The integration of machine/deep learning and sensing technologies is transforming
healthcare and medical practice. However, inherent limitations in healthcare data, namely …

Recent transformer-based solutions have been introduced to estimate 3D human pose from
2D keypoint sequence by considering body joints among all frames globally to learn spatio …

We present a unified perspective on tackling various human-centric video tasks by learning
human motion representations from large-scale and heterogeneous data resources …

Modern neural networks use building blocks such as convolutions that are equivariant to
arbitrary 2 D translations. However, these vanilla blocks are not equivariant to arbitrary 3 D …

We present an algorithm for re-rendering a person from a single image under arbitrary
poses. Existing methods often have difficulties in hallucinating occluded contents photo …

In this work, we propose a new solution to 3D human pose estimation in videos. Instead of
directly regressing the 3D joint locations, we draw inspiration from the human skeleton …

In this paper, we propose a novel monocular ray-based 3D (Ray3D) absolute human pose
estimation with calibrated camera. Accurate and generalizable absolute 3D human pose …

3D human pose estimation can be handled by encoding the geometric dependencies
between the body parts and enforcing the kinematic constraints. Recently, Transformer has …

In computer vision, models must be able to adapt to changes in image resolution to
effectively carry out tasks such as image segmentation; This is known as scale-equivariance …

With the advances in capturing 2D or 3D skeleton data, skeleton-based action recognition
has received an increasing interest over the last years. As skeleton data is commonly …