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ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2023
License: CC BY
Data sources: ZENODO
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ReSyRIS: Real-Synthetic Rock Instance Segmentation dataset

Authors: Boerdijk, Wout; Müller, Marcus Gerhard; Durner, Maximilian; Triebel, Rudolph;

ReSyRIS: Real-Synthetic Rock Instance Segmentation dataset

Abstract

# ReSyRIS The Real-Synthetic Rock Instance Segmentation dataset (ReSyRIS) is created for training and evaluation of rock segmentation, detection and instance segmentation in (quasi-)extra-terrestrial environments. It consists of a set of annotated, real images of rocks on a lunar-like surface, a precisely mimicked synthetic version thereof, and respective synthetic assets for training data generation. In the folders, you find the following structure: - `stone_models`: all 36 .obj files of the 3d reconstructed stones - `test_data_realworld`: the real world recordings with accompanying ground truth - `test_data_synthetic`: the synthetic renderings matching approximately the real world recordings, with accompanying ground truth - `oaisys`: config files for rendering synthetic training data with oaisys If you find this dataset useful for your work please consider citing our paper: https://elib.dlr.de/194113/.

Related Organizations
Keywords

rock instance segmentation, rock detection, autonomous exploration, moon analogue, dataset, oaisys

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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.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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