SETR applies Vision Transformers to semantic segmentation tasks by treating image patches as sequences and using a transformer encoder for dense prediction. The project provides model implementations and configurations for Cityscapes and other segmentation benchmarks, including SETR-Naive and SETR-MLA variants with pretrained weights.