Frontiers of Data and Computing ›› 2024, Vol. 6 ›› Issue (2): 177-193.

CSTR: 32002.14.jfdc.CN10-1649/TP.2024.02.016

doi: 10.11871/jfdc.issn.2096-742X.2024.02.016

• Technology and Application • Previous Articles    

An Overview of Object Detection Datasets

LI Lin(),WANG Jiahua,ZHOU Chenyang,KONG Siman,SUN Jianzhi*()   

  1. School of Computer and Artificial Intelligence, Beijing Technology and Business University, Beijing 100048, China
  • Received:2023-07-10 Online:2024-04-20 Published:2024-04-26


[Application Background] Object detection is one of the basic research issues in computer vision, and the object detection dataset is the basis for evaluating the performance of object detection methods. [Purpose] Analyzing and introducing the datasets generated with the development of the object detection field can effectively reveal the characteristics, development trends, and main problems faced in object detection research. It can also present the status of object detection datasets from the perspective of time and domain, and to some extent, provide reference for researchers to use datasets. [Method] From the perspectives of the general datasets of object detection and the specific datasets that include multiple application scenarios such as pedestrian detection, face detection, traffic and road scene object detection, aviation remote sensing detection, and text detection, we focus on the challenges of datasets, list and analyze the most widely used and diverse datasets, provide image examples of different scene datasets, and analyze their main challenges. [Conclusions] While introducing the dataset in the field of object detection, it also reveals the importance of object detection datasets, the challenges and characteristics in different scenarios, as well as the main challenges and future development trends in constructing object detection datasets.

Key words: object detection, dataset, pedestrian detection, face detection, computer vision