Deep learning-based face super-resolution: A survey

J Jiang, C Wang, X Liu, J Ma - ACM Computing Surveys (CSUR), 2021 - dl.acm.org
Face super-resolution (FSR), also known as face hallucination, which is aimed at enhancing
the resolution of low-resolution (LR) face images to generate high-resolution face images, is …

Deepfake generation and detection: A benchmark and survey

G Pei, J Zhang, M Hu, Z Zhang, C Wang, Y Wu… - ar** from low-quality images to their high-quality
counterparts. Such optimal map** is usually nonlinear and learnable by machine …

Weighted gate layer autoencoders

H El-Fiqi, M Wang, K Kasmarik… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
A single dataset could hide a significant number of relationships among its feature set.
Learning these relationships simultaneously avoids the time complexity associated with …

Biprediction-based video quality enhancement via learning

D Ding, W Wang, J Tong, X Gao, Z Liu… - IEEE transactions on …, 2020 - ieeexplore.ieee.org
Convolutional neural networks (CNNs)-based video quality enhancement generally
employs optical flow for pixelwise motion estimation and compensation, followed by utilizing …

Face super resolution based on attention upsampling and gradient

A Zheng, X Zeng, P Song, Y Mi, Z He - Multimedia Tools and Applications, 2024 - Springer
Abstract Face Super-Resolution (SR) is a specific domain SR task, which is to reconstruct
low-resolution (LR) face images. Recently, many face super-resolution methods based on …

Nonlinear loose coupled non-negative matrix factorization for low-resolution image recognition

Y Zhao, C Wang, J Pei, X Yang - Neurocomputing, 2021 - Elsevier
In the existing coupled map**-based methods for low-resolution image recognition
(LRIR), the potential relationship between the high-and low-resolution images conforming to …