16 datasets found

A depth-based person identification dataset with 12 subjects, 300 videos, and 25 appearances per class.

A dataset of depth images collected from children under 5 years of age using a smartphone, used for height estimation.

The dataset used for testing the HandVoxNet approach for 3D hand shape and pose estimation from a single depth map.

A hand, which is an articulated object, is composed of six local parts: the palm and five independent fingers.

The dataset used for training a Convolutional Neural Network to predict a grasp quality score over all grasp poses, given a depth image of an object.

The dataset used for head pose estimation on depth images only.

The dataset used for head pose estimation on depth images only.

The dataset used for head pose estimation on depth images only.

The ICVL Hand Posture Dataset comprises a training set of over 180k depth images showing various hand poses.

The NYU Hand Pose Dataset comprises 70,000 images captured with a depth sensor in VGA resolution accompanied by ground truth annotations of positions of hand joints.

A benchmark for evaluating hand pose tracking/estimation algorithms on passive stereo. Unlike existing benchmarks, it contains both stereo images from a binocular stereo camera...

The ITOP dataset contains depth images from top and front view. The training split and the test split consist of 40k and 10k images, respectively.

BIWI dataset has total of 15,678 frames from 24 videos with 20 different subjects captured in the controlled indoor environment.

A real dataset of depth images of fabrics, with mechanical ground truth parameters, used to test and evaluate a method for estimating fabric mechanics from depth images.

A synthetic dataset of depth images of fabrics, with mechanical ground truth parameters, used to train and evaluate a method for estimating fabric mechanics from depth images.

A large-scale dataset for robotic grasp detection, containing 54000 images and 1.1 million grasp annotations.