CVPR 2023 - Zero-Shot Noise2Noise: Efficient Image Denoising without any Data

In this episode we discuss Zero-Shot Noise2Noise: Efficient Image Denoising without any Data by Youssef Mansour, Reinhard Heckel. The paper proposes a new method for image denoising that does not rely on any training data or knowledge of the noise distribution and is computationally efficient. The proposed method utilizes a simple 2-layer network that can denoise pixel-wise independent noise and outperforms existing dataset-free methods at a reduced cost. The method is motivated by Noise2Noise and Neighbour2Neighbour and achieves a better trade-off between denoising quality, generalization, and computational resources.