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3D models, rendered datasets, physics simulation, digital twins, synthetic data generation, game engine data
1,020 datasets
Pavo miejue NTUM-VP 241105 is a 3D model of a newly described Pleistocene peafowl species. The model, published by Yong-Jie Lan on figshare under a CC-BY-4.0 license, was last updated on 2026-05-07. It likely represents a fossil specimen from Taiwan, illustrating a large galliform bird now extinct in East Asia.
10,071 AI-generated 3D meshes across 65 categories, curated by Zero One Creative. The dataset is designed for spatial alignment, with assets being metric-scaled and semantically anchored. It was last updated on April 17, 2026.
JoyAI-Image-OpenSpatial is a spatial understanding dataset built on the OpenSpatial framework. It contains approximately 3 million multi-turn visual-spatial question-answer samples aggregated from 7 open-source datasets and web data. The dataset was created by jdopensource and was last updated on April 15, 2026.
A dataset from OpenML with an unknown number of rows and columns. The specific content, features, and provenance are not detailed in the provided input.
August 2010 to September 2011 data from multiple R/V Weatherbird II cruises in the Gulf of Mexico contains short-lived radioisotope measurements, sediment core photographs, and sediment texture and composition analysis. The dataset was collected and organized by NOAA NCEI and the Gulf of Mexico Research Initiative (GOMRI). It provides high-resolution sampling of sediment cores at 2mm intervals for surficial units and 5mm intervals to the core base.
Plankton species abundance data was collected from 13 sites in the Gulf of Mexico's DeSoto Canyon during the R/V Bellows cruise BE-1311 from December 12-14, 2012. The dataset includes net tow samples categorized into broad taxonomic groups and detailed quantitative phytoplankton profiles from four sites, analyzed using a JEOL JSM-6480 LV scanning electron microscope. It was produced by NOAA NCEI and includes both count data and associated micrographs.
Synthetic data from 9 files contains measures of cognitive performance, attention tasks, and working memory assessments. It is intended to support research on cognitive neuroscience in Latin American contexts. The dataset can be used for comparative studies, methodological development, and educational purposes.
Renderings of the surface of the Ashkelon excavation site, authored by Daniel M. Master. The dataset was last updated on 2026-05-19 20:44:10.
Meta_Album_TEX_Micro is a preprocessed image dataset containing 800 texture images across 20 classes, sourced from the KTH-TIPS, Kylberg, and UIUC texture datasets. The dataset was created by Ihsan Ullah in March 2022 as part of the Meta-Album benchmark. All images are cropped to squares and resized to 128x128 pixels with an anti-aliasing filter.
2560 preprocessed texture images across 64 classes, sourced from four established academic datasets. The Meta-Album Textures (Mini) dataset was created by Ihsan Ullah in March 2022, combining and standardizing images from KTH-TIPS, Kylberg, and UIUC texture collections. All images are cropped to squares and resized to 128x128 pixels with an anti-aliasing filter.
100 objects are planned for inclusion in this dataset. Each object is captured by 514 images taken from viewpoints distributed evenly across a hemisphere. The dataset, authored by siaih22, was last updated on Hugging Face in April 2026.
January 1948 to December 2014 of 3-hourly land surface parameters simulated from the Noah Model 3.6, forced by Princeton meteorological data. The dataset is part of NASA's Global Land Data Assimilation System Version 2.0 (GLDAS-2.0) and was reprocessed in November 2019, with further post-processing in October 2020.
January 1948 to December 2014 of global land surface parameters simulated at 3-hourly intervals and 0.25 x 0.25 degree spatial resolution. The data is produced by NASA's Global Land Data Assimilation System Version 2.0 (GLDAS-2.0) using the Noah land surface model, forced with Princeton meteorological data. It was reprocessed in November 2019 and post-processed with a MODIS land mask in October 2020.
Sediment cores from the southern Gulf of Mexico, collected aboard R/V Justo Sierra cruise JS-0815 between July 31 and August 8, 2015, contain detailed chemical and biological measurements. The dataset includes concentrations of polycyclic aromatic hydrocarbons (PAHs) and biomarkers analyzed by GC-MS, FTICR-MS mass spectrometry data, sediment texture, short-lived radioisotope profiles, and species-level benthic foraminiferal assemblages. This multi-faceted data supports integrated studies of pollution, sedimentology, and ecosystem health in a marine environment.
Released in February 2026 by Tencent, HY3D-Bench is a large-scale collection of 3D datasets. It comprises over 252,000 watertight meshes with multi-view renderings, 240,000 objects with part-level decompositions, and 125,000 AI-synthesized objects across 1,252 categories. The dataset is hosted on Hugging Face and was last updated in April 2026.
A controlled millimetre-wave radar point-cloud dataset created by Guo, Kailu of milipointwithKinect. The data is designed for analyzing guided rehabilitation-related movements in standardized indoor settings. The dataset was last updated on 2026-05-18.
A dataset of spatial point clouds captured using millimetre-wave radar technology, intended for health-related applications. It was authored by Guo, Kailu of milipointwithKinect and last updated on 2026-05-18.
EgoPoseVR is a large-scale synthetic dataset for egocentric full-body pose estimation in virtual reality. It contains 18,235 motion clips with paired RGB-D observations, pose annotations, HMD tracking signals, and SMPL body parameters across 7 virtual scenes. The dataset was created by AplusX and was last updated on April 12, 2026.
Data and materials supporting a paper on individual differences in Virtual Reality experiences. The dataset likely contains measures of presence, embodiment, and engagement from a VR intervention study. It was authored by Aniek Siezinga and last updated in May 2026.
HorizonRobotics introduced ARSG-110K, a large-scale scene-level dataset comprising over 110,000 diverse scenes and 3 million annotated images. It provides high-fidelity 3D ground truth, including accurate object-level data, layout, and annotations. The dataset was last updated on April 8, 2026.