Learning and Tracking the 3D Body Shape of Freely Moving Infants from RGB-D sequences

17 October 2018

Papers citing "Learning and Tracking the 3D Body Shape of Freely Moving Infants from RGB-D sequences"

7 / 7 papers shown

Title
Markerless human pose estimation for biomedical applications: a survey Andrea Avogaro Federico Cunico Bodo Rosenhahn Francesco Setti 3DH 35 14 0 01 Aug 2023
Human Digital Twin: A Survey Yujia Lin L. Chen Aftab Ali C. Nugent I. Cleland Rongyang Li D. Gao Hang Wang Yajie Wang Huansheng Ning 35 27 0 12 Dec 2022
Automatic Assessment of Infant Face and Upper-Body Symmetry as Early Signs of Torticollis Michael Wan Xiaofei Huang Bethany Tunik Sarah Ostadabbas CVBM 27 3 0 26 Oct 2022
Infant movement classification through pressure distribution analysis Tomas Kulvicius Dajie Zhang K. Nielsen‐Saines Sven Bolte M. Kraft Christa Einspieler Luise Poustka F. Worgotter Peter B Marschik 15 9 0 26 Jul 2022
imGHUM: Implicit Generative Models of 3D Human Shape and Articulated Pose Thiemo Alldieck Hongyi Xu C. Sminchisescu 3DH 43 116 0 24 Aug 2021
Disentangled Human Body Embedding Based on Deep Hierarchical Neural Network Boyi Jiang Juyong Zhang Jianfei Cai Jianmin Zheng 3DH AI4CE 25 37 0 14 May 2019
DoubleFusion: Real-time Capture of Human Performances with Inner Body Shapes from a Single Depth Sensor Tao Yu Zerong Zheng Kaiwen Guo Jianhui Zhao Qionghai Dai Hao Li Gerard Pons-Moll Yebin Liu 3DH 138 271 0 17 Apr 2018