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.
250
datasets available to search
ShareScore release 0.9.0
Dataset results
250 results for “3D scan”
Ganesha_3D scans with iPhone12 Pro
Ganesha_3D scans with iPhone12 Pro (3dScannerApp) Ganesha is one of the best-known and most worshipped deities in the Hindu pantheon.  Source: Objaverse 1.0 / Sketchfab
Vandalized 3D scan
[Original HD object](https://skfb.ly/KsHn) (292k verts) from MGD Films.  This is my first test to develop an efficient workflow to "vandalize" existing scans, by baking new textures onto the already baked model (~500 verts). The final idea being to seamlessly vandalize famous buildings with famous paintings. This particuliar object was remeshed with mmgs followed by heavy decimate modifiers in blender. I did not care at all about topology. Baking from diffuse and normals only, using a plane with the Banksy texture as an emission shader. Source: Objaverse 1.0 / Sketchfab
Stobnica Castle, Poland | Drone 3D Scan
The Stobnica castle is a modern building with a purpose of looking like a medieval castle, the building began in 2015 and is still on going. The 3d reconstruction was made in Agisoft software from 231 frames from this video: https://www.youtube.com/watch?v=m32yIoU5310 Source: Objaverse 1.0 / Sketchfab
HistoryView VR - 3D Matterport Scan
HistoryView VR is the educational platform for teachers & students to access 3D Virtual Reality Field Trips powered by Matterport. Working with museums and historical sites, HistoryView is able to share historical experiences and bring history to life for classrooms worldwide. In connection with Matterport's state of the art technology, HistoryView is able to create virtual reality field trips for education and digitally preserve anthropology. [HistoryView.org](http://HistoryView.org) Source: Objaverse 1.0 / Sketchfab
Octopus vulgaris, Sepia officinalis, Loligo vulgaris and Illex coindetii early life phases Light Sheet Fluerescence Microscopy (LSFM) 3D scans.
<p>Acronyms: OV: <em>Octopus vulgaris</em>, SO: <em>Sepia officinalis</em>, LV: <em>Loligo vulgaris</em>, IC: <em>Illex coindetii</em>, DPH: Days Post-Hatching.</p> <p>Two detection objectives were used, depending on sample size, a 4x/0.28 NA Olympus XLFLUOR4x/340 objective (0, 5, 10, 19 DPH <em>Octopus vulgaris</em> individuals,<em> Loligo vulgaris</em> and<em> Illex coindetii</em>) and a Nikon 10x/0.5 NA CFI Plan Apochromat 10xC Glyc (Rest of the samples). For illumination, two 4x/0.95 NA Nikon CFI Plan Apo Lambda 4x were used when using the 10x detection objective and two 4x/0.13 NA Nikon Plan Fluor illumination objectives were used when using the 4x detection objective. </p> <p>Microscope: MuVi SPIM (Luxendo), LCS SPIM (Luxendo, only <em>Sepia officinalis</em> and 60 DPH <em>Octopus vulgaris</em> individuals).</p> <p>All the data has been scaled in order to reduce file sizes. Full size stacks can be requested to dgvilar@gmail.com.</p>
Dataset accompanying the publication "Towards 3D determination of the surface roughness of core-shell microparticles as a routine quality control procedure by scanning electron microscopy"
<p>This dataset accompanies the following publication:</p> <p>Hülagü, D., Tobias, C., Dao, R., Komarov, P., Rurack, K., Hodoroaba, V.-D., Towards 3D determination of the surface roughness of core-shell microparticles as a routine quality control procedure by scanning electron microscopy. Sci.Rep, <span>14<span>, 17936 (2024), https://doi.org/10.1038/s41598-024-68797-7.</span></span></p> <p>It contains SEM and AFM-in-SEM images of polystyrene (PS) core particles, polystyrene-iron oxide (PS/Fe3O4) core-shell particles, and polystyrene-iron oxide-silica (PS/Fe3O4/SiO2) core-shell-shell particles. Please refer to the publication and its supporting information for more details on the acquisition and contents of the dataset, as well as the GitHub repository at https://github.Com/denizhulagu/roughness-analysis-by-electron-microscopy.</p> <p> </p> <p>The investigated particles were produced at BAM laboratories as previously described in:</p> <p>Hülagü, D. et al. Generalized analysis approach of the profile roughness by electron microscopy with the example of hierarchically grown polystyrene–iron oxide–silica core–shell–shell particles. Adv. Eng. Mater. 24, 2101344, https://doi.org/10.1002/adem.202101344 (2022).</p> <p>Tobias, C., Climent, E., Gawlitza, K. & Rurack, K. Polystyrene microparticles with convergently grown mesoporous silica shells as a promising tool for multiplexed bioanalytical assays. ACS Appl. Mater. Interfaces 13, 207, https://dx.doi.org/10.1021/acsami.0c17940 (2020).</p>
3D Laser Scanning Data: Public Square in Murcia and Engineering Laboratory at the University of Alicante
<p>This dataset includes 3D terrestrial laser scans obtained using the Leica C10 ScanStation. The data covers two distinct scenarios:</p> <ol> <li> <p><strong>Public Square in Murcia Capital</strong>: This dataset includes two scan positions within a public square located in Murcia. Three HDTarget markers were placed, and their center or vertex coordinates are provided in the accompanying _vertices.txt file. The scans were conducted with the laser scanner leveled, but they are not registered.</p> </li> <li> <p><strong>Engineering Laboratory at the University of Alicante</strong>: This dataset consists of two scans of the Ground Engineering Laboratory at the University of Alicante. The scans were conducted with the same leveled laser scanner, and no targets were used. Between the two scans, some elements in the laboratory were slightly moved, which can be identified by comparing the point clouds.</p> </li> </ol>
Measuring avian bill size: Comparing and evaluating 3D surface scanning with traditional size estimates in Australian birds
<p>Unidimensional measurements for estimating bill size, like length and width, are commonly used in ecology and evolution, but can be criticised due to issues with repeatability and accuracy. Furthermore, formula-based estimates of bill surface area tend to assume uniform bill shapes across species, which is rarely the case. 3D surface scanning can potentially help overcome some such issues by collecting detailed external morphology and direct measurements of surface area, rather than composite estimates of size. Here, we evaluate the use of 3D surface scanners on avian museum specimens to test the repeatability of 3D-based measurements and compare these to traditional formula-based methods of estimating bill size from unidimensional measurements. Using 28 Australian bird species, we investigate inter-observer repeatability of surface area measurements from 3D surface scans. We then compare 3D-based size estimates to formula-based size estimates to infer the accuracy and precision of formula-based measurements of bill surface area. We find that morphometric measurements from 3D surface scans are highly repeatable between observers, without the need for extensive training, demonstrating an advantage over unidimensional measuring methods, like callipers. When comparing 3D-based measurements to formula-based estimates of bill surface area, most formulae for estimating size consistently underestimate surface area, and with considerable variation between species. Where 3D scanning is not possible, we find that a commonly used cone formula for estimating bill size is most precise across diverse bill shapes, therefore supporting its use in interspecific contexts. However, we find that incorporating an additional unidimensional measure of bill curvature into formulae improves the accuracy of the calculated area. Our results reveal the high potential for 3D surface scanners in avian morphometric research, especially for studies necessitating large sample sizes collected by multiple observers, and gives suggestions for formula-based approaches to estimate bill size.</p>
3D scans of subglacial conduit under Rieperbreen, Svalbard
<p>3D scans of subglacial conduit under Rieperbreen, Svalbard. Data was collected with kinect_record from the libfreenect project (https://github.com/mankoff/kinect_record ). See <a href="https://github.com/mankoff/Hansbreen_2012">https://github.com/mankoff/Hansbreen_2012</a>, DOI <a href="https://dx.doi.org/10.1029/2018gl079590">10.1029/2018gl079590</a> and DOI <a href="https://dx.doi.org/10.1017/jog.2016.134">10.1017/jog.2016.134</a> for more information.</p>
Body-fit and Body-rgb (NOMO-3d-4K-scans)
<p>For details, see <strong>Silhouette Body Measurement Benchmarks</strong> (ICPR2020).</p> <p>Cite this article</p> <blockquote> <p>S. Yan, J. Wirta and J. -K. Kämäräinen, "Silhouette Body Measurement Benchmarks," <em>2020 25th International Conference on Pattern Recognition (ICPR)</em>, 2021, pp. 7804-7809, doi: 10.1109/ICPR48806.2021.9412708.</p> </blockquote> <p>or </p> <blockquote> <pre>@INPROCEEDINGS{yansilh, author={Yan, Song and Wirta, Johan and Kämäräinen, Joni-Kristian}, booktitle={2020 25th International Conference on Pattern Recognition (ICPR)}, title={Silhouette Body Measurement Benchmarks}, year={2021}, volume={}, number={}, pages={7804-7809}, doi={10.1109/ICPR48806.2021.9412708}} </pre> </blockquote> <p><strong>We did not upload the real scan data here, because of the privacy protection for NOMO custormers, please contact the authors to access the dataset.</strong></p> <p><strong>BUT we uploaded the fits of the scans :</strong></p> <ol> <li><strong>caesar6449v_nicp_fits.zip : </strong>fits of the CAESAR mean body shape, 6449 vertices, using NICP, the same topology as "<em>Building statistical shape spaces for 3d human modeling</em>"</li> <li><strong>smpl6890v_nicp_fits.zip : </strong>fits of the SMPL template, 6890 vertices, using NICP</li> <li><strong>smpl6890v_lbfgsb_fits.zip : </strong>fits of the SMPL template, 6890 vertices, using LBFGSB algorithm</li> <li><strong>rendered_rgb.zip : </strong>rendered RGB images with SMPL fits, using SURREAL algorithm, with random RGB background images, random noisy background images, and silhouettes.</li> <li><strong>smpl_lbfgsb_params.zip : </strong>parameters of SMPL LBFGSB fits, can be used for initial meshes for NICP</li> <li><strong>bodymeasurement_mat.zip : </strong>body measurements from a tailor, the tailor did the measurement on the customer body, so there may be differences between scans and real body.</li> </ol> <p><strong>For body measurements, if needed, you can define the measurement paths by yourself.</strong></p> <p>The scans are collected by NOMO Technologies (https://nomo3d.com/) Ltd, Finland.</p> <p>We scanned 1474 male and 2675 female 3D body scans (<strong>BODY-fit</strong>), and captured a realistic RGB dataset (<strong>BODY-rgb</strong>) of 86 male and 108 female subjects and manually tape measured ground truth.</p> <p>This <em>database</em> is only used for scientific purpose. Companies need to contact NOMO Technologies for commercial purpose.</p> <p>-----------------------------------<br> <em>The database can be freely donwloaded and used for scientific research purposes. You are not allowed redistribute or modify it. Proper citing of this resource is expected if the database is used in research or other reporting. </em></p> <p><em>The database is meant to be useful, but it is distributed WITHOUT ANY WARRANTY, and without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.</em></p> <p><em>Inclusion of this database or even parts of it in a proprietary program is not allowed without a written permission from the owners of the copyright. If you wish to obtain such a permission, you should contact:</em></p> <p> <strong>Sizey Ltd</strong></p> <p><strong> Company ID: 2642975-3</strong></p> <p><strong> Company address: Metsänneidonkuja 6, 02130 Espoo Finland</strong></p> <p><strong> Contact e-mail: sizey (at) sizey.ai</strong></p> <p>OR:</p> <ul> <li><a href="https://scholar.google.com/citations?user=nmLU3wwAAAAJ&hl=en"><strong>Song Yan</strong></a>, <em>song.yan at tuni.fi</em></li> <li><a href="http://vision.cs.tut.fi/personal/JoniKamarainen/"><strong>Joni-Kristian Kämäräinen</strong></a>, <em>joni.kamarainen at tuni.fi</em></li> <li><a href="https://nomo3d.com"><strong>Johan Wirta</strong></a>, <em>johan.wirta at nomo3d.com</em></li> </ul> <p> </p>
Benchmark table 3D scanning applications
<p>Benchmark results of the native Leica software and several iPad LiDAR scanning solutions, measured within the 2.17 classroom of the Product Development campus at the University of Antwerp</p>
Whole-Brain 3D MRF and MRI Multi-Scanner, Scan-Rescan Dataset at 3T
<p>This repository contains a multi-scanner, scan-rescan dataset comprising thirty (30) whole-brain 3D MRI acquisitions. Each scan acquisition (n = 30) includes whole-brain quantitative MRI maps (MRF T1, MRF T2, and ADC) and weighted MR images (T1w MPRAGE, T2w SPACE, and T2w FLAIR). Five healthy subjects (deidentified) were scanned over three scanners (all 3T field strength). Each subject was scanned twice per scanner, for a total of 30 scans (5 subjects × 3 scanners × 2 scans). All data was acquired at University Hospitals Cleveland Medical Center and Case Western Reserve University.</p> <p> </p> <p>This dataset was used in the analysis for the following research article published in Investigative Radiology: "<strong><a href="https://journals.lww.com/investigativeradiology/fulltext/9900/physics_informed_discretization_for_reproducible.159.aspx">Physics-Informed Discretization for Reproducible and Robust Radiomic Feature Extraction Using Quantitative MRI</a></strong>" and request this article be referenced in all research works that use this dataset.</p>
Doppler-only Single-scan 3D Vehicle Odometry
<p>Dataset provided with the article of the same name. Created to test the performance of 3D Doppler-capable radar odometry in outdoor scenarios. Sensors mounted on the vehicle include a 3D Doppler-capable radar, 3D lidar, and an IMU. </p>
BMP-2 photogrammetry 3D scan
This 3D model was generated with the photogrammetry software 3DF Zephyr v4.530 processing 683 images of which abuot 430 where DSLR RAW images and the rest being from 2 iPhone videos. **This 3D model is to be used as reference for 3D artists.** Originially created for [Gunner, HEAT, PC!](https://www.gunnerheatpc.com/)(GHPC). The BMP-2 (Boyevaya Mashina Pekhoty, Russian: Боевая Машина Пехоты, literally "infantry combat vehicle") is a second-generation, amphibious infantry fighting vehicle introduced in the 1980s in the Soviet Union, following on from the BMP-1 of the 1960s. This specific BMP-2 was used by the NVA the army of East Germany.  Source: Objaverse 1.0 / Sketchfab
Church Main Hall - SiteScape 3D Scan
3D point cloud scan of an old methodist church, ready for some renovations! Captured with the SiteScape beta app for the 2020 iPad Pro. Request an invite to the SiteScape Beta at: https://www.sitescape.ai/ Source: Objaverse 1.0 / Sketchfab
Old Lamp Poll 3D Scan - Highpoly (Free Download)
Section of a lamp 3D scanned - Highpoly (Free Download) Iv'e made it downloadable, use it how ever you wish. But if you make something cool please send it my way so I can check it out. Make sure you check out my page for the cleaned/poly reduced version. Have a good one 👍 Source: Objaverse 1.0 / Sketchfab
Samurai Helmet 3D Scan
Here is one of my best 3d scans. The scan took place in Copenhagen national museum. You are free to edit and use it. Source: Objaverse 1.0 / Sketchfab
manhole cover 3d scan
Old, worn and rusty manhole cover. Photogrammetry 3d scan. High res poly, 4k texture, normals. Source: Objaverse 1.0 / Sketchfab
Azure Window - 3D scan before the collapse, 2016
The Azure Window was a limestone natural arch in Gozo, Malta. It collapsed on March 8th, 2017, during a strong storm.  This model was made from 102 still frames from [this video](https://www.youtube.com/watch?v=Rv_rLS_4bkc) by [The Maltese Drone](https://www.youtube.com/channel/UCDE3rpUz6ij-vanNW02by5g) About the Azure Window: https://en.wikipedia.org/wiki/Azure_Window Source: Objaverse 1.0 / Sketchfab
3D orthogonal woven carbon fibre fabric and composites - Micro-computed tomography scans
<p>Computed tomography images of a 3D orthogonal woven carbon fibre fabric and composites. Detailed description can be found in the attached metadata files as well as in the associated paper: <a href="https://doi.org/10.1016/j.compositesa.2013.10.004">https://doi.org/10.1016/j.compositesa.2013.10.004</a></p> <p>The sample was used for geometrical analysis and for creating a TexGen model with the subsequent permeability and mechanical modelling.</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.