State of the Art on Deep Learning-enhanced Rendering Methods

doi:10.1007/s11633-022-1400-x

CORC > 自动化研究所 > 中国科学院自动化研究所 > 学术期刊 > International Journal of Automation and Computing

	State of the Art on Deep Learning-enhanced Rendering Methods
	Qi Wang 2
刊名	Machine Intelligence Research
	2023
卷号	20 期号:6 页码:799-821
关键词	Neural rendering, computer graphics, scene representation, rendering, post-processing
ISSN号	2731-538X
DOI	10.1007/s11633-022-1400-x
英文摘要	Photorealistic rendering of the virtual world is an important and classic problem in the field of computer graphics. With the development of GPU hardware and continuous research on computer graphics, representing and rendering virtual scenes has become easier and more efficient. However, there are still unresolved challenges in efficiently rendering global illumination effects. At the same time, machine learning and computer vision provide real-world image analysis and synthesis methods, which can be exploited by computer graphics rendering pipelines. Deep learning-enhanced rendering combines techniques from deep learning and computer vision into the traditional graphics rendering pipeline to enhance existing rasterization or Monte Carlo integration renderers. This state-of-the-art report summarizes recent studies of deep learning-enhanced rendering in the computer graphics community. Specifically, we focus on works of renderers represented using neural networks, whether the scene is represented by neural networks or traditional scene files. These works are either for general scenes or specific scenes, which are differentiated by the need to retrain the network for new scenes.
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/54168]
专题	自动化研究所_学术期刊_International Journal of Automation and Computing
作者单位	1.Zhejiang Laboratory, Hangzhou 311121, China 2.State Key Laboratory of CAD&CG, Zhejiang University, Hangzhou 310058, China
推荐引用方式 GB/T 7714	Qi Wang. State of the Art on Deep Learning-enhanced Rendering Methods[J]. Machine Intelligence Research,2023,20(6):799-821.
APA	Qi Wang.(2023).State of the Art on Deep Learning-enhanced Rendering Methods.Machine Intelligence Research,20(6),799-821.
MLA	Qi Wang."State of the Art on Deep Learning-enhanced Rendering Methods".Machine Intelligence Research 20.6(2023):799-821.