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Korobkova A.Yu., Tyurin I.N., Kovaleva O.V., Belgorodsky V.S. Digital reinterpretation of archival sketches from Slava Zaitsev’s first collection for the design of contemporary apparel collections. Journal of Clothing Science. 2025; 10(4). Available at: https://kostumologiya.ru/PDF/14IVKL425.pdf (in Russian).

Digital reinterpretation of archival sketches from Slava Zaitsev’s first collection for the design of contemporary apparel collections

Korobkova Alena Yuryevna
Russian State University named A.N. Kosygin (Technologies. Design. Art), Moscow, Russia
E-mail: Alenakorobok2@gmail.com

Tyurin Igor Nikolaevich
Russian State University named A.N. Kosygin (Technologies. Design. Art), Moscow, Russia
Namangan State Technical University, Namangan, Uzbekistan
E-mail: tyurin-in@rguk.ru
ORCID: https://orcid.org/0000-0002-5696-1586

Kovaleva Olga Vladimirovna
Russian State University named A.N. Kosygin (Technologies. Design. Art), Moscow, Russia
E-mail: kovaleva-ov@rguk.ru
ORCID: https://orcid.org/0000-0002-1160-5780

Belgorodsky Valery Savelevich
Russian State University named A.N. Kosygin (Technologies. Design. Art), Moscow, Russia
E-mail: rector@rguk.ru

Abstract. The article examines the use of artificial intelligence technologies in the process of digitally reinterpreting archival sketches of authorial costume based on historical graphic concepts of Soviet fashion from the 1960s. Using the only surviving sketch of a painted quilted jacket from Slava Zaitsev’s first collection (1963) as a reference point, the study traces how contemporary image-generation algorithms can reproduce the artistic logic of the original while simultaneously generating new compositional and plastic solutions. The research focuses on input parameters such as the weight of the source image, the degree of stylization, and variations in text descriptions (prompts) that determine the character of interpretation. The analysis shows that minimizing the number of variables while preserving the priority of the original image ensures a balance between archival authenticity and digital creativity. A comparative examination of the resulting visual series demonstrates the possibility of maintaining stylistic continuity and the plastic expressiveness of form while varying color schemes and textural accents. The results confirm the potential of artificial intelligence in the artistic design of costume as a tool for the actualization of archival heritage. In the long term, these methods can be applied to the reconstruction, visualization, and exhibition representation of historical collections of Russian fashion.

Keywords: Slava Zaitsev; Vyacheslav Mikhailovich Zaitsev; People’s Artist of Russia; fashion designer; preservation of Russian cultural heritage; Russian culture; artificial intelligence; artificial neural networks; convolutional neural networks; image processing; generative design

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