SCB-Dataset3: A Benchmark for Detecting Student Classroom Behavior

Fan Yang, Tao Wang
10/4/2023
cs.CV

Official code: Whiffe/SCB-dataset (496 stars, last commit 2025-09-18).

Abstract

The use of deep learning methods to automatically detect students' classroom behavior is a promising approach for analyzing their class performance and improving teaching effectiveness. However, the lack of publicly available datasets on student behavior poses a challenge for researchers in this field. To address this issue, we propose the Student Classroom Behavior dataset (SCB-dataset3), which represents real-life scenarios. Our dataset comprises 5686 images with 45578 labels, focusing on six behaviors: hand-raising, reading, writing, using a phone, bowing the head, and leaning over the table. We evaluated the dataset using the YOLOv5, YOLOv7, and YOLOv8 algorithms, achieving a mean average precision (map) of up to 80.3$\%$. We believe that our dataset can serve as a robust foundation for future research in student behavior detection and contribute to advancements in this field. Our SCB-dataset3 is available for download at: https://github.com/Whiffe/SCB-dataset

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Code Implementations(1)

Whiffe/SCB-datasetOfficial100%

Student Classroom Behavior dataset

49652Apr 5, 20231 years ago

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Cite this paper

@article{yang2023scbdataset,
  title  = {SCB-Dataset3: A Benchmark for Detecting Student Classroom Behavior},
  author = {Fan Yang and Tao Wang},
  year   = {2023},
  eprint = {2310.02522},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2310.02522v2}
}

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