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Nvidia has developed an impressive deep learning technique capable of automatically removing noise and artifacts from photos. Whereas recent deep learning work in this field has focused on training a neural network with clean and noisy images, Nvidia’s AI can do so without ever being shown a noise-free example.
The new deep learning-based approach, developed alongside researchers from MIT and Aalto University, can remove noise, artifacts and grain after only seeing two “dirty” samples.
Nvidia used Tesla P100 GPUs with the cuDNN-accelerated TensorFlow deep learning framework and trained the system on 50,000 images in the ImageNet validation set. It then validated the neural network on three different datasets.
The results are rather impressive, especially on images corrupted with random text and photos with excessive noise. As anyone that has worked with photo editing software can attest to, however, noise reduction tools and techniques have been around for many years and in the hands of a skilled user, it’s possible to get very good results.
Also, as with traditional techniques, there does appear to be a loss of sharpness when using Nvidia’s AI.
The development team will be presenting its work in an oral presentation at the International Conference on Machine Learning in Stockholm, Sweden this week.