Hunting out graphic images from real images using recurrent neural network and extended principal color components.
SA '18: SIGGRAPH Asia 2018 Tokyo Japan December, 2018(2018)
摘要
With recent graphics technology creates surprisingly realistic contents, most of such artificial creatures help immersive virtual experience. On the other hand, still human can recognize whether an observed visual information is real or graphic model. In this work, we propose a deep learning based graphic and real image classification method to hunt out a graphic image from real images. In order to employ a deep learning approach, we have built graphic-real image data set consists of around 25K images. Quantitative classification and qualitative graphic image hunting results are presented that helps interesting applications such as fake image detection or image realism enhancement.
更多查看译文
关键词
Graphic real image classification
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络