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3D models, rendered datasets, physics simulation, digital twins, synthetic data generation, game engine data
1,020 datasets
24 sequences simulate articulated object motion for 17 categories from PartNet-Mobility, including Camera, Chair, and Refrigerator. The dataset supports research on reconstructing articulated digital twins from monocular video, as presented in the associated paper by author ShawnRicardo.
1 million rows of synthetic data designed for predicting gym membership churn. The dataset likely contains features related to customer demographics and behavior patterns. It originates from Kaggle, but specific authorship and update details are unknown.
A synthetic dataset for bin picking tasks involving mechanical rod ends. The data likely contains images or 3D representations of rod ends placed in cluttered industrial bins. It was uploaded to Kaggle, but details about its creator, size, and update date are unknown.
A synthetic dataset of 1000 utility store product purchases. It contains over 1000 rows of simulated transaction data. The dataset was sourced from Kaggle, but its author, organization, and last update date are unknown.
An R package implementation of the 3D alpha-shape algorithm for reconstructing surfaces from point clouds. The package, authored by Beatriz Pateiro-López, generalizes the convex hull to model non-convex and non-connected 3D shapes. It provides functions for computing volume, identifying connected components, and visualizing the estimated 3D set.
A synthetic dataset for training and evaluating robotic bin-picking systems. The data likely contains images of mechanical pistons arranged in cluttered industrial bins, simulating a common manufacturing challenge. The dataset's author, organization, and exact size are unspecified.
A synthetic dataset simulating factors related to burnout, stress, productivity, and habits. The dataset was found on Kaggle, but its author, organization, and specific creation date are unknown. The exact number of records and features is unspecified.
Kaggle hosts a synthetic dataset of mechanical hinges in cluttered industrial bins. The dataset likely contains images or point clouds generated for simulation purposes. Its author, organization, and specific size are unknown.
10 million chemical structure images sourced from real-world documents like patents, scientific literature, books, and websites. MolGallery captures complex noise, diverse rendering styles, and scanning artifacts absent in synthetic datasets. The dataset was created by UniParser and last updated on March 17, 2026.
USGS 3DEP LiDAR Point Clouds provide two realizations of high-resolution elevation data for the conterminous United States, Hawaii, and U.S. territories. The data was collected over an 8-year period by the U.S. Geological Survey's 3D Elevation Program. One resource is a public access, full-density streamable format, while the other is a more complete, requester-pays version of the original raw data.
RealX3D provides multi-view RGB images in JPEG and Sony RAW formats, COLMAP sparse reconstructions, and high-precision 3D ground-truth geometry. The benchmark includes a diverse set of scenes and challenging degradation types like low light and smoke for visual restoration and reconstruction tasks.
Finevision_iam is a FiftyOne dataset with 5,663 samples, authored by Voxel51. The dataset is hosted on Hugging Face and was last updated on February 9, 2026. It is associated with platform tags for OCR, image modality, and visual document retrieval.
A synthetic dataset published on Kaggle for machine learning model development. The dataset likely contains artificially generated data designed for training and testing algorithms. Its specific content, size, and creator are unknown from the provided metadata.
Aerial laser surveys, airborne laser bathymetry, and mobile mapping systems were used to produce this high-precision 3D point cloud data covering all prefectures in Japan. The dataset, published by AIGID under a CC-BY-4.0 license, represents the culmination of many years of dedicated effort. It is hosted on AWS Open Data and is intended for visualization and analysis.
Point clouds and depth maps derived from the Hypersim dataset, re-rendered with all objects removed to retain only the first structural layout surface and its normal map. The dataset was created by user 'hugsam' and was last updated on March 6, 2026. It originates from Apple Inc.'s Hypersim dataset of photorealistic synthetic indoor scenes.
A dataset from Kaggle focusing on mapping relationships within the OpenAlex scholarly database. The specific content and scale require verification after download. Its structure likely represents a network of academic concepts or entities.
A synthetic dataset designed for analyzing student productivity and focus behavior. The dataset likely contains simulated records of student work sessions and breaks. Its synthetic nature allows for controlled analysis of productivity patterns.
São Paulo City Hall's 3D Digital City Map (M3DC) provides LiDAR point cloud data for the municipality. The initial data was acquired in 2017 via aerial survey, with future updates planned. The dataset is publicly accessible in the Entwine Point Tiles format, using lossless LAZ encoding.
Nemotron Challenge Synthetic dataset is a dataset hosted on Kaggle. The dataset is likely designed for AI/ML training challenges and contains synthetic data. Its specific content, size, and origin are not detailed in the available metadata.
Sc077y created a synthetic dataset of 9,852 pixel art images, each paired with a descriptive text prompt. The images are 64x64 pixels in size and use a shared 256-color palette. The dataset was generated using the FLUX.1-dev model with a Retro-Pixel LoRA and was last updated on February 26, 2026.