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Face Inpainting with Local Linear Representations

Authors: Zhenyao Mo; John P. Lewis; Ulrich Neumann;

Face Inpainting with Local Linear Representations

Abstract

A numberof investigatorshave had success usingdomainspecific priorknowledgeto produce improved superresolution images of faces (“hallucinating faces”). These efforts address the scenario where a face image is obtained from a low-resolutioncamera. A related but less studied problem occurs when the missing information is the result of occlusion rather than low camera resolution, as in the case when a person is wearing sunglasses. Recently Hwang and Lee [14] introduced the first algorithm for solving this reconstruction “inpainting” problem. In the current work we report results of a psychological study that provides independent evidence regarding the validity of the face reconstruction task, and we demonstrate an improved reconstruction approach using a positive, local linear representation. The positive, local mixture operates on real-world images without manual intervention in many cases, and provides demonstrably lower reconstruction error than is obtainable with a global representation.

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    Average
    influence
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
27
Average
Top 10%
Top 10%
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