{"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/deep-cascaded-bi-network-for-face","title":"Deep Cascaded Bi-Network for Face Hallucination","arxiv_id":"1607.05046","date":"2016-07-18","proceeding":null,"authors":["Shizhan Zhu","Sifei Liu","Chen Change Loy","Xiaoou Tang"],"abstract":"We present a novel framework for hallucinating faces of unconstrained poses\nand with very low resolution (face size as small as 5pxIOD). In contrast to\nexisting studies that mostly ignore or assume pre-aligned face spatial\nconfiguration (e.g. facial landmarks localization or dense correspondence\nfield), we alternatingly optimize two complementary tasks, namely face\nhallucination and dense correspondence field estimation, in a unified\nframework. In addition, we propose a new gated deep bi-network that contains\ntwo functionality-specialized branches to recover different levels of texture\ndetails. Extensive experiments demonstrate that such formulation allows\nexceptional hallucination quality on in-the-wild low-res faces with significant\npose and illumination variations.","url_abs":"http://arxiv.org/abs/1607.05046v1","url_pdf":"http://arxiv.org/pdf/1607.05046v1.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":"face-hallucination","task_name":"Face Hallucination"},{"task_slug":"hallucination","task_name":"Hallucination"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/image-super-resolution-on-vggface2-8x","task":"Image Super-Resolution","dataset":"VggFace2 - 8x upscaling","model":"CBN","rank_in_archive_order":5,"of":7,"metrics":{"PSNR":"21.84"},"uses_additional_data":false},{"leaderboard":"/sota/image-super-resolution-on-webface-8x","task":"Image Super-Resolution","dataset":"WebFace - 8x upscaling","model":"CBN","rank_in_archive_order":5,"of":7,"metrics":{"PSNR":"23.10"},"uses_additional_data":false}],"syntology":{"syntology_url":"https://syntology.ai/paper/1607.05046","atlas_url":"https://app.syntology.ai/?focus=1607.05046","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}