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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 35 / No. 9: AAAI-21 Technical Tracks 9

Unsupervised Domain Adaptation for Semantic Segmentation by Content Transfer

February 1, 2023

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Authors

Suhyeon Lee

Yonsei University


Junhyuk Hyun

Yonsei University


Hongje Seong

Yonsei University


Euntai Kim

Yonsei University


DOI:

10.1609/aaai.v35i9.17010


Abstract:

In this paper, we tackle the unsupervised domain adaptation (UDA) for semantic segmentation, which aims to segment the unlabeled real data using labeled synthetic data. The main problem of UDA for semantic segmentation relies on reducing the domain gap between the real image and synthetic image. To solve this problem, we focused on separating information in an image into content and style. Here, only the content has cues for semantic segmentation, and the style makes the domain gap. Thus, precise separation of content and style in an image leads to effect as supervision of real data even when learning with synthetic data. To make the best of this effect, we propose a zero-style loss. Even though we perfectly extract content for semantic segmentation in the real domain, another main challenge, the class imbalance problem, still exists in UDA for semantic segmentation. We address this problem by transferring the contents of tail classes from synthetic to real domain. Experimental results show that the proposed method achieves the state-of-the-art performance in semantic segmentation on the major two UDA settings.

Topics: AAAI

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HOW TO CITE:

Suhyeon Lee||Junhyuk Hyun||Hongje Seong||Euntai Kim Unsupervised Domain Adaptation for Semantic Segmentation by Content Transfer Proceedings of the AAAI Conference on Artificial Intelligence (2021) 8306-8315.

Suhyeon Lee||Junhyuk Hyun||Hongje Seong||Euntai Kim Unsupervised Domain Adaptation for Semantic Segmentation by Content Transfer AAAI 2021, 8306-8315.

Suhyeon Lee||Junhyuk Hyun||Hongje Seong||Euntai Kim (2021). Unsupervised Domain Adaptation for Semantic Segmentation by Content Transfer. Proceedings of the AAAI Conference on Artificial Intelligence, 8306-8315.

Suhyeon Lee||Junhyuk Hyun||Hongje Seong||Euntai Kim. Unsupervised Domain Adaptation for Semantic Segmentation by Content Transfer. Proceedings of the AAAI Conference on Artificial Intelligence 2021 p.8306-8315.

Suhyeon Lee||Junhyuk Hyun||Hongje Seong||Euntai Kim. 2021. Unsupervised Domain Adaptation for Semantic Segmentation by Content Transfer. "Proceedings of the AAAI Conference on Artificial Intelligence". 8306-8315.

Suhyeon Lee||Junhyuk Hyun||Hongje Seong||Euntai Kim. (2021) "Unsupervised Domain Adaptation for Semantic Segmentation by Content Transfer", Proceedings of the AAAI Conference on Artificial Intelligence, p.8306-8315

Suhyeon Lee||Junhyuk Hyun||Hongje Seong||Euntai Kim, "Unsupervised Domain Adaptation for Semantic Segmentation by Content Transfer", AAAI, p.8306-8315, 2021.

Suhyeon Lee||Junhyuk Hyun||Hongje Seong||Euntai Kim. "Unsupervised Domain Adaptation for Semantic Segmentation by Content Transfer". Proceedings of the AAAI Conference on Artificial Intelligence, 2021, p.8306-8315.

Suhyeon Lee||Junhyuk Hyun||Hongje Seong||Euntai Kim. "Unsupervised Domain Adaptation for Semantic Segmentation by Content Transfer". Proceedings of the AAAI Conference on Artificial Intelligence, (2021): 8306-8315.

Suhyeon Lee||Junhyuk Hyun||Hongje Seong||Euntai Kim. Unsupervised Domain Adaptation for Semantic Segmentation by Content Transfer. AAAI[Internet]. 2021[cited 2023]; 8306-8315.


ISSN: 2374-3468


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