Inferring human pose from a monocular RGB image remains an interesting field of research
in computer vision. It serves as a fundamental key for many real-world applications …

Three-dimensional human pose estimation has made significant advancements through the
integration of deep learning techniques. This survey provides a comprehensive review of …

Traditionally, monocular 3D human pose estimation employs a machine learning model to
predict the most likely 3D pose for a given input image. However, a single image can be …

Abstract 3D human pose estimation from monocular images is a highly ill-posed problem
due to depth ambiguities and occlusions. Nonetheless, most existing works ignore these …

Understanding social interactions from egocentric views is crucial for many applications,
ranging from assistive robotics to AR/VR. Key to reasoning about interactions is to …

Learning-based methods have dominated the 3D human pose estimation (HPE) tasks with
significantly better performance in most benchmarks than traditional optimization-based …

Existing self-supervised 3D human pose estimation schemes have largely relied on weak
supervisions like consistency loss to guide the learning, which, inevitably, leads to inferior …

Egocentric 3D human pose estimation using a single fisheye camera has become popular
recently as it allows capturing a wide range of daily activities in unconstrained environments …

Abstract Markerless three-dimensional (3D) pose estimation has become an indispensable
tool for kinematic studies of laboratory animals. Most current methods recover 3D poses by …

Human pose estimation from single images is a challenging problem that is typically solved
by supervised learning. Unfortunately, labeled training data does not yet exist for many …