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[1]Qingxuan Shi, Huijun Di, Yao Lu, Feng Lv, and Xuedong Tian. Video Pose Estimation with Global Motion Cues. Neurocomputing, 2017, 219(1) :269-279.
[2]史青宣, 邸慧军, 陆耀, 田学东. 基于中粒度模型的视频人体姿态估计. 自动化学报, 2018, 44(4):646-655.
[3]Qingxuan Shi, Huijun Di, Yao Lu, Ming Qin, and Xuedong Tian. Video Pose Estimation via Medium Granularity Graphical Model with Spatial-temporal Symmetric Constraint Part Model, IEEE International Conference on Image Processing, 2016:1299-1303.
[4]Qingxuan Shi, Huijun Di, Yao Lu, and Feng Lv. Human Pose Estimation with Global Motion Cues. IEEE International Conference on Image Processing, 2015: 442-446.
[5]史青宣，王谦，田学东. 基于层叠的部件轨迹片段模型的视频人体姿态估计. 山东大学学报, 2018, 48(2):14-21.
[6]Huijun Di, Qingxuan Shi, Feng Lv, Ming Qin, and Yao Lu. Contour Flow: Middle-Level Motion Estimation by Combining Motion Segmentation and Contour Alignment. ICCV, 2015:4355-4363.
[7]Qingxuan Shi, Yao Lu and Tianfei Zhou, Spatio-Temporal Context for More Accurate Dense Point Trajectories Estimation. International Conference on Computational Intelligence and Security, 2014:256-259.
[8]Liu, Ya；Lu, Yao; Shi, Qingxuan; Ding, Jianhua , Optical flow based urban road vehicle tracking, International Conference on Computational Intelligence and Security, 2013.
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