SeNM-VAE: Semi-Supervised Noise Modeling with Hierarchical Variational Autoencoder

The data bottleneck has emerged as a fundamental challenge in learning based image restoration methods. Researchers have attempted to generate synthesized training data using paired or unpaired samples to address this challenge. This study proposes SeNM-VAE, a semi-supervised noise modeling method t...

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Bibliographic Details

Published in:	Proceedings (IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Online) pp. 25889 - 25899
Main Authors:	Zheng, Dihan, Zou, Yihang, Zhang, Xiaowen, Bao, Chenglong
Format:	Conference Proceeding
Language:	English
Published:	IEEE 16.06.2024
Subjects:	Computational modeling Linear programming Noise Noise reduction Superresolution Training Training data
ISSN:	1063-6919
Online Access:	Get full text
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