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Dec 24, 2021 · We propose to leverage the invertible network to enhance low-light image in forward process and degrade the normal-light one inversely with unpaired learning.
Feb 18, 2023 · We propose to leverage the invertible neural network to enhance the low-light images in the forward process and degrade the unpaired normal-light photograph ...
Invertible network for unpaired low-light image enhancement. J Zhang, H Wang, X Wu, W Zuo. The Visual Computer 40 (1), 109-120, 2024. 5, 2024. Learning diverse ...
In this study, we propose a Multi-Technology Fusion of Low-light Image Enhancement Network (MTIE-Net) that modularizes the enhancement task.
An invertible network that takes the low-light images/features as the condition and learns to map the distribution of normally exposed images into a Gaussian ...
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Adaptive Single Low-Light Image Enhancement by Fractional Stretching in Logarithmic Domain · Invertible network for unpaired low-light image enhancement · DBCGN: ...
Finally, an invertible normalizing flow decoder is used to recover the normally exposed image from the illumination-robust features. 3.1. Adaptive Dual ...
This paper proposes a novel low-light images Enhancement and Denoising model based on unsupervised learning Multi-Stream feature modeling (MSED).
An invertible network that takes the low-light images/features as the condition and learns to map the distribu- tion of normally exposed images into a ...
This article proposes an unsupervised model with a unique data augmentation technique that transforms a regular image database into a paired image database.