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20182022
most citedBlind Face Restoration via Deep Multi-scale Component Dictionaries

14 citations · 20 across the 5 of their papers we have counts for

collaborators

8 papers

cs.CV2022

Semantic-shape Adaptive Feature Modulation for Semantic Image Synthesis

Zhengyao Lv, Xiaoming Li, Zhenxing Niu +2

Recent years have witnessed substantial progress in semantic image synthesis, it is still challenging in synthesizing photo-realistic images with rich details. Most previous method…

cs.CV20214 cited

Learning Semantic Person Image Generation by Region-Adaptive Normalization

Zhengyao Lv, Xiaoming Li, Xin Li +4

Human pose transfer has received great attention due to its wide applications, yet is still a challenging task that is not well solved. Recent works have achieved great success to…

cs.CV2020

Progressive Semantic-Aware Style Transformation for Blind Face Restoration

Chaofeng Chen, Xiaoming Li, Lingbo Yang +3

Face restoration is important in face image processing, and has been widely studied in recent years. However, previous works often fail to generate plausible high quality (HQ) resu…

cs.CV202014 cited

Blind Face Restoration via Deep Multi-scale Component Dictionaries

Xiaoming Li, Chaofeng Chen, Shangchen Zhou +3

Recent reference-based face restoration methods have received considerable attention due to their great capability in recovering high-frequency details on real low-quality images.…

cs.CV2020

Face Super-Resolution Guided by 3D Facial Priors

Xiaobin Hu, Wenqi Ren, John LaMaster +5

State-of-the-art face super-resolution methods employ deep convolutional neural networks to learn a mapping between low- and high- resolution facial patterns by exploring local app…

cs.CV20182 cited

Learning Symmetry Consistent Deep CNNs for Face Completion

Xiaoming Li, Ming Liu, Jieru Zhu +4

Deep convolutional networks (CNNs) have achieved great success in face completion to generate plausible facial structures. These methods, however, are limited in maintaining global…