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Found 7 papers, 2 papers with code
Learning Rate Dropout
The uncertainty of the descent path helps the model avoid saddle points and bad local minima.
Hard Class Rectification for Domain Adaptation
Second, we further consider that the predictions of target samples belonging to the hard class are vulnerable to perturbations.
Semi-supervised Domain Adaptation
Unsupervised Domain Adaptation
A^2Net: Adjacent Aggregation Networks for Image Raindrop Removal
Existing methods for single images raindrop removal either have poor robustness or suffer from parameter burdens.
Rain O'er Me: Synthesizing real rain to derain with data distillation
We present a supervised technique for learning to remove rain from images without using synthetic rain software.
Noise2Blur: Online Noise Extraction and Denoising
Using the new image pair, the denoising network learns to generate clean and high-quality images from noisy observations.
Adaptive noise imitation for image denoising
Coupling the noisy data output from ADANI with the corresponding ground-truth, a denoising CNN is then trained in a fully-supervised manner.
Self-Verification in Image Denoising
Specifically, we treat the output of the network as a ``prior'' that we denoise again after ``re-noising''.
