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Found 11 papers, 5 papers with code
NTIRE 2024 Challenge on Low Light Image Enhancement: Methods and Results
This paper reviews the NTIRE 2024 low light image enhancement challenge, highlighting the proposed solutions and results.
The Ninth NTIRE 2024 Efficient Super-Resolution Challenge Report
In sub-track 1, the practical runtime performance of the submissions was evaluated, and the corresponding score was used to determine the ranking.
NTIRE 2024 Challenge on Image Super-Resolution ($\times$4): Methods and Results
This paper reviews the NTIRE 2024 challenge on image super-resolution ($\times$4), highlighting the solutions proposed and the outcomes obtained.
GT-Rain Single Image Deraining Challenge Report
This report reviews the results of the GT-Rain challenge on single image deraining at the UG2+ workshop at CVPR 2023.
Diving Deep into Regions: Exploiting Regional Information Transformer for Single Image Deraining
Our RTB is used for attention selection of rain-affected and unaffected regions and local modeling of mixed scales.
Clarity ChatGPT: An Interactive and Adaptive Processing System for Image Restoration and Enhancement
The generalization capability of existing image restoration and enhancement (IRE) methods is constrained by the limited pre-trained datasets, making it difficult to handle agnostic inputs such as different degradation levels and scenarios beyond their design scopes.
Stereo Image Rain Removal via Dual-View Mutual Attention
Stereo images, containing left and right view images with disparity, are utilized in solving low-vision tasks recently, e. g., rain removal and super-resolution.
Semi-DerainGAN: A New Semi-supervised Single Image Deraining Network
Although supervised deep deraining networks have obtained impressive results on synthetic datasets, they still cannot obtain satisfactory results on real images due to weak generalization of rain removal capacity, i. e., the pre-trained models usually cannot handle new shapes and directions that may lead to over-derained/under-derained results.
DerainCycleGAN: Rain Attentive CycleGAN for Single Image Deraining and Rainmaking
However, in practice it is rather common to have no un-paired images in real deraining task, in such cases how to remove the rain streaks in an unsupervised way will be a very challenging task due to lack of constraints between images and hence suffering from low-quality recovery results.
A Coarse-to-Fine Multi-stream Hybrid Deraining Network for Single Image Deraining
To obtain the negative rain streaks during training process more accurately, we present a new module named dual path residual dense block, i. e., Residual path and Dense path.
Color Image Enhancement Method Based on Weighted Image Guided Filtering
Then a linear color restoration algorithm is adopted to convert the enhanced intensity image back to the RGB color model, which ensures the hue is constant and undistorted.
