Machine vision, an interdisciplinary field that aims to replicate human visual perception in
computers, has experienced rapid progress and significant contributions. This paper traces …

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 …

Recent studies on 2D pose estimation have achieved excellent performance on public
benchmarks, yet its application in the industrial community still suffers from heavy model …

In this paper, we are interested in the bottom-up paradigm of estimating human poses from
an image. We study the dense keypoint regression framework that is previously inferior to …

Vision transformers have achieved great successes in many computer vision tasks. Most
methods generate vision tokens by splitting an image into a regular and fixed grid and …

With the advances of data-driven machine learning research, a wide variety of prediction
problems have been tackled. It has become critical to explore how machine learning and …

Pose estimation plays a critical role in human-centered vision applications. However, it is
difficult to deploy state-of-the-art HRNet-based pose estimation models on resource …

The objective of human pose estimation (HPE) derived from deep learning aims to
accurately estimate and predict the human body posture in images or videos via the …

In keypoint estimation tasks such as human pose estimation, heatmap-based regression is
the dominant approach despite possessing notable drawbacks: heatmaps intrinsically suffer …

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 …