{"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/subjective-face-transform-using-human-first","title":"Subjective Face Transform using Human First Impressions","arxiv_id":"2309.15381","date":"2023-09-27","proceeding":null,"authors":["Chaitanya Roygaga","Joshua Krinsky","Kai Zhang","Kenny Kwok","Aparna Bharati"],"abstract":"Humans tend to form quick subjective first impressions of non-physical attributes when seeing someone's face, such as perceived trustworthiness or attractiveness. To understand what variations in a face lead to different subjective impressions, this work uses generative models to find semantically meaningful edits to a face image that change perceived attributes. Unlike prior work that relied on statistical manipulation in feature space, our end-to-end framework considers trade-offs between preserving identity and changing perceptual attributes. It maps identity-preserving latent space directions to changes in attribute scores, enabling transformation of any input face along an attribute axis according to a target change. We train on real and synthetic faces, evaluate for in-domain and out-of-domain images using predictive models and human ratings, demonstrating the generalizability of our approach. Ultimately, such a framework can be used to understand and explain biases in subjective interpretation of faces that are not dependent on the identity.","url_abs":"https://arxiv.org/abs/2309.15381v1","url_pdf":"https://arxiv.org/pdf/2309.15381v1.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":"subjective-face-transform-using-human-first","repo_url":"https://github.com/CV-Lehigh/subjective_face_transform","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"attribute","task_name":"Attribute"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}