Sign language, as a different form of the communication language, is important to large
groups of people in society. There are different signs in each sign language with variability …

Most of the existing deep learning-based methods for 3D hand and human pose estimation
from a single depth map are based on a common framework that takes a 2D depth map and …

A machine can understand human activities, and the meaning of signs can help overcome
the communication barriers between the inaudible and ordinary people. Sign Language …

For 3D hand and body pose estimation task in depth image, a novel anchor-based approach
termed Anchor-to-Joint regression network (A2J) with the end-to-end learning ability is …

In this paper, we strive to answer two questions: What is the current state of 3D hand pose
estimation from depth images? And, what are the next challenges that need to be tackled …

We present a method for the real-time estimation of the full 3D pose of one or more human
hands using a single commodity RGB camera. Recent work in the area has displayed …

Hand pose estimation from single depth images is an essential topic in computer vision and
human computer interaction. Despite recent advancements in this area promoted by …

Dynamic hand gesture recognition is a crucial yet challenging task in computer vision. The
key of this task lies in an effective extraction of discriminative spatial and temporal features to …

The Huber loss is a robust loss function used for a wide range of regression tasks. To utilize
the Huber loss, a parameter that controls the transitions from a quadratic function to an …

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 …