datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
HumanGenaloha_sim_transfer_cube_humanThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v2.0",
"robot_type": "aloha",
"total_episodes": 50,
"total_frames": 20000,
"total_tasks": 1,
"total_videos": 50,
"total_chunks": 1,
"chunks_size": 1000,
"fps": 50,
"splits": {
"train": "0:50"
},
"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/lerobot/aloha_sim_transfer_cube_human.PhysicalAI-WorldModel-Synthetic-Digital-Human-Scenes
Dataset Description:
The SDG-SynHuman is a large-scale synthetic video dataset of digital humans rendered in diverse indoor and outdoor 3D environments. The dataset contains 236,937 clips, totaling approximately 5,841 hours of video, and is designed to support training and post-training of NVIDIA Cosmos world foundation models and related physical AI research.
Each sample is a temporally coherent 60-120 second video clip rendered at 1080p and 30 fps. Clips contain… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/PhysicalAI-WorldModel-Synthetic-Digital-Human-Scenes.aloha_sim_insertion_humanThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v2.0",
"robot_type": "aloha",
"total_episodes": 50,
"total_frames": 25000,
"total_tasks": 1,
"total_videos": 50,
"total_chunks": 1,
"chunks_size": 1000,
"fps": 50,
"splits": {
"train": "0:50"
},
"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/lerobot/aloha_sim_insertion_human.humanoid-everyday
Humanoid Everyday
A Comprehensive Robotic Dataset for Open-World Humanoid Manipulation
Overview
Humanoid Everyday is a large-scale, diverse humanoid manipulation dataset designed for open-world robotic learning and embodied intelligence.
It contains over 260 tasks across 7 major categories, covering dexterous manipulation, human–humanoid interaction, and locomotion-integrated activities.All data were collected through a human-supervised teleoperation pipeline… See the full description on the dataset page: https://huggingface.co/datasets/USC-PSI-Lab/humanoid-everyday.Xspark-HumanTouch
HumanTouch 数据集发布页
HumanTouch: A Multimodal System for Scalable Human-Hand Tactile Acquisition
运动展示手在做什么，触觉揭示物理世界如何响应。机器人需要理解接触丰富的交互，而不只是模仿运动轨迹。
项目主页：https://xsparkai.com/sparklab/humantouch/
出品机构：SparkLab@Xspark AI
项目负责人：Chuqiao Lyu｜lvcq@xsparkai.com
通讯作者：Wenbo Ding, Tianxing Chen, Qi Xiong
核心贡献：Chenze Yu, Eric J Chen, Wenxuan Zhu
项目成员：Youchen Lai, Raymond Lee, Daniel Li, Kai-Chong Lei, Kehe Ye, Jiahao Zhang, Yuxiao Huo, Xiwen Tan, Weining Lu, Gengqiu Yang, Junhao Gong… See the full description on the dataset page: https://huggingface.co/datasets/chuqiaoLyu/Xspark-HumanTouch.HumanVidhumanplus-1000
HumanPlus-1000
HumanPlus-1000 is a large-scale multimodal human behavior dataset
designed for learning and modeling human perception, motion, and interaction
in real-world environments.
It captures synchronized egocentric visual observations, full-body motion,
hand motion, camera motion, and 3D environment information, with the goal of
providing paired human perception–action data for embodied intelligence,
human motion modeling, and robotics.
Current Release: This repository… See the full description on the dataset page: https://huggingface.co/datasets/humanplus-ai/humanplus-1000.Robo-ValueRL
Robo-ValueRL Dataset
[Project Page] [GitHub] [Model] [Paper]
This repository contains the dataset for Robo-ValueRL: Reliable Value Estimation for Offline-to-Online Reinforcement Learning.
The Robo-ValueRL dataset provides heterogeneous real-robot experience for studying reliable value estimation, value-guided offline policy pretraining, and online residual adaptation.
Dataset Description
The Robo-ValueRL dataset contains real-robot trajectories collected on two… See the full description on the dataset page: https://huggingface.co/datasets/X-Humanoid/Robo-ValueRL.humanoid-everyday
Humanoid Everyday
A Comprehensive Robotic Dataset for Open-World Humanoid Manipulation
Overview
Humanoid Everyday is a large-scale, diverse humanoid manipulation dataset designed for open-world robotic learning and embodied intelligence.
It contains over 260 tasks across 7 major categories, covering dexterous manipulation, human–humanoid interaction, and locomotion-integrated activities.All data were collected through a human-supervised teleoperation pipeline, recording… See the full description on the dataset page: https://huggingface.co/datasets/Fizzi789/humanoid-everyday.humanoid-everyday
Humanoid Everyday
A Comprehensive Robotic Dataset for Open-World Humanoid Manipulation
Overview
Humanoid Everyday is a large-scale, diverse humanoid manipulation dataset designed for open-world robotic learning and embodied intelligence.
It contains over 260 tasks across 7 major categories, covering dexterous manipulation, human–humanoid interaction, and locomotion-integrated activities.All data were collected through a human-supervised teleoperation pipeline, recording… See the full description on the dataset page: https://huggingface.co/datasets/FedorX8/humanoid-everyday.human_behavior_atlas
Human Behavior Atlas
A large-scale multimodal dataset for human behavior understanding, spanning emotion recognition, sentiment analysis, humor detection, mental health screening, and video question answering. The dataset integrates 16 source datasets into a unified schema with audio, video, and pre-extracted features.
This dataset was used to train OmniSapiens, a foundation model for social behavior processing.
Papers:
Human Behavior Atlas: Benchmarking Unified Psychological and… See the full description on the dataset page: https://huggingface.co/datasets/HumanBehaviorAtlas/human_behavior_atlas.LA_dataset_human_made_franka_eef_Lerobotv21_260511humanoid-robots-training-dataset
Dynamic Intelligence — Humanoid Robot Training Dataset
A first-person (egocentric) video dataset of human hand manipulation, designed for training humanoid robot policies via imitation learning. Each episode captures a person performing an everyday household task — folding clothes, moving dishes, opening doors — filmed from a head-mounted iPhone using its built-in LiDAR and depth sensors.
The dataset pairs each video with frame-level 3D hand tracking and camera pose data, giving… See the full description on the dataset page: https://huggingface.co/datasets/DynamicIntelligence/humanoid-robots-training-dataset.RoboGene
Dataset Card for RoboGene-Dataset
Figure 1: Overview of the RoboGene dataset.
RoboGene is a large-scale robotic task dataset generated by a diversity-driven agentic framework. Specifically designed for Vision-Language-Action (VLA) model pre-training, it addresses the critical bottlenecks of limited scene variety and insufficient physical grounding in existing datasets, significantly enhancing the generalization capabilities of humanoid robots in complex real-world… See the full description on the dataset page: https://huggingface.co/datasets/X-Humanoid/RoboGene.Humanoid-Everyday-G1Humanoid-Everyday-G1robocasa_target_human_unifiedThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"robot_type": "robocasa",
"total_episodes": 25307,
"total_frames": 14957899,
"total_tasks": 50,
"chunks_size": 1000,
"data_files_size_in_mb": 100,
"video_files_size_in_mb": 200,
"fps": 20,
"splits": {
"train": "0:25307"
},
"data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet",
"video_path":… See the full description on the dataset page: https://huggingface.co/datasets/lerobot/robocasa_target_human_unified.human-motion-tracking-deeplabcutThis dataset is used to adapt DeepLabCut for Human motion tracking.
Structure of the dataset
videos contains 100+ videos of 4 candidates recorded during a game of darts.
labeled-data contains labels on the corresponding frames of the videos. These labels are used to adapt DeepLabCut for human motion tracking. Under labeled-data there are 2 folders for every video.
video_name has all the relevant frames extracted from the video, xy coordinates of the labels in the csv file and the… See the full description on the dataset page: https://huggingface.co/datasets/GT-Neuronext/human-motion-tracking-deeplabcut.human-motion-tracking-deeplabcutThis dataset is used to adapt DeepLabCut for Human motion tracking.
Structure of the dataset
videos contains 100+ videos of 4 candidates recorded during a game of darts.
labeled-data contains labels on the corresponding frames of the videos. These labels are used to adapt DeepLabCut for human motion tracking. Under labeled-data there are 2 folders for every video.
video_name has all the relevant frames extracted from the video, xy coordinates of the labels in the csv file and the… See the full description on the dataset page: https://huggingface.co/datasets/pratikshapai/human-motion-tracking-deeplabcut.robocasa_pretrain_human300_v3
RoboCasa Pretrain Human 300 — LeRobot v3
This is one LeRobot v3 dataset assembled from the 300 task-folder datasets in
Whalswp/robocasa_v3_official_presliced.
The direct source is the seed-0, 100-episode-per-task-folder slice of the
RoboCasa pretrain_human300 dataset soup. The merge preserves the source order:
all 65 atomic task folders first, followed by all 235 composite task folders.
The upstream simulator and dataset are provided by
RoboCasa / RoboCasa365.… See the full description on the dataset page: https://huggingface.co/datasets/Whalswp/robocasa_pretrain_human300_v3.humanoid-everyday
Humanoid Everyday
A Comprehensive Robotic Dataset for Open-World Humanoid Manipulation
Overview
Humanoid Everyday is a large-scale, diverse humanoid manipulation dataset designed for open-world robotic learning and embodied intelligence.
It contains over 260 tasks across 7 major categories, covering dexterous manipulation, human–humanoid interaction, and locomotion-integrated activities.All data were collected through a human-supervised teleoperation pipeline, recording… See the full description on the dataset page: https://huggingface.co/datasets/SmallSmartPiggy/humanoid-everyday.HumanoidArena_rawHumanoid-Everyday-H1text-2-video-human-preferences
Rapidata Video Generation Preference Dataset
This dataset was collected in ~12 hours using the Rapidata Python API, accessible to anyone and ideal for large scale data annotation.
The data collected in this dataset informs our text-2-video model benchmark. We just started so currently only two models are represented in this set:
Sora
Hunyouan
Pika 2.0
Runway ML Alpha
Luma Ray 2
Explore our latest model rankings on our website.
If you get value from this dataset and would… See the full description on the dataset page: https://huggingface.co/datasets/Rapidata/text-2-video-human-preferences.robocasa_pretrain_human300_v4_annotated5This dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"fps": 20,
"features": {
"observation.images.robot0_agentview_left": {
"dtype": "video",
"shape": [
256,
256,
3
],
"names": [
"height",
"width",
"channel"
],
"video_info": {… See the full description on the dataset page: https://huggingface.co/datasets/pepijn223/robocasa_pretrain_human300_v4_annotated5.HumanPCR
HumanPCR benchmark preview
This repository contains the preview data and code for the HumanPCR benchmark in submission.
Model Evaluation
code/evaluate.py is a utility script for evaluating your model’s predictions against ground truth and compute the accuracy.
The predictions file must be a JSON array where each element has two fields:
id: A unique identifier for the sample.
model_prediction: The model’s predicted output for that sample.
Example (predictions.json):
[… See the full description on the dataset page: https://huggingface.co/datasets/HumanPCR/HumanPCR.text-2-video-human-preferences-wan2.1
Rapidata Video Generation Alibaba Wan2.1 Human Preference
If you get value from this dataset and would like to see more in the future, please consider liking it.
This dataset was collected in ~1 hour total using the Rapidata Python API, accessible to anyone and ideal for large scale data annotation.
Overview
In this dataset, ~45'000 human annotations were collected to evaluate Alibaba Wan 2.1 video generation model on our benchmark. The up to date benchmark… See the full description on the dataset page: https://huggingface.co/datasets/Rapidata/text-2-video-human-preferences-wan2.1.humanoid-everyday-stepit
Humanoid-Everyday · stepit action（G1 子集）
一个自包含的标准 LeRobot v2.1 数据集，由原始 Humanoid-Everyday 数据集的 Unitree G1 子集
重新表达而来。与原始数据唯一的区别是 action 列被替换成了一个 41 维、包含完整 base 状态
（位置 + 姿态 + 线速度）的动作向量；其余所有列均逐字节保持不变，可直接用标准 LeRobot 加载器读取。
动作空间：41 维 = base(10) + G1 身体 29 关节 + 双手开合 2；抽取相应切片即可喂给
stepit（Unitree G1 29-DOF）控制器（见下文 stepit qpos）。
规模：4068 episodes / 1,781,092 frames / 246 tasks / 9 chunks，fps = 30，robot_type = g1。
体积：≈ 394 GB（parquet ≈ 391 GB + 视频 ≈ 3 GB + meta ≈ 2 MB）。
原始数据是 G1/H1 混合的（共… See the full description on the dataset page: https://huggingface.co/datasets/UsanoCoCr/humanoid-everyday-stepit.human_behavior_atlas
Human Behavior Atlas
A large-scale multimodal dataset for human behavior understanding, spanning emotion recognition, sentiment analysis, humor detection, mental health screening, and video question answering. The dataset integrates 16 source datasets into a unified schema with audio, video, and pre-extracted features.
This dataset was used to train OmniSapiens, a foundation model for social behavior processing.
Papers:
Human Behavior Atlas: Benchmarking Unified Psychological… See the full description on the dataset page: https://huggingface.co/datasets/DennisDengHUst/human_behavior_atlas.