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 …

Abstract Three-dimensional (3D) human pose estimation involves estimating the articulated
3D joint locations of a human body from an image or video. Due to its widespread …

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 …

The desire to understand how the brain generates and patterns behavior has driven rapid
methodological innovation in tools to quantify natural animal behavior. While advances in …

Abstract Large-scale Text-to-Image (T2I) models have rapidly gained prominence across
creative fields generating visually compelling outputs from textual prompts. However …

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 motion prediction is a challenging task due to the stochasticity and aperiodicity of
future poses. Recently, graph convolutional network has been proven to be very effective 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 …

Automatic synthesis of realistic co-speech gestures is an increasingly important yet
challenging task in artificial embodied agent creation. Previous systems mainly focus on …

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 …