Conference Agenda

This paper introduces the 3D-4CH project and its open framework, i.e. a sustainable ecosystem of tools designed to overcome the fragmentation and limited maintainability of previous EU-funded 3D heritage initiatives. Aligned with the European Collaborative Cloud for Cultural Heritage (ECCCH), the framework integrates an end-to-end pipeline for 3D data generation and processing, semantic enrichment and long-term dissemination, including metadata and paradata inclusion. The 3D-4CH initiative bridges the gap between ICT research and operational heritage practices, ensuring the scalability and reproducibility of 3D digital assets for cross-institutional data sharing and preservation. All software components, including GitHub repositories and online processing frameworks, are openly available, in accordance with open science principles and FAIR data practices. Further information is available at https://www.3d4ch-competencecentre.eu/en/tools/.

The paper presents the integrated 3D metric survey of the Genete Leul Palace in Addis Ababa, demonstrating how metric reliability and operational speditivity can coexist through an adaptive hybrid TLS–MMS workflow that supported the restoration project and heritage documentation in a low-infrastructure context.

Laser scanning, photogrammetry, and other technical tools are staples for cultural heritage documentation and reverse engineering projects. However, manufacturers and even researchers often conflate the data capture process with reverse engineering itself, even though the data alone cannot provide the insight needed for a full reverse engineering or understanding of the historic site. This paper illustrates how laser scanning and photogrammetric applications were used in reverse engineering the construction and details of Conrad’s Jewel, a 1908 Silver/Gold mill in the Yukon, Canada. Analogous to systems and software engineering fields, the reverse engineering process is framed by considering related designs, existing documentation, personal experience, and general external knowledge.

The 3D reconstruction of cultural heritage artefacts plays a crucial role in documentation, conservation and dissemination. While recent advances in photogrammetry, laser scanning and neural rendering techniques have significantly improved the geometric accuracy and visual realism of digitised assets, the reconstruction of transparent and reflective materials - typical in museal collections - remains a major challenge. Materials such as glass, glazes and varnishes exhibit complex optical behaviours, leading to incomplete or inaccurate 3D models. Recent developments in Gaussian Splatting (GS) offer a potential alternative by enabling efficient, high-fidelity scene representation without explicit surface modelling. However, their application to non-Lambertian and transparent heritage objects remains largely unexplored. This paper presents a study on GS methods for the 3D digitisation of transparent cultural heritage artefacts. Through a series of experimental reconstructions, the work investigates the potential and limitations of GS, highlight the opportunities of hybrid pipelines for addressing long-standing challenges in the digitisation of non-collaborative materials.

In recent years, the European Commission (EC) identified the 3D digitization of cultural heritage sites and artifacts as one of its priorities and promoted numerous initiatives and recommendations to accelerate documentation campaigns. However, current digitization targets remain far from being achieved, and heritage institutions have been increasingly encouraged to explore faster and cost-effective 3D documentation solutions. Moreover, traditional image- and range-based 3D surveying techniques frequently struggle when reconstructing objects featuring non-collaborative surfaces (such as reflective or transparent objects), are time-consuming, and require specialized knowledge. Generative AI methods, able to generate 3D models also from a single input image, have recently emerged as a potentially faster alternative, yet their performance on heritage assets remains mostly unexplored. This paper evaluates three state-of-the-art and recent single-image GenAI frameworks - SAM3D, Tripo3D and Trellis2 - on several museum artifacts featuring diffuse, reflective, transparent, and mixed-material surfaces of varying scale and geometric complexity, for which accurate ground truth is available. The aim is to analyze whether these frameworks can act as complementary or alternative solutions for fast heritage documentation.

To address the issues of geometric distortion and loss of details in 3D modeling for complex cultural heritage scenes, this paper proposes an improved 3D Gaussian Splatting (3DGS) reconstruction method that integrates LiDAR and illumination-awareness. First, high-precision 3D coordinates from LiDAR point clouds are utilized to guide the initialization of Gaussian Primitives, establishing a precise geometric foundation and effectively overcoming deformation on weakly textured surfaces. Second, an illumination-aware network is constructed to dynamically adjust appearance parameters by combining global illumination from images with LiDAR reflectance intensity. This decouples complex lighting from material properties, accurately reproducing the unique textures of artifacts. Finally, a multi-dimensional joint loss function incorporating photometric, scale, and appearance smoothness constraints is introduced to collaboratively optimize scene geometry, appearance, and camera poses. Experimental results on indoor and outdoor cultural heritage preservation scenarios demonstrate that the proposed method significantly outperforms various comparative algorithms in terms of both visual fidelity and geometric accuracy. The quantitative and qualitative evaluations confirm that our approach effectively eliminates geometric distortions and recovers fine texture details, providing an efficient and reliable technical solution for the digital preservation of cultural heritage.

Cultural Heritage assets as the Bremen Cog at the German Maritime Museum are often subject to long-term preservation processes and being monitored over time. The Bremen Cog, a clinker-build vessel from 1380, was found in the River Weser in 1962 and thereafter salvaged and reconstructed until 1981. Prior to conservation efforts (1981 to 1999), a photogrammetric 3D measurement campaign was conducted using a stereometric camera SMK 120. Due to deformation a permanent support system was installed in 2003 including the application of local corrections using pressure plates to correct the hull to its measured one from 1980. Since 2020 a long-term geometric monitoring of the cog has been carried out in order to detect deformation. With the analyses of the monitoring data in connection with the measurement conditions, it is of high interest whether the cog in its current shape corresponds to the one estimated in 1980. Historic SMK 120 stereo image pairs on glass plates are analysed in order to estimate their usability and potential for 3D object reconstruction and subsequently comparing the results to the current monitoring data. The proposed workflow includes an optimized digitization process of the glass plate and reconstruction of the interior and exterior orientations. Feature detection and matching methods as well as robust orientation tasks are analysed in order to allow for a 3D hull reconstruction. The reconstruction at least in parts of the cog and with lower precision is desirable and promising in terms of evaluating changes of the hull over time.

Photogrammetry and laser scanning are widespread tools for documenting movable and immovable cultural heritage assets. Documenting the entire surface of an object presents a set of specific challenges, with various solutions currently available. Complete object documentation relies on established capture techniques that utilize the registration method for different model orientations. This paper presents the “Mask Model Method,” a semi-automatic approach for seamlessly documenting entire objects while seeking high-quality results. This workflow works well for most objects that would be considered viable for general photogrammetric capture. The advantages are also in capturing small and large objects (with and without a turntable) with hinge-type moving parts. This method of documenting full architectural artefacts is useful in heritage conservation, repairs, and restoration; specifically, digital patternmaking, virtual reconstruction, digital annotation of historic materials & geometry, and applied experimental archaeology.