Single face hallucination via local neighbor patches |
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| Affiliation: | 1. College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing, China;2. School of Information and Communication Engineering, Dalian University of Technology, Dalian, China;1. Institute of Space Electronics and Information Technology, School of Electronic Science and Engineering, National University of Defense Technology, China;2. Department of Signal Processing and Acoustics, Aalto University, Finland;3. China Academy of Electronics and Information Technology, China Electronics Technology Group Corporation, China;1. National Research Center of Railway Safety Assessment, Beijing Jiaotong University, Beijing 100044, China;2. State Key Lab of Rail Traffic Control & Safety, Beijing Jiaotong University, Beijing 100044, China |
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| Abstract: | Based on learning neighborhood patches a new single face hallucination method is proposed in this paper. In the proposed method, each input low-resolution (LR) position-patch and all patches in a local window centered at the same position of training images are used to hallucinate a high-resolution (HR) face patch, meanwhile two local similarity measurements between each input LR patch and all local LR and HR neighborhood patches of training images are computed to constrain the hallucination. Additionally, a residue image is estimated for the further improvement of the reconstructed result. Experimental results show that the proposed method can obtain superior or competitive results. |
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| Keywords: | Face hallucination Local window Neighbor patch Similarity measurement |
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