Dataset Open Access

UnLoc dataset (Synthetic + Real)

Loing, Vianney


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<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:creator>Loing, Vianney</dc:creator>
  <dc:date>2019-02-12</dc:date>
  <dc:description>This dataset contains the synthetic and real data used in the article " Virtual Training for a Real Application: Accurate Object-Robot Relative Localization Without Calibration " to train 3 convolutional neural networks (CNNs) in order to perform uncalibrated relative localization of a cuboid block with respect to a robot, and to evaluate them. 

It consists of a dataset composed of synthetic pictures for training the CNNs and a dataset of real pictures for evaluation. 

The "synthetic" dataset is composed 3 sub-datasets (each of them composed of thousands of synthetic pictures and corresponding groundtruth) for training : 


	a dataset for coarse relative localization subtask : coarse_estimation_data (~14.6 GB when extracted)
	a dataset for the tool localization subtask : tool_detection_data (~4.3 GB when extracted)
	a dataset for the fine relative localization subtask : fine_estimation_data (~13.3 GB when extracted)


These sub-datasets are composed of raw data as well as post-treated data ready to be used for training CNNs, in CSV format and in Torch format (.t7). 

The "real" dataset is composed of real pictures with a precisely localized cuboid block for evaluation only : UnLoc_real (~2.5 GB when extracted). 

More information available on the project page : http://imagine.enpc.fr/~loingvi/unloc/</dc:description>
  <dc:identifier>https://zenodo.org/record/2563622</dc:identifier>
  <dc:identifier>10.5281/zenodo.2563622</dc:identifier>
  <dc:identifier>oai:zenodo.org:2563622</dc:identifier>
  <dc:language>eng</dc:language>
  <dc:relation>doi:10.1007/s11263-018-1102-6</dc:relation>
  <dc:relation>doi:10.5281/zenodo.2563621</dc:relation>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
  <dc:subject>uncalibrated relative localization</dc:subject>
  <dc:subject>pose estimation</dc:subject>
  <dc:subject>synthetic data</dc:subject>
  <dc:subject>virtual training</dc:subject>
  <dc:subject>robotics</dc:subject>
  <dc:title>UnLoc dataset (Synthetic + Real)</dc:title>
  <dc:type>info:eu-repo/semantics/other</dc:type>
  <dc:type>dataset</dc:type>
</oai_dc:dc>
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