Deep Multi-Branch Aggregation Network for Real-Time Semantic Segmentation in Street Scenes

Author:

Weng Xi1ORCID,Yan Yan1ORCID,Dong Genshun1,Shu Chang2,Wang Biao3,Wang Hanzi1ORCID,Zhang Ji4ORCID

Affiliation:

1. Fujian Key Laboratory of Sensing and Computing for Smart City, School of Informatics, Xiamen University, Xiamen, China

2. School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China

3. Zhejiang Laboratory, Hangzhou, China

4. School of Mathematics, Physics, and Computing, University of Southern Queensland, Toowoomba, QLD, Australia

Funder

National Natural Science Foundation of China

Open Research Projects of Zhejiang Laboratory

Youth Innovation Foundation of Xiamen

Zhejiang Provincial Natural Science Foundation

China Postdoctoral Science Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Mechanical Engineering,Automotive Engineering

Reference47 articles.

1. Expectation-Maximization Attention Networks for Semantic Segmentation

2. Dual Attention Network for Scene Segmentation

3. A Real-Time Algorithm for Signal Analysis with the Help of the Wavelet Transform

4. U-Net: Convolutional networks for biomedical image segmentation;ronneberger;Proc Int Conf Med Image Comput Comput -Assist Intervent (MICCAI),2015

5. ImageNet classification with deep convolutional neural networks;krizhevsky;Proc Adv Neural Inf Process Syst (NIPS),2012

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