Transformation GAN for Unsupervised Image Synthesis and Representation Learning

CVPR 2020 Jiayu Wang Wengang Zhou Guo-Jun Qi Zhongqian Fu Qi Tian Houqiang Li

Generative Adversarial Networks (GAN) have shown promising performance in image synthesis and unsupervised learning (USL). In most cases, however, the representations extracted from unsupervised GAN are usually unsatisfactory in other computer vision tasks... (read more)

PDF Abstract

Results from the Paper

  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods used in the Paper

🤖 No Methods Found Help the community by adding them if they're not listed; e.g. Deep Residual Learning for Image Recognition uses ResNet