datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
3DCode
Project page
Paper
Code
3dcodebench.com
arXiv:2606.01057
gaoypeng/3dcodebench
News
[06/01/2026] Paper released on arXiv: 3DCodeBench: Benchmarking Agentic Procedural 3D Modeling Via Code.
Note. This is an open-source reproduction of 3DCodeBench.
⚠️ Under final check. The 3DCodeData/ code is still undergoing final
quality review and may contain occasional issues (non-executable scripts, mismatched
captions/renders, or imperfect geometry). If you run… See the full description on the dataset page: https://huggingface.co/datasets/YipengGao/3DCode.3d-front-rgb3D-ADAMRepository for the 3D-ADAM (3D Anomaly Detection in Additive Manufacturing) Dataset. This is the raw data for our complete dataset, separated by part-instance to allow users to utilise the dataset as desired.
We provide a single-camera (using the MechMind-Nano) subset prepared for unsupervised training at anomaly detection, localisation and segementation tasks through the anomalib library in a separate repository: here
Our ArXiv paper can also be found here: 3D-ADAM Dataset
This project has… See the full description on the dataset page: https://huggingface.co/datasets/pmchard/3D-ADAM.3dfront_render_views3d-arenaFor more information, visit the 3D Arena Space.
Inputs are sourced from iso3D.
To assist with easily running inputs, are input image URLs are provided in inputs.txt.
3d-front-ar3d-spatial-reasoning-23d_optical_flow_droid
3D Optical Flow DROID Dataset
Processed DROID robotics dataset with optical flow and scene flow annotations.
Dataset Structure
Organized by lab, each trajectory in separate tar.gz archive:
IPRL/IPRL+2023-06-19+Mon_Jun_19_23:27:48_2023.tar.gz
CLVR/CLVR+2023-...tar.gz
... (15 labs, ~33K trajectories)
Each trajectory contains:
metadata.json - Trajectory metadata
trajectory.h5 - Robot state and actions
camera_left/, camera_right/ - Camera data
rgb/ - RGB images
depth/ -… See the full description on the dataset page: https://huggingface.co/datasets/Salesforce/3d_optical_flow_droid.3D-ZeFThis is the dataset page for 3D-ZeF, the first RGB 3D multiple object tracking dataset of its kind. Zebrafish is a widely used model organism for studying neurological disorders, social anxiety, and more. Behavioral analysis can be a critical part of such research and it has traditionally been conducted manually, which is an expensive, time consuming, and subjective task.
Dataset Setup
We have used an off-the-shelf setup for capturing the dataset, which consists of two GoPro cameras… See the full description on the dataset page: https://huggingface.co/datasets/vapaau/3D-ZeF.SAGE-3D_Collision_Mesh
SAGE-3D Collision Mesh: Physics-Enabled Collision Bodies for 3D Gaussian Scenes
Paper | Project Page | Code
High-precision collision geometry dataset extracted from 1,000 indoor Mesh scenes, enabling physically accurate navigation and interaction in virtual environments.
Collision Mesh of InteriorGS data captured on Issac Sim 5.0.
📢 News
2025-12-15: Released SAGE-3D Collision Mesh dataset with collision bodies for 1000 InteriorGS scenes.… See the full description on the dataset page: https://huggingface.co/datasets/spatialverse/SAGE-3D_Collision_Mesh.3dfront-render-views3d-pinn-bedrock3dfront-render-diffuse3DSpatialBench
3DSpatialBench
This dataset repository contains a processed CSV file for 3D spatial benchmarking.
File: filtered_processed_.csv
Source path (local): /pfs/gaohongcheng/3ddata/filtered_processed_.csv
Please update this README with schema, column descriptions, and licensing info.
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.3dfront_render3D-ADAMRepository for the 3D-ADAM (3D Anomaly Detection in Additive Manufacturing) Dataset. This is the raw data for our complete dataset, separated by part-instance to allow users to utilise the dataset as desired.
We provide a single-camera (using the MechMind-Nano) subset prepared for unsupervised training at anomaly detection, localisation and segementation tasks through the anomalib library in a separate repository: here
Our ArXiv paper can also be found here: 3D-ADAM Dataset
This project has… See the full description on the dataset page: https://huggingface.co/datasets/wuzhao73/3D-ADAM.3DSRBench
3DSRBench: A Comprehensive 3D Spatial Reasoning Benchmark
We present 3DSRBench, a new 3D spatial reasoning benchmark that significantly advances the evaluation of 3D spatial reasoning capabilities of LMMs by manually annotating 2,100 VQAs on MS-COCO images and 672 on multi-view synthetic images rendered from HSSD. Experimental results on different splits of our 3DSRBench provide valuable findings and insights that will benefit future research on 3D spatially… See the full description on the dataset page: https://huggingface.co/datasets/ccvl/3DSRBench.omages_ABOThis repo hosts the processed data of the ABO dataset for the paper An Object is Worth 64x64 Pixels: Generating 3D Object via Image Diffusion.
Please refer to the project homepage, arxiv page and github repo for more details.
Dataset details
We first download the .glb ABO shapes, then we turn the .glb files into 1024x1024x12 object images using Blender 4.0. We set the maximum number of patches to 64 and set the margin to be 2%. The 1024 resolution data is in the data/ folder… See the full description on the dataset page: https://huggingface.co/datasets/3dlg-hcvc/omages_ABO.SAGE-3D_InteriorGS_usdz
SAGE-3D InteriorGS USDZ: USDZ-Format 3D Gaussian Scenes for Isaac Sim
Paper | Project Page | Code
InteriorGS dataset converted to USDZ format for seamless integration with NVIDIA Omniverse and Isaac Sim platforms.
USDZ format InteriorGS data captured on Issac Sim 5.0.
📢 News
2025-12-15: Released SAGE-3D InteriorGS USDZ dataset with 1,000 converted scenes.
📋 Overview
While the original InteriorGS dataset provides high-quality 3D… See the full description on the dataset page: https://huggingface.co/datasets/spatialverse/SAGE-3D_InteriorGS_usdz.3DHarnessBench
Probing Agentic 3D-to-Code Capabilities of Frontier Vision-Language Models
Project Page
·
GitHub
·
GitHub
Abstract
3DHarnessBench evaluates the agentic capacity of frontier vision-language models (VLMs) to recover 3D geometry as executable Blender Python code from multiple forms of target evidence. Rather than restricting every system to a single fixed input, the benchmark compares four progressively richer harnesses: Single-view, Multi-view, Active… See the full description on the dataset page: https://huggingface.co/datasets/lingada/3DHarnessBench.3D-FUTURE-FCO3D_Visual_Illusion_Depth_Estimation
3D Visual Illusion Depth Estimation Dataset
Dataset Summary
The 3D Visual Illusion Depth Estimation Dataset is designed for research on stereo and monocular depth estimation in 3D visual illusion scenes.It contains left and right stereo images, depth maps estimated from DepthAnything V2, and illusion-region masks.
Dataset Structure
Each sample in the dataset includes:
left: Left-view RGB image
right: Right-view RGB image
depth: Monocularly estimated depth… See the full description on the dataset page: https://huggingface.co/datasets/AdamYao/3D_Visual_Illusion_Depth_Estimation.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.annotated-3DGS-artifacts
Puzzle Similarity
Project page | Paper | Code
This repository contains the dataset presented in the ICCV 2025 paper "Puzzle Similarity: A Perceptually-guided Cross-Reference Metric for Artifact Detection in 3D Scene Reconstructions"Authors: Nicolai Hermann, Jorge Condor, and Piotr Didyk
Dataset Description
The Dataset consists of 36 hand-selected 3D Gaussian Splatting renderings containing common reconstruction artefacts, (aligned) ground truths, human-annotated… See the full description on the dataset page: https://huggingface.co/datasets/nihermann/annotated-3DGS-artifacts.ophnet_3d3d-front-inst-woRGBgodot_rl_3DCarParkingA RL environment called 3DCarParking for the Godot Game Engine.
This environment was created with: https://github.com/edbeeching/godot_rl_agents
Downloading the environment
After installing Godot RL Agents, download the environment with:
gdrl.env_from_hub -r edbeeching/godot_rl_3DCarParking
STS-3D-Tooth
STS-3D-Tooth
The 3D Cone-Beam CT (CBCT) subset of the STS (Semi-supervised Teeth
Segmentation) multi-modal dental dataset, as released in
Wang et al., Scientific Data 12, 117 (2025)
and used in the MICCAI 2023/2024 STS Challenges.
The companion 2D panoramic X-ray subset is hosted at
Angelou0516/STS-2D-Tooth.
Dataset Summary
Field
Details
Modality
Cone-Beam CT (CBCT), NIfTI (.nii.gz)
Body Part
Teeth (32 permanent teeth, FDI numbering)
Volumes
371… See the full description on the dataset page: https://huggingface.co/datasets/MedOtter/STS-3D-Tooth.3DCoMPaT200
3DCoMPaT200 Dataset
The 3DCoMPaT200 dataset is a comprehensive collection of 3D objects with compositional part annotations. This repository contains various formats and versions of the dataset organized for different use cases.
📁 Directory Structure
2D Folder
Contains train, validation, and test data in tar format for 10 compositions:
Training set
Validation set
Test set
Each file contains 2D representations of the objects with their corresponding… See the full description on the dataset page: https://huggingface.co/datasets/CoMPaT/3DCoMPaT200.