{"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/convolutional-experts-constrained-local-model","title":"Convolutional Experts Constrained Local Model for Facial Landmark Detection","arxiv_id":"1611.08657","date":"2016-11-26","proceeding":null,"authors":["Amir Zadeh","Tadas Baltrušaitis","Louis-Philippe Morency"],"abstract":"Constrained Local Models (CLMs) are a well-established family of methods for\nfacial landmark detection. However, they have recently fallen out of favor to\ncascaded regression-based approaches. This is in part due to the inability of\nexisting CLM local detectors to model the very complex individual landmark\nappearance that is affected by expression, illumination, facial hair, makeup,\nand accessories. In our work, we present a novel local detector --\nConvolutional Experts Network (CEN) -- that brings together the advantages of\nneural architectures and mixtures of experts in an end-to-end framework. We\nfurther propose a Convolutional Experts Constrained Local Model (CE-CLM)\nalgorithm that uses CEN as local detectors. We demonstrate that our proposed\nCE-CLM algorithm outperforms competitive state-of-the-art baselines for facial\nlandmark detection by a large margin on four publicly-available datasets. Our\napproach is especially accurate and robust on challenging profile images.","url_abs":"http://arxiv.org/abs/1611.08657v5","url_pdf":"http://arxiv.org/pdf/1611.08657v5.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":"convolutional-experts-constrained-local-model","repo_url":"https://github.com/TadasBaltrusaitis/OpenFace","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"facial-landmark-detection","task_name":"Facial Landmark Detection"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}