labmlai--annotated_deep_learning_paper_implementations

{
 "<h1><a href=\"https://nn.labml.ai/gan/cycle_gan/index.html\">Cycle GAN</a></h1>\n<p>This is a <a href=\"https://pytorch.org\">PyTorch</a> implementation/tutorial of the paper <a href=\"https://arxiv.org/abs/1703.10593\">Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks</a>. </p>\n": "<h1><a href=\"https://nn.labml.ai/gan/cycle_gan/index.html\">\u5faa\u73af\u589e\u76ca</a></h1>\n<p>\u8fd9\u662f\u8bba\u6587\u300a<a href=\"https://arxiv.org/abs/1703.10593\">\u4f7f\u7528\u5468\u671f\u4e00\u81f4\u7684\u5bf9\u6297\u7f51\u7edc\u8fdb\u884c\u672a\u914d\u5bf9\u7684\u56fe\u50cf\u5230\u56fe\u50cf\u8f6c\u6362\u300b\u7684 Py</a> <a href=\"https://pytorch.org\">Torch</a> \u5b9e\u73b0/\u6559\u7a0b\u3002</p>\n",
 "Cycle GAN": "\u5faa\u73af\u589e\u76ca"
}