scholarly journals Motion Style Transfer using Variational Autoencoder

2021 ◽  
Vol 27 (5) ◽  
pp. 33-43
Author(s):  
Jewon Ahn ◽  
Taesoo Kwon
Keyword(s):  
Style Transfer ◽  
Variational Autoencoder ◽  
Motion Style

scholarly journals A Cyclic Consistency Motion Style Transfer Method Combined with Kinematic Constraints

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Huaijun Wang ◽  
Dandan Du ◽  
Junhuai Li ◽  
Wenchao Ji ◽  
Lei Yu
Keyword(s):  
Motion Capture ◽  
Human Movement ◽  
Motion Capture Data ◽  
Style Transfer ◽  
Kinematic Constraints ◽  
Film And Television ◽  
Adversarial Network ◽  
Transfer Method ◽  
Motion Style ◽  
The Cost

Motion capture technology plays an important role in the production field of film and television, animation, etc. In order to reduce the cost of data acquisition and improve the reuse rate of motion capture data and the effect of movement style migration, the synthesis technology of motion capture data in human movement has become a research hotspot in this field. In this paper, kinematic constraints (KC) and cyclic consistency (CC) network are employed to study the methods of kinematic style migration. Firstly, cycle-consistent adversarial network (CCycleGAN) is constructed, and the motion style migration network based on convolutional self-encoder is used as a generator to establish the cyclic consistent constraint between the generated motion and the content motion, so as to improve the action consistency between the generated motion and the content motion and eliminate the lag phenomenon of the generated motion. Then, kinematic constraints are introduced to normalize the movement generation, so as to solve the problems such as jitter and sliding step in the movement style migration results. Experimental results show that the generated motion of the cyclic consistent style transfer method with kinematic constraints is more similar to the style of style motion, which improves the effect of motion style transfer.

scholarly journals Unpaired motion style transfer from video to animation

2020 ◽  
Vol 39 (4) ◽  
Author(s):  
Kfir Aberman ◽  
Yijia Weng ◽  
Dani Lischinski ◽  
Daniel Cohen-Or ◽  
Baoquan Chen
Keyword(s):  
Style Transfer ◽  
Motion Style

scholarly journals Learning and transferring motion style using Sparse PCA

2019 ◽  
Vol 35 (1) ◽  
Author(s):  
Khac Phong Do ◽  
Nguyen Xuan Thanh ◽  
Hongchuan Yu
Keyword(s):  
Computer Animation ◽  
Data Driven ◽  
Large Dataset ◽  
Sparse Pca ◽  
Style Transfer ◽  
Novel Method ◽  
Motion Style ◽  
Primary Problem ◽  
Small Dataset

Motion style transfer is a primary problem in computer animation, allowing us to convert the motion of an actor to that of another one. Myriads approaches have been developed to perform this task, however, the majority of them are data-driven, which require a large dataset and a time-consuming period for training a model in order to achieve good results. In contrast, we propose a novel method applied successfully for this task in a small dataset. This exploits Sparse PCA to decompose original motions into smaller components which are learned with particular constraints. The synthesized results are highly precise and smooth motions with its emotion as shown in our experiments.

scholarly journals Efficient Neural Networks for Real-time Motion Style Transfer

2019 ◽  
Vol 2 (2) ◽  
pp. 1-17 ◽  
Author(s):  
Harrison Jesse Smith ◽  
Chen Cao ◽  
Michael Neff ◽  
Yingying Wang
Keyword(s):  
Neural Networks ◽  
Real Time ◽  
Style Transfer ◽  
Time Motion ◽  
Motion Style

scholarly journals Camera Motion Style Transfer

2010 ◽  
Author(s):  
Christian Kurz ◽  
Tobias Ritschel ◽  
Elmar Eisemann ◽  
Thorsten Thormahlen ◽  
Hans-Peter Seidel
Keyword(s):  
Camera Motion ◽  
Style Transfer ◽  
Motion Style

scholarly journals Multiple Style Transfer Via Variational Autoencoder

2021 ◽  
Author(s):  
Zhi-Song Liu ◽  
Vicky Kalogeiton ◽  
Marie-Paule Cani
Keyword(s):  
Style Transfer ◽  
Variational Autoencoder

scholarly journals On-Line Motion Style Transfer

2006 ◽  
pp. 268-279 ◽  
Author(s):  
Xiaomao Wu ◽  
Lizhuang Ma ◽  
Can Zheng ◽  
Yanyun Chen ◽  
Ke-Sen Huang
Keyword(s):  
Style Transfer ◽  
On Line ◽  
Motion Style
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