Relevant bibliographies by topics / 3D model-Driven reconstruction

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic '3D model-Driven reconstruction'

Author: Grafiati
Published: 25 May 2024
Last updated: 31 July 2025

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Journal articles on the topic "3D model-Driven reconstruction"

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Meng, Ge, Jingyan Tu, Jingjia Huang, et al. "Sp3ctralMamba: Physics-Driven Joint State Space Model for Hyperspectral Image Reconstruction." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 6 (2025): 6108–16. https://doi.org/10.1609/aaai.v39i6.32653.

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Hyperspectral image (HSI) reconstruction aims to restore the original 3D HSIs from the 2D hyperspectral snapshot compressive images (SCIs). The key to high-fidelity HSI reconstruction lies in designing refined spatial and spectral attention mechanisms, which are crucial for generating fine-grained representations of HSI based on the limited spatial and spectral information available in SCI. Recently, Mamba has demonstrated remarkable performance and efficiency in modeling spatial correlations. Its implicit attention mechanism generates three orders of magnitude more attention matrices than tra
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Huang, Wei, San Jiang, and Wanshou Jiang. "A Model-Driven Method for Pylon Reconstruction from Oblique UAV Images." Sensors 20, no. 3 (2020): 824. http://dx.doi.org/10.3390/s20030824.

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Pylons play an important role in the safe operation of power transmission grids. Directly reconstructing pylons from UAV images is still a great challenge due to problems of weak texture, hollow-carved structure, and self-occlusion. This paper presents an automatic model-driven method for pylon reconstruction from oblique UAV images. The pylons are reconstructed with the aid of the 3D parametric model library, which is represented by connected key points based on symmetry and coplanarity. First, an efficient pylon detection method is applied to detect the pylons in the proposed region, which a
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Troccaz, J., and P. Cinquin. "Model Driven Therapy." Methods of Information in Medicine 42, no. 02 (2003): 169–76. http://dx.doi.org/10.1055/s-0038-1634329.

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Summary Objectives: Taking into account a priori knowledge is a key issue to meet the medical, scientific and industrial challenges of the progresses of Minimally Invasive Surgery. We propose an overview of these challenges. Methods: Models play a major role in representing the relevant knowledge to plan and realize complex medical and surgical interventions. We analyze the three basic steps of Perception, Decision and Action, and illustrate by some instances how models may be integrated in these steps. Results: We propose a selection of the results obtained in Model Driven Therapy. These resu
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Nguyen, Duc-Phong, Tan-Nhu Nguyen, Stéphanie Dakpé, Marie-Christine Ho Ba Ho Ba Tho, and Tien-Tuan Dao. "Fast 3D Face Reconstruction from a Single Image Using Different Deep Learning Approaches for Facial Palsy Patients." Bioengineering 9, no. 11 (2022): 619. http://dx.doi.org/10.3390/bioengineering9110619.

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The 3D reconstruction of an accurate face model is essential for delivering reliable feedback for clinical decision support. Medical imaging and specific depth sensors are accurate but not suitable for an easy-to-use and portable tool. The recent development of deep learning (DL) models opens new challenges for 3D shape reconstruction from a single image. However, the 3D face shape reconstruction of facial palsy patients is still a challenge, and this has not been investigated. The contribution of the present study is to apply these state-of-the-art methods to reconstruct the 3D face shape mod
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Pistellato, Mara, Filippo Bergamasco, Andrea Torsello, et al. "A Physics-Driven CNN Model for Real-Time Sea Waves 3D Reconstruction." Remote Sensing 13, no. 18 (2021): 3780. http://dx.doi.org/10.3390/rs13183780.

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One of the most promising techniques for the analysis of Spatio-Temporal ocean wave fields is stereo vision. Indeed, the reconstruction accuracy and resolution typically outperform other approaches like radars, satellites, etc. However, it is computationally expensive so its application is typically restricted to the analysis of short pre-recorded sequences. What prevents such methodology from being truly real-time is the final 3D surface estimation from a scattered, non-equispaced point cloud. Recently, we studied a novel approach exploiting the temporal dependence of subsequent frames to ite
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Liu, Yilin, Liqiang Lin, Yue Hu, et al. "Learning Reconstructability for Drone Aerial Path Planning." ACM Transactions on Graphics 41, no. 6 (2022): 1–17. http://dx.doi.org/10.1145/3550454.3555433.

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We introduce the first learning-based reconstructability predictor to improve view and path planning for large-scale 3D urban scene acquisition using unmanned drones. In contrast to previous heuristic approaches, our method learns a model that explicitly predicts how well a 3D urban scene will be reconstructed from a set of viewpoints. To make such a model trainable and simultaneously applicable to drone path planning, we simulate the proxy-based 3D scene reconstruction during training to set up the prediction. Specifically, the neural network we design is trained to predict the scene reconstr
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Li, Jinwen, Guangli Ren, Youmei Pan, et al. "Surface Reconstruction Planning with High-Quality Satellite Stereo Pairs Searching." Remote Sensing 17, no. 14 (2025): 2390. https://doi.org/10.3390/rs17142390.

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Advancements in remote sensing technology have remarkably enhanced the 3D Earth surface reconstruction, which is pivotal for applications such as disaster relief, emergency management, and urban planning, etc. Although satellite imagery offers a cost-effective and extensive coverage solution for 3D reconstruction, the quality of the resulted digital surface model (DSM) heavily relies on the choice of stereo image pairs. However, current approaches of stereo Earth observation still employ a post-acquisition manner without sophisticated planning in advance, causing inefficiencies and low reconst
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Hou, Yaohui, Jianwen Song, and Lijun Wang. "P‐2.27: Application of 3D reconstruction technology in VR industry." SID Symposium Digest of Technical Papers 54, S1 (2023): 588–90. http://dx.doi.org/10.1002/sdtp.16361.

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VR content is a key link in building a VR ecosystem, but the extreme lack of high-quality content has become the core shortcoming restricting the development of the VR industry, so in the medium and long term, the VR industry will shift from hardware technology upgrades to high-quality content-oriented, and is expected to usher in a new round of growth driven by business model innovation and content explosion. With 3D reconstruction, users can experience virtual scenes visually and audibly. The development of 3D reconstruction technology will bring great changes to existing players, and also g
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Deng, Yujuan. "Fluid Equation-Based and Data-Driven Simulation of Special Effects Animation." Advances in Mathematical Physics 2021 (November 22, 2021): 1–11. http://dx.doi.org/10.1155/2021/7480422.

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This paper analyzes the simulation of special effects animation through fluid equations and data-driven methods. This paper also considers the needs of computer fluid animation simulation in terms of computational accuracy and simulation efficiency, takes high real-time, high interactivity, and high physical accuracy of simulation algorithm as the research focus and target, and proposes a solution algorithm and acceleration scheme based on deep neural network framework for the key problems of simulation of natural phenomena including smoke and liquid. With the deep development of artificial in
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Zhou, Ding, Guohua Wei, and Xiaojun Yuan. "Three-Dimensional Shape Reconstruction from Digital Freehand Design Sketching Based on Deep Learning Techniques." Applied Sciences 14, no. 24 (2024): 11717. https://doi.org/10.3390/app142411717.

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This paper proposes a method for 3D reconstruction from Freehand Design Sketching (FDS) in architecture and industrial design. The implementation begins by extracting features from the FDS using the self-supervised learning model DINO, followed by the continuous Signed Distance Function (SDF) regression as an implicit representation through a Multi-Layer Perceptron network. Taking eyeglass frames as an example, the 2D contour and freehand sketch optimize the alignment by their geometrical similarity while exploiting symmetry to improve reconstruction accuracy. Experiments demonstrate that this
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Dissertations / Theses on the topic "3D model-Driven reconstruction"

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Jin, Nan. "ModSETS : a model-driven stereo eye tracking system : application in the medical field." Electronic Thesis or Diss., Aix-Marseille, 2020. http://www.theses.fr/2020AIXM0339.

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La plupart des systèmes de suivi de l’œil existants ne fournissent que des analyses précises et en temps réel des mouvements oculaires 2D (horizontaux et verticaux) dans des conditions de laboratoire. Ils sont en général insuffisants pour les applications du domaine médical, parce que leur robustesse est souvent mise à l'épreuve dans la pratique et la mesure du mouvement torsionnel de l’œil est ignorée la plupart du temps. Cela augmente la difficulté d'interprétation des données collectées et peut donc affecter la qualité du diagnostic médical. Un système de suivi de l’œil en stéréophotogrammé
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Partovi, Tahmineh. "3D Building Model Reconstruction from Very High Resolution Satellite Stereo Imagery." Doctoral thesis, 2019. https://repositorium.ub.uni-osnabrueck.de/handle/urn:nbn:de:gbv:700-201910022067.

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Automatic three-dimensional (3D) building model reconstruction using remote sensing data is crucial in applications which require large-scale and frequent building model updates, such as disaster monitoring and urban management, to avoid huge manual efforts and costs. Recent advances in the availability of very high-resolution satellite data together with efficient data acquisition and large area coverage have led to an upward trend in their applications for 3D building model reconstructions. In this dissertation, a novel multistage hybrid automatic 3D building model reconstruction approach is
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Book chapters on the topic "3D model-Driven reconstruction"

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Berretti, Stefano, Alberto Del Bimbo, and Pietro Pala. "3D Face Reconstruction from Two Orthogonal Images for Face Recognition Applications." In Multimedia Storage and Retrieval Innovations for Digital Library Systems. IGI Global, 2012. http://dx.doi.org/10.4018/978-1-4666-0900-6.ch012.

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In this paper, an original hybrid 2D-3D face recognition approach is proposed using two orthogonal face images, frontal and side views of the face, to reconstruct the complete 3D geometry of the face. This is obtained using a model based solution, in which a 3D template face model is morphed according to the correspondence of a limited set of control points identified on the frontal and side images in addition to the model. Control points identification is driven by an Active Shape Model applied to the frontal image, whereas subsequent manual assistance is required for control points localizat
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Conference papers on the topic "3D model-Driven reconstruction"

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Hanajik, Milan. "Efficient data-driven algorithm for the model-based 3D scene reconstruction from perspective images." In Spatial Information from Digital Photogrammetry and Computer Vision: ISPRS Commission III Symposium, edited by Heinrich Ebner, Christian Heipke, and Konrad Eder. SPIE, 1994. http://dx.doi.org/10.1117/12.182824.

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Partovi, Tahmineh, Thomas Kraus, Hossein Arefi, Mohammad Omidalizarandi, and Peter Reinartz. "Model-driven 3D building reconstruction based on integeration of DSM and spectral information of satellite images." In IGARSS 2014 - 2014 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2014. http://dx.doi.org/10.1109/igarss.2014.6947150.

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Xu, Baixin, Jiarui Zhang, Kwan-Yee Lin, Chen Qian, and Ying He. "Deformable Model-Driven Neural Rendering for High-Fidelity 3D Reconstruction of Human Heads Under Low-View Settings." In 2023 IEEE/CVF International Conference on Computer Vision (ICCV). IEEE, 2023. http://dx.doi.org/10.1109/iccv51070.2023.01643.

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Hu, Yazhe, and Tomonari Furukawa. "A Self-Supervised Learning Technique for Road Defects Detection Based on Monocular Three-Dimensional Reconstruction." In ASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/detc2019-98135.

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Abstract This paper presents a self-supervised learning technique for road surface defects detection using a monocular camera. The uniqueness of the proposed technique relies on its self-supervised learning structure which is achieved by combining physics-driven three-dimensional (3D) reconstruction with data-driven Convolutional Neural Network (CNN). Only images from one camera are needed as the inputs to the model without human labeling. The 3D point cloud are reconstructed from input images based on a near-planar road 3D reconstruction process to self-supervise the learning process. During
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"ONTOLOGY-DRIVEN 3D RECONSTRUCTION OF ARCHITECTURAL OBJECTS." In 3D Model Aquisition and Representation. SciTePress - Science and and Technology Publications, 2007. http://dx.doi.org/10.5220/0002047300470054.

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Reck, Michaela, Marc Hilbert, René Hilhorst, and Thomas Indinger. "Comparison of Deep Learning Architectures for Dimensionality Reduction of 3D Flow Fields of a Racing Car." In WCX SAE World Congress Experience. SAE International, 2023. http://dx.doi.org/10.4271/2023-01-0862.

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<div class="section abstract"><div class="htmlview paragraph">In motorsports, aerodynamic development processes target to achieve gains in performance. This requires a comprehensive understanding of the prevailing aerodynamics and the capability of analysing large quantities of numerical data. However, manual analysis of a significant amount of Computational Fluid Dynamics (CFD) data is time consuming and complex. The motivation is to optimize the aerodynamic analysis workflow with the use of deep learning architectures. In this research, variants of 3D deep learning models (3D-DL)
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Omar, Saad, Diogo Salim, Mikhail Zaslavsky, and Lin Liang. "High-Resolution 3D Reservoir Mapping and Geosteering Using Voxel-Based Inversion Processing of UDAR Measurements." In 2024 SPWLA 65th Annual Symposium. Society of Petrophysicists and Well Log Analysts, 2024. https://doi.org/10.30632/spwla-2024-0092.

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Ultradeep azimuthal resistivity (UDAR) measurements provide full three-dimensional (3D) volumetric sensitivity to the surrounding formation and are routinely used for strategic geosteering, reservoir navigation, reservoir characterization, and real-time drilling decision making based on the inverted resistivity profile. The initial layered-earth-model (1D) reservoir map can be further refined (on demand) with two-dimensional (2D) and 3D processing. Existing 3D processing, employing octree gridding for modeling and inversion, leads to extreme smoothing in the formation mapping with artifacts ap
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Wang, Zihan, Austin Bray, Kiarash Naghavi Khanghah, and Hongyi Xu. "A Generative Graph Neural Network-Based Framework for Designing Connectivity-Guaranteed Porous Metamaterial Units." In ASME 2024 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2024. http://dx.doi.org/10.1115/detc2024-143200.

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Abstract Porous metamaterial units filled with fluid have been used in engineering systems due to their ability to achieve desired properties (e.g., effective thermal conductvity). Designing 3D porous metamaterial units while ensuring complete connectivity of both solid and pore phases presents a significant challenge. In this study, we propose a generative graph neural network-based framework for designing the porous metamaterial units infilled with liquid. Firstly, we propose a graph-based metamaterial unit generation approach to generate porous metamaterial samples with complete connectivit
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Akram Abdulrahman, Raghad, and Emad Hani Ismaeel. "4D Representation of the Built Heritage Post-Conflict: Interactive Modeling of the Qattanin Mosque in Old Mosul." In 5th International Conference on Architectural and Civil Engineering Sciences (CIC-ICACE'25). Cihan University-Erbil, 2025. https://doi.org/10.24086/icace2025/paper.1640.

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Abstract—The integration of technology in the domain of urban heritage management has witnessed a significant surge, driven by the multifaceted advantages it offers for the administration of conservation efforts. Among the most prominent technological advancements is the application of virtual reality (VR) systems, which facilitate digital preservation through the creation of detailed 3D models of historical edifices. These models can then be embedded within interactive environments, such as those provided by augmented reality (AR) systems. AR enables users to identify and explore historical b
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Amerinatanzi, Amirhesam, Narges Shayesteh Moghaddam, Hamdy Ibrahim, and Mohammad Elahinia. "Evaluating a NiTi Implant Under Realistic Loads: A Simulation Study." In ASME 2016 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/smasis2016-9287.

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Additive manufacturing (i.e. 3D printing) has only recently be shown as a well-established technology to create complex shapes and porous structures from different biocompatible metal powder such as titanium, nitinol, and stainless steel alloys. This allows for manufacturing bone fixation hardware with patient-specific geometry and properties (e.g. density and mechanical properties) directly from CAD files. Superelastic NiTi is one of the most biocompatible alloys with high shock absorption and biomimetic hysteresis behavior. More importantly, NiTi has the lowest stiffness (36–68 GPa) among al
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