{"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/o-gan-extremely-concise-approach-for-auto","title":"O-GAN: Extremely Concise Approach for Auto-Encoding Generative Adversarial Networks","arxiv_id":"1903.01931","date":"2019-03-05","proceeding":null,"authors":["Jianlin Su"],"abstract":"In this paper, we propose Orthogonal Generative Adversarial Networks\n(O-GANs). We decompose the network of discriminator orthogonally and add an\nextra loss into the objective of common GANs, which can enforce discriminator\nbecome an effective encoder. The same extra loss can be embedded into any kind\nof GANs and there is almost no increase in computation. Furthermore, we discuss\nthe principle of our method, which is relative to the fully-exploiting of the\nremaining degrees of freedom of discriminator. As we know, our solution is the\nsimplest approach to train a generative adversarial network with auto-encoding\nability.","url_abs":"http://arxiv.org/abs/1903.01931v1","url_pdf":"http://arxiv.org/pdf/1903.01931v1.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":"o-gan-extremely-concise-approach-for-auto","repo_url":"https://github.com/bojone/o-gan","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"tf","reach":null}],"tasks":[{"task_slug":null,"task_name":"Generative Adversarial Network"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=1903.01931","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}