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DeepDR: Deep Structure-Aware RGB-D Inpainting for Diminished Reality

C. Gsaxner, S. Mori, D. Schmalstieg, J. Egger, G. Paar, W. Bailer, and D. Kalkofen. (2024)
DOI: 10.1109/3dv62453.2024.00037

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Christina Michalak University of Stuttgart

Christina Abele University of Stuttgart

Christina Eisenbarth University of Stuttgart

Christina Ungerer University of Stuttgart

Christina Karagianni University of Stuttgart

Other publications of authors with the same name

A Marker-Less Registration Approach for Mixed Reality-Aided Maxillofacial Surgery: a Pilot Evaluation.A. Pepe, G. Trotta, P. Mohr-Ziak, C. Gsaxner, J. Wallner, V. Bevilacqua, and J. Egger. J. Digital Imaging, 32 (6): 1008-1018 (2019)A review on multiplatform evaluations of semi-automatic open-source based image segmentation for cranio-maxillofacial surgery.J. Wallner, M. Schwaiger, K. Hochegger, C. Gsaxner, W. Zemann, and J. Egger. Computer Methods and Programs in Biomedicine, (2019)Depth-Awareness in a System for Mixed-Reality Aided Surgical Procedures.M. Labini, C. Gsaxner, A. Pepe, J. Wallner, J. Egger, and V. Bevilacqua. ICIC (3), volume 11645 of Lecture Notes in Computer Science, page 716-726. Springer, (2019)Detection, segmentation, simulation and visualization of aortic dissections: A review.A. Pepe, J. Li, M. Rolf-Pissarczyk, C. Gsaxner, X. Chen, G. Holzapfel, and J. Egger. Medical Image Anal., (2020)DeepDR: Deep Structure-Aware RGB-D Inpainting for Diminished RealityC. Gsaxner, S. Mori, D. Schmalstieg, J. Egger, G. Paar, W. Bailer, and D. Kalkofen. (2024)Sparse convolutional neural network for high-resolution skull shape completion and shape super-resolutionJ. Li, C. Gsaxner, A. Pepe, D. Schmalstieg, J. Kleesiek, and J. Egger. Scientific Reports, (2024)A comprehensive workflow and framework for immersive virtual endoscopy of dissected aortae from CTA data.J. Egger, S. Gunacker, A. Pepe, G. Melito, C. Gsaxner, J. Li, K. Ellermann, and X. Chen. Medical Imaging: Image-Guided Procedures, volume 11315 of SPIE Proceedings, page 1131531. SPIE, (2020)Exploit fully automatic low-level segmented PET data for training high-level deep learning algorithms for the corresponding CT data.C. Gsaxner, P. Roth, J. Wallner, and J. Egger. CoRR, (2019)Fully Convolutional Mandible Segmentation on a valid Ground- Truth Dataset.J. Egger, B. Pfarrkirchner, C. Gsaxner, L. Lindner, D. Schmalstieg, and J. Wallner. EMBC, page 656-660. IEEE, (2018)Lower jawbone data generation for deep learning tools under MeVisLab.B. Pfarrkirchner, C. Gsaxner, L. Lindner, N. Jakse, J. Wallner, D. Schmalstieg, and J. Egger. Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging, volume 10578 of SPIE Proceedings, page 105782O. SPIE, (2018)

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Disambiguation of "Gsaxner, Christina"

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DeepDR: Deep Structure-Aware RGB-D Inpainting for Diminished Reality

Please choose a person to relate this publication to

Christina Michalak University of Stuttgart

Christina Abele University of Stuttgart

Christina Eisenbarth University of Stuttgart

Christina Ungerer University of Stuttgart

Christina Karagianni University of Stuttgart

Other publications of authors with the same name

Disambiguation

PUMA

Disambiguation of "Gsaxner, Christina"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML DeepDR: Deep Structure-Aware RGB-D Inpainting for Diminished Reality

Please choose a person to relate this publication to

Christina Michalak University of Stuttgart

Christina Abele University of Stuttgart

Christina Eisenbarth University of Stuttgart

Christina Ungerer University of Stuttgart

Christina Karagianni University of Stuttgart

Other publications of authors with the same name

Disambiguation

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URL
DOI
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DeepDR: Deep Structure-Aware RGB-D Inpainting for Diminished Reality