datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
3d-spatial-reasoning-2amara-spatial-10k
AmaraSpatial-10K
A Semantically Anchored, Metric-Scale 3D Dataset for Embodied AI and Spatial Computing
10,071 AI-generated 3D meshes across 10 top-level categories and 476 subcategories — from basilisks to bassoons, cottages to cosmic stations — curated by Zero One Creative to close the spatial alignment gap that makes most generative 3D repositories unusable for zero-shot deployment in game engines, robotics simulators, and AR/VR pipelines.
Every asset is… See the full description on the dataset page: https://huggingface.co/datasets/ZeroOneCreative/amara-spatial-10k.SpatialEdit-500K
SpatialEdit-500K
SpatialEdit-500K is a synthetic training dataset for fine-grained image spatial editing. It is built for learning geometry-aware edits such as object moving, object rotation, and camera viewpoint change.
The dataset was introduced in the paper SpatialEdit: Benchmarking Fine-Grained Image Spatial Editing. It is generated with a controllable rendering pipeline to provide structured spatial transformations at scale.
Project Resources
GitHub Repository:… See the full description on the dataset page: https://huggingface.co/datasets/EasonXiao-888/SpatialEdit-500K.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.qwen_trajectories_finalspatial_lm_dataset
Dataset Card for Spatial LM
This is a FiftyOne 3D dataset with 19,992 samples representing indoor room point clouds with structured 3D layout and object annotations from the SpatialLM benchmark.
Each sample is an .fo3d scene containing a coloured point cloud with overlaid 3D bounding box annotations for walls, doors, windows, and furniture/objects — all browsable and queryable in the FiftyOne App.
Installation
If you haven't already, install FiftyOne:
pip install -U… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/spatial_lm_dataset.Awesome_Spatial_VQA_BenchmarksSpatialRGPT-BenchSAGE-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.spatial-moe-resultsllava_trajectorieslibero_spatial_imageThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
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"robot_type": "panda",
"total_episodes": 432,
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"fps": 10,
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"data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet",
"video_path": "videos/{video_key}/chunk-{chunk_index:03d}/file-{file_index:03d}.mp4"… See the full description on the dataset page: https://huggingface.co/datasets/lerobot/libero_spatial_image.gpt5_trajectories_finallibero_gen_spatial_combination_train_openpiSpatial457Awesome_Spatial_VQA_Benchmarks_ViewSpatial-Benchspatialuncertain
SpatialUncertain
A controlled 3D benchmark evaluating whether Vision-Language Models (VLMs) know
when not to answer spatial reasoning questions under occlusion and
perspective ambiguity.
Companion to the paper Seeing Isn't Knowing: Do VLMs Know When Not to Answer
Spatial Questions (and Why)?
Structure
SpatialUncertain/
├── questions/
│ ├── occlusion_benchmark.json # ~6,600 questions
│ ├── perspective_benchmark.json # ~3,700 questions
│ └──… See the full description on the dataset page: https://huggingface.co/datasets/Yuezhangjoslin/spatialuncertain.SpatialBlock-15k
SpatialBlock-15k
This dataset accompanies the paper SpatialBlock: Enhancing Spatial Intelligence in LVLMs via Synthetic Block-Stacking Problem. It contains 15,000 synthetic block-stacking problems for training large vision-language models (LVLMs) to improve spatial reasoning. The dataset includes three types of multiple-choice questions:
Q1: 3D-to-2D projection
Q2: viewpoint transformation
Q3: structural combination
The dataset is organized into a train split of 15,000… See the full description on the dataset page: https://huggingface.co/datasets/rsoohyun/SpatialBlock-15k.Q-Spatial-Bench
Dataset Card for Q-Spatial Bench
Q-Spatial Bench is a benchmark designed to measure the quantitative spatial reasoning 📏 in large vision-language models.
🔥The paper associated with Q-Spatial Bench is accepted by EMNLP 2024 main track!
Our paper: Reasoning Paths with Reference Objects Elicit Quantitative Spatial Reasoning in Large Vision-Language Models [arXiv link]
Project website: [link]
Dataset Details
Q-Spatial Bench is a benchmark designed to measure the… See the full description on the dataset page: https://huggingface.co/datasets/andrewliao11/Q-Spatial-Bench.libero_spatial_with_depthThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
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"robot_type": "panda",
"total_episodes": 476,
"total_frames": 60429,
"total_tasks": 10,
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"fps": 20,
"splits": {
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"data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet",
"video_path": null,
"features": {… See the full description on the dataset page: https://huggingface.co/datasets/WillMandil001/libero_spatial_with_depth.map-spatial-benchmark
Map-based Spatial Reasoning Benchmark
A multi-view map-based spatial reasoning benchmark. Each row is one multiple-choice
question instance over a registered map image; models must answer with a single option
letter. Four tasks (T1–T4), four base-map views, and controlled evidence conditions
(direct / query / oracle) and world perturbations (transform / world layers) allow
fine-grained analysis of spatial reasoning robustness.
Task overview
Task
Question… See the full description on the dataset page: https://huggingface.co/datasets/mapspatial/map-spatial-benchmark.embodied-spatial-reasoning
Embodied Spatial Reasoning Tasks
Dataset Description
This dataset is part of the embodied-spatial-reasoning project, where the agent has to actively explore the environment to determine if certain spatial relationships hold true. The tasks involve spatial reasoning with various objects and scenes. Each task includes a query about the spatial relationships between objects within a scene, which the agent must verify through exploration.
Dataset Structure
The… See the full description on the dataset page: https://huggingface.co/datasets/thanhqt2002/embodied-spatial-reasoning.SpatialVQASpatial-SSRL-81k
Spatial-SSRL-81k
📖Paper| 🏠Github |🤗Spatial-SSRL-7B Model |
🤗Spatial-SSRL-3B Model | 🤗Spatial-SSRL-Qwen3VL-4B Model |
🤗Spatial-SSRL-81k Dataset | 📰Daily Paper
Spatial-SSRL-81k is a training dataset for enhancing spatial understanding in large vision-language models. It contains 81,053 samples of five pretext tasks for self-supervised learning, offering simple, intrinsic supervision that scales RLVR efficiently.
📢 News
🚀 [2026/04/05] We have released… See the full description on the dataset page: https://huggingface.co/datasets/internlm/Spatial-SSRL-81k.SpatialEval
🤔 About SpatialEval
SpatialEval is a comprehensive benchmark for evaluating spatial intelligence in LLMs and VLMs across four key dimensions:
Spatial relationships
Positional understanding
Object counting
Navigation
Benchmark Tasks
Spatial-Map: Understanding spatial relationships between objects in map-based scenarios
Maze-Nav: Testing navigation through complex environments
Spatial-Grid: Evaluating spatial reasoning within structured environments
Spatial-Real:… See the full description on the dataset page: https://huggingface.co/datasets/MilaWang/SpatialEval.spatialvlm_qa
Synthetic Spatial Visual Language Question Answering Dataset
Automatically generated from the Blender Scene Dataset. Each example contains an image and a question-answer pair to probe metric (numeric) and relation (true/false) spatial reasoning skills.
Images: Rendered using Blender (1000 scenes, 5 random primitives each, random cameras and lighting).
Metadata: Object name, position, scale, color, material flags.
Questions: 10 per image, drawn from handcrafted templates… See the full description on the dataset page: https://huggingface.co/datasets/Litian2002/spatialvlm_qa.SAT-Spatial-VQAlibero_spatial_imageThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
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"robot_type": "panda",
"total_episodes": 432,
"total_frames": 52970,
"total_tasks": 10,
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"fps": 10,
"splits": {
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"video_path": "videos/{video_key}/chunk-{chunk_index:03d}/file-{file_index:03d}.mp4",
"features": {… See the full description on the dataset page: https://huggingface.co/datasets/theayos/libero_spatial_image.SpatialTree-Benchlibero_spatial_onlyThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v2.1",
"robot_type": "panda",
"total_episodes": 432,
"total_frames": 52970,
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"splits": {
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"data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet",
"video_path":… See the full description on the dataset page: https://huggingface.co/datasets/Mirage415/libero_spatial_only.