# A Multi-Person Video Dataset Annotation Method of Spatio-Temporally Actions

arXiv: https://arxiv.org/abs/2204.10160 · HTML: https://mlsanity.com/paper/2204.10160/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 7 of its 11 references that are in the map.
- First posted on arXiv 21 Apr 2022.

## Builds on (most cited first, 7 of 7)

- [SlowFast Networks for Video Recognition](https://mlsanity.com/paper/1812.03982/) (2018)
- [Simple Online and Realtime Tracking with a Deep Association Metric](https://mlsanity.com/paper/1703.07402/) (2017)
- [AVA: A Video Dataset of Spatio-temporally Localized Atomic Visual Actions](https://mlsanity.com/paper/1705.08421/) (2017)
- [Long-Term Feature Banks for Detailed Video Understanding](https://mlsanity.com/paper/1812.05038/) (2018)
- [A Comprehensive Study of Deep Video Action Recognition](https://mlsanity.com/paper/2012.06567/) (2020)
- [Actor-Centric Relation Network](https://mlsanity.com/paper/1807.10982/) (2018)
- [MultiSports: A Multi-Person Video Dataset of Spatio-Temporally Localized Sports Actions](https://mlsanity.com/paper/2105.07404/) (2021)

## Built on by (most cited first, 1 of 1)

- [Student Classroom Behavior Detection based on YOLOv7-BRA and Multi-Model Fusion](https://mlsanity.com/paper/2305.07825/) (2023)

## Abstract (arXiv)

Spatio-temporal action detection is an important and challenging problem in video understanding. However, the application of the existing large-scale spatio-temporal action datasets in specific fields is limited, and there is currently no public tool for making spatio-temporal action datasets, it takes a lot of time and effort for researchers to customize the spatio-temporal action datasets, so we propose a multi-Person video dataset Annotation Method of spatio-temporally 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. https://github.com/Whiffe/Custom-ava-dataset_Custom-Spatio-Temporally-Action-Video-Dataset