BriefGPT.xyz
Feb, 2017
通过生成对抗网络实现无监督多样化着色
Unsupervised Diverse Colorization via Generative Adversarial Networks
HTML
PDF
Yun Cao, Zhiming Zhou, Weinan Zhang, Yong Yu
TL;DR
本文介绍了一种使用条件生成式对抗网络解决无监督多样化上色问题的方法，并在 LSUN 卧室数据集上表现出高竞争性和高可信度的着色结果。
Abstract
colorization
of grayscale images has been a hot topic in
computer vision
. Previous research mainly focuses on producing a colored image to match the original one. However, since many colors share the same gray va
→