{"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-cnn-denoiser-and-multi-layer-neighbor","title":"Deep CNN Denoiser and Multi-layer Neighbor Component Embedding for Face Hallucination","arxiv_id":"1806.10726","date":"2018-06-28","proceeding":null,"authors":["Junjun Jiang","Yi Yu","Jinhui Hu","Suhua Tang","Jiayi Ma"],"abstract":"Most of the current face hallucination methods, whether they are shallow\nlearning-based or deep learning-based, all try to learn a relationship model\nbetween Low-Resolution (LR) and High-Resolution (HR) spaces with the help of a\ntraining set. They mainly focus on modeling image prior through either\nmodel-based optimization or discriminative inference learning. However, when\nthe input LR face is tiny, the learned prior knowledge is no longer effective\nand their performance will drop sharply. To solve this problem, in this paper\nwe propose a general face hallucination method that can integrate model-based\noptimization and discriminative inference. In particular, to exploit the model\nbased prior, the Deep Convolutional Neural Networks (CNN) denoiser prior is\nplugged into the super-resolution optimization model with the aid of\nimage-adaptive Laplacian regularization. Additionally, we further develop a\nhigh-frequency details compensation method by dividing the face image to facial\ncomponents and performing face hallucination in a multi-layer neighbor\nembedding manner. Experiments demonstrate that the proposed method can achieve\npromising super-resolution results for tiny input LR faces.","url_abs":"http://arxiv.org/abs/1806.10726v1","url_pdf":"http://arxiv.org/pdf/1806.10726v1.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":"deep-cnn-denoiser-and-multi-layer-neighbor","repo_url":"https://github.com/ZoieMo/Multi-task","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"unanswered"}}],"tasks":[{"task_slug":"face-hallucination","task_name":"Face Hallucination"},{"task_slug":"hallucination","task_name":"Hallucination"},{"task_slug":"super-resolution","task_name":"Super-Resolution"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}