Recent research on Diffusion Models and Transformers has brought significant advancements to 3D Human Pose Estimation (HPE). Nonetheless, existing methods often fail to concurrently address the issues of accuracy and generalization. In this paper, we propose a Geometry-guided Diffusion Model with Masked...
Human pose estimation (HPE) has developed over the past decade into a vibrant field for research with a variety of real-world applications like 3D reconstruction, virtual testing and re-identification of the person. Information about human poses is also a critical component in many downstream tasks...
den Uyl, "Human pose estimation in space and time using 3D CNN," in ECCVW, 2016. 7Grinciunaite A,Gudi A,Tasli E,et al.Human pose estimationin space and time using 3D CNN[M]//Lecture Notes in ComputerScience.Heidelberg:Springer,2016,9915:32-39....
Pose Recognition with Cascade Transformers paper:http://arxiv.org/abs/2104.06976 code:https://github.com/mlpc-ucsd/PRTR 原文链接 Pose Recognition with Cascade Transformers · 语雀www.yuque.com/jinluzhang/researchblog/prtr Summary 论文来自CVPR2021,是第一篇发表的基于transformer结构的human pose est...
In this paper, we focus on three critical factors to tackle human body pose estimation, namely, feature extraction, learning algorithm and camera utilization. On the feature level, we describe images using the salient interest points represented by SIFT-like descriptors, in which the posi- tion,...
In this paper, we are interested in the human pose estimation problem with a focus on learning reliable high-resolution representations. Most existing methods recover high-resolution representations from low-resolution representations produced by a high-to-low resolution network. In...
The purpose of 3D human pose estimation is to predict information such as the 3D coordinate position and angle of human joint points, and construct human representations (such as human bones) for further analysis of human posture. With the continuous adv
human pose estimation, there still remain challenges due to insufficient training data, depth ambiguities, and occlusions. The goal of this survey paper is to provide a comprehensive review of recent deep learning-based solutions for both 2D and 3D pose estimation via a systematic analysis and ...
3D Human Pose Estimation (3D-HPE) is a highly active and evolving research area in computer vision with numerous applications such as extended reality, action recognition, and video surveillance. The field has significantly advanced with deep learning, public datasets, and enhanced computational power...
With the advancement of image sensing technology, estimating 3D human poses from monocular video has become a hot research topic in computer vision. 3D human pose estimation is an essential prerequisite for subsequent action analysis and understanding. It has a wide range of applications, such as ...