FastDVDnet: Towards Real-Time Deep Video Denoising Without Flow Estimation

Understand

In this paper, we propose a state-of-the-art video denoising algorithm based on a convolutional neural network architecture.

• Until recently, video denoising with neural networks had been a largely under explored domain, and existing methods could not compete with the performance of the best patch-based methods.
• The approach we introduce in this paper, called FastDVDnet, shows similar or better performance than other state-of-the-art competitors with significantly lower computing times.
• In contrast to other existing neural network denoisers, our algorithm exhibits several desirable properties such as fast runtimes, and the ability to handle a wide range of noise levels with a single network model.