CCNet is a research implementation of a semantic segmentation architecture that uses a novel Criss-Cross Attention mechanism to model long-range contextual dependencies efficiently. The model is built on PyTorch and achieves state-of-the-art results on the Cityscapes dataset. This branch contains the pure Python implementation of the original work.