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3D models, rendered datasets, physics simulation, digital twins, synthetic data generation, game engine data
1,415 datasets
A 2026 release by author 'A GISer' provides assets and a plugin for Unreal Engine 5.2. It contains decal assets for road modeling and a custom visualization environment plugin with adjustable parameters. The resource is distributed as a 1.1 GB ZIP file.
Nine synthetic datasets designed to contain planted traps for common machine learning pitfalls. The collection likely contains examples of data leakage, bias, drift, and confounding variables. It is hosted on Kaggle, but specific details about the creator, size, and license are not provided.
The lunar surface is mapped by nearly 7 billion individual laser altimeter returns from the Lunar Orbiter Laser Altimeter (LOLA). NASA organized this data into 15-degree by 15-degree tiles, compressed into the Cloud Optimized Point Cloud (COPC) format and cataloged in a Spatio-Temporal Asset Catalog (STAC) collection. The data is in latitude, longitude, and radius coordinates using the IAU 2015 30100 projection, covering the -180 to 180 longitude domain.
Geoscience Australia produced free Web-viewable 3D models of coastal seabed characteristics. The models integrate spatial data including DEMs, multibeam bathymetry, sediment samples, benthic habitats, and satellite imagery. They use the open-source ISO standard Virtual Reality Modelling Language (VRML) file format.
Articulate-100 is a collection of 100 articulated object instances spanning common household and workspace categories. The dataset was created by ArtMesh2026 and released on Hugging Face in May 2026. Each archive contains assets for a single object instance, supporting research in part-aware articulated mesh fields.
Beijing, Jinan, and Ningbo are covered by this 1.4 TB dataset containing 119,537 panoramic RGB images and an equal number of corresponding depth maps, each at 2048×4096 resolution. The dataset was created by YijingGuo and is hosted on Hugging Face. It was last updated on April 19, 2026.
Experimental data, numerical simulation data, and analysis scripts for reproducing results from the paper 'Swimming speed of schooling fish controls social interaction strength in open-loop immersive virtual reality'. The dataset is 471.2 MB and includes files in TXT, GNUPLOT, SH, PDF, DAT, PY, and ODT formats. It was authored by Ramón Escobedo and last updated on April 11, 2026.
Andreea Toiu's dataset contains 396 patent families from ten major industrial firms like Siemens and IBM, covering 2003–2023. It supports replication for a study on digital twin patent functions, with each family classified into one of three functional categories.
A quantitative dataset for a thesis assessing collaborative non-technical skills training for Norwegian maritime pilots in virtual reality. Team Bridge Resource Management (BRM) performance data was collected before, after, and six months after the training intervention, as well as during the training itself. The dataset also contains data series for the validation of a BRM measurement instrument developed for the thesis.
A 5.5 KB Excel file containing performance metrics for registration methods evaluated on the ModelNet40 dataset. The dataset was authored by Anila Johnson and last updated on April 28, 2026. It is shared under a CC-BY-4.0 license on the figshare platform.
Turf Bookings Synthetic Dataset is a machine learning-ready collection for exploratory data analysis. The dataset is synthetic, generated for modeling and analysis tasks. It was sourced from the Kaggle platform, but specific authorship, size, and update details are unknown.
16.4 KB of raw experimental data in an XLSX file, supporting statistical analyses for a study on CT-based 3D reconstruction of insect galleries. The dataset was authored by Ziwen Tong and last updated on April 28, 2026. It is shared under a CC-BY-4.0 license on the figshare platform.
ThickMesh-Data-Discovery contains example records for discovery and classification tasks related to ThickMesh/mesh-structured data. The dataset, created by usermma, consists of 4 split files named ThickMesh-zero-split_'0-3'.jsonl. It was last updated on May 12, 2026.
Three-dimensional rendering models from a paleontological study on early vascular systems. The models are provided as Blender project files and were created by Qingyi Tian. The dataset was last updated on May 27, 2026.
TaskGrasp-Pro extends the original TaskGrasp dataset with fine-grained part decompositions and part-level physical property annotations for 190 household objects. The dataset, created by WCL-Robotics, defines three task types per object instance, resulting in a total of 2,850 tasks. It includes point clouds, multi-view RGB-D images, and task-related data.
Real-world point cloud recordings of a folding and unfolding cloth, used to evaluate state-estimation models from UniClothDiff. Each rollout contains two synchronized point cloud streams derived from an Intel RealSense depth camera and a monocular RGB image. The dataset was authored by Cloth-splatters and last updated on Hugging Face in May 2026.
tw-instruct-500k-2511 is a 2025 November version of a synthetic dialogue dataset for training Taiwanese Mandarin conversational models. It combines reference-based and reference-free generation methods to produce instruction-response pairs aligned with Taiwanese context. The dataset was created by lianghsun and updated on HuggingFace in May 2026.
A multimodal dataset for 3D scene and object generation research. Each sample pairs a Blender Python script that procedurally generates a 3D object with a rendered preview image and a natural-language description. The dataset was created by MaxRondelli and last updated on Hugging Face in May 2026.
Aggregating monthly zooplankton biomass samples from nine reference stations around the Australian coastline. The sampling program analyzes community composition, biomass, and size spectrum, with data planned for interoperability through IMOS infrastructure.
A 1500-year chronology of shoreline sediment accumulation is reconstructed from beach ridge deposits in Queensland, Australia. The Australian Ocean Data Network provides this study, which analyzes ridge morphology, sediment texture, and geochemistry. Preliminary results indicate changes in sediment supply rates, source areas, and minor relative sea-level falls.