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=== DIDYMOS-XR Project ===
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! CORDIS Reference !! Start date !! End date !! Coordinator !! Project website
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| https://cordis.europa.eu/project/id/101092875 || 01/01/2023 || 31/12/2025 || JOANNEUM / Austria || https://didymos-xr.eu/
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=== Project description ===
The digital transformation and the availability of more diversified and cost-effective means for 3D capture have led to the creation of digital twins also for physical environments. Based on such digital twins, various applications could be built using real-time data from real-world environments, serving as a blueprint for smart cities and for improving performance and efficiency across industries. Currently, creating high-fidelity digital twins is costly, and their update requires manual intervention. Furthermore, data integration from heterogeneous sensors is challenging. The EU-funded DIDYMOS-XR project will implement technology to create improved large-scale digital twins, synchronised with the real world. DIDYMOS-XR will investigate and develop methods for data reconstruction and mapping from heterogeneous inputs, including static and mobile sensors, AI-based data fusion, scene understanding and rendering.

=== Project outputs ===
==== Publications ====
{| class="wikitable sortable"
! Domain !! Type of output !! Title !! DOI URL
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| AI, Machine Learning & Data Science || Conference proceedings || Perception for Connected Autonomous Vehicles under Adverse Weather Conditions || https://doi.org/10.1109/IROS58592.2024.10801295
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| AI, Machine Learning & Data Science || Conference proceedings || User-Centric Evaluation Methods for Digital Twin Applications in Extended Reality || https://doi.org/10.1109/AIXVR63409.2025.00028
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| AI, Machine Learning & Data Science || Conference proceedings || MGSO: Monocular Real-Time Photometric SLAM with Efficient 3D Gaussian Splatting || https://doi.org/10.48550/ARXIV.2409.13055
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| Computer Vision, 3D Modeling & Rendering || Conference proceedings || HINT-3D: Human-in-the-Loop Interactive Test-Time Adaptation for 3D Segmentation || https://doi.org/10.5281/ZENODO.18491843
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| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Deep 3D Geometric Saliency Estimation from Light Field Images || https://doi.org/10.1109/DSP58604.2023.10167953
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| Computer Vision, 3D Modeling & Rendering || Conference proceedings || HAME-NeRF: High Accuracy Mesh Extraction Leveraging Neural Radiance Fields || https://doi.org/10.1007/978-3-032-04968-1_28
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| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Visual Localization in Complex Environments: Merging Traditional Geometry with Learning-Based Techniques || https://doi.org/10.1109/AIXVR63409.2025.00022
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| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Volumetric Video Reconstruction and Communications: Toward a New Era of Interactive and Immersive Social Virtual Reality (VR) Experiences || https://doi.org/10.1145/3672406.3672421
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| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Training a Segmentation-Based Visual Anonymization Service for Street Scenes || https://doi.org/10.1007/978-981-96-2074-6_26
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| Computer Vision, 3D Modeling & Rendering || Conference proceedings || GDNeRF: Generalizable Depth-based NeRF for sparse view synthesis || https://doi.org/10.1109/ICME59968.2025.11209482
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| Computer Vision, 3D Modeling & Rendering || Conference proceedings || HAL-NeRF: High Accuracy Localization Leveraging Neural Radiance Fields || https://doi.org/10.1109/AIXVR63409.2025.00024
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| Computer Vision, 3D Modeling & Rendering || Conference proceedings || Leveraging Anisotropic Error for Robust Point Cloud Registration || https://doi.org/10.1109/DSP65409.2025.11074865
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| Computer Vision, 3D Modeling & Rendering || Peer reviewed articles || Urban scene removal and completion || https://doi.org/10.3233/FAIA250603
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| Computer Vision, 3D Modeling & Rendering || Peer reviewed articles || Visual localization using implicit representations and particle filtering-based pose refinement || https://doi.org/10.5281/ZENODO.18468790
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| Computer Vision, 3D Modeling & Rendering || Peer reviewed articles || ExpPoint-MAE: Better Interpretability and Performance for Self-Supervised Point Cloud Transformers || https://doi.org/10.1109/ACCESS.2024.3388155
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| Computer Vision, 3D Modeling & Rendering || Peer reviewed articles || Interactive digital twins enabling responsible extended reality applications || https://doi.org/10.1038/S41598-025-17855-9
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| Computer Vision, 3D Modeling & Rendering || Peer reviewed articles || MaskUno: Switch-Split Block For Enhancing Instance Segmentation || https://doi.org/10.48550/ARXIV.2407.21498
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| Ethics, Society, Arts & Culture || Conference proceedings || Digital Twins for Extended Reality Tourism: User Experience Evaluation Across User Groups || https://doi.org/10.1007/978-3-031-97769-5_3
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| Ethics, Society, Arts & Culture || Peer reviewed articles || Reimagining Historical Exploration: Multi-User Mixed Reality Systems for Cultural Heritage Sites || https://doi.org/10.3390/APP15052854
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| Extended Reality (VR/AR/MR) & HCI || Conference proceedings || Cooperative Perception for Digital Twin Reconstruction* || https://doi.org/10.1109/AIXVR63409.2025.00023
|}

==== Technological assets ====
{| class="wikitable sortable"
! Title !! Type of Asset !! Link / DOI !! Description
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| Dataset for Learning Scene Semantics from Vehicle-centric Data for City-scale Digital Twins || Dataset || https://ieeexplore.ieee.org/document/10859207 || Data utilized for learning scene semantics intended for city-scale digital twins.
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| ADAPT JR-Sim2Real dataset || Dataset || https://zenodo.org/records/12805642 || Dataset associated with domain transfer for instance segmentations for AR scenes.
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| MGSO || Software / Algorithm || https://doi.org/10.48550/ARXIV.2409.13055 || A monocular real-time photometric SLAM algorithm utilizing efficient 3D Gaussian Splatting.
|-
| HINT-3D || Software / Framework || https://doi.org/10.5281/ZENODO.18491843 || A human-in-the-loop interactive test-time adaptation framework for 3D segmentation.
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| Visual localization using implicit representations || Software / Model || https://doi.org/10.5281/ZENODO.18468790 || Software for visual localization utilizing implicit representations and particle filtering-based pose refinement.
|}

DIDYMOS-XR - Revision history

CollectiveIntelligenceAdmin at 14:48, 1 September 2026