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 …

Increased global competition has placed a premium on customer satisfaction, and there is a
greater demand for manufacturers to be flexible with their products and services. This …

Accurate whole-body multi-person pose estimation and tracking is an important yet
challenging topic in computer vision. To capture the subtle actions of humans for complex …

We introduce YOLO-pose, a novel heatmap-free approach for joint detection, and 2D multi-
person pose estimation in an image based on the popular YOLO object detection …

We present an efficient high-resolution network, Lite-HRNet, for human pose estimation. We
start by simply applying the efficient shuffle block in ShuffleNet to HRNet (high-resolution …

Given two images depicting a person and a garment worn by another person, our goal is to
generate a visualization of how the garment might look on the input person. A key challenge …

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 …

Human pose estimation deeply relies on visual clues and anatomical constraints between
parts to locate keypoints. Most existing CNN-based methods do well in visual …

Heatmap-based methods dominate in the field of human pose estimation by modelling the
output distribution through likelihood heatmaps. In contrast, regression-based methods are …

While CNN-based models have made remarkable progress on human pose estimation,
what spatial dependencies they capture to localize keypoints remains unclear. In this work …