Eurographics Digital Library
Not a member yet
17121 research outputs found
Sort by
Digital Exploration of the Hydrosystems of the Haut Adour (French Pyrenees)
No full textThis research focuses on identifying hydrosystems in the Haut-Adour region of the Pyrenees (France), including lakes, streams, canals, and ancient water infrastructure. These elements reveal long-term human and animal use of the mountain landscape, shaped by cycles of occupation and abandonment. Using digital tools like IGN orthophotos and high-resolution LiDAR, the team developed a method to map and analyze these systems. Fieldwork, drone imagery, and 3D scanning further supported the study, which highlights the evolving relationship between societies and their environment in the face of social and climate change.Digital HeritageAnalysing and Documenting Sites and Landscape
VOLMAP Viewer: a Web-Based Interactive Visual Tool to Explore Volume Maps
No full textVOLMAP Viewer is a web-based tool for the visual assessment and analysis of maps between tetrahedral meshes. Users can load models directly in the browser and manage them with data structures optimized for interactive visualization. They can display and interact in real-time with both source and target domains, check map validity, and compute map quality according to a variety of popular distortion metrics. Fundamental interaction features such as volume slicing and synchronized picking are also possible: users can select any tetrahedron, highlighting the corresponding element on both domains and inspecting its associated map distortion. Thanks to its portability and interactive performances VOLMAP Viewer complements existing datasets and offline tools, supporting ongoing research on volume mapping algorithms.Smart Tools and Applications in Graphics - Eurographics Italian Chapter ConferenceTools in Computer Graphic
Exploring Ownership of an Avatar's Cat Ears through Visual, Auditory, and Haptic Multimodal Feedback
No full textExtensions of body parts that humans are not innately endowed with, such as supernumerary limbs, have attracted attention. Since these body parts resemble existing ones, their movements and sensations can be inferred from the innately existing body parts. However, the sense of ownership for imaginary body parts, such as cat ears, which humans have never possessed, has not been sufficiently investigated. This paper proposes an experiment to examine the changing sense of ownership of cat ears, a body part that humans are not innately endowed with, through multimodal feedback that integrates visual, auditory, and haptic stimuli. Using an avatar with cat ears attached to the top of the head, we suggest presenting visual stimuli of the avatar's cat ears along with spatially congruent auditory and haptic feedback to enhance the sense of ownership over imaginary cat ears.ICAT-EGVE 2025 - International Conference on Artificial Reality and Telexistence and Eurographics Symposium on Virtual Environments - Posters and DemosPosters and Demo
Real-Time Per-Garment Virtual Try-On with Temporal Consistency for Loose-Fitting Garments
No full textPer-garment virtual try-on methods collect garment-specific datasets and train networks tailored to each garment to achieve superior results. However, these approaches often struggle with loose-fitting garments due to two key limitations: (1) They rely on human body semantic maps to align garments with the body, but these maps become unreliable when body contours are obscured by loose-fitting garments, resulting in degraded outcomes; (2) They train garment synthesis networks on a per-frame basis without utilizing temporal information, leading to noticeable jittering artifacts. To address the first limitation, we propose a two-stage approach for robust semantic map estimation. First, we extract a garment-invariant representation from the raw input image. This representation is then passed through an auxiliary network to estimate the semantic map. This enhances the robustness of semantic map estimation under loose-fitting garments during garment-specific dataset generation. To address the second limitation, we introduce a recurrent garment synthesis framework that incorporates temporal dependencies to improve frame-to-frame coherence while maintaining real-time performance. We conducted qualitative and quantitative evaluations to demonstrate that our method outperforms existing approaches in both image quality and temporal coherence. Ablation studies further validate the effectiveness of the garment-invariant representation and the recurrent synthesis framework.Computer Graphics ForumDigital Clothing44
Neural Film Grain Rendering
No full textFilm grain refers to the specific texture of film-acquired images, due to the physical nature of photographic film. Being a visual signature of such images, there is a strong interest in the film-industry for the rendering of these textures for digital images. Some previous works are able to closely mimic the physics of films and produce high quality results, but are computationally expensive. We propose a method based on a lightweight neural network and a texture aware loss function, achieving realistic results with very low complexity, even for large grains and high resolutions. We evaluate our algorithm both quantitatively and qualitatively with respect to previous work.Computer Graphics ForumThe Artful Edit: Stylization and Editing for Images and Video44
Small Codes: a platform for digital resources and tools for minority languages and dialects
No full textSmall Codes is an open digital infrastructure designed to support the preservation and revitalization of minority languages through scalable, interoperable and user-friendly tools. The platform combines linguistic data management with web-based technologies, offering an integrated suite of software modules-including online dictionaries, spell-checkers, corpus alignment systems, linguistic maps, and multimedia archives-tailored for under-resourced and dialectally fragmented languages. Unlike standard language technology pipelines designed for dominant languages, Small Codes supports linguistically diverse input and community-led data models. It operates through a federated, semi-industrial development model, balancing long-term sustainability with flexibility for academic and institutional partners. This paper outlines the system architecture and core functionalities of Small Codes, presents selected implementation scenarios, and discusses its contribution to digital heritage and computational dialectology.Digital HeritageDigital Technologies for CHANGES (CHANGES SESSION) - Part
AI-ChartParser: A Method For Extracting Experimental Data From Curve Charts in Academic Papers
No full textIn the fields of engineering and natural sciences, curve charts serve as indispensable visualization tools for scientific research, product development and engineering design, as they encapsulate crucial data necessary for comprehensive analysis. Existing methodologies for data extraction from line charts predominantly depend on single-task models, which frequently exhibit limitations in efficiency and generalization. To overcome these challenges, we propose AI-ChartParser, an end-to-end deep learning model that employs multi-task learning to concurrently execute chart element detection, pivot point detection and curve detection. This approach effectively and efficiently parses diverse chart formats within a cohesive framework. Furthermore, we introduce an Interval-Mean Space-Numerical Mapping algorithm designed to address challenges in data range extraction, thereby significantly minimizing conversion errors. We have incorporated all the methodologies discussed in this paper to develop a comprehensive data extraction tool, facilitating the automatic conversion of line charts into tabular data. Our model exhibits exceptional performance on complex real-world datasets, achieving state-of-the-art accuracy and speed across all three tasks. To facilitate further research, the source codes and pre-trained models are released at https://github.com/ywking/ChartParser.git.Computer Graphics ForumOriginal Article44
Extensible TensorFlow Implementations of Projection Quality Metrics
No full textDimensionality Reduction (DR, also called Projection) algorithms enable the exploration of high-dimensional data by generating low-dimensional representations of it - typically 2D or 3D scatterplots. Such representations are designed to map data patterns to visual patterns analyzable by humans. Projections can vary wildly - even for a fixed dataset - depending on technique and hyperparameters chosen and, as such, do not all preserve all data patterns equally well. To assess this, so-called Projection Quality Metrics (PQMs) are used. However, the ever-growing number of Projection Quality Metrics has led to fragmented implementations which hinder their easy reuse, leading in turn to unequal adoption and inconsistent implementations. In this work, we propose a TensorFlow-based library of PQMs, improving the previous state of the art in terms of ergonomics, extensibility, and computational scalability. We discuss our improvements and elicit areas where the gap between implementation and research is significant in the area of Projection Quality Metrics, pointing to avenues for future work in developing better PQM libraries that aim to fill this gap.VisGap - The Gap between Visualization Research and Visualization SoftwarePaper Session
TIGHT Intervals for Provably Correct Geometric Computation
No full textInterval arithmetic is a practical method for robust computation, bridging the gap between fast, but inexact, floating-point arithmetic and slow, exact arithmetic, such as rational or arbitrary-precision. In this system, numbers are represented as intervals bounded by floating-point numbers, and operations are performed conservatively, guaranteeing that the resulting interval contains the exact mathematical result. We extend a fast C++ library for interval arithmetic by adding support for several transcendental functions. A key feature of our library is that all operations are correctly rounded, ensuring the resulting interval is the smallest floating-point interval that contains the true result. We demonstrate the library's effectiveness by applying it to complex non-polynomial problems, including surface-surface intersection and continuous collision detection for geometric primitives undergoing roto-translational motion.Smart Tools and Applications in Graphics - Eurographics Italian Chapter ConferenceTools in Computer Graphic
Interactive and immersive discovery of diagnostic processes on multi-layered 3D collections on the web: the MuLaX tool
No full textWeb3D technologies and recent standards allow nowadays to craft rich and interactive tools to present complex and multi-dimensional scientific data. The efficient visualization of 3D models enriched with analytical data acquired from archaeometric surveys on cultural heritage artefacts have become a fundamental aspect in digital preservation. Innovative scientific approaches and accessible interaction models enable experts and the general public to discover invisible or lost information (e.g. ancient polychromy on statuary or faded colors on paintings or textiles), edit and compare multiple datasets. In this paper, we present a Web3D tool called ''MuLaX'', designed and developed under the PERCEIVE European project: we describe its modular architecture, components and features offering users new ways to access, discover and examine multi-dimensional statuary collections directly online. The tool was developed on top of the open-source ATON framework, as plug\&play vertical application: it offers interactive discovery models for analytical/color data (layers), interactive annotation system for spot-analyses (microscope, X-ray fluorescence, etc.) or imaging (Visible-induced Luminescence, Ultraviolet-induced Visible Luminescence, etc.). Designed to handle multiple items (collections), MuLaX is also accessible on every device - from smartphones up to XR devices - and embraces modern web standards, formats and large open ecosystems to maximize interoperability and reuse. Furthermore, MuLaX explores dynamic image-based masks, providing easy ways to describe complex but network-wise compact semantic areas on top of the artwork, generated by other services or via interactive semantic painting. The Web3D tool also integrates with the PERCEIVE ecosystem, using its cloud to access items collection, analytical/color layers and semantic masks. This enables comfortable and flexible management by remote researchers and professionals, as well as remote processing of such data by online PERCEIVE services. In addition to a responsive UI, MuLaX also offers final users access to different XR presentation modes via WebXR, using spatial user interfaces for immersive inspection and discovery of artworks. The preliminary results of the considerable applicability of the tool were discussed in the context of the case study of Venus in a bikini exhibited at the National Archaeological Museum of Naples (MANN) and studied within the PERCEIVE project, as well as ongoing extension of MuLaX tool to embrace artworks in the 2D domain (like paintings), thanks to its flexible architectural design.Digital HeritagePERCEIVE: Exhibiting the ''Unexhibitable'