FBCNN is a state-of-the-art blind JPEG artifacts removal model published at ICCV 2021. It uses deep convolutional networks to estimate JPEG quality factors and remove compression artifacts from single and double JPEG images, handling both color and grayscale inputs. The model is trained with PyTorch and supports arbitrary quality factor prediction for flexible blind restoration.