{"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/hierarchical-attention-based-age-estimation","title":"Hierarchical Attention-based Age Estimation and Bias Estimation","arxiv_id":"2103.09882","date":"2021-03-17","proceeding":null,"authors":["Shakediel Hiba","Yosi Keller"],"abstract":"In this work we propose a novel deep-learning approach for age estimation based on face images. We first introduce a dual image augmentation-aggregation approach based on attention. This allows the network to jointly utilize multiple face image augmentations whose embeddings are aggregated by a Transformer-Encoder. The resulting aggregated embedding is shown to better encode the face image attributes. We then propose a probabilistic hierarchical regression framework that combines a discrete probabilistic estimate of age labels, with a corresponding ensemble of regressors. Each regressor is particularly adapted and trained to refine the probabilistic estimate over a range of ages. Our scheme is shown to outperform contemporary schemes and provide a new state-of-the-art age estimation accuracy, when applied to the MORPH II dataset for age estimation. Last, we introduce a bias analysis of state-of-the-art age estimation results.","url_abs":"https://arxiv.org/abs/2103.09882v2","url_pdf":"https://arxiv.org/pdf/2103.09882v2.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":[],"tasks":[{"task_slug":"age-estimation","task_name":"Age Estimation"},{"task_slug":"image-augmentation","task_name":"Image Augmentation"},{"task_slug":"morph","task_name":"MORPH"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/age-estimation-on-morph-album2","task":"Age Estimation","dataset":"MORPH Album2","model":"Hierarchical Attention-based Age Estimation (RS)","rank_in_archive_order":1,"of":9,"metrics":{"MAE":"1.13"},"uses_additional_data":false},{"leaderboard":"/sota/age-estimation-on-morph-album2","task":"Age Estimation","dataset":"MORPH Album2","model":"Hierarchical Attention-based Age Estimation (SE)","rank_in_archive_order":8,"of":9,"metrics":{"MAE":"2.53"},"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}