[1] REN S,HE K,GIRSHICK R,et al.Faster R-CNN:Towards real-time object detection with region proposal networks[C]//International Conference on Neural Information Processing Systems.Cambridge:MIT Press,2015:91-99. [2] LIU W,ANGUELOW D,ERHAN D,et al.SSD:Single shot multibox detector[C]//European Conference on Computer Vision.Berlin:Springer,2016:21-37. [3] ZHANG X W,CHENG L C,LI B,et al.Too far to see? Not really!-Pedestrian detection with scale-aware localization policy[J].IEEE Transactions on Image Processing,2018,27(8):3703-3715. [4] GIRSHICK R,DONAHUE J,DARRELL T,et al.Rich feature hierarchies for accurate object detection and semantic segmentation[C]//IEEE Conference on Computer Vision and Pattern Recognition.Piscataway:IEEE Press,2014:580-587. [5] DALAL N,TRIGGS B.Histograms of oriented gradients for human detection[C]//IEEE Conference on Computer Vision and Pattern Recognition.Piscataway:IEEE Press,2014:886-893. [6] 种衍文,匡湖林,李清泉.一种基于多特征和机器学习的分级行人检测方法[J].自动化学报,2012,38(3):375-381.ZHONG Y W,KUANG H L,LING Q Q.Two-stage pedestrain detection based on multiple features and machine learning[J].Acta Automatica Sinica,2012,38(3):375-381(in Chinese). [7] SINGH B,DAVIS L.An analysis of scale invariance in object detection snip[C]//IEEE Conference on Computer Vision and Pattern Recognition.Piscataway:IEEE Press,2018:3578-3587 [8] SINGH B,NAJIBI M,DAVIS L.SNIPER:Efficient multi-scale training[C]//International Conference on Neural Information Processing Systems.Cambridge:MIT Press,2018:9310-9320. [9] LIU S T,HUANG D,WANG Y H.Receptive field block net for accurate and fast object detection[C]//European Conference on Computer Vision.Berlin:Springer,2018:385-400. [10] LIU W,LIAO S C,HU W D,et al.Learning efficient single-stage pedestrian detectors by asymptotic localization fitting[C]//European Conference on Computer Vision.Berlin:Springer,2018:643-659. [11] HE K Y,ZHANG X Y,REN S Q,et al.Deep residual learning for image recognition[C]//IEEE Conference on Computer Vision and Pattern Recognition.Piscataway:IEEE Press,2016:770-778. [12] HONARI S,YOSINSKI J,VINCENT P,et al.Recombinator networks:Learning coarse-to-fine feature aggregation[C]//IEEE Conference on Computer Vision and Pattern Recognition.Piscataway:IEEE Press,2016:5743-5752. [13] 谭红臣,李淑华,刘彬,等.特征增强的SSD算法及其在目标检测中的应用[J].计算机辅助设计与图形学学报,2019,31(4):63-69.TAN H C,LI S H,LIU B,et al.Feature enhancement SSD for object detection[J].Journal of Computer-Aided Design & Computer Graphics,2019,31(4):63-69(in Chinese). [14] LIN T Y,DOLLAR P,GIRSHICK R,et al.Feature pyramid networks for object detection[C]//IEEE Conference on Computer Vision and Pattern Recognition.Piscataway:IEEE Press,2017:2117-2125. [15] LIU S,QI L,QIN H F,et al.Path aggregation network for instance segmentation[C]//IEEE Conference on Computer Vision and Pattern Recognition.Piscataway:IEEE Press,2018:8759-8768. [16] ZHAO Q J,SHENG T,WANG Y T,et al.M2Det:A single-shot object detector based on multi-level feature pyramid network[C]//AAAI Conference on Artificial Intelligence.Menlo Park:AAAI Press,2019,33:9259-9266. [17] LI Y,CHEN Y,WANG N,et al.Scale-aware trident networks for object detection[C]//IEEE International Conference on Computer Vision.Piscataway:IEEE Press,2019:6054-6063. [18] LI J,LIANG X,SHEN S M,et al.Scale-aware fast R-CNN for pedestrian detection[J].IEEE Transactions on Multimedia,2017,20(4):985-996. [19] DOLLA P,WOJEK C,SCHIELE B,et al.Pedestrian detection:An evaluation of the state of the art[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2011,34(4):743-761. [20] ESS A,LEIBE B,GOOL L V.Depth and appearance for mobile scene analysis[C]//IEEE International Conference on Computer Vision.Piscataway:IEEE Press,2007:1-8. [21] SONG T,SUN L Y,XIE D,et al.Small-scale pedestrian detection based on topological line localization and temporal feature aggregation[C]//European Conference on Computer Vision.Berlin:Springer,2018:536-551. [22] 王刚,陈永光,杨锁昌,等.鲁棒的红外小目标视觉显著性检测方法[J].北京航空航天大学学报,2015,41(12):2309-2318.WAGN G,CHEN Y G,YANG S C,et al.Robust visual saliency detection method for infrared small target[J].Journal of Beijing University of Aeronautics and Astronautics,2015,41(12):2309-2318(in Chinese). [23] ZHOU P,NI B B,GENG C,et al.Scale-transferrable object detection[C]//IEEE Conference on Computer Vision and Pattern Recognition.Piscataway:IEEE Press,2018:528-537. [24] 李晓光,付陈平,李晓莉,等.面向多尺度目标检测的改进Faster R-CNN算法[J].计算机辅助设计与图形学学报,2019,31(7):1095-1101.LI X G,FU C P,LI X L,et al.Improved Faster R-CNN for multi-scale object detection[J].Journal of Computer-Aided Design & Computer Graphics,2019,31(7):1095-1101(in Chinese). [25] 裴伟,许晏铭,朱永英,等.改进的SSD航拍目标检测方法[J].软件学报,2019,30(3):248-268.PEI W,XU Y M,ZHU Y Y,et al.The target detection method of aerial photography images with improved SSD[J].Journal of Software,2019,30(3):248-268(in Chinese). [26] 许冰,牛燕雄,吕建明.复杂动态场景下目标检测与分割算法[J].北京航空航天大学学报,2016,42(2):310-317.XU B,NIU Y X,LYU J M.Object detection and segmentation algorithm in complex dynamic scene[J].Journal of Beijing University of Aeronautics and Astronautics,2016,42(2):310-317(in Chinese). [27] LIU W,LIAO S C,REN W Q,et al.High-level semantic feature detection:A new perspective for pedestrian detection[C]//IEEE Conference on Computer Vision and Pattern Recognition.Piscataway:IEEE Press,2019:5187-5196. [28] ZHANG S J,YANG J,SCHIELE B.Occluded pedestrian detection through guided attention in CNNs[C]//IEEE Conference on Computer Vision and Pattern Recognition.Piscataway:IEEE Press,2018:6995-7003. [29] ZHANG L L,LIN L,LIANG X D,et al.Is Faster R-CNN doing well for pedestrian detection?[C]//European Conference on Computer Vision.Berlin:Springer,2018:618-634. [30] ZHANG S S,BENENSON R,SCHIELE B.Citypersons:A diverse dataset for pedestrian detection[C]//IEEE Conference on Computer Vision and Pattern Recognition.Piscataway:IEEE Press,2017:3213-3221. [31] DU X Z,EL-KHAMY M,LEE J,et al.Fused DNN:A deep neural network fusion approach to fast and robust pedestrian detection[C]//IEEE Winter Conference on Applications of Computer Vision.Piscataway:IEEE Press,2017:953-961. [32] WANG S G,CHENG J,LIU H J,et al.PCN:Part and context information for pedestrian detection with CNNs[EB/OL].(2018-04-12)[2020-01-27].https://arxiv.org/abs/1804.04483. [33] LIN C Z,LU J W,WANG G,et al.Graininess-aware deep feature learning for pedestrian detection[C]//European Conference on Computer Vision.Berlin:Springer,2018:732-747. [34] DU X,EL-KHAMY M,MORARIU V I,et al.Fused deep neural networks for efficient pedestrian detection[EB/OL].(2018-05-02)[2020-01-27].https://arxiv.org/abs/1805.08688. [35] BRAZIL G,LIU X M.Pedestrian detection with autoregressive network phases[C]//IEEE Conference on Computer Vision and Pattern Recognition.Piscataway:IEEE Press,2019:7231-7240. [36] DOLLAR P,TU Z,PERONA P,et al.Integral channel features[C]//British Machine Vision Conference,2009:91.1-91.11. [37] OUYANG W L,WANG X G.Joint deep learning for pedestrian detection[C]//IEEE International Conference on Computer Vision.Piscataway:IEEE Press,2013:2056-2063. [38] ZENG X Y,OUYANG W L,WANG X G.Multi-stage contextual deep learning for pedestrian detection[C]//IEEE International Conference on Computer Vision.Piscataway:IEEE Press,2013:121-128. [39] OUYANG W L,ZENG X Y,WANG X G.Modeling mutual visibility relationship in pedestrian detection[C]//IEEE Conference on Computer Vision and Pattern Recognition.Piscataway:IEEE Press,2013:3222-3229. [40] TIAN Y L,LUO P,WANG X G,et al.Pedestrian detection aided by deep learning semantic tasks[C]//IEEE Conference on Computer Vision and Pattern Recognition.Piscataway:IEEE Press,2015:5079-5087. |