Laser & Infrared, Volume. 55, Issue 5, 781(2025)
Infrared and visible light fusion object detection algorithm based on YOLOv7
[1] [1] Ren S Q, He K M, Girshick R, et al. Faster R-CNN: towards real-time object detection with region proposal networks[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017, 39(6): 1137-1149.
[2] [2] Redmon J, Farhadi A. Yolov3: an incremental improvement[EB/OL]. (2018-04-08). https://arxiv.org/abs/1804.02767.
[3] [3] Liu W, Anguelov D, Erhan D, et al. SSD: single shot multibox detector[C]//Leibe B, Matas J, Sebe N, et al. Computer Vision-ECCV 2016. Cham: Springer, 2016: 21-37.
[10] [10] Wang Q L, Wu B G, Zhu P F, et al. ECA-Net: efficient channel attention for deep convolutional neural networks[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). Seattle: CVF, 2020: 11534-11542.
[11] [11] Jia X Y, Zhu C, Li M Z, et al. LLVIP: A visible-infrared paired dataset for low-light vision[C]//Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops. Montreal: CVF, 2021: 3496-3504.
[12] [12] Liu J Y, Fan X, Huang Z B, et al. Target-aware dual adversarial learning and a multi-scenario multi-modality benchmark to fuse infrared and visible for object detection[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). New Orleans: CVF, 2022: 5802-5811.
[13] [13] Zhang H, Fromont E, Lefevre S, et al. Multispectral fusion for object detection with cyclic fuse-and-refine blocks[C]//2020 IEEE International Conference on Image Processing (ICIP). Abu Dhabi: IEEE, 2020: 276-280.
[14] [14] Wang C Y, Bochkovskiy A, Liao H Y M. YOLOv7: trainable bag-of-freebies sets new state-of-the-art for real-time object detectors[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. Vancouver: CVF, 2023: 7464-7475.
[15] [15] Jocher, Glenn, Chaurasia A, et al. YOLOv8: state-of-the-art object detection and segmentation[EB/OL]. https://github.com/ultralytics/ultralytics.
[16] [16] ZHANG H, FROMONT E, LEFEVRE S, et al. Guided attentive feature fusion for multispectral pedestrian detection[C]//Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision. Waikoloa: CVF, 2021: 72-80.
[17] [17] Tang L F, Yuan J T, Zhang H, et al. PIAFusion: a progressive infrared and visible image fusion network based on illumination aware[J]. Information Fusion, 2022, 83/84: 79-92.
[18] [18] Lin T Y, Maire M, Belongie S, et al. Microsoft COCO: common objects in context[C]//Computer Vision-ECCV 2014. Cham: Springer, 2014: 740-755.
Get Citation
Copy Citation Text
WANG Kai, LOU Shu-li, DING Xiao-zhen. Infrared and visible light fusion object detection algorithm based on YOLOv7[J]. Laser & Infrared, 2025, 55(5): 781
Category:
Received: Jul. 1, 2024
Accepted: Jul. 11, 2025
Published Online: Jul. 11, 2025
The Author Email: LOU Shu-li (shulilou@sina.com)