@inproceedings{8ed8e4ee55e3424195d14c90ea03b673,
title = "Dual-Encoding Y-ResNet for generating a lens flare effect in images",
abstract = "Taking photos against the light generates a certain visual effect. Taking a photo in the direction where the sun is located also results in a change in the temperature of the photo as well as the appearance of a visual effect in the form of the flare of light. In this article, we present an innovative neural network model called Y-ResNet, whose input consists of two samples and the output consists of one. This solution makes it possible to train the network by providing the original image and the flare effect, which will result in a modified sample. The training was conducted on a commonly known CityScapes dataset, where, by using classic data processing methods and the k-means algorithm, it was possible to add a flare if there was a visible portion of the sky in the input image. The proposed solution was described and tested to demonstrate the capabilities of the proposed method. The results show the superiority of the approach against the traditional ResNet without a second encoding path, generating better results, and creating a better impression of the lens-flare effect.",
keywords = "CityScapes, dual-encoding, flare, image manipulation, light, segmentation, y-resnet",
author = "Dawid Polap and Antoni Jaszcz and Gautam Srivastava",
note = "Publisher Copyright: {\textcopyright} 2024 IEEE.; 2024 International Joint Conference on Neural Networks, IJCNN 2024 ; Conference date: 30-06-2024 Through 05-07-2024",
year = "2024",
doi = "10.1109/IJCNN60899.2024.10651041",
language = "English",
series = "Proceedings of the International Joint Conference on Neural Networks",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2024 International Joint Conference on Neural Networks, IJCNN 2024 - Proceedings",
address = "United States",
}