HOLD is a CVPR 2024 research project that uses deep learning to simultaneously reconstruct articulated hands and objects from single-view RGB videos. The method leverages neural networks and PyTorch to achieve category-agnostic 3D reconstruction without assuming pre-scanned object templates or requiring 3D hand/object training data. It addresses hand-object interaction reconstruction tasks relevant to augmented and virtual reality applications.