datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
RT-PosePaper
RT-Pose: A 4D Radar Tensor-based 3D Human Pose Estimation and Localization Benchmark (ECCV 2024)
RT-Pose introduces a human pose estimation (HPE) dataset and benchmark by integrating a unique combination of calibrated radar ADC data, 4D radar tensors, stereo RGB images, and LiDAR point clouds.
This integration marks a significant advancement in studying human pose analysis through multi-modality datasets.
Dataset Details
Dataset Description… See the full description on the dataset page: https://huggingface.co/datasets/uwipl/RT-Pose.MPII_Human_Pose_Dataset
Dataset Card for MPII Human Pose
MPII Human Pose dataset is a state of the art benchmark for evaluation of articulated human pose estimation.
The dataset includes around 25K images containing over 40K people with annotated body joints.
The images were systematically collected using an established taxonomy of every day human activities.
Overall the dataset covers 410 human activities and each image is provided with an activity label.
Each image was extracted from a YouTube… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/MPII_Human_Pose_Dataset.yoga_posesasl-citizen-posesdigit-pose-estimation
Dataset Details
This dataset contains time-synchronized pairs of DIGIT images and SE(3) object poses. In our setup, the robot hand is stationary with its palm facing downwards and pressing against the object on a table. The robot hand has DIGIT sensors mounted on the index, middle, and ring fingertips, all of which are in contact with the object. A human manually perturbs the object's pose by translating and rotating it in SE(2). We use tag tracking to obtain the object's pose. We… See the full description on the dataset page: https://huggingface.co/datasets/facebook/digit-pose-estimation.POSEJEPA_Training
What is?
A set of prerender 2D images from GSO datasets, including png, mask, camera calibration and poses.
Why this DATASET Could be used to others??
When training Deep Learning models for Novel View Synthesis (NVS) or 3D-to-2D Representation Learning, loading 3D meshes and rendering views on-the-fly inside PyTorch DataLoaders creates massive bottlenecks. This script solves critical problems:
Time consumption
Ram OOM
pxr-structure-pose-pool
PXR Structure Challenge — Full Multi-Model Pose Pool (184 ligands)
Every protein–ligand pose generated during the OpenADMET PXR (pregnane X receptor / NR1I2)
structure-prediction challenge, released openly with per-pose labels so the community can
reuse the compute already spent — and, we hope, crack the problem this data makes visible.
What's here
poses/<model>/<SID>.pdb — one best pose per (model, ligand). Protein chain A + ligand
(resname LIG). 15 models, up… See the full description on the dataset page: https://huggingface.co/datasets/xX-its-amit-Xx/pxr-structure-pose-pool.HumanVid_poseposeidon3dPoseidon-Reasoning-5M
Poseidon-Reasoning-5M
Poseidon-Reasoning-5M is a high-quality, compact reasoning dataset curated for advanced applications in mathematics, coding, and science. The dataset distinctly emphasizes mathematical and general reasoning challenges, ensuring its suitability for large language model (LLM) research, benchmarking, and STEM-focused educational tools.
Quick Start with Hugging Face Datasets🤗
pip install -U datasets
from datasets import load_dataset
dataset =… See the full description on the dataset page: https://huggingface.co/datasets/prithivMLmods/Poseidon-Reasoning-5M.PoseDreamerProject page: https://prosperolo.github.io/posedreamer
open_pose_controlnet
Dataset for training controlnet models with conditioning images as Human Pose
the entries have been taken from this dataset
ptx0/photo-concept-bucket
the open pose images have been generated with
controlnet_aux
for the scripts to download the files, generate the open pose and the dataset please refer to:
raulc0399/dataset_scripts
protein_ligand_cofolding_posebusters
Protein-Ligand Cofolding PoseBusters
Frozen data for the Autoresearch task
protein_ligand_cofolding_posebusters.
visible/: 20 development cases.
heldout/: 42 evaluation cases.
This revision is a storage migration of the accepted 62-case union. It does
not change any case bytes, metric, threshold, or weighting. Task images
download a pinned dataset revision during image construction and run without
Hugging Face access.
OpenDV_Poses
OpenDV Poses and Captions
This dataset contains extracted structured annotations for the OpenDV-YouTube
driving-video dataset released by OpenDriveLab as part of
DriveAGI, together with the
OpenDV-YouTube-Language
metadata. It was collected and generated as part of the
MAD project.
The repository includes:
car skeleton keypoints extracted with OpenPifPaf;
lane skeleton keypoints extracted with OpenPifPaf;
pedestrian whole-body keypoints extracted with DWPose;
image captions… See the full description on the dataset page: https://huggingface.co/datasets/AhmadRH/OpenDV_Poses.Pose_Reward_DPOCN_pose3D_V7ramanv-image-real-pose-depthpose-guided-fall-detection-icta2026
Pose-Guided Temporal Modeling for Robust Vision-Based Fall Detection
This repository contains a reproducible vision-based fall detection pipeline for an ICTA-style technical paper. It focuses on pose/keypoint dynamics, lightweight temporal modeling, ablation, and robustness tests on a 24 GB RTX 3090.
What is included
Dataset manifest builder for URFD, Multiple Cameras Fall Dataset, and generic video folders.
Pose extraction with YOLO pose models from sampled… See the full description on the dataset page: https://huggingface.co/datasets/MahedixHasan/pose-guided-fall-detection-icta2026.CN_pose3D_V10_512
CN_pose3D_V10 Processed
Processed version of tori29umai/CN_pose3D_V10
Progress
Processed: 66500/66500 images (100.0%)
Shards uploaded: 67
Processing:
Resized to 512x512 (LANCZOS)
Binary masks for white background removal
GPU-accelerated batch processing
Columns:
image: RGB (512x512)
conditioning_image: RGB pose (512x512)
mask: Binary (512x512) - 0=ignore white bg, 255=keep
text: Text prompt
Attribution
Original dataset:… See the full description on the dataset page: https://huggingface.co/datasets/AbstractPhil/CN_pose3D_V10_512.sleap_mice_hc_yolo_pose
mice_hc — Home-cage mice pose (SLEAP) converted to YOLO pose format with Annolid (https://github.com/healthonrails/annolid)
Dataset Summary
mice_hc is a two-animal pose dataset consisting of pairs of male and female white Swiss Webster mice recorded from an overhead home-cage view with light bedding. The animals are low contrast relative to background, which makes it a useful benchmark for robust pose estimation in challenging conditions.
This Hugging Face dataset… See the full description on the dataset page: https://huggingface.co/datasets/healthonrails/sleap_mice_hc_yolo_pose.pose-extra-WLASLpose6daug
pose6daug
Real-world Franka manipulation episodes with object-swap and action augmentation
artifacts. 120 training episodes over 4 objects (blue_cup, green_pear, kanu,
white_spray), dual ZED cameras (exo static + ego wrist-mounted).
Layout
Per-frame PNGs are packed into uncompressed tars per episode — the dataset has
~427k mask/plate frames and loose files hit Hugging Face's per-repo file
recommendation and API rate limits hard.
data/<object>/<NNNN>/
masks.tar… See the full description on the dataset page: https://huggingface.co/datasets/Ronaldo-GOAT/pose6daug.dw_pose_controlnet
Important Notice
This is a copy of raulc0399/open_pose_controlnet replacing openpose conditioning images
with DW pose.
Dataset for training controlnet models with conditioning images as Human Pose
the entries have been taken from this dataset
ptx0/photo-concept-bucket
the open pose images have been generated with
controlnet_aux
for the scripts to download the files, generate the openpose and the dataset please refer to:
raulc0399/dataset_scripts
Openpose to… See the full description on the dataset page: https://huggingface.co/datasets/dimitribarbot/dw_pose_controlnet.phhi_train_poseimagePose_Reward_DPO_condso100_marker_new_camera_pose_newThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v2.1",
"robot_type": "so100",
"total_episodes": 23,
"total_frames": 6047,
"total_tasks": 1,
"total_videos": 46,
"total_chunks": 1,
"chunks_size": 1000,
"fps": 30,
"splits": {
"train": "0:23"
},
"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/jiuyal2/so100_marker_new_camera_pose_new.scripted_atomic_step_pose_0.6This dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v2.1",
"robot_type": "ur5_wsg50_lego_atomic_step",
"total_episodes": 955,
"total_frames": 159935,
"total_tasks": 1,
"total_videos": 0,
"total_chunks": 1,
"chunks_size": 1000,
"fps": 20,
"splits": {
"train": "0:955"
},
"data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet",
"video_path": null… See the full description on the dataset page: https://huggingface.co/datasets/windfromthenorth/scripted_atomic_step_pose_0.6.CN_pose3D_V10table_spill_cleanup_bimanual_rgbd_segmentation_poses
Exylos Bimanual Table Spill Cleanup Rich-Modality Sample
A compact, rich-modality bimanual robot manipulation dataset for tabletop spill cleanup.
Each episode combines synchronized dual-arm Panda state/action trajectories, 7 RGB camera streams, per-frame depth maps, per-frame segmentation masks, object pose streams, phase annotations, and an objective cleanup success metric based on the remaining spill fraction.
This dataset is a rich-modality inspection sample for the Exylos… See the full description on the dataset page: https://huggingface.co/datasets/ExylosAi/table_spill_cleanup_bimanual_rgbd_segmentation_poses.IndustryShapes
IndustryShapes
Project Page | Paper
IndustryShapes is a new benchmark dataset tailored for 6D object pose estimation in industrial settings. Targeting the challenges of textureless objects, reflective surfaces, and complex assembly tools, this dataset provides high-quality RGB-D data with precise annotations to advance the state of the art in robotic manipulation.
Dataset Features
Unlike traditional datasets focused on household products, IndustryShapes introduces… See the full description on the dataset page: https://huggingface.co/datasets/POSE-Lab/IndustryShapes.