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 …

In the last few years, the deep learning (DL) computing paradigm has been deemed the
Gold Standard in the machine learning (ML) community. Moreover, it has gradually become …

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 …

Automatic medical image segmentation has made great progress owing to powerful deep
representation learning. Inspired by the success of self-attention mechanism in transformer …

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 …

The recently developed vision transformer (ViT) has achieved promising results on image
classification compared to convolutional neural networks. Inspired by this, in this paper, we …

Human skeleton, as a compact representation of human action, has received increasing
attention in recent years. Many skeleton-based action recognition methods adopt GCNs to …

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 …

Photorealistic rendering and reposing of humans is important for enabling augmented reality
experiences. We propose a novel framework to reconstruct the human and the scene that …

Estimating the pose of multiple animals is a challenging computer vision problem: frequent
interactions cause occlusions and complicate the association of detected keypoints to the …