SegFormer is a semantic segmentation method using hierarchical transformers that was published at NeurIPS 2021. It provides official PyTorch training and evaluation code along with pretrained models. The approach uses a hierarchical transformer encoder combined with a lightweight all-MLP decoder head to achieve efficient pixel-level segmentation across datasets like ADE20K and Cityscapes.