Reflection Removal with Generative Adversarial Networks

dc.contributor.author	Zabulskyi, Volodymyr
dc.date.accessioned	2024-02-15T08:17:46Z
dc.date.available	2024-02-15T08:17:46Z
dc.date.issued	2020
dc.identifier.citation	Zabulskyi, Volodymyr. Reflection Removal with Generative Adversarial Networks / Zabulskyi, Volodymyr; Supervisor: Jiri Matas; Ukrainian Catholic University, Department of Computer Sciences. – Lviv: 2020. – 38 p.	uk
dc.identifier.uri	https://er.ucu.edu.ua/handle/1/4490
dc.language.iso	en	uk
dc.title	Reflection Removal with Generative Adversarial Networks	uk
dc.type	Preprint	uk
dc.status	Публікується вперше	uk
dc.description.abstracten	We propose an approach for the single image reflection removal problem. Our model is based on a feature pyramid network (FPN), trained with adversarial and perceptual losses. Additionally, we address the problem of bright spots removal when only a small portion of an image is covered with the reflection. The difficulty of collecting real-world data makes the problem even harder to solve. We propose a novel method of collecting real-world data, that does not require any additional devices but a camera, and is cheaper than the existing ones. We collected a small dataset with this approach.	uk