  Computer vision encompasses a range of tasks such as object detection,
semantic segmentation, and 3D reconstruction. Despite its relevance to African
communities, research in this field within Africa represents only 0.06% of
top-tier publications over the past decade. This study undertakes a thorough
analysis of 63,000 Scopus-indexed computer vision publications from Africa,
spanning from 2012 to 2022. The aim is to provide a survey of African computer
vision topics, datasets and researchers. A key aspect of our study is the
identification and categorization of African Computer Vision datasets using
large language models that automatically parse abstracts of these publications.
We also provide a compilation of unofficial African Computer Vision datasets
distributed through challenges or data hosting platforms, and provide a full
taxonomy of dataset categories. Our survey also pinpoints computer vision
topics trends specific to different African regions, indicating their unique
focus areas. Additionally, we carried out an extensive survey to capture the
views of African researchers on the current state of computer vision research
in the continent and the structural barriers they believe need urgent
attention. In conclusion, this study catalogs and categorizes Computer Vision
datasets and topics contributed or initiated by African institutions and
identifies barriers to publishing in top-tier Computer Vision venues. This
survey underscores the importance of encouraging African researchers and
institutions in advancing computer vision research in the continent. It also
stresses on the need for research topics to be more aligned with the needs of
African communities.
