Awesome-Transformer-Attention

Why we included this project

Anyone doing research on vision transformers will appreciate how complete this paper index is. It groups hundreds of papers on attention mechanisms and transformer architectures for computer vision into clear sections, with entries on image classification backbones, detection, segmentation, and multimodal work, each linking to official code and related resources. The maintainer actively folds in papers from major conferences like CVPR, ICCV, NeurIPS, and ICLR as they appear, so the list stays current enough to be a practical starting point for literature reviews and related-work searches. It also collects attention-free alternatives and tutorial material, which gives newcomers a way to see how the field has evolved rather than just a flat list of titles.