Three-dimensional quantitative analysis of temporal region morphology in Chinese young adult. Y Wu, C Zeng, D Feng, Z Chen, Q Fu, W Liao.
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MimicME: A Large Scale Diverse 4D Database for Facial Expression Analysis. A Papaioannou et al.
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Articulated Objects in Free-form Hand Interaction. Z Fan, O Taheri, D Tzionas, M Kocabas, M Kaufmann, MJ Black, O Hilliges.
Introducing ARCTIC – the first dataset of free-form interactions of hands and articulated objects. ARCTIC has 1.2M images paired with accurate 3D meshes for both hands and for objects that move and deform over time. The dataset also provides hand-object contact information.
Khronos Group Welcomes 3dMD as Contributor Member.
The Khronos Group is creating interoperability standards for 3D, AR/VR, vision, and machine learning.
Projection-wise Disentangling for Fair and Interpretable Representation Learning: Application to 3D Facial Shape Analysis. X Liu, B Li, E Bron, W Niessen, E Wolvius, G Roshchupkin.
The proposed method was evaluated on the analysis of 3D facial shape and patient characteristics (N=5011). Experiments showed that this conceptually simple method achieved state-of-the-art fair prediction performance and interpretability, showing its great potential for clinical applications.
3D human tongue reconstruction from single “in-the-wild” images. S Ploumpis, S Moschoglou, V Triantafyllou, S Zafeiriou.
In this work, we presented the first pipeline which is able to perform 3D head and tongue reconstruction from a single image. To achieve this, we collected the first diverse tongue dataset with various tongue shapes and positions which we make publicly available to the research community.
Posture-Invariant 3D Human Hand Statistical Shape Model. Y Yang, T Yuan, T Huysmans, WS Elkhuizen, F Tajdari, Y Song.
It is concluded that the proposed posture correction approach can effectively improve the accuracy of the hand SSM and therefore enables its wide usage in human-integrated digital twin applications.
Anthropometric accuracy of three-dimensional average faces compared to conventional facial measurements. Z Shan, R TC Hsung, C Zhang et al.
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Statistical Shape and Pose Model of the Forearm for Custom Splint Design. F Danckaers, JV Houtte, BG Booth, F Verstreken and J Sijbers.
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Three-dimensional virtual planning in mandibular advancement surgery: soft tissue prediction based on deep learning. R ter Horst, H van Weert, T Loonen, S Bergé, S Vinayahalingam, F Baan, T Maal, G de Jong, T Xi.
This study focused on developing a novel deep-learning (DL)-based algorithm to predict the virtual soft tissue profile after mandibular advancement surgery and comparing its accuracy with the mass tensor model (MTM).