Track 1: Micro-Action Recognition
Micro-Action 52 (MA-52) dataset:  🧾Application Form  |  License Aggreements   |   Data (🤗[Hugging Face]) Â
Track 2: Micro-Action Recognition
Multi-label Micro-Action 52 (MMA-52) dataset:  🧾Application Form  |  License Aggreements   |   Data (🤗[Hugging Face]) Â
The Application Form and License Agreements (LA) must be filled out before participants can get access to any data. Â
(1) The LA must be signed by a person with an email that affiliated with an institution or company (e.g., xx.xx@mit.edu, xx.xx@microsoft.com ), which means that the person has a fixed position in the institution or company (e.g., a professor from a university, or an employee from a company). Personal emails (e.g., xxx@gmail.com, xxx@qq.com ) are NOT valid. For students, please ask your supervisor to sign the LA.
(2) The signer is fully responsible (for all users whose IDs are associated with him/her) to make sure that all associated ID users are fully aware of the LA contents, and the data is accessed and used in the proper way according to LA. Data users have no right to distribute the data in any form.
(3) Researchers are only permitted to utilize the RGB visual information from the dataset. The use of audio data is no longer allowed under the updated policy.
(4) The data is shared only for the research purpose of this competition usage but not for any other usage.Â
(5) Participants should send ONE email with all the signed LA in PDF format to Dr. Kun Li (kunli.hfut@gmail.com) and Prof. Dan Guo(guodan@hfut.edu.cn). In addition, please apply the access on the HuggingFace page. We will approve your application after receiving the signed LA and the team registration form.Â
Note: Applications without a valid submission of the signed LA and application form will not be granted access to the dataset.
Reference:
[1] Guo D, Li K, Hu B, Zhang Y, Wang M. Benchmarking micro-action recognition: Dataset, methods, and applications. IEEE Transactions on Circuits and Systems for Video Technology. 2024; 34(7):6238-52. [PDF]
[2] Li et al. MMAD: Multi-label Micro-Action Detection in Videos. arXiv 2024. [PDF]
[3] Chen H., Shi H., Liu X., Li X., and Zhao G. SMG: A Micro-gesture Dataset Towards Spontaneous Body Gestures for Emotional Stress State Analysis. International Journal of Computer Vision. 2023: 1-21. [PDF]
[4] Liu, X., Shi H., Chen H., Yu Z., Li X., and Zhao G. "iMiGUE: An identity-free video dataset for micro-gesture understanding and emotion analysis." In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 10631-10642. 2021. [PDF]