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Face Hallucination

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 )

Papers

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Showing 26–50 of 51 papers

TitleStatusHype
Joint Face Hallucination and Deblurring via Structure Generation and Detail Enhancement—0
Hallucinating very low-resolution and obscured face images—0
Super-Identity Convolutional Neural Network for Face Hallucination—0
3D Face Hallucination from a Single Depth Frame—0
Context-Patch Face Hallucination Based on Thresholding Locality-constrained Representation and Reproducing LearningCode1
Face Super-resolution Guided by Facial Component Heatmaps—0
ESRGAN: Enhanced Super-Resolution Generative Adversarial NetworksCode3
SiGAN: Siamese Generative Adversarial Network for Identity-Preserving Face HallucinationCode0
Deep CNN Denoiser and Multi-layer Neighbor Component Embedding for Face HallucinationCode0
Super-Resolving Very Low-Resolution Face Images With Supplementary Attributes—0
CerfGAN: A Compact, Effective, Robust, and Fast Model for Unsupervised Multi-Domain Image-to-Image Translation—0
Face hallucination using cascaded super-resolution and identity priors—0
Super-FAN: Integrated facial landmark localization and super-resolution of real-world low resolution faces in arbitrary poses with GANs—0
Wavelet-SRNet: A Wavelet-Based CNN for Multi-Scale Face Super Resolution—0
Adversarial Discriminative Heterogeneous Face Recognition—0
Attention-Aware Face Hallucination via Deep Reinforcement Learning—0
Learning to Hallucinate Face Images via Component Generation and Enhancement—0
Hallucinating Very Low-Resolution Unaligned and Noisy Face Images by Transformative Discriminative Autoencoders—0
Random Sampling for Fast Face Sketch Synthesis—0
Deep Joint Face Hallucination and Recognition—0
Deep Identity-aware Transfer of Facial Attributes—0
Deep Cascaded Bi-Network for Face Hallucination—0
Global-Local Face Upsampling Network—0
Face Hallucination using Linear Models of Coupled Sparse Support—0
Robust Multi-Image Based Blind Face Hallucination—0
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