3D human pose and shape estimationSelf-supervised learningOcclusion handlingWe consider the task of estimating 3D human pose and shape from videos. While existing frame-based approaches have made significant progress, these methods are independently applied to each image, thereby often leading to ...
2. 3D keypoint estimation Model-based 3D pose and shape estimation指的是输出parametric human body model,简单来讲就是类似游戏里的捏model,已知人体基本的静态model(rest model),然后输入一些描述参数(parameters),包括shape parameters(描述人体高矮胖瘦)、pose parameters(描述人体姿态动作),让参数改变rest model...
In this work, we present a video-based learning algorithm for 3D human pose and shape estimation. The key insights of our method are two-fold. First, to address the inconsistent temporal prediction issue, we exploit temporal information in videos and propose a self-attention module that jointly...
从单张图像中恢复出3D pose和shape。基于DeepCut,bottom-up方法预测出二维关键点坐,基于SMPL top-down 方法和二维关键点匹配 最小化目标函数,惩罚3D关键点投影和2D关键点坐标,达到了SOTA水平 贡献点: 提出了第一种从单个图像预测3D shape和pose的自动方法 提出了损失函数中的穿透项 提出了将3D关键点和2D关键...
Inthis paper, we introduce Silhouette Occlusion Index (SOI), an objective measure designed to quantify occlusion in the context of 3DHuman Pose and Shape (HPS) tasks, relying solely on SMPL and camera parameters. Further, with the recognition that differentbody regions contain varying amounts of...
论文学习笔记:Learning to Estimate 3D Human Pose and Shape From a Single Color Image,程序员大本营,技术文章内容聚合第一站。
Human2D:使用stacked-hourglass模型,对输入图像处理得到关节热力图与轮廓图 SMPL参数生成:PosePrior是全连接层,对热力图处理后得到SMPL的θ参数;ShapePrior则是卷积层与全连接层,对轮廓图处理后得到SMPL的β参数 Mesh Generator:可微SMPL生成函数,作为网络的一部分,没有可学习的参数 ...
3D human pose estimation in video with temporal convolutions and semi-supervised training 一、简介 本文是CVPR2019的文章,预测视频中的三维人体姿态,主要是通过时域上的卷积,将2D人体姿态点提升为3D人体姿态点。该方法具有通用性,可兼容多种2D人体姿态点预测方法,如Mask R-CNN、cascaded pyramid network (CPN) ...
Object-Occluded Human Shape and Pose Estimation from a Single Color Image 这是东南大学2020年在cvpr上发布的一篇3D的人体姿态估计的论文。 原文链接: https://openaccess.thecvf.com/content_CVPR_2020/html/Zhang_Object-Occluded_Human_Shape_and_Pose_Estimation_From_a_Single_Color_CVPR_2020_paper.html...
人工智能领域顶级期刊IEEE TPAMI的主编Kyoung Mu Lee教授受邀将于北京时间2023年7月19日晚8点进行线上学术讲座,本次讲座将与清华大学电子系的因材施教特色本科生培养项目联动,并且向各界学者开放,欢迎大家参与。报告题目为3D Human Pose and Sh...