SemanticRT: A Large-Scale Dataset and Method for Robust Semantic Segmentation in Multispectral Images

Author:

Ji Wei1ORCID,Li Jingjing1ORCID,Bian Cheng2ORCID,Zhang Zhicheng3ORCID,Cheng Li1ORCID

Affiliation:

1. University of Alberta, Edmonton, AB, Canada

2. ByteDance Ltd, Beijing, China

3. JancsiTech, Guangdong, China

Funder

Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Grants

Guangzhou Key Research and Development Project

National Natural Science Foundation of China

Publisher

ACM

Reference80 articles.

1. MiniNet: An Efficient Semantic Segmentation ConvNet for Real-Time Robotic Applications

2. Aiding the Diagnosis of Diabetic and Hypertensive Retinopathy Using Artificial Intelligence-Based Semantic Segmentation

3. Jens Behley , Martin Garbade , Andres Milioto , Jan Quenzel , Sven Behnke , Cyrill Stachniss , and Jurgen Gall . 2019 . Semantickitti: A dataset for semantic scene understanding of lidar sequences. In ICCV. 9297--9307. Jens Behley, Martin Garbade, Andres Milioto, Jan Quenzel, Sven Behnke, Cyrill Stachniss, and Jurgen Gall. 2019. Semantickitti: A dataset for semantic scene understanding of lidar sequences. In ICCV. 9297--9307.

4. Liang-Chieh Chen , George Papandreou , Iasonas Kokkinos , Kevin Murphy , and Alan L Yuille . 2014. Semantic image segmentation with deep convolutional nets and fully connected crfs. arXiv preprint arXiv:1412.7062 ( 2014 ). Liang-Chieh Chen, George Papandreou, Iasonas Kokkinos, Kevin Murphy, and Alan L Yuille. 2014. Semantic image segmentation with deep convolutional nets and fully connected crfs. arXiv preprint arXiv:1412.7062 (2014).

5. DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs

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