This repository maintains an organized collection of research papers on transformer-based approaches in computer vision, covering topics like classification, detection, segmentation, generative models, and video understanding. Papers are categorized by task (action recognition, depth estimation, adversarial attacks, etc.) with links to code implementations where available. It serves as a reference resource for researchers tracking developments in vision transformers (ViT), DETR, and related deep learning architectures.