Training Generative Image Super-Resolution Models by Wavelet-Domain Losses Enables Better Control of Artifacts

29 February 2024

Papers citing "Training Generative Image Super-Resolution Models by Wavelet-Domain Losses Enables Better Control of Artifacts"

8 / 8 papers shown

Title
Exploring Semantic Feature Discrimination for Perceptual Image Super-Resolution and Opinion-Unaware No-Reference Image Quality Assessment Guanglu Dong Xiangyu Liao Mingyang Li Guihuan Guo Chao Ren 39 0 0 25 Mar 2025
Implicit Neural Representation for Video and Image Super-Resolution M. Aiyetigbo Wanqi Yuan Feng Luo Nianyi Li SupR 51 0 0 06 Mar 2025
Aquatic-GS: A Hybrid 3D Representation for Underwater Scenes Shaohua Liu Junzhe Lu Zuoya Gu Jiajun Li Yue Deng 3DGS 41 0 0 31 Oct 2024
FIPER: Generalizable Factorized Features for Robust Low-Level Vision Models Yang-Che Sun Cheng Yu Yeo Ernie Chu Jun-Cheng Chen Yu-Lun Liu SupR 30 0 0 23 Oct 2024
Training Transformer Models by Wavelet Losses Improves Quantitative and Visual Performance in Single Image Super-Resolution Cansu Korkmaz A. Murat Tekalp ViT 36 6 0 17 Apr 2024
Perception-Distortion Balanced Super-Resolution: A Multi-Objective Optimization Perspective Lingchen Sun Jiejing Liang Shuai Liu Hongwei Yong Lei Zhang 15 6 0 24 Dec 2023
ESRGAN+ : Further Improving Enhanced Super-Resolution Generative Adversarial Network Nathanaël Carraz Rakotonirina Andry Rasoanaivo GAN SupR 22 142 0 21 Jan 2020
Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network Wenzhe Shi Jose Caballero Ferenc Huszár J. Totz Andrew P. Aitken Rob Bishop Daniel Rueckert Zehan Wang SupR 190 5,138 0 16 Sep 2016