Optics and Precision Engineering, Volume. 30, Issue 14, 1764(2022)
Lightweight pedestrian detection for multiple scenes
[1] R P YADAV, V SENTHAMILARASU, K KUTTY et al. Implementation of robust HOG-SVM based pedestrian classification. International Journal of Computer Applications, 114, 10-16(2015).
[2] P SABZMEYDANI, G MORI. Detecting pedestrians by learning shapelet features. MN, 1-8(2007).
[3] J CAO, Y PANG, J XIE et al. From handcrafted to deep features for pedestrian detection: a survey. IEEE Transactions on Pattern Analysis and Machine Intelligence(2021).
[4] Z CAI, Q FAN, R S FERIS et al. A unified multi-scale deep convolutional neural network for fast object detection, 354-370(2016).
[5] P Y YANG, G F ZHANG, L WANG et al. A part-aware multi-scale fully convolutional network for pedestrian detection. IEEE Transactions on Intelligent Transportation Systems, 22, 1125-1137(2021).
[6] [6] 6邹梓吟, 盖绍彦, 达飞鹏, 等. 基于注意力机制的遮挡行人检测算法[J]. 光学学报, 2021, 41(15): 1515001. doi: 10.3788/aos202141.1515001ZOUZ Y, GAIS Y, DAF P, et al. Occluded pedestrian detection algorithm based on attention mechanism[J]. Acta Optica Sinica, 2021, 41(15): 1515001.(in Chinese). doi: 10.3788/aos202141.1515001
[7] J L WU, C L ZHOU, M YANG et al. Temporal-context enhanced detection of heavily occluded pedestrians, 13427-13436(2020).
[8] [8] 8时小虎, 吴佳琦, 吴春国, 等.基于残差网络的弯道增强车道线检测方法[J/OL].吉林大学学报(工学版):1-9. [2022-04-02]. DOI: 10.13229/j.cnki.jdxbgxb20210618.SHIX H, WUJ Q, WUC G, et al. Residual network based curve enhanced lane detection method [J/OL].Journal of Jilin University(Engineering and Technology Edition):1-9. [2022-04-02]. DOI: 10.13229/j.cnki.jdxbgxb20210618. (in Chinese)
[9] Z GE, S LIU, F WANG et al. Yolox: Exceeding yolo series in 2021. arXiv preprint arXiv, 2021(2017).
[10] Q B HOU, D Q ZHOU, J S FENG. Coordinate attention for efficient mobile network design, 13708-13717(2021).
[11] Z LIU, J G LI, Z Q SHEN et al. Learning efficient convolutional networks through network slimming, 2755-2763(2017).
[12] [12] 12任彬, 王宇庆, 丛振, 等. 基于MPSOC的航空图像目标检测系统设计[J]. 液晶与显示, 2021, 36(7): 1006-1017. doi: 10.37188/CJLCD.2020-0310RENB, WANGY Q, CONGZ, et al. Design of aerial image target detection system based on MPSOC[J]. Chinese Journal of Liquid Crystals and Displays, 2021, 36(7): 1006-1017.(in Chinese). doi: 10.37188/CJLCD.2020-0310
[13] [13] 13周经美, 王钰, 宁航, 等. 面向多元场景结合GLNet的车道线检测算法[J]. 中国公路学报, 2021, 34(7): 118-127. doi: 10.3969/j.issn.1001-7372.2021.07.010ZHOUJ M, WANGY, NINGH, et al. Lane detection algorithm based on GLNet for multiple scenes[J]. China Journal of Highway and Transport, 2021, 34(7): 118-127.(in Chinese). doi: 10.3969/j.issn.1001-7372.2021.07.010
[14] P BABAKHANI, P ZAREI. Automatic gamma correction based on average of brightness. Advances in Computer Science: an International Journal, 4, 156-159(2015).
[15] S G WANG, J CHENG, H J LIU et al. PCN: part and context information for pedestrian detection with CNNs. arXiv preprint arXiv, 2018.
Get Citation
Copy Citation Text
Yunzuo ZHANG, Wenbo LI, Wei GUO, Zhouchen SONG. Lightweight pedestrian detection for multiple scenes[J]. Optics and Precision Engineering, 2022, 30(14): 1764
Category: Information Sciences
Received: Apr. 19, 2022
Accepted: --
Published Online: Sep. 6, 2022
The Author Email: ZHANG Yunzuo (zyz2016@stdu.edu.cn)