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 with no code
Audio-visual video face hallucination with frequency supervision and cross modality support by speech based lip reading loss
In order to learn these fine spatio-temporal motion details, we propose a novel cross-modal audio-visual Video Face Hallucination Generative Adversarial Network (VFH-GAN).
Escaping Data Scarcity for High-Resolution Heterogeneous Face Hallucination
In Heterogeneous Face Recognition (HFR), the objective is to match faces across two different domains such as visible and thermal.
GCFSR: a Generative and Controllable Face Super Resolution Method Without Facial and GAN Priors
The style modulation aims to generate realistic face details and the feature modulation dynamically fuses the multi-level encoded features and the generated ones conditioned on the upscaling factor.
Identity-Preserving Pose-Robust Face Hallucination Through Face Subspace Prior
Over the past few decades, numerous attempts have been made to address the problem of recovering a high-resolution (HR) facial image from its corresponding low-resolution (LR) counterpart, a task commonly referred to as face hallucination.
AGA-GAN: Attribute Guided Attention Generative Adversarial Network with U-Net for Face Hallucination
The performance of facial super-resolution methods relies on their ability to recover facial structures and salient features effectively.
Frequency Aware Face Hallucination Generative Adversarial Network with Semantic Structural Constraint
To explicitly encode the high frequency components, an auto encoder is proposed to generate high resolution coefficients of Discrete Cosine Transform (DCT).
LR-to-HR Face Hallucination with an Adversarial Progressive Attribute-Induced Network
Face super-resolution is a challenging and highly ill-posed problem since a low-resolution (LR) face image may correspond to multiple high-resolution (HR) ones during the hallucination process and cause a dramatic identity change for the final super-resolved results.
Pro-UIGAN: Progressive Face Hallucination from Occluded Thumbnails
Specifically, we design a novel cross-modal transformer module for facial priors estimation, in which an input face and its landmark features are formulated as queries and keys, respectively.
3D human tongue reconstruction from single "in-the-wild" images
3D face reconstruction from a single image is a task that has garnered increased interest in the Computer Vision community, especially due to its broad use in a number of applications such as realistic 3D avatar creation, pose invariant face recognition and face hallucination.
Copy and Paste GAN: Face Hallucination from Shaded Thumbnails
This paper proposes a Copy and Paste Generative Adversarial Network (CPGAN) to recover authentic high-resolution (HR) face images while compensating for low and non-uniform illumination.
