{"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/age-and-gender-classification-using","title":"Age and Gender Classification using Convolutional Neural Networks","arxiv_id":null,"date":"2015-10-26","proceeding":"2015 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) 2015 10","authors":["Gil Levi","Tal Hassner"],"abstract":"Automatic age and gender classification has become relevant to an increasing amount of applications, particularly since the rise of social platforms and social media. Nevertheless, performance of existing methods on real-world images is still significantly lacking, especially when compared to the tremendous leaps in performance recently reported for the related task of face recognition. In this paper we show that by learning representations through the use of deep-convolutional neural networks (CNN), a significant increase in performance can be obtained on these tasks. To this end, we propose a simple convolutional net architecture that can be used even when the amount of learning data is limited. We evaluate our method on the recent Adience benchmark for age and gender estimation and show it to dramatically outperform current state-of-the-art methods.","url_abs":"https://talhassner.github.io/home/publication/2015_CVPR","url_pdf":"https://talhassner.github.io/home/projects/cnn_agegender/CVPR2015_CNN_AgeGenderEstimation.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":"age-and-gender-classification-using","repo_url":"https://github.com/GilLevi/AgeGenderDeepLearning","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"age-and-gender-classification-using","repo_url":"https://github.com/dpressel/rude-carnie","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"tf","reach":null}],"tasks":[{"task_slug":"age-and-gender-classification","task_name":"Age And Gender Classification"},{"task_slug":"age-and-gender-estimation","task_name":"Age and Gender Estimation"},{"task_slug":"classification-1","task_name":"Classification"},{"task_slug":"face-recognition","task_name":"Face Recognition"},{"task_slug":"gender-classification","task_name":"Gender Classification"},{"task_slug":"classification","task_name":"General Classification"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/age-and-gender-classification-on-adience-age","task":"Age And Gender Classification","dataset":"Adience Age","model":"Levi_Hassner CNN (over-sample, caffe)","rank_in_archive_order":13,"of":16,"metrics":{"Accuracy (5-fold)":"50.7"},"uses_additional_data":false},{"leaderboard":"/sota/age-and-gender-classification-on-adience-age","task":"Age And Gender Classification","dataset":"Adience Age","model":"Levi_Hassner CNN (single crop, caffe)","rank_in_archive_order":14,"of":16,"metrics":{"Accuracy (5-fold)":"49.5"},"uses_additional_data":false},{"leaderboard":"/sota/age-and-gender-classification-on-adience-age","task":"Age And Gender Classification","dataset":"Adience Age","model":"Levi_Hassner CNN (single crop, tensorflow)","rank_in_archive_order":16,"of":16,"metrics":{"Accuracy (5-fold)":"44.14"},"uses_additional_data":false},{"leaderboard":"/sota/age-and-gender-classification-on-adience","task":"Age And Gender Classification","dataset":"Adience Gender","model":"Levi_Hassner CNN ( over-sample, caffe)","rank_in_archive_order":7,"of":10,"metrics":{"Accuracy (5-fold)":"86.8"},"uses_additional_data":false},{"leaderboard":"/sota/age-and-gender-classification-on-adience","task":"Age And Gender Classification","dataset":"Adience Gender","model":"Levi_Hassner CNN (single crop, caffe)","rank_in_archive_order":8,"of":10,"metrics":{"Accuracy (5-fold)":"85.9"},"uses_additional_data":false},{"leaderboard":"/sota/age-and-gender-classification-on-adience","task":"Age And Gender Classification","dataset":"Adience Gender","model":"Levi_Hassner CNN (single crop, tensorflow)","rank_in_archive_order":10,"of":10,"metrics":{"Accuracy (5-fold)":"82.52"},"uses_additional_data":false}],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}