{"id":22919922,"url":"https://github.com/zjcv/c3d","last_synced_at":"2026-05-19T05:34:40.959Z","repository":{"id":111996869,"uuid":"290806121","full_name":"ZJCV/C3D","owner":"ZJCV","description":"[ICCV 2015] Learning Spatiotemporal Features with 3D Convolutional Networks","archived":false,"fork":false,"pushed_at":"2020-09-12T13:01:42.000Z","size":47,"stargazers_count":2,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-10-20T08:31:55.052Z","etag":null,"topics":["3d-convolutional-networks","c3d","pytorch"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/ZJCV.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":"2020-08-27T15:02:10.000Z","updated_at":"2023-10-12T08:17:37.000Z","dependencies_parsed_at":null,"dependency_job_id":"572aecac-f0d3-441b-8ce3-f756fd479d89","html_url":"https://github.com/ZJCV/C3D","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/ZJCV/C3D","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ZJCV%2FC3D","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ZJCV%2FC3D/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ZJCV%2FC3D/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ZJCV%2FC3D/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ZJCV","download_url":"https://codeload.github.com/ZJCV/C3D/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ZJCV%2FC3D/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":33203121,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-18T09:27:30.708Z","status":"online","status_checked_at":"2026-05-19T02:00:06.763Z","response_time":58,"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":["3d-convolutional-networks","c3d","pytorch"],"created_at":"2024-12-14T07:13:52.992Z","updated_at":"2026-05-19T05:34:40.926Z","avatar_url":"https://github.com/ZJCV.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003cdiv align=\"right\"\u003e\n  语言:\n    🇨🇳\n  \u003ca title=\"英语\" href=\"./README.en.md\"\u003e🇺🇸\u003c/a\u003e\n  \u003c!-- \u003ca title=\"俄语\" href=\"../ru/README.md\"\u003e🇷🇺\u003c/a\u003e --\u003e\n\u003c/div\u003e\n\n \u003cdiv align=\"center\"\u003e\u003ca title=\"\" href=\"https://github.com/ZJCV/C3D\"\u003e\u003cimg align=\"center\" src=\"./imgs/C3D.png\"\u003e\u003c/a\u003e\u003c/div\u003e\n\n\u003cp align=\"center\"\u003e\n  «C3D» 复现了论文\u003ca title=\"\" href=\"https://arxiv.org/abs/1412.0767v4\"\u003eLearning Spatiotemporal Features with 3D Convolutional Networks\n\u003c/a\u003e提出的视频分类模型\n\u003cbr\u003e\n\u003cbr\u003e\n  \u003ca href=\"https://github.com/RichardLitt/standard-readme\"\u003e\u003cimg src=\"https://img.shields.io/badge/standard--readme-OK-green.svg?style=flat-square\"\u003e\u003c/a\u003e\n  \u003ca href=\"https://conventionalcommits.org\"\u003e\u003cimg src=\"https://img.shields.io/badge/Conventional%20Commits-1.0.0-yellow.svg\"\u003e\u003c/a\u003e\n  \u003ca href=\"http://commitizen.github.io/cz-cli/\"\u003e\u003cimg src=\"https://img.shields.io/badge/commitizen-friendly-brightgreen.svg\"\u003e\u003c/a\u003e\n\u003c/p\u003e\n\n`C3D`扩展了卷积核的维度，通过加入时间维度，将卷积核从空间感受野（`HxW`）扩展到时空感受野（`TxHxW`），能够有效的捕捉视频片段中的动作信息\n\n## 内容列表\n\n- [内容列表](#内容列表)\n- [使用](#使用)\n- [主要维护人员](#主要维护人员)\n- [参与贡献方式](#参与贡献方式)\n- [许可证](#许可证)\n\n## 使用\n\n训练命令如下：\n\n```\n$ export CUDA_VISIBLE_DEVICES=1\n$ export PYTHONPATH=.\n$ python tools/train.py --config_file configs/c3d_hmdb51.yaml\n```\n\n*本工程使用了`PyTorch`实现的`HMDB51`和`UCF101`数据集类，其解析和加载速度非常慢*\n\n## 主要维护人员\n\n* zhujian - *Initial work* - [zjykzj](https://github.com/zjykzj)\n\n## 参与贡献方式\n\n欢迎任何人的参与！打开[issue](https://github.com/zjykzj/C3D/issues)或提交合并请求。\n\n注意:\n\n* `GIT`提交，请遵守[Conventional Commits](https://www.conventionalcommits.org/en/v1.0.0-beta.4/)规范\n* 语义版本化，请遵守[Semantic Versioning 2.0.0](https://semver.org)规范\n* `README`编写，请遵守[standard-readme](https://github.com/RichardLitt/standard-readme)规范\n\n## 许可证\n\n[Apache License 2.0](LICENSE) © 2020 zjykzj","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fzjcv%2Fc3d","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fzjcv%2Fc3d","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fzjcv%2Fc3d/lists"}