This repository implements HaMeR (Hand Mesh Recovery), a deep learning system for reconstructing 3D hand pose and mesh from single RGB images. The approach uses Transformer architectures to process visual features and predict hand parameters including joint rotations and vertex positions. It provides training code, evaluation pipelines, pretrained model weights, and was developed as part of a published research paper.