A Survey on African Computer Vision Datasets, Topics and Researchers
- URL: http://arxiv.org/abs/2401.11617v2
- Date: Sun, 4 Feb 2024 18:17:27 GMT
- Title: A Survey on African Computer Vision Datasets, Topics and Researchers
- Authors: Abdul-Hakeem Omotayo, Ashery Mbilinyi, Lukman Ismaila, Houcemeddine
Turki, Mahmoud Abdien, Karim Gamal, Idriss Tondji, Yvan Pimi, Naome A. Etori,
Marwa M. Matar, Clifford Broni-Bediako, Abigail Oppong, Mai Gamal, Eman Ehab,
Gbetondji Dovonon, Zainab Akinjobi, Daniel Ajisafe, Oluwabukola G. Adegboro,
Mennatullah Siam
- Abstract summary: This study undertakes a thorough analysis of 63,000 Scopus-indexed computer vision publications from Africa.
The aim is to provide a survey of African computer vision topics, datasets and researchers.
- Score: 5.12557893822503
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: 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.
Related papers
- Vision-Language Models under Cultural and Inclusive Considerations [53.614528867159706]
Large vision-language models (VLMs) can assist visually impaired people by describing images from their daily lives.
Current evaluation datasets may not reflect diverse cultural user backgrounds or the situational context of this use case.
We create a survey to determine caption preferences and propose a culture-centric evaluation benchmark by filtering VizWiz, an existing dataset with images taken by people who are blind.
We then evaluate several VLMs, investigating their reliability as visual assistants in a culturally diverse setting.
arXiv Detail & Related papers (2024-07-08T17:50:00Z) - A Comprehensive Survey on Underwater Image Enhancement Based on Deep Learning [51.7818820745221]
Underwater image enhancement (UIE) presents a significant challenge within computer vision research.
Despite the development of numerous UIE algorithms, a thorough and systematic review is still absent.
arXiv Detail & Related papers (2024-05-30T04:46:40Z) - What do we know about Computing Education in Africa? A Systematic Review of Computing Education Research Literature [0.0]
Africa is underrepresented in the computing education research (CER) community.
This research investigates the prominent CER journals and conferences to discern the kind of research that has been published and how much contribution they have made to the growing field.
arXiv Detail & Related papers (2024-03-28T20:34:16Z) - Data Augmentation in Human-Centric Vision [54.97327269866757]
This survey presents a comprehensive analysis of data augmentation techniques in human-centric vision tasks.
It delves into a wide range of research areas including person ReID, human parsing, human pose estimation, and pedestrian detection.
Our work categorizes data augmentation methods into two main types: data generation and data perturbation.
arXiv Detail & Related papers (2024-03-13T16:05:18Z) - Flickr Africa: Examining Geo-Diversity in Large-Scale, Human-Centric
Visual Data [3.4022338837261525]
We analyze human-centric image geo-diversity on a massive scale using geotagged Flickr images associated with each nation in Africa.
We report the quantity and content of available data with comparisons to population-matched nations in Europe.
We present findings for an othering'' phenomenon as evidenced by a substantial number of images from Africa being taken by non-local photographers.
arXiv Detail & Related papers (2023-08-16T20:12:01Z) - Towards a Better Understanding of the Computer Vision Research Community
in Africa [4.775172424932638]
We study the opportunities available for African institutions to publish in top-tier computer vision venues.
We show that African publishing trends in top-tier venues do not exhibit consistent growth, unlike other continents such as North America or Asia.
We highlight that both Eastern and Western Africa are exhibiting a promising increase with the last two years closing the gap with Southern Africa.
arXiv Detail & Related papers (2023-05-11T12:54:10Z) - A Survey on RGB-D Datasets [69.73803123972297]
This paper reviewed and categorized image datasets that include depth information.
We gathered 203 datasets that contain accessible data and grouped them into three categories: scene/objects, body, and medical.
arXiv Detail & Related papers (2022-01-15T05:35:19Z) - Reconfiguring Data Infrastructure Ecosystem in Africa: A Primer Toward
Digital Sovereignty [0.0]
The growth of the Internet and its associated technologies have tremendously impacted our society.
There is therefore a need for African nations to design appropriate blueprint to ensure security of her digital infrastructure.
A roadmap in the immediate, short and long-term in accordance with the framework of African developmental goals should be put in place to guide the implementation.
arXiv Detail & Related papers (2021-09-29T04:13:18Z) - MasakhaNER: Named Entity Recognition for African Languages [48.34339599387944]
We create the first large publicly available high-quality dataset for named entity recognition in ten African languages.
We detail characteristics of the languages to help researchers understand the challenges that these languages pose for NER.
arXiv Detail & Related papers (2021-03-22T13:12:44Z) - A Survey of Embedding Space Alignment Methods for Language and Knowledge
Graphs [77.34726150561087]
We survey the current research landscape on word, sentence and knowledge graph embedding algorithms.
We provide a classification of the relevant alignment techniques and discuss benchmark datasets used in this field of research.
arXiv Detail & Related papers (2020-10-26T16:08:13Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.