{"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/named-entity-driven-zero-shot-image","title":"Named Entity Driven Zero-Shot Image Manipulation","arxiv_id":null,"date":"2024-01-01","proceeding":"CVPR 2024 1","authors":["Zhida Feng","Li Chen","Jing Tian","Jiaxiang Liu","Shikun Feng"],"abstract":"    We introduced StyleEntity a zero-shot image manipulation model that utilizes named entities as proxies during its training phase. This strategy enables our model to manipulate images using unseen textual descriptions during inference all within a single training phase. Additionally we proposed an inference technique termed Prompt Ensemble Latent Averaging (PELA). PELA averages the manipulation directions derived from various named entities during inference effectively eliminating the noise directions thus achieving stable manipulation. In our experiments StyleEntity exhibited superior performance in a zero-shot setting compared to other methods. The code model weights and datasets is available at https://github.com/feng-zhida/StyleEntity.    ","url_abs":"http://openaccess.thecvf.com//content/CVPR2024/html/Feng_Named_Entity_Driven_Zero-Shot_Image_Manipulation_CVPR_2024_paper.html","url_pdf":"http://openaccess.thecvf.com//content/CVPR2024/papers/Feng_Named_Entity_Driven_Zero-Shot_Image_Manipulation_CVPR_2024_paper.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":"named-entity-driven-zero-shot-image","repo_url":"https://github.com/feng-zhida/styleentity","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"image-manipulation","task_name":"Image Manipulation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}