[1] J K DENG, J GUO, N N XUE et al. ArcFace： additive angular margin loss for deep face recognition, 4685-4694(2020).
[2] M YE, J B SHEN, G J LIN et al. Deep learning for person re-identification： a survey and outlook. IEEE Transactions on Pattern Analysis and Machine Intelligence, 44, 2872-2893(2022).
[3] 3高毅. 基于步态识别的跨场景多目标跟踪算法［J］. 控制工程， 2021， 28（7）： 1375-1381.GAOY. Multi-camera multi-target tracking algorithm based on gait recognition［J］. Control Engineering of China， 2021， 28（7）： 1375-1381.（in Chinese）
[4] J K ZHENG, X C LIU, W LIU et al. Gait recognition in the wild with dense 3D representations and A benchmark, 20196-20205(2022).
[5] Y SUN, Q BAO, W LIU et al. Monocular， one-stage， regression of multiple 3D people, 11159-11168(2022).
[6] X CHEN, J WENG, W LU et al. Multi-gait recognition based on attribute discovery. IEEE Transactions on Pattern Analysis and Machine Intelligence, 40, 1697-1710(2018).
[7] Z F WU, Y Z HUANG, L WANG et al. A comprehensive study on cross-view gait based human identification with deep CNNs. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39, 209-226(2017).
[8] Y W HE, J P ZHANG, H M SHAN et al. Multi-task GANs for view-specific feature learning in gait recognition. IEEE Transactions on Information Forensics and Security, 14, 102-113(2019).
[9] R J LIAO, C S CAO, E B GARCIA et al.
[10] T WOLF, M BABAEE, G RIGOLL. Multi-view gait recognition using 3D convolutional neural networks, 4165-4169(2016).
[11] X H WU, W Z AN, S Q YU et al. Spatial-temporal graph attention network for video-based gait recognition(2020).
[12] H Q CHAO, K WANG, Y W HE et al. GaitSet： cross-view gait recognition through utilizing gait As a deep set. IEEE Transactions on Pattern Analysis and Machine Intelligence, 44, 3467-3478(2022).
[13] S Q YU, D L TAN, T N TAN. A framework for evaluating the effect of view angle， clothing and carrying condition on gait recognition, 441-444(2006).
[14] Z ZHONG, L ZHENG, G L KANG et al. Random erasing data augmentation. Proceedings of the AAAI Conference on Artificial Intelligence, 34, 13001-13008(2020).
[15] R LIU, J LEHMAN, P MOLINO et al. An intriguing failing of convolutional neural networks and the CoordConv solution, 9628-9639(2018).
[16] 16韩东岳， 桑海峰. 利用动态步态图进行步态识别［J］. 电子测量与仪器学报， 2022， 36（2）： 139-145.HAND Y， SANGH F. Gait recognition based on dynamic gait image［J］. Journal of Electronic Measurement and Instrumentation， 2022， 36（2）： 139-145.（in Chinese）
[17] 17曾维， 何刚强， 罗伟洋， 等. 基于ICNet模型的人体步态识别研究［J］. 电子测量技术， 2022， 45（4）： 120-125.ZENGW， HEG Q， LUOW Y， et al. Research on gait recognition of human body based on ICNet model［J］. Electronic Measurement Technology， 2022， 45（4）： 120-125.（in Chinese）
[18] 18周潇涵， 王修晖. 基于非对称双路识别网络的步态识别方法［J］. 计算机工程与应用， 2022， 58（4）： 150-156. doi: 10.3778/j.issn.1002-8331.2008-0355ZHOUX H， WANGX H. Novel gait recognition method based on asymmetric two-path network［J］. Computer Engineering and Applications， 2022， 58（4）： 150-156.（in Chinese）. doi: 10.3778/j.issn.1002-8331.2008-0355
[19] 19胡少晖， 王修晖， 刘砚秋. 基于多支路残差深度网络的跨视角步态识别方法［J］. 模式识别与人工智能， 2021， 34（5）： 455-462.HUSH H， WANGX H， LIUY Q. Cross-view gait recognition method based on multi-branch residual deep network［J］. Pattern Recognition and Artificial Intelligence， 2021， 34（5）： 455-462.（in Chinese）
[20] J KOVAČ, V ŠTRUC, P PEER. Frame-based classification for cross-speed gait recognition. Multimedia Tools and Applications, 78, 5621-5643(2019).
[21] 21罗正平， 刘延钧， 杨天奇. 光流分量分解的步态识别［J］. 计算机科学， 2016， 43（9）： 295-300. doi: 10.11896/j.issn.1002-137X.2016.09.059LUOZH P， LIUY J， YANGT Q. Gait recognition based on decomposition of optical flow components［J］. Computer Science， 2016， 43（9）： 295-300.（in Chinese）. doi: 10.11896/j.issn.1002-137X.2016.09.059
