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 …

Estimation of the human pose from a monocular camera has been an emerging research
topic in the computer vision community with many applications. Recently, benefiting from the …

Given an image with multiple people, our goal is to directly regress the pose and shape of all
the people as well as their relative depth. Inferring the depth of a person in an image …

This paper focuses on the regression of multiple 3D people from a single RGB image.
Existing approaches predominantly follow a multi-stage pipeline that first detects people in …

We present an approach for 3D global human mesh recovery from monocular videos
recorded with dynamic cameras. Our approach is robust to severe and long-term occlusions …

We present SLOPER4D, a novel scene-aware dataset collected in large urban
environments to facilitate the research of global human pose estimation (GHPE) with human …

Inferring human pose from a monocular RGB image remains an interesting field of research
in computer vision. It serves as a fundamental key for many real-world applications …

In this paper, we propose a novel monocular ray-based 3D (Ray3D) absolute human pose
estimation with calibrated camera. Accurate and generalizable absolute 3D human pose …

Existing methods of multi-person video 3D human Pose and Shape Estimation (PSE)
typically adopt a two-stage strategy, which first detects human instances in each frame and …

We present Multi-HMR, a strong single-shot model for multi-person 3D human mesh
recovery from a single RGB image. Predictions encompass the whole body, ie., including …