pose
Datasets
All datasets matching “pose”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