Optics and Precision Engineering, Volume. 31, Issue 10, 1532(2023)

Dense pedestrian detection algorithm in multi-branch non-anchor frame network

Zhixuan LÜ, Xia WEI*, and Deqi HUANG
Author Affiliations
  • School of Electrical Engineering, XinJiang University, Urumqi830049, China
  • show less
    References(37)

    [1] [1] 1侯佳伟. 从七次全国人口普查看我国人口发展新特点及新趋势[J]. 学术论坛, 2021, 44(5): 1-14. doi: 10.3969/j.issn.1004-4434.2021.05.001HOUJ W. Looking at the new characteristics and trends of China’s population development from the seven national censuses[J]. Academic Forum, 2021, 44(5): 1-14. (in Chinese). doi: 10.3969/j.issn.1004-4434.2021.05.001

    [2] LUO C X, YANG X D, YUILLE A. Exploring Simple 3D Multi-Object Tracking for Autonomous Driving[C], 10468-10477(10).

    [3] LIU C, TANG X, MA J J et al. Remote Sensing Images Feature Learning Based on Multi-Branch Networks[C], 2057-2060(2021).

    [4] KE W, ZHANG T L, HUANG Z Y et al. Multiple Anchor Learning for Visual Object Detection[C], 10203-10212(13).

    [5] LI S, YANG L X, HUANG J Q et al. Dynamic Anchor Feature Selection for Single-Shot Object Detection[C], 6608-6617(2019).

    [6] GIRSHICK R, DONAHUE J, DARRELL T et al. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation[C], 580-587(23).

    [7] REDMON J, DIVVALA S, GIRSHICK R et al. You Only Look Once: Unified, Real-Time Object Detection[C], 779-788(27).

    [8] ROSZYK K, NOWICKI M R, SKRZYPCZYŃSKI P. Adopting the YOLOv4 architecture for low-latency multispectral pedestrian detection in autonomous driving[J]. Sensors, 22, 1082(2022).

    [9] GAWANDE U, HAJARI K, GOLHAR Y. SIRA: Scale illumination rotation affine invariant mask R-CNN for pedestrian detection[J]. Applied Intelligence, 52, 10398-10416(2022).

    [10] [10] 10李经宇, 杨静, 孔斌, 等. 基于注意力机制的多尺度车辆行人检测算法[J]. 光学 精密工程, 2021, 29(6): 1448-1458. doi: 10.37188/OPE.20212906.1448LIJ Y, YANGJ, KONGB, et al. Multi-scale vehicle and pedestrian detection algorithm based on attention mechanism[J]. Opt. Precision Eng., 2021, 29(6): 1448-1458. (in Chinese). doi: 10.37188/OPE.20212906.1448

    [11] [11] 11马立, 巩笑天, 欧阳航空. Tiny YOLOV3目标检测改进[J]. 光学 精密工程, 2020, 28(4): 988-995. doi: 10.3788/OPE.20202804.0988MAL, GONGX T, OUYANGH K. Improvement of Tiny YOLOV3 target detection[J]. Opt. Precision Eng., 2020, 28(4): 988-995. (in Chinese). doi: 10.3788/OPE.20202804.0988

    [12] JIN Z C, LIU B, CHU Q et al. SAFNet: A Semi-Anchor-Free Network with Enhanced Feature Pyramid for Object Detection[C], 9445-9457(2020).

    [13] ZHU C C, HE Y H, SAVVIDES M. Feature Selective Anchor-Free Module for Single-Shot Object Detection[C], 840-849(15).

    [14] ZHANG S F, CHI C, YAO Y Q et al. Bridging the Gap Between Anchor-Based and Anchor-Free Detection via Adaptive Training Sample Selection[C], 9756-9765(13).

    [15] LAW H, DENG J. CornerNet: detecting objects as paired keypoints[J]. International Journal of Computer Vision, 128, 642-656(2020).

    [16] ZHOU X, WANG D, KRÄHENBÜHL P. Objects as points[J]. arXiv preprint(2019).

    [17] DUAN K W, BAI S, XIE L X et al. Centernet: keypoint triplets for object detection[C], 6568-6577(2019).

    [18] CAO Z W, YANG H H, XU W J et al. Multiscale anchor-free region proposal network for pedestrian detection[J]. Wireless Communications and Mobile Computing, 2021, 1-12(2021).

    [19] DING Z F, GU Z C, SUN Y P et al. Cascaded cross-layer fusion network for pedestrian detection[J]. Mathematics, 10, 139(2022).

    [20] [20] 20邹逸群, 肖志红, 唐夏菲, 等. Anchor-free的尺度自适应行人检测算法[J]. 控制与决策, 2021, 36(2): 295-302. doi: 10.13195/j.kzyjc.2020.0124ZOUY Q, XIAOZH H, TANGX F, et al. Anchor-free scale adaptive pedestrian detection algorithm[J]. Control and Decision, 2021, 36(2): 295-302. (in Chinese). doi: 10.13195/j.kzyjc.2020.0124

    [21] HE K M, ZHANG X Y, REN S Q et al. Deep Residual Learning for Image Recognition[C], 770-778(27).

    [22] CHU S W, SONG Y, ZOUO J J et al. Human Pose Estimation Using Deep Convolutional Densenet Hourglass Network with Intermediate Points Voting[C], 594-598(22).

    [23] WENG X, YAN Y, DONG G S et al. Deep multi-branch aggregation network for real-time semantic segmentation in street scenes[C], 17224-17240(2022).

    [24] CHEN Z F, QIN X, YANG C et al. Composite localization for human pose estimation[J]. arXiv preprint(2021).

    [25] DU C J, YU H, YU L. A scale-sensitive heatmap representation for multi-person pose estimation[J]. IET Image Processing, 16, 1194-1207(2022).

    [26] WU H, CAO Y, WEI H P et al. Face recognition based on haar like and euclidean distance[J]. Journal of Physics: Conference Series, 1813(2021).

    [27] CHOI SBIN, LEE S S, PARK J et al. Standard greedy non maximum suppression optimization for efficient and high speed inference[C], 1-4(1).

    [28] ZHANG S F, XIE Y L, WAN J et al. WiderPerson: a diverse dataset for dense pedestrian detection in the wild[J]. IEEE Transactions on Multimedia, 22, 380-393(2020).

    [29] SHAO S, ZHAO Z, LI B et al. Crowdhuman: A benchmark for detecting human in a crowd[J]. arXiv preprint(2018).

    [30] TIAN Z, SHEN C H, CHEN H et al. FCOS: A Simple and Strong Anchor-Free Object Detector[C], 1922-1933(2020).

    [31] [31] 31王宸, 张秀峰, 刘超, 等. 改进YOLOv3的轮毂焊缝缺陷检测[J]. 光学 精密工程, 2021, 29(8): 1942-1954. doi: 10.37188/OPE.20212908.1942WANGCH, ZHANGX F, LIUCH, et al. Detection method of wheel hub weld defects based on the improved YOLOv3[J]. Opt. Precision Eng., 2021, 29(8): 1942-1954. (in Chinese). doi: 10.37188/OPE.20212908.1942

    [32] KANG H J. Real-time Object Detection on 640x480 Image with VGG16 SSD[C], 419-422(9).

    [33] WANG Y M, JIA K B, LIU P Y. Impolite pedestrian detection by using enhanced YOLOv3-tiny[J]. Journal on Artificial Intelligence, 2, 113-124(2020).

    [34] [34] 34陈一潇, 阿里甫·库尔班, 林文龙, 等. 面向拥挤行人检测的CA-YOLOv5[J]. 计算机工程与应用, 2022, 58(9): 238-245. doi: 10.3778/j.issn.1002-8331.2201-0058CHENY X, ALIFUK, LINW L, et al. CA-YOLOv5 for crowded pedestrian detection[J]. Computer Engineering and Applications, 2022, 58(9): 238-245. (in Chinese). doi: 10.3778/j.issn.1002-8331.2201-0058

    [35] REDMON J, FARHADI A. YOLO9000: Better, Faster, Stronger[C], 6517-6525(21).

    [36] CAO J, PANG Y, ANWER R M et al. PSTR: End-To-End One-Step Person Search with Transformers[C], 9458-9467(2022).

    [37] YU R, DU D, LALONDE R et al. Cascade Transformers for End-to-End Person Search[C], 2022, 7267-7276.

    Tools

    Get Citation

    Copy Citation Text

    Zhixuan LÜ, Xia WEI, Deqi HUANG. Dense pedestrian detection algorithm in multi-branch non-anchor frame network[J]. Optics and Precision Engineering, 2023, 31(10): 1532

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category: Information Sciences

    Received: May. 30, 2022

    Accepted: --

    Published Online: Jul. 4, 2023

    The Author Email: Xia WEI (30462111@qq.com)

    DOI:10.37188/OPE.20233110.1532

    Topics