Human pose estimation aims to locate the human body parts and build human body
representation (eg, body skeleton) from input data such as images and videos. It has drawn …

Long short-term memory (LSTM) has transformed both machine learning and
neurocomputing fields. According to several online sources, this model has improved …

The pandemic of coronavirus disease 2019 (COVID-19) is spreading all over the world.
Medical imaging such as X-ray and computed tomography (CT) plays an essential role in …

Estimation of the human pose from a monocular camera has been an emerging research
topic in the computer vision community with many applications. Recently, benefiting from the …

Vision-based monocular human pose estimation, as one of the most fundamental and
challenging problems in computer vision, aims to obtain posture of the human body from …

Human pose estimation aims at predicting the poses of human body parts in images or
videos. Since pose motions are often driven by some specific human actions, knowing the …

Denoising diffusion probabilistic models that were initially proposed for realistic image
generation have recently shown success in various perception tasks (eg, object detection …

Multi-frame human pose estimation in complicated situations is challenging. Although state-
of-the-art human joints detectors have demonstrated remarkable results for static images …

We propose UniPose, a unified framework for human pose estimation, based on our"
Waterfall" Atrous Spatial Pooling architecture, that achieves state-of-art-results on several …

Human Pose Estimation (HPE) is the task that aims to predict the location of human joints
from images and videos. This task is used in many applications, such as sports analysis and …