[1] Sun Y C, Pan S G, Zhao T et al. Traffic light detection based on optimized YOLOv3 algorithm[J]. Acta Optica Sinica, 40, 1215001(2020).

[2] Mou L C, Zhu X X. Spatiotemporal scene interpretation of space videos via deep neural network and tracklet analysis[C], 1823-1826(2016).

[3] Kopsiaftis G, Karantzalos K. Vehicle detection and traffic density monitoring from very high resolution satellite video data[C], 1881-1884(2015).

[4] Guo L, Ma Y, Yue M et al. Overview of recognition and evaluation of driving characteristics and their applications in intelligent vehicles[J]. Journal of Traffic and Transportation Engineering, 21, 7-20(2021).

[5] Wang R M, Zhu Y, Zhao X M et al. Research progress on test scenario of autonomous driving[J]. Journal of Traffic and Transportation Engineering, 21, 21-37(2021).

[6] Shen H, Li S M, Bo F C et al. On road vehicles real-time detection and tracking using vision based approach[J]. Acta Optica Sinica, 30, 1076-1083(2010).

[7] Zhao L, Hu J, Liu H et al. Deep learning based on semantic segmentation for three-dimensional object detection from point clouds[J]. Chinese Journal of Lasers, 48, 1710004(2021).

[8] Hu J, Liu H, Xu W C et al. Position detection algorithm of road obstacles based on 3D LiDAR[J]. Chinese Journal of Lasers, 48, 2410001(2021).

[9] Nong Y J, Wang J J. Real-time object detection in remote sensing images based on embedded system[J]. Acta Optica Sinica, 41, 1028001(2021).

[10] Nong Y J, Wang J J, Zhao X B et al. Spatial relationship detection method of remote sensing objects[J]. Acta Optica Sinica, 41, 1628001(2021).

[11] Ji D F, Ding X M. Specific region decorrelation feature channel on pedestrian detection[J]. Information and Control, 49, 401-413(2020).

[12] Xuan Y, Han C, Sha W H. Improved Tiny Yolov4 algorithm in pedestrian detection[J]. Laser & Optoelectronics Progress, 59, 1215002(2022).

[13] Liu T G, Liu K, Dai L et al. Research progress of key technologies in recognition sensing for opto-electronic information and event[J]. Acta Optica Sinica, 41, 0106002(2021).

[14] Bodla N, Singh B, Chellappa R et al. Soft-NMS: improving object detection with one line of code[C], 5562-5570(2017).

[15] Liu S T, Huang D, Wang Y H. Adaptive NMS: refining pedestrian detection in a crowd[C], 6452-6461(2019).

[16] Ma J, Wan H L, Wang J X et al. An improved one-stage pedestrian detection method based on multi-scale attention feature extraction[J]. Journal of Real-Time Image Processing, 18, 1965-1978(2021).

[17] Zou Z Y, Gai S Y, Da F P et al. Occluded pedestrian detection algorithm based on attention mechanism[J]. Acta Optica Sinica, 41, 1515001(2021).

[18] Redmon J, Farhadi A. YOLOv3: an incremental improvement[EB/OL]. https://arxiv.org/abs/1804.02767

[19] Alexey B, Wang C et al. YOLOv4: optimal speed and accuracy of object detection[EB/OL]. https://arxiv.org/abs/2004.10934

[20] Wang C Y, Bochkovskiy A, Liao H Y M. Scaled-YOLOv4: scaling cross stage partial network[C], 13024-13033(2021).

[21] Ge Z, Liu S T, Wang F et al. YOLOX: exceeding YOLO series in 2021[EB/OL]. https://arxiv.org/abs/2107.08430

[22] Shao S, Zhao Z J, Li B X et al. CrowdHuman: a benchmark for detecting human in a crowd[EB/OL]. https://arxiv.org/abs/1805.00123

[23] Zheng Z H, Wang P, Liu W et al. Distance-IoU loss: faster and better learning for bounding box regression[J]. Proceedings of the AAAI Conference on Artificial Intelligence, 34, 12993-13000(2020).

[24] Woo S, Park J, Lee J Y et al. CBAM: convolutional block attention module[M]. Ferrari V, Hebert M, Sminchisescu C, et al. Computer vision-ECCV 2018, 11211, 3-19(2018).

[25] Loshchilov I, Hutter F. SGDR: stochastic gradient descent with warm restarts[EB/OL]. https://arxiv.org/abs/1608.03983

[26] Rukhovich D, Sofiiuk K, Galeev D et al. IterDet: iterative scheme for object detection in crowded environments[M]. Torsello A, Rossi L, Pelillo M, et al. Structural, syntactic, and statistical pattern recognition. Lecture notes in computer science, 12644, 344-354(2021).

[27] Ge Z, Jie Z Q, Huang X et al. PS-RCNN: detecting secondary human instances in a crowd via primary object suppression[C], 19870687(2020).