@inproceedings{f70f429cd2a346a4b7562904b71c7aea,
title = "NL-DSE: Non-Local Neural Network with Decoder-Squeeze-and-Excitation for Monocular Depth Estimation",
abstract = "Monocular Depth Estimation is a popular and challenging problem for many years. IR CNNs (Convolutional Neural Networks)-based method with encoder-decoder architecture is proposed and shows a reasonable result. In this paper, we propose a SE-Net-based module for the decoder part in the encoder-decoder architecture to improve the result. We proposed a DSE (Decoder-Squeeze-and-Excitation) module to deal with the whole up-sampling process globally for the decoder part. We also include the Non-local Network space attention method to design the Non-Local Decoder-Squeeze-and-Excitation (NL-DSE) module. The proposed NL-DSE module is installed and evaluated on the NYU Depth V2 dataset and achieves higher accuracy. Moreover, the design is independent of the encoder-decoder architecture and can be applied in the other encoder-decoder networks to have a more accurate network.",
keywords = "CNNs, SE-Net, encoder-decoder, monocular depth estimation, up-sampling recalibration",
author = "Tsai, {Tsung Han} and Wan, {Wei Chung}",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023 ; Conference date: 04-06-2023 Through 10-06-2023",
year = "2023",
doi = "10.1109/ICASSP49357.2023.10095633",
language = "???core.languages.en_GB???",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing, Proceedings",
}