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 …

Gait recognition, which identifies individuals based on their walking patterns, is an important
biometric technique since it can be observed from a distance and does not require the …

Human pose estimation can be applied to many computer vision tasks, such as human–
computer interaction, motion recognition, and action detection. However, few previous …

Accurate 2D human pose estimation from images is vital for understanding human actions.
However, deploying the latest models, eg, regression-based models, on resource-limited …

Model-based gait recognition methods usually adopt the pedestrian walking postures to
identify human beings. However, existing methods did not explicitly resolve the large intra …

Multi-person pose estimation in crowded scenes remains a very challenging task. This
paper finds that most previous methods fail to estimate or group visible keypoints in crowded …

Single-stage models for multi-person pose estimation have garnered significant attention
due to their streamlined approach in generating person position localization and body …

Bottom-up human pose estimation decouples computational complexity from the number of
people but requires additional operations to match the detected keypoints to each human …

This work studies the multi-human parsing problem. Existing methods, either following top-
down or bottom-up two-stage paradigms, usually involve expensive computational costs. We …

Monocular 3D human pose estimation is an ill-posed problem in computer vision due to its
depth ambiguity. Most existing works supplement the depth information by extracting …