text: 76,140,1126332235215294464,4475055297,Ming-Yu Liu,"Check out our new #GAN work on translating images to unseen domains in the test time with few example images. Live demo <LINK> Project page <LINK> Paper <LINK> Video <LINK> #NVIDIA <LINK> Brought to you by @xunhuang1995 @arunmallya #TeroKarras, #TimoAila of #StyleGAN, @jaakkolehtinen, and @jankautz @NvidiaAI The web demo might be buggy. I know nothing about Javascript until last week. So please read the instruction carefully for run the demo. It currently works only on Chrome and Firefox and you have to click ""Load unsafe scripts"" or ""Disable protection for now"" buttons. Check out our paper for more results including translating all kinds of foods to Chowmein. <LINK> PetSwap demo video <LINK> live demo available at <LINK> It works for non standard pet too. <LINK> The PetSwap model is trained using carnivorous animals. It might be funny when you input images of other kinds of animals. <LINK> @chris_j_beckham Man. I am just having fun. :)",https://arxiv.org/abs/1905.01723,"Unsupervised image-to-image translation methods learn to map images in a given class to an analogous image in a different class, drawing on unstructured (non-registered) datasets of images. While remarkably successful, current methods require access to many images in both source and destination classes at training time. We argue this greatly limits their use. Drawing inspiration from the human capability of picking up the essence of a novel object from a small number of examples and generalizing from there, we seek a few-shot, unsupervised image-to-image translation algorithm that works on previously unseen target classes that are specified, at test time, only by a few example images. Our model achieves this few-shot generation capability by coupling an adversarial training scheme with a novel network design. Through extensive experimental validation and comparisons to several baseline methods on benchmark datasets, we verify the effectiveness of the proposed framework. Our implementation and datasets are available at this https URL . ",Few-Shot Unsupervised Image-to-Image Translation,8,"['Check out our new #GAN work on translating images to unseen domains in the test time with few example images.\nLive demo <LINK>\nProject page <LINK>\nPaper <LINK>\nVideo <LINK>\n#NVIDIA <LINK>', 'Brought to you by @xunhuang1995  @arunmallya #TeroKarras, #TimoAila of #StyleGAN, @jaakkolehtinen, and @jankautz @NvidiaAI', 'The web demo might be buggy. I know nothing about Javascript until last week. So please read the instruction carefully for run the demo. It currently works only on Chrome and Firefox and you have to click  ""Load unsafe scripts"" or  ""Disable protection for now"" buttons.', 'Check out our paper for more results including translating all kinds of foods to Chowmein. https://t.co/iYwv3wh5Ts', 'PetSwap demo video\nhttps://t.co/CRAoLundVy\n\nlive demo available at https://t.co/KeYHIDpgcx', 'It works for non standard pet too. https://t.co/GcYOPA3Oix', 'The PetSwap model is trained using carnivorous animals. It might be funny when you input images of other kinds of animals. https://t.co/0Lq1BVuJUa', '@chris_j_beckham Man. I am just having fun. :)']",19,05,950