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Survey and Digital Representation of the Statue of San Carlo Borromeo in Arona to Support Conservation Activities
No full textThe project aims to create a digital model that supports diagnostic, conservation, restoration, consolidation, and maintenance activities related to the Colossus of San Carlo Borromeo. The first phase focused on the accurate digital documentation of the Colossus's exterior surfaces using digital photogrammetry and laser scanning technology. A subsequent phase-currently in progress-is dedicated to the survey and digital representation of the complex internal and external metal structure that supports the riveted copper plates.Digital HeritageInstrumental and Computational Approaches for CH Conservation and Restauratio
StaffsVerse: Exploring Unreal Editor for Fortnite in Virtual Campus Design
No full textVirtual campuses have seen expanded development in the past few years, appearing in various technical forms ranging from WebVR to Minecraft. This paper presents the considerations behind development of the StaffsVerse, a virtual recreation of the University of Staffordshire's campuses, designed within Unreal Editor for Fortnite. In this work, we have discussed the optimization strategies behind designing the StaffsVerse and the social and marketing impacts during its initial release. The StaffsVerse is the first virtual campus to be released within Fortnite and serves as a new form of engagement and outreach. Future works can utilize the findings within this paper to inform design decisions when developing large-scale virtual campuses within UEFN.Computer Graphics and Visual Computing (CGVC)Short Papers Session: VR and M
Region-Aware Sparse Attention Network for Lane Detection
No full textLane detection is a fundamental task in intelligent driving systems. However, the slender and sparse structure of lanes, combined with the dominance of irrelevant background regions in road scenes, makes accurate lane localization particularly challenging, especially under complex and adverse conditions. To address these issues, we propose a novel Region-Aware Sparse Attention Network (RSANet), which is designed to selectively enhance lane-relevant features while suppressing background interference. Specifically, we introduce the Region-guided Pooling Predictor (RPP) that generates lane region activation maps to guide the backbone network in focusing on informative areas. To improve the multi-scale feature fusion capability of the Feature Pyramid Network (FPN), we propose the Bilateral Pooling Attention Module (BPAM) that captures discriminative features by jointly modeling dependencies along both the channel and spatial dimensions. Furthermore, the Lane-guided Sparse Attention Mechanism (LSAM) efficiently aggregates global contextual information from the most relevant spatial regions to reinforce lane prior representations while significantly reducing redundant computation. Extensive experiments on benchmark datasets demonstrate that RSANet outperforms state-of-the-art methods in a variety of challenging scenarios. Notably, RSANet achieves an F1@50 score of 80.04% on the CULane dataset that shows notable improvements.Computer Graphics ForumDetecting & Estimating from images and videos44
Powering 3D digitisation of Europe's heritage: challenges and opportunities
No full textDigitisation of Europe's cultural heritage in 3D offers opportunities to increase public access and engagement while supporting preservation and sustainable management of monuments and sites. In 2019 European Union (EU) member states signed up to a 'declaration of cooperation on advancing digitisation of cultural heritage' which began a pan-European initiative for 3D digitisation of cultural heritage artefacts, monuments and sites (European Commission, 2019). This was followed in 2021 by a European Commission (EC) Recommendation which set a grand challenge by inviting EU Member States to digitise in 3D all monuments and sites deemed at risk, and half of those which are most physically visited. The EC recommendation has stimulated initiatives at national and European levels and by individual institutions. The EC has funded tens of projects to work on 3D heritage data including the 3D-4CH online competence centre for 3D. Some member states have established eCulture programmes with funding from either the EU Recovery and Resilience Facility and/or national funding streams. Yet progress towards the recommendation varies from region to region, as does access to funding, resources and trained personnel. The potential of 3D for cultural heritage is acknowledged by EU member states which are establishing digital strategies and assessing the digital skills needed in the cultural sector. Institutions on the ground are leveraging funding opportunities and building their capacity to carry out 3D projects. There are excellent examples of best practices from across Europe.Digital HeritagePanels, Roundtable
Projective Displacement Mapping for Ray Traced Editable Surfaces
No full textDisplacement mapping is an important tool for modeling detailed geometric features. We explore the problem of authoring complex surfaces while ray tracing interactively. Current techniques for ray tracing displaced surfaces rely on acceleration structures that require dynamic rebuilding when edited. These techniques are typically used for massive static scenes or the compression of detailed source assets. Our interest lies in modeling and look development of artistic features with real-time ray tracing. We introduce projective displacement mapping as a direct sampling method combined with a hardware BVH. Quality and performance are improved over existing methods with smoothed displaced normals, thin feature sampling, tight prism bounds and ray bi-linear patch intersections.Computer Graphics ForumLines, Surfaces & Fields44
ACM/EG Expressive Symposium 2025: Frontmatter
No full textACM/EG Expressive Symposium - Eurographics Workshop on Intelligent Cinematography and Editing 202
Characterizing the Performance of Counterfactual and Correlation Guidance via Dataset Perturbations
No full textGuidance methods are often employed in visual analytics systems to help users navigate complex datasets and discover meaningful insights. Guidance based on correlation is a common method that can steer users towards closely related variables. However, recent work has shown that guidance based on counterfactual subsets can more effectively capture and surface causal relationships. In this work we further explore these guidance methods by characterizing their performance by systematically introducing perturbations in both the data points generated from a ground truth causal graph, and the causal relationships in the graph itself. Our results indicate that while both guidance types exhibit similar sensitivity to global data point perturbations, counterfactual guidance can better capture perturbations affecting only a single dimension, and more effectively reflect changes in causal link strengths, indicating an improved ability to capture narrow data changes and causal relationships.EuroVis 2025 - PostersPoster
Bayesian 3D Shape Reconstruction from Noisy Points and Normals
No full textReconstructing three-dimensional shapes from point clouds remains a central challenge in geometry processing, particularly due to the inherent uncertainties in real-world data acquisition. In this work, we introduce a novel Bayesian framework that explicitly models and propagates uncertainty from both input points and their estimated normals. Our method incorporates the uncertainty of normals derived via Principal Component Analysis (PCA) from noisy input points. Building upon the Smooth Signed Distance (SSD) reconstruction algorithm, we integrate a smoothness prior based on the curvatures of the resulting implicit function following Gaussian behavior. Our method reconstructs a shape represented as a distribution, from which sampling and statistical queries regarding the shape's properties are possible. Additionally, because of the high cost of computing the variance of the resulting distribution, we develop efficient techniques for variance computation. Our approach thus combines two common steps of the geometry processing pipeline, normal estimation and surface reconstruction, while computing the uncertainty of the output of each of these steps.Computer Graphics ForumReconstruction44
Uniform Sampling of Surfaces by Casting Rays
No full textRandomly sampling points on surfaces is an essential operation in geometry processing. This sampling is computationally straightforward on explicit meshes, but it is much more difficult on other shape representations, such as widely-used implicit surfaces. This work studies a simple and general scheme for sampling points on a surface, which is derived from a connection to the intersections of random rays with the surface. Concretely, given a subroutine to cast a ray against a surface and find all intersections, we can use that subroutine to uniformly sample white noise points on the surface. This approach is particularly effective in the context of implicit signed distance functions, where sphere marching allows us to efficiently cast rays and sample points, without needing to extract an intermediate mesh. We analyze the basic method to show that it guarantees uniformity, and find experimentally that it is significantly more efficient than alternative strategies on a variety of representations. Furthermore, we show extensions to blue noise sampling and stratified sampling, and applications to deform neural implicit surfaces as well as moment estimation.Computer Graphics ForumImplicit Representations44
SMACC: Sketching Motion for Articulated Characters with Comics-based annotations
No full textWe introduce SMACC, a sketch-based system for animating short sequences of 3D articulated characters inspired by 2D comic motion line annotations. SMACC relies on classical rules of motion depiction used in comic books, allowing the depiction of dynamism in static images while being universally understood. Building on this, SMACC introduces an algorithmic interpretation of these principles in the context of a 3D character animation, guided by three fundamental types of motion lines: trajectory, circumfixing and impact. The adaptation to rigged 3D characters relies on the automatic computation of how these motion cues spatially influence the character's skeleton, achieved through a global analysis of sketch annotations relative to the character's pose. The resulting animation is generated by encoding the kinematic clues and constraints into joint angular velocities. Finally, the proof-of-concept demonstrated by SMACC is validated through a user study, which evaluates the effectiveness and accuracy of this sketch-based approach applied to 3D character animation.Pacific Graphics Conference Papers, Posters, and DemosCharacter Animatio