Cross View Image To Image Translation On 2

SSIM

Results

Performance results of various models on this benchmark

		Paper Title
SelectionGAN	0.5938	Multi-Channel Attention Selection GAN with Cascaded Semantic Guidance for Cross-View Image Translation
LGGAN	0.5457	Local Class-Specific and Global Image-Level Generative Adversarial Networks for Semantic-Guided Scene Generation
X-Seq	0.5031	Cross-View Image Synthesis using Conditional GANs
X-Fork	0.4963	Cross-View Image Synthesis using Conditional GANs
Pix2pix	0.418	Image-to-Image Translation with Conditional Adversarial Networks
UniGAN	0.3357	Unified Generative Adversarial Networks for Controllable Image-to-Image Translation

0 of 6 row(s) selected.