Real-Time Hair Filtering with Convolutional Neural Networks-Reference-Cited by-同舟云学术

Real-Time Hair Filtering with Convolutional Neural Networks

Published:2022-05-04 Issue:1 Volume:5 Page:1-15
ISSN:2577-6193
Container-title:Proceedings of the ACM on Computer Graphics and Interactive Techniques
language:en
Short-container-title:Proc. ACM Comput. Graph. Interact. Tech.

Author:

Currius Roc R.¹,Assarsson Ulf¹,Sintorn Erik¹

Affiliation:

1. Chalmers Institute of Technology, Gothenburg, Sweden

Abstract

Rendering of realistic-looking hair is in general still too costly to do in real-time applications, from simulating the physics to rendering the fine details required for it to look natural, including self-shadowing. We show how an autoencoder network, that can be evaluated in real time, can be trained to filter an image of few stochastic samples, including self-shadowing, to produce a much more detailed image that takes into account real hair thickness and transparency.

Funder

Vetenskapsrådet

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Graphics and Computer-Aided Design,Computer Science Applications

Link

https://dl.acm.org/doi/pdf/10.1145/3522606

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