This repository provides PyTorch implementations of various CNN visualization and interpretability techniques. It includes gradient-based methods like guided backpropagation, saliency maps, Grad-CAM and its variants, as well as image generation approaches such as deep dream and class-specific synthesis. The tools help researchers understand what features CNNs detect and how decisions are made by visualizing gradients, activations, and class-specific image patterns.