Fast and effective element-aware domain enhancement and adaptation for semantic segmentation

Kuo-Liang Chung; Ya-Yun Cheng; Arie Tando; Don-Kai Chiang

doi:10.1117/12.2567017

1 June 2020 Fast and effective element-aware domain enhancement and adaptation for semantic segmentation

Kuo-Liang Chung, Ya-Yun Cheng, Arie Tando, Don-Kai Chiang

Proceedings Volume 11515, International Workshop on Advanced Imaging Technology (IWAIT) 2020; 115150M (2020) https://doi.org/10.1117/12.2567017
Event: International Workshop on Advanced Imaging Technologies 2020 (IWAIT 2020), 2020, Yogyakarta, Indonesia

Abstract

In this paper, we propose a novel element-aware domain enhancement and adaptation (EDEA) approach for semantic segmentation to increase the segmentation accuracy. In the proposed EDEA approach, we first analyze the warning elements in the testing step, such as the falling-leaves, manhole covers, cirrus, advertisements, etc., caused invalid segmented objects. Then, we create a new GTA5-like (Grand Theft Auto V-like) dataset containing the scenarios including these warning elements. Further, we perform a domain adaptation on the created GTA5-like dataset to generate a photo-realistic GTA5-like dataset. Finally, we combine the generated dataset with the original photo-realistic GTA5 dataset and the realistic Camvid dataset to constitute a more diverse training dataset. The comprehensive experimental results have confirmed the semantic segmentation accuracy improvement of the proposed EDEA approach relative to the previous two domain adaptation methods.

Citation Download Citation

Kuo-Liang Chung, Ya-Yun Cheng, Arie Tando, and Don-Kai Chiang "Fast and effective element-aware domain enhancement and adaptation for semantic segmentation", Proc. SPIE 11515, International Workshop on Advanced Imaging Technology (IWAIT) 2020, 115150M (1 June 2020); https://doi.org/10.1117/12.2567017

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
6 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Image segmentation

Roads

Gallium nitride

Automatic tracking

Computer science

Computer vision technology

Convolutional neural networks

Show All Keywords

Keywords/Phrases

Search In:

Publication Years