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@article{long2015fcn,
title={Fully convolutional networks for semantic segmentation},
author={Long, Jonathan and Shelhamer, Evan and Darrell, Trevor},
journal={Proceedings of the IEEE conference on computer vision and pattern recognition},
pages={3431--3440},
year={2015}
}
long2015fcn
@article{chen2018deeplab,
title={Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs},
author={Chen, Liang-Chieh and Papandreou, George and Kokkinos, Iasonas and Murphy, Kevin and Yuille, Alan L},
journal={IEEE transactions on pattern analysis and machine intelligence},
volume={40},
number={4},
pages={834--848},
year={2018},
publisher={IEEE}
}
@article{yu2018bisenet,
title={Bisenet: Bilateral segmentation network for real-time semantic segmentation},
author={Yu, Changqian and Wang, Jingbo and Peng, Chao and Gao, Changxin and Yu, Gang and Sang, Nong},
journal={Proceedings of the European conference on computer vision (ECCV)},
pages={325--341},
year={2018}
}
@article{tsai2018learning,
title={Learning to adapt structured output space for semantic segmentation},
author={Tsai, Yi-Hsuan and Hung, Wei-Chih and Schulter, Samuel and Sohn, Kihyuk and Yang, Ming-Hsuan and Chandraker, Manmohan},
journal={Proceedings of the IEEE conference on computer vision and pattern recognition},
pages={7472--7481},
year={2018}
}
@article{tranheden2021dacs,
title={Dacs: Domain adaptation via cross-domain mixed sampling},
author={Tranheden, Wilhelm and Olsson, Viktor and Pinto, Juliano and Svensson, Lennart},
journal={Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision},
pages={1479--1489},
year={2021}
}
@article{he2016deep,
title={Deep residual learning for image recognition},
author={He, Kaiming and Zhang, Xiangyu and Ren, Shaoqing and Sun, Jian},
journal={Proceedings of the IEEE conference on computer vision and pattern recognition},
pages={770--778},
year={2016}
}
@article{chaurasia2017linknet,
title={Linknet: Exploiting encoder representations for efficient semantic segmentation},
author={Chaurasia, Abhishek and Culurciello, Eugenio},
journal={2017 IEEE Visual Communications and Image Processing (VCIP)},
pages={1--4},
year={2017},
organization={IEEE}
}
@article{loveda2021,
author = {Junjue Wang and
Zhuo Zheng and
Ailong Ma and
Xiaoyan Lu and
Yanfei Zhong},
title = {LoveDA: {A} Remote Sensing Land-Cover Dataset for Domain Adaptive
Semantic Segmentation},
journal = {CoRR},
volume = {abs/2110.08733},
year = {2021},
url = {https://arxiv.org/abs/2110.08733},
eprinttype = {arXiv},
eprint = {2110.08733},
timestamp = {Fri, 22 Oct 2021 13:33:09 +0200},
biburl = {https://dblp.org/rec/journals/corr/abs-2110-08733.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
@misc{pidnet2023,
title={PIDNet: A Real-time Semantic Segmentation Network Inspired by PID Controllers},
author={Jiacong Xu and Zixiang Xiong and Shankar P. Bhattacharyya},
year={2023},
eprint={2206.02066},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2206.02066},
}
@article{DBLP:journals/corr/abs-1912-10230,
author = {Irem {\"{U}}lk{\"{u}} and
Erdem Akag{\"{u}}nd{\"{u}}z},
title = {A Survey on Deep Learning-based Architectures for Semantic Segmentation
on 2D images},
journal = {CoRR},
volume = {abs/1912.10230},
year = {2019},
url = {http://arxiv.org/abs/1912.10230},
eprinttype = {arXiv},
eprint = {1912.10230},
timestamp = {Fri, 03 Jan 2020 16:10:45 +0100},
biburl = {https://dblp.org/rec/journals/corr/abs-1912-10230.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
@article{fan2021rethinking,
author = {Mingyuan Fan and
Shenqi Lai and
Junshi Huang and
Xiaoming Wei and
Zhenhua Chai and
Junfeng Luo and
Xiaolin Wei},
title = {Rethinking BiSeNet For Real-time Semantic Segmentation},
journal = {CoRR},
volume = {abs/2104.13188},
year = {2021},
url = {https://arxiv.org/abs/2104.13188},
eprinttype = {arXiv},
eprint = {2104.13188},
timestamp = {Mon, 26 Aug 2024 16:11:59 +0200},
biburl = {https://dblp.org/rec/journals/corr/abs-2104-13188.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}