13 datasets found

Hand pose estimation from monocular depth images is an important and challenging problem for human-computer interaction. Recently deep convolutional networks (ConvNet) with...

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 MuViHand dataset is a synthetic multi-view video-based hand pose dataset with 402,000 synthetic hand images available in 4,560 videos.

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...

DART is a larger open-domain dataset, where triples are composed of tree-structured ontology.

Re:InterHand dataset is a large-scale dataset for 3D interacting hand pose estimation from a single RGB image.

The InterHand2.6M dataset contains 366K training samples, 110K validation samples, and 261K test samples. It is the only interacting two-hand dataset with dense shape annotations.

RenderIH dataset is a large-scale synthetic dataset for 3D interacting hand pose estimation from a single RGB image.

The Honnotate dataset is a method for 3D annotation of hand and object poses.

A new multi-stream 3D mesh reconstruction network (MSMR-Net) for hand pose estimation from a single RGB image.

CORe50 is a video benchmark for continual learning, consisting of 164,866 128x128 images of 50 domestic objects belonging to 10 categories.