DexYCB is a dataset for capturing hand grasping of objects. It can be used three relevant tasks: 2D object and keypoint detection, 6D object pose estimation, and 3D hand pose estimation. The dataset was built using 20 objects from the YCB-Video dataset, and consists of multiple trials from 10 subjects. For each trial, there is a target object with 2 to 4 other objects placed on a table. The subject is asked to start from a relaxed pose, pick up the target object, and hold it in the air. Some subjects were asked to pretend to hand over the object to someone across from them. Each action is recorded for 3 seconds, repeating the trial 5 times for each target object, each time with a random set of accompanied objects and placement. In total there are 100 trials per subject, and 1,000 trials in total for all subjects. Source: DexYCB: A Benchmark for Capturing Hand Grasping of Objects
A hand-object interaction dataset with 3D pose annotations of hand and object. The dataset contains 66,034 training images and 11,524 test images from a total of 68 sequences. The sequences are captured in multi-camera and single-camera setups and contain 10 different subjects manipulating 10 different objects from YCB dataset. The annotations are automatically obtained using an optimization algorithm. The hand pose annotations for the test set are withheld and the accuracy of the algorithms on the test set can be evaluated with standard metrics using the CodaLab challenge submission(see project page). The object pose annotations for the test and train set are provided along with the dataset.
ARCTIC is a dataset of free-form interactions of hands and articulated objects. ARCTIC has 1.2M images paired with accurate 3D meshes for both hands and for objects that move and deform over time. The dataset also provides hand-object contact information.
The dataset consists of images of Human palms captured using a mobile phone. The images have been taken in a real-world scenario like holding objects or performing simple gestures. The dataset has a wide variety of variations like illumination, distances etc. It consists of images of 3 main gestures: Frontal-open palm, Back open palm and fist with the wrist. It also has a lot of images with people wearing gloves. Dataset Features: - Captured by 4000+ unique users - Covers wide variety of palm images in indoor and outdoor scenes - Images of palm with gloves - Captured by male and female - Distributed age groups like teenage, adults and old - Captured using mobile phones - Highly diverse - Various lighting conditions like day, night, indoor and outdoor - Outdoor scene with a variety of viewpoints Annotations Format: - Classification and detection annotations available - Multiple category annotations possible - COCO, PASCAL VOC and YOLO formats To download full datasets or to submit a request for your dataset needs, please ping us at (sales@datacluster.ai)[sales@datacluster.ai] Visit www.datacluster.ai to know more.