@inproceedings{20797e61b91e4bd99ce1f6c548f07d30,
title = "Joint coarse-and-fine semantic segmentation",
abstract = "The issue of image semantic segmentation is renowned within computer vision and artificial intelligence. The ground truth in image segmentation is hard to produce and is time- and resource-intensive. Recent research on realtime image semantic segmentation based on deep learning has reduced image resolution through pooling operations, resulting in detail loss in the scene. In order to generate high-quality annotated data, in this paper, we propose a joint coarse-and-fine (JCF) architecture that can repair fragment defects based on a coarse module, and also produce fine details based on a fine module. The experiments show promising results compared to state-of-the-art methods.",
author = "Chiu, {Yi Cheng} and Lin, {Chih Yang} and Timothy Shih",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 16th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2019 ; Conference date: 18-09-2019 Through 21-09-2019",
year = "2019",
month = sep,
doi = "10.1109/AVSS.2019.8909829",
language = "???core.languages.en_GB???",
series = "2019 16th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2019 16th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2019",
}