{"id":22919740,"url":"https://github.com/stanfordasl/nhumanmodeling","last_synced_at":"2026-03-15T21:01:59.238Z","repository":{"id":81489708,"uuid":"123646313","full_name":"StanfordASL/NHumanModeling","owner":"StanfordASL","description":"Contains the code for \"Generative Modeling of Multimodal Multi-Human Behavior\" by Boris Ivanovic, Edward Schmerling, Karen Leung, and Marco Pavone.","archived":false,"fork":false,"pushed_at":"2019-02-10T01:11:51.000Z","size":873,"stargazers_count":16,"open_issues_count":0,"forks_count":10,"subscribers_count":20,"default_branch":"master","last_synced_at":"2025-05-12T20:19:51.690Z","etag":null,"topics":["deep-learning","human-robot-interaction","multi-agent-modeling","trajectory-prediction"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/StanfordASL.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2018-03-03T00:50:38.000Z","updated_at":"2024-12-03T04:13:42.000Z","dependencies_parsed_at":null,"dependency_job_id":"c21c5c7f-da6a-4d78-9866-7e7cd37cb772","html_url":"https://github.com/StanfordASL/NHumanModeling","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/StanfordASL/NHumanModeling","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/StanfordASL%2FNHumanModeling","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/StanfordASL%2FNHumanModeling/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/StanfordASL%2FNHumanModeling/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/StanfordASL%2FNHumanModeling/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/StanfordASL","download_url":"https://codeload.github.com/StanfordASL/NHumanModeling/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/StanfordASL%2FNHumanModeling/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":271789258,"owners_count":24821323,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-08-24T02:00:11.135Z","response_time":111,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["deep-learning","human-robot-interaction","multi-agent-modeling","trajectory-prediction"],"created_at":"2024-12-14T07:13:03.100Z","updated_at":"2026-03-15T21:01:59.149Z","avatar_url":"https://github.com/StanfordASL.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"**UPDATE**: There is a newer and much faster version of this codebase implemented in PyTorch! Take a look **[here](https://github.com/StanfordASL/DynSTGModeling)**!\n\n# N-Human Modeling\n\nThis repository contains the code for [Generative Modeling of Multimodal Multi-Human Behavior](https://arxiv.org/abs/1803.02015) by Boris Ivanovic, Edward Schmerling, Karen Leung, and Marco Pavone.\n\n**Note**: We use [Git LFS](https://git-lfs.github.com) to version large files (such as model checkpoints and data). \n\n## Installation ##\n\nFirst, we'll create a conda environment to hold the dependencies.\n```\nconda create --name modeling python=2.7 -y\nsource activate modeling\npip install -r requirements.txt\n```\n\nThen, since this project uses IPython notebooks, we'll install this conda environment as a kernel.\n```\npython -m ipykernel install --user --name modeling --display-name \"Python 2.7 (NHumanModeling)\"\n```\n\nNow, you can start a Jupyter session and view/run all the notebooks with\n```\njupyter notebook\n```\n\nWhen you're done, don't forget to deactivate the conda environment with\n```\nsource deactivate\n```\n\n## Datasets ##\n\nThe preprocessed datasets are available in this repository, under `data/` folders (e.g. `nba-dataset/data/`).\n\nIf you want the *original* traffic weaving or NBA datasets, I obtained them from here: [Traffic Weaving Dataset](https://github.com/StanfordASL/TrafficWeavingCVAE) and [NBA Dataset](https://github.com/linouk23/NBA-Player-Movements).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fstanfordasl%2Fnhumanmodeling","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fstanfordasl%2Fnhumanmodeling","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fstanfordasl%2Fnhumanmodeling/lists"}