The ICSC National Research Centre for High Performance Computing, Big Data and Quantum Computing promotes national and international-level innovation, building on a state-of-the-art infrastructure for computation and big data management. The Center focuses, on the one hand, on the maintenance and enhancement of the Italian HPC and Big Data infrastructure and, on the other hand, on the development of advanced numerical methods and applications, software tools and workflows, to integrate the computation, simulation, collection and analysis of data of interest to the research system and the productive and social system, including through cloud and distributed approaches. It engages and promotes the best interdisciplinary expertise in science and engineering, enabling radical and sustainable innovations in fields ranging from basic research to computational and experimental sciences of climate, environment, space, matter and life, epidemiology, materials technologies, and future systems and devices for IT and the production system at large. The Center supports higher education and promotes policy development for responsible data management from an open data and open science perspective, combining regulatory, standardization and compliance profiles. CRS4 participates in the project in Spoke 9 (Digital Cities) through [a] the research and development of AI solutions to infer, from visual data or other measurements, of 3D structured models of buildings; [b] solutions to improve the quality and reliability of digital twins by fostering composability, interoperability, reusability and reproducibility of datasets, computational tools and their results; [c] the study and development of probabilistic methods for forecasting electricity consumption and renewable generation for individuals and smart and artificial intelligence methods for electricity consumption analysis and non-intrusive disaggregation of household electric loads.
| [1] Muhammad Tukur, Sara Jashari, Mahmood Alzubaidi, Babatunde Abiodun Salami, Yehia Boraey, Sindy Yong, Dina Saleh, Giovanni Pintore, Enrico Gobbetti, Jens Schneider, Noora Fetais, and Marco Agus. Panoramic Imaging in Immersive Extended Reality: A Scoping Review of Technologies, Applications, Perceptual Studies, and User Experience Challenges. Frontiers in Virtual Reality, 6, 2025. DOI: 10.3389/frvir.2025.1622605. To appear. 
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| [2] Giovanni Pintore, Sara Jashari, Marco Agus, and Enrico Gobbetti. PanoFloor: reconstruction and immersive exploration of large multi-room scenes from a minimal set of registered panoramic images using denoised density maps. In Proc. IEEE ISMAR, October 2025. To appear. 
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| [3] Ruggero Pintus, Antonio Zorcolo, Alberto Jaspe-Villanueva, and Enrico Gobbetti. A Practical Inverse Rendering Strategy for Enhanced Albedo Estimation for Cultural Heritage Model Reconstruction. In Proc. Digital Heritage, September 2025. To appear.
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| [4] Giovanni Pintore, Marco Agus, Alberto Signoroni, and Enrico Gobbetti. DDD++: Exploiting Density map consistency for Deep Depth estimation in indoor environments. Graphical Models, 140: 101281, August 2025. DOI: 10.1016/j.gmod.2025.101281.
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| [5] Giovanni Pintore, Uzair Shah, Marco Agus, and Enrico Gobbetti. NadirFloorNet: reconstructing multi-room floorplans from a small set of registered panoramic images. In 2nd CVPR Workshop on Urban Scene Modeling. Pages 1986-1994, June 2025. IEEE.
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| [6] Giovanni Pintore, Marco Agus, and Enrico Gobbetti. Automatic 3D modeling and exploration of indoor structures from panoramic imagery. In SIGGRAPH Asia 2024 Courses (SA Courses '24), December 2024. ACM Press. DOI: 10.1145/3680532.3689580.
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| [7] Giovanni Pintore, Marco Agus, Alberto Signoroni, and Enrico Gobbetti. DDD: Deep indoor panoramic Depth estimation with Density maps consistency. In STAG: Smart Tools and Applications in Graphics, November 2024. DOI: 10.2312/stag.20241336.
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| [8] Uzair Shah, Sara Jashari, Muhammad Tukur, Giovanni Pintore, Enrico Gobbetti, Jens Schneider, and Marco Agus. VISPI: Virtual Staging Pipeline for Single Indoor Panoramic Images. In STAG: Smart Tools and Applications in Graphics, November 2024. DOI: 10.2312/stag.20241334.
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| [9] Sara Jashari, Muhammad Tukur, Yehia Boraey, Uzair Shah, Mahmood Alzubaidi, Giovanni Pintore, Enrico Gobbetti, Alberto Jaspe-Villanueva, Jens Schneider, Noora Fetais, and Marco Agus. Evaluating AI-based static stereoscopic rendering of indoor panoramic scenes. In STAG: Smart Tools and Applications in Graphics, November 2024. DOI: 10.2312/stag.20241333.
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| [10] Uzair Shah, Jens Schneider, Giovanni Pintore, Enrico Gobbetti, Mahmood Alzubaidi, Mowafa Househ, and Marco Agus. EleViT: exploiting element-wise products for designing efficient and lightweight vision transformers. In Proc. T4V - IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2024.
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| [11] Uzair Shah, Muhammad Tukur, Mahmood Alzubaidi, Giovanni Pintore, Enrico Gobbetti, Mowafa Househ, Jens Schneider, and Marco Agus. MultiPanoWise: holistic deep architecture for multi-task dense prediction from a single panoramic image. In Proc. OmniCV - IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). Pages 1311-1321, 2024. DOI: 0.1109/CVPRW63382.2024.00138.
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| [12] Giovanni Pintore, Alberto Jaspe-Villanueva, Markus Hadwiger, Jens Schneider, Marco Agus, Fabio Marton, Fabio Bettio, and Enrico Gobbetti. Deep synthesis and exploration of omnidirectional stereoscopic environments from a single surround-view panoramic image. Computers & Graphics, 119: 103907, March 2024. DOI: 10.1016/j.cag.2024.103907.
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| [13] Luca Massidda, Fabio Bettio, and Marino Marrocu. Probabilistic day-ahead prediction of PV generation. A comparative analysis of forecasting methodologies and of the factors influencing accuracy. Solar Energy, 271: 112422, March 2024. DOI: 10.1016/j.solener.2024.112422. |
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