Custom Spatio-Temporal Action Video Dataset

This spatio-temporal actions dataset for video understanding consists of 4 parts: original videos, cropped videos, video frames, and annotation files. This dataset uses a proposed new multi-person annotation method of spatio-temporal actions. First, we use ffmpeg to crop the videos and frame the videos; then use yolov5 to detect human in the video frame, and then use deep sort to detect the ID of the human in the video frame. By processing the detection results of yolov5 and deep sort, we can get the annotation file of the spatio-temporal action dataset to complete the work of customizing the spatio-temporal action dataset.