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3D models, rendered datasets, physics simulation, digital twins, synthetic data generation, game engine data
1,406 datasets
Ten 3D point clouds of individual trees from various global biomes, including forests and urban areas, were captured using a Riegl VZ-400 terrestrial laser scanner. This dataset was created specifically to validate a leaf and wood classification framework for terrestrial LiDAR data. The collection provides a focused benchmark for developing and testing algorithms that separate tree components.
Matheus Boni Vicari from University College London created a set of 200 simulated 3D point clouds. The data was generated using Monte Carlo ray tracing (librat) on four 3D tree models sourced from the RAMI exercise phase four.
A 3D volumetric model of the Cottesloe Syncline district in the northwest Paterson Orogen, Western Australia, constructed using 3D Geomodeller software. The model was built by members of the Paterson Project and specialists from Geoscience Australia. The resultant model, including sections, maps, and images, was exported to Virtual Reality Modelling Language (VRML) for broad accessibility.
68 years of shark catch and netting effort data from the Shark Meshing (Bather Protection) Program in New South Wales, Australia. The dataset includes total shark catch, catch of great white, tiger, and whaler sharks, estimates of netting effort, and catch per unit effort. It was created by Lachlan C. Fetterplace and colleagues, supporting a 2019 study on shark hazard management.
156 samples comprise this image dataset hosted by Voxel51 on Hugging Face. It is designed for use with the FiftyOne computer vision toolkit, as indicated by the provided installation and usage instructions. The dataset was last updated on July 8, 2026.
A 3-D discretized model of the unit cell for a spiral antenna system embedded into a building's load-bearing wall, supplementing a journal publication. The model is provided in .STP format for import into CAD software, with material properties calculated using the ITU-R P.2040-2 model. The dataset was created by Lauri Vähä-Savo of Aalto University.
Thirty younger and thirty older adults performed a city-like virtual reality wayfinding task across multiple exposures. The dataset includes navigation performance metrics and scores from an allocentric representation assessment, revealing a bimodal distribution of performance among older adults. Authored by Yasmine Bassil and published under CC-BY-4.0 on figshare in June 2026.
An experimental study of 36 mortar mixtures prepared with varying mixing times, admixture contents, and aggregate sizes. The research evaluated the influence of air entraining admixtures (AEA), hydration stabilising admixtures (HSA), aggregate type, and mixing time on air entrainment in ready-mix mortars. The dataset likely contains results from this controlled laboratory investigation, authored by Juliana Pippi Antoniazzi.
A 1500-year record of coastal sediment accumulation preserved in beach deposits at Keppel Bay, Queensland, Australia. The dataset, hosted by the Australian Ocean Data Network, examines ridge morphology, sediment texture, and geochemistry, with a chronology built using optically stimulated luminescence (OSL) dating. The results suggest changes in shoreline accumulation rates, sediment sources, and minor relative sea-level falls.
Three glass samples were probed at 10x10x10 testing sites with variations in probing region size from 2.5 to 10 atomic distances. The data, associated with research from Johns Hopkins University, supports the investigation of local yield surface anisotropy and the prediction of plastic events under shear loading.
1456 unique data sources, including multibeam echosounders, LiDAR, and satellite-derived bathymetry, were compiled to create this 2024 national-scale depth grid for Australia. The model results from a partnership between Geoscience Australia, the Australian Hydrographic Office, and academic institutions, representing decades of data collection and analysis. It covers a vast area from 92°E to 172°E and 8°S to 60°S, including the continent, Tasmania, and several offshore territories.
Pheno4D is a dataset containing 223 samples, curated by Voxel51 and hosted on Hugging Face. It is designed for use with the FiftyOne computer vision toolkit, suggesting a focus on visual data analysis. The dataset was last updated on July 10, 2026.
Voxel51 provides a FiftyOne dataset containing 24,866 image samples organized into 23,875 groups, with slices labeled 'pre' and 'post'. The dataset was last updated on July 10, 2026.
Voxel51 provides a FiftyOne dataset with 12 samples for computer vision tasks. The dataset appears to be related to lettuce plants, likely containing annotated images. It was last updated on July 10, 2026.
A dataset likely containing results or supporting data for the RPINet model, which integrates 2D remote sensing images with 3D point cloud data for urban scene understanding. The data was created by Zhe Jing and last updated on May 22, 2026. The dataset is small, at 5.5 KB, and is stored in an XLS file format.
Zhe Jing published ablation study results for RPINet on 2026-05-22. RPINet is a Remote-Projection and Intelligent Network integrating 2D remote sensing images with 3D point cloud data for semantic segmentation of urban scenes. The dataset likely contains performance metrics from experiments conducted on the SensatUrban dataset.
A tabular dataset comparing class-wise mean Intersection over Union (mIoU) scores for semantic segmentation models on the SensatUrban benchmark. The data, stored in an XLS file of 5.5 KB, was uploaded by Zhe Jing in May 2026 under a CC-BY-4.0 license. It likely contains performance metrics for models like RPINet, which integrates 2D remote sensing images with 3D point cloud data.
RPINet achieved a mean IoU of 66.5% on the SensatUrban dataset, outperforming existing methods. This 5.5 KB Excel file, authored by Zhe Jing and last updated in May 2026, contains performance comparison data for a novel model integrating 2D images with 3D point clouds. The dataset is licensed under CC-BY-4.0 and hosted on figshare.
11,397 groups (21,407 samples) of apple orchard imagery form this FiftyOne dataset. It was created by Voxel51 and last updated on Hugging Face on 2026-07-10. The dataset is intended for computer vision applications in agriculture.
Voxel51 provides the AgroMind dataset, a collection of 21,339 samples accessible via the FiftyOne platform. The dataset page on Hugging Face contains the full description, and it was last updated on July 10, 2026. The specific content and collection method are detailed on the source page.