{"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/fer2013-recognition-resnet18-with-tricks","title":"Fer2013 Recognition - ResNet18 With Tricks","arxiv_id":null,"date":"2021-12-29","proceeding":"None 2021 12","authors":["Xiaojian Yuan"],"abstract":"This work is the final project of the Computer Vision Course of USTC. However, I achieve the highest single-network classification accuracy on FER2013 based on ResNet18. To my best knowledge, this work achieves state-of-the-art single-network accuracy of 73.70 % on FER2013 without using extra training data, which exceeds the previous work [1] of 73.28%.","url_abs":"https://github.com/LetheSec/Fer2013-Recognition-Pytorch/blob/main/README.md","url_pdf":"https://github.com/LetheSec/Fer2013-Recognition-Pytorch/blob/main/README.md","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":"fer2013-recognition-resnet18-with-tricks","repo_url":"https://github.com/LetheSec/Fer2013-Facial-Emotion-Recognition-Pytorch","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"facial-expression-recognition","task_name":"Facial Expression Recognition (FER)"}],"methods":[{"method_slug":"1-bit-adam","method_name":"1-bit Adam"},{"method_slug":"adam","method_name":"Adam"}],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/facial-expression-recognition-on-fer2013","task":"Facial Expression Recognition (FER)","dataset":"FER2013","model":"ResNet18 With Tricks","rank_in_archive_order":11,"of":17,"metrics":{"Accuracy":"73.70"},"uses_additional_data":false}],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}