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FPHA Dataset
The FPHA dataset is a real-world dataset for studying hand-object interaction. -
HO-3D and FPHA Datasets
The HO-3D and FPHA datasets are real-world datasets for studying hand-object interaction. -
REGION ENSEMBLE NETWORK: IMPROVING CONVOLUTIONAL NETWORK FOR HAND POSE ESTIMA...
Hand pose estimation from monocular depth images is an important and challenging problem for human-computer interaction. Recently deep convolutional networks (ConvNet) with... -
First-person hand benchmark (FHB)
The FHB dataset contains egocentric RGB-D videos on a wide range of hand-object interactions. -
NYU Hand Pose Dataset
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. -
Stereo-based Hand Tracking Benchmark
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... -
Re:InterHand
Re:InterHand dataset is a large-scale dataset for 3D interacting hand pose estimation from a single RGB image. -
InterHand2.6M
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. -
Parallel mesh reconstruction streams for pose estimation of interacting hands
A new multi-stream 3D mesh reconstruction network (MSMR-Net) for hand pose estimation from a single RGB image.