Graph convolutional networks (GCNs) have a strong ability to learn graph representation
and have achieved good performance in a range of applications, including social …

The advance of deep learning has shown great potential in applications (speech, image,
and video classification). In these applications, deep learning models are trained by …

Recently, the vision transformer and its variants have played an increasingly important role
in both monocular and multi-view human pose estimation. Considering image patches as …

Estimating the 2D human poses in each view is typically the first step in calibrated multi-view
3D pose estimation. But the performance of 2D pose detectors suffers from challenging …

Despite the impressive performance obtained by recent single-image hand modeling
techniques, they lack the capability to capture sufficient details of the 3D hand mesh. This …

Reconstructing 3D hand meshes from monocular RGB images has attracted increasing
amount of attention due to its enormous potential applications in the field of AR/VR. Most …

Estimating 3D hand poses from a single RGB image is challenging because depth
ambiguity leads the problem ill-posed. Training hand pose estimators with 3D hand mesh …

Estimating 3D hand pose directly from RGB images is challenging but has gained steady
progress recently by training deep models with annotated 3D poses. However annotating …

Abstract Space-time video super-resolution (STVSR) aims to construct a high space-time
resolution video sequence from the corresponding low-frame-rate, low-resolution video …

Parkinson's Disease (PD) is a commonly diagnosed movement disorder with more than 10
million patients worldwide. Its clinical evaluation relies on a rating system called MDS …