{"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/smell-and-emotion-recognising-emotions-in","title":"Smell and Emotion: Recognising emotions in smell-related artworks","arxiv_id":"2407.04592","date":"2024-07-05","proceeding":null,"authors":["Vishal Patoliya","Mathias Zinnen","Andreas Maier","Vincent Christlein"],"abstract":"Emotions and smell are underrepresented in digital art history. In this exploratory work, we show that recognising emotions from smell-related artworks is technically feasible but has room for improvement. Using style transfer and hyperparameter optimization we achieve a minor performance boost and open up the field for future extensions.","url_abs":"https://arxiv.org/abs/2407.04592v1","url_pdf":"https://arxiv.org/pdf/2407.04592v1.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":"smell-and-emotion-recognising-emotions-in","repo_url":"https://github.com/MindSpore-scientific/code-10/tree/main/SmeLU-master","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"mindspore","reach":null}],"tasks":[{"task_slug":"hyperparameter-optimization","task_name":"Hyperparameter Optimization"},{"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}