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Information × Registration Number 2120U007880, Article popup.category Препринт Title Region-Selected Image Generation with Generative Adversarial Networks (AI translated) popup.author Korshunov VadymKorshunov Vadym popup.publication 01-01-2020 popup.source_user Український католицький університет popup.source https://hdl.handle.net/20.500.14570/2049 popup.publisher Description Generative adversarial networks (GANs) are one of the most popular models capable of producing high-quality images. However, most of the works generate images from the vector of random values, without explicit control of desired output properties. We study the ways of introducing such control for the user-selected region of interest (RoI). First, we overview and analyze the existing works in areas of image completion (inpainting) and controllable generation. Second, we propose our model based on GANs, which united approaches from the two mentioned areas, for the controllable local content generation. Third, we evaluate the controllability of our model on three accessible datasets – Celeba, Cats, and Cars – and give numerical and visual results of our method. popup.nrat_date 2025-11-05 Close
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Препринт
Korshunov Vadym. Region-Selected Image Generation with Generative Adversarial Networks (AI translated) : published. 2020-01-01; Український католицький університет, 2120U007880
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Updated: 2026-03-21