@inproceedings{43935ff0753d4b0ea70ea87f221edf46,
title = "Improved YOLOv7 for Small and Overlapping Objects Detection",
abstract = "Object detection is a crucial task in Deep Learning applications. However, detecting small, overlapping objects in complex scenes has always been challenging. To overcome this challenge, we propose a new algorithm based on YOLOv7, which incorporates a multi-path attention enhancement module in the neck part and a receptive field enhancement module on the feature layer responsible for forecasting small objects before the head. This allows all detection layers to focus more effectively on features that require attention and enhance receptive fields. Our experiments on the PASCAL VOC dataset demonstrate that our proposed approach significantly improves the detection of small and overlapping objects compared to YOLOv7.",
keywords = "Multi-path Attention, Object Detection, Receptive Field Enhancement, YOLOv7",
author = "Kaiwen Liang and Weimin Zhang and Fangxing Li and Zhou Jiang and Di Zhang",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 6th IEEE International Conference on Pattern Recognition and Artificial Intelligence, PRAI 2023 ; Conference date: 18-08-2023 Through 20-08-2023",
year = "2023",
doi = "10.1109/PRAI59366.2023.10332096",
language = "English",
series = "2023 IEEE 6th International Conference on Pattern Recognition and Artificial Intelligence, PRAI 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "153--157",
booktitle = "2023 IEEE 6th International Conference on Pattern Recognition and Artificial Intelligence, PRAI 2023",
address = "United States",
}