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.
6
datasets available to search
ShareScore release 0.9.0
Dataset results
6 results for “Sidewalk”
Sidewalk Environment for Visual Navigation
<p>This dataset contains low and high resolution panoramic images, coordinates, labels and a connectivity graph. In order to run this simulated environment, you will need at least one copy of the panoramic images, which are available in low (84x224 pixels) or high resolution (1280x3840 pixels). For more information, visit https://mweiss17.github.io/SEVN/.</p>
A Dataset of Synthetic Images of Outdoor Scenes Taken from Sidewalks, for Temporal Semantic Segmentation Applications
<p>This dataset has been generated using the CARLA simulator (release 0.9.11), an open-source 3D simulator for experiments in autonomous vehicle, based on the Unreal Engine game engine. It comes with pre-made city environment maps. CARLA is distributed with several integrated maps as well as parameters to increase the variety in the dataset. In the release that we have used, there are 13 semantic segmentation classes: None, Building, Fence, Other, Pedestrian, Pole, Lane-marking, Road, Sidewalk, Vegetation, Vehicle, Wall, and Traffic sign. The "None" category corresponds to textures that are not part of an object, such as lawns which are not part of "Vegetation", or sky. In the “Other” category are found objects that are not included in the other classes like plant and flower pots. For smart mobility applications, the “Sidewalks” and “Road” classes are of particular importance to find the way forward, as well as “Buildings” and “Poles” for obstacle avoidance. Sequences are made of 4 images. The dataset is composed of 46436 frames (11609 sequences) partitioned in 41024 frames (10256 sequences) for train, 2696 frames (674 sequences) for validation, and 2716 for test (679 sequences). The size of the images is 800 x 600 (resp. width x height).</p> <p>Additionaly, we have generated another smaller dataset with images taken from 2 different viewpoints: one located on the road and the other located on the sidewalk. The number of frames for train/validation/test is respectively 7288 (1822 sequences) partitioned in 6344 (1687 sequences) for train, 416 frames (104 sequences) for validation, and 424 for test (106 sequences). This smaller dataset is aimed at showing the importance of the viewpoint in the result of semantic segmentation. This can be done by cross-validation: learning on images taken from a viewpoint located on the road and test on images with a viewpoint located on the sidewalk, and vice versa.</p>
Leaf traits Plantago major, urban sidewalk, city park and nature reserve populations
<p>These measurements include the raw data on the petiole and lamina length and width of Plantago major populations growing within city parks, urban sidewalks or nature reserves in the Netherlands. The data was collected between 12-04-2021 and 07-05-2021 by Roman Beukema. The dataset includes both GPS longitude and latitude locations from each sample, as well as the lamina and petiole length and width in millimeters precise.</p> <p> </p>
Multi-city street-sidewalk imagery from pedestrian mobile cameras
<p>We present TerraFirma, a multi-city dataset which captures street and sidewalk imagery from the pedestrians' perspective. Motivated by challenges in the realm of pedestrian safety, we present a diverse and extensive dataset that provides a foundation for the design and validation of pedestrian safety systems that rely on street-sidewalk imagery. The data was collected by 9 volunteers in 4 metropolitan cities across the world. Volunteers carried mobile cameras or smartphones in a texting position, such that the rear camera was directed to the ground in front of them. TerraFirma classifies images by the material used for street/sidewalk construction in each city. </p>
Multi-city street-sidewalk imagery from pedestrian mobile cameras
Open the record for dataset details and reuse information.
Cool colors promote a restorative sidewalk experience: Effects of urban sidewalk ground mural design on pedestrians' mood states, perceived restorativeness, and heart rate in virtual reality
<p>This dataset contains the survey and heart rate data used in the paper.</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.