{"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/enhancing-perceptual-attributes-with-bayesian","title":"Enhancing Perceptual Attributes with Bayesian Style Generation","arxiv_id":"1812.00717","date":"2018-12-03","proceeding":null,"authors":["Aliaksandr Siarohin","Gloria Zen","Nicu Sebe","Elisa Ricci"],"abstract":"Deep learning has brought an unprecedented progress in computer vision and\nsignificant advances have been made in predicting subjective properties\ninherent to visual data (e.g., memorability, aesthetic quality, evoked\nemotions, etc.). Recently, some research works have even proposed deep learning\napproaches to modify images such as to appropriately alter these properties.\nFollowing this research line, this paper introduces a novel deep learning\nframework for synthesizing images in order to enhance a predefined perceptual\nattribute. Our approach takes as input a natural image and exploits recent\nmodels for deep style transfer and generative adversarial networks to change\nits style in order to modify a specific high-level attribute. Differently from\nprevious works focusing on enhancing a specific property of a visual content,\nwe propose a general framework and demonstrate its effectiveness in two use\ncases, i.e. increasing image memorability and generating scary pictures. We\nevaluate the proposed approach on publicly available benchmarks, demonstrating\nits advantages over state of the art methods.","url_abs":"http://arxiv.org/abs/1812.00717v1","url_pdf":"http://arxiv.org/pdf/1812.00717v1.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":"enhancing-perceptual-attributes-with-bayesian","repo_url":"https://github.com/aliaksandrsiarohin/bae","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"tf","reach":null}],"tasks":[{"task_slug":"attribute","task_name":"Attribute"},{"task_slug":"deep-learning","task_name":"Deep Learning"},{"task_slug":"style-transfer","task_name":"Style Transfer"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}