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Access FreeMan on Hugging Face

This is a form to enable access to FreeMan on Hugging Face after you have been granted access.
Please visit the FreeMan Project Page and complete pre requisite procudures before confirming request here.
Requests will be processed in 1-2 days.

Your Hugging Face account email address MUST match the email or Huggingface ID you provide on the information backup forms matches the one filled in previous step, or your request will not be approved. For who are in mainland China, you can also apply & download from OpenDataLab for stable connection. 中国大陆的使用者可以考虑通过OpenDataLab获取下载链接。
FreeMan Usage Agreement can be found on our website.

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FreeMan: Towards 3D Human Pose Estimation In the Wild

🌏 Project Page🙋‍♂️ Download Procedure📄 Paper ▶️ YouTube 🖥️ Code


This is official release of FreeMan dataset. To access the dataset, please submit previous steps at HERE.

[❗️❗️❗️] MAKE SURE you finish required steps HERE before apply dataset access here. Otherwise access request will NOT be approved.

For who are in mainland China, you can also apply & download from OpenDataLab for stable connection.

中国大陆的使用者可以考虑通过OpenDataLab获取下载链接。

Notice

[2023.09] 30FPS data for 3D Human Pose Estimation uploaded. Other data are under processing.

[2023.09] Paper released on arxiv. We are uploading the datasets. Please stay tuned.


Overview

Current uploaded data:

  • 8 views
  • 40 subjects
  • 11M frames
  • 10 types of scenarios
  • 27 locations

File Info

The whole dataset is about 800GB and all RGB data are stored in video format. RGB data are zipped by subject, while all annotation files are zipped all togethers. Besides zip files, text files store list of each subsets.

session_list.txt: all session names included in FreeMan;
session_list_mono.txt: sample names and corrsponding view index in monocular experiments;
ignore_list.txt: sessions not used temporarily in experiments of FreeMan Paper(https://arxiv.org/abs/2309.05073);
train/valid/test.txt: session names in train/validation/test subset, respectivelly. They are seperated by subject.

To verify downloaded items, sha256sum for video files are shown here:

File Name sha256sum File Name sha256sum File Name sha256sum File Name sha256sum
subj01.zip a02d8e47d36235ae760f553b85b7df21cb711fecea73e7542df49e5c2d1441e6 subj02.zip 10d9b9af46ade9069401832ad0f1b06edd12a9e39f2ea9d06a55f1371bb9a28f subj02.01 94ac1a0af242c33bb0d8777bea094fe0542ace0077f8836ff3944b0e41d3e45b subj02.02 67174ca443c7c35fd1604d69ae30a46fece96af83d83d7428db1ce6483782739
subj02.03 05534d4e352454a5ffe0df802da53057953df274879d3067e023f2667773e4f6 subj03.zip 6825c59ecaec5114ead9f8d5f88d3d8ec2949cb9db102fb6beee6c338d2ae174 subj04.zip 48dc77e2c6fe741b8b271ee302ba5883eabec5ed960dac66181b58e38a36282d subj05.zip ab8033cc55e5e4f578490a225e60e986e67f162b79da44e68afcab805f396f2a
subj06.zip a204970bc9ebd142a97276ed6bb095cb3a9e621090a8fad57fb8bbe99b23d733 subj07.zip 292cf18231592c730a811488e9896756ee137b737c1e207428efda9f73a75d2d subj08.zip fad741aa4400c813a8a71303ad855c7d0e130613db3c72222b14f010ee8c74d4 subj09.zip 46bcf599207c7fcaac84102e40a60c29720e916431f13b932273d33199bab922
subj10.zip 320f9c0cb169261bbcdc60163525d5b0b35fb17110dc488ad71491047b35d582 subj11.zip 72e3f99b5bfb918c269bfc53515c1d556e3ee8eed8d5aa82d619971eb74e76af subj12.zip 5e7c8dea74b59f14f65b08a51c1688f920ac24f943a1a6102fdb519b5df4702a subj13.zip 4a76b93a26fad023b315f46ff107ed619adb920cb2fb5d03e8de7f33bc68d0f6
subj14.zip d78998c715bd54a65c9da7b247212c1a1833405c125bb5492b5d5fca9ec0e17f subj15.zip 070dfdd2d420c4392f487ae9558406cee970fe43f802f26ca28a4871f8b46d0b subj16.zip 9933c2e3f8b114b96e4b5f9938d22ca77686b6952489406ee07705ac4601caa2 subj17.zip 2e80f886faf3a5b3679da8f8f7bde0034008415128c404ea9445368f1d0cbe17
subj18.zip 0f060e6c2b1699e9780f60b826946d69a77ae6c668cf6d02d3063b172ba3e3e0 subj19.zip 12bb121a1f4bd57a741ab651375af9bed105a9226390d225d8b08512d910f5d6 subj20.zip c07f8e261b4df3913399589405cbefd6a70807c6400373c92a4635390d4ee644 subj21.zip 26bc74962012698402836d2c327872c240b638a2bb54ae3b85af12b6a93269ee
subj22.zip 0b69237ff95205ff51c95bdb34cdaabf0304ecf856d4ce1f07d9f76c16e42cd1 subj22.01 f66ac6370835164ee66e7db1cf9c60609218f3c6d19dfe2b07f39bffa12635ae subj23.zip 2ad8a29c949e0208c7338efd955a3f6b9322c61a691ceac3be89d356fb02eb1c subj24.zip 1902fd34d9d9717c5be95af36162095aa2db35d6327e6d7d828b3c7ffe97587c
subj25.zip 01209473ca4a50e72e20849150dd489b62b6153fd2be798b699ceb106af40d1d subj26.zip 6cf1b76860a68bf8452e7e7719b2bb18bcb727691fb14e37da3864170973bfba subj27.zip a6e17a99b4597e26bb38ab86eb1c6f31534a643fb5ede55c888d34eda87fa546 subj28.zip f4ba067b02e2fd15d06f3e9d0eb750d2054d199b18d53258a77158153bef5c20
subj29.zip 2cfec4175ed17b2763af4d21b6a924fd31cc4176109e53beaa5141ff63715db0 subj30.zip c57c28de39dd81f579df00758717e1e9f3a73df338c61b51667be450beea8220 subj31.zip ee83b60bc25e5e3fe63f56437e8a9c023d9e7deebea987e20516d568280f01c0 subj32.zip 7e217b54696f9214585072def09f43a11a3f0fa2181d9478106055c69f2a2a48
subj33.zip 3f214e38daf8d416d2c5a5f5c32e6ea093a6c5cbc4c9eaa47e4a7e23c733a001 subj34.zip 39634d0f0e2db1bce9b9254a7dbc1425d5c4f83b38b64158e6ad8d411dfe4c65 subj35.zip 75c41ae4ade932774a3e8d58684c2b7fb9d62895dc87df9e1112d4d54894dae5 subj36.zip fc71637a6c46ad8de362204277c0bd68058b7a1e88c05c1bd713d80a85ea74ed
subj37.zip 75347b1c8cd5e4afaa923376bfe5109e890c5593388de2145cfd2fc081d9ba83 subj38.zip e99d2de0a05c798fa91112ea69468bd0cbeb00aaad1c5d330bacee0ede30f540 subj39.zip 669feb7b7effee0cc6d532151c509c89dcd5e85a259ad56cf9df321e526f56fa subj40.zip c3f632c5e52331209af17c44d4ee6a16511d625096a19b4b043bc811489b0fa3

Citation

If you find FreeMan helpful and used in your project, please cite our paper.

@article{wang2023freeman,
  title={FreeMan: Towards Benchmarking 3D Human Pose Estimation in the Wild},
  author={Wang, Jiong and Yang, Fengyu and Gou, Wenbo and Li, Bingliang and Yan, Danqi and Zeng, Ailing and Gao, Yijun and Wang, Junle and Zhang, Ruimao},
  journal={arXiv preprint arXiv:2309.05073},
  year={2023}
}

Contact

If any questions, please feel free to email us at [email protected], [email protected], or leave your questions in chat/issues.

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