Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
9
datasets available to search
ShareScore release 0.9.0
Dataset results
9 results for “OpenDR”
ΑUTH-AGI OpenDR Humans in Fields Dataset
<p>The OpenDR Humans in Fields dataset is a 2D Object Detection dataset, specifically designed for person detection in agricultural fields. A Robotti robot was deployed by <a href="https://agrointelli.com/">AGI</a> to collect images with a front and back camera, in a realistic scenario to mimic the images that the robot might encounter in the agricultural use case. The cameras are equipped with wide-angle lenses, contributing to the domain shift problem when applying pretrained person detectors to the task. The collected images are saved in JPG format at a resolution of 2048x1536. The dataset is split in train and test sets, and each of these is split in two subsets: a) images depicting humans, and b) images with no humans. The dataset was annotated with bounding boxes by AUTH using the <a href="https://github.com/tzutalin/labelImg">labelImg</a> tool, and the annotations are provided in PASCAL VOC .xml format.</p> <p> </p>
AUTH-OpenDR Mixed Image Annotated Dataset for Human-centric Perception Tasks
<p>The dataset was generated through a mixed (real and synthetic) image data generation method which utilizes real background images and DL-generated human models. It contains 50000 real images depicting urban scenes, populated by synthetic human models in various positions and poses and is suitable for training/evaluating (a) pose estimation, (b) person detection, (c) identity recognition methods. Annotations for 2D bounding boxes of the depicted humans, their IDs and 2D keypoints etc are provided. The 133 3D human models, required by the method, were generated using the Pixel-aligned Implicit Function (PIFu) and full-body images of people from the Clothing Co-Parsing (CCP) dataset. As background images, a subset of the Cityscapes dataset was used. The Cityscapes license prohibits the distribution of any modified versions of itself. Thus, we provide code that can re-generate the exact same dataset, given that the Cityscapes dataset is downloaded by the website of its authors.</p> <p>Code and instructions for re-generating the dataset are provided <a href="https://github.com/opendr-eu/opendr/tree/master/projects/python/simulation/human_dataset_generation">here</a>.</p> <p>The dataset was developed by Aristotle University of Thessaloniki (AUTH) within the H2020 OpenDR Project.</p>
AUTH-OpenDR ACelebA Dataset
<p><strong>Multi-view Facial Image Dataset Based on CelebA</strong>: A dataset of facial images from several viewing angles was created by Aristotle University of Thessaloniki based on the<strong> <a href="https://mmlab.ie.cuhk.edu.hk/projects/CelebA.html">CelebA</a></strong> image dataset, using the software that was created in OpenDR H2020 research project based on this <a href="https://openaccess.thecvf.com/content_CVPR_2020/html/Zhou_Rotate-and-Render_Unsupervised_Photorealistic_Face_Rotation_From_Single-View_Images_CVPR_2020_paper.html">paper</a> and the respective code provided by the authors. CelebA is a large scale facial dataset and consists of 202,599 facial images of 10,177 celebrities captured in the wild. The new dataset namely <strong>AUTH-OpenDR Augmented CelebA (AUTH-OpenDR ACelebA)</strong> was generated from 140,000 facial images corresponding to 9161 persons, i.e. a subset of CelebA was used. For each CelebA image used, 13 synthetic images generated by yaw axis camera rotation in the interval [0◦ : +60◦ ] with step +5◦ were obtained. Moreover, 10 synthetic images generated by pitch axis camera rotation in the interval [0◦: +45◦] with step +5◦ are also created for each facial image of the aforementioned dataset. Since CelebA license does not allow distribution of derivative work we do not make AcelebA directly available but instead provide instructions and scripts on how to recreate it.</p>
AUTH-OpenDR ALFW Dataset
<p><strong>Multi-view Facial Image Dataset Based on LFW</strong>: Using software that is based on the code that accompanies this <a href="https://openaccess.thecvf.com/content_CVPR_2020/html/Zhou_Rotate-and-Render_Unsupervised_Photorealistic_Face_Rotation_From_Single-View_Images_CVPR_2020_paper.html">paper</a> a set of synthetically generated multi-view facial images has been created within OpenDR H2020 research project by Aristotle University of Thessaloniki based on the <a href="http://vis-www.cs.umass.edu/lfw/"><strong>LFW</strong></a> image dataset which is a facial image dataset that consists of 13,233 facial images in the wild for 5,749 person identities collected from the Web. The resulting set, named<strong> AUTH-OpenDR Augmented LFW (AUTH-OpenDR ALFW)</strong>, consists of 5,749 person identities. From each image of these subjects (13,233 in total), 13 synthetic images generated by yaw axis camera rotation in the interval [0◦: +60◦ ] with step +5◦ are obtained. Moreover, 10 synthetic images generated by pitch axis camera rotation in the interval [0◦ : +45◦ ] with step +5◦ are also created for each facial image of the aforementioned dataset. The ALFW dataset can be downloaded from this <a>FTP site</a></p>
OpenDRIVE sample dataset of Test Bed Lower Saxony
<p>This OpenDRIVE dataset models a road network snippet of the motorway A39 near Wolfsburg. It is intended to be used for data evaluation. The data snippet is part of a greater dataset which has been acquired in the context of the project <a href="http://verkehrsforschung.dlr.de/en/projects/test-bed-lower-saxony-automated-and-connected-mobility">Test Bed Lower Saxony</a>. Main application scopes of this OpenDRIVE data are driving simulation, verification and validation. The raw data has been surveyed through mobile mapping end of 2019.</p>
OpenDRIVE dataset of 5G Living Lab research track in Wolfsburg
<p>This OpenDRIVE dataset models a road network excerpt of the city of Wolfsburg, Lower Saxony, Germany. Main application scopes of this OpenDRIVE data are in the domain of automated driving: simulation, verification and validation. The data has been acquired in context of the research project <a href="https://verkehrsforschung.dlr.de/en/projekte/5g-reallabor">5G Living Lab in the Mobility Region Braunschweig-Wolfsburg</a>.</p>
OpenDRIVE dataset of ViVre research track in Brunswick
<p>This OpenDRIVE dataset models a road network excerpt of the city of Brunswick, Lower Saxony, Germany. Main application scopes of this OpenDRIVE data are in the domain of automated driving: simulation, verification and validation. The data has been acquired in context of the research project <a href="https://verkehrsforschung.dlr.de/de/projekte/vivre-virtuelle-haltestellen-fuer-den-automatisierten-verkehr-der-zukunft">ViVre</a>.</p>
AUTH-OpenDR SMPL+D Human Bodies Dataset
<p>The dataset contains 2982 human bodies in various shapes and textures folowing the SMPL-D template. At its core, our dataset consists of 183 unique SMPL+D bodies, which were generated through non-rigid shape registration of manually generated MakeHuman models. The rest were generated by applying shape and texture alterations to those models. In addition, we provide code for converting those human models in the FBX format. However, pose-dependent deformations are not applied to the human models. Finally, instructions for setting a demo project in the Webots simulator are provided. In the project, one the SMPL+D models in FBX format can perform an animation from AMASS.</p> <p>The dataset was developed by Aristotle University of Thessaloniki (AUTH) within the H2020 OpenDR Project.</p> <p>The dataset is available through the official GitHub repository of the OpenDR toolkit <a href="https://github.com/opendr-eu/opendr/tree/master/projects/python/simulation/SMPL%2BD_human_models">here</a>.</p>
OpenDRIVE dataset of the inner ring road in Brunswick
<p>This OpenDRIVE dataset contains a highly detailed model of the inner-city ring road of Brunswick, primarily to be used in driving simulation applications. The raw data has been surveyed in 2012 with the transformation/annotation into OpenDRIVE having been finalised 2015-03-25.</p> <p>The data has been acquired in the context of the project <a href="https://www.dlr.de/ts/en/desktopdefault.aspx/tabid-6422/#gallery/25304">Application Platform for Intelligent Mobility (AIM)</a>.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.