Face Hallucination
12 papers with code • 1 benchmarks • 3 datasets
Face hallucination is the task of generating high-resolution (HR) facial images from low-resolution (LR) inputs.
( Image credit: Deep CNN Denoiser and Multi-layer Neighbor Component Embedding for Face Hallucination )
Benchmarks
These leaderboards are used to track progress in Face Hallucination
| Trend | Dataset | Best Model | Paper | Code | Compare |
|---|---|---|---|---|---|
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FFHQ
EDFace-Celeb-1M
KID-F
Latest papers
SiGAN: Siamese Generative Adversarial Network for Identity-Preserving Face Hallucination
jesse1029/SiGAN
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Despite generative adversarial networks (GANs) can hallucinate photo-realistic high-resolution (HR) faces from low-resolution (LR) faces, they cannot guarantee preserving the identities of hallucinated HR faces, making the HR faces poorly recognizable.
Deep CNN Denoiser and Multi-layer Neighbor Component Embedding for Face Hallucination
Most of the current face hallucination methods, whether they are shallow learning-based or deep learning-based, all try to learn a relationship model between Low-Resolution (LR) and High-Resolution (HR) spaces with the help of a training set.
