodynamics and Gasdynamics Germany University of Magdeburg Visual Computing Group Germany Zuse Institute Berlin Visualization and Data Analysis Germany

ISBN: (纸本)9781632666918

In the present study a flow simulation of a rotor hovering in ground effect was performed and compared to an experimental study from literature. Different reconstruction schemes in the finite volume flow solver were employed, leading to a computation of second and fifth order accuracy in space. The higher order computation was also performed on different grids with six and 23 million grid cells. The integral simulation values were compared to the experimental results and other literature, showing good agreement. Further on, the vortex conservation of the several schemes was compared. The higher order computation yields a much longer vortex preservation and a much better shape approximation, especially with a fine spatial resolution of the computational domain. Moreover, brownout simulations were done in a one-way coupled post processing mode of the flow computation. The results show that a good preservation of the vortices is crucial for a following brownout simulation, which leads to the necessity of a fine resolution and high order computations. The influence of the particle size was examined, leading to the finding that especially a mix of big and small particles in the sediment bed may lead to severe brownout conditions, when flying near the ground. The blade tip vortices are interacting with the sediment and are one of the main drivers of particle entrainment in brownout conditions. ©2014. All rights reserved.

关键词： Vortex flow

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VoxSculpt: An Open-Source Voxel Library for Tomographic Volume Sculpting in Virtual Reality 9

VoxSculpt: An Open-Source Voxel Library for Tomographic Volu...

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9th International Conference on Virtual Reality, ICVR 2023

作者： Rodrigues, Lucas Siqueira Riehm, Felix Zachow, Stefan Israel, Johann Habakuk Humboldt-Universität zu Berlin Cluster of Excellence 'Matters of Activity' Berlin Germany Angewandte Informatik Hochschule für Technik und Wirtschaft Berlin Berlin Germany Visual and Data-Centric Computing Zuse Institute Berlin Berlin Germany Forschungsgruppe Centis Hochschule für Technik und Wirtschaft Berlin Berlin Germany

ISBN: (纸本)9798350345810

Manual processing of tomographic data volumes, such as interactive image segmentation in medicine or paleontology, is considered a time-consuming and cumbersome endeavor. Immersive volume sculpting stands as a potential solution to improve its efficiency and intuitiveness. However, current open-source software solutions do not yield the required performance and functionalities. We address this issue by contributing a novel open-source game engine voxel library that supports real-time immersive volume sculpting. Our design leverages GPU instancing, parallel computing, and a chunk-based data structure to optimize collision detection and rendering. We have implemented features that enable fast voxel interaction and improve precision. Our benchmark evaluation indicates that our implementation offers a significant improvement over the state-of-the-art and can render and modify millions of visible voxels while maintaining stable performance for real-time interaction in virtual reality. © 2023 IEEE.

关键词： Virtual reality

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Mass-dependent integral curves in unsteady vector fields

Mass-dependent integral curves in unsteady vector fields

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15th Eurographics Conference on visualization, EuroVis 2013

作者： Günther, Tobias Kuhn, Alexander Kutz, Benjamin Theisel, Holger Visual Computing Group University of Magdeburg Germany Visualization and Data Analysis Zuse Institute Berlin Germany Institute of Aerodynamics and Gas Dynamics University of Stuttgart Germany

Recent research in flow visualization is focusing on the analysis of time-dependent, but mass-less particles. However, in many application scenarios, the mass of particles and their resulting inertia - is essential in understanding fluid mechanics. This includes critical processes, such as dust particles interacting with aircraft (e.g., brownor white-out effects) and particle separation based on density variation. In this paper, we contribute a generalized description of mass-dependent particle trajectories and apply existing unsteady flow visualization methods to the mass-dependent case. This comprises the extension of common concepts, i.e., path lines, streak lines, and time lines. Furthermore, we introduce a new class of integral curves, called mass lines that effectively visualizes mass separation and captures mass-related features in unsteady flow fields that are inaccessible using traditional methods. We demonstrate the applicability of our method, using a number of real-world and artificial data sets, in which mass is a crucial parameter. In particular, we focus on the analysis of brown-out conditions, introduced by a helicopter in forward flight close to the ground. © 2013 The Author(s).

关键词： Flow visualization

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