@inproceedings{bfd0a976ac6a4592b4ad24d330644fe9,
title = "Object-Ratio-Preserving Video Retargeting Framework based on Segmentation and Inpainting",
abstract = "The recent development of video-based content platforms led the easy access to videos decades ago. However, some past videos have a old screen ratio. If an image with this ratio is executed on a display with a wider screen ratio, the image is excessively stretched horizontally or creates a black box, which prevents efficient viewing of content. In this paper, we propose a method for retargeting the old ratio video frames to a wider ratio while maintaining the original ratio of important objects in content using deep learning-based semantic segmentation and inpainting techniques. Our research shows that proposed method can make a retargeted frames visually natural.",
author = "Jin, {Jun Gyu} and Jaehyun Bae and Baek, {Han Gyul} and Park, {Sang Hyo}",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops, WACVW 2023 ; Conference date: 03-01-2023 Through 07-01-2023",
year = "2023",
doi = "10.1109/WACVW58289.2023.00055",
language = "English",
series = "Proceedings - 2023 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops, WACVW 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "497--503",
booktitle = "Proceedings - 2023 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops, WACVW 2023",
address = "United States",
}