HyperColor: A HyperNetwork Approach for Synthesizing Auto-Colored 3D Models for Game Scenes Population

Abstract

Designing a 3D game scene is a tedious task that often requires a substantial amount of work. Typically, this task involves the synthesis and coloring of 3D models within the scene. To lessen this workload, we can apply machine learning to automate some aspects of the game scene development. Earlier research has already tackled automated generation of the game scene background with machine learning. However, model auto-coloring remains an underexplored problem. The automatic coloring of a 3D model is a challenging task, especially when dealing with the digital representation of a colorful, multipart object. In such a case, we have to “understand” the object’s composition and coloring scheme of each part. Moreover, existing single-stage methods have their caveats. We address these limitations by proposing a two-stage training approach to synthesize auto-colored 3D models. In the first stage, we obtain a 3D point cloud representing a 3D object, while in the second stage, we assign colors to points within such a cloud. Next, we generate a 3D mesh in which the surfaces are colored based on the interpolation of colored points representing vertices of a given mesh triangle. This approach allows us to develop a smooth coloring scheme.

BibTeX

				
					@ARTICLE{9830072,  author={Kostiuk, Ivan and Stachura, Przemysław and Tadeja, Sławomir K. and Trzciński, Tomasz and Spurek, Przemysław},  journal={IEEE Transactions on Games},   title={HyperColor: A HyperNetwork Approach for Synthesizing Auto-Colored 3D Models for Game Scenes Population},   year={2022},  volume={},  number={},  pages={1-10},  doi={10.1109/TG.2022.3190792}}
				
			
APA Reference

Kostiuk, I., Stachura, P., Tadeja, S. K., Trzciński, T., & Spurek, P. (2022). HyperColor: A HyperNetwork Approach for Synthesizing Auto-Colored 3D Models for Game Scenes Population. IEEE Transactions on Games, 1–10. doi:10.1109/TG.2022.3190792

Cyber-human Lab Contributors

Dr Sławomir Tadeja

Slawomir K. Tadeja is a postdoctoral research associate in the Cyber-Human Lab belonging to the Institute of Manufacturing at the University of Cambridge. Previously...