SFG-Net: an Efficient Image to Image Translation Approach for Synthetic Fog Generation

Mahmood Hussain Bhat; Trung Hieu Le; Shih Chia Huang

doi:10.1109/ICCE-Taiwan55306.2022.9868997

SFG-Net: an Efficient Image to Image Translation Approach for Synthetic Fog Generation

Mahmood Hussain Bhat
, Trung Hieu Le
, Shih Chia Huang

Department of Electronic Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

In this study, we propose a new synthetic fog generation network (SFG-Net), which employs the two-stream image-to-image translation model as a base backbone and integrates a self-attention (SA) module for generating foggy images. With the presence of the SA module between the style pipeline and generator of the proposed SFG-Net, the style structure from style features of the input images is captured to advance the image translation performance. Experimental results show the effectiveness of the proposed SFG-Net in both quantitative evaluations and perceptual quality compared with the competitive method.

Original language	English
Title of host publication	Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	435-436
Number of pages	2
ISBN (Electronic)	9781665470506
DOIs	https://doi.org/10.1109/ICCE-Taiwan55306.2022.9868997
State	Published - 2022
Event	2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022 - Taipei, Taiwan Duration: 6 Jul 2022 → 8 Jul 2022

Publication series

Name	Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022

Conference

Conference	2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022
Country/Territory	Taiwan
City	Taipei
Period	6/07/22 → 8/07/22

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Access to Document

10.1109/ICCE-Taiwan55306.2022.9868997

Cite this

Bhat, M. H., Le, T. H., & Huang, S. C. (2022). SFG-Net: an Efficient Image to Image Translation Approach for Synthetic Fog Generation. In Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022 (pp. 435-436). (Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCE-Taiwan55306.2022.9868997

Bhat, Mahmood Hussain ; Le, Trung Hieu ; Huang, Shih Chia. / SFG-Net : an Efficient Image to Image Translation Approach for Synthetic Fog Generation. Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022. Institute of Electrical and Electronics Engineers Inc., 2022. pp. 435-436 (Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022).

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title = "SFG-Net: an Efficient Image to Image Translation Approach for Synthetic Fog Generation",

abstract = "In this study, we propose a new synthetic fog generation network (SFG-Net), which employs the two-stream image-to-image translation model as a base backbone and integrates a self-attention (SA) module for generating foggy images. With the presence of the SA module between the style pipeline and generator of the proposed SFG-Net, the style structure from style features of the input images is captured to advance the image translation performance. Experimental results show the effectiveness of the proposed SFG-Net in both quantitative evaluations and perceptual quality compared with the competitive method.",

author = "Bhat, \{Mahmood Hussain\} and Le, \{Trung Hieu\} and Huang, \{Shih Chia\}",

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series = "Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022",

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Bhat, MH, Le, TH & Huang, SC 2022, SFG-Net: an Efficient Image to Image Translation Approach for Synthetic Fog Generation. in Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022. Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022, Institute of Electrical and Electronics Engineers Inc., pp. 435-436, 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022, Taipei, Taiwan, 6/07/22. https://doi.org/10.1109/ICCE-Taiwan55306.2022.9868997

SFG-Net: an Efficient Image to Image Translation Approach for Synthetic Fog Generation. / Bhat, Mahmood Hussain; Le, Trung Hieu; Huang, Shih Chia.
Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022. Institute of Electrical and Electronics Engineers Inc., 2022. p. 435-436 (Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - In this study, we propose a new synthetic fog generation network (SFG-Net), which employs the two-stream image-to-image translation model as a base backbone and integrates a self-attention (SA) module for generating foggy images. With the presence of the SA module between the style pipeline and generator of the proposed SFG-Net, the style structure from style features of the input images is captured to advance the image translation performance. Experimental results show the effectiveness of the proposed SFG-Net in both quantitative evaluations and perceptual quality compared with the competitive method.

AB - In this study, we propose a new synthetic fog generation network (SFG-Net), which employs the two-stream image-to-image translation model as a base backbone and integrates a self-attention (SA) module for generating foggy images. With the presence of the SA module between the style pipeline and generator of the proposed SFG-Net, the style structure from style features of the input images is captured to advance the image translation performance. Experimental results show the effectiveness of the proposed SFG-Net in both quantitative evaluations and perceptual quality compared with the competitive method.

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Bhat MH, Le TH, Huang SC. SFG-Net: an Efficient Image to Image Translation Approach for Synthetic Fog Generation. In Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022. Institute of Electrical and Electronics Engineers Inc. 2022. p. 435-436. (Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022). doi: 10.1109/ICCE-Taiwan55306.2022.9868997

SFG-Net: an Efficient Image to Image Translation Approach for Synthetic Fog Generation

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