NAFNet: Image restoration without nonlinear activations

NAFNet is a convolutional neural network architecture designed for low-level vision tasks including image deblurring, denoising, and stereo super-resolution. The model is implemented in PyTorch and operates by replacing traditional nonlinear activation functions with multiplication operations or removing them entirely from the network. The architecture achieves competitive results on standard benchmarks such as GoPro for deblurring and SIDD for denoising while requiring substantially fewer computational operations than comparable methods. The framework is applicable to various image restoration scenarios where computational efficiency and inference speed are relevant considerations.