Low-Light Detector Based on Feature Filtering and Enhancement

Xinyu Wang, Baoguo Wei, Yuetong Su, Xu Li, Lixin Li

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Low-light scenarios pose a challenge for object detection due to noise and low brightness. The degraded feature maps are the main factors affecting detection performance. To improve the quality of low-light feature maps, we propose double adaptive filters (DAF) and dark feature pyramid network (DFPN). DAF enhances feature representation by filtering and enhancement. Applying the adaptive kernel adjustment to the filters effectively improves interactions in the current dimension. Due to the limited detail information in low-light feature maps, the DFPN is proposed to compensate for the details. We integrate these two modules into the advanced YOLOX detector. We achieve state-of-the-art performance with unloaded and loaded COCO weights, achieving 69.1% and 83.2% accuracy on the ExDark dataset.

源语言英语
主期刊名2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025 - Proceedings
编辑Bhaskar D Rao, Isabel Trancoso, Gaurav Sharma, Neelesh B. Mehta
出版商Institute of Electrical and Electronics Engineers Inc.
ISBN(电子版)9798350368741
DOI
出版状态已出版 - 2025
活动2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025 - Hyderabad, 印度
期限: 6 4月 202511 4月 2025

出版系列

姓名ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN(印刷版)1520-6149

会议

会议2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025
国家/地区印度
Hyderabad
时期6/04/2511/04/25

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