The dataset contains 10000 event stream, saved in the format of “npy”. Each file contains multiple events with the form of (timestamp, x, y, polarity).
Folder’s names consist of individuals’ code, action name, illumination, camera position. Labels for pose estimation are in COCO format.
For more information of how the dataset was created, please refer to the paper.
We provide an interface to this dataset so that users can easily access their own applications using Pytorch, Python 3 is recommended.
Preprocessing code for the dataset can be found here: https://github.com/Brain-Cog-Lab/Bullying10k.
More details can be found in this program.
[1] Yiting Dong, Yang Li, Dongcheng Zhao, Guobin Shen, Yi Zeng. Bullying10K: A Neuromorphic Dataset towards Privacy-Preserving Bullying Recognition. figshare (2023).
[2] Yiting Dong, Yang Li, Dongcheng Zhao, Guobin Shen, Yi Zeng. Bullying10K: A Neuromorphic Dataset towards Privacy-Preserving Bullying Recognition. arXiv preprint ArXiv. /abs/2306.11546 (2023).