A deep learning‐based framework for fast generation of photorealistic hair animations-Reference-Cited by-同舟云学术

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A deep learning‐based framework for fast generation of photorealistic hair animations

Published:2022-09-30 Issue:2 Volume:17 Page:375-387
ISSN:1751-9659
Container-title:IET Image Processing
language:en
Short-container-title:IET Image Processing

Author:

Qiao Zhi¹^ORCID,Li Tianxing²,Hui Li¹,Liu Ruijun³

Affiliation:

1. College of Information and Electrical Engineering China Agricultural University Beijing China

2. Faculty of Information Technology Beijing University of Technology Beijing China

3. Beijing Key Laboratory of Big Data Technology for Food Safety Beijing Technology and Business University Beijing China

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/ipr2.12638

Reference42 articles.

1. Petrovic L. Henne M. Anderson J.:Volumetric methods for simulation and rendering of hair(2006)

2. Simulating the structure and dynamics of human hair: Modelling, rendering and animation

3. A mass spring model for hair simulation

4. A hybrid iterative solver for robustly capturing coulomb friction in hair dynamics

5. Iben H. Meyer M. Petrovic L. Soares O. Anderson J. Witkin A.:Artistic simulation of curly hair. In:Proceedings of the 12th ACM SIGGRAPH/Eurographics Symposium on Computer Animation pp.63–71.Association for Computing Machinery New York(2013).https://doi.org/10.1145/2485895.2485913

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Image Generation and Feedback Based on Deep Learning in Visual Communication Design;2023 International Conference on Evolutionary Algorithms and Soft Computing Techniques (EASCT);2023-10-20

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