{"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/boundary-aware-network-for-fast-and-high","title":"Boundary-Aware Network for Fast and High-Accuracy Portrait Segmentation","arxiv_id":"1901.03814","date":"2019-01-12","proceeding":null,"authors":["Xi Chen","Donglian Qi","Jianxin Shen"],"abstract":"Compared with other semantic segmentation tasks, portrait segmentation\nrequires both higher precision and faster inference speed. However, this\nproblem has not been well studied in previous works. In this paper, we propose\na lightweight network architecture, called Boundary-Aware Network (BANet) which\nselectively extracts detail information in boundary area to make high-quality\nsegmentation output with real-time( >25FPS) speed. In addition, we design a new\nloss function called refine loss which supervises the network with image level\ngradient information. Our model is able to produce finer segmentation results\nwhich has richer details than annotations.","url_abs":"http://arxiv.org/abs/1901.03814v1","url_pdf":"http://arxiv.org/pdf/1901.03814v1.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":"boundary-aware-network-for-fast-and-high","repo_url":"https://github.com/lewisluk/BoundaryAwareNetwork","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null},{"paper_slug":"boundary-aware-network-for-fast-and-high","repo_url":"https://github.com/minus31/Portrait-segmentation","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"portrait-segmentation","task_name":"Portrait Segmentation"},{"task_slug":"segmentation","task_name":"Segmentation"},{"task_slug":"semantic-segmentation","task_name":"Semantic Segmentation"},{"task_slug":"high","task_name":"Vocal Bursts Intensity Prediction"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1901.03814","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}