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3D models, rendered datasets, physics simulation, digital twins, synthetic data generation, game engine data
1,418 datasets
Featuring wood block decomposition data from the Litchfield Savanna site, part of a global program studying microbial and invertebrate influences on wood decay. The study used a common protocol exposing untreated Pinus radiata wood blocks to the environment with and without macroinvertebrate exclusion via plastic mesh.
Wood block decomposition assessment data from the Calperum Mallee site, part of a global program studying microbial and invertebrate influences on wood decay. The protocol involved exposing small untreated Pinus radiata wood blocks to the environment, with treatments to exclude or not exclude macroinvertebrates like termites.
Comprising wood block decomposition assessments from the Wombat Stringybark Eucalypt site, part of a global program studying microbial and invertebrate influence on wood decay. The data follows a common protocol using untreated Pinus radiata wood blocks, with experimental setups to exclude or include macroinvertebrates like termites.
Synthetic data, likely generated for machine learning model training and testing. The dataset is hosted on Kaggle, but specific details about its size, creator, and creation date are unknown. Its content and structure must be verified after download.
Comprising wood block decomposition assessments from the Robson Creek Rainforest site in 2019, part of a global program studying microbial and invertebrate influences on decay. It follows a common protocol using untreated Pinus radiata wood blocks, with treatments to exclude or include macroinvertebrates like termites.
Comprising wood block decomposition assessment data from the Warra Tall Eucalypt site in Australia, collected in 2019. It is part of a global program studying the influence of microbes and invertebrates on wood decay using a standardized protocol with untreated Pinus radiata wood blocks. The dataset is provided in CSV format.
Wood block decomposition assessment data from the Boyagin Wandoo Woodland site in Australia, collected in 2018. It is part of a global program studying the influence of microbes and invertebrates on wood decay using a common protocol with untreated Pinus radiata wood blocks. The dataset is provided in CSV, HTML, and PNG formats.
Encompassing wood block decomposition assessments from the Samford Peri-Urban site in Australia, part of a global program studying microbial and invertebrate influences on wood decay. The data follows a common protocol using untreated Pinus radiata wood blocks, with experimental controls for macroinvertebrate exclusion. Row and column counts are not specified in the input.
Encompassing wood block decomposition assessment data from the Cumberland Plain site in Australia, part of a global program studying microbial and invertebrate influences on wood decay. The study used a common protocol exposing small pieces of untreated Pinus radiata wood to the environment, with and without macroinvertebrate exclusion via plastic mesh.
Approximately 3.65 GB of 3D assets and textures for the RoboCasa simulation environment in VLAForge. The collection includes objects from Objaverse, Sketchfab, and Lightwheel, plus environment and AI-generated textures. Livfour uploaded this dataset on Hugging Face, with a last recorded update on 2026-04-11.
Insta360-Research provides a high-fidelity simulation platform and a large-scale synthetic dataset called Omni360-X, last updated on 2026-04-11. The dataset is designed for panoramic vision, closed-loop reconstruction, and autonomous system training. The repository hosts both the AirSim360 software and the associated synthetic dataset.
A custom synthetic dataset designed for salary analysis, exploratory data analysis, SQL, and machine learning projects. The dataset likely contains features relevant to data science compensation across global regions. Its synthetic nature suggests it was generated for educational or benchmarking purposes.
A dataset released in April 2026 by yejunliang23 as the official data for the Nano3D framework. It supports a training-free approach for precise and coherent 3D object editing without masks, as described in the associated research paper and project page.
DB-HLSTM Synthetic Data is a dataset published on Kaggle. The title and platform tags suggest it contains synthetic data likely generated for modeling time series with LSTM neural network architectures. The dataset's specific content, size, and creation details are not provided in the available metadata.
Synthetic security data produced by Zia Data Labs for developers, ML engineers, QA teams, and data pipelines. The dataset is production-grade and intended for training purposes. The author is ziadatalabs, and the listing was last updated on April 29, 2026.
100 AQMesh sensor pods form a stationary network measuring air pollutants in near real-time. The pods collect data on nitrogen dioxide (NO₂), nitric oxide (NO), particulate matter (PM₂.₅, PM10), carbon dioxide (CO₂), and in some locations ozone (O3), along with temperature, humidity, and air pressure. The data is collected by the Greater London Authority, with the last metadata update recorded on 2026-03-25.
DB-HLSTM-Synthetic Data is a dataset published on Kaggle. The title suggests it contains artificially generated sequences, likely for testing or benchmarking machine learning models, particularly those based on LSTM architectures. No information is available regarding its size, creator, or specific contents.
A FiftyOne dataset with 12 samples, created by Voxel51 and last updated on March 17, 2026. The dataset appears to contain 3D graphics data, likely including images and point clouds.
Zooplankton collections from 21 stations in the Chukchi Sea during August 1953 and 1954. Vertical stratified tows were conducted using a Nansen net, with accompanying temperature, salinity, and oxygen measurements. The data were collected by the Russian R/V Lomonosov under program ANII A-65 to investigate interannual changes in species composition, abundance, and distribution.
Vertical stratified zooplankton collections from the Chuckchi Sea in the Arctic Ocean during August of 1953 and 1954. The dataset includes measurements of temperature, salinity, and oxygen concentrations at multiple depth layers across 21 stations, collected by the Russian R/V Lomonosov under program ANII A-65. Data was gathered to assess interannual changes in species composition, abundance, and distribution.