Perceptual Adversarial Networks for Image-to-Image Transformation.

IEEE Transactions on Image Processing(2018)

引用 387|浏览535
暂无评分
摘要
In this paper, we propose perceptual adversarial networks (PANs) for image-to-image transformations. Different from existing application driven algorithms, PAN provides a generic framework of learning to map from input images to desired images (Fig. 1), such as a rainy image to its de-rained counterpart, object edges to photos, and semantic labels to a scenes image. The proposed PAN consists of tw...
更多
查看译文
关键词
Gallium nitride,Task analysis,Training,Loss measurement,Feature extraction,Image resolution,Semantics
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要