Name
Abstract | ||
|---|---|---|
Character customization system is an important component in Role-Playing Games (RPGs), where players are allowed to edit the facial appearance of their in-game characters with their own preferences rather than using default templates. This paper proposes a method for automatically creating in-game characters of players according to an input face photo. We formulate the above "artistic creation" process under a facial similarity measurement and parameter searching paradigm by solving an optimization problem over a large set of physically meaningful facial parameters. To effectively minimize the distance between the created face and the real one, two loss functions, i.e. a "discriminative loss" and a "facial content loss", are specifically designed. As the rendering process of a game engine is not differentiable, a generative network is further introduced as an "imitator" to imitate the physical behavior of the game engine so that the proposed method can be implemented under a neural style transfer framework and the parameters can be optimized by gradient descent. Experimental results demonstrate that our method achieves a high degree of generation similarity between the input face photo and the created in-game character in terms of both global appearance and local details. Our method has been deployed in a new game last year and has now been used by players over 1 million times. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/ICCV.2019.00025 | 2019 IEEE/CVF International Conference on Computer Vision (ICCV) |
Keywords | Field | DocType |
game character autocreation,game engine,facial content loss,physically meaningful facial parameters,parameter searching paradigm,facial similarity measurement,artistic creation process,input face photo,in-game character,facial appearance,role-playing games,character customization system,face-to-parameter translation | Computer vision,Computer science,Artificial intelligence | Conference |
Volume | Issue | ISSN |
2019 | 1 | 1550-5499 |
ISBN | Citations | PageRank |
978-1-7281-4804-5 | 4 | 0.48 |
References | Authors | |
12 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tianyang Shi | 1 | 4 | 0.82 |
| Yi Yuan | 2 | 10 | 7.65 |
| Changjie Fan | 3 | 57 | 21.37 |
| Zhengxia Zou | 4 | 123 | 15.80 |
| Zhenwei Shi | 5 | 559 | 63.11 |
| Yong Liu | 6 | 213 | 45.82 |