Autors: Nikolova, D. V., Vladimirov, I. H., Terneva, Z. A.
Title: Artificial Humans: an Overview of Photorealistic Synthetic Datasets and Possible Applications
Keywords: Artificial Humans, Synthetic Dataset, Photorealistic, Human

Abstract: In this scientific paper, an overview of different photorealistic synthetic human datasets is presented. The creation of more and more artificial data is leading to rapid progress in various fields. Synthetic faces and whole bodies are needed during the processes of training and exploitation of applications in the field. The state-of-the-art synthetic human representations are listed, including their applications.


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ICEST Conference, issue 57, 2022, Macedonia, IEEE, DOI 10.1109/ICEST55168.2022.9828729

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Цитирания (Citation/s):
1. Nikolova, D., Vladimirov, I., & Manolova, A. (2023, June). An Experimental Analysis of Deep Learning Models for Human Activity Recognition with Synthetic Data. In 2023 58th International Scientific Conference on Information, Communication and Energy Systems and Technologies (ICEST) (pp. 277-280). IEEE. - 2023 - в издания, индексирани в Scopus или Web of Science
2. Mejia-Escobar, C., Cazorla, M., & Martinez-Martin, E. (2023). Improving Facial Expression Recognition through Data Preparation & Merging. IEEE Access. - 2023 - в издания, индексирани в Scopus или Web of Science

Вид: пленарен доклад в международен форум, публикация в реферирано издание, индексирана в Scopus