expression transfer
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2021 ◽  
Author(s):  
Gabriel Haddon-Hill ◽  
Keerthy Kusumam ◽  
Michel Valstar
Keyword(s):  

2021 ◽  
Author(s):  
Xiao S Zeng ◽  
Surya Dwarakanath ◽  
Wuyue Lu ◽  
Masaki Nakada ◽  
Demetri Terzopoulos

2021 ◽  
Author(s):  
Andrea Valenzuela ◽  
Carlos Segura ◽  
Ferran Diego ◽  
Vicenc Gomez

2021 ◽  
Vol 22 (5) ◽  
pp. 606
Author(s):  
Andrea Duggento ◽  
Dan-Mikael Ellingsen ◽  
Kylie Isenburg ◽  
Changjin Jung ◽  
Jeungchan Lee ◽  
...  

2021 ◽  
Vol 33 (2) ◽  
pp. 186-198
Author(s):  
Zhiping Yu ◽  
Jing Chi ◽  
Yanan Ye ◽  
Fuyun Dai

2021 ◽  
pp. 116-127
Author(s):  
Xiao S. Zeng ◽  
Surya Dwarakanath ◽  
Wuyue Lu ◽  
Masaki Nakada ◽  
Demetri Terzopoulos

2021 ◽  
Vol 30 ◽  
pp. 4610-4621
Author(s):  
Zhiwen Shao ◽  
Hengliang Zhu ◽  
Junshu Tang ◽  
Xuequan Lu ◽  
Lizhuang Ma

2020 ◽  
Author(s):  
Stella Graßhof

In this work, different methods are presented to create 3D face models from databases of 3D face scans. The challenge in this endeavour is to balance the limited training data with the high demands of various applications. The 3D scans stem from various persons showing different expressions, with varying number of points per 3D scan and different numbers of scans per person. This data of posed facial expressions revealed substructures, which are utilised to improve the proposed model. In the process of creating and using the models, for each specifc application objective quality criteria are carefully designed tailored to the task to quantify the quality. In total four face models built from three databases are compared based on: 3D face synthesis, 3D approximation, person and expression transfer, and 3D reconstruction from 2D. Contents Abbreviations and Nomenclature XII 1 Introduction 1 1.1 The Difficulty of Quality Assessment . . . . . . . . . . . . . . 2 1.2 Face Models ....


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