Web: http://arxiv.org/abs/2206.07298

June 17, 2022, 1:13 a.m. | Mohammed A. M. Elhassan, Chenhui Yang, Chenxi Huang, Tewodros Legesse Munea, Xin Hong

cs.CV updates on arXiv.org arxiv.org

Modern high-performance semantic segmentation methods employ a heavy backbone
and dilated convolution to extract the relevant feature. Although extracting
features with both contextual and semantic information is critical for the
segmentation tasks, it brings a memory footprint and high computation cost for
real-time applications. This paper presents a new model to achieve a trade-off
between accuracy/speed for real-time road scene semantic segmentation.
Specifically, we proposed a lightweight model named Scale-aware Strip Attention
Guided Feature Pyramid Network (S$^2$-FPN). Our network consists …

arxiv attention cv feature network real-time scale segmentation semantic time

More from arxiv.org / cs.CV updates on arXiv.org

Machine Learning Researcher - Saalfeld Lab

@ Howard Hughes Medical Institute - Chevy Chase, MD | Ashburn, Virginia

Project Director, Machine Learning in US Health

@ ideas42.org | Remote, US

Data Science Intern

@ NannyML | Remote

Machine Learning Engineer NLP/Speech

@ Play.ht | Remote

Research Scientist, 3D Reconstruction

@ Yembo | Remote, US

Clinical Assistant or Associate Professor of Management Science and Systems

@ University at Buffalo | Buffalo, NY