{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/perturbative-gan-gan-with-perturbation-layers","title":"Perturbative GAN: GAN with Perturbation Layers","arxiv_id":"1902.01514","date":"2019-02-05","proceeding":null,"authors":["Yuma Kishi","Tsutomu Ikegami","Shin-ichi O'uchi","Ryousei Takano","Wakana Nogami","Tomohiro Kudoh"],"abstract":"Perturbative GAN, which replaces convolution layers of existing convolutional\nGANs (DCGAN, WGAN-GP, BIGGAN, etc.) with perturbation layers that adds a fixed\nnoise mask, is proposed. Compared with the convolu-tional GANs, the number of\nparameters to be trained is smaller, the convergence of training is faster, the\nincep-tion score of generated images is higher, and the overall training cost\nis reduced. Algorithmic generation of the noise masks is also proposed, with\nwhich the training, as well as the generation, can be boosted with hardware\nacceleration. Perturbative GAN is evaluated using con-ventional datasets\n(CIFAR10, LSUN, ImageNet), both in the cases when a perturbation layer is\nadopted only for Generators and when it is introduced to both Generator and\nDiscriminator.","url_abs":"http://arxiv.org/abs/1902.01514v1","url_pdf":"http://arxiv.org/pdf/1902.01514v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"perturbative-gan-gan-with-perturbation-layers","repo_url":"https://github.com/obake2ai/Obake-GAN","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"perturbative-gan-gan-with-perturbation-layers","repo_url":"https://github.com/yumfab-eeis/Obake-GAN","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[],"methods":[{"method_slug":"convolution","method_name":"Convolution"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}