{"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/learning-face-age-progression-a-pyramid","title":"Learning Face Age Progression: A Pyramid Architecture of GANs","arxiv_id":"1711.10352","date":"2017-11-28","proceeding":"CVPR 2018 6","authors":["Hongyu Yang","Di Huang","Yunhong Wang","Anil K. Jain"],"abstract":"The two underlying requirements of face age progression, i.e. aging accuracy\nand identity permanence, are not well studied in the literature. In this paper,\nwe present a novel generative adversarial network based approach. It separately\nmodels the constraints for the intrinsic subject-specific characteristics and\nthe age-specific facial changes with respect to the elapsed time, ensuring that\nthe generated faces present desired aging effects while simultaneously keeping\npersonalized properties stable. Further, to generate more lifelike facial\ndetails, high-level age-specific features conveyed by the synthesized face are\nestimated by a pyramidal adversarial discriminator at multiple scales, which\nsimulates the aging effects in a finer manner. The proposed method is\napplicable to diverse face samples in the presence of variations in pose,\nexpression, makeup, etc., and remarkably vivid aging effects are achieved. Both\nvisual fidelity and quantitative evaluations show that the approach advances\nthe state-of-the-art.","url_abs":"http://arxiv.org/abs/1711.10352v4","url_pdf":"http://arxiv.org/pdf/1711.10352v4.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":"learning-face-age-progression-a-pyramid","repo_url":"https://github.com/lumosity4tpj/Pytorch-Implementation-of-A-Pyramid-Architecture-of-GANs","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"unanswered"}}],"tasks":[{"task_slug":null,"task_name":"Generative Adversarial Network"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1711.10352","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}