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17121 research outputs found
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NODKANT: Exploring Constructive Network Physicalization
No full textPhysicalizations, which combine perceptual and sensorimotor interactions, offer an immersive way to comprehend complex data visualizations by stimulating active construction and manipulation. This study investigates the impact of personal construction on the comprehension of physicalized networks. We propose a physicalization toolkit-NODKANT-for constructing modular node-link diagrams consisting of a magnetic surface, 3D printable and stackable node labels, and edges of adjustable length. In a mixed-methods between-subject lab study with 27 participants, three groups of people used NODKANT to complete a series of low-level analysis tasks in the context of an animal contact network. The first group was tasked with freely constructing their network using a sorted edge list, the second group received step-by-step instructions to create a predefined layout, and the third group received a pre-constructed representation. While free construction proved on average more time-consuming, we show that users extract more insights from the data during construction and interact with their representation more frequently, compared to those presented with step-by-step instructions. Interestingly, the increased time demand cannot be measured in users' subjective task load. Finally, our findings indicate that participants who constructed their own representations were able to recall more detailed insights after a period of 10-14 days compared to those who were given a pre-constructed network physicalization. All materials, data, code for generating instructions, and 3D printable meshes are available on https://osf.io/tk3g5/.Computer Graphics ForumBest Paper
VisibleUS: From Cryosectional Images to Real-Time Ultrasound Simulation
No full textThe VisibleUS project aims to generate synthetic ultrasound images from cryosection images, focusing on the musculoskeletal system. Cryosection images provide a highly accurate representation of real tissue structures without artifacts. Using this rich anatomical data, we developed a ray-tracing-based simulation algorithm that models ultrasound wave propagation, scattering, and attenuation. This results in highly realistic ultrasound images that accurately depict fine anatomical details, such as muscle fibers and connective tissues. The simulation tool has various applications, including generating datasets for training neural networks and developing interactive training tools for ultrasound specialists. Its ability to produce realistic ultrasound images in real time enhances medical education and research, improving both the understanding and interpretation of ultrasound imaging.Eurographics 2025 - PostersPoster
A Bag of Tricks for Efficient Implicit Neural Point Clouds
No full textImplicit Neural Point Cloud (INPC) is a recent hybrid representation that combines the expressiveness of neural fields with the efficiency of point-based rendering, achieving state-of-the-art image quality in novel view synthesis. However, as with other high-quality approaches that query neural networks during rendering, the practical usability of INPC is limited by comparatively slow rendering. In this work, we present a collection of optimizations that significantly improve both the training and inference performance of INPC without sacrificing visual fidelity. The most significant modifications are an improved rasterizer implementation, more effective sampling techniques, and the incorporation of pre-training for the convolutional neural network used for hole-filling. Furthermore, we demonstrate that points can be modeled as small Gaussians during inference to further improve quality in extrapolated, e.g., close-up views of the scene. We design our implementations to be broadly applicable beyond INPC and systematically evaluate each modification in a series of experiments. Our optimized INPC pipeline achieves up to 25% faster training, 2× faster rendering, and 20% reduced VRAM usage paired with slight image quality improvements.Vision, Modeling, and VisualizationNeural and Differentiable Renderin
Sampling of Anisotropic Spatial Gaussians for Path Guiding
No full textDirectional models in path guiding struggle with representing parallax effects or anisotropic features. Our model instead describes the spatial distribution of a target vertex using a 3D Gaussian mixture model. While this dispenses with the need for reprojection and allows to represent anisotropic features easily, its directional probability density is not readily available, since it involves a marginal integral. In this work, we derive an expression for the PDF of our model in solid angle measure that is practical to evaluate. We demonstrate how our model can improve guiding accuracy in various scenes.Eurographics 2025 - PostersPoster
Controllable Biophysical Human Faces
No full textWe present a novel generative model that synthesizes photorealistic, biophysically plausible faces by capturing the intricate relationships between facial geometry and biophysical attributes. Our approach models facial appearance in a biophysically grounded manner, allowing for the editing of both high-level attributes such as age and gender, as well as low-level biophysical properties such as melanin level and blood content. This enables continuous modeling of physical skin properties that correlate changes in skin properties with shape changes. We showcase the capabilities of our framework beyond its role as a generative model through two practical applications: editing the texture maps of 3D faces that have already been captured, and serving as a strong prior for face reconstruction when combined with differentiable rendering. Our model allows for the creation of physically-based relightable, editable faces with consistent topology and uv layout that can be integrated into traditional computer graphics pipelines.Computer Graphics ForumDifferentiable Rendering44
Triangle Rejection Sampling for Density-Equipped Meshes on GPU
No full textNon-uniform random point sampling on 3D surfaces offers a powerful framework to capture complex distributions such as fur seeds, scattered geometric instances or light emitter flux. As most other on-surface signals, practitioners design such distribution by the means of 2D maps, parameterized over the surface, and indicating locally the desired point density that should be synthesized, along with any primitive-specific attribute such as fiber thickness or instance size. Numerous application scenarios imply large such point sets which would ideally be generated in real-time to be consumed immediately by downstream applications. We propose a method to distribute such white noise point sets under non-uniform densities, designed to cope with parallel GPU execution and able to produce, in real time, hundreds of millions of density-constrained samples over arbitrary 3D triangle meshes. At the core of our method, we introduce a stratified rejection sampling scheme where triangles act as strata, greatly improving the locality of the sampling process, and significantly diminishing the probability of rejecting a sample. Our method relies on a series of simple GPU kernels, introducing a new fast and exact texel-triangle overlap computation method as well as the notion of unordered cumulative sum. As a result, our approach provides real-time systems with the ability to tailor, on-the-fly, highly dynamic density distributions in the form of procedural or raster maps. We illustrate its application with interactive fur design, geometry instancing, and Monte Carlo light sampling.Computer Graphics ForumProcedural Generation and Sculpting44
Visual Analysis of Time-Dependent Observables in Cell Signaling Simulations
No full textThe ability of a cell to communicate with its environment is essential for key cellular functions like replication, metabolism, or cell fate decisions. The involved molecular mechanisms are highly dynamic and difficult to capture experimentally. Simulation studies offer a valuable means for exploring and predicting how cell signaling processes unfold. We present a design study on the visual analysis of such studies to support 1) modelers in calibrating model parameters such that the simulated signal responses over time reflect reference behavior from cell biology research and 2) cell biologists in exploring the influence of receptor trafficking on the efficiency of signal transmission within the cell. We embed time series plots into parallel coordinates to enable a simultaneous analysis of model parameters and temporal outputs. A usage scenario illustrates how our approach assists with typical tasks such as assessing the plausibility of temporal outputs or their sensitivity across model configurations.Eurographics Workshop on Visual Computing for Biology and MedicineSession
Towards Automated 2D Character Animation
No full textAutomating facial expression changes in comics and 2D animation presents several challenges, as facial structures can vary widely, and audiences are susceptible to the subtlest changes. Building on extensive research in human face image manipulation, landmark-guided image editing offers a promising solution, providing precise control and yielding satisfactory results. This study addresses the challenges hindering the advancement of landmark-based methods for cartoon characters and proposes the use of object detection models -specifically YOLOX and Faster R-CNN- to detect initial facial regions. These detections serve as a foundation for expanding landmark annotations, enabling more effective expression manipulation to animate expressive characters. The codes and trained models are publicly available here.ACM/EG Expressive Symposium - WICED: Eurographics Workshop on Intelligent Cinematography and Editing - Artworks, Posters, DemosPoster
Scenting Heritage: Real-Time Olfactory Augmentation
No full textThis paper outlines and reflects on our work to create a digital-olfactive experience via the conceptual and technical elaboration of an interactive installation, the Terapixel Panorama - centred on the 1.6 terapixel digital twin of the Panorama of the Battle of Murten, an iconic, 1000m2 panorama painting - in what is the first-ever use of real time and dynamic olfactory augmentation in the cultural heritage domain. The paper will cover both technical and curatorial/interpretive dimensions of the work. We outline the genesis and implementation of the digital twin's smellscape, beginning with the identification of smells that evoke both the material object and the painting's visual narrative. This was followed by a precursory exercise in 'olfactive' thinking in which narrative approaches to the panorama were considered through the lens of smell. This thinking culminated in the creation of a series of smell maps which encode our vision for the panorama's organic smell universe and which we use to technically integrate synthetic smell information into the twin's digital file. By endowing the digital material with some of the original object's multisensory, and, in this case, olfactive life, we shift away from the purely visual towards a form of visual and visceral realism in which the object's olfactive materiality and multisensorial narrativity are formally encoded.Digital HeritagePhygital Worlds and XR in Cultural Heritag
Geometric Modeling for Immersive VR Exploration of Underground Heritage: Matera's Hypogeum Case Study
No full textThis paper present a methodology for reconstructing and optimizing 3D digital models of complex, tangible underground heritage sites that are difficult to access or even closed to the public, with the ultimate goal of integrating them into interactive virtual reality experiences, both for preservation and to make them accessible to a wider audience. The approach is demonstrated through the complete digitization of Matera's Hypogeum, in southern Italy. Faced with the site's challenging conditions (i.e., intricate passageways, poor lighting, and physical constraints), we developed a specialized workflow that combines handheld laser scanning acquisition with optimized mesh processing, in order to produce a model that can balance details visualization and realism with performance efficiency when used in VR environments. A preliminary development of an immersive VR application is also presented to provide an initial qualitative analysis of the model.Digital HeritageDigitization Case Studie