Face Hallucination

10 papers with code • 1 benchmarks • 1 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 )

Datasets


Greatest papers with code

ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

eriklindernoren/PyTorch-GAN 1 Sep 2018

To further enhance the visual quality, we thoroughly study three key components of SRGAN - network architecture, adversarial loss and perceptual loss, and improve each of them to derive an Enhanced SRGAN (ESRGAN).

Face Hallucination Image Super-Resolution

PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models

adamian98/pulse CVPR 2020

We present an algorithm addressing this problem, PULSE (Photo Upsampling via Latent Space Exploration), which generates high-resolution, realistic images at resolutions previously unseen in the literature.

Face Hallucination Image Super-Resolution

Cross-Resolution Face Recognition via Prior-Aided Face Hallucination and Residual Knowledge Distillation

ZhaoJ9014/face.evoLVe.PyTorch 26 May 2019

Recent deep learning based face recognition methods have achieved great performance, but it still remains challenging to recognize very low-resolution query face like 28x28 pixels when CCTV camera is far from the captured subject.

Face Hallucination Face Recognition +2

HiFaceGAN: Face Renovation via Collaborative Suppression and Replenishment

Lotayou/Face-Renovation 11 May 2020

Existing face restoration researches typically relies on either the degradation prior or explicit guidance labels for training, which often results in limited generalization ability over real-world images with heterogeneous degradations and rich background contents.

Face Hallucination Image Denoising +2

DeepSEE: Deep Disentangled Semantic Explorative Extreme Super-Resolution

andreas128/NTIRE21_Learning_SR_Space 9 Apr 2020

To the best of our knowledge, DeepSEE is the first method to leverage semantic maps for explorative super-resolution.

Face Hallucination Super-Resolution

Context-Patch Face Hallucination Based on Thresholding Locality-constrained Representation and Reproducing Learning

junjun-jiang/Face-Hallucination-Benchmark 3 Sep 2018

To this end, this study incorporates the contextual information of image patch and proposes a powerful and efficient context-patch based face hallucination approach, namely Thresholding Locality-constrained Representation and Reproducing learning (TLcR-RL).

Face Hallucination

SiGAN: Siamese Generative Adversarial Network for Identity-Preserving Face Hallucination

jesse1029/SiGAN 22 Jul 2018

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.

Face Hallucination Face Reconstruction +1

Face Hallucination Using Split-Attention in Split-Attention Network

mdswyz/SISN-Face-Hallucination 22 Oct 2020

Recently, attention mechanism has been applied into convolutional neural networks(CNNs) based super-resolution (SR) tasks for exploring internal feature map correlation.

Face Hallucination Image Reconstruction +1

Simultaneous Face Hallucination and Translation for Thermal to Visible Face Verification using Axial-GAN

sam575/axial-gan 13 Apr 2021

Existing thermal-to-visible face verification approaches expect the thermal and visible face images to be of similar resolution.

Face Hallucination Face Verification

Deep CNN Denoiser and Multi-layer Neighbor Component Embedding for Face Hallucination

ZoieMo/Multi-task 28 Jun 2018

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.

Face Hallucination Super-Resolution