https://vimeo.com/1134260310?autoplay=1&loop=1&autopause=0&background=1&muted=1&ratio=2386:1634 A collection of datasets and tools for egocentric and exocentric human activity understanding, featuring hand-object interactions, manipulation tasks, and multi-view recordings. ## Background EgoExo Forge provides a consistent labeling scheme and data layout across multiple egocentric and exocentric human datasets with varying sensor configurations and annotations. The following datasets are supported: * [Assembly101](https://assembly-101.github.io/): A procedural activity dataset with 4321 multi-view videos of people assembling and disassembling 101 take-apart toy vehicles, featuring rich variations in action ordering, mistakes, and corrections. * [HO-Cap](https://irvlutd.github.io/HOCap/): A dataset for 3D reconstruction and pose tracking of hands and objects in videos, featuring humans interacting with objects for various tasks including pick-and-place actions and handovers. * [EgoDex](https://arxiv.org/abs/2505.11709): The largest and most diverse dataset of dexterous human manipulation with 829 hours of egocentric video and paired 3D hand tracking, covering 194 different tabletop tasks with everyday household objects. ## Run the code This is an external example. Check the [repository](https://github.com/rerun-io/egoexo-forge) for more information. You can try the example on a HuggingFace space [here](https://pablovela5620-egoexo-forge-viewer.hf.space/). Or locally, make sure you have the [Pixi package manager](https://pixi.sh/latest/#installation) installed and run ```sh git clone https://github.com/rerun-io/egoexo-forge.git cd egoexo-forge pixi run app ```