Hands are often severely occluded by objects, which makes 3D hand mesh estimation
challenging. Previous works often have disregarded information at occluded regions …

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 …

We present a simple and effective method for 3D hand pose estimation from a single depth
frame. As opposed to previous state-of-arts based on holistic 3D regression, our method …

We propose an approach to estimate 3D human pose in real world units from a single RGBD
image and show that it exceeds performance of monocular 3D pose estimation approaches …

Despite the substantial progress in 3D hand pose estimation, inferring plausible and
accurate poses in the presence of severe self-occlusion and high self-similarity remains an …

Training an accurate 3D human pose estimator often requires a large amount of 3D ground-
truth data which is inefficient and costly to collect. Previous methods have either resorted to …

We present a multi-sensor system for consistent 3D hand pose tracking and modeling that
leverages the advantages of both wearable and optical sensors. Specifically, we employ a …

As the manipulation object of a patient transfer robot is a human, which can be considered a
complex and time-varying system, motion adjustment of a patient transfer robot is inevitable …

Human pose estimation is considered one of the major challenges in the field of Computer
Vision, playing an integral role in a large variety of technology domains. While, in the last …

In Human-Robot Interaction (HRI), accurate 3D hand pose and mesh estimation hold critical
importance. However, inferring reasonable and accurate poses in severe self-occlusion and …