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3D models, rendered datasets, physics simulation, digital twins, synthetic data generation, game engine data
1,020 datasets
A study by Shaojin Ma, uploaded to figshare in 2026, employed computer vision to grade the age of test fabric used in washing machine performance standards. The dataset likely contains computational results for k-nearest neighbors, multilayer perceptron, linear discriminant analysis, and logistic regression classifiers trained on image features from fabric samples subjected to 1–100 accelerated washing cycles. The logistic regression model achieved accuracy scores ranging from 0.62 to 1.00 across five degradation stages.
86.4 KB of image-derived features from fabric samples undergoing 1–100 accelerated washing cycles. Shaojin Ma published this dataset on figshare in April 2026 to investigate computer vision techniques for grading fabric degradation. Features include color, texture, and area metrics extracted from wrinkle and plain weave structure information.
LR classifier achieved accuracy of 0.75, 0.75, 0.62, 0.75, and 1.00 for five fabric degradation stages. This dataset contains image features extracted from base load fabric samples subjected to 1–100 accelerated washing cycles, used to investigate computer vision for aging assessment. It was created by Shaojin Ma and uploaded to figshare on April 10, 2026.
Geoscience Australia produced free Web-viewable 3D models integrating coastal spatial data. The models combine digital elevation models, multibeam bathymetry, sediment samples, benthic habitats, and satellite imagery for the Keppel Bay and Fitzroy River area in Queensland, Australia. These models use the open-source ISO standard Virtual Reality Modelling Language (VRML) format for easy data sharing and interpretation.
Supplementary PDF files for a research article evaluating the business justification for implementing Digital Twins in legacy manufacturing systems. The files are associated with a dual-method study combining a systematic literature review and an industry survey of practitioners in the fast-moving consumer goods sector. The files were authored by Trev Bean and published on figshare in April 2026 under a CC-BY 4.0 license.
Imagery-derived point clouds classify elevation data into categories like ground and low noise. The data is organized into non-overlapping 1 km by 1 km tiles in a compressed format. The Government of Ontario maintains this dataset, with a last recorded update in March 2026.
UnrealMVS is a large-scale synthetic omnidirectional depth dataset rendered in Unreal Engine. It is designed for training and evaluating multi-view stereo networks, such as OmniMVS, on fisheye camera rigs. The dataset was created by flw-tu-dortmund and was last updated on 2026-05-22.
27 textured 3D scenes rendered for research in novel view synthesis and neural rendering. Each scene includes 401 frames captured along a predefined monocular camera trajectory. The dataset, created by Tengpaz, is a synthetic multi-scene rendering test for 3D-conditioned generative modeling.
SWOT Version C science data provides auxiliary information linking individual pixels to specific rivers and lakes. This point cloud data, covering tiles of approximately 64x64 km², includes height-constrained geolocation after reach- or lake-scale averaging. It is available in netCDF-4 format and supports the classification of water bodies from satellite observations.
SWOT Version C science data products provide a point cloud of water mask pixels over tiles approximately 64x64 km2. The data includes geolocated heights, backscatter, geophysical fields, and flags for each pixel. It is available in netCDF-4 format and represents a half swath from the SWOT instrument.
StereoDataset is a synthetic multiview stereo dataset rendered in Unreal Engine. Each scene combines a map, a character mesh, an animation clip, a validated spawn location, and a camera trajectory. The dataset was created by 'stereo-dataset' and was last updated on the Hugging Face platform in May 2026.
Experimental results for surface roughness, cutting force, and cutting power for various textured tools. The dataset is provided by Palanisamy Angappan and was last updated on May 12, 2026. It is stored in an XLS file with a size of 9.5 KB and is licensed under CC-BY-4.0.
176 chest and abdomen CT scans feature manually-traced voxel-wise mediastinal and abdominal lymph node segmentations. The collection underpins the Roth 2014 detection benchmark and Seff 2015 segmentation benchmark. It remains a widely-cited reference for thoracic-abdominal lymph node computer-aided detection work.
Keppel Bay, on the central coast of Queensland, Australia, contains a 1500-year record of coastal sediment accumulation preserved in beach deposits. The dataset, provided by Geoscience Australia, includes analyses of 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.
Geoscience Australia produced free Web-viewable 3D models of coastal data for the Keppel Bay and Fitzroy River area in Queensland, Australia. The models integrate spatial data including digital elevation models, multibeam bathymetry, sediment samples, benthic habitats, and satellite imagery. They use the open-source ISO standard Virtual Reality Modelling Language (VRML) file format for easy web transfer.
The Paterson National Geoscience Agreement project used 3D Geomodeller software to construct a three-dimensional volumetric model of the Cottesloe Syncline district in the northwest Paterson Orogen of Western Australia. The model was built by project members and specialists from Geoscience Australia, with results exported to Virtual Reality Modelling Language (VRML) for broad accessibility. This report documents the model building process and the geological insights gained from the exercise.
Karla Negrete's 2026 figshare publication presents a proof-of-concept automated image classification pipeline for detecting invasive spotted lanternfly egg masses. The method uses a support vector machine trained on 12 selected spatial texture features, achieving a mean Matthews Correlation Coefficient of 0.881 in cross-validation. The work aims to support scalable, low-cost surveillance in high-risk transport corridors.
A numerical solution dataset for an Extended Blasius Problem, generated using a non-iterative transformation method. The method, originally defined by Töpfer in 1912, solves a boundary value problem via a related initial value problem and rescaling. Numerical results were improved using mesh refinement and Richardson's extrapolation, with six decimal places verified as correct.
35 medical interns in Iran participated in a pilot randomized controlled trial comparing virtual reality with eye-tracking feedback to conventional mannequin-based training. The study, authored by Navaz Emadi and hosted on Jeehp Dataverse, measured changes in situational awareness, Advanced Trauma Life Support performance, and error scores. Data was last updated on May 20, 2026.
6.29 terabytes of raw elevation point cloud data derived from overlapping aerial photography stereo strips. The Government of Ontario's Geospatial Ontario program created this dataset using a pixel-autocorrelation process, with the record last updated in March 2026. Points are unclassified but include RGB color values extracted from the source imagery.