Adaptive Local Context Embedding for Small Vehicle Detection from Aerial Optical Remote Sensing Images

Shanjunyu Liu; Yin Zhuang; Hao Dong; Peng Gao; Guanqun Wang; Tong Zhang; Liang Chen; He Chen; Lianlin Li

doi:10.1109/IGARSS46834.2022.9883080

Adaptive Local Context Embedding for Small Vehicle Detection from Aerial Optical Remote Sensing Images

Shanjunyu Liu, Yin Zhuang^*, Hao Dong, Peng Gao, Guanqun Wang, Tong Zhang, Liang Chen, He Chen, Lianlin Li

^*Corresponding author for this work

School of Information and Electronics

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

Abstract

Small vehicle detection is one of the remaining challenging task because the ambiguous appearance is against complex background interference. Consequently, in order to improve the performance of small vehicle detection from aerial optical remote sensing images, a novel adaptive local context (ALC) embedding way is designed and further introduced into an anchor free detection manner which is called ALC-Net, and in ALC-Net, it can adaptively set up the effective local context feature to improve keypoint description of small vehicles and boost the detection performance without adding extra prior information. Finally, several experiments are carried out on two widely used datasets (e.g., UCAS-AOD [1] and VEDAI [2]) and the results indicate that the proposed ALC-Net can exhibit the competitive small vehicle detection performance than other detectors.

Original language	English
Title of host publication	IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1712-1715
Number of pages	4
ISBN (Electronic)	9781665427920
DOIs	https://doi.org/10.1109/IGARSS46834.2022.9883080
Publication status	Published - 2022
Event	2022 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2022 - Kuala Lumpur, Malaysia Duration: 17 Jul 2022 → 22 Jul 2022

Publication series

Name	International Geoscience and Remote Sensing Symposium (IGARSS)
Volume	2022-July

Conference

Conference	2022 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2022
Country/Territory	Malaysia
City	Kuala Lumpur
Period	17/07/22 → 22/07/22

Keywords

Adaptive local context embedding
anchor free
small vehicle detection

Access to Document

10.1109/IGARSS46834.2022.9883080

Cite this

Liu, S., Zhuang, Y., Dong, H., Gao, P., Wang, G., Zhang, T., Chen, L., Chen, H., & Li, L. (2022). Adaptive Local Context Embedding for Small Vehicle Detection from Aerial Optical Remote Sensing Images. In IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium (pp. 1712-1715). (International Geoscience and Remote Sensing Symposium (IGARSS); Vol. 2022-July). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IGARSS46834.2022.9883080

Liu, Shanjunyu ; Zhuang, Yin ; Dong, Hao et al. / Adaptive Local Context Embedding for Small Vehicle Detection from Aerial Optical Remote Sensing Images. IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium. Institute of Electrical and Electronics Engineers Inc., 2022. pp. 1712-1715 (International Geoscience and Remote Sensing Symposium (IGARSS)).

@inproceedings{dcfa0a6dda2c48d2b20d89b1d78e3410,

title = "Adaptive Local Context Embedding for Small Vehicle Detection from Aerial Optical Remote Sensing Images",

abstract = "Small vehicle detection is one of the remaining challenging task because the ambiguous appearance is against complex background interference. Consequently, in order to improve the performance of small vehicle detection from aerial optical remote sensing images, a novel adaptive local context (ALC) embedding way is designed and further introduced into an anchor free detection manner which is called ALC-Net, and in ALC-Net, it can adaptively set up the effective local context feature to improve keypoint description of small vehicles and boost the detection performance without adding extra prior information. Finally, several experiments are carried out on two widely used datasets (e.g., UCAS-AOD [1] and VEDAI [2]) and the results indicate that the proposed ALC-Net can exhibit the competitive small vehicle detection performance than other detectors.",

keywords = "Adaptive local context embedding, anchor free, small vehicle detection",

author = "Shanjunyu Liu and Yin Zhuang and Hao Dong and Peng Gao and Guanqun Wang and Tong Zhang and Liang Chen and He Chen and Lianlin Li",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2022 ; Conference date: 17-07-2022 Through 22-07-2022",

year = "2022",

doi = "10.1109/IGARSS46834.2022.9883080",

language = "English",

series = "International Geoscience and Remote Sensing Symposium (IGARSS)",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "1712--1715",

booktitle = "IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium",

address = "United States",

}

Liu, S, Zhuang, Y, Dong, H, Gao, P, Wang, G, Zhang, T, Chen, L , Chen, H & Li, L 2022, Adaptive Local Context Embedding for Small Vehicle Detection from Aerial Optical Remote Sensing Images. in IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium. International Geoscience and Remote Sensing Symposium (IGARSS), vol. 2022-July, Institute of Electrical and Electronics Engineers Inc., pp. 1712-1715, 2022 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2022, Kuala Lumpur, Malaysia, 17/07/22. https://doi.org/10.1109/IGARSS46834.2022.9883080

Adaptive Local Context Embedding for Small Vehicle Detection from Aerial Optical Remote Sensing Images. / Liu, Shanjunyu; Zhuang, Yin; Dong, Hao et al.
IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium. Institute of Electrical and Electronics Engineers Inc., 2022. p. 1712-1715 (International Geoscience and Remote Sensing Symposium (IGARSS); Vol. 2022-July).

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

TY - GEN

T1 - Adaptive Local Context Embedding for Small Vehicle Detection from Aerial Optical Remote Sensing Images

AU - Liu, Shanjunyu

AU - Zhuang, Yin

AU - Dong, Hao

AU - Gao, Peng

AU - Wang, Guanqun

AU - Zhang, Tong

AU - Chen, Liang

AU - Chen, He

AU - Li, Lianlin

PY - 2022

Y1 - 2022

N2 - Small vehicle detection is one of the remaining challenging task because the ambiguous appearance is against complex background interference. Consequently, in order to improve the performance of small vehicle detection from aerial optical remote sensing images, a novel adaptive local context (ALC) embedding way is designed and further introduced into an anchor free detection manner which is called ALC-Net, and in ALC-Net, it can adaptively set up the effective local context feature to improve keypoint description of small vehicles and boost the detection performance without adding extra prior information. Finally, several experiments are carried out on two widely used datasets (e.g., UCAS-AOD [1] and VEDAI [2]) and the results indicate that the proposed ALC-Net can exhibit the competitive small vehicle detection performance than other detectors.

AB - Small vehicle detection is one of the remaining challenging task because the ambiguous appearance is against complex background interference. Consequently, in order to improve the performance of small vehicle detection from aerial optical remote sensing images, a novel adaptive local context (ALC) embedding way is designed and further introduced into an anchor free detection manner which is called ALC-Net, and in ALC-Net, it can adaptively set up the effective local context feature to improve keypoint description of small vehicles and boost the detection performance without adding extra prior information. Finally, several experiments are carried out on two widely used datasets (e.g., UCAS-AOD [1] and VEDAI [2]) and the results indicate that the proposed ALC-Net can exhibit the competitive small vehicle detection performance than other detectors.

KW - Adaptive local context embedding

KW - anchor free

KW - small vehicle detection

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DO - 10.1109/IGARSS46834.2022.9883080

M3 - Conference contribution

AN - SCOPUS:85140414561

T3 - International Geoscience and Remote Sensing Symposium (IGARSS)

SP - 1712

EP - 1715

BT - IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium

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Y2 - 17 July 2022 through 22 July 2022

ER -

Liu S, Zhuang Y, Dong H, Gao P, Wang G, Zhang T et al. Adaptive Local Context Embedding for Small Vehicle Detection from Aerial Optical Remote Sensing Images. In IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium. Institute of Electrical and Electronics Engineers Inc. 2022. p. 1712-1715. (International Geoscience and Remote Sensing Symposium (IGARSS)). doi: 10.1109/IGARSS46834.2022.9883080

Adaptive Local Context Embedding for Small Vehicle Detection from Aerial Optical Remote Sensing Images

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Keywords

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