Image Data Augmentation

CutBlur is a data augmentation method that is specifically designed for the low-level vision tasks. It cuts a low-resolution patch and pastes it to the corresponding high-resolution image region and vice versa. The key intuition of Cutblur is to enable a model to learn not only "how" but also "where" to super-resolve an image. By doing so, the model can understand "how much" instead of blindly learning to apply super-resolution to every given pixel.

Source: Rethinking Data Augmentation for Image Super-resolution: A Comprehensive Analysis and a New Strategy


Paper Code Results Date Stars


Task Papers Share
Denoising 1 25.00%
Image Restoration 1 25.00%
Image Super-Resolution 1 25.00%
Super-Resolution 1 25.00%


Component Type
🤖 No Components Found You can add them if they exist; e.g. Mask R-CNN uses RoIAlign