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Found 6 papers, 5 papers with code
PNEN: Pyramid Non-Local Enhanced Networks
Additionally, the pyramid non-local block can be directly incorporated into convolution neural networks for other image restoration tasks.
Learning a Single Model with a Wide Range of Quality Factors for JPEG Image Artifacts Removal
Our proposed network is a single model approach that can be trained for handling a wide range of quality factors while consistently delivering superior or comparable image artifacts removal performance.
RPATTACK: Refined Patch Attack on General Object Detectors
Firstly, we propose a patch selection and refining scheme to find the pixels which have the greatest importance for attack and remove the inconsequential perturbations gradually.
CMUA-Watermark: A Cross-Model Universal Adversarial Watermark for Combating Deepfakes
Then, we design a two-level perturbation fusion strategy to alleviate the conflict between the adversarial watermarks generated by different facial images and models.
Uncertainty Inspired Underwater Image Enhancement
After that, we adopt a consensus process to predict a deterministic result based on a set of samples from the distribution.
Learning a Simple Low-Light Image Enhancer From Paired Low-Light Instances
Those solutions, however, often fail in revealing image details due to the limited information in a single image and the poor adaptability of handcrafted priors.
Ranked #2 on
Low-Light Image Enhancement
on VV
