datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
quickstart-3d
Dataset Card for quickstart-3d
This is a FiftyOne dataset with 200 samples.
Installation
If you haven't already, install FiftyOne:
pip install -U fiftyone
Usage
import fiftyone as fo
import fiftyone.utils.huggingface as fouh
# Load the dataset
# Note: other available arguments include 'max_samples', etc
dataset = fouh.load_from_hub("Voxel51/quickstart-3d")
# Launch the App
session = fo.launch_app(dataset)
Dataset Details… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/quickstart-3d.3dvs2026_papers
Dataset Card for 3dvs2026_papers
This is a FiftyOne dataset with 176 samples.
Installation
If you haven't already, install FiftyOne:
pip install -U fiftyone
Usage
import fiftyone as fo
from fiftyone.utils.huggingface import load_from_hub
# Load the dataset
# Note: other available arguments include 'max_samples', etc
dataset = load_from_hub("Voxel51/3dvs2026_papers")
# Launch the App
session = fo.launch_app(dataset)
Dataset Details… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/3dvs2026_papers.3D-PC
Summary
Visual perspective taking (VPT), the ability to accurately perceive and reason about the perspectives of others, is an essential feature of human intelligence.
Deep neural networks (DNNs) may be a good candidate for modeling VPT and its computational demands in light of a growing number of reports indicating that DNNs gain the ability to analyze 3D scenes after training on large static-image datasets.
We developed the 3D perception challenge (3D-PC) for comparing 3D… See the full description on the dataset page: https://huggingface.co/datasets/3D-PC/3D-PC.synthetic-human-expressions-poses-3d
3D Synthetic Human Poses and FACS Expressions Dataset
This is a high-fidelity synthetic dataset consisting of 10,075 pairs of 3D human character renders and detailed natural language annotations.
Dataset Structure & Generation
To ensure consistency, the dataset is generated using a single base 3D human model. The diversity of the dataset is achieved through a wide range of body poses, facial expressions, and camera angles:
Character: 1 base human model.
Camera… See the full description on the dataset page: https://huggingface.co/datasets/nadizik/synthetic-human-expressions-poses-3d.DB-3DME
DB-3DME: From Dataset to Benchmark for Human-aligned Automatic 3D Mesh Evaluation
DB-3DME is a benchmark dataset for evaluating 3D mesh generation, featuring human annotations for Geometry and Prompt Adherence, along with corresponding text prompts and GIF visualizations of generated 3D assets. It is intended to facilitate research on reliable evaluation protocols for modern 3D generative models.
Dataset Description
Each entry in the dataset links a text prompt to a… See the full description on the dataset page: https://huggingface.co/datasets/nsjia/DB-3DME.3d-printed-or-not
3d-printed-or-not: An Image Dataset of 3D-printed Prototypes
This dataset is a collection of images that are particularly relevant to engineering and design, consisting of two categories: 3D-printed prototypes, and non-3D-printed prototypes This data was collected through a hybrid approach that entailed both web scraping and direct collection from engineering labs and workspaces at Penn State University. The initial data was then augmented using several data augmentation techniques… See the full description on the dataset page: https://huggingface.co/datasets/cmudrc/3d-printed-or-not.marvel-masterpieces-with-3dmesh
Dataset Card for reconstructions
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This is a FiftyOne dataset with 255 samples.
Installation
If you haven't already, install FiftyOne:
pip install -U fiftyone
Usage
import fiftyone as fo
from fiftyone.utils.huggingface import load_from_hub
# Load the dataset
# Note: other available arguments include 'max_samples', etc
dataset =… See the full description on the dataset page: https://huggingface.co/datasets/harpreetsahota/marvel-masterpieces-with-3dmesh.3D-MammographyDataset
3D Mammography (Digital Breast Tomosynthesis) Dataset
Overview
This dataset contains annotated 3D mammography (Digital Breast Tomosynthesis, DBT) imaging data for research in breast cancer detection using machine learning.
The dataset was developed through a collaboration between iMerit, Segmed, and Advocate Health.
Full dataset access:
https://imerit.net/3d-mammogram-dataset/
Official announcement:… See the full description on the dataset page: https://huggingface.co/datasets/iMerit/3D-MammographyDataset.