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Cited by 361

The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.

A two-step approach to hallucinating faces: global parametric model and local nonparametric model

Ce Liu, Heung-Yeung Shum, Chang-Shui Zhang·2005·Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001

Abstract

In this paper, we study face hallucination, or synthesizing a high-resolution face image from low-resolution input, with the help of a large collection of high-resolution face images. We develop a two-step statistical modeling approach that integrates both a global parametric model and a local nonparametric model. First, we derive a global linear model to learn the relationship between the high-resolution face images and their smoothed and down-sampled lower resolution ones. Second, the residual between an original high-resolution image and the reconstructed high-resolution image by a learned linear model is modeled by a patch-based nonparametric Markov network, to capture the high-frequency content of faces. By integrating both global and local models, we can generate photorealistic face images. Our approach is demonstrated by extensive experiments with high-quality hallucinated faces.

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Crossref · 10.1109/cvpr.2001.990475

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Metadata

Authors
Liu, C., Shum, H.-Y., & Zhang, C.-S.
Venue
Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001
Published
2005-08-24
Volume
1
Pages
I-192-I-198
ISSN
1063-6919 (ISSN-L)
OpenAlex
W2164307510
Cited by
361
References
15
FWCI
21.62
Type
conference paper
Language
en
Open access
closed

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