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Dataset . 2025
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
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Plenoptic 2.0 - Synthetic datasets - Cubes and Shapes

Authors: Fachada, Sarah; Bonatto, Daniele; Sancho Aragón, Jaime; Lafruit, Gauthier; Teratani, Mehrdad; Juarez, Eduardo;

Plenoptic 2.0 - Synthetic datasets - Cubes and Shapes

Abstract

Plenoptic 2.0 - Synthetic datasets - Cubes and Shapes The test sequence "Plenoptic 2.0 - Synthetic datasets - Cubes and Shapes" is provided by Sarah Fachada, Daniele Bonatto, Jaime Sancho, Gauthier Lafruit,Mehrdad Teratani, and Eduardo Juárez, members of the LISA department, EPB (Ecole Polytechnique de Bruxelles), ULB (Université Libre de Bruxelles), Belgium and CITSEM (Centro de Investigación en Tecnologías Software y Sistemas Multimedia para la Sostenibilidad), UPM (Universidad Politecnica de Madrid), Spain. License CC BY-NC-SA Terms of Use Any kind of publication or report using this sequence should refer to the following reference: [1] Sarah Fachada, Daniele Bonatto, Jaime Sancho, Gauthier Lafruit, Mehrdad Teratani, and Eduardo Juárez, "Plenoptic 2.0 - Synthetic datasets - Cubes and Shapes," 2025.01, 10.5281/zenodo.14728981. bibtex @misc{fachada_cubesshapes_2025, title = {{Plenoptic} 2.0 } {Synthetic} {datasets} - {Cubes} and {Shapes}}, author = {Fachada, Sarah and Bonatto, Daniele and Sancho, Jaime and Lafruit, Gauthier and Teratani, Mehrdad and Juárez, Eduardo}, month = jan, year = {2025}, doi = {10.5281/zenodo.14728981} } Production Laboratory of Image Synthesis and Analysis, LISA department, Ecole Polytechnique de Bruxelles, Université Libre de Bruxelles, Belgium, Centro de Investigación en Tecnologías Software y Sistemas Multimedia para la Sostenibilidad, CITSEM, Universidad Politécnica de Madrid, Spain. Content This dataset contains two multiview scenes featuring simple geometric objects rendered using a Blender plenoptic addon for plenoptic cameras [1].The dataset additionally contains cameras.txt files with the parameters of the cameras. The dataset contains - `Cubes` and `Shapes` folder containing: - TXT parameters - Plenoptic images in PNG format - Disparity maps in PNG format, encoded between 0 and 255 (the last number in the filenames indicates the maximum disparity) - Micro-lens mask in PNG format References and links [1] https://github.com/Arne-Petersen/Plenoptic-Simulation Acknowledgments Sarah Fachada is a Postdoctoral Researcher of the Fonds de la Recherche Scientifique - FNRS, Belgium. This work was supported in part by the HoviTron project (no. 951989), the FER 2021 project (no. 1060H000066-FAISAN), the Emile DEFAY 2021 project (no. 4R00H000236), and the FER 2023 project (no. 1060H000075). Additionally, this work has been funded by the project AIMS5.0, supported by the Chips Joint Undertaking and its members, including top-up funding by National Funding Authorities from involved countries (no. 101112089), and the European project STRATUM (no. 101137416). The robotic bench was funded by “Programa Propio UPM” in the call “convocatoria de ayudas a centros e institutos de I+D+i”.

Keywords

Multiview, Disparity maps, Plenoptic camera, Blender

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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Average
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